Adaptive correlation filter-based video stabilization without accumulative global motion estimation

NASA Astrophysics Data System (ADS)

Koh, Eunjin; Lee, Chanyong; Jeong, Dong Gil

2014-12-01

We present a digital video stabilization approach that provides both robustness and efficiency for practical applications. In this approach, we adopt a stabilization model that maintains spatio-temporal information of past input frames efficiently and can track original stabilization position. Because of the stabilization model, the proposed method does not need accumulative global motion estimation and can recover the original position even if there is a failure in interframe motion estimation. It can also intelligently overcome the situation of damaged or interrupted video sequences. Moreover, because it is simple and suitable to parallel scheme, we implement it on a commercial field programmable gate array and a graphics processing unit board with compute unified device architecture in a breeze. Experimental results show that the proposed approach is both fast and robust.

Adaptive particle filter for robust visual tracking

NASA Astrophysics Data System (ADS)

Dai, Jianghua; Yu, Shengsheng; Sun, Weiping; Chen, Xiaoping; Xiang, Jinhai

2009-10-01

Object tracking plays a key role in the field of computer vision. Particle filter has been widely used for visual tracking under nonlinear and/or non-Gaussian circumstances. In particle filter, the state transition model for predicting the next location of tracked object assumes the object motion is invariable, which cannot well approximate the varying dynamics of the motion changes. In addition, the state estimate calculated by the mean of all the weighted particles is coarse or inaccurate due to various noise disturbances. Both these two factors may degrade tracking performance greatly. In this work, an adaptive particle filter (APF) with a velocity-updating based transition model (VTM) and an adaptive state estimate approach (ASEA) is proposed to improve object tracking. In APF, the motion velocity embedded into the state transition model is updated continuously by a recursive equation, and the state estimate is obtained adaptively according to the state posterior distribution. The experiment results show that the APF can increase the tracking accuracy and efficiency in complex environments.

Motion adaptive Kalman filter for super-resolution

NASA Astrophysics Data System (ADS)

Richter, Martin; Nasse, Fabian; Schröder, Hartmut

2011-01-01

Superresolution is a sophisticated strategy to enhance image quality of both low and high resolution video, performing tasks like artifact reduction, scaling and sharpness enhancement in one algorithm, all of them reconstructing high frequency components (above Nyquist frequency) in some way. Especially recursive superresolution algorithms can fulfill high quality aspects because they control the video output using a feed-back loop and adapt the result in the next iteration. In addition to excellent output quality, temporal recursive methods are very hardware efficient and therefore even attractive for real-time video processing. A very promising approach is the utilization of Kalman filters as proposed by Farsiu et al. Reliable motion estimation is crucial for the performance of superresolution. Therefore, robust global motion models are mainly used, but this also limits the application of superresolution algorithm. Thus, handling sequences with complex object motion is essential for a wider field of application. Hence, this paper proposes improvements by extending the Kalman filter approach using motion adaptive variance estimation and segmentation techniques. Experiments confirm the potential of our proposal for ideal and real video sequences with complex motion and further compare its performance to state-of-the-art methods like trainable filters.

Adaptive robust motion trajectory tracking control of pneumatic cylinders with LuGre model-based friction compensation

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Liu, Hao; Zhu, Xiaocong

2014-07-01

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation (RLSE) to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

Robust adaptive antiswing control of underactuated crane systems with two parallel payloads and rail length constraint.

PubMed

Zhang, Zhongcai; Wu, Yuqiang; Huang, Jinming

2016-11-01

The antiswing control and accurate positioning are simultaneously investigated for underactuated crane systems in the presence of two parallel payloads on the trolley and rail length limitation. The equations of motion for the crane system in question are established via the Euler-Lagrange equation. An adaptive control strategy is proposed with the help of system energy function and energy shaping technique. Stability analysis shows that under the designed adaptive controller, the payload swings can be suppressed ultimately and the trolley can be regulated to the destination while not exceeding the pre-specified boundaries. Simulation results are provided to show the satisfactory control performances of the presented control method in terms of working efficiency as well as robustness with respect to external disturbances. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Robust adaptive kinematic control of redundant robots

NASA Technical Reports Server (NTRS)

Tarokh, M.; Zuck, D. D.

1992-01-01

The paper presents a general method for the resolution of redundancy that combines the Jacobian pseudoinverse and augmentation approaches. A direct adaptive control scheme is developed to generate joint angle trajectories for achieving desired end-effector motion as well as additional user defined tasks. The scheme ensures arbitrarily small errors between the desired and the actual motion of the manipulator. Explicit bounds on the errors are established that are directly related to the mismatch between actual and estimated pseudoinverse Jacobian matrix, motion velocity and the controller gain. It is shown that the scheme is tolerant of the mismatch and consequently only infrequent pseudoinverse computations are needed during a typical robot motion. As a result, the scheme is computationally fast, and can be implemented for real-time control of redundant robots. A method is incorporated to cope with the robot singularities allowing the manipulator to get very close or even pass through a singularity while maintaining a good tracking performance and acceptable joint velocities. Computer simulations and experimental results are provided in support of the theoretical developments.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

PubMed

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

2015-11-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal

PubMed Central

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D.; Hubbi, Basil; Liu, Xuan

2015-01-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue. PMID:26600996

Human Guidance Behavior Decomposition and Modeling

NASA Astrophysics Data System (ADS)

Feit, Andrew James

Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

On decentralized adaptive full-order sliding mode control of multiple UAVs.

PubMed

Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

2017-11-01

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Strategies for Controls of Flexible Arms. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Yuan, Bau-San

1989-01-01

An adaptive controller for a modern manipulator has been designed based on asymptotical stability via the Lyapunov criterion with the output error between the system and a reference model used as the actuating control signal. Computer simulations were carried out to test the design. The combination of the adaptive controller and a system vibration and mode shape estimator show that the flexible arm should move along a pre-defined trajectory with high-speed motion and fast vibration setting time. An existing computer-controlled prototype two link manipulator, RALF (Robotic Arm, Large Flexible), with a parallel mechanism driven by hydraulic actuators was used to verify the mathematical analysis. The experimental results illustrate that assumed modes found from finite element techniques can be used to derive the equations of motion with acceptable accuracy. The robust adaptive (modal) control is implemented to compensate for unmodelled modes and nonlinearities and is compared with the joint feedback control in additional experiments. Preliminary results show promise for the experimental control algorithm.

Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array.

PubMed

Boutemedjet, Ayoub; Deng, Chenwei; Zhao, Baojun

2016-11-10

In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above.

Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

PubMed Central

Boutemedjet, Ayoub; Deng, Chenwei; Zhao, Baojun

2016-01-01

In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above. PMID:27834893

Sliding-mode control combined with improved adaptive feedforward for wafer scanner

NASA Astrophysics Data System (ADS)

Li, Xiaojie; Wang, Yiguang

2018-03-01

In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

Fuzzy Behavior-Based Navigation for Planetary

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Danny, Harrison; Lippincott, Tanya; Jamshidi, Mo

1997-01-01

Adaptive behavioral capabilities are necessary for robust rover navigation in unstructured and partially-mapped environments. A control approach is described which exploits the approximate reasoning capability of fuzzy logic to produce adaptive motion behavior. In particular, a behavior-based architecture for hierarchical fuzzy control of microrovers is presented. Its structure is described, as well as mechanisms of control decision-making which give rise to adaptive behavior. Control decisions for local navigation result from a consensus of recommendations offered only by behaviors that are applicable to current situations. Simulation predicts the navigation performance on a microrover in simplified Mars-analog terrain.

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

Robust adaptive relative position and attitude control for spacecraft autonomous proximity.

PubMed

Sun, Liang; Huo, Wei; Jiao, Zongxia

2016-07-01

This paper provides new results of the dynamical modeling and controller designing for autonomous close proximity phase during rendezvous and docking in the presence of kinematic couplings and model uncertainties. A globally defined relative motion mechanical model for close proximity operations is introduced firstly. Then, in spite of the kinematic couplings and thrust misalignment between relative rotation and relative translation, robust adaptive relative position and relative attitude controllers are designed successively. Finally, stability of the overall system is proved that the relative position and relative attitude are uniformly ultimately bounded, and the size of the ultimate bound can be regulated small enough by control system parameters. Performance of the controlled overall system is demonstrated via a representative numerical example. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Biomechanical Reconstruction Using the Tacit Learning System: Intuitive Control of Prosthetic Hand Rotation.

PubMed

Oyama, Shintaro; Shimoda, Shingo; Alnajjar, Fady S K; Iwatsuki, Katsuyuki; Hoshiyama, Minoru; Tanaka, Hirotaka; Hirata, Hitoshi

2016-01-01

Background: For mechanically reconstructing human biomechanical function, intuitive proportional control, and robustness to unexpected situations are required. Particularly, creating a functional hand prosthesis is a typical challenge in the reconstruction of lost biomechanical function. Nevertheless, currently available control algorithms are in the development phase. The most advanced algorithms for controlling multifunctional prosthesis are machine learning and pattern recognition of myoelectric signals. Despite the increase in computational speed, these methods cannot avoid the requirement of user consciousness and classified separation errors. "Tacit Learning System" is a simple but novel adaptive control strategy that can self-adapt its posture to environment changes. We introduced the strategy in the prosthesis rotation control to achieve compensatory reduction, as well as evaluated the system and its effects on the user. Methods: We conducted a non-randomized study involving eight prosthesis users to perform a bar relocation task with/without Tacit Learning System support. Hand piece and body motions were recorded continuously with goniometers, videos, and a motion-capture system. Findings: Reduction in the participants' upper extremity rotatory compensation motion was monitored during the relocation task in all participants. The estimated profile of total body energy consumption improved in five out of six participants. Interpretation: Our system rapidly accomplished nearly natural motion without unexpected errors. The Tacit Learning System not only adapts human motions but also enhances the human ability to adapt to the system quickly, while the system amplifies compensation generated by the residual limb. The concept can be extended to various situations for reconstructing lost functions that can be compensated.

Adaptive attitude control and momentum management for large-angle spacecraft maneuvers

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Sunkel, John W.

1992-01-01

The fully coupled equations of motion are systematically linearized around an equilibrium point of a gravity gradient stabilized spacecraft, controlled by momentum exchange devices. These equations are then used for attitude control system design of an early Space Station Freedom flight configuration, demonstrating the errors caused by the improper approximation of the spacecraft dynamics. A full state feedback controller, incorporating gain-scheduled adaptation of the attitude gains, is developed for use during spacecraft on-orbit assembly or operations characterized by significant mass properties variations. The feasibility of the gain adaptation is demonstrated via a Space Station Freedom assembly sequence case study. The attitude controller stability robustness and transient performance during gain adaptation appear satisfactory.

Adaptive motion artifact reducing algorithm for wrist photoplethysmography application

NASA Astrophysics Data System (ADS)

Zhao, Jingwei; Wang, Guijin; Shi, Chenbo

2016-04-01

Photoplethysmography (PPG) technology is widely used in wearable heart pulse rate monitoring. It might reveal the potential risks of heart condition and cardiopulmonary function by detecting the cardiac rhythms in physical exercise. However the quality of wrist photoelectric signal is very sensitive to motion artifact since the thicker tissues and the fewer amount of capillaries. Therefore, motion artifact is the major factor that impede the heart rate measurement in the high intensity exercising. One accelerometer and three channels of light with different wavelengths are used in this research to analyze the coupled form of motion artifact. A novel approach is proposed to separate the pulse signal from motion artifact by exploiting their mixing ratio in different optical paths. There are four major steps of our method: preprocessing, motion artifact estimation, adaptive filtering and heart rate calculation. Five healthy young men are participated in the experiment. The speeder in the treadmill is configured as 12km/h, and all subjects would run for 3-10 minutes by swinging the arms naturally. The final result is compared with chest strap. The average of mean square error (MSE) is less than 3 beats per minute (BPM/min). Proposed method performed well in intense physical exercise and shows the great robustness to individuals with different running style and posture.

Inspiration for wing design: how forelimb specialization enables active flight in modern vertebrates

PubMed Central

2017-01-01

Harnessing flight strategies refined by millions of years of evolution can help expedite the design of more efficient, manoeuvrable and robust flying robots. This review synthesizes recent advances and highlights remaining gaps in our understanding of how bird and bat wing adaptations enable effective flight. Included in this discussion is an evaluation of how current robotic analogues measure up to their biological sources of inspiration. Studies of vertebrate wings have revealed skeletal systems well suited for enduring the loads required during flight, but the mechanisms that drive coordinated motions between bones and connected integuments remain ill-described. Similarly, vertebrate flight muscles have adapted to sustain increased wing loading, but a lack of in vivo studies limits our understanding of specific muscular functions. Forelimb adaptations diverge at the integument level, but both bird feathers and bat membranes yield aerodynamic surfaces with a level of robustness unparalleled by engineered wings. These morphological adaptations enable a diverse range of kinematics tuned for different flight speeds and manoeuvres. By integrating vertebrate flight specializations—particularly those that enable greater robustness and adaptability—into the design and control of robotic wings, engineers can begin narrowing the wide margin that currently exists between flying robots and vertebrates. In turn, these robotic wings can help biologists create experiments that would be impossible in vivo. PMID:28592663

Inspiration for wing design: how forelimb specialization enables active flight in modern vertebrates.

PubMed

Chin, Diana D; Matloff, Laura Y; Stowers, Amanda Kay; Tucci, Emily R; Lentink, David

2017-06-01

Harnessing flight strategies refined by millions of years of evolution can help expedite the design of more efficient, manoeuvrable and robust flying robots. This review synthesizes recent advances and highlights remaining gaps in our understanding of how bird and bat wing adaptations enable effective flight. Included in this discussion is an evaluation of how current robotic analogues measure up to their biological sources of inspiration. Studies of vertebrate wings have revealed skeletal systems well suited for enduring the loads required during flight, but the mechanisms that drive coordinated motions between bones and connected integuments remain ill-described. Similarly, vertebrate flight muscles have adapted to sustain increased wing loading, but a lack of in vivo studies limits our understanding of specific muscular functions. Forelimb adaptations diverge at the integument level, but both bird feathers and bat membranes yield aerodynamic surfaces with a level of robustness unparalleled by engineered wings. These morphological adaptations enable a diverse range of kinematics tuned for different flight speeds and manoeuvres. By integrating vertebrate flight specializations-particularly those that enable greater robustness and adaptability-into the design and control of robotic wings, engineers can begin narrowing the wide margin that currently exists between flying robots and vertebrates. In turn, these robotic wings can help biologists create experiments that would be impossible in vivo . © 2017 The Author(s).

Adaptive relative pose control of spacecraft with model couplings and uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2018-02-01

The spacecraft pose tracking control problem for an uncertain pursuer approaching to a space target is researched in this paper. After modeling the nonlinearly coupled dynamics for relative translational and rotational motions between two spacecraft, position tracking and attitude synchronization controllers are developed independently by using a robust adaptive control approach. The unknown kinematic couplings, parametric uncertainties, and bounded external disturbances are handled with adaptive updating laws. It is proved via Lyapunov method that the pose tracking errors converge to zero asymptotically. Spacecraft close-range rendezvous and proximity operations are introduced as an example to validate the effectiveness of the proposed control approach.

Control of joint motion simulators for biomechanical research

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.

1992-01-01

The authors present a hierarchical adaptive algorithm for controlling upper extremity human joint motion simulators. A joint motion simulator is a computer-controlled, electromechanical system which permits the application of forces to the tendons of a human cadaver specimen in such a way that the cadaver joint under study achieves a desired motion in a physiologic manner. The proposed control scheme does not require knowledge of the cadaver specimen dynamic model, and solves on-line the indeterminate problem which arises because human joints typically possess more actuators than degrees of freedom. Computer simulation results are given for an elbow/forearm system and wrist/hand system under hierarchical control. The results demonstrate that any desired normal joint motion can be accurately tracked with the proposed algorithm. These simulation results indicate that the controller resolved the indeterminate problem redundancy in a physiologic manner, and show that the control scheme was robust to parameter uncertainty and to sensor noise.

Robust Fusion of Color and Depth Data for RGB-D Target Tracking Using Adaptive Range-Invariant Depth Models and Spatio-Temporal Consistency Constraints.

PubMed

Xiao, Jingjing; Stolkin, Rustam; Gao, Yuqing; Leonardis, Ales

2017-09-06

This paper presents a novel robust method for single target tracking in RGB-D images, and also contributes a substantial new benchmark dataset for evaluating RGB-D trackers. While a target object's color distribution is reasonably motion-invariant, this is not true for the target's depth distribution, which continually varies as the target moves relative to the camera. It is therefore nontrivial to design target models which can fully exploit (potentially very rich) depth information for target tracking. For this reason, much of the previous RGB-D literature relies on color information for tracking, while exploiting depth information only for occlusion reasoning. In contrast, we propose an adaptive range-invariant target depth model, and show how both depth and color information can be fully and adaptively fused during the search for the target in each new RGB-D image. We introduce a new, hierarchical, two-layered target model (comprising local and global models) which uses spatio-temporal consistency constraints to achieve stable and robust on-the-fly target relearning. In the global layer, multiple features, derived from both color and depth data, are adaptively fused to find a candidate target region. In ambiguous frames, where one or more features disagree, this global candidate region is further decomposed into smaller local candidate regions for matching to local-layer models of small target parts. We also note that conventional use of depth data, for occlusion reasoning, can easily trigger false occlusion detections when the target moves rapidly toward the camera. To overcome this problem, we show how combining target information with contextual information enables the target's depth constraint to be relaxed. Our adaptively relaxed depth constraints can robustly accommodate large and rapid target motion in the depth direction, while still enabling the use of depth data for highly accurate reasoning about occlusions. For evaluation, we introduce a new RGB-D benchmark dataset with per-frame annotated attributes and extensive bias analysis. Our tracker is evaluated using two different state-of-the-art methodologies, VOT and object tracking benchmark, and in both cases it significantly outperforms four other state-of-the-art RGB-D trackers from the literature.

Robust patella motion tracking using intensity-based 2D-3D registration on dynamic bi-plane fluoroscopy: towards quantitative assessment in MPFL reconstruction surgery

NASA Astrophysics Data System (ADS)

Otake, Yoshito; Esnault, Matthieu; Grupp, Robert; Kosugi, Shinichi; Sato, Yoshinobu

2016-03-01

The determination of in vivo motion of multiple-bones using dynamic fluoroscopic images and computed tomography (CT) is useful for post-operative assessment of orthopaedic surgeries such as medial patellofemoral ligament reconstruction. We propose a robust method to measure the 3D motion of multiple rigid objects with high accuracy using a series of bi-plane fluoroscopic images and a multi-resolution, intensity-based, 2D-3D registration. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer was used with a gradient correlation similarity metric. Four approaches to register three rigid objects (femur, tibia-fibula and patella) were implemented: 1) an individual bone approach registering one bone at a time, each with optimization of a six degrees of freedom (6DOF) parameter, 2) a sequential approach registering one bone at a time but using the previous bone results as the background in DRR generation, 3) a simultaneous approach registering all the bones together (18DOF) and 4) a combination of the sequential and the simultaneous approaches. These approaches were compared in experiments using simulated images generated from the CT of a healthy volunteer and measured fluoroscopic images. Over the 120 simulated frames of motion, the simultaneous approach showed improved registration accuracy compared to the individual approach: with less than 0.68mm root-mean-square error (RMSE) for translation and less than 1.12° RMSE for rotation. A robustness evaluation was conducted with 45 trials of a randomly perturbed initialization showed that the sequential approach improved robustness significantly (74% success rate) compared to the individual bone approach (34% success) for patella registration (femur and tibia-fibula registration had a 100% success rate with each approach).

Assessing the performance of a motion tracking system based on optical joint transform correlation

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

2015-08-01

We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

AFFINE-CORRECTED PARADISE: FREE-BREATHING PATIENT-ADAPTIVE CARDIAC MRI WITH SENSITIVITY ENCODING

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

We propose a real-time cardiac imaging method with parallel MRI that allows for free breathing during imaging and does not require cardiac or respiratory gating. The method is based on the recently proposed PARADISE (Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding) scheme. The new acquisition method adapts the PARADISE k-t space sampling pattern according to an affine model of the respiratory motion. The reconstruction scheme involves multi-channel time-sequential imaging with time-varying channels. All model parameters are adapted to the imaged patient as part of the experiment and drive both data acquisition and cine reconstruction. Simulated cardiac MRI experiments using the realistic NCAT phantom show high quality cine reconstructions and robustness to modeling inaccuracies. PMID:24390159

Symmetry-breaking phase transitions in highly concentrated semen

PubMed Central

Creppy, Adama; Plouraboué, Franck; Praud, Olivier; Druart, Xavier; Cazin, Sébastien; Yu, Hui

2016-01-01

New experimental evidence of self-motion of a confined active suspension is presented. Depositing fresh semen sample in an annular shaped microfluidic chip leads to a spontaneous vortex state of the fluid at sufficiently large sperm concentration. The rotation occurs unpredictably clockwise or counterclockwise and is robust and stable. Furthermore, for highly active and concentrated semen, richer dynamics can occur such as self-sustained or damped rotation oscillations. Experimental results obtained with systematic dilution provide a clear evidence of a phase transition towards collective motion associated with local alignment of spermatozoa akin to the Vicsek model. A macroscopic theory based on previously derived self-organized hydrodynamics models is adapted to this context and provides predictions consistent with the observed stationary motion. PMID:27733694

Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

NASA Astrophysics Data System (ADS)

Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

2016-11-01

For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

Motion-guided attention promotes adaptive communications during social navigation.

PubMed

Lemasson, B H; Anderson, J J; Goodwin, R A

2013-03-07

Animals are capable of enhanced decision making through cooperation, whereby accurate decisions can occur quickly through decentralized consensus. These interactions often depend upon reliable social cues, which can result in highly coordinated activities in uncertain environments. Yet information within a crowd may be lost in translation, generating confusion and enhancing individual risk. As quantitative data detailing animal social interactions accumulate, the mechanisms enabling individuals to rapidly and accurately process competing social cues remain unresolved. Here, we model how motion-guided attention influences the exchange of visual information during social navigation. We also compare the performance of this mechanism to the hypothesis that robust social coordination requires individuals to numerically limit their attention to a set of n-nearest neighbours. While we find that such numerically limited attention does not generate robust social navigation across ecological contexts, several notable qualities arise from selective attention to motion cues. First, individuals can instantly become a local information hub when startled into action, without requiring changes in neighbour attention level. Second, individuals can circumvent speed-accuracy trade-offs by tuning their motion thresholds. In turn, these properties enable groups to collectively dampen or amplify social information. Lastly, the minority required to sway a group's short-term directional decisions can change substantially with social context. Our findings suggest that motion-guided attention is a fundamental and efficient mechanism underlying collaborative decision making during social navigation.

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

PubMed Central

Brinkworth, Russell S. A.; O'Carroll, David C.

2009-01-01

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. PMID:19893631

Infrared Thermography Sensor for Temperature and Speed Measurement of Moving Material.

PubMed

Usamentiaga, Rubén; García, Daniel Fernando

2017-05-18

Infrared thermography offers significant advantages in monitoring the temperature of objects over time, but crucial aspects need to be addressed. Movements between the infrared camera and the inspected material seriously affect the accuracy of the calculated temperature. These movements can be the consequence of solid objects that are moved, molten metal poured, material on a conveyor belt, or just vibrations. This work proposes a solution for monitoring the temperature of material in these scenarios. In this work both real movements and vibrations are treated equally, proposing a unified solution for both problems. The three key steps of the proposed procedure are image rectification, motion estimation and motion compensation. Image rectification calculates a front-parallel projection of the image that simplifies the estimation and compensation of the movement. Motion estimation describes the movement using a mathematical model, and estimates the coefficients using robust methods adapted to infrared images. Motion is finally compensated for in order to produce the correct temperature time history of the monitored material regardless of the movement. The result is a robust sensor for temperature of moving material that can also be used to measure the speed of the material. Different experiments are carried out to validate the proposed method in laboratory and real environments. Results show excellent performance.

Infrared Thermography Sensor for Temperature and Speed Measurement of Moving Material

PubMed Central

Usamentiaga, Rubén; García, Daniel Fernando

2017-01-01

Infrared thermography offers significant advantages in monitoring the temperature of objects over time, but crucial aspects need to be addressed. Movements between the infrared camera and the inspected material seriously affect the accuracy of the calculated temperature. These movements can be the consequence of solid objects that are moved, molten metal poured, material on a conveyor belt, or just vibrations. This work proposes a solution for monitoring the temperature of material in these scenarios. In this work both real movements and vibrations are treated equally, proposing a unified solution for both problems. The three key steps of the proposed procedure are image rectification, motion estimation and motion compensation. Image rectification calculates a front-parallel projection of the image that simplifies the estimation and compensation of the movement. Motion estimation describes the movement using a mathematical model, and estimates the coefficients using robust methods adapted to infrared images. Motion is finally compensated for in order to produce the correct temperature time history of the monitored material regardless of the movement. The result is a robust sensor for temperature of moving material that can also be used to measure the speed of the material. Different experiments are carried out to validate the proposed method in laboratory and real environments. Results show excellent performance. PMID:28524110

Robust moving mesh algorithms for hybrid stretched meshes: Application to moving boundaries problems

NASA Astrophysics Data System (ADS)

Landry, Jonathan; Soulaïmani, Azzeddine; Luke, Edward; Ben Haj Ali, Amine

2016-12-01

A robust Mesh-Mover Algorithm (MMA) approach is designed to adapt meshes of moving boundaries problems. A new methodology is developed from the best combination of well-known algorithms in order to preserve the quality of initial meshes. In most situations, MMAs distribute mesh deformation while preserving a good mesh quality. However, invalid meshes are generated when the motion is complex and/or involves multiple bodies. After studying a few MMA limitations, we propose the following approach: use the Inverse Distance Weighting (IDW) function to produce the displacement field, then apply the Geometric Element Transformation Method (GETMe) smoothing algorithms to improve the resulting mesh quality, and use an untangler to revert negative elements. The proposed approach has been proven efficient to adapt meshes for various realistic aerodynamic motions: a symmetric wing that has suffered large tip bending and twisting and the high-lift components of a swept wing that has moved to different flight stages. Finally, the fluid flow problem has been solved on meshes that have moved and they have produced results close to experimental ones. However, for situations where moving boundaries are too close to each other, more improvements need to be made or other approaches should be taken, such as an overset grid method.

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

PubMed

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Robust object tacking based on self-adaptive search area

NASA Astrophysics Data System (ADS)

Dong, Taihang; Zhong, Sheng

2018-02-01

Discriminative correlation filter (DCF) based trackers have recently achieved excellent performance with great computational efficiency. However, DCF based trackers suffer boundary effects, which result in the unstable performance in challenging situations exhibiting fast motion. In this paper, we propose a novel method to mitigate this side-effect in DCF based trackers. We change the search area according to the prediction of target motion. When the object moves fast, broad search area could alleviate boundary effects and reserve the probability of locating object. When the object moves slowly, narrow search area could prevent effect of useless background information and improve computational efficiency to attain real-time performance. This strategy can impressively soothe boundary effects in situations exhibiting fast motion and motion blur, and it can be used in almost all DCF based trackers. The experiments on OTB benchmark show that the proposed framework improves the performance compared with the baseline trackers.

An efficient motion-resistant method for wearable pulse oximeter.

PubMed

Yan, Yong-Sheng; Zhang, Yuan-Ting

2008-05-01

Reduction of motion artifact and power saving are crucial in designing a wearable pulse oximeter for long-term telemedicine application. In this paper, a novel algorithm, minimum correlation discrete saturation transform (MCDST) has been developed for the estimation of arterial oxygen saturation (SaO2), based on an optical model derived from photon diffusion analysis. The simulation shows that the new algorithm MCDST is more robust under low SNRs than the clinically verified motion-resistant algorithm discrete saturation transform (DST). Further, the experiment with different severity of motions demonstrates that MCDST has a slightly better performance than DST algorithm. Moreover, MCDST is more computationally efficient than DST because the former uses linear algebra instead of the time-consuming adaptive filter used by latter, which indicates that MCDST can reduce the required power consumption and circuit complexity of the implementation. This is vital for wearable devices, where the physical size and long battery life are crucial.

Limb Position Tolerant Pattern Recognition for Myoelectric Prosthesis Control with Adaptive Sparse Representations From Extreme Learning.

PubMed

Betthauser, Joseph L; Hunt, Christopher L; Osborn, Luke E; Masters, Matthew R; Levay, Gyorgy; Kaliki, Rahul R; Thakor, Nitish V

2018-04-01

Myoelectric signals can be used to predict the intended movements of an amputee for prosthesis control. However, untrained effects like limb position changes influence myoelectric signal characteristics, hindering the ability of pattern recognition algorithms to discriminate among motion classes. Despite frequent and long training sessions, these deleterious conditional influences may result in poor performance and device abandonment. We present a robust sparsity-based adaptive classification method that is significantly less sensitive to signal deviations resulting from untrained conditions. We compare this approach in the offline and online contexts of untrained upper-limb positions for amputee and able-bodied subjects to demonstrate its robustness compared against other myoelectric classification methods. We report significant performance improvements () in untrained limb positions across all subject groups. The robustness of our suggested approach helps to ensure better untrained condition performance from fewer training conditions. This method of prosthesis control has the potential to deliver real-world clinical benefits to amputees: better condition-tolerant performance, reduced training burden in terms of frequency and duration, and increased adoption of myoelectric prostheses.

A method for acquiring random range uncertainty probability distributions in proton therapy

NASA Astrophysics Data System (ADS)

Holloway, S. M.; Holloway, M. D.; Thomas, S. J.

2018-01-01

In treatment planning we depend upon accurate knowledge of geometric and range uncertainties. If the uncertainty model is inaccurate then the plan will produce under-dosing of the target and/or overdosing of OAR. We aim to provide a method for which centre and site-specific population range uncertainty due to inter-fraction motion can be quantified to improve the uncertainty model in proton treatment planning. Daily volumetric MVCT data from previously treated radiotherapy patients has been used to investigate inter-fraction changes to water equivalent path-length (WEPL). Daily image-guidance scans were carried out for each patient and corrected for changes in CTV position (using rigid transformations). An effective depth algorithm was used to determine residual range changes, after corrections had been applied, throughout the treatment by comparing WEPL within the CTV at each fraction for several beam angles. As a proof of principle this method was used to quantify uncertainties for inter-fraction range changes for a sample of head and neck patients of Σ=3.39 mm, σ = 4.72 mm and overall mean = -1.82 mm. For prostate Σ=5.64 mm, σ = 5.91 mm and overall mean = 0.98 mm. The choice of beam angle for head and neck did not affect the inter-fraction range error significantly; however this was not the same for prostate. Greater range changes were seen using a lateral beam compared to an anterior beam for prostate due to relative motion of the prostate and femoral heads. A method has been developed to quantify population range changes due to inter-fraction motion that can be adapted for the clinic. The results of this work highlight the importance of robust planning and analysis in proton therapy. Such information could be used in robust optimisation algorithms or treatment plan robustness analysis. Such knowledge will aid in establishing beam start conditions at planning and for establishing adaptive planning protocols.

Adaptive algorithm of magnetic heading detection

NASA Astrophysics Data System (ADS)

Liu, Gong-Xu; Shi, Ling-Feng

2017-11-01

Magnetic data obtained from a magnetic sensor usually fluctuate in a certain range, which makes it difficult to estimate the magnetic heading accurately. In fact, magnetic heading information is usually submerged in noise because of all kinds of electromagnetic interference and the diversity of the pedestrian’s motion states. In order to solve this problem, a new adaptive algorithm based on the (typically) right-angled corridors of a building or residential buildings is put forward to process heading information. First, a 3D indoor localization platform is set up based on MPU9250. Then, several groups of data are measured by changing the experimental environment and pedestrian’s motion pace. The raw data from the attached inertial measurement unit are calibrated and arranged into a time-stamped array and written to a data file. Later, the data file is imported into MATLAB for processing and analysis using the proposed adaptive algorithm. Finally, the algorithm is verified by comparison with the existing algorithm. The experimental results show that the algorithm has strong robustness and good fault tolerance, which can detect the heading information accurately and in real-time.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Shaohua; School of Automation, Chongqing University, Chongqing 400044; Sun, Quanping

This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Puttingmore » tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.« less

Multivariable robust adaptive sliding mode control of an industrial boiler-turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller.

PubMed

Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza

2015-09-01

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Extended state observer based robust adaptive control on SE(3) for coupled spacecraft tracking maneuver with actuator saturation and misalignment

NASA Astrophysics Data System (ADS)

Zhang, Jianqiao; Ye, Dong; Sun, Zhaowei; Liu, Chuang

2018-02-01

This paper presents a robust adaptive controller integrated with an extended state observer (ESO) to solve coupled spacecraft tracking maneuver in the presence of model uncertainties, external disturbances, actuator uncertainties including magnitude deviation and misalignment, and even actuator saturation. More specifically, employing the exponential coordinates on the Lie group SE(3) to describe configuration tracking errors, the coupled six-degrees-of-freedom (6-DOF) dynamics are developed for spacecraft relative motion, in which a generic fully actuated thruster distribution is considered and the lumped disturbances are reconstructed by using anti-windup technique. Then, a novel ESO, developed via second order sliding mode (SOSM) technique and adding linear correction terms to improve the performance, is designed firstly to estimate the disturbances in finite time. Based on the estimated information, an adaptive fast terminal sliding mode (AFTSM) controller is developed to guarantee the almost global asymptotic stability of the resulting closed-loop system such that the trajectory can be tracked with all the aforementioned drawbacks addressed simultaneously. Finally, the effectiveness of the controller is illustrated through numerical examples.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Bio-inspired optical rotation sensor

NASA Astrophysics Data System (ADS)

O'Carroll, David C.; Shoemaker, Patrick A.; Brinkworth, Russell S. A.

2007-01-01

Traditional approaches to calculating self-motion from visual information in artificial devices have generally relied on object identification and/or correlation of image sections between successive frames. Such calculations are computationally expensive and real-time digital implementation requires powerful processors. In contrast flies arrive at essentially the same outcome, the estimation of self-motion, in a much smaller package using vastly less power. Despite the potential advantages and a few notable successes, few neuromorphic analog VLSI devices based on biological vision have been employed in practical applications to date. This paper describes a hardware implementation in aVLSI of our recently developed adaptive model for motion detection. The chip integrates motion over a linear array of local motion processors to give a single voltage output. Although the device lacks on-chip photodetectors, it includes bias circuits to use currents from external photodiodes, and we have integrated it with a ring-array of 40 photodiodes to form a visual rotation sensor. The ring configuration reduces pattern noise and combined with the pixel-wise adaptive characteristic of the underlying circuitry, permits a robust output that is proportional to image rotational velocity over a large range of speeds, and is largely independent of either mean luminance or the spatial structure of the image viewed. In principle, such devices could be used as an element of a velocity-based servo to replace or augment inertial guidance systems in applications such as mUAVs.

High speed, precision motion strategies for lightweight structures

NASA Technical Reports Server (NTRS)

Book, Wayne J.

1989-01-01

Research on space telerobotics is summarized. Adaptive control experiments on the Robotic Arm, Large and Flexible (RALF) were preformed and are documented, along with a joint controller design for the Small Articulated Manipulator (SAM), which is mounted on the RALF. A control algorithm is described as a robust decentralized adaptive control based on a bounded uncertainty approach. Dynamic interactions between SAM and RALF are examined. Unstability of the manipulator is studied from the perspective that the inertial forces generated could actually be used to more rapidly damp out the flexible manipulator's vibration. Currently being studied is the modeling of the constrained dynamics of flexible arms.

Kinematics and Dynamics of Motion Control Based on Acceleration Control

NASA Astrophysics Data System (ADS)

Ohishi, Kiyoshi; Ohba, Yuzuru; Katsura, Seiichiro

The first IEEE International Workshop on Advanced Motion Control was held in 1990 pointed out the importance of physical interpretation of motion control. The software servoing technology is now common in machine tools, robotics, and mechatronics. It has been intensively developed for the numerical control (NC) machines. Recently, motion control in unknown environment will be more and more important. Conventional motion control is not always suitable due to the lack of adaptive capability to the environment. A more sophisticated ability in motion control is necessary for compliant contact with environment. Acceleration control is the key technology of motion control in unknown environment. The acceleration control can make a motion system to be a zero control stiffness system without losing the robustness. Furthermore, a realization of multi-degree-of-freedom motion is necessary for future human assistance. A human assistant motion will require various control stiffness corresponding to the task. The review paper focuses on the modal coordinate system to integrate the various control stiffness in the virtual axes. A bilateral teleoperation is a good candidate to consider the future human assistant motion and integration of decentralized systems. Thus the paper reviews and discusses the bilateral teleoperation from the control stiffness and the modal control design points of view.

IECON '87: Industrial applications of control and simulation; Proceedings of the 1987 International Conference on Industrial Electronics, Control, and Instrumentation, Cambridge, MA, Nov. 3, 4, 1987

NASA Technical Reports Server (NTRS)

Hartley, Tom T. (Editor)

1987-01-01

Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.

Motion vector field phase-to-amplitude resampling for 4D motion-compensated cone-beam CT

NASA Astrophysics Data System (ADS)

Sauppe, Sebastian; Kuhm, Julian; Brehm, Marcus; Paysan, Pascal; Seghers, Dieter; Kachelrieß, Marc

2018-02-01

We propose a phase-to-amplitude resampling (PTAR) method to reduce motion blurring in motion-compensated (MoCo) 4D cone-beam CT (CBCT) image reconstruction, without increasing the computational complexity of the motion vector field (MVF) estimation approach. PTAR is able to improve the image quality in reconstructed 4D volumes, including both regular and irregular respiration patterns. The PTAR approach starts with a robust phase-gating procedure for the initial MVF estimation and then switches to a phase-adapted amplitude gating method. The switch implies an MVF-resampling, which makes them amplitude-specific. PTAR ensures that the MVFs, which have been estimated on phase-gated reconstructions, are still valid for all amplitude-gated reconstructions. To validate the method, we use an artificially deformed clinical CT scan with a realistic breathing pattern and several patient data sets acquired with a TrueBeamTM integrated imaging system (Varian Medical Systems, Palo Alto, CA, USA). Motion blurring, which still occurs around the area of the diaphragm or at small vessels above the diaphragm in artifact-specific cyclic motion compensation (acMoCo) images based on phase-gating, is significantly reduced by PTAR. Also, small lung structures appear sharper in the images. This is demonstrated both for simulated and real patient data. A quantification of the sharpness of the diaphragm confirms these findings. PTAR improves the image quality of 4D MoCo reconstructions compared to conventional phase-gated MoCo images, in particular for irregular breathing patterns. Thus, PTAR increases the robustness of MoCo reconstructions for CBCT. Because PTAR does not require any additional steps for the MVF estimation, it is computationally efficient. Our method is not restricted to CBCT but could rather be applied to other image modalities.

Image-guided positioning and tracking.

PubMed

Ruan, Dan; Kupelian, Patrick; Low, Daniel A

2011-01-01

Radiation therapy aims at maximizing tumor control while minimizing normal tissue complication. The introduction of stereotactic treatment explores the volume effect and achieves dose escalation to tumor target with small margins. The use of ablative irradiation dose and sharp dose gradients requires accurate tumor definition and alignment between patient and treatment geometry. Patient geometry variation during treatment may significantly compromise the conformality of delivered dose and must be managed properly. Setup error and interfraction/intrafraction motion are incorporated in the target definition process by expanding the clinical target volume to planning target volume, whereas the alignment between patient and treatment geometry is obtained with an adaptive control process, by taking immediate actions in response to closely monitored patient geometry. This article focuses on the monitoring and adaptive response aspect of the problem. The term "image" in "image guidance" will be used in a most general sense, to be inclusive of some important point-based monitoring systems that can be considered as degenerate cases of imaging. Image-guided motion adaptive control, as a comprehensive system, involves a hierarchy of decisions, each of which balances simplicity versus flexibility and accuracy versus robustness. Patient specifics and machine specifics at the treatment facility also need to be incorporated into the decision-making process. Identifying operation bottlenecks from a system perspective and making informed compromises are crucial in the proper selection of image-guidance modality, the motion management mechanism, and the respective operation modes. Not intended as an exhaustive exposition, this article focuses on discussing the major issues and development principles for image-guided motion management systems. We hope these information and methodologies will facilitate conscientious practitioners to adopt image-guided motion management systems accounting for patient and institute specifics and to embrace advances in knowledge and new technologies subsequent to the publication of this article.

SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, W; Schild, S; Bues, M

Purpose: We compared conventionally optimized intensity-modulated proton therapy (IMPT) treatment plans against the worst-case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set-up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods: For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from themore » internal target volume (ITV). The second employed the worst-case robust optimization scheme that addressed set-up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two-sided paired t-tests. Results: Without respiratory motion considered, we affirmed that worst-case robust optimization is superior to PTV-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% - D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)]. Conclusion: Worst-case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly account for respiratory motion it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization.« less

Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients †

PubMed Central

Fidan, Barış; Umay, Ilknur

2015-01-01

Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. PMID:26690441

A Kinect-Based Real-Time Compressive Tracking Prototype System for Amphibious Spherical Robots

PubMed Central

Pan, Shaowu; Shi, Liwei; Guo, Shuxiang

2015-01-01

A visual tracking system is essential as a basis for visual servoing, autonomous navigation, path planning, robot-human interaction and other robotic functions. To execute various tasks in diverse and ever-changing environments, a mobile robot requires high levels of robustness, precision, environmental adaptability and real-time performance of the visual tracking system. In keeping with the application characteristics of our amphibious spherical robot, which was proposed for flexible and economical underwater exploration in 2012, an improved RGB-D visual tracking algorithm is proposed and implemented. Given the limited power source and computational capabilities of mobile robots, compressive tracking (CT), which is the effective and efficient algorithm that was proposed in 2012, was selected as the basis of the proposed algorithm to process colour images. A Kalman filter with a second-order motion model was implemented to predict the state of the target and select candidate patches or samples for the CT tracker. In addition, a variance ratio features shift (VR-V) tracker with a Kalman estimation mechanism was used to process depth images. Using a feedback strategy, the depth tracking results were used to assist the CT tracker in updating classifier parameters at an adaptive rate. In this way, most of the deficiencies of CT, including drift and poor robustness to occlusion and high-speed target motion, were partly solved. To evaluate the proposed algorithm, a Microsoft Kinect sensor, which combines colour and infrared depth cameras, was adopted for use in a prototype of the robotic tracking system. The experimental results with various image sequences demonstrated the effectiveness, robustness and real-time performance of the tracking system. PMID:25856331

A Kinect-based real-time compressive tracking prototype system for amphibious spherical robots.

PubMed

Pan, Shaowu; Shi, Liwei; Guo, Shuxiang

2015-04-08

A visual tracking system is essential as a basis for visual servoing, autonomous navigation, path planning, robot-human interaction and other robotic functions. To execute various tasks in diverse and ever-changing environments, a mobile robot requires high levels of robustness, precision, environmental adaptability and real-time performance of the visual tracking system. In keeping with the application characteristics of our amphibious spherical robot, which was proposed for flexible and economical underwater exploration in 2012, an improved RGB-D visual tracking algorithm is proposed and implemented. Given the limited power source and computational capabilities of mobile robots, compressive tracking (CT), which is the effective and efficient algorithm that was proposed in 2012, was selected as the basis of the proposed algorithm to process colour images. A Kalman filter with a second-order motion model was implemented to predict the state of the target and select candidate patches or samples for the CT tracker. In addition, a variance ratio features shift (VR-V) tracker with a Kalman estimation mechanism was used to process depth images. Using a feedback strategy, the depth tracking results were used to assist the CT tracker in updating classifier parameters at an adaptive rate. In this way, most of the deficiencies of CT, including drift and poor robustness to occlusion and high-speed target motion, were partly solved. To evaluate the proposed algorithm, a Microsoft Kinect sensor, which combines colour and infrared depth cameras, was adopted for use in a prototype of the robotic tracking system. The experimental results with various image sequences demonstrated the effectiveness, robustness and real-time performance of the tracking system.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heijkoop, Sabrina T., E-mail: s.heijkoop@erasmusmc.nl; Langerak, Thomas R.; Quint, Sandra

Purpose: To evaluate the clinical implementation of an online adaptive plan-of-the-day protocol for nonrigid target motion management in locally advanced cervical cancer intensity modulated radiation therapy (IMRT). Methods and Materials: Each of the 64 patients had four markers implanted in the vaginal fornix to verify the position of the cervix during treatment. Full and empty bladder computed tomography (CT) scans were acquired prior to treatment to build a bladder volume-dependent cervix-uterus motion model for establishment of the plan library. In the first phase of clinical implementation, the library consisted of one IMRT plan based on a single model-predicted internal targetmore » volume (mpITV), covering the target for the whole pretreatment observed bladder volume range, and a 3D conformal radiation therapy (3DCRT) motion-robust backup plan based on the same mpITV. The planning target volume (PTV) combined the ITV and nodal clinical target volume (CTV), expanded with a 1-cm margin. In the second phase, for patients showing >2.5-cm bladder-induced cervix-uterus motion during planning, two IMRT plans were constructed, based on mpITVs for empty-to-half-full and half-full-to-full bladder. In both phases, a daily cone beam CT (CBCT) scan was acquired to first position the patient based on bony anatomy and nodal targets and then select the appropriate plan. Daily post-treatment CBCT was used to verify plan selection. Results: Twenty-four and 40 patients were included in the first and second phase, respectively. In the second phase, 11 patients had two IMRT plans. Overall, an IMRT plan was used in 82.4% of fractions. The main reasons for selecting the motion-robust backup plan were uterus outside the PTV (27.5%) and markers outside their margin (21.3%). In patients with two IMRT plans, the half-full-to-full bladder plan was selected on average in 45% of the first 12 fractions, which was reduced to 35% in the last treatment fractions. Conclusions: The implemented online adaptive plan-of-the-day protocol for locally advanced cervical cancer enables (almost) daily tissue-sparing IMRT.« less

A self-adaptive algorithm for traffic sign detection in motion image based on color and shape features

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Gong, Zhijun; Ye, Chun; Li, Yongqiang; Liang, Cheng

2007-06-01

As an important sub-system in intelligent transportation system (ITS), the detection and recognition of traffic signs from mobile images is becoming one of the hot spots in the international research field of ITS. Considering the problem of traffic sign automatic detection in motion images, a new self-adaptive algorithm for traffic sign detection based on color and shape features is proposed in this paper. Firstly, global statistical color features of different images are computed based on statistics theory. Secondly, some self-adaptive thresholds and special segmentation rules for image segmentation are designed according to these global color features. Then, for red, yellow and blue traffic signs, the color image is segmented to three binary images by these thresholds and rules. Thirdly, if the number of white pixels in the segmented binary image exceeds the filtering threshold, the binary image should be further filtered. Fourthly, the method of gray-value projection is used to confirm top, bottom, left and right boundaries for candidate regions of traffic signs in the segmented binary image. Lastly, if the shape feature of candidate region satisfies the need of real traffic sign, this candidate region is confirmed as the detected traffic sign region. The new algorithm is applied to actual motion images of natural scenes taken by a CCD camera of the mobile photogrammetry system in Nanjing at different time. The experimental results show that the algorithm is not only simple, robust and more adaptive to natural scene images, but also reliable and high-speed on real traffic sign detection.

The effects of motion artifact on mechanomyography: A comparative study of microphones and accelerometers.

PubMed

Posatskiy, A O; Chau, T

2012-04-01

Mechanomyography (MMG) is an important kinesiological tool and potential communication pathway for individuals with disabilities. However, MMG is highly susceptible to contamination by motion artifact due to limb movement. A better understanding of the nature of this contamination and its effects on different sensing methods is required to inform robust MMG sensor design. Therefore, in this study, we recorded MMG from the extensor carpi ulnaris of six able-bodied participants using three different co-located condenser microphone and accelerometer pairings. Contractions at 30% MVC were recorded with and without a shaker-induced single-frequency forearm motion artifact delivered via a custom test rig. Using a signal-to-signal-plus-noise-ratio and the adaptive Neyman curve-based statistic, we found that microphone-derived MMG spectra were significantly less influenced by motion artifact than corresponding accelerometer-derived spectra (p⩽0.05). However, non-vanishing motion artifact harmonics were present in both spectra, suggesting that simple bandpass filtering may not remove artifact influences permeating into typical MMG bands of interest. Our results suggest that condenser microphones are preferred for MMG recordings when the mitigation of motion artifact effects is important. Copyright © 2011. Published by Elsevier Ltd.

Adaptive ISAR Imaging of Maneuvering Targets Based on a Modified Fourier Transform.

PubMed

Wang, Binbin; Xu, Shiyou; Wu, Wenzhen; Hu, Pengjiang; Chen, Zengping

2018-04-27

Focusing on the inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, this paper presents a new imaging method which works well when the target's maneuvering is not too severe. After translational motion compensation, we describe the equivalent rotation of maneuvering targets by two variables-the relative chirp rate of the linear frequency modulated (LFM) signal and the Doppler focus shift. The first variable indicates the target's motion status, and the second one represents the possible residual error of the translational motion compensation. With them, a modified Fourier transform matrix is constructed and then used for cross-range compression. Consequently, the imaging of maneuvering is converted into a two-dimensional parameter optimization problem in which a stable and clear ISAR image is guaranteed. A gradient descent optimization scheme is employed to obtain the accurate relative chirp rate and Doppler focus shift. Moreover, we designed an efficient and robust initialization process for the gradient descent method, thus, the well-focused ISAR images of maneuvering targets can be achieved adaptively. Human intervention is not needed, and it is quite convenient for practical ISAR imaging systems. Compared to precedent imaging methods, the new method achieves better imaging quality under reasonable computational cost. Simulation results are provided to validate the effectiveness and advantages of the proposed method.

Robust laser-based detection of Lamb waves using photo-EMF sensors

NASA Astrophysics Data System (ADS)

Klein, Marvin B.; Bacher, Gerald D.

1998-03-01

Lamb waves are easily generated and detected using laser techniques. It has been shown that both symmetric and antisymmetric modes can be produced, using single-spot and phased array generation. Detection has been demonstrated with Michelson interferometers, but these instruments can not function effectively on rough surfaces. By contrast, the confocal Fabry-Perot interferometer can interrogate rough surfaces, but generally is not practical for operation below 300 kHz. In this paper we will present Lamb wave data on a number of parts using a robust, adaptive receiver based on photo-emf detection. This receiver has useful sensitivity down to at least 100 kHz, can process speckled beams and can be easily configured to measure both out-of-plane and in- plane motion with a single probe beam.

A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

PubMed

Zhang, Qingxue; Zhou, Dian; Zeng, Xuan

2016-11-01

This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous heart rate (IHR) from wrist-electrocardiography (ECG) signals continuously and heavily corrupted by random motion artifacts in wearable applications. The framework includes two stages, i.e. heartbeat identification and refinement, respectively. In the first stage, an adaptive threshold-based auto-segmentation approach is proposed to select out heartbeat candidates, including the real heartbeats and large amounts of motion-artifact-induced interferential spikes. Then twenty-six features are extracted for each candidate in time, spatial, frequency and statistical domains, and evaluated by a spare support vector machine (SVM) to select out ten critical features which can effectively reveal residual heartbeat information. Afterwards, an SVM model, created on the training data using the selected feature set, is applied to find high confident heartbeats from a large number of candidates in the testing data. In the second stage, the SVM classification results are further refined by two steps: (1) a rule-based classifier with two attributes named 'continuity check' and 'locality check' for outlier (false positives) removal, and (2) a heartbeat interpolation strategy for missing-heartbeat (false negatives) recovery. The framework is evaluated on a wrist-ECG dataset acquired by a semi-customized platform and also a public dataset. When the signal-to-noise ratio is as low as  -7 dB, the mean absolute error of the estimated IHR is 1.4 beats per minute (BPM) and the root mean square error is 6.5 BPM. The proposed framework greatly outperforms well-established approaches, demonstrating that it can effectively identify the heartbeats from ECG signals continuously corrupted by intense motion artifacts and robustly estimate the IHR. This study is expected to contribute to robust long-term wearable IHR monitoring for pervasive heart health and fitness management.

Siamese convolutional networks for tracking the spine motion

NASA Astrophysics Data System (ADS)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Robust and efficient method for matching features in omnidirectional images

NASA Astrophysics Data System (ADS)

Zhu, Qinyi; Zhang, Zhijiang; Zeng, Dan

2018-04-01

Binary descriptors have been widely used in many real-time applications due to their efficiency. These descriptors are commonly designed for perspective images but perform poorly on omnidirectional images, which are severely distorted. To address this issue, this paper proposes tangent plane BRIEF (TPBRIEF) and adapted log polar grid-based motion statistics (ALPGMS). TPBRIEF projects keypoints to a unit sphere and applies the fixed test set in BRIEF descriptor on the tangent plane of the unit sphere. The fixed test set is then backprojected onto the original distorted images to construct the distortion invariant descriptor. TPBRIEF directly enables keypoint detecting and feature describing on original distorted images, whereas other approaches correct the distortion through image resampling, which introduces artifacts and adds time cost. With ALPGMS, omnidirectional images are divided into circular arches named adapted log polar grids. Whether a match is true or false is then determined by simply thresholding the match numbers in a grid pair where the two matched points located. Experiments show that TPBRIEF greatly improves the feature matching accuracy and ALPGMS robustly removes wrong matches. Our proposed method outperforms the state-of-the-art methods.

Suppressive mechanisms in visual motion processing: from perception to intelligence

PubMed Central

Tadin, Duje

2015-01-01

Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and those with schizophrenia—a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores. PMID:26299386

Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters.

PubMed

Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

2016-09-07

Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers.

Sustainable Cooperative Robotic Technologies for Human and Robotic Outpost Infrastructure Construction and Maintenance

NASA Technical Reports Server (NTRS)

Stroupe, Ashley W.; Okon, Avi; Robinson, Matthew; Huntsberger, Terry; Aghazarian, Hrand; Baumgartner, Eric

2004-01-01

Robotic Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous acquisition, transport, and precision mating of components in construction tasks. RCC minimizes resources constrained in a space environment such as computation, power, communication and, sensing. A behavior-based architecture provides adaptability and robustness despite low computational requirements. RCC successfully performs several construction related tasks in an emulated outdoor environment despite high levels of uncertainty in motions and sensing. Quantitative results are provided for formation keeping in component transport, precision instrument placement, and construction tasks.

Parameter Studies, time-dependent simulations and design with automated Cartesian methods

NASA Technical Reports Server (NTRS)

Aftosmis, Michael

2005-01-01

Over the past decade, NASA has made a substantial investment in developing adaptive Cartesian grid methods for aerodynamic simulation. Cartesian-based methods played a key role in both the Space Shuttle Accident Investigation and in NASA's return to flight activities. The talk will provide an overview of recent technological developments focusing on the generation of large-scale aerodynamic databases, automated CAD-based design, and time-dependent simulations with of bodies in relative motion. Automation, scalability and robustness underly all of these applications and research in each of these topics will be presented.

A closed-loop neurobotic system for fine touch sensing

NASA Astrophysics Data System (ADS)

Bologna, L. L.; Pinoteau, J.; Passot, J.-B.; Garrido, J. A.; Vogel, J.; Ros Vidal, E.; Arleo, A.

2013-08-01

Objective. Fine touch sensing relies on peripheral-to-central neurotransmission of somesthetic percepts, as well as on active motion policies shaping tactile exploration. This paper presents a novel neuroengineering framework for robotic applications based on the multistage processing of fine tactile information in the closed action-perception loop. Approach. The integrated system modules focus on (i) neural coding principles of spatiotemporal spiking patterns at the periphery of the somatosensory pathway, (ii) probabilistic decoding mechanisms mediating cortical-like tactile recognition and (iii) decision-making and low-level motor adaptation underlying active touch sensing. We probed the resulting neural architecture through a Braille reading task. Main results. Our results on the peripheral encoding of primary contact features are consistent with experimental data on human slow-adapting type I mechanoreceptors. They also suggest second-order processing by cuneate neurons may resolve perceptual ambiguities, contributing to a fast and highly performing online discrimination of Braille inputs by a downstream probabilistic decoder. The implemented multilevel adaptive control provides robustness to motion inaccuracy, while making the number of finger accelerations covariate with Braille character complexity. The resulting modulation of fingertip kinematics is coherent with that observed in human Braille readers. Significance. This work provides a basis for the design and implementation of modular neuromimetic systems for fine touch discrimination in robotics.

Robust path planning for flexible needle insertion using Markov decision processes.

PubMed

Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong

2018-05-11

Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

Differential effect of visual motion adaption upon visual cortical excitability.

PubMed

Lubeck, Astrid J A; Van Ombergen, Angelique; Ahmad, Hena; Bos, Jelte E; Wuyts, Floris L; Bronstein, Adolfo M; Arshad, Qadeer

2017-03-01

The objectives of this study were 1 ) to probe the effects of visual motion adaptation on early visual and V5/MT cortical excitability and 2 ) to investigate whether changes in cortical excitability following visual motion adaptation are related to the degree of visual dependency, i.e., an overreliance on visual cues compared with vestibular or proprioceptive cues. Participants were exposed to a roll motion visual stimulus before, during, and after visual motion adaptation. At these stages, 20 transcranial magnetic stimulation (TMS) pulses at phosphene threshold values were applied over early visual and V5/MT cortical areas from which the probability of eliciting a phosphene was calculated. Before and after adaptation, participants aligned the subjective visual vertical in front of the roll motion stimulus as a marker of visual dependency. During adaptation, early visual cortex excitability decreased whereas V5/MT excitability increased. After adaptation, both early visual and V5/MT excitability were increased. The roll motion-induced tilt of the subjective visual vertical (visual dependence) was not influenced by visual motion adaptation and did not correlate with phosphene threshold or visual cortex excitability. We conclude that early visual and V5/MT cortical excitability is differentially affected by visual motion adaptation. Furthermore, excitability in the early or late visual cortex is not associated with an increase in visual reliance during spatial orientation. Our findings complement earlier studies that have probed visual cortical excitability following motion adaptation and highlight the differential role of the early visual cortex and V5/MT in visual motion processing. NEW & NOTEWORTHY We examined the influence of visual motion adaptation on visual cortex excitability and found a differential effect in V1/V2 compared with V5/MT. Changes in visual excitability following motion adaptation were not related to the degree of an individual's visual dependency. Copyright © 2017 the American Physiological Society.

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Investigation of whether in-room CT-based adaptive intracavitary brachytherapy for uterine cervical cancer is robust against interfractional location variations of organs and/or applicators

PubMed Central

Oku, Yoshifumi; Arimura, Hidetaka; Nguyen, Tran Thi Thao; Hiraki, Yoshiyuki; Toyota, Masahiko; Saigo, Yasumasa; Yoshiura, Takashi; Hirata, Hideki

2016-01-01

This study investigates whether in-room computed tomography (CT)-based adaptive treatment planning (ATP) is robust against interfractional location variations, namely, interfractional organ motions and/or applicator displacements, in 3D intracavitary brachytherapy (ICBT) for uterine cervical cancer. In ATP, the radiation treatment plans, which have been designed based on planning CT images (and/or MR images) acquired just before the treatments, are adaptively applied for each fraction, taking into account the interfractional location variations. 2D and 3D plans with ATP for 14 patients were simulated for 56 fractions at a prescribed dose of 600 cGy per fraction. The standard deviations (SDs) of location displacements (interfractional location variations) of the target and organs at risk (OARs) with 3D ATP were significantly smaller than those with 2D ATP (P < 0.05). The homogeneity index (HI), conformity index (CI) and tumor control probability (TCP) in 3D ATP were significantly higher for high-risk clinical target volumes than those in 2D ATP. The SDs of the HI, CI, TCP, bladder and rectum D2cc, and the bladder and rectum normal tissue complication probability (NTCP) in 3D ATP were significantly smaller than those in 2D ATP. The results of this study suggest that the interfractional location variations give smaller impacts on the planning evaluation indices in 3D ATP than in 2D ATP. Therefore, the 3D plans with ATP are expected to be robust against interfractional location variations in each treatment fraction. PMID:27296250

Segmentation and tracking of lung nodules via graph-cuts incorporating shape prior and motion from 4D CT.

PubMed

Cha, Jungwon; Farhangi, Mohammad Mehdi; Dunlap, Neal; Amini, Amir A

2018-01-01

We have developed a robust tool for performing volumetric and temporal analysis of nodules from respiratory gated four-dimensional (4D) CT. The method could prove useful in IMRT of lung cancer. We modified the conventional graph-cuts method by adding an adaptive shape prior as well as motion information within a signed distance function representation to permit more accurate and automated segmentation and tracking of lung nodules in 4D CT data. Active shape models (ASM) with signed distance function were used to capture the shape prior information, preventing unwanted surrounding tissues from becoming part of the segmented object. The optical flow method was used to estimate the local motion and to extend three-dimensional (3D) segmentation to 4D by warping a prior shape model through time. The algorithm has been applied to segmentation of well-circumscribed, vascularized, and juxtapleural lung nodules from respiratory gated CT data. In all cases, 4D segmentation and tracking for five phases of high-resolution CT data took approximately 10 min on a PC workstation with AMD Phenom II and 32 GB of memory. The method was trained based on 500 breath-held 3D CT data from the LIDC data base and was tested on 17 4D lung nodule CT datasets consisting of 85 volumetric frames. The validation tests resulted in an average Dice Similarity Coefficient (DSC) = 0.68 for all test data. An important by-product of the method is quantitative volume measurement from 4D CT from end-inspiration to end-expiration which will also have important diagnostic value. The algorithm performs robust segmentation of lung nodules from 4D CT data. Signed distance ASM provides the shape prior information which based on the iterative graph-cuts framework is adaptively refined to best fit the input data, preventing unwanted surrounding tissue from merging with the segmented object. © 2017 American Association of Physicists in Medicine.

A solution-adaptive hybrid-grid method for the unsteady analysis of turbomachinery

NASA Technical Reports Server (NTRS)

Mathur, Sanjay R.; Madavan, Nateri K.; Rajagopalan, R. G.

1993-01-01

A solution-adaptive method for the time-accurate analysis of two-dimensional flows in turbomachinery is described. The method employs a hybrid structured-unstructured zonal grid topology in conjunction with appropriate modeling equations and solution techniques in each zone. The viscous flow region in the immediate vicinity of the airfoils is resolved on structured O-type grids while the rest of the domain is discretized using an unstructured mesh of triangular cells. Implicit, third-order accurate, upwind solutions of the Navier-Stokes equations are obtained in the inner regions. In the outer regions, the Euler equations are solved using an explicit upwind scheme that incorporates a second-order reconstruction procedure. An efficient and robust grid adaptation strategy, including both grid refinement and coarsening capabilities, is developed for the unstructured grid regions. Grid adaptation is also employed to facilitate information transfer at the interfaces between unstructured grids in relative motion. Results for grid adaptation to various features pertinent to turbomachinery flows are presented. Good comparisons between the present results and experimental measurements and earlier structured-grid results are obtained.

Respiratory motion correction in dynamic MRI using robust data decomposition registration - application to DCE-MRI.

PubMed

Hamy, Valentin; Dikaios, Nikolaos; Punwani, Shonit; Melbourne, Andrew; Latifoltojar, Arash; Makanyanga, Jesica; Chouhan, Manil; Helbren, Emma; Menys, Alex; Taylor, Stuart; Atkinson, David

2014-02-01

Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15-62% reduction following registration) in tissue time-intensity curves and improved areas under the curve (AUC60) at early enhancement. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Control design based on dead-zone and leakage adaptive laws for artificial swarm mechanical systems

NASA Astrophysics Data System (ADS)

Zhao, Xiaomin; Chen, Y. H.; Zhao, Han

2017-05-01

We consider the control design of artificial swarm systems with emphasis on four characteristics. First, the agent is made of mechanical components. As a result, the motion of each agent is subject to physical laws that govern mechanical systems. Second, both nonlinearity and uncertainty of the mechanical system are taken into consideration. Third, the ideal agent kinematic performance is treated as a desired d'Alembert constraint. This in turn suggests a creative way of embedding the constraint into the control design. Fourth, two types of adaptive robust control schemes are designed. They both contain leakage and dead-zone. However, one design suggests a trade-off between the amount of leakage and the size of dead-zone, in exchange for a simplified dead-zone structure.

Real-Time Robust Tracking for Motion Blur and Fast Motion via Correlation Filters

PubMed Central

Xu, Lingyun; Luo, Haibo; Hui, Bin; Chang, Zheng

2016-01-01

Visual tracking has extensive applications in intelligent monitoring and guidance systems. Among state-of-the-art tracking algorithms, Correlation Filter methods perform favorably in robustness, accuracy and speed. However, it also has shortcomings when dealing with pervasive target scale variation, motion blur and fast motion. In this paper we proposed a new real-time robust scheme based on Kernelized Correlation Filter (KCF) to significantly improve performance on motion blur and fast motion. By fusing KCF and STC trackers, our algorithm also solve the estimation of scale variation in many scenarios. We theoretically analyze the problem for CFs towards motions and utilize the point sharpness function of the target patch to evaluate the motion state of target. Then we set up an efficient scheme to handle the motion and scale variation without much time consuming. Our algorithm preserves the properties of KCF besides the ability to handle special scenarios. In the end extensive experimental results on benchmark of VOT datasets show our algorithm performs advantageously competed with the top-rank trackers. PMID:27618046

Rapid Motion Adaptation Reveals the Temporal Dynamics of Spatiotemporal Correlation between ON and OFF Pathways

PubMed Central

Oluk, Can; Pavan, Andrea; Kafaligonul, Hulusi

2016-01-01

At the early stages of visual processing, information is processed by two major thalamic pathways encoding brightness increments (ON) and decrements (OFF). Accumulating evidence suggests that these pathways interact and merge as early as in primary visual cortex. Using regular and reverse-phi motion in a rapid adaptation paradigm, we investigated the temporal dynamics of within and across pathway mechanisms for motion processing. When the adaptation duration was short (188 ms), reverse-phi and regular motion led to similar adaptation effects, suggesting that the information from the two pathways are combined efficiently at early-stages of motion processing. However, as the adaption duration was increased to 752 ms, reverse-phi and regular motion showed distinct adaptation effects depending on the test pattern used, either engaging spatiotemporal correlation between the same or opposite contrast polarities. Overall, these findings indicate that spatiotemporal correlation within and across ON-OFF pathways for motion processing can be selectively adapted, and support those models that integrate within and across pathway mechanisms for motion processing. PMID:27667401

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

On adaptive robustness approach to Anti-Jam signal processing

NASA Astrophysics Data System (ADS)

Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

Suppressive mechanisms in visual motion processing: From perception to intelligence.

PubMed

Tadin, Duje

2015-10-01

Perception operates on an immense amount of incoming information that greatly exceeds the brain's processing capacity. Because of this fundamental limitation, the ability to suppress irrelevant information is a key determinant of perceptual efficiency. Here, I will review a series of studies investigating suppressive mechanisms in visual motion processing, namely perceptual suppression of large, background-like motions. These spatial suppression mechanisms are adaptive, operating only when sensory inputs are sufficiently robust to guarantee visibility. Converging correlational and causal evidence links these behavioral results with inhibitory center-surround mechanisms, namely those in cortical area MT. Spatial suppression is abnormally weak in several special populations, including the elderly and individuals with schizophrenia-a deficit that is evidenced by better-than-normal direction discriminations of large moving stimuli. Theoretical work shows that this abnormal weakening of spatial suppression should result in motion segregation deficits, but direct behavioral support of this hypothesis is lacking. Finally, I will argue that the ability to suppress information is a fundamental neural process that applies not only to perception but also to cognition in general. Supporting this argument, I will discuss recent research that shows individual differences in spatial suppression of motion signals strongly predict individual variations in IQ scores. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Psychophysical and neuroimaging responses to moving stimuli in a patient with the Riddoch phenomenon due to bilateral visual cortex lesions.

PubMed

Arcaro, Michael J; Thaler, Lore; Quinlan, Derek J; Monaco, Simona; Khan, Sarah; Valyear, Kenneth F; Goebel, Rainer; Dutton, Gordon N; Goodale, Melvyn A; Kastner, Sabine; Culham, Jody C

2018-05-09

Patients with injury to early visual cortex or its inputs can display the Riddoch phenomenon: preserved awareness for moving but not stationary stimuli. We provide a detailed case report of a patient with the Riddoch phenomenon, MC. MC has extensive bilateral lesions to occipitotemporal cortex that include most early visual cortex and complete blindness in visual field perimetry testing with static targets. Nevertheless, she shows a remarkably robust preserved ability to perceive motion, enabling her to navigate through cluttered environments and perform actions like catching moving balls. Comparisons of MC's structural magnetic resonance imaging (MRI) data to a probabilistic atlas based on controls reveals that MC's lesions encompass the posterior, lateral, and ventral early visual cortex bilaterally (V1, V2, V3A/B, LO1/2, TO1/2, hV4 and VO1 in both hemispheres) as well as more extensive damage to right parietal (inferior parietal lobule) and left ventral occipitotemporal cortex (VO1, PHC1/2). She shows some sparing of anterior occipital cortex, which may account for her ability to see moving targets beyond ~15 degrees eccentricity during perimetry. Most strikingly, functional and structural MRI revealed robust and reliable spared functionality of the middle temporal motion complex (MT+) bilaterally. Moreover, consistent with her preserved ability to discriminate motion direction in psychophysical testing, MC also shows direction-selective adaptation in MT+. A variety of tests did not enable us to discern whether input to MT+ was driven by her spared anterior occipital cortex or subcortical inputs. Nevertheless, MC shows rich motion perception despite profoundly impaired static and form vision, combined with clear preservation of activation in MT+, thus supporting the role of MT+ in the Riddoch phenomenon. Copyright © 2018 Elsevier Ltd. All rights reserved.

Robust output tracking control of a laboratory helicopter for automatic landing

NASA Astrophysics Data System (ADS)

Liu, Hao; Lu, Geng; Zhong, Yisheng

2014-11-01

In this paper, robust output tracking control problem of a laboratory helicopter for automatic landing in high seas is investigated. The motion of the helicopter is required to synchronise with that of an oscillating platform, e.g. the deck of a vessel subject to wave-induced motions. A robust linear time-invariant output feedback controller consisting of a nominal controller and a robust compensator is designed. The robust compensator is introduced to restrain the influences of parametric uncertainties, nonlinearities and external disturbances. It is shown that robust stability and robust tracking property can be achieved simultaneously. Experimental results on the laboratory helicopter for automatic landing demonstrate the effectiveness of the designed control approach.

Robustly stable adaptive control of a tandem of master-slave robotic manipulators with force reflection by using a multiestimation scheme.

PubMed

Ibeas, Asier; de la Sen, Manuel

2006-10-01

The problem of controlling a tandem of robotic manipulators composing a teleoperation system with force reflection is addressed in this paper. The final objective of this paper is twofold: 1) to design a robust control law capable of ensuring closed-loop stability for robots with uncertainties and 2) to use the so-obtained control law to improve the tracking of each robot to its corresponding reference model in comparison with previously existing controllers when the slave is interacting with the obstacle. In this way, a multiestimation-based adaptive controller is proposed. Thus, the master robot is able to follow more accurately the constrained motion defined by the slave when interacting with an obstacle than when a single-estimation-based controller is used, improving the transparency property of the teleoperation scheme. The closed-loop stability is guaranteed if a minimum residence time, which might be updated online when unknown, between different controller parameterizations is respected. Furthermore, the analysis of the teleoperation and stability capabilities of the overall scheme is carried out. Finally, some simulation examples showing the working of the multiestimation scheme complete this paper.

Numerical Algorithms for Acoustic Integrals - The Devil is in the Details

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.

1996-01-01

The accurate prediction of the aeroacoustic field generated by aerospace vehicles or nonaerospace machinery is necessary for designers to control and reduce source noise. Powerful computational aeroacoustic methods, based on various acoustic analogies (primarily the Lighthill acoustic analogy) and Kirchhoff methods, have been developed for prediction of noise from complicated sources, such as rotating blades. Both methods ultimately predict the noise through a numerical evaluation of an integral formulation. In this paper, we consider three generic acoustic formulations and several numerical algorithms that have been used to compute the solutions to these formulations. Algorithms for retarded-time formulations are the most efficient and robust, but they are difficult to implement for supersonic-source motion. Collapsing-sphere and emission-surface formulations are good alternatives when supersonic-source motion is present, but the numerical implementations of these formulations are more computationally demanding. New algorithms - which utilize solution adaptation to provide a specified error level - are needed.

Sliding Mode Control of Real-Time PNU Vehicle Driving Simulator and Its Performance Evaluation

NASA Astrophysics Data System (ADS)

Lee, Min Cheol; Park, Min Kyu; Yoo, Wan Suk; Son, Kwon; Han, Myung Chul

This paper introduces an economical and effective full-scale driving simulator for study of human sensibility and development of new vehicle parts and its control. Real-time robust control to accurately reappear a various vehicle motion may be a difficult task because the motion platform is the nonlinear complex system. This study proposes the sliding mode controller with a perturbation compensator using observer-based fuzzy adaptive network (FAN). This control algorithm is designed to solve the chattering problem of a sliding mode control and to select the adequate fuzzy parameters of the perturbation compensator. For evaluating the trajectory control performance of the proposed approach, a tracking control of the developed simulator named PNUVDS is experimentally carried out. And then, the driving performance of the simulator is evaluated by using human perception and sensibility of some drivers in various driving conditions.

Catheter tracking via online learning for dynamic motion compensation in transcatheter aortic valve implantation.

PubMed

Wang, Peng; Zheng, Yefeng; John, Matthias; Comaniciu, Dorin

2012-01-01

Dynamic overlay of 3D models onto 2D X-ray images has important applications in image guided interventions. In this paper, we present a novel catheter tracking for motion compensation in the Transcatheter Aortic Valve Implantation (TAVI). To address such challenges as catheter shape and appearance changes, occlusions, and distractions from cluttered backgrounds, we present an adaptive linear discriminant learning method to build a measurement model online to distinguish catheters from background. An analytic solution is developed to effectively and efficiently update the discriminant model and to minimize the classification errors between the tracking object and backgrounds. The online learned discriminant model is further combined with an offline learned detector and robust template matching in a Bayesian tracking framework. Quantitative evaluations demonstrate the advantages of this method over current state-of-the-art tracking methods in tracking catheters for clinical applications.

Feasibility of online IMPT adaptation using fast, automatic and robust dose restoration

NASA Astrophysics Data System (ADS)

Bernatowicz, Kinga; Geets, Xavier; Barragan, Ana; Janssens, Guillaume; Souris, Kevin; Sterpin, Edmond

2018-04-01

Intensity-modulated proton therapy (IMPT) offers excellent dose conformity and healthy tissue sparing, but it can be substantially compromised in the presence of anatomical changes. A major dosimetric effect is caused by density changes, which alter the planned proton range in the patient. Three different methods, which automatically restore an IMPT plan dose on a daily CT image were implemented and compared: (1) simple dose restoration (DR) using optimization objectives of the initial plan, (2) voxel-wise dose restoration (vDR), and (3) isodose volume dose restoration (iDR). Dose restorations were calculated for three different clinical cases, selected to test different capabilities of the restoration methods: large range adaptation, complex dose distributions and robust re-optimization. All dose restorations were obtained in less than 5 min, without manual adjustments of the optimization settings. The evaluation of initial plans on repeated CTs showed large dose distortions, which were substantially reduced after restoration. In general, all dose restoration methods improved DVH-based scores in propagated target volumes and OARs. Analysis of local dose differences showed that, although all dose restorations performed similarly in high dose regions, iDR restored the initial dose with higher precision and accuracy in the whole patient anatomy. Median dose errors decreased from 13.55 Gy in distorted plan to 9.75 Gy (vDR), 6.2 Gy (DR) and 4.3 Gy (iDR). High quality dose restoration is essential to minimize or eventually by-pass the physician approval of the restored plan, as long as dose stability can be assumed. Motion (as well as setup and range uncertainties) can be taken into account by including robust optimization in the dose restoration. Restoring clinically-approved dose distribution on repeated CTs does not require new ROI segmentation and is compatible with an online adaptive workflow.

Investigation of whether in-room CT-based adaptive intracavitary brachytherapy for uterine cervical cancer is robust against interfractional location variations of organs and/or applicators.

PubMed

Oku, Yoshifumi; Arimura, Hidetaka; Nguyen, Tran Thi Thao; Hiraki, Yoshiyuki; Toyota, Masahiko; Saigo, Yasumasa; Yoshiura, Takashi; Hirata, Hideki

2016-11-01

This study investigates whether in-room computed tomography (CT)-based adaptive treatment planning (ATP) is robust against interfractional location variations, namely, interfractional organ motions and/or applicator displacements, in 3D intracavitary brachytherapy (ICBT) for uterine cervical cancer. In ATP, the radiation treatment plans, which have been designed based on planning CT images (and/or MR images) acquired just before the treatments, are adaptively applied for each fraction, taking into account the interfractional location variations. 2D and 3D plans with ATP for 14 patients were simulated for 56 fractions at a prescribed dose of 600 cGy per fraction. The standard deviations (SDs) of location displacements (interfractional location variations) of the target and organs at risk (OARs) with 3D ATP were significantly smaller than those with 2D ATP (P < 0.05). The homogeneity index (HI), conformity index (CI) and tumor control probability (TCP) in 3D ATP were significantly higher for high-risk clinical target volumes than those in 2D ATP. The SDs of the HI, CI, TCP, bladder and rectum D 2cc , and the bladder and rectum normal tissue complication probability (NTCP) in 3D ATP were significantly smaller than those in 2D ATP. The results of this study suggest that the interfractional location variations give smaller impacts on the planning evaluation indices in 3D ATP than in 2D ATP. Therefore, the 3D plans with ATP are expected to be robust against interfractional location variations in each treatment fraction. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Adaptation aftereffects in the perception of gender from biological motion.

PubMed

Troje, Nikolaus F; Sadr, Javid; Geyer, Henning; Nakayama, Ken

2006-07-28

Human visual perception is highly adaptive. While this has been known and studied for a long time in domains such as color vision, motion perception, or the processing of spatial frequency, a number of more recent studies have shown that adaptation and adaptation aftereffects also occur in high-level visual domains like shape perception and face recognition. Here, we present data that demonstrate a pronounced aftereffect in response to adaptation to the perceived gender of biological motion point-light walkers. A walker that is perceived to be ambiguous in gender under neutral adaptation appears to be male after adaptation with an exaggerated female walker and female after adaptation with an exaggerated male walker. We discuss this adaptation aftereffect as a tool to characterize and probe the mechanisms underlying biological motion perception.

Robust fitting for neuroreceptor mapping.

PubMed

Chang, Chung; Ogden, R Todd

2009-03-15

Among many other uses, positron emission tomography (PET) can be used in studies to estimate the density of a neuroreceptor at each location throughout the brain by measuring the concentration of a radiotracer over time and modeling its kinetics. There are a variety of kinetic models in common usage and these typically rely on nonlinear least-squares (LS) algorithms for parameter estimation. However, PET data often contain artifacts (such as uncorrected head motion) and so the assumptions on which the LS methods are based may be violated. Quantile regression (QR) provides a robust alternative to LS methods and has been used successfully in many applications. We consider fitting various kinetic models to PET data using QR and study the relative performance of the methods via simulation. A data adaptive method for choosing between LS and QR is proposed and the performance of this method is also studied.

Directional bias of illusory stream caused by relative motion adaptation.

PubMed

Tomimatsu, Erika; Ito, Hiroyuki

2016-07-01

Enigma is an op-art painting that elicits an illusion of rotational streaming motion. In the present study, we tested whether adaptation to various motion configurations that included relative motion components could be reflected in the directional bias of the illusory stream. First, participants viewed the center of a rotating Enigma stimulus for adaptation. There was no physical motion on the ring area. During the adaptation period, the illusory stream on the ring was mainly seen in the direction opposite to that of the physical rotation. After the physical rotation stopped, the illusory stream on the ring was mainly seen in the same direction as that of the preceding physical rotation. Moreover, adapting to strong relative motion induced a strong bias in the illusory motion direction in the subsequently presented static Enigma stimulus. The results suggest that relative motion detectors corresponding to the ring area may produce the illusory stream of Enigma. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

NASA Astrophysics Data System (ADS)

Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.

2011-02-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.

Robust adaptive vibration control of a flexible structure.

PubMed

Khoshnood, A M; Moradi, H M

2014-07-01

Different types of L1 adaptive control systems show that using robust theories with adaptive control approaches has produced high performance controllers. In this study, a model reference adaptive control scheme considering robust theories is used to propose a practical control system for vibration suppression of a flexible launch vehicle (FLV). In this method, control input of the system is shaped from the dynamic model of the vehicle and components of the control input are adaptively constructed by estimating the undesirable vibration frequencies. Robust stability of the adaptive vibration control system is guaranteed by using the L1 small gain theorem. Simulation results of the robust adaptive vibration control strategy confirm that the effects of vibration on the vehicle performance considerably decrease without the loss of the phase margin of the system. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Robust Parallel Motion Estimation and Mapping with Stereo Cameras in Underground Infrastructure

NASA Astrophysics Data System (ADS)

Liu, Chun; Li, Zhengning; Zhou, Yuan

2016-06-01

Presently, we developed a novel robust motion estimation method for localization and mapping in underground infrastructure using a pre-calibrated rigid stereo camera rig. Localization and mapping in underground infrastructure is important to safety. Yet it's also nontrivial since most underground infrastructures have poor lighting condition and featureless structure. Overcoming these difficulties, we discovered that parallel system is more efficient than the EKF-based SLAM approach since parallel system divides motion estimation and 3D mapping tasks into separate threads, eliminating data-association problem which is quite an issue in SLAM. Moreover, the motion estimation thread takes the advantage of state-of-art robust visual odometry algorithm which is highly functional under low illumination and provides accurate pose information. We designed and built an unmanned vehicle and used the vehicle to collect a dataset in an underground garage. The parallel system was evaluated by the actual dataset. Motion estimation results indicated a relative position error of 0.3%, and 3D mapping results showed a mean position error of 13cm. Off-line process reduced position error to 2cm. Performance evaluation by actual dataset showed that our system is capable of robust motion estimation and accurate 3D mapping in poor illumination and featureless underground environment.

Equivalent background speed in recovery from motion adaptation.

PubMed

Simpson, W A; Newman, A; Aasland, W

1997-01-01

We measured, in the same observers, (1) the detectability, d, of a small rotational jump following adaptation to rotational motion and (2) the detectability of the same jump when superimposed on one of several background rotation speeds. Following 90 s of motion adaptation the detectability of the jump was impaired, and sensitivity slowly recovered over the course of 60 s. The detectability of the jump was also impaired by the background speed in a way consistent with a quadratic form of Weber's law. We propose that motion adaptation impairs the detectability of the small jump because it is as if an equivalent background speed has been superimposed on the display. We measured the equivalent background by finding the real background speed that produced the same d' at each instant in the recovery from motion adaptation. The equivalent background started at approximately one to two thirds the speed of the adapting motion, declined rapidly, rose to a small peak at 30 s, then disappeared by 60 s. Since the equivalent background speed corresponds to the speed of the motion aftereffect, we have measured the time course of the motion aftereffect with objective psychophysics.

The tactile motion aftereffect suggests an intensive code for speed in neurons sensitive to both speed and direction of motion

PubMed Central

Birznieks, I.; Vickery, R. M.; Holcombe, A. O.; Seizova-Cajic, T.

2016-01-01

Neurophysiological studies in primates have found that direction-sensitive neurons in the primary somatosensory cortex (SI) generally increase their response rate with increasing speed of object motion across the skin and show little evidence of speed tuning. We employed psychophysics to determine whether human perception of motion direction could be explained by features of such neurons and whether evidence can be found for a speed-tuned process. After adaptation to motion across the skin, a subsequently presented dynamic test stimulus yields an impression of motion in the opposite direction. We measured the strength of this tactile motion aftereffect (tMAE) induced with different combinations of adapting and test speeds. Distal-to-proximal or proximal-to-distal adapting motion was applied to participants' index fingers using a tactile array, after which participants reported the perceived direction of a bidirectional test stimulus. An intensive code for speed, like that observed in SI neurons, predicts greater adaptation (and a stronger tMAE) the faster the adapting speed, regardless of the test speed. In contrast, speed tuning of direction-sensitive neurons predicts the greatest tMAE when the adapting and test stimuli have matching speeds. We found that the strength of the tMAE increased monotonically with adapting speed, regardless of the test speed, showing no evidence of speed tuning. Our data are consistent with neurophysiological findings that suggest an intensive code for speed along the motion processing pathways comprising neurons sensitive both to speed and direction of motion. PMID:26823511

SU-E-T-07: 4DCT Robust Optimization for Esophageal Cancer Using Intensity Modulated Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, L; Department of Industrial Engineering, University of Houston, Houston, TX; Yu, J

2015-06-15

Purpose: To develop a 4DCT robust optimization method to reduce the dosimetric impact from respiratory motion in intensity modulated proton therapy (IMPT) for esophageal cancer. Methods: Four esophageal cancer patients were selected for this study. The different phases of CT from a set of 4DCT were incorporated into the worst-case dose distribution robust optimization algorithm. 4DCT robust treatment plans were designed and compared with the conventional non-robust plans. Result doses were calculated on the average and maximum inhale/exhale phases of 4DCT. Dose volume histogram (DVH) band graphic and ΔD95%, ΔD98%, ΔD5%, ΔD2% of CTV between different phases were used tomore » evaluate the robustness of the plans. Results: Compare to the IMPT plans optimized using conventional methods, the 4DCT robust IMPT plans can achieve the same quality in nominal cases, while yield a better robustness to breathing motion. The mean ΔD95%, ΔD98%, ΔD5% and ΔD2% of CTV are 6%, 3.2%, 0.9% and 1% for the robustly optimized plans vs. 16.2%, 11.8%, 1.6% and 3.3% from the conventional non-robust plans. Conclusion: A 4DCT robust optimization method was proposed for esophageal cancer using IMPT. We demonstrate that the 4DCT robust optimization can mitigate the dose deviation caused by the diaphragm motion.« less

The effects of SENSE on PROPELLER imaging.

PubMed

Chang, Yuchou; Pipe, James G; Karis, John P; Gibbs, Wende N; Zwart, Nicholas R; Schär, Michael

2015-12-01

To study how sensitivity encoding (SENSE) impacts periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) image quality, including signal-to-noise ratio (SNR), robustness to motion, precision of motion estimation, and image quality. Five volunteers were imaged by three sets of scans. A rapid method for generating the g-factor map was proposed and validated via Monte Carlo simulations. Sensitivity maps were extrapolated to increase the area over which SENSE can be performed and therefore enhance the robustness to head motion. The precision of motion estimation of PROPELLER blades that are unfolded with these sensitivity maps was investigated. An interleaved R-factor PROPELLER sequence was used to acquire data with similar amounts of motion with and without SENSE acceleration. Two neuroradiologists independently and blindly compared 214 image pairs. The proposed method of g-factor calculation was similar to that provided by the Monte Carlo methods. Extrapolation and rotation of the sensitivity maps allowed for continued robustness of SENSE unfolding in the presence of motion. SENSE-widened blades improved the precision of rotation and translation estimation. PROPELLER images with a SENSE factor of 3 outperformed the traditional PROPELLER images when reconstructing the same number of blades. SENSE not only accelerates PROPELLER but can also improve robustness and precision of head motion correction, which improves overall image quality even when SNR is lost due to acceleration. The reduction of SNR, as a penalty of acceleration, is characterized by the proposed g-factor method. © 2014 Wiley Periodicals, Inc.

Design of sliding-mode observer for a class of uncertain neutral stochastic systems

NASA Astrophysics Data System (ADS)

Liu, Zhen; Zhao, Lin; Zhu, Quanmin; Gao, Cunchen

2017-05-01

The problem of robust ? control for a class of uncertain neutral stochastic systems (NSS) is investigated by utilising the sliding-mode observer (SMO) technique. This paper presents a novel observer and integral-type sliding-surface design, based on which a new sufficient condition guaranteeing the resultant sliding-mode dynamics (SMDs) to be mean-square exponentially stable with a prescribed level of ? performance is derived. Then, an adaptive reaching motion controller is synthesised to lead the system to the predesigned sliding surface in finite-time almost surely. Finally, two illustrative examples are exhibited to verify the validity and superiority of the developed scheme.

Global versus local adaptation in fly motion-sensitive neurons

PubMed Central

Neri, Peter; Laughlin, Simon B

2005-01-01

Flies, like humans, experience a well-known consequence of adaptation to visual motion, the waterfall illusion. Direction-selective neurons in the fly lobula plate permit a detailed analysis of the mechanisms responsible for motion adaptation and their function. Most of these neurons are spatially non-opponent, they sum responses to motion in the preferred direction across their entire receptive field, and adaptation depresses responses by subtraction and by reducing contrast gain. When we adapted a small area of the receptive field to motion in its anti-preferred direction, we discovered that directional gain at unadapted regions was enhanced. This novel phenomenon shows that neuronal responses to the direction of stimulation in one area of the receptive field are dynamically adjusted to the history of stimulation both within and outside that area. PMID:16191636

Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-navigator.

PubMed

Jiang, Wenwen; Ong, Frank; Johnson, Kevin M; Nagle, Scott K; Hope, Thomas A; Lustig, Michael; Larson, Peder E Z

2018-06-01

To achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data. Five-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states. Respiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients. An optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Adaptive learning compressive tracking based on Markov location prediction

NASA Astrophysics Data System (ADS)

Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

2017-03-01

Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

Analyzing the effects of human-aware motion planning on close-proximity human-robot collaboration.

PubMed

Lasota, Przemyslaw A; Shah, Julie A

2015-02-01

The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort. The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation. The lack of true human-in-the-loop evaluation has made it impossible to determine whether such adaptation would lead to efficient and satisfying human-robot interaction. We conducted an experiment in which participants worked with a robot to perform a collaborative task. Participants worked with an adaptive robot incorporating human-aware motion planning and with a baseline robot using shortest-path motions. Team fluency was evaluated through a set of quantitative metrics, and human satisfaction and perceived safety and comfort were evaluated through questionnaires. When working with the adaptive robot, participants completed the task 5.57% faster, with 19.9% more concurrent motion, 2.96% less human idle time, 17.3% less robot idle time, and a 15.1% greater separation distance. Questionnaire responses indicated that participants felt safer and more comfortable when working with an adaptive robot and were more satisfied with it as a teammate than with the standard robot. People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human-robot team fluency and human worker satisfaction. Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human-robot collaboration.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

PubMed

Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

2016-04-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control

PubMed Central

Adewuyi, Adenike A.; Hargrove, Levi J.; Kuiken, Todd A.

2015-01-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for partial-hand applications. PMID:25955989

Limited Impact of Setup and Range Uncertainties, Breathing Motion, and Interplay Effects in Robustly Optimized Intensity Modulated Proton Therapy for Stage III Non-small Cell Lung Cancer.

PubMed

Inoue, Tatsuya; Widder, Joachim; van Dijk, Lisanne V; Takegawa, Hideki; Koizumi, Masahiko; Takashina, Masaaki; Usui, Keisuke; Kurokawa, Chie; Sugimoto, Satoru; Saito, Anneyuko I; Sasai, Keisuke; Van't Veld, Aart A; Langendijk, Johannes A; Korevaar, Erik W

2016-11-01

To investigate the impact of setup and range uncertainties, breathing motion, and interplay effects using scanning pencil beams in robustly optimized intensity modulated proton therapy (IMPT) for stage III non-small cell lung cancer (NSCLC). Three-field IMPT plans were created using a minimax robust optimization technique for 10 NSCLC patients. The plans accounted for 5- or 7-mm setup errors with ±3% range uncertainties. The robustness of the IMPT nominal plans was evaluated considering (1) isotropic 5-mm setup errors with ±3% range uncertainties; (2) breathing motion; (3) interplay effects; and (4) a combination of items 1 and 2. The plans were calculated using 4-dimensional and average intensity projection computed tomography images. The target coverage (TC, volume receiving 95% of prescribed dose) and homogeneity index (D2 - D98, where D2 and D98 are the least doses received by 2% and 98% of the volume) for the internal clinical target volume, and dose indexes for lung, esophagus, heart and spinal cord were compared with that of clinical volumetric modulated arc therapy plans. The TC and homogeneity index for all plans were within clinical limits when considering the breathing motion and interplay effects independently. The setup and range uncertainties had a larger effect when considering their combined effect. The TC decreased to <98% (clinical threshold) in 3 of 10 patients for robust 5-mm evaluations. However, the TC remained >98% for robust 7-mm evaluations for all patients. The organ at risk dose parameters did not significantly vary between the respective robust 5-mm and robust 7-mm evaluations for the 4 error types. Compared with the volumetric modulated arc therapy plans, the IMPT plans showed better target homogeneity and mean lung and heart dose parameters reduced by about 40% and 60%, respectively. In robustly optimized IMPT for stage III NSCLC, the setup and range uncertainties, breathing motion, and interplay effects have limited impact on target coverage, dose homogeneity, and organ-at-risk dose parameters. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of Crowding and Attention on High-Levels of Motion Processing and Motion Adaptation

PubMed Central

Pavan, Andrea; Greenlee, Mark W.

2015-01-01

The motion after-effect (MAE) persists in crowding conditions, i.e., when the adaptation direction cannot be reliably perceived. The MAE originating from complex moving patterns spreads into non-adapted sectors of a multi-sector adapting display (i.e., phantom MAE). In the present study we used global rotating patterns to measure the strength of the conventional and phantom MAEs in crowded and non-crowded conditions, and when attention was directed to the adapting stimulus and when it was diverted away from the adapting stimulus. The results show that: (i) the phantom MAE is weaker than the conventional MAE, for both non-crowded and crowded conditions, and when attention was focused on the adapting stimulus and when it was diverted from it, (ii) conventional and phantom MAEs in the crowded condition are weaker than in the non-crowded condition. Analysis conducted to assess the effect of crowding on high-level of motion adaptation suggests that crowding is likely to affect the awareness of the adapting stimulus rather than degrading its sensory representation, (iii) for high-level of motion processing the attentional manipulation does not affect the strength of either conventional or phantom MAEs, neither in the non-crowded nor in the crowded conditions. These results suggest that high-level MAEs do not depend on attention and that at high-level of motion adaptation the effects of crowding are not modulated by attention. PMID:25615577

Vehicle lateral motion regulation under unreliable communication links based on robust H∞ output-feedback control schema

NASA Astrophysics Data System (ADS)

Li, Cong; Jing, Hui; Wang, Rongrong; Chen, Nan

2018-05-01

This paper presents a robust control schema for vehicle lateral motion regulation under unreliable communication links via controller area network (CAN). The communication links between the system plant and the controller are assumed to be imperfect and therefore the data packet dropouts occur frequently. The paper takes the form of parallel distributed compensation and treats the dropouts as random binary numbers that form Bernoulli distribution. Both of the tire cornering stiffness uncertainty and external disturbances are considered to enhance the robustness of the controller. In addition, a robust H∞ static output-feedback control approach is proposed to realize the lateral motion control with relative low cost sensors. The stochastic stability of the closed-loop system and conservation of the guaranteed H∞ performance are investigated. Simulation results based on CarSim platform using a high-fidelity and full-car model verify the effectiveness of the proposed control approach.

Attention and apparent motion.

PubMed

Horowitz, T; Treisman, A

1994-01-01

Two dissociations between short- and long-range motion in visual search are reported. Previous research has shown parallel processing for short-range motion and apparently serial processing for long-range motion. This finding has been replicated and it has also been found that search for short-range targets can be impaired both by using bicontrast stimuli, and by prior adaptation to the target direction of motion. Neither factor impaired search in long-range motion displays. Adaptation actually facilitated search with long-range displays, which is attributed to response-level effects. A feature-integration account of apparent motion is proposed. In this theory, short-range motion depends on specialized motion feature detectors operating in parallel across the display, but subject to selective adaptation, whereas attention is needed to link successive elements when they appear at greater separations, or across opposite contrasts.

Local motion adaptation enhances the representation of spatial structure at EMD arrays

PubMed Central

Lindemann, Jens P.; Egelhaaf, Martin

2017-01-01

Neuronal representation and extraction of spatial information are essential for behavioral control. For flying insects, a plausible way to gain spatial information is to exploit distance-dependent optic flow that is generated during translational self-motion. Optic flow is computed by arrays of local motion detectors retinotopically arranged in the second neuropile layer of the insect visual system. These motion detectors have adaptive response characteristics, i.e. their responses to motion with a constant or only slowly changing velocity decrease, while their sensitivity to rapid velocity changes is maintained or even increases. We analyzed by a modeling approach how motion adaptation affects signal representation at the output of arrays of motion detectors during simulated flight in artificial and natural 3D environments. We focused on translational flight, because spatial information is only contained in the optic flow induced by translational locomotion. Indeed, flies, bees and other insects segregate their flight into relatively long intersaccadic translational flight sections interspersed with brief and rapid saccadic turns, presumably to maximize periods of translation (80% of the flight). With a novel adaptive model of the insect visual motion pathway we could show that the motion detector responses to background structures of cluttered environments are largely attenuated as a consequence of motion adaptation, while responses to foreground objects stay constant or even increase. This conclusion even holds under the dynamic flight conditions of insects. PMID:29281631

Robust Optimal Adaptive Control Method with Large Adaptive Gain

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Analyzing the Effects of Human-Aware Motion Planning on Close-Proximity Human–Robot Collaboration

PubMed Central

Shah, Julie A.

2015-01-01

Objective: The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort. Background: The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation. The lack of true human-in-the-loop evaluation has made it impossible to determine whether such adaptation would lead to efficient and satisfying human–robot interaction. Method: We conducted an experiment in which participants worked with a robot to perform a collaborative task. Participants worked with an adaptive robot incorporating human-aware motion planning and with a baseline robot using shortest-path motions. Team fluency was evaluated through a set of quantitative metrics, and human satisfaction and perceived safety and comfort were evaluated through questionnaires. Results: When working with the adaptive robot, participants completed the task 5.57% faster, with 19.9% more concurrent motion, 2.96% less human idle time, 17.3% less robot idle time, and a 15.1% greater separation distance. Questionnaire responses indicated that participants felt safer and more comfortable when working with an adaptive robot and were more satisfied with it as a teammate than with the standard robot. Conclusion: People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human–robot team fluency and human worker satisfaction. Application: Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human–robot collaboration. PMID:25790568

Model reference tracking control of an aircraft: a robust adaptive approach

NASA Astrophysics Data System (ADS)

Tanyer, Ilker; Tatlicioglu, Enver; Zergeroglu, Erkan

2017-05-01

This work presents the design and the corresponding analysis of a nonlinear robust adaptive controller for model reference tracking of an aircraft that has parametric uncertainties in its system matrices and additive state- and/or time-dependent nonlinear disturbance-like terms in its dynamics. Specifically, robust integral of the sign of the error feedback term and an adaptive term is fused with a proportional integral controller. Lyapunov-based stability analysis techniques are utilised to prove global asymptotic convergence of the output tracking error. Extensive numerical simulations are presented to illustrate the performance of the proposed robust adaptive controller.

Low dose tomographic fluoroscopy: 4D intervention guidance with running prior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flach, Barbara; Kuntz, Jan; Brehm, Marcus

Purpose: Today's standard imaging technique in interventional radiology is the single- or biplane x-ray fluoroscopy which delivers 2D projection images as a function of time (2D+T). This state-of-the-art technology, however, suffers from its projective nature and is limited by the superposition of the patient's anatomy. Temporally resolved tomographic volumes (3D+T) would significantly improve the visualization of complex structures. A continuous tomographic data acquisition, if carried out with today's technology, would yield an excessive patient dose. Recently the authors proposed a method that enables tomographic fluoroscopy at the same dose level as projective fluoroscopy which means that if scanning time ofmore » an intervention guided by projective fluoroscopy is the same as that of an intervention guided by tomographic fluoroscopy, almost the same dose is administered to the patient. The purpose of this work is to extend authors' previous work and allow for patient motion during the intervention.Methods: The authors propose the running prior technique for adaptation of a prior image. This adaptation is realized by a combination of registration and projection replacement. In a first step the prior is deformed to the current position via affine and deformable registration. Then the information from outdated projections is replaced by newly acquired projections using forward and backprojection steps. The thus adapted volume is the running prior. The proposed method is validated by simulated as well as measured data. To investigate motion during intervention a moving head phantom was simulated. Real in vivo data of a pig are acquired by a prototype CT system consisting of a flat detector and a continuously rotating clinical gantry.Results: With the running prior technique it is possible to correct for motion without additional dose. For an application in intervention guidance both steps of the running prior technique, registration and replacement, are necessary. Reconstructed volumes based on the running prior show high image quality without introducing new artifacts and the interventional materials are displayed at the correct position.Conclusions: The running prior improves the robustness of low dose 3D+T intervention guidance toward intended or unintended patient motion.« less

Adaptation of velocity encoding in synaptically coupled neurons in the fly visual system.

PubMed

Kalb, Julia; Egelhaaf, Martin; Kurtz, Rafael

2008-09-10

Although many adaptation-induced effects on neuronal response properties have been described, it is often unknown at what processing stages in the nervous system they are generated. We focused on fly visual motion-sensitive neurons to identify changes in response characteristics during prolonged visual motion stimulation. By simultaneous recordings of synaptically coupled neurons, we were able to directly compare adaptation-induced effects at two consecutive processing stages in the fly visual motion pathway. This allowed us to narrow the potential sites of adaptation effects within the visual system and to relate them to the properties of signal transfer between neurons. Motion adaptation was accompanied by a response reduction, which was somewhat stronger in postsynaptic than in presynaptic cells. We found that the linear representation of motion velocity degrades during adaptation to a white-noise velocity-modulated stimulus. This effect is caused by an increasingly nonlinear velocity representation rather than by an increase of noise and is similarly strong in presynaptic and postsynaptic neurons. In accordance with this similarity, the dynamics and the reliability of interneuronal signal transfer remained nearly constant. Thus, adaptation is mainly based on processes located in the presynaptic neuron or in more peripheral processing stages. In contrast, changes of transfer properties at the analyzed synapse or in postsynaptic spike generation contribute little to changes in velocity coding during motion adaptation.

Real-time tumor motion estimation using respiratory surrogate via memory-based learning

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Berbeco, Ross I.; Xing, Lei

2012-08-01

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ∼50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.

The continuous Wagon Wheel Illusion depends on, but is not identical to neuronal adaptation.

PubMed

VanRullen, Rufin

2007-07-01

The occurrence of perceived reversed motion while observers view a continuous, periodically moving stimulus (a bistable phenomenon coined the "continuous Wagon Wheel Illusion" or "c-WWI") has been taken as evidence that some aspects of motion perception rely on discrete sampling of visual information. Alternative accounts rely on the possibility of a motion aftereffect that may become visible even while the adapting stimulus is present. Here I show that motion adaptation might be necessary, but is not sufficient to explain the illusion. When local adaptation is prevented by slowly drifting the moving wheel across the retina, the c-WWI illusion tends to decrease, as do other bistable percepts (e.g. binocular rivalry). However, the strength of the c-WWI and that of adaptation (as measured by either the static or flicker motion aftereffects) are not directly related: although the c-WWI decreases with increasing eccentricity, the aftereffects actually intensify concurrently. A similar dissociation can be induced by manipulating stimulus contrast. This indicates that the c-WWI may be enabled by, but is not equivalent to, local motion adaptation - and that other factors such as discrete sampling may be involved in its generation.

Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data

NASA Astrophysics Data System (ADS)

Ameur, Mourad; Derras, Boumédiène; Zendagui, Djawed

2018-03-01

Adaptive neuro-fuzzy inference systems (ANFIS) are used here to obtain the robust ground motion prediction model (GMPM). Avoiding a priori functional form, ANFIS provides fully data-driven predictive models. A large subset of the NGA-West2 database is used, including 2335 records from 580 sites and 137 earthquakes. Only shallow earthquakes and recordings corresponding to stations with measured V s30 properties are selected. Three basics input parameters are chosen: the moment magnitude ( Mw), the Joyner-Boore distance ( R JB) and V s30. ANFIS model output is the peak ground acceleration (PGA), peak ground velocity (PGV) and 5% damped pseudo-spectral acceleration (PSA) at periods from 0.01 to 4 s. A procedure similar to the random-effects approach is developed to provide between- and within-event standard deviations. The total standard deviation (SD) varies between [0.303 and 0.360] (log10 units) depending on the period. The ground motion predictions resulting from such simple three explanatory variables ANFIS models are shown to be comparable to the most recent NGA results (e.g., Boore et al., in Earthquake Spectra 30:1057-1085, 2014; Derras et al., in Earthquake Spectra 32:2027-2056, 2016). The main advantage of ANFIS compared to artificial neuronal network (ANN) is its simple and one-off topology: five layers. Our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude and amplification on soft soils. The ability to implement ANFIS model using an analytic equation and Excel is demonstrated.

Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data

NASA Astrophysics Data System (ADS)

Ameur, Mourad; Derras, Boumédiène; Zendagui, Djawed

2017-12-01

Adaptive neuro-fuzzy inference systems (ANFIS) are used here to obtain the robust ground motion prediction model (GMPM). Avoiding a priori functional form, ANFIS provides fully data-driven predictive models. A large subset of the NGA-West2 database is used, including 2335 records from 580 sites and 137 earthquakes. Only shallow earthquakes and recordings corresponding to stations with measured V s30 properties are selected. Three basics input parameters are chosen: the moment magnitude (Mw), the Joyner-Boore distance (R JB) and V s30. ANFIS model output is the peak ground acceleration (PGA), peak ground velocity (PGV) and 5% damped pseudo-spectral acceleration (PSA) at periods from 0.01 to 4 s. A procedure similar to the random-effects approach is developed to provide between- and within-event standard deviations. The total standard deviation (SD) varies between [0.303 and 0.360] (log10 units) depending on the period. The ground motion predictions resulting from such simple three explanatory variables ANFIS models are shown to be comparable to the most recent NGA results (e.g., Boore et al., in Earthquake Spectra 30:1057-1085, 2014; Derras et al., in Earthquake Spectra 32:2027-2056, 2016). The main advantage of ANFIS compared to artificial neuronal network (ANN) is its simple and one-off topology: five layers. Our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude and amplification on soft soils. The ability to implement ANFIS model using an analytic equation and Excel is demonstrated.

Single neural adaptive controller and neural network identifier based on PSO algorithm for spherical actuators with 3D magnet array

NASA Astrophysics Data System (ADS)

Yan, Liang; Zhang, Lu; Zhu, Bo; Zhang, Jingying; Jiao, Zongxia

2017-10-01

Permanent magnet spherical actuator (PMSA) is a multi-variable featured and inter-axis coupled nonlinear system, which unavoidably compromises its motion control implementation. Uncertainties such as external load and friction torque of ball bearing and manufacturing errors also influence motion performance significantly. Therefore, the objective of this paper is to propose a controller based on a single neural adaptive (SNA) algorithm and a neural network (NN) identifier optimized with a particle swarm optimization (PSO) algorithm to improve the motion stability of PMSA with three-dimensional magnet arrays. The dynamic model and computed torque model are formulated for the spherical actuator, and a dynamic decoupling control algorithm is developed. By utilizing the global-optimization property of the PSO algorithm, the NN identifier is trained to avoid locally optimal solution and achieve high-precision compensations to uncertainties. The employment of the SNA controller helps to reduce the effect of compensation errors and convert the system to a stable one, even if there is difference between the compensations and uncertainties due to external disturbances. A simulation model is established, and experiments are conducted on the research prototype to validate the proposed control algorithm. The amplitude of the parameter perturbation is set to 5%, 10%, and 15%, respectively. The strong robustness of the proposed hybrid algorithm is validated by the abundant simulation data. It shows that the proposed algorithm can effectively compensate the influence of uncertainties and eliminate the effect of inter-axis couplings of the spherical actuator.

Structured illumination 3D microscopy using adaptive lenses and multimode fibers

NASA Astrophysics Data System (ADS)

Czarske, Jürgen; Philipp, Katrin; Koukourakis, Nektarios

2017-06-01

Microscopic techniques with high spatial and temporal resolution are required for in vivo studying biological cells and tissues. Adaptive lenses exhibit strong potential for fast motion-free axial scanning. However, they also lead to a degradation of the achievable resolution because of aberrations. This hurdle can be overcome by digital optical technologies. We present a novel High-and-Low-frequency (HiLo) 3D-microscope using structured illumination and an adaptive lens. Uniform illumination is used to obtain optical sectioning for the high-frequency (Hi) components of the image, and nonuniform illumination is needed to obtain optical sectioning for the low-frequency (Lo) components of the image. Nonuniform illumination is provided by a multimode fiber. It ensures robustness against optical aberrations of the adaptive lens. The depth-of-field of our microscope can be adjusted a-posteriori by computational optics. It enables to create flexible scans, which compensate for irregular axial measurement positions. The adaptive HiLo 3D-microscope provides an axial scanning range of 1 mm with an axial resolution of about 4 microns and sub-micron lateral resolution over the full scanning range. In result, volumetric measurements with high temporal and spatial resolution are provided. Demonstration measurements of zebrafish embryos with reporter gene-driven fluorescence in the thyroid gland are presented.

Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

PubMed Central

Qian, Jiuchao; Pei, Ling; Ma, Jiabin; Ying, Rendong; Liu, Peilin

2015-01-01

The paper presents a hybrid indoor positioning solution based on a pedestrian dead reckoning (PDR) approach using built-in sensors on a smartphone. To address the challenges of flexible and complex contexts of carrying a phone while walking, a robust step detection algorithm based on motion-awareness has been proposed. Given the fact that step length is influenced by different motion states, an adaptive step length estimation algorithm based on motion recognition is developed. Heading estimation is carried out by an attitude acquisition algorithm, which contains a two-phase filter to mitigate the distortion of magnetic anomalies. In order to estimate the heading for an unconstrained smartphone, principal component analysis (PCA) of acceleration is applied to determine the offset between the orientation of smartphone and the actual heading of a pedestrian. Moreover, a particle filter with vector graph assisted particle weighting is introduced to correct the deviation in step length and heading estimation. Extensive field tests, including four contexts of carrying a phone, have been conducted in an office building to verify the performance of the proposed algorithm. Test results show that the proposed algorithm can achieve sub-meter mean error in all contexts. PMID:25738763

On-Line Fringe Tracking and Prediction at IOTA

NASA Technical Reports Server (NTRS)

Wilson, Edward; Mah, Robert; Lau, Sonie (Technical Monitor)

1999-01-01

The Infrared/Optical Telescope Array (IOTA) is a multi-aperture Michelson interferometer located on Mt. Hopkins near Tucson, Arizona. To enable viewing of fainter targets, an on-line fringe tracking system is presently under development at NASA Ames Research Center. The system has been developed off-line using actual data from IOTA, and is presently undergoing on-line implementation at IOTA. The system has two parts: (1) a fringe tracking system that identifies the center of a fringe packet by fitting a parametric model to the data; and (2) a fringe packet motion prediction system that uses characteristics of past fringe packets to predict fringe packet motion. Combined, this information will be used to optimize on-line the scanning trajectory, resulting in improved visibility of faint targets. Fringe packet identification is highly accurate and robust (99% of the 4000 fringe packets were identified correctly, the remaining 1% were either out of the scan range or too noisy to be seen) and is performed in 30-90 milliseconds on a Pentium II-based computer. Fringe packet prediction, currently performed using an adaptive linear predictor, delivers a 10% improvement over the baseline of predicting no motion.

Phantom motion after effects--evidence of detectors for the analysis of optic flow.

PubMed

Snowden, R J; Milne, A B

1997-10-01

Electrophysiological recording from the extrastriate cortex of non-human primates has revealed neurons that have large receptive fields and are sensitive to various components of object or self movement, such as translations, rotations and expansion/contractions. If these mechanisms exist in human vision, they might be susceptible to adaptation that generates motion aftereffects (MAEs). Indeed, it might be possible to adapt the mechanism in one part of the visual field and reveal what we term a 'phantom MAE' in another part. The existence of phantom MAEs was probed by adapting to a pattern that contained motion in only two non-adjacent 'quarter' segments and then testing using patterns that had elements in only the other two segments. We also tested for the more conventional 'concrete' MAE by testing in the same two segments that had adapted. The strength of each MAE was quantified by measuring the percentage of dots that had to be moved in the opposite direction to the MAE in order to nullify it. Four experiments tested rotational motion, expansion/contraction motion, translational motion and a 'rotation' that consisted simply of the two segments that contained only translational motions of opposing direction. Compared to a baseline measurement where no adaptation took place, all subjects in all experiments exhibited both concrete and phantom MAEs, with the size of the latter approximately half that of the former. Adaptation to two segments that contained upward and downward motion induced the perception of leftward and rightward motion in another part of the visual field. This strongly suggests there are mechanisms in human vision that are sensitive to complex motions such as rotations.

Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm

PubMed Central

Svečko, Rajko

2014-01-01

This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749

Spot Weight Adaptation for Moving Target in Spot Scanning Proton Therapy.

PubMed

Morel, Paul; Wu, Xiaodong; Blin, Guillaume; Vialette, Stéphane; Flynn, Ryan; Hyer, Daniel; Wang, Dongxu

2015-01-01

This study describes a real-time spot weight adaptation method in spot-scanning proton therapy for moving target or moving patient, so that the resultant dose distribution closely matches the planned dose distribution. The method proposed in this study adapts the weight (MU) of the delivering pencil beam to that of the target spot; it will actually hit during patient/target motion. The target spot that a certain delivering pencil beam may hit relies on patient monitoring and/or motion modeling using four-dimensional (4D) CT. After the adapted delivery, the required total weight [Monitor Unit (MU)] for this target spot is then subtracted from the planned value. With continuous patient motion and continuous spot scanning, the planned doses to all target spots will eventually be all fulfilled. In a proof-of-principle test, a lung case was presented with realistic temporal and motion parameters; the resultant dose distribution using spot weight adaptation was compared to that without using this method. The impact of the real-time patient/target position tracking or prediction was also investigated. For moderate motion (i.e., mean amplitude 0.5 cm), D95% to the planning target volume (PTV) was only 81.5% of the prescription (RX) dose; with spot weight adaptation PTV D95% achieves 97.7% RX. For large motion amplitude (i.e., 1.5 cm), without spot weight adaptation PTV D95% is only 42.9% of RX; with spot weight adaptation, PTV D95% achieves 97.7% RX. Larger errors in patient/target position tracking or prediction led to worse final target coverage; an error of 3 mm or smaller in patient/target position tracking is preferred. The proposed spot weight adaptation method was able to deliver the planned dose distribution and maintain target coverage when patient motion was involved. The successful implementation of this method would rely on accurate monitoring or prediction of patient/target motion.

TU-AB-BRB-03: Coverage-Based Treatment Planning to Accommodate Organ Deformable Motions and Contouring Uncertainties for Prostate Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, H.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

TU-AB-BRB-02: Stochastic Programming Methods for Handling Uncertainty and Motion in IMRT Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unkelbach, J.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

Constructing binary black hole initial data with high mass ratios and spins

NASA Astrophysics Data System (ADS)

Ossokine, Serguei; Foucart, Francois; Pfeiffer, Harald; Szilagyi, Bela; Simulating Extreme Spacetimes Collaboration

2015-04-01

Binary black hole systems have now been successfully modelled in full numerical relativity by many groups. In order to explore high-mass-ratio (larger than 1:10), high-spin systems (above 0.9 of the maximal BH spin), we revisit the initial-data problem for binary black holes. The initial-data solver in the Spectral Einstein Code (SpEC) was not able to solve for such initial data reliably and robustly. I will present recent improvements to this solver, among them adaptive mesh refinement and control of motion of the center of mass of the binary, and will discuss the much larger region of parameter space this code can now address.

Adaptation without parameter change: Dynamic gain control in motion detection

PubMed Central

Borst, Alexander; Flanagin, Virginia L.; Sompolinsky, Haim

2005-01-01

Many sensory systems adapt their input-output relationship to changes in the statistics of the ambient stimulus. Such adaptive behavior has been measured in a motion detection sensitive neuron of the fly visual system, H1. The rapid adaptation of the velocity response gain has been interpreted as evidence of optimal matching of the H1 response to the dynamic range of the stimulus, thereby maximizing its information transmission. Here, we show that correlation-type motion detectors, which are commonly thought to underlie fly motion vision, intrinsically possess adaptive properties. Increasing the amplitude of the velocity fluctuations leads to a decrease of the effective gain and the time constant of the velocity response without any change in the parameters of these detectors. The seemingly complex property of this adaptation turns out to be a straightforward consequence of the multidimensionality of the stimulus and the nonlinear nature of the system. PMID:15833815

The Binding of Learning to Action in Motor Adaptation

PubMed Central

Gonzalez Castro, Luis Nicolas; Monsen, Craig Bryant; Smith, Maurice A.

2011-01-01

In motor tasks, errors between planned and actual movements generally result in adaptive changes which reduce the occurrence of similar errors in the future. It has commonly been assumed that the motor adaptation arising from an error occurring on a particular movement is specifically associated with the motion that was planned. Here we show that this is not the case. Instead, we demonstrate the binding of the adaptation arising from an error on a particular trial to the motion experienced on that same trial. The formation of this association means that future movements planned to resemble the motion experienced on a given trial benefit maximally from the adaptation arising from it. This reflects the idea that actual rather than planned motions are assigned ‘credit’ for motor errors because, in a computational sense, the maximal adaptive response would be associated with the condition credited with the error. We studied this process by examining the patterns of generalization associated with motor adaptation to novel dynamic environments during reaching arm movements in humans. We found that these patterns consistently matched those predicted by adaptation associated with the actual rather than the planned motion, with maximal generalization observed where actual motions were clustered. We followed up these findings by showing that a novel training procedure designed to leverage this newfound understanding of the binding of learning to action, can improve adaptation rates by greater than 50%. Our results provide a mechanistic framework for understanding the effects of partial assistance and error augmentation during neurologic rehabilitation, and they suggest ways to optimize their use. PMID:21731476

Enduring stereoscopic motion aftereffects induced by prolonged adaptation.

PubMed

Bowd, C; Rose, D; Phinney, R E; Patterson, R

1996-11-01

This study investigated the effects of prolonged adaptation on the recovery of the stereoscopic motion aftereffect (adaptation induced by moving binocular disparity information). The adapting and test stimuli were stereoscopic grating patterns created from disparity, embedded in dynamic random-dot stereograms. Motion aftereffects induced by luminance stimuli were included in the study for comparison. Adaptation duration was either 1, 2, 4, 8, 16, 32 or 64 min and the duration of the ensuing aftereffect was the variable of interest. The results showed that aftereffect duration was proportional to the square root of adaptation duration for both stereoscopic and luminance stimuli; on log-log axes, the relation between aftereffect duration and adaptation duration was a power law with the slope near 0.5 in both cases. For both kinds of stimuli, there was no sign of adaptation saturation even at the longest adaptation duration.

Limited Impact of Setup and Range Uncertainties, Breathing Motion, and Interplay Effects in Robustly Optimized Intensity Modulated Proton Therapy for Stage III Non-small Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inoue, Tatsuya; Widder, Joachim; Dijk, Lisanne V. van

2016-11-01

Purpose: To investigate the impact of setup and range uncertainties, breathing motion, and interplay effects using scanning pencil beams in robustly optimized intensity modulated proton therapy (IMPT) for stage III non-small cell lung cancer (NSCLC). Methods and Materials: Three-field IMPT plans were created using a minimax robust optimization technique for 10 NSCLC patients. The plans accounted for 5- or 7-mm setup errors with ±3% range uncertainties. The robustness of the IMPT nominal plans was evaluated considering (1) isotropic 5-mm setup errors with ±3% range uncertainties; (2) breathing motion; (3) interplay effects; and (4) a combination of items 1 and 2.more » The plans were calculated using 4-dimensional and average intensity projection computed tomography images. The target coverage (TC, volume receiving 95% of prescribed dose) and homogeneity index (D{sub 2} − D{sub 98}, where D{sub 2} and D{sub 98} are the least doses received by 2% and 98% of the volume) for the internal clinical target volume, and dose indexes for lung, esophagus, heart and spinal cord were compared with that of clinical volumetric modulated arc therapy plans. Results: The TC and homogeneity index for all plans were within clinical limits when considering the breathing motion and interplay effects independently. The setup and range uncertainties had a larger effect when considering their combined effect. The TC decreased to <98% (clinical threshold) in 3 of 10 patients for robust 5-mm evaluations. However, the TC remained >98% for robust 7-mm evaluations for all patients. The organ at risk dose parameters did not significantly vary between the respective robust 5-mm and robust 7-mm evaluations for the 4 error types. Compared with the volumetric modulated arc therapy plans, the IMPT plans showed better target homogeneity and mean lung and heart dose parameters reduced by about 40% and 60%, respectively. Conclusions: In robustly optimized IMPT for stage III NSCLC, the setup and range uncertainties, breathing motion, and interplay effects have limited impact on target coverage, dose homogeneity, and organ-at-risk dose parameters.« less

Energy capture and storage in asymmetrically multistable modular structures inspired by skeletal muscle

NASA Astrophysics Data System (ADS)

Kidambi, Narayanan; Harne, Ryan L.; Wang, K. W.

2017-08-01

The remarkable versatility and adaptability of skeletal muscle that arises from the assembly of its nanoscale cross-bridges into micro-scale assemblies known as sarcomeres provides great inspiration for the development of advanced adaptive structures and material systems. Motivated by the capability of cross-bridges to capture elastic strain energy to improve the energetic efficiency of sudden movements and repeated motions, and by models of cross-bridge power stroke motions and sarcomere contractile behaviors that incorporate asymmetric, bistable potential energy landscapes, this research develops and studies modular mechanical structures that trap and store energy in higher-energy configurations. Modules exhibiting tailorable asymmetric bistability are first designed and fabricated, revealing how geometric parameters influence the asymmetry of the resulting double-well energy landscapes. These experimentally-observed characteristics are then investigated with numerical and analytical methods to characterize the dynamics of asymmetrically bistable modules. The assembly of such modules into greater structures generates complex, multi-well energy landscapes with stable system configurations exhibiting different quantities of stored elastic potential energy. Dynamic analyses illustrate the ability of these structures to capture a portion of the initial kinetic energy due to impulsive excitations as recoverable strain potential energy, and reveal how stiffness parameters, damping, and the presence of thermal noise in micro- and nano-scale applications influence energy capture behaviors. The insights gained could foster the development of advanced structural/material systems inspired by skeletal muscle, including actuators that effectively capture, store, and release energy, as well as adaptive, robust, and reusable armors and protective devices.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

Robust object tracking techniques for vision-based 3D motion analysis applications

NASA Astrophysics Data System (ADS)

Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

2016-04-01

Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

Space adaptation syndrome: multiple etiological factors and individual differences

NASA Technical Reports Server (NTRS)

Lackner, J. R.; DiZio, P.

1991-01-01

Space motion sickness is a significant operational concern in the American and Soviet space programs. Nearly 70% of all astronauts and cosmonauts are affected to some degree during their first several days of flight. It is now beginning to appear that space motion sickness like terrestrial motion sickness is the consequence of multiple etiological factors. As we come to understand basic mechanisms of spatial orientation and sensory-motor adaptation we can begin to predict etiological factors in different motion environments. Individuals vary greatly in the extent to which they are susceptible to these different factors. However, individuals seem to be relatively self-consistent in terms of their rates of adaptation to provocative stimulation and their retention of adaptation. Attempts to relate susceptibility to motion sickness during the microgravity phases of parabolic flight maneuvers to vestibular function under 1G and 0G test conditions are described.

Motion-artifact-robust, polarization-resolved second-harmonic-generation microscopy based on rapid polarization switching with electro-optic Pockells cell and its application to in vivo visualization of collagen fiber orientation in human facial skin

PubMed Central

Tanaka, Yuji; Hase, Eiji; Fukushima, Shuichiro; Ogura, Yuki; Yamashita, Toyonobu; Hirao, Tetsuji; Araki, Tsutomu; Yasui, Takeshi

2014-01-01

Polarization-resolved second-harmonic-generation (PR-SHG) microscopy is a powerful tool for investigating collagen fiber orientation quantitatively with low invasiveness. However, the waiting time for the mechanical polarization rotation makes it too sensitive to motion artifacts and hence has hampered its use in various applications in vivo. In the work described in this article, we constructed a motion-artifact-robust, PR-SHG microscope based on rapid polarization switching at every pixel with an electro-optic Pockells cell (PC) in synchronization with step-wise raster scanning of the focus spot and alternate data acquisition of a vertical-polarization-resolved SHG signal and a horizontal-polarization-resolved one. The constructed PC-based PR-SHG microscope enabled us to visualize orientation mapping of dermal collagen fiber in human facial skin in vivo without the influence of motion artifacts. Furthermore, it implied the location and/or age dependence of the collagen fiber orientation in human facial skin. The robustness to motion artifacts in the collagen orientation measurement will expand the application scope of SHG microscopy in dermatology and collagen-related fields. PMID:24761292

WE-G-BRD-08: Motion Analysis for Rectal Cancer: Implications for Adaptive Radiotherapy On the MR-Linac

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleijnen, J; Asselen, B van; Burbach, M

2015-06-15

Purpose: Purpose of this study is to find the optimal trade-off between adaptation interval and margin reduction and to define the implications of motion for rectal cancer boost radiotherapy on a MR-linac. Methods: Daily MRI scans were acquired of 16 patients, diagnosed with rectal cancer, prior to each radiotherapy fraction in one week (N=76). Each scan session consisted of T2-weighted and three 2D sagittal cine-MRI, at begin (t=0 min), middle (t=9:30 min) and end (t=18:00 min) of scan session, for 1 minute at 2 Hz temporal resolution. Tumor and clinical target volume (CTV) were delineated on each T2-weighted scan andmore » transferred to each cine-MRI. The start frame of the begin scan was used as reference and registered to frames at time-points 15, 30 and 60 seconds, 9:30 and 18:00 minutes and 1, 2, 3 and 4 days later. Per time-point, motion of delineated voxels was evaluated using the deformation vector fields of the registrations and the 95th percentile distance (dist95%) was calculated as measure of motion. Per time-point, the distance that includes 90% of all cases was taken as estimate of required planning target volume (PTV)-margin. Results: Highest motion reduction is observed going from 9:30 minutes to 60 seconds. We observe a reduction in margin estimates from 10.6 to 2.7 mm and 16.1 to 4.6 mm for tumor and CTV, respectively, when adapting every 60 seconds compared to not adapting treatment. A 75% and 71% reduction, respectively. Further reduction in adaptation time-interval yields only marginal motion reduction. For adaptation intervals longer than 18:00 minutes only small motion reductions are observed. Conclusion: The optimal adaptation interval for adaptive rectal cancer (boost) treatments on a MR-linac is 60 seconds. This results in substantial smaller PTV-margin estimates. Adaptation intervals of 18:00 minutes and higher, show little improvement in motion reduction.« less

Inherent robustness of discrete-time adaptive control systems

NASA Technical Reports Server (NTRS)

Ma, C. C. H.

1986-01-01

Global stability robustness with respect to unmodeled dynamics, arbitrary bounded internal noise, as well as external disturbance is shown to exist for a class of discrete-time adaptive control systems when the regressor vectors of these systems are persistently exciting. Although fast adaptation is definitely undesirable, so far as attaining the greatest amount of global stability robustness is concerned, slow adaptation is shown to be not necessarily beneficial. The entire analysis in this paper holds for systems with slowly varying return difference matrices; the plants in these systems need not be slowly varying.

Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.

PubMed

Peng, Jinzhu; Yu, Jie; Wang, Jie

2014-07-01

In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Optimizing 4-Dimensional Magnetic Resonance Imaging Data Sampling for Respiratory Motion Analysis of Pancreatic Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stemkens, Bjorn, E-mail: b.stemkens@umcutrecht.nl; Tijssen, Rob H.N.; Senneville, Baudouin D. de

2015-03-01

Purpose: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. Methods and Materials: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously. Results: The MRI navigator was foundmore » to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor. Conclusions: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients.« less

Real-time people counting system using a single video camera

NASA Astrophysics Data System (ADS)

Lefloch, Damien; Cheikh, Faouzi A.; Hardeberg, Jon Y.; Gouton, Pierre; Picot-Clemente, Romain

2008-02-01

There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter is likely to occur whenever multiple persons move closely, e.g. in shopping centers. Several persons may be considered to be a single person by automatic segmentation algorithms, due to occlusions or shadows, leading to under-counting. Therefore, to account for noises, illumination and static objects changes, a background substraction is performed using an adaptive background model (updated over time based on motion information) and automatic thresholding. Furthermore, post-processing of the segmentation results is performed, in the HSV color space, to remove shadows. Moving objects are tracked using an adaptive Kalman filter, allowing a robust estimation of the objects future positions even under heavy occlusion. The system is implemented in Matlab, and gives encouraging results even at high frame rates. Experimental results obtained based on the PETS2006 datasets are presented at the end of the paper.

Motion-form interactions beyond the motion integration level: evidence for interactions between orientation and optic flow signals.

PubMed

Pavan, Andrea; Marotti, Rosilari Bellacosa; Mather, George

2013-05-31

Motion and form encoding are closely coupled in the visual system. A number of physiological studies have shown that neurons in the striate and extrastriate cortex (e.g., V1 and MT) are selective for motion direction parallel to their preferred orientation, but some neurons also respond to motion orthogonal to their preferred spatial orientation. Recent psychophysical research (Mather, Pavan, Bellacosa, & Casco, 2012) has demonstrated that the strength of adaptation to two fields of transparently moving dots is modulated by simultaneously presented orientation signals, suggesting that the interaction occurs at the level of motion integrating receptive fields in the extrastriate cortex. In the present psychophysical study, we investigated whether motion-form interactions take place at a higher level of neural processing where optic flow components are extracted. In Experiment 1, we measured the duration of the motion aftereffect (MAE) generated by contracting or expanding dot fields in the presence of either radial (parallel) or concentric (orthogonal) counterphase pedestal gratings. To tap the stage at which optic flow is extracted, we measured the duration of the phantom MAE (Weisstein, Maguire, & Berbaum, 1977) in which we adapted and tested different parts of the visual field, with orientation signals presented either in the adapting (Experiment 2) or nonadapting (Experiments 3 and 4) sectors. Overall, the results showed that motion adaptation is suppressed most by orientation signals orthogonal to optic flow direction, suggesting that motion-form interactions also take place at the global motion level where optic flow is extracted.

Correlation processing for correction of phase distortions in subaperture imaging.

PubMed

Tavh, B; Karaman, M

1999-01-01

Ultrasonic subaperture imaging combines synthetic aperture and phased array approaches and permits low-cost systems with improved image quality. In subaperture processing, a large array is synthesized using echo signals collected from a number of receive subapertures by multiple firings of a phased transmit subaperture. Tissue inhomogeneities and displacements in subaperture imaging may cause significant phase distortions on received echo signals. Correlation processing on reference echo signals can be used for correction of the phase distortions, for which the accuracy and robustness are critically limited by the signal correlation. In this study, we explore correlation processing techniques for adaptive subaperture imaging with phase correction for motion and tissue inhomogeneities. The proposed techniques use new subaperture data acquisition schemes to produce reference signal sets with improved signal correlation. The experimental test results were obtained using raw radio frequency (RF) data acquired from two different phantoms with 3.5 MHz, 128-element transducer array. The results show that phase distortions can effectively be compensated by the proposed techniques in real-time adaptive subaperture imaging.

Dominant-limb range-of-motion and humeral-retrotorsion adaptation in collegiate baseball and softball position players.

PubMed

Hibberd, Elizabeth E; Oyama, Sakiko; Tatman, Justin; Myers, Joseph B

2014-01-01

Biomechanically, the motions used by baseball and softball pitchers differ greatly; however, the throwing motions of position players in both sports are strikingly similar. Although the adaptations to the dominant limb from overhead throwing have been well documented in baseball athletes, these adaptations have not been clearly identified in softball players. This information is important in order to develop and implement injury-prevention programs specific to decreasing the risk of upper extremity injury in softball athletes. To compare range-of-motion and humeral-retrotorsion characteristics of collegiate baseball and softball position players and of baseball and softball players to sex-matched controls. Cross-sectional study. Research laboratories and athletic training rooms at the University of North Carolina at Chapel Hill. Fifty-three collegiate baseball players, 35 collegiate softball players, 25 male controls (nonoverhead athletes), and 19 female controls (nonoverhead athletes). Range of motion and humeral retrotorsion were measured using a digital inclinometer and diagnostic ultrasound. Glenohumeral internal-rotation deficit, external-rotation gain, total glenohumeral range of motion, and humeral retrotorsion. Baseball players had greater glenohumeral internal-rotation deficit, total-range-of-motion, and humeral-retrotorsion difference than softball players and male controls. There were no differences between glenohumeral internal-rotation deficit, total-range-of-motion, and humeral-retrotorsion difference in softball players and female controls. Few differences were evident between softball players and female control participants, although range-of-motion and humeral-retrotorsion adaptations were significantly different than baseball players. The throwing motions are similar between softball and baseball, but the athletes adapt to the demands of the sport differently; thus, stretching/strengthening programs designed for baseball may not be the most effective programs for softball athletes.

Dominant-Limb Range-of-Motion and Humeral-Retrotorsion Adaptation in Collegiate Baseball and Softball Position Players

PubMed Central

Hibberd, Elizabeth E.; Oyama, Sakiko; Tatman, Justin; Myers, Joseph B.

2014-01-01

Context: Biomechanically, the motions used by baseball and softball pitchers differ greatly; however, the throwing motions of position players in both sports are strikingly similar. Although the adaptations to the dominant limb from overhead throwing have been well documented in baseball athletes, these adaptations have not been clearly identified in softball players. This information is important in order to develop and implement injury-prevention programs specific to decreasing the risk of upper extremity injury in softball athletes. Objective: To compare range-of-motion and humeral-retrotorsion characteristics of collegiate baseball and softball position players and of baseball and softball players to sex-matched controls. Design: Cross-sectional study. Setting: Research laboratories and athletic training rooms at the University of North Carolina at Chapel Hill. Patients or Other Participants: Fifty-three collegiate baseball players, 35 collegiate softball players, 25 male controls (nonoverhead athletes), and 19 female controls (nonoverhead athletes). Intervention(s): Range of motion and humeral retrotorsion were measured using a digital inclinometer and diagnostic ultrasound. Main Outcome Measure(s): Glenohumeral internal-rotation deficit, external-rotation gain, total glenohumeral range of motion, and humeral retrotorsion. Results: Baseball players had greater glenohumeral internal-rotation deficit, total–range-of-motion, and humeral-retrotorsion difference than softball players and male controls. There were no differences between glenohumeral internal-rotation deficit, total–range-of-motion, and humeral-retrotorsion difference in softball players and female controls. Conclusions: Few differences were evident between softball players and female control participants, although range-of-motion and humeral-retrotorsion adaptations were significantly different than baseball players. The throwing motions are similar between softball and baseball, but the athletes adapt to the demands of the sport differently; thus, stretching/strengthening programs designed for baseball may not be the most effective programs for softball athletes. PMID:25098655

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

A robust high-order lattice adaptive notch filter and its application to narrowband noise cancellation

NASA Astrophysics Data System (ADS)

Kim, Seong-woo; Park, Young-cheol; Seo, Young-soo; Youn, Dae Hee

2014-12-01

In this paper, we propose a high-order lattice adaptive notch filter (LANF) that can robustly track multiple sinusoids. Unlike the conventional cascade structure, the proposed high-order LANF has robust tracking characteristics regardless of the frequencies of reference sinusoids and initial notch frequencies. The proposed high-order LANF is applied to a narrowband adaptive noise cancellation (ANC) to mitigate the effect of the broadband disturbance in the reference signal. By utilizing the gradient adaptive lattice (GAL) ANC algorithm and approximately combining it with the proposed high-order LANF, a computationally efficient narrowband ANC system is obtained. Experimental results demonstrate the robustness of the proposed high-order LANF and the effectiveness of the obtained narrowband ANC system.

Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains

NASA Technical Reports Server (NTRS)

Zaal, P. M. T; Pool, D. M.

2014-01-01

In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.

Impact of respiratory motion on worst-case scenario optimized intensity modulated proton therapy for lung cancers.

PubMed

Liu, Wei; Liao, Zhongxing; Schild, Steven E; Liu, Zhong; Li, Heng; Li, Yupeng; Park, Peter C; Li, Xiaoqiang; Stoker, Joshua; Shen, Jiajian; Keole, Sameer; Anand, Aman; Fatyga, Mirek; Dong, Lei; Sahoo, Narayan; Vora, Sujay; Wong, William; Zhu, X Ronald; Bues, Martin; Mohan, Radhe

2015-01-01

We compared conventionally optimized intensity modulated proton therapy (IMPT) treatment plans against worst-case scenario optimized treatment plans for lung cancer. The comparison of the 2 IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient setup, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. For each of the 9 lung cancer cases, 2 treatment plans were created that accounted for treatment uncertainties in 2 different ways. The first used the conventional method: delivery of prescribed dose to the planning target volume that is geometrically expanded from the internal target volume (ITV). The second used a worst-case scenario optimization scheme that addressed setup and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of changes in patient anatomy attributable to respiratory motion were investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the 2 groups were compared with 2-sided paired Student t tests. Without respiratory motion considered, we affirmed that worst-case scenario optimization is superior to planning target volume-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, worst-case scenario optimization still achieved more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality (D95% ITV, 96.6% vs 96.1% [P = .26]; D5%- D95% ITV, 10.0% vs 12.3% [P = .082]; D1% spinal cord, 31.8% vs 36.5% [P = .035]). Worst-case scenario optimization led to superior solutions for lung IMPT. Despite the fact that worst-case scenario optimization did not explicitly account for respiratory motion, it produced motion-resistant treatment plans. However, further research is needed to incorporate respiratory motion into IMPT robust optimization. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR

PubMed Central

Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

2014-01-01

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively. PMID:25207868

Motion field estimation for a dynamic scene using a 3D LiDAR.

PubMed

Li, Qingquan; Zhang, Liang; Mao, Qingzhou; Zou, Qin; Zhang, Pin; Feng, Shaojun; Ochieng, Washington

2014-09-09

This paper proposes a novel motion field estimation method based on a 3D light detection and ranging (LiDAR) sensor for motion sensing for intelligent driverless vehicles and active collision avoidance systems. Unlike multiple target tracking methods, which estimate the motion state of detected targets, such as cars and pedestrians, motion field estimation regards the whole scene as a motion field in which each little element has its own motion state. Compared to multiple target tracking, segmentation errors and data association errors have much less significance in motion field estimation, making it more accurate and robust. This paper presents an intact 3D LiDAR-based motion field estimation method, including pre-processing, a theoretical framework for the motion field estimation problem and practical solutions. The 3D LiDAR measurements are first projected to small-scale polar grids, and then, after data association and Kalman filtering, the motion state of every moving grid is estimated. To reduce computing time, a fast data association algorithm is proposed. Furthermore, considering the spatial correlation of motion among neighboring grids, a novel spatial-smoothing algorithm is also presented to optimize the motion field. The experimental results using several data sets captured in different cities indicate that the proposed motion field estimation is able to run in real-time and performs robustly and effectively.

Development of a robust and cost-effective 3D respiratory motion monitoring system using the kinect device: Accuracy comparison with the conventional stereovision navigation system.

PubMed

Bae, Myungsoo; Lee, Sangmin; Kim, Namkug

2018-07-01

To develop and validate a robust and cost-effective 3D respiratory monitoring system based on a Kinect device with a custom-made simple marker. A 3D respiratory monitoring system comprising the simple marker and the Microsoft Kinect v2 device was developed. The marker was designed for simple and robust detection, and the tracking algorithm was developed using the depth, RGB, and infra-red images acquired from the Kinect sensor. A Kalman filter was used to suppress movement noises. The major movements of the marker attached to the four different locations of body surface were determined from the initially collected tracking points of the marker while breathing. The signal level of respiratory motion with the tracking point was estimated along the major direction vector. The accuracy of the results was evaluated through a comparison with those of the conventional stereovision navigation system (NDI Polaris Spectra). Sixteen normal volunteers were enrolled to evaluate the accuracy of this system. The correlation coefficients between the respiratory motion signal from the Kinect device and conventional navigation system ranged from 0.970 to 0.999 and from 0.837 to 0.995 at the abdominal and thoracic surfaces, respectively. The respiratory motion signal from this system was obtained at 27-30 frames/s. This system with the Kinect v2 device and simple marker could be used for cost-effective, robust and accurate 3D respiratory motion monitoring. In addition, this system is as reliable for respiratory motion signal generation and as practically useful as the conventional stereovision navigation system and is less sensitive to patient posture. Copyright © 2018 Elsevier B.V. All rights reserved.

Expanded envelope concepts for aircraft control-element failure detection and identification

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1988-01-01

The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.

Scene-Aware Adaptive Updating for Visual Tracking via Correlation Filters

PubMed Central

Zhang, Sirou; Qiao, Xiaoya

2017-01-01

In recent years, visual object tracking has been widely used in military guidance, human-computer interaction, road traffic, scene monitoring and many other fields. The tracking algorithms based on correlation filters have shown good performance in terms of accuracy and tracking speed. However, their performance is not satisfactory in scenes with scale variation, deformation, and occlusion. In this paper, we propose a scene-aware adaptive updating mechanism for visual tracking via a kernel correlation filter (KCF). First, a low complexity scale estimation method is presented, in which the corresponding weight in five scales is employed to determine the final target scale. Then, the adaptive updating mechanism is presented based on the scene-classification. We classify the video scenes as four categories by video content analysis. According to the target scene, we exploit the adaptive updating mechanism to update the kernel correlation filter to improve the robustness of the tracker, especially in scenes with scale variation, deformation, and occlusion. We evaluate our tracker on the CVPR2013 benchmark. The experimental results obtained with the proposed algorithm are improved by 33.3%, 15%, 6%, 21.9% and 19.8% compared to those of the KCF tracker on the scene with scale variation, partial or long-time large-area occlusion, deformation, fast motion and out-of-view. PMID:29140311

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera.

PubMed

Ci, Wenyan; Huang, Yingping

2016-10-17

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

PubMed Central

Ci, Wenyan; Huang, Yingping

2016-01-01

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera’s 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg–Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade–Lucas–Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method. PMID:27763508

Minimal time change detection algorithm for reconfigurable control system and application to aerospace

NASA Technical Reports Server (NTRS)

Kim, Sungwan

1994-01-01

System parameters should be tracked on-line to build a reconfigurable control system even though there exists an abrupt change. For this purpose, a new performance index that we are studying is the speed of adaptation- how quickly does the system determine that a change has occurred? In this paper, a new, robust algorithm that is optimized to minimize the time delay in detecting a change for fixed false alarm probability is proposed. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well. One of its distinguishing properties is that detection delay of this algorithm is superior to that of Whiteness Test.

A robust motion estimation system for minimal invasive laparoscopy

NASA Astrophysics Data System (ADS)

Marcinczak, Jan Marek; von Öhsen, Udo; Grigat, Rolf-Rainer

2012-02-01

Laparoscopy is a reliable imaging method to examine the liver. However, due to the limited field of view, a lot of experience is required from the surgeon to interpret the observed anatomy. Reconstruction of organ surfaces provide valuable additional information to the surgeon for a reliable diagnosis. Without an additional external tracking system the structure can be recovered from feature correspondences between different frames. In laparoscopic images blurred frames, specular reflections and inhomogeneous illumination make feature tracking a challenging task. We propose an ego-motion estimation system for minimal invasive laparoscopy that can cope with specular reflection, inhomogeneous illumination and blurred frames. To obtain robust feature correspondence, the approach combines SIFT and specular reflection segmentation with a multi-frame tracking scheme. The calibrated five-point algorithm is used with the MSAC robust estimator to compute the motion of the endoscope from multi-frame correspondence. The algorithm is evaluated using endoscopic videos of a phantom. The small incisions and the rigid endoscope limit the motion in minimal invasive laparoscopy. These limitations are considered in our evaluation and are used to analyze the accuracy of pose estimation that can be achieved by our approach. The endoscope is moved by a robotic system and the ground truth motion is recorded. The evaluation on typical endoscopic motion gives precise results and demonstrates the practicability of the proposed pose estimation system.

Binding of motion and colour is early and automatic.

PubMed

Blaser, Erik; Papathomas, Thomas; Vidnyánszky, Zoltán

2005-04-01

At what stages of the human visual hierarchy different features are bound together, and whether this binding requires attention, is still highly debated. We used a colour-contingent motion after-effect (CCMAE) to study the binding of colour and motion signals. The logic of our approach was as follows: if CCMAEs can be evoked by targeted adaptation of early motion processing stages, without allowing for feedback from higher motion integration stages, then this would support our hypothesis that colour and motion are bound automatically on the basis of spatiotemporally local information. Our results show for the first time that CCMAE's can be evoked by adaptation to a locally paired opposite-motion dot display, a stimulus that, importantly, is known to trigger direction-specific responses in the primary visual cortex yet results in strong inhibition of the directional responses in area MT of macaques as well as in area MT+ in humans and, indeed, is perceived only as motionless flicker. The magnitude of the CCMAE in the locally paired condition was not significantly different from control conditions where the different directions were spatiotemporally separated (i.e. not locally paired) and therefore perceived as two moving fields. These findings provide evidence that adaptation at an early, local motion stage, and only adaptation at this stage, underlies this CCMAE, which in turn implies that spatiotemporally coincident colour and motion signals are bound automatically, most probably as early as cortical area V1, even when the association between colour and motion is perceptually inaccessible.

A dosimetric comparison of real-time adaptive and non-adaptive radiotherapy: A multi-institutional study encompassing robotic, gimbaled, multileaf collimator and couch tracking.

PubMed

Colvill, Emma; Booth, Jeremy; Nill, Simeon; Fast, Martin; Bedford, James; Oelfke, Uwe; Nakamura, Mitsuhiro; Poulsen, Per; Worm, Esben; Hansen, Rune; Ravkilde, Thomas; Scherman Rydhög, Jonas; Pommer, Tobias; Munck Af Rosenschold, Per; Lang, Stephanie; Guckenberger, Matthias; Groh, Christian; Herrmann, Christian; Verellen, Dirk; Poels, Kenneth; Wang, Lei; Hadsell, Michael; Sothmann, Thilo; Blanck, Oliver; Keall, Paul

2016-04-01

A study of real-time adaptive radiotherapy systems was performed to test the hypothesis that, across delivery systems and institutions, the dosimetric accuracy is improved with adaptive treatments over non-adaptive radiotherapy in the presence of patient-measured tumor motion. Ten institutions with robotic(2), gimbaled(2), MLC(4) or couch tracking(2) used common materials including CT and structure sets, motion traces and planning protocols to create a lung and a prostate plan. For each motion trace, the plan was delivered twice to a moving dosimeter; with and without real-time adaptation. Each measurement was compared to a static measurement and the percentage of failed points for γ-tests recorded. For all lung traces all measurement sets show improved dose accuracy with a mean 2%/2mm γ-fail rate of 1.6% with adaptation and 15.2% without adaptation (p<0.001). For all prostate the mean 2%/2mm γ-fail rate was 1.4% with adaptation and 17.3% without adaptation (p<0.001). The difference between the four systems was small with an average 2%/2mm γ-fail rate of <3% for all systems with adaptation for lung and prostate. The investigated systems all accounted for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive delivery methods. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Control of a small working robot on a large flexible manipulator for suppressing vibrations: Development of a robust control law for flexible robot and it's stability analysis

NASA Technical Reports Server (NTRS)

Soo, Han Lee

1991-01-01

Researchers developed a robust control law for slow motions for the accurate trajectory control of a flexible robot. The control law does not need larger velocity gains than position gains, which some researchers need to ensure the stability of a rigid robot. Initial experimentation for the Small Articulated Manipulator (SAM) shows that control laws that use smaller velocity gains are more robust to signal noise than the control laws that use larger velocity gains. Researchers analyzed the stability of the composite control law, the robust control for the slow motion, and the strain rate feedback for the fast control. The stability analysis was done by using a quadratic Liapunov function. Researchers found that the flexible motion of links could be controlled by relating the input force to the flexible signals which are sensed at the near tip of each link. The signals are contaminated by the time delayed input force. However, the effect of the time delayed input force can be reduced by giving a certain configuration to the SAM.

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

PubMed

Wang, Ding; Liu, Derong

2018-06-01

The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

Motion-form interactions beyond the motion integration level: Evidence for interactions between orientation and optic flow signals

PubMed Central

Pavan, Andrea; Marotti, Rosilari Bellacosa; Mather, George

2013-01-01

Motion and form encoding are closely coupled in the visual system. A number of physiological studies have shown that neurons in the striate and extrastriate cortex (e.g., V1 and MT) are selective for motion direction parallel to their preferred orientation, but some neurons also respond to motion orthogonal to their preferred spatial orientation. Recent psychophysical research (Mather, Pavan, Bellacosa, & Casco, 2012) has demonstrated that the strength of adaptation to two fields of transparently moving dots is modulated by simultaneously presented orientation signals, suggesting that the interaction occurs at the level of motion integrating receptive fields in the extrastriate cortex. In the present psychophysical study, we investigated whether motion-form interactions take place at a higher level of neural processing where optic flow components are extracted. In Experiment 1, we measured the duration of the motion aftereffect (MAE) generated by contracting or expanding dot fields in the presence of either radial (parallel) or concentric (orthogonal) counterphase pedestal gratings. To tap the stage at which optic flow is extracted, we measured the duration of the phantom MAE (Weisstein, Maguire, & Berbaum, 1977) in which we adapted and tested different parts of the visual field, with orientation signals presented either in the adapting (Experiment 2) or nonadapting (Experiments 3 and 4) sectors. Overall, the results showed that motion adaptation is suppressed most by orientation signals orthogonal to optic flow direction, suggesting that motion-form interactions also take place at the global motion level where optic flow is extracted. PMID:23729767

Intelligent nonsingular terminal sliding-mode control using MIMO Elman neural network for piezo-flexural nanopositioning stage.

PubMed

Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan

2012-12-01

The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.

Separate Perceptual and Neural Processing of Velocity- and Disparity-Based 3D Motion Signals

PubMed Central

Czuba, Thaddeus B.; Cormack, Lawrence K.; Huk, Alexander C.

2016-01-01

Although the visual system uses both velocity- and disparity-based binocular information for computing 3D motion, it is unknown whether (and how) these two signals interact. We found that these two binocular signals are processed distinctly at the levels of both cortical activity in human MT and perception. In human MT, adaptation to both velocity-based and disparity-based 3D motions demonstrated direction-selective neuroimaging responses. However, when adaptation to one cue was probed using the other cue, there was no evidence of interaction between them (i.e., there was no “cross-cue” adaptation). Analogous psychophysical measurements yielded correspondingly weak cross-cue motion aftereffects (MAEs) in the face of very strong within-cue adaptation. In a direct test of perceptual independence, adapting to opposite 3D directions generated by different binocular cues resulted in simultaneous, superimposed, opposite-direction MAEs. These findings suggest that velocity- and disparity-based 3D motion signals may both flow through area MT but constitute distinct signals and pathways. SIGNIFICANCE STATEMENT Recent human neuroimaging and monkey electrophysiology have revealed 3D motion selectivity in area MT, which is driven by both velocity-based and disparity-based 3D motion signals. However, to elucidate the neural mechanisms by which the brain extracts 3D motion given these binocular signals, it is essential to understand how—or indeed if—these two binocular cues interact. We show that velocity-based and disparity-based signals are mostly separate at the levels of both fMRI responses in area MT and perception. Our findings suggest that the two binocular cues for 3D motion might be processed by separate specialized mechanisms. PMID:27798134

Separate Perceptual and Neural Processing of Velocity- and Disparity-Based 3D Motion Signals.

PubMed

Joo, Sung Jun; Czuba, Thaddeus B; Cormack, Lawrence K; Huk, Alexander C

2016-10-19

Although the visual system uses both velocity- and disparity-based binocular information for computing 3D motion, it is unknown whether (and how) these two signals interact. We found that these two binocular signals are processed distinctly at the levels of both cortical activity in human MT and perception. In human MT, adaptation to both velocity-based and disparity-based 3D motions demonstrated direction-selective neuroimaging responses. However, when adaptation to one cue was probed using the other cue, there was no evidence of interaction between them (i.e., there was no "cross-cue" adaptation). Analogous psychophysical measurements yielded correspondingly weak cross-cue motion aftereffects (MAEs) in the face of very strong within-cue adaptation. In a direct test of perceptual independence, adapting to opposite 3D directions generated by different binocular cues resulted in simultaneous, superimposed, opposite-direction MAEs. These findings suggest that velocity- and disparity-based 3D motion signals may both flow through area MT but constitute distinct signals and pathways. Recent human neuroimaging and monkey electrophysiology have revealed 3D motion selectivity in area MT, which is driven by both velocity-based and disparity-based 3D motion signals. However, to elucidate the neural mechanisms by which the brain extracts 3D motion given these binocular signals, it is essential to understand how-or indeed if-these two binocular cues interact. We show that velocity-based and disparity-based signals are mostly separate at the levels of both fMRI responses in area MT and perception. Our findings suggest that the two binocular cues for 3D motion might be processed by separate specialized mechanisms. Copyright © 2016 the authors 0270-6474/16/3610791-12$15.00/0.

Sagittal fresh blood imaging with interleaved acquisition of systolic and diastolic data for improved robustness to motion.

PubMed

Atanasova, Iliyana P; Kim, Daniel; Storey, Pippa; Rosenkrantz, Andrew B; Lim, Ruth P; Lee, Vivian S

2013-02-01

To improve robustness to patient motion of "fresh blood imaging" (FBI) for lower extremity noncontrast MR angiography. In FBI, two sets of three-dimensional fast spin echo images are acquired at different cardiac phases and subtracted to generate bright-blood angiograms. Routinely performed with a single coronal slab and sequential acquisition of systolic and diastolic data, FBI is prone to subtraction errors due to patient motion. In this preliminary feasibility study, FBI was implemented with two sagittal imaging slabs, and the systolic and diastolic acquisitions were interleaved to minimize sensitivity to motion. The proposed technique was evaluated in volunteers and patients. In 10 volunteers, imaged while performing controlled movements, interleaved FBI demonstrated better tolerance to subject motion than sequential FBI. In one patient with peripheral arterial disease, interleaved FBI offered better depiction of collateral flow by reducing sensitivity to inadvertent motion. FBI with interleaved acquisition of diastolic and systolic data in two sagittal imaging slabs offers improved tolerance to patient motion. Copyright © 2013 Wiley Periodicals, Inc.

Sagittal Fresh Blood Imaging with Interleaved Acquisition of Systolic and Diastolic Data for Improved Robustness to Motion

PubMed Central

Atanasova, Iliyana P.; Kim, Daniel; Storey, Pippa; Rosenkrantz, Andrew B; Lim, Ruth P.; Lee, Vivian S.

2012-01-01

Purpose To improve robustness to patient motion of ‘fresh blood imaging’ (FBI) for lower extremity non-contrast MRA. Methods In FBI, two sets of 3D fast spin echo images are acquired at different cardiac phases and subtracted to generate bright-blood angiograms. Routinely performed with a single coronal slab and sequential acquisition of systolic and diastolic data, FBI is prone to subtraction errors due to patient motion. In this preliminary feasibility study, FBI was implemented with two sagittal imaging slabs, and the systolic and diastolic acquisitions were interleaved to minimize sensitivity to motion. The proposed technique was evaluated in volunteers and patients. Results In ten volunteers, imaged while performing controlled movements, interleaved FBI demonstrated better tolerance to subject motion than sequential FBI. In one patient with peripheral arterial disease, interleaved FBI offered better depiction of collateral flow by reducing sensitivity to inadvertent motion. Conclusions FBI with interleaved acquisition of diastolic and systolic data in two sagittal imaging slabs offers improved tolerance to patient motion. PMID:23300129

Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness

PubMed Central

Spering, Miriam; Carrasco, Marisa

2012-01-01

Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth pursuit eye movements in response to moving dichoptic plaids–stimuli composed of two orthogonally-drifting gratings, presented separately to each eye–in human observers. Monocular adaptation to one grating prior to the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating’s motion direction or to both (neutral condition). We show that observers were better in detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating’s motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted towards the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it. PMID:22649238

Similar effects of feature-based attention on motion perception and pursuit eye movements at different levels of awareness.

PubMed

Spering, Miriam; Carrasco, Marisa

2012-05-30

Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth-pursuit eye movements in response to moving dichoptic plaids--stimuli composed of two orthogonally drifting gratings, presented separately to each eye--in human observers. Monocular adaptation to one grating before the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating's motion direction or to both (neutral condition). We show that observers were better at detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating's motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted toward the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it.

Adaptive Radiation for Lung Cancer

PubMed Central

Gomez, Daniel R.; Chang, Joe Y.

2011-01-01

The challenges of lung cancer radiotherapy are intra/inter-fraction tumor/organ anatomy/motion changes and the need to spare surrounding critical structures. Evolving radiotherapy technologies, such as four-dimensional (4D) image-based motion management, daily on-board imaging and adaptive radiotherapy based on volumetric images over the course of radiotherapy, have enabled us to deliver higher dose to target while minimizing normal tissue toxicities. The image-guided radiotherapy adapted to changes of motion and anatomy has made the radiotherapy more precise and allowed ablative dose delivered to the target using novel treatment approaches such as intensity-modulated radiation therapy, stereotactic body radiation therapy, and proton therapy in lung cancer, techniques used to be considered very sensitive to motion change. Future clinical trials using real time tracking and biological adaptive radiotherapy based on functional images are proposed. PMID:20814539

SU-G-JeP1-07: Development of a Programmable Motion Testbed for the Validation of Ultrasound Tracking Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shepard, A; Matrosic, C; Zagzebski, J

Purpose: To develop an advanced testbed that combines a 3D motion stage and ultrasound phantom to optimize and validate 2D and 3D tracking algorithms for real-time motion management during radiation therapy. Methods: A Siemens S2000 Ultrasound scanner utilizing a 9L4 transducer was coupled with the Washington University 4D Phantom to simulate patient motion. The transducer was securely fastened to the 3D stage and positioned to image three cylinders of varying contrast in a Gammex 404GS LE phantom. The transducer was placed within a water bath above the phantom in order to maintain sufficient coupling for the entire range of simulatedmore » motion. A programmed motion sequence was used to move the transducer during image acquisition and a cine video was acquired for one minute to allow for long sequence tracking. Images were analyzed using a normalized cross-correlation block matching tracking algorithm and compared to the known motion of the transducer relative to the phantom. Results: The setup produced stable ultrasound motion traces consistent with those programmed into the 3D motion stage. The acquired ultrasound images showed minimal artifacts and an image quality that was more than suitable for tracking algorithm verification. Comparisons of a block matching tracking algorithm with the known motion trace for the three features resulted in an average tracking error of 0.59 mm. Conclusion: The high accuracy and programmability of the 4D phantom allows for the acquisition of ultrasound motion sequences that are highly customizable; allowing for focused analysis of some common pitfalls of tracking algorithms such as partial feature occlusion or feature disappearance, among others. The design can easily be modified to adapt to any probe such that the process can be extended to 3D acquisition. Further development of an anatomy specific phantom better resembling true anatomical landmarks could lead to an even more robust validation. This work is partially funded by NIH grant R01CA190298.« less

PROPER MOTIONS AND ORIGINS OF SGR 1806-20 AND SGR 1900+14

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tendulkar, Shriharsh P.; Kulkarni, Shrinivas R.; Cameron, P. Brian, E-mail: spt@astro.caltech.edu

2012-12-10

We present results from high-resolution infrared observations of magnetars SGR 1806-20 and SGR 1900+14 over 5 years using laser-supported adaptive optics at the 10 m Keck Observatory. Our measurements of the proper motions of these magnetars provide robust links between magnetars and their progenitors and provide age estimates for magnetars. At the measured distances of their putative associations, we measure the linear transverse velocity of SGR 1806-20 to be 350 {+-} 100 km s{sup -1} and of SGR 1900+14 to be 130 {+-} 30 km s{sup -1}. The transverse velocity vectors for both magnetars point away from the clusters ofmore » massive stars, solidifying their proposed associations. Assuming that the magnetars were born in the clusters, we can estimate the braking index to be {approx}1.8 for SGR 1806-20 and {approx}1.2 for SGR 1900+14. This is significantly lower than the canonical value of n = 3 predicted by the magnetic dipole spin-down suggesting an alternative source of dissipation such as twisted magnetospheres or particle winds.« less

Use of promethazine to hasten adaptation to provocative motion

NASA Technical Reports Server (NTRS)

Lackner, J. R.; Graybiel, A.

1994-01-01

In an earlier study, the authors found that severely motion sick individuals could be greatly relieved of their symptoms by intramuscular injections of promethazine (50 mg) or scopolamine (.5 mg). Comparable 50-mg injections of promethazine also have been found effective in alleviating symptoms of space motion sickness. The concern has risen, however, that such drugs may delay or retard the acquisition of adaptation to stressful environments. In the current study, we controlled arousal using a mental arithmetic task and precisely equated the exposure history (number of head movements during rotation) of a placebo, control group and an experimental group who had received promethazine. No differences in total adaptation or in rates of adaptation were present between the two groups. Another experimental group also received promethazine and was allowed to make as many head movements as they could, before reaching nausea, up to 800. This group showed a greater level of adaptation than the placebo group. These results suggest a strategy for dealing with space motion sickness that is described.

Application of nonlinear adaptive motion washout to transport ground-handling simulation

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Martin, D. J., Jr.

1983-01-01

The application of a nonlinear coordinated adaptive motion washout to the transport ground-handling environment is documented. Additions to both the aircraft math model and the motion washout system are discussed. The additions to the simulated-aircraft math model provided improved modeling fidelity for braking and reverse-thrust application, and the additions to the motion-base washout system allowed transition from the desired flight parameters to the less restrictive ground parameters of the washout.

Effects of proposed preflight adaptation training on eye movements, self-motion perception, and motion sickness - A progress report

NASA Technical Reports Server (NTRS)

Parker, D. E.; Reschke, M. F.; Von Gierke, H. E.; Lessard, C. S.

1987-01-01

The preflight adaptation trainer (PAT) was designed to produce rearranged relationships between visual and otolith signals analogous to those experienced in space. Investigations have been undertaken with three prototype trainers. The results indicated that exposure to the PAT sensory rearrangement altered self-motion perception, induced motion sickness, and changed the amplitude and phase of the horizontal eye movements evoked by roll stimulation. However, the changes were inconsistent.

Stretchable Materials for Robust Soft Actuators towards Assistive Wearable Devices

NASA Astrophysics Data System (ADS)

Agarwal, Gunjan; Besuchet, Nicolas; Audergon, Basile; Paik, Jamie

2016-09-01

Soft actuators made from elastomeric active materials can find widespread potential implementation in a variety of applications ranging from assistive wearable technologies targeted at biomedical rehabilitation or assistance with activities of daily living, bioinspired and biomimetic systems, to gripping and manipulating fragile objects, and adaptable locomotion. In this manuscript, we propose a novel two-component soft actuator design and design tool that produces actuators targeted towards these applications with enhanced mechanical performance and manufacturability. Our numerical models developed using the finite element method can predict the actuator behavior at large mechanical strains to allow efficient design iterations for system optimization. Based on two distinctive actuator prototypes’ (linear and bending actuators) experimental results that include free displacement and blocked-forces, we have validated the efficacy of the numerical models. The presented extensive investigation of mechanical performance for soft actuators with varying geometric parameters demonstrates the practical application of the design tool, and the robustness of the actuator hardware design, towards diverse soft robotic systems for a wide set of assistive wearable technologies, including replicating the motion of several parts of the human body.

Cortex Inspired Model for Inverse Kinematics Computation for a Humanoid Robotic Finger

PubMed Central

Gentili, Rodolphe J.; Oh, Hyuk; Molina, Javier; Reggia, James A.; Contreras-Vidal, José L.

2013-01-01

In order to approach human hand performance levels, artificial anthropomorphic hands/fingers have increasingly incorporated human biomechanical features. However, the performance of finger reaching movements to visual targets involving the complex kinematics of multi-jointed, anthropomorphic actuators is a difficult problem. This is because the relationship between sensory and motor coordinates is highly nonlinear, and also often includes mechanical coupling of the two last joints. Recently, we developed a cortical model that learns the inverse kinematics of a simulated anthropomorphic finger. Here, we expand this previous work by assessing if this cortical model is able to learn the inverse kinematics for an actual anthropomorphic humanoid finger having its two last joints coupled and controlled by pneumatic muscles. The findings revealed that single 3D reaching movements, as well as more complex patterns of motion of the humanoid finger, were accurately and robustly performed by this cortical model while producing kinematics comparable to those of humans. This work contributes to the development of a bioinspired controller providing adaptive, robust and flexible control of dexterous robotic and prosthetic hands. PMID:23366569

Stretchable Materials for Robust Soft Actuators towards Assistive Wearable Devices

PubMed Central

Agarwal, Gunjan; Besuchet, Nicolas; Audergon, Basile; Paik, Jamie

2016-01-01

Soft actuators made from elastomeric active materials can find widespread potential implementation in a variety of applications ranging from assistive wearable technologies targeted at biomedical rehabilitation or assistance with activities of daily living, bioinspired and biomimetic systems, to gripping and manipulating fragile objects, and adaptable locomotion. In this manuscript, we propose a novel two-component soft actuator design and design tool that produces actuators targeted towards these applications with enhanced mechanical performance and manufacturability. Our numerical models developed using the finite element method can predict the actuator behavior at large mechanical strains to allow efficient design iterations for system optimization. Based on two distinctive actuator prototypes’ (linear and bending actuators) experimental results that include free displacement and blocked-forces, we have validated the efficacy of the numerical models. The presented extensive investigation of mechanical performance for soft actuators with varying geometric parameters demonstrates the practical application of the design tool, and the robustness of the actuator hardware design, towards diverse soft robotic systems for a wide set of assistive wearable technologies, including replicating the motion of several parts of the human body. PMID:27670953

Stretchable Materials for Robust Soft Actuators towards Assistive Wearable Devices.

PubMed

Agarwal, Gunjan; Besuchet, Nicolas; Audergon, Basile; Paik, Jamie

2016-09-27

Soft actuators made from elastomeric active materials can find widespread potential implementation in a variety of applications ranging from assistive wearable technologies targeted at biomedical rehabilitation or assistance with activities of daily living, bioinspired and biomimetic systems, to gripping and manipulating fragile objects, and adaptable locomotion. In this manuscript, we propose a novel two-component soft actuator design and design tool that produces actuators targeted towards these applications with enhanced mechanical performance and manufacturability. Our numerical models developed using the finite element method can predict the actuator behavior at large mechanical strains to allow efficient design iterations for system optimization. Based on two distinctive actuator prototypes' (linear and bending actuators) experimental results that include free displacement and blocked-forces, we have validated the efficacy of the numerical models. The presented extensive investigation of mechanical performance for soft actuators with varying geometric parameters demonstrates the practical application of the design tool, and the robustness of the actuator hardware design, towards diverse soft robotic systems for a wide set of assistive wearable technologies, including replicating the motion of several parts of the human body.

The control of the controller: molecular mechanisms for robust perfect adaptation and temperature compensation.

PubMed

Ni, Xiao Yu; Drengstig, Tormod; Ruoff, Peter

2009-09-02

Organisms have the property to adapt to a changing environment and keep certain components within a cell regulated at the same level (homeostasis). "Perfect adaptation" describes an organism's response to an external stepwise perturbation by regulating some of its variables/components precisely to their original preperturbation values. Numerous examples of perfect adaptation/homeostasis have been found, as for example, in bacterial chemotaxis, photoreceptor responses, MAP kinase activities, or in metal-ion homeostasis. Two concepts have evolved to explain how perfect adaptation may be understood: In one approach (robust perfect adaptation), the adaptation is a network property, which is mostly, but not entirely, independent of rate constant values; in the other approach (nonrobust perfect adaptation), a fine-tuning of rate constant values is needed. Here we identify two classes of robust molecular homeostatic mechanisms, which compensate for environmental variations in a controlled variable's inflow or outflow fluxes, and allow for the presence of robust temperature compensation. These two classes of homeostatic mechanisms arise due to the fact that concentrations must have positive values. We show that the concept of integral control (or integral feedback), which leads to robust homeostasis, is associated with a control species that has to work under zero-order flux conditions and does not necessarily require the presence of a physico-chemical feedback structure. There are interesting links between the two identified classes of homeostatic mechanisms and molecular mechanisms found in mammalian iron and calcium homeostasis, indicating that homeostatic mechanisms may underlie similar molecular control structures.

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm.

PubMed

Zhang, Man; Wang, Guanyong; Zhang, Lei

2017-10-26

Precise azimuth-variant motion compensation (MOCO) is an essential and difficult task for high-resolution synthetic aperture radar (SAR) imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA), have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA) is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT) is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

Global motion compensated visual attention-based video watermarking

NASA Astrophysics Data System (ADS)

Oakes, Matthew; Bhowmik, Deepayan; Abhayaratne, Charith

2016-11-01

Imperceptibility and robustness are two key but complementary requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often suffer from embedding distortions resulting in poor visual quality in host media. This paper proposes a unique video watermarking algorithm that offers a fine balance between imperceptibility and robustness using motion compensated wavelet-based visual attention model (VAM). The proposed VAM includes spatial cues for visual saliency as well as temporal cues. The spatial modeling uses the spatial wavelet coefficients while the temporal modeling accounts for both local and global motion to arrive at the spatiotemporal VAM for video. The model is then used to develop a video watermarking algorithm, where a two-level watermarking weighting parameter map is generated from the VAM saliency maps using the saliency model and data are embedded into the host image according to the visual attentiveness of each region. By avoiding higher strength watermarking in the visually attentive region, the resulting watermarked video achieves high perceived visual quality while preserving high robustness. The proposed VAM outperforms the state-of-the-art video visual attention methods in joint saliency detection and low computational complexity performance. For the same embedding distortion, the proposed visual attention-based watermarking achieves up to 39% (nonblind) and 22% (blind) improvement in robustness against H.264/AVC compression, compared to existing watermarking methodology that does not use the VAM. The proposed visual attention-based video watermarking results in visual quality similar to that of low-strength watermarking and a robustness similar to those of high-strength watermarking.

TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boeck, M; KTH Royal Institute of Technology, Stockholm; Eriksson, K

Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errorsmore » on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need for an adaptive treatment strategy.« less

Robustness of non-interdependent and interdependent networks against dependent and adaptive attacks

NASA Astrophysics Data System (ADS)

Tyra, Adam; Li, Jingtao; Shang, Yilun; Jiang, Shuo; Zhao, Yanjun; Xu, Shouhuai

2017-09-01

Robustness of complex networks has been extensively studied via the notion of site percolation, which typically models independent and non-adaptive attacks (or disruptions). However, real-life attacks are often dependent and/or adaptive. This motivates us to characterize the robustness of complex networks, including non-interdependent and interdependent ones, against dependent and adaptive attacks. For this purpose, dependent attacks are accommodated by L-hop percolation where the nodes within some L-hop (L ≥ 0) distance of a chosen node are all deleted during one attack (with L = 0 degenerating to site percolation). Whereas, adaptive attacks are launched by attackers who can make node-selection decisions based on the network state in the beginning of each attack. The resulting characterization enriches the body of knowledge with new insights, such as: (i) the Achilles' Heel phenomenon is only valid for independent attacks, but not for dependent attacks; (ii) powerful attack strategies (e.g., targeted attacks and dependent attacks, dependent attacks and adaptive attacks) are not compatible and cannot help the attacker when used collectively. Our results shed some light on the design of robust complex networks.

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

A new robust adaptive controller for vibration control of active engine mount subjected to large uncertainties

NASA Astrophysics Data System (ADS)

Fakhari, Vahid; Choi, Seung-Bok; Cho, Chang-Hyun

2015-04-01

This work presents a new robust model reference adaptive control (MRAC) for vibration control caused from vehicle engine using an electromagnetic type of active engine mount. Vibration isolation performances of the active mount associated with the robust controller are evaluated in the presence of large uncertainties. As a first step, an active mount with linear solenoid actuator is prepared and its dynamic model is identified via experimental test. Subsequently, a new robust MRAC based on the gradient method with σ-modification is designed by selecting a proper reference model. In designing the robust adaptive control, structured (parametric) uncertainties in the stiffness of the passive part of the mount and in damping ratio of the active part of the mount are considered to investigate the robustness of the proposed controller. Experimental and simulation results are presented to evaluate performance focusing on the robustness behavior of the controller in the face of large uncertainties. The obtained results show that the proposed controller can sufficiently provide the robust vibration control performance even in the presence of large uncertainties showing an effective vibration isolation.

Linear force device

NASA Technical Reports Server (NTRS)

Clancy, John P.

1988-01-01

The object of the invention is to provide a mechanical force actuator which is lightweight and manipulatable and utilizes linear motion for push or pull forces while maintaining a constant overall length. The mechanical force producing mechanism comprises a linear actuator mechanism and a linear motion shaft mounted parallel to one another. The linear motion shaft is connected to a stationary or fixed housing and to a movable housing where the movable housing is mechanically actuated through actuator mechanism by either manual means or motor means. The housings are adapted to releasably receive a variety of jaw or pulling elements adapted for clamping or prying action. The stationary housing is adapted to be pivotally mounted to permit an angular position of the housing to allow the tool to adapt to skewed interfaces. The actuator mechanisms is operated by a gear train to obtain linear motion of the actuator mechanism.

Adaptive integral robust control and application to electromechanical servo systems.

PubMed

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Prolonged asymmetric vestibular stimulation induces opposite, long-term effects on self-motion perception and ocular responses.

PubMed

Pettorossi, V E; Panichi, R; Botti, F M; Kyriakareli, A; Ferraresi, A; Faralli, M; Schieppati, M; Bronstein, A M

2013-04-01

Self-motion perception and the vestibulo-ocular reflex (VOR) were investigated in healthy subjects during asymmetric whole body yaw plane oscillations while standing on a platform in the dark. Platform oscillation consisted of two half-sinusoidal cycles of the same amplitude (40°) but different duration, featuring a fast (FHC) and a slow half-cycle (SHC). Rotation consisted of four or 20 consecutive cycles to probe adaptation further with the longer duration protocol. Self-motion perception was estimated by subjects tracking with a pointer the remembered position of an earth-fixed visual target. VOR was measured by electro-oculography. The asymmetric stimulation pattern consistently induced a progressive increase of asymmetry in motion perception, whereby the gain of the tracking response gradually increased during FHCs and decreased during SHCs. The effect was observed already during the first few cycles and further increased during 20 cycles, leading to a totally distorted location of the initial straight-ahead. In contrast, after some initial interindividual variability, the gain of the slow phase VOR became symmetric, decreasing for FHCs and increasing for SHCs. These oppositely directed adaptive effects in motion perception and VOR persisted for nearly an hour. Control conditions using prolonged but symmetrical stimuli produced no adaptive effects on either motion perception or VOR. These findings show that prolonged asymmetric activation of the vestibular system leads to opposite patterns of adaptation of self-motion perception and VOR. The results provide strong evidence that semicircular canal inputs are processed centrally by independent mechanisms for perception of body motion and eye movement control. These divergent adaptation mechanisms enhance awareness of movement toward the faster body rotation, while improving the eye stabilizing properties of the VOR.

Prolonged asymmetric vestibular stimulation induces opposite, long-term effects on self-motion perception and ocular responses

PubMed Central

Pettorossi, V E; Panichi, R; Botti, F M; Kyriakareli, A; Ferraresi, A; Faralli, M; Schieppati, M; Bronstein, A M

2013-01-01

Self-motion perception and the vestibulo-ocular reflex (VOR) were investigated in healthy subjects during asymmetric whole body yaw plane oscillations while standing on a platform in the dark. Platform oscillation consisted of two half-sinusoidal cycles of the same amplitude (40°) but different duration, featuring a fast (FHC) and a slow half-cycle (SHC). Rotation consisted of four or 20 consecutive cycles to probe adaptation further with the longer duration protocol. Self-motion perception was estimated by subjects tracking with a pointer the remembered position of an earth-fixed visual target. VOR was measured by electro-oculography. The asymmetric stimulation pattern consistently induced a progressive increase of asymmetry in motion perception, whereby the gain of the tracking response gradually increased during FHCs and decreased during SHCs. The effect was observed already during the first few cycles and further increased during 20 cycles, leading to a totally distorted location of the initial straight-ahead. In contrast, after some initial interindividual variability, the gain of the slow phase VOR became symmetric, decreasing for FHCs and increasing for SHCs. These oppositely directed adaptive effects in motion perception and VOR persisted for nearly an hour. Control conditions using prolonged but symmetrical stimuli produced no adaptive effects on either motion perception or VOR. These findings show that prolonged asymmetric activation of the vestibular system leads to opposite patterns of adaptation of self-motion perception and VOR. The results provide strong evidence that semicircular canal inputs are processed centrally by independent mechanisms for perception of body motion and eye movement control. These divergent adaptation mechanisms enhance awareness of movement toward the faster body rotation, while improving the eye stabilizing properties of the VOR. PMID:23318876

Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

PubMed Central

Steiner, Christopher F.

2012-01-01

The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Experiment M131. Human vestibular function

NASA Technical Reports Server (NTRS)

Graybiel, A.; Miller, E. F., II; Homick, J. L.

1977-01-01

The lower susceptibility to vestibular stimulation aloft, compared with that on ground under experimental conditions, is attributed to a precondition, namely, either there is no need to adapt, or, as exemplified by the Skylab 3 pilot, adaptation to weightlessness is achieved. Findings in some of the astronauts emphasize the distinction between two categories of vestibular side effects: immediate reflex phenomena (illusions, sensations of turning, etc.), and delayed epiphenomena that include the constellation of symptoms and syndromes comprising motion sickness. The drug combinations 1-scopolamine and d-amphetamine and promethazine hydrochloride and ephedrine sulfate are effective in prevention and treatment of motion sickness. It is concluded that prevention of motion sickness in any stressful motion environment involves selection, adaptation, and the use of drugs.

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

Fast Compressive Tracking.

PubMed

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

A frequency-domain estimator for use in adaptive control systems

NASA Technical Reports Server (NTRS)

Lamaire, Richard O.; Valavani, Lena; Athans, Michael; Stein, Gunter

1991-01-01

This paper presents a frequency-domain estimator that can identify both a parametrized nominal model of a plant as well as a frequency-domain bounding function on the modeling error associated with this nominal model. This estimator, which we call a robust estimator, can be used in conjunction with a robust control-law redesign algorithm to form a robust adaptive controller.

Human Age Estimation Method Robust to Camera Sensor and/or Face Movement

PubMed Central

Nguyen, Dat Tien; Cho, So Ra; Pham, Tuyen Danh; Park, Kang Ryoung

2015-01-01

Human age can be employed in many useful real-life applications, such as customer service systems, automatic vending machines, entertainment, etc. In order to obtain age information, image-based age estimation systems have been developed using information from the human face. However, limitations exist for current age estimation systems because of the various factors of camera motion and optical blurring, facial expressions, gender, etc. Motion blurring can usually be presented on face images by the movement of the camera sensor and/or the movement of the face during image acquisition. Therefore, the facial feature in captured images can be transformed according to the amount of motion, which causes performance degradation of age estimation systems. In this paper, the problem caused by motion blurring is addressed and its solution is proposed in order to make age estimation systems robust to the effects of motion blurring. Experiment results show that our method is more efficient for enhancing age estimation performance compared with systems that do not employ our method. PMID:26334282

Robustness and management adaptability in tropical rangelands: a viability-based assessment under the non-equilibrium paradigm.

PubMed

Accatino, F; Sabatier, R; De Michele, C; Ward, D; Wiegand, K; Meyer, K M

2014-08-01

Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.

A Robust Design Methodology for Optimal Microscale Secondary Flow Control in Compact Inlet Diffusers

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Keller, Dennis J.

2001-01-01

It is the purpose of this study to develop an economical Robust design methodology for microscale secondary flow control in compact inlet diffusers. To illustrate the potential of economical Robust Design methodology, two different mission strategies were considered for the subject inlet, namely Maximum Performance and Maximum HCF Life Expectancy. The Maximum Performance mission maximized total pressure recovery while the Maximum HCF Life Expectancy mission minimized the mean of the first five Fourier harmonic amplitudes, i.e., 'collectively' reduced all the harmonic 1/2 amplitudes of engine face distortion. Each of the mission strategies was subject to a low engine face distortion constraint, i.e., DC60<0.10, which is a level acceptable for commercial engines. For each of these missions strategies, an 'Optimal Robust' (open loop control) and an 'Optimal Adaptive' (closed loop control) installation was designed over a twenty degree angle-of-incidence range. The Optimal Robust installation used economical Robust Design methodology to arrive at a single design which operated over the entire angle-of-incident range (open loop control). The Optimal Adaptive installation optimized all the design parameters at each angle-of-incidence. Thus, the Optimal Adaptive installation would require a closed loop control system to sense a proper signal for each effector and modify that effector device, whether mechanical or fluidic, for optimal inlet performance. In general, the performance differences between the Optimal Adaptive and Optimal Robust installation designs were found to be marginal. This suggests, however, that Optimal Robust open loop installation designs can be very competitive with Optimal Adaptive close loop designs. Secondary flow control in inlets is inherently robust, provided it is optimally designed. Therefore, the new methodology presented in this paper, combined array 'Lower Order' approach to Robust DOE, offers the aerodynamicist a very viable and economical way of exploring the concept of Robust inlet design, where the mission variables are brought directly into the inlet design process and insensitivity or robustness to the mission variables becomes a design objective.

Motion compensation for cone-beam CT using Fourier consistency conditions

NASA Astrophysics Data System (ADS)

Berger, M.; Xia, Y.; Aichinger, W.; Mentl, K.; Unberath, M.; Aichert, A.; Riess, C.; Hornegger, J.; Fahrig, R.; Maier, A.

2017-09-01

In cone-beam CT, involuntary patient motion and inaccurate or irreproducible scanner motion substantially degrades image quality. To avoid artifacts this motion needs to be estimated and compensated during image reconstruction. In previous work we showed that Fourier consistency conditions (FCC) can be used in fan-beam CT to estimate motion in the sinogram domain. This work extends the FCC to 3\\text{D} cone-beam CT. We derive an efficient cost function to compensate for 3\\text{D} motion using 2\\text{D} detector translations. The extended FCC method have been tested with five translational motion patterns, using a challenging numerical phantom. We evaluated the root-mean-square-error and the structural-similarity-index between motion corrected and motion-free reconstructions. Additionally, we computed the mean-absolute-difference (MAD) between the estimated and the ground-truth motion. The practical applicability of the method is demonstrated by application to respiratory motion estimation in rotational angiography, but also to motion correction for weight-bearing imaging of knees. Where the latter makes use of a specifically modified FCC version which is robust to axial truncation. The results show a great reduction of motion artifacts. Accurate estimation results were achieved with a maximum MAD value of 708 μm and 1184 μm for motion along the vertical and horizontal detector direction, respectively. The image quality of reconstructions obtained with the proposed method is close to that of motion corrected reconstructions based on the ground-truth motion. Simulations using noise-free and noisy data demonstrate that FCC are robust to noise. Even high-frequency motion was accurately estimated leading to a considerable reduction of streaking artifacts. The method is purely image-based and therefore independent of any auxiliary data.

Modeling rate sensitivity of exercise transient responses to limb motion.

PubMed

Yamashiro, Stanley M; Kato, Takahide

2014-10-01

Transient responses of ventilation (V̇e) to limb motion can exhibit predictive characteristics. In response to a change in limb motion, a rapid change in V̇e is commonly observed with characteristics different than during a change in workload. This rapid change has been attributed to a feed-forward or adaptive response. Rate sensitivity was explored as a specific hypothesis to explain predictive V̇e responses to limb motion. A simple model assuming an additive feed-forward summation of V̇e proportional to the rate of change of limb motion was studied. This model was able to successfully account for the adaptive phase correction observed during human sinusoidal changes in limb motion. Adaptation of rate sensitivity might also explain the reduction of the fast component of V̇e responses previously reported following sudden exercise termination. Adaptation of the fast component of V̇e response could occur by reduction of rate sensitivity. Rate sensitivity of limb motion was predicted by the model to reduce the phase delay between limb motion and V̇e response without changing the steady-state response to exercise load. In this way, V̇e can respond more quickly to an exercise change without interfering with overall feedback control. The asymmetry between responses to an incremental and decremental ramp change in exercise can also be accounted for by the proposed model. Rate sensitivity leads to predicted behavior, which resembles responses observed in exercise tied to expiratory reserve volume. Copyright © 2014 the American Physiological Society.

Visuomotor adaptation to a visual rotation is gravity dependent.

PubMed

Toma, Simone; Sciutti, Alessandra; Papaxanthis, Charalambos; Pozzo, Thierry

2015-03-15

Humans perform vertical and horizontal arm motions with different temporal patterns. The specific velocity profiles are chosen by the central nervous system by integrating the gravitational force field to minimize energy expenditure. However, what happens when a visuomotor rotation is applied, so that a motion performed in the horizontal plane is perceived as vertical? We investigated the dynamic of the adaptation of the spatial and temporal properties of a pointing motion during prolonged exposure to a 90° visuomotor rotation, where a horizontal movement was associated with a vertical visual feedback. We found that participants immediately adapted the spatial parameters of motion to the conflicting visual scene in order to keep their arm trajectory straight. In contrast, the initial symmetric velocity profiles specific for a horizontal motion were progressively modified during the conflict exposure, becoming more asymmetric and similar to those appropriate for a vertical motion. Importantly, this visual effect that increased with repetitions was not followed by a consistent aftereffect when the conflicting visual feedback was absent (catch and washout trials). In a control experiment we demonstrated that an intrinsic representation of the temporal structure of perceived vertical motions could provide the error signal allowing for this progressive adaptation of motion timing. These findings suggest that gravity strongly constrains motor learning and the reweighting process between visual and proprioceptive sensory inputs, leading to the selection of a motor plan that is suboptimal in terms of energy expenditure. Copyright © 2015 the American Physiological Society.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

PubMed

Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T

2014-07-15

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www.brainwavelet.org. Copyright © 2014. Published by Elsevier Inc.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

PubMed Central

Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.

2014-01-01

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www.brainwavelet.org. PMID:24657353

Space motion sickness preflight adaptation training: preliminary studies with prototype trainers

NASA Technical Reports Server (NTRS)

Parker, D. E.; Rock, J. C.; von Gierke, H. E.; Ouyang, L.; Reschke, M. F.; Arrott, A. P.

1987-01-01

Preflight training frequently has been proposed as a potential solution to the problem of space motion sickness. The paper considers successively the otolith reinterpretation, the concept for a preflight adaptation trainer and the research with the Miami University Seesaw, the Wright Patterson Air-Force Base Dynamic Environment Simulator and the Visually Coupled Airborne Systems Simulator prototype adaptation trainers.

The tactile speed aftereffect depends on the speed of adapting motion across the skin rather than other spatiotemporal features

PubMed Central

Seizova-Cajic, Tatjana; Holcombe, Alex O.

2015-01-01

After prolonged exposure to a surface moving across the skin, this felt movement appears slower, a phenomenon known as the tactile speed aftereffect (tSAE). We asked which feature of the adapting motion drives the tSAE: speed, the spacing between texture elements, or the frequency with which they cross the skin. After adapting to a ridged moving surface with one hand, participants compared the speed of test stimuli on adapted and unadapted hands. We used surfaces with different spatial periods (SPs; 3, 6, 12 mm) that produced adapting motion with different combinations of adapting speed (20, 40, 80 mm/s) and temporal frequency (TF; 3.4, 6.7, 13.4 ridges/s). The primary determinant of tSAE magnitude was speed of the adapting motion, not SP or TF. This suggests that adaptation occurs centrally, after speed has been computed from SP and TF, and/or that it reflects a speed cue independent of those features in the first place (e.g., indentation force). In a second experiment, we investigated the properties of the neural code for speed. Speed tuning predicts that adaptation should be greatest for speeds at or near the adapting speed. However, the tSAE was always stronger when the adapting stimulus was faster (242 mm/s) than the test (30–143 mm/s) compared with when the adapting and test speeds were matched. These results give no indication of speed tuning and instead suggest that adaptation occurs at a level where an intensive code dominates. In an intensive code, the faster the stimulus, the more the neurons fire. PMID:26631149

Adaptive torque estimation of robot joint with harmonic drive transmission

NASA Astrophysics Data System (ADS)

Shi, Zhiguo; Li, Yuankai; Liu, Guangjun

2017-11-01

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

An extended Lagrangian method

NASA Technical Reports Server (NTRS)

Liou, Meng-Sing

1993-01-01

A unique formulation of describing fluid motion is presented. The method, referred to as 'extended Lagrangian method', is interesting from both theoretical and numerical points of view. The formulation offers accuracy in numerical solution by avoiding numerical diffusion resulting from mixing of fluxes in the Eulerian description. Meanwhile, it also avoids the inaccuracy incurred due to geometry and variable interpolations used by the previous Lagrangian methods. The present method is general and capable of treating subsonic flows as well as supersonic flows. The method proposed in this paper is robust and stable. It automatically adapts to flow features without resorting to clustering, thereby maintaining rather uniform grid spacing throughout and large time step. Moreover, the method is shown to resolve multidimensional discontinuities with a high level of accuracy, similar to that found in 1D problems.

Robust high-performance control for robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1989-01-01

A robust control scheme to accomplish accurate trajectory tracking for an integrated system of manipulator-plus-actuators is proposed. The control scheme comprises a feedforward and a feedback controller. The feedforward controller contains any known part of the manipulator dynamics that can be used for online control. The feedback controller consists of adaptive position and velocity feedback gains and an auxiliary signal which is simply generated by a fixed-gain proportional/integral/derivative controller. The feedback controller is updated by very simple adaptation laws which contain both proportional and integral adaptation terms. By introduction of a simple sigma modification to the adaptation laws, robustness is guaranteed in the presence of unmodeled dynamics and disturbances.

CPG-inspired workspace trajectory generation and adaptive locomotion control for quadruped robots.

PubMed

Liu, Chengju; Chen, Qijun; Wang, Danwei

2011-06-01

This paper deals with the locomotion control of quadruped robots inspired by the biological concept of central pattern generator (CPG). A control architecture is proposed with a 3-D workspace trajectory generator and a motion engine. The workspace trajectory generator generates adaptive workspace trajectories based on CPGs, and the motion engine realizes joint motion imputes. The proposed architecture is able to generate adaptive workspace trajectories online by tuning the parameters of the CPG network to adapt to various terrains. With feedback information, a quadruped robot can walk through various terrains with adaptive joint control signals. A quadruped platform AIBO is used to validate the proposed locomotion control system. The experimental results confirm the effectiveness of the proposed control architecture. A comparison by experiments shows the superiority of the proposed method against the traditional CPG-joint-space control method.

Adaptive time-stepping Monte Carlo integration of Coulomb collisions

NASA Astrophysics Data System (ADS)

Särkimäki, K.; Hirvijoki, E.; Terävä, J.

2018-01-01

We report an accessible and robust tool for evaluating the effects of Coulomb collisions on a test particle in a plasma that obeys Maxwell-Jüttner statistics. The implementation is based on the Beliaev-Budker collision integral which allows both the test particle and the background plasma to be relativistic. The integration method supports adaptive time stepping, which is shown to greatly improve the computational efficiency. The Monte Carlo method is implemented for both the three-dimensional particle momentum space and the five-dimensional guiding center phase space. Detailed description is provided for both the physics and implementation of the operator. The focus is in adaptive integration of stochastic differential equations, which is an overlooked aspect among existing Monte Carlo implementations of Coulomb collision operators. We verify that our operator converges to known analytical results and demonstrate that careless implementation of the adaptive time step can lead to severely erroneous results. The operator is provided as a self-contained Fortran 95 module and can be included into existing orbit-following tools that trace either the full Larmor motion or the guiding center dynamics. The adaptive time-stepping algorithm is expected to be useful in situations where the collision frequencies vary greatly over the course of a simulation. Examples include the slowing-down of fusion products or other fast ions, and the Dreicer generation of runaway electrons as well as the generation of fast ions or electrons with ion or electron cyclotron resonance heating.

Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

NASA Technical Reports Server (NTRS)

Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

2010-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

Proprioceptive recalibration in the right and left hands following abrupt visuomotor adaptation.

PubMed

Salomonczyk, Danielle; Henriques, Denise Y P; Cressman, Erin K

2012-03-01

Previous studies have demonstrated that after reaching with misaligned visual feedback of the hand, one adapts his or her reaches and partially recalibrates proprioception, such that sense of felt hand position is shifted to match the seen hand position. However, to date, this has only been demonstrated in the right (dominant) hand following reach training with a visuomotor distortion in which the rotated cursor distortion was introduced gradually. As reach adaptation has been shown to differ depending on how the distortion is introduced (gradual vs. abrupt), we sought to examine proprioceptive recalibration following reach training with a cursor that was abruptly rotated 30° clockwise relative to hand motion. Furthermore, because the left and right arms have demonstrated selective advantages when matching visual and proprioceptive targets, respectively, we assessed proprioceptive recalibration in right-handed subjects following training with either the right or the left hand. On average, we observed shifts in felt hand position of approximately 7.6° following training with misaligned visual feedback of the hand, which is consistent with our previous findings in which the distortion was introduced gradually. Moreover, no difference was observed in proprioceptive recalibration across the left and right hands. These findings suggest that proprioceptive recalibration is a robust process that arises symmetrically in the two hands following visuomotor adaptation regardless of the initial magnitude of the error signal.

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A mathematical model of the creative control process is presented that illustrates the use for mobile robots. Examples from a variety of intelligent mobile robot applications are also presented. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots that could lead to many applications.

Funnel Libraries for Real-Time Robust Feedback Motion Planning

DTIC Science & Technology

2016-07-21

motion plans for a robot that are guaranteed to suc- ceed despite uncertainty in the environment, parametric model uncertainty, and disturbances...resulting funnel library is then used to sequentially compose motion plans at runtime while ensuring the safety of the robot . A major advantage of...the work presented here is that by explicitly taking into account the effect of uncertainty, the robot can evaluate motion plans based on how vulnerable

Probabilistic reconstruction of GPS vertical ground motion and comparison with GIA models

NASA Astrophysics Data System (ADS)

Husson, Laurent; Bodin, Thomas; Choblet, Gael; Kreemer, Corné

2017-04-01

The vertical position time-series of GPS stations have become long enough for many parts of the world to infer modern rates of vertical ground motion. We use the worldwide compilation of GPS trend velocities of the Nevada Geodetic Laboratory. Those rates are inferred by applying the MIDAS algorithm (Blewitt et al., 2016) to time-series obtained from publicly available data from permanent stations. Because MIDAS filters out seasonality and discontinuities, regardless of their causes, it gives robust long-term rates of vertical ground motion (except where there is significant postseismic deformation). As the stations are unevenly distributed, and because data errors are also highly variable, sometimes to an unknown degree, we use a Bayesian inference method to reconstruct 2D maps of vertical ground motion. Our models are based on a Voronoi tessellation and self-adapt to the spatially variable level of information provided by the data. Instead of providing a unique interpolated surface, each point of the reconstructed surface is defined through a probability density function. We apply our method to a series of vast regions covering entire continents. Not surprisingly, the reconstructed surface at a long wavelength is dominated by the GIA. This result can be exploited to evaluate whether forward models of GIA reproduce geodetic rates within the uncertainties derived from our interpolation, not only at high latitudes where postglacial rebound is fast, but also in more temperate latitudes where, for instance, such rates may compete with modern sea level rise. At shorter wavelengths, the reconstructed surface of vertical ground motion features a variety of identifiable patterns, whose geometries and rates can be mapped. Examples are transient dynamic topography over the convecting mantle, actively deforming domains (mountain belts and active margins), volcanic areas, or anthropogenic contributions.

A Nonlinear, Human-Centered Approach to Motion Cueing with a Neurocomputing Solver

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Cardullo, Frank M.; Houck, Jacob A.

2002-01-01

This paper discusses the continuation of research into the development of new motion cueing algorithms first reported in 1999. In this earlier work, two viable approaches to motion cueing were identified: the coordinated adaptive washout algorithm or 'adaptive algorithm', and the 'optimal algorithm'. In this study, a novel approach to motion cueing is discussed that would combine features of both algorithms. The new algorithm is formulated as a linear optimal control problem, incorporating improved vestibular models and an integrated visual-vestibular motion perception model previously reported. A control law is generated from the motion platform states, resulting in a set of nonlinear cueing filters. The time-varying control law requires the matrix Riccati equation to be solved in real time. Therefore, in order to meet the real time requirement, a neurocomputing approach is used to solve this computationally challenging problem. Single degree-of-freedom responses for the nonlinear algorithm were generated and compared to the adaptive and optimal algorithms. Results for the heave mode show the nonlinear algorithm producing a motion cue with a time-varying washout, sustaining small cues for a longer duration and washing out larger cues more quickly. The addition of the optokinetic influence from the integrated perception model was shown to improve the response to a surge input, producing a specific force response with no steady-state washout. Improved cues are also observed for responses to a sway input. Yaw mode responses reveal that the nonlinear algorithm improves the motion cues by reducing the magnitude of negative cues. The effectiveness of the nonlinear algorithm as compared to the adaptive and linear optimal algorithms will be evaluated on a motion platform, the NASA Langley Research Center Visual Motion Simulator (VMS), and ultimately the Cockpit Motion Facility (CMF) with a series of pilot controlled maneuvers. A proposed experimental procedure is discussed. The results of this evaluation will be used to assess motion cueing performance.

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

NASA Astrophysics Data System (ADS)

Chen, Xianshun; Feng, Liang; Ong, Yew Soon

2012-07-01

In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

Real-time physics-based 3D biped character animation using an inverted pendulum model.

PubMed

Tsai, Yao-Yang; Lin, Wen-Chieh; Cheng, Kuangyou B; Lee, Jehee; Lee, Tong-Yee

2010-01-01

We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.

TU-AB-BRB-01: Coverage Evaluation and Probabilistic Treatment Planning as a Margin Alternative

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siebers, J.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

TU-AB-BRB-00: New Methods to Ensure Target Coverage

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2015-06-15

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

Analysis and Synthesis of Robust Data Structures

DTIC Science & Technology

1990-08-01

1.3.2 Multiversion Software. .. .. .. .. .. .... .. ... .. ...... 5 1.3.3 Robust Data Structure .. .. .. .. .. .. .. .. .. ... .. ..... 6 1.4...context are 0 multiversion software, which is an adaptation oi N-modulo redundancy (NMR) tech- nique. * recovery blocks, which is an adaptation of...implementations using these features for such a hybrid approach. 1.3.2 Multiversion Software Avizienis [AC77] was the first to adapt NMR technique into

The topological requirements for robust perfect adaptation in networks of any size.

PubMed

Araujo, Robyn P; Liotta, Lance A

2018-05-01

Robustness, and the ability to function and thrive amid changing and unfavorable environments, is a fundamental requirement for living systems. Until now it has been an open question how large and complex biological networks can exhibit robust behaviors, such as perfect adaptation to a variable stimulus, since complexity is generally associated with fragility. Here we report that all networks that exhibit robust perfect adaptation (RPA) to a persistent change in stimulus are decomposable into well-defined modules, of which there exist two distinct classes. These two modular classes represent a topological basis for all RPA-capable networks, and generate the full set of topological realizations of the internal model principle for RPA in complex, self-organizing, evolvable bionetworks. This unexpected result supports the notion that evolutionary processes are empowered by simple and scalable modular design principles that promote robust performance no matter how large or complex the underlying networks become.

A Self-Synthesis Approach to Perceptual Learning for Multisensory Fusion in Robotics

PubMed Central

Axenie, Cristian; Richter, Christoph; Conradt, Jörg

2016-01-01

Biological and technical systems operate in a rich multimodal environment. Due to the diversity of incoming sensory streams a system perceives and the variety of motor capabilities a system exhibits there is no single representation and no singular unambiguous interpretation of such a complex scene. In this work we propose a novel sensory processing architecture, inspired by the distributed macro-architecture of the mammalian cortex. The underlying computation is performed by a network of computational maps, each representing a different sensory quantity. All the different sensory streams enter the system through multiple parallel channels. The system autonomously associates and combines them into a coherent representation, given incoming observations. These processes are adaptive and involve learning. The proposed framework introduces mechanisms for self-creation and learning of the functional relations between the computational maps, encoding sensorimotor streams, directly from the data. Its intrinsic scalability, parallelisation, and automatic adaptation to unforeseen sensory perturbations make our approach a promising candidate for robust multisensory fusion in robotic systems. We demonstrate this by applying our model to a 3D motion estimation on a quadrotor. PMID:27775621

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.

PubMed

Huang, Lvwen; Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-08-23

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor

PubMed Central

Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-01-01

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields. PMID:28832520

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

High degree-of-freedom dynamic manipulation

NASA Astrophysics Data System (ADS)

Murphy, Michael P.; Stephens, Benjamin; Abe, Yeuhi; Rizzi, Alfred A.

2012-06-01

The creation of high degree of freedom dynamic mobile manipulation techniques and behaviors will allow robots to accomplish difficult tasks in the field. We are investigating the use of the body and legs of legged robots to improve the strength, velocity, and workspace of an integrated manipulator to accomplish dynamic manipulation. This is an especially challenging task, as all of the degrees of freedom are active at all times, the dynamic forces generated are high, and the legged system must maintain robust balance throughout the duration of the tasks. To accomplish this goal, we are utilizing trajectory optimization techniques to generate feasible open-loop behaviors for our 28 dof quadruped robot (BigDog) by planning the trajectories in a 13 dimensional space. Covariance Matrix Adaptation techniques are utilized to optimize for several criteria such as payload capability and task completion speed while also obeying constraints such as torque and velocity limits, kinematic limits, and center of pressure location. These open-loop behaviors are then used to generate feed-forward terms, which are subsequently used online to improve tracking and maintain low controller gains. Some initial results on one of our existing balancing quadruped robots with an additional human-arm-like manipulator are demonstrated on robot hardware, including dynamic lifting and throwing of heavy objects 16.5kg cinder blocks, using motions that resemble a human athlete more than typical robotic motions. Increased payload capacity is accomplished through coordinated body motion.

Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

PubMed

Huang, X N; Ren, H P

2016-05-13

Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation.

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Singularity-robustness and task-prioritization in configuration control of redundant robots

NASA Technical Reports Server (NTRS)

Seraji, H.; Colbaugh, R.

1990-01-01

The authors present a singularity-robust task-prioritized reformulation of the configuration control for redundant robot manipulators. This reformation suppresses large joint velocities to induce minimal errors in the task performance by modifying the task trajectories. Furthermore, the same framework provides a means for assignment of priorities between the basic task of end-effector motion and the user-defined additional task for utilizing redundancy. This allows automatic relaxation of the additional task constraints in favor of the desired end-effector motion when both cannot be achieved exactly.

Evaluating a robust contour tracker on echocardiographic sequences.

PubMed

Jacob, G; Noble, J A; Mulet-Parada, M; Blake, A

1999-03-01

In this paper we present an evaluation of a robust visual image tracker on echocardiographic image sequences. We show how the tracking framework can be customized to define an appropriate shape space that describes heart shape deformations that can be learnt from a training data set. We also investigate energy-based temporal boundary enhancement methods to improve image feature measurement. Results are presented demonstrating real-time tracking on real normal heart motion data sequences and abnormal synthesized and real heart motion data sequences. We conclude by discussing some of our current research efforts.

Relevance of phenotypic noise to adaptation and evolution.

PubMed

Kaneko, K; Furusawa, C

2008-09-01

Biological processes are inherently noisy, as highlighted in recent measurements of stochasticity in gene expression. Here, the authors show that such phenotypic noise is essential to the adaptation of organisms to a variety of environments and also to the evolution of robustness against mutations. First, the authors show that for any growing cell showing stochastic gene expression, the adaptive cellular state is inevitably selected by noise, without the use of a specific signal transduction network. In general, changes in any protein concentration in a cell are products of its synthesis minus dilution and degradation, both of which are proportional to the rate of cell growth. In an adaptive state, both the synthesis and dilution terms of proteins are large, and so the adaptive state is less affected by stochasticity in gene expression, whereas for a non-adaptive state, both terms are smaller, and so cells are easily knocked out of their original state by noise. This leads to a novel, generic mechanism for the selection of adaptive states. The authors have confirmed this selection by model simulations. Secondly, the authors consider the evolution of gene networks to acquire robustness of the phenotype against noise and mutation. Through simulations using a simple stochastic gene expression network that undergoes mutation and selection, the authors show that a threshold level of noise in gene expression is required for the network to acquire both types of robustness. The results reveal how the noise that cells encounter during growth and development shapes any network's robustness, not only to noise but also to mutations. The authors also establish a relationship between developmental and mutational robustness.

Evaluation of adaptation to visually induced motion sickness based on the maximum cross-correlation between pulse transmission time and heart rate.

PubMed

Sugita, Norihiro; Yoshizawa, Makoto; Abe, Makoto; Tanaka, Akira; Watanabe, Takashi; Chiba, Shigeru; Yambe, Tomoyuki; Nitta, Shin-ichi

2007-09-28

Computer graphics and virtual reality techniques are useful to develop automatic and effective rehabilitation systems. However, a kind of virtual environment including unstable visual images presented to wide field screen or a head mounted display tends to induce motion sickness. The motion sickness induced in using a rehabilitation system not only inhibits effective training but also may harm patients' health. There are few studies that have objectively evaluated the effects of the repetitive exposures to these stimuli on humans. The purpose of this study is to investigate the adaptation to visually induced motion sickness by physiological data. An experiment was carried out in which the same video image was presented to human subjects three times. We evaluated changes of the intensity of motion sickness they suffered from by a subjective score and the physiological index rho(max), which is defined as the maximum cross-correlation coefficient between heart rate and pulse wave transmission time and is considered to reflect the autonomic nervous activity. The results showed adaptation to visually-induced motion sickness by the repetitive presentation of the same image both in the subjective and the objective indices. However, there were some subjects whose intensity of sickness increased. Thus, it was possible to know the part in the video image which related to motion sickness by analyzing changes in rho(max) with time. The physiological index, rho(max), will be a good index for assessing the adaptation process to visually induced motion sickness and may be useful in checking the safety of rehabilitation systems with new image technologies.

Are face representations depth cue invariant?

PubMed

Dehmoobadsharifabadi, Armita; Farivar, Reza

2016-06-01

The visual system can process three-dimensional depth cues defining surfaces of objects, but it is unclear whether such information contributes to complex object recognition, including face recognition. The processing of different depth cues involves both dorsal and ventral visual pathways. We investigated whether facial surfaces defined by individual depth cues resulted in meaningful face representations-representations that maintain the relationship between the population of faces as defined in a multidimensional face space. We measured face identity aftereffects for facial surfaces defined by individual depth cues (Experiments 1 and 2) and tested whether the aftereffect transfers across depth cues (Experiments 3 and 4). Facial surfaces and their morphs to the average face were defined purely by one of shading, texture, motion, or binocular disparity. We obtained identification thresholds for matched (matched identity between adapting and test stimuli), non-matched (non-matched identity between adapting and test stimuli), and no-adaptation (showing only the test stimuli) conditions for each cue and across different depth cues. We found robust face identity aftereffect in both experiments. Our results suggest that depth cues do contribute to forming meaningful face representations that are depth cue invariant. Depth cue invariance would require integration of information across different areas and different pathways for object recognition, and this in turn has important implications for cortical models of visual object recognition.

Effect of light intensity on flight control and temporal properties of photoreceptors in bumblebees.

PubMed

Reber, Therese; Vähäkainu, Antti; Baird, Emily; Weckström, Matti; Warrant, Eric; Dacke, Marie

2015-05-01

To control flight, insects rely on the pattern of visual motion generated on the retina as they move through the environment. When light levels fall, vision becomes less reliable and flight control thus becomes more challenging. Here, we investigated the effect of light intensity on flight control by filming the trajectories of free-flying bumblebees (Bombus terrestris, Linnaeus 1758) in an experimental tunnel at different light levels. As light levels fell, flight speed decreased and the flight trajectories became more tortuous but the bees were still remarkably good at centring their flight about the tunnel's midline. To investigate whether this robust flight performance can be explained by visual adaptations in the bumblebee retina, we also examined the response speed of the green-sensitive photoreceptors at the same light intensities. We found that the response speed of the photoreceptors significantly decreased as light levels fell. This indicates that bumblebees have both behavioural (reduction in flight speed) and retinal (reduction in response speed of the photoreceptors) adaptations to allow them to fly in dim light. However, the more tortuous flight paths recorded in dim light suggest that these adaptations do not support flight with the same precision during the twilight hours of the day. © 2015. Published by The Company of Biologists Ltd.

Irradiation of the prostate and pelvic lymph nodes with an adaptive algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hwang, A. B.; Chen, J.; Nguyen, T. B.

2012-02-15

Purpose: The simultaneous treatment of pelvic lymph nodes and the prostate in radiotherapy for prostate cancer is complicated by the independent motion of these two target volumes. In this work, the authors study a method to adapt intensity modulated radiation therapy (IMRT) treatment plans so as to compensate for this motion by adaptively morphing the multileaf collimator apertures and adjusting the segment weights. Methods: The study used CT images, tumor volumes, and normal tissue contours from patients treated in our institution. An IMRT treatment plan was then created using direct aperture optimization to deliver 45 Gy to the pelvic lymphmore » nodes and 50 Gy to the prostate and seminal vesicles. The prostate target volume was then shifted in either the anterior-posterior direction or in the superior-inferior direction. The treatment plan was adapted by adjusting the aperture shapes with or without re-optimizing the segment weighting. The dose to the target volumes was then determined for the adapted plan. Results: Without compensation for prostate motion, 1 cm shifts of the prostate resulted in an average decrease of 14% in D-95%. If the isocenter is simply shifted to match the prostate motion, the prostate receives the correct dose but the pelvic lymph nodes are underdosed by 14% {+-} 6%. The use of adaptive morphing (with or without segment weight optimization) reduces the average change in D-95% to less than 5% for both the pelvic lymph nodes and the prostate. Conclusions: Adaptive morphing with and without segment weight optimization can be used to compensate for the independent motion of the prostate and lymph nodes when combined with daily imaging or other methods to track the prostate motion. This method allows the delivery of the correct dose to both the prostate and lymph nodes with only small changes to the dose delivered to the target volumes.« less

Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

PubMed Central

Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

2013-01-01

Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines. PMID:23408775

Real-time stylistic prediction for whole-body human motions.

PubMed

Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun

2012-01-01

The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Motion Cueing Algorithm Development: Initial Investigation and Redesign of the Algorithms

NASA Technical Reports Server (NTRS)

Telban, Robert J.; Wu, Weimin; Cardullo, Frank M.; Houck, Jacob A. (Technical Monitor)

2000-01-01

In this project four motion cueing algorithms were initially investigated. The classical algorithm generated results with large distortion and delay and low magnitude. The NASA adaptive algorithm proved to be well tuned with satisfactory performance, while the UTIAS adaptive algorithm produced less desirable results. Modifications were made to the adaptive algorithms to reduce the magnitude of undesirable spikes. The optimal algorithm was found to have the potential for improved performance with further redesign. The center of simulator rotation was redefined. More terms were added to the cost function to enable more tuning flexibility. A new design approach using a Fortran/Matlab/Simulink setup was employed. A new semicircular canals model was incorporated in the algorithm. With these changes results show the optimal algorithm has some advantages over the NASA adaptive algorithm. Two general problems observed in the initial investigation required solutions. A nonlinear gain algorithm was developed that scales the aircraft inputs by a third-order polynomial, maximizing the motion cues while remaining within the operational limits of the motion system. A braking algorithm was developed to bring the simulator to a full stop at its motion limit and later release the brake to follow the cueing algorithm output.

Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems.

PubMed

Wang, Ding; Liu, Derong; Zhang, Yun; Li, Hongyi

2018-01-01

In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton-Jacobi-Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Image-guided adaptive gating of lung cancer radiotherapy: a computer simulation study

NASA Astrophysics Data System (ADS)

Aristophanous, Michalis; Rottmann, Joerg; Park, Sang-June; Nishioka, Seiko; Shirato, Hiroki; Berbeco, Ross I.

2010-08-01

The purpose of this study is to investigate the effect that image-guided adaptation of the gating window during treatment could have on the residual tumor motion, by simulating different gated radiotherapy techniques. There are three separate components of this simulation: (1) the 'Hokkaido Data', which are previously measured 3D data of lung tumor motion tracks and the corresponding 1D respiratory signals obtained during the entire ungated radiotherapy treatments of eight patients, (2) the respiratory gating protocol at our institution and the imaging performed under that protocol and (3) the actual simulation in which the Hokkaido Data are used to select tumor position information that could have been collected based on the imaging performed under our gating protocol. We simulated treatments with a fixed gating window and a gating window that is updated during treatment. The patient data were divided into different fractions, each with continuous acquisitions longer than 2 min. In accordance to the imaging performed under our gating protocol, we assume that we have tumor position information for the first 15 s of treatment, obtained from kV fluoroscopy, and for the rest of the fractions the tumor position is only available during the beam-on time from MV imaging. The gating window was set according to the information obtained from the first 15 s such that the residual motion was less than 3 mm. For the fixed gating window technique the gate remained the same for the entire treatment, while for the adaptive technique the range of the tumor motion during beam-on time was measured and used to adapt the gating window to keep the residual motion below 3 mm. The algorithm used to adapt the gating window is described. The residual tumor motion inside the gating window was reduced on average by 24% for the patients with regular breathing patterns and the difference was statistically significant (p-value = 0.01). The magnitude of the residual tumor motion depended on the regularity of the breathing pattern suggesting that image-guided adaptive gating should be combined with breath coaching. The adaptive gating window technique was able to track the exhale position of the breathing cycle quite successfully. Out of a total of 53 fractions the duty cycle was greater than 20% for 42 fractions for the fixed gating window technique and for 39 fractions for the adaptive gating window technique. The results of this study suggest that real-time updating of the gating window can result in reliably low residual tumor motion and therefore can facilitate safe margin reduction.

A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts.

PubMed

Ye, Yalan; He, Wenwen; Cheng, Yunfei; Huang, Wenxia; Zhang, Zhilin

2017-02-16

The estimation of heart rate (HR) based on wearable devices is of interest in fitness. Photoplethysmography (PPG) is a promising approach to estimate HR due to low cost; however, it is easily corrupted by motion artifacts (MA). In this work, a robust approach based on random forest is proposed for accurately estimating HR from the photoplethysmography signal contaminated by intense motion artifacts, consisting of two stages. Stage 1 proposes a hybrid method to effectively remove MA with a low computation complexity, where two MA removal algorithms are combined by an accurate binary decision algorithm whose aim is to decide whether or not to adopt the second MA removal algorithm. Stage 2 proposes a random forest-based spectral peak-tracking algorithm, whose aim is to locate the spectral peak corresponding to HR, formulating the problem of spectral peak tracking into a pattern classification problem. Experiments on the PPG datasets including 22 subjects used in the 2015 IEEE Signal Processing Cup showed that the proposed approach achieved the average absolute error of 1.65 beats per minute (BPM) on the 22 PPG datasets. Compared to state-of-the-art approaches, the proposed approach has better accuracy and robustness to intense motion artifacts, indicating its potential use in wearable sensors for health monitoring and fitness tracking.

Decoherence of Topological Qubit in Linear Motions: Decoherence Impedance, Anti-Unruh and Information Backflow

NASA Astrophysics Data System (ADS)

Liu, Pei-Hua; Lin, Feng-Li

2017-08-01

In this work we study the decoherence of topological qubits in linear motions. The topological qubit is made of two spatially-separated Majorana zero modes which are the edge excitations of Kitaev chain [1]. In a previous work [2], it was shown by one of us and his collaborators that the decoherence of topological qubit is exactly solvable, moreover, topological qubit is robust against decoherence in the super-Ohmic environments. We extend the setup of [2] to consider the effect of motions on the decoherence of the topological qubits. Our results show the thermalization as expected by Unruh effect. Besides, we also find the so-called “anti-Unruh” phenomena which shows the rate of decoherence is anti-correlated with the acceleration in short-time scale. Moreover, we modulate the motion patterns of each Majorana modes and find information backflow and the preservation of coherence even with nonzero accelerations. This is the characteristics of the underlying non-Markovian reduced dynamics. We conclude that he topological qubit is in general more robust against decoherence than the usual qubits, and can be take into serious consideration for realistic implementation to have robust quantum computation and communication. This talk is based on our work in [3].

Locomotor Adaptation Improves Balance Control, Multitasking Ability and Reduces the Metabolic Cost of Postural Instability

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Brady, R. A.; Batson, C. D.; Miller, C. A.; Ploutz-Snyder, R. J.; Guined, J. R.; Buxton, R. E.; Cohen, H. S.

2011-01-01

During exploration-class missions, sensorimotor disturbances may lead to disruption in the ability to ambulate and perform functional tasks during the initial introduction to a novel gravitational environment following a landing on a planetary surface. The overall goal of our current project is to develop a sensorimotor adaptability training program to facilitate rapid adaptation to these environments. We have developed a unique training system comprised of a treadmill placed on a motion-base facing a virtual visual scene. It provides an unstable walking surface combined with incongruent visual flow designed to enhance sensorimotor adaptability. Greater metabolic cost incurred during balance instability means more physical work is required during adaptation to new environments possibly affecting crewmembers? ability to perform mission critical tasks during early surface operations on planetary expeditions. The goal of this study was to characterize adaptation to a discordant sensory challenge across a number of performance modalities including locomotor stability, multi-tasking ability and metabolic cost. METHODS: Subjects (n=15) walked (4.0 km/h) on a treadmill for an 8 -minute baseline walking period followed by 20-minutes of walking (4.0 km/h) with support surface motion (0.3 Hz, sinusoidal lateral motion, peak amplitude 25.4 cm) provided by the treadmill/motion-base system. Stride frequency and auditory reaction time were collected as measures of locomotor stability and multi-tasking ability, respectively. Metabolic data (VO2) were collected via a portable metabolic gas analysis system. RESULTS: At the onset of lateral support surface motion, subj ects walking on our treadmill showed an increase in stride frequency and auditory reaction time indicating initial balance and multi-tasking disturbances. During the 20-minute adaptation period, balance control and multi-tasking performance improved. Similarly, throughout the 20-minute adaptation period, VO2 gradually decreased following an initial increase after the onset of support surface motion. DISCUSSION: Resu lts confirmed that walking in discordant conditions not only compromises locomotor stability and the ability to multi-task, but comes at a quantifiable metabolic cost. Importantly, like locomotor stability and multi-tasking ability, metabolic expenditure while walking in discordant sensory conditions improved during adaptation. This confirms that sensorimotor adaptability training can benefit multiple performance parameters central to the successful completion of critical mission tasks.

Effective Use of Weigh-in-Motion Data : The Netherlands Case Study

DOT National Transportation Integrated Search

2007-10-01

Transportation and law enforcement agencies in the Netherlands have developed a robust weigh-in-motion (WIM) data management system that supports a broad array of vehicle weight regulation and enforcement activities, as well as long-term planning and...

Development and implementation of Inflight Neurosensory Training for Adaptation/Readaptation (INSTAR)

NASA Technical Reports Server (NTRS)

Harm, D. L.; Guedry, F. E.; Parker, Donald E.; Reschke, M. F.

1993-01-01

Resolution of space motion sickness, and improvements in spatial orientation, posture and motion control, and compensatory eye movements occur as a function of neurosensory and sensorimotor adaptation to microgravity. These adaptive responses, however, are inappropriate for return to Earth. Even following relatively brief space Shuttle missions, significant re-adaptation disturbances related to visual performance, locomotion, and perceived self-motion have been observed. Russian reports suggest that these disturbances increase with mission duration and may be severe following landing after prolonged microgravity exposure such as during a voyage to Mars. Consequently, there is a need to enable the astronauts to be prepared for and more quickly re-adapt to a gravitational environment following extended space missions. Several devices to meet this need are proposed including a virtual environment - centrifuge device (VECD). A short-arm centrifuge will provide centripetal acceleration parallel to the astronaut's longitudinal body axis and a restraint system will be configured to permit head movements only in the plane of rotation (to prevent 'cross-coupling'). A head-mounted virtual environment system will be used to develop appropriate 'calibration' between visual motion/orientation signals and inertial motion/orientation signals generated by the centrifuge. This will permit vestibular, visual and somatosensory signal matches to bias central interpretation of otolith signals toward the 'position' responses and to recalibrate the vestibulo-ocular reflex (VOR).

Image guided adaptive external beam radiation therapy for cervix cancer: Evaluation of a clinically implemented plan-of-the-day technique.

PubMed

Buschmann, Martin; Majercakova, Katarina; Sturdza, Alina; Smet, Stephanie; Najjari, Dina; Daniel, Michaela; Pötter, Richard; Georg, Dietmar; Seppenwoolde, Yvette

2017-10-12

Radiotherapy for cervix cancer is challenging in patients exhibiting large daily changes in the pelvic anatomy, therefore adaptive treatments (ART) have been proposed. The aim of this study was the clinical implementation and subsequent evaluation of plan-of-the-day (POTD)-ART for cervix cancer in supine positioning. The described workflow was based on standard commercial equipment and current quality assurance (QA) methods. A POTD strategy, which employs a VMAT plan library consisting of an empty bladder plan, a full bladder plan and a motion robust backup plan, was developed. Daily adaption was guided by cone beam computed tomography (CBCT) imaging after which the best plan from the library was selected. Sixteen patients were recruited in a clinical study on ART, for nine POTD was applied due to their large organ motion derived from two computed tomography (CT) scans with variable bladder filling. All patients were treated to 45Gy in 25 fractions. Plan selection frequencies over the treatment course were analyzed. Daily doses in the rectum, bladder and cervix-uterus target (CTV-T) were derived and compared to a simulated non-adapted treatment (non-ART), which employed the robust plan for each fraction. Additionally, the adaption consistency was determined by repeating the plan selection procedure one month after treatment by a group of experts. ART-specific QA methods are presented. 225 ART fractions with CBCTs were analyzed. The empty bladder plan was delivered in 49% of the fractions in the first treatment week and this number increased to 78% in the fifth week. The daily coverage of the CTV-T was equivalent between ART and the non-ART simulation, while the daily total irradiated volume V42.75Gy (95% of prescription dose) was reduced by a median of 87cm 3 . The median delivered V42.75Gy was 1782cm 3 . Daily delivered doses (V42.75Gy, V40Gy, V30G) to the organs at risk were statistically significantly reduced by ART, with a median difference in daily V42.75Gy in rectum and bladder of 3.2% and 1.1%, respectively. The daily bladder V42.75Gy and V40Gy were decreased by more than 10 percent points in 30% and 24% of all fractions, respectively, through ART. The agreement between delivered plans and retrospective expert-group plan selections was 84%. A POTD-ART technique for cervix cancer was successfully and safely implemented in the clinic and evaluated. Improved normal tissue sparing compared to a simulated non-ART treatment could be demonstrated. Future developments should focus on commercial automated software solutions to allow for a more widespread adoption and to keep the increased workload manageable. Copyright © 2017. Published by Elsevier GmbH.

Motion estimation of magnetic resonance cardiac images using the Wigner-Ville and hough transforms

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Bayerl, P.; Neumann, H.

2007-12-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation of the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach. More specifically it relies on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The latter is a well-known line and shape detection method that is highly robust against incomplete data and noise. The rationale of using the HT in this context is that it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results in the case of synthetic sequences are compared with an implementation of the variational technique for local and global motion estimation, where it is shown that the results are accurate and robust to noise degradations. Results obtained with real cardiac magnetic resonance images are presented.

A hybrid spatiotemporal and Hough-based motion estimation approach applied to magnetic resonance cardiac images

NASA Astrophysics Data System (ADS)

Carranza, N.; Cristóbal, G.; Sroubek, F.; Ledesma-Carbayo, M. J.; Santos, A.

2006-08-01

Myocardial motion analysis and quantification is of utmost importance for analyzing contractile heart abnormalities and it can be a symptom of a coronary artery disease. A fundamental problem in processing sequences of images is the computation of the optical flow, which is an approximation to the real image motion. This paper presents a new algorithm for optical flow estimation based on a spatiotemporal-frequency (STF) approach, more specifically on the computation of the Wigner-Ville distribution (WVD) and the Hough Transform (HT) of the motion sequences. The later is a well-known line and shape detection method very robust against incomplete data and noise. The rationale of using the HT in this context is because it provides a value of the displacement field from the STF representation. In addition, a probabilistic approach based on Gaussian mixtures has been implemented in order to improve the accuracy of the motion detection. Experimental results with synthetic sequences are compared against an implementation of the variational technique for local and global motion estimation, where it is shown that the results obtained here are accurate and robust to noise degradations. Real cardiac magnetic resonance images have been tested and evaluated with the current method.

Robust, Flexible Motion Control for the Mars Explorer Rovers

NASA Technical Reports Server (NTRS)

Maimone, Mark; Biesiadecki, Jeffrey

2007-01-01

The Mobility Flight Software, running on computers aboard the Mars Explorer Rover (MER) robotic vehicles Spirit and Opportunity, affords the robustness and flexibility of control to enable safe and effective operation of these vehicles in traversing natural terrain. It can make the vehicles perform specific maneuvers commanded from Earth, and/or can autonomously administer multiple aspects of mobility, including choice of motion, measurement of actual motion, and even selection of targets to be approached. Motion of a vehicle can be commanded by use of multiple layers of control, ranging from motor control at a low level, direct drive operations (e.g., motion along a circular arc, motion along a straight line, or turn in place) at an intermediate level to goal-position driving (that is, driving to a specified location) at a high level. The software can also perform high-level assessment of terrain and selection of safe paths across the terrain: this involves processing of the digital equivalent of a local traversability map generated from images acquired by stereoscopic pairs of cameras aboard the vehicles. Other functions of the software include interacting with the rest of the MER flight software and performing safety checks.

Turboprop IDEAL: a motion-resistant fat-water separation technique.

PubMed

Huo, Donglai; Li, Zhiqiang; Aboussouan, Eric; Karis, John P; Pipe, James G

2009-01-01

Suppression of the fat signal in MRI is very important for many clinical applications. Multi-point water-fat separation methods, such as IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation), can robustly separate water and fat signal, but inevitably increase scan time, making separated images more easily affected by patient motions. PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) and Turboprop techniques offer an effective approach to correct for motion artifacts. By combining these techniques together, we demonstrate that the new TP-IDEAL method can provide reliable water-fat separation with robust motion correction. The Turboprop sequence was modified to acquire source images, and motion correction algorithms were adjusted to assure the registration between different echo images. Theoretical calculations were performed to predict the optimal shift and spacing of the gradient echoes. Phantom images were acquired, and results were compared with regular FSE-IDEAL. Both T1- and T2-weighted images of the human brain were used to demonstrate the effectiveness of motion correction. TP-IDEAL images were also acquired for pelvis, knee, and foot, showing great potential of this technique for general clinical applications.

Robust design of configurations and parameters of adaptable products

NASA Astrophysics Data System (ADS)

Zhang, Jian; Chen, Yongliang; Xue, Deyi; Gu, Peihua

2014-03-01

An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

Robust Notion Vision For A Vehicle Moving On A Plane

NASA Astrophysics Data System (ADS)

Moni, Shankar; Weldon, E. J.

1987-05-01

A vehicle equipped with a cemputer vision system moves on a plane. We show that subject to certain constraints, the system can determine the motion of the vehicle (one rotational and two translational degrees of freedom) and the depth of the scene in front of the vehicle. The constraints include limits on the speed of the vehicle, presence of texture on the plane and absence of pitch and roll in the vehicular motion. It is possible to decouple the problems of finding the vehicle's motion and the depth of the scene in front of the vehicle by using two rigidly connected cameras. One views a field with known depth (i.e. the ground plane) and estimates the motion parameters and the other determines the depth map knowing the motion parameters. The motion is constrained to be planar to increase robustness. We use a least squares method of fitting the vehicle motion to observer brightness gradients. With this method, no correspondence between image points needs to be established and information fran the entire image is used in calculating notion. The algorithm performs very reliably on real image sequences and these results have been included. The results compare favourably to the performance of the algorithm of Negandaripour and Horn [2] where six degrees of freedom are assumed.

WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection.

PubMed

Gong, Liangyi; Yang, Wu; Man, Dapeng; Dong, Guozhong; Yu, Miao; Lv, Jiguang

2015-12-21

With the rapid development of WLAN technology, wireless device-free passive human detection becomes a newly-developing technique and holds more potential to worldwide and ubiquitous smart applications. Recently, indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Previous wireless device-free passive human detection systems either rely on deploying specialized systems with dense transmitter-receiver links or elaborate off-line training process, which blocks rapid deployment and weakens system robustness. In the paper, we explore to research a novel fine-grained real-time calibration-free device-free passive human motion via physical layer information, which is independent of indoor scenarios and needs no prior-calibration and normal profile. We investigate sensitivities of amplitude and phase to human motion, and discover that phase feature is more sensitive to human motion, especially to slow human motion. Aiming at lightweight and robust device-free passive human motion detection, we develop two novel and practical schemes: short-term averaged variance ratio (SVR) and long-term averaged variance ratio (LVR). We realize system design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve a high detection rate and low false positive rate.

WiFi-Based Real-Time Calibration-Free Passive Human Motion Detection †

PubMed Central

Gong, Liangyi; Yang, Wu; Man, Dapeng; Dong, Guozhong; Yu, Miao; Lv, Jiguang

2015-01-01

With the rapid development of WLAN technology, wireless device-free passive human detection becomes a newly-developing technique and holds more potential to worldwide and ubiquitous smart applications. Recently, indoor fine-grained device-free passive human motion detection based on the PHY layer information is rapidly developed. Previous wireless device-free passive human detection systems either rely on deploying specialized systems with dense transmitter-receiver links or elaborate off-line training process, which blocks rapid deployment and weakens system robustness. In the paper, we explore to research a novel fine-grained real-time calibration-free device-free passive human motion via physical layer information, which is independent of indoor scenarios and needs no prior-calibration and normal profile. We investigate sensitivities of amplitude and phase to human motion, and discover that phase feature is more sensitive to human motion, especially to slow human motion. Aiming at lightweight and robust device-free passive human motion detection, we develop two novel and practical schemes: short-term averaged variance ratio (SVR) and long-term averaged variance ratio (LVR). We realize system design with commercial WiFi devices and evaluate it in typical multipath-rich indoor scenarios. As demonstrated in the experiments, our approach can achieve a high detection rate and low false positive rate. PMID:26703612

Dosimetric evaluation of three adaptive strategies for prostate cancer treatment including pelvic lymph nodes irradiation.

PubMed

Cantin, Audrey; Gingras, Luc; Lachance, Bernard; Foster, William; Goudreault, Julie; Archambault, Louis

2015-12-01

The movements of the prostate relative to the pelvic lymph nodes during intensity-modulated radiation therapy treatment can limit margin reduction and affect the protection of the organs at risk (OAR). In this study, the authors performed an analysis of three adaptive treatment strategies that combine information from both bony and gold marker registrations. The robustness of those treatments against the interfraction prostate movements was evaluated. A retrospective study was conducted on five prostate cancer patients with 7-13 daily cone-beam CTs (CBCTs). The clinical target volumes (CTVs) consisting of pelvic lymph nodes, prostate, and seminal vesicles as well as the OARs were delineated on each CBCT and the initial CT. Three adaptive strategies were analyzed. Two of these methods relied on a two-step patient positioning at each fraction. First step: a bony registration was used to deliver the nodal CTV prescription. Second step: a gold marker registration was then used either to (1) complete the dose delivered to the prostate (complement); (2) or give almost the entire prescription to the prostate with a weak dose gradient between the targets to compensate for possible motions (gradient). The third method (COR) used a pool of precalculated plans based on images acquired at previous treatment fractions. At each new fraction, a plan is selected from that pool based on the daily position of prostate center-of-mass. The dosimetric comparison was conducted and results are presented with and without the systematic shift in the prostate position on the CT planning. The adaptive strategies were compared to the current clinical standard where all fractions are treated with the initial nonadaptive plan. The minimum daily prostate D95% is improved by 2%, 9%, and 6% for the complement, the gradient, and the COR approaches, respectively, compared to the nonadaptive method. The average nodal CTV D95% remains constant across the strategies, except for the gradient approach where a reduction of 7% is observed. However, a correction of the systematic shift reduced the problem, and the adaptive strategies remain robust against the prostate movement across the fraction. The bladder V55Gy is reduced by 35% on average for the adaptive strategies. Because they offer increased CTV coverage and OAR sparing, adaptive methods may be suitable candidates for simple and efficient adaptive treatment strategies for prostate cancer. Margin reduction and systematic error correction in the prostate position improve the protection of the OAR and the dose coverage. A cumulative dose to simulate a complete treatment would show real effects and allow a better comparison between each method.

Modification of Motion Perception and Manual Control Following Short-Durations Spaceflight

NASA Technical Reports Server (NTRS)

Wood, S. J.; Vanya, R. D.; Esteves, J. T.; Rupert, A. H.; Clement, G.

2011-01-01

Adaptive changes during space flight in how the brain integrates vestibular cues with other sensory information can lead to impaired movement coordination and spatial disorientation following G-transitions. This ESA-NASA study was designed to examine both the physiological basis and operational implications for disorientation and tilt-translation disturbances following short-duration spaceflights. The goals of this study were to (1) examine the effects of stimulus frequency on adaptive changes in motion perception during passive tilt and translation motion, (2) quantify decrements in manual control of tilt motion, and (3) evaluate vibrotactile feedback as a sensorimotor countermeasure.

Free-breathing volumetric fat/water separation by combining radial sampling, compressed sensing, and parallel imaging.

PubMed

Benkert, Thomas; Feng, Li; Sodickson, Daniel K; Chandarana, Hersh; Block, Kai Tobias

2017-08-01

Conventional fat/water separation techniques require that patients hold breath during abdominal acquisitions, which often fails and limits the achievable spatial resolution and anatomic coverage. This work presents a novel approach for free-breathing volumetric fat/water separation. Multiecho data are acquired using a motion-robust radial stack-of-stars three-dimensional GRE sequence with bipolar readout. To obtain fat/water maps, a model-based reconstruction is used that accounts for the off-resonant blurring of fat and integrates both compressed sensing and parallel imaging. The approach additionally enables generation of respiration-resolved fat/water maps by detecting motion from k-space data and reconstructing different respiration states. Furthermore, an extension is described for dynamic contrast-enhanced fat-water-separated measurements. Uniform and robust fat/water separation is demonstrated in several clinical applications, including free-breathing noncontrast abdominal examination of adults and a pediatric subject with both motion-averaged and motion-resolved reconstructions, as well as in a noncontrast breast exam. Furthermore, dynamic contrast-enhanced fat/water imaging with high temporal resolution is demonstrated in the abdomen and breast. The described framework provides a viable approach for motion-robust fat/water separation and promises particular value for clinical applications that are currently limited by the breath-holding capacity or cooperation of patients. Magn Reson Med 78:565-576, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

a Robust Method for Stereo Visual Odometry Based on Multiple Euclidean Distance Constraint and Ransac Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Q.; Tong, X.; Liu, S.; Lu, X.; Liu, S.; Chen, P.; Jin, Y.; Xie, H.

2017-07-01

Visual Odometry (VO) is a critical component for planetary robot navigation and safety. It estimates the ego-motion using stereo images frame by frame. Feature points extraction and matching is one of the key steps for robotic motion estimation which largely influences the precision and robustness. In this work, we choose the Oriented FAST and Rotated BRIEF (ORB) features by considering both accuracy and speed issues. For more robustness in challenging environment e.g., rough terrain or planetary surface, this paper presents a robust outliers elimination method based on Euclidean Distance Constraint (EDC) and Random Sample Consensus (RANSAC) algorithm. In the matching process, a set of ORB feature points are extracted from the current left and right synchronous images and the Brute Force (BF) matcher is used to find the correspondences between the two images for the Space Intersection. Then the EDC and RANSAC algorithms are carried out to eliminate mismatches whose distances are beyond a predefined threshold. Similarly, when the left image of the next time matches the feature points with the current left images, the EDC and RANSAC are iteratively performed. After the above mentioned, there are exceptional remaining mismatched points in some cases, for which the third time RANSAC is applied to eliminate the effects of those outliers in the estimation of the ego-motion parameters (Interior Orientation and Exterior Orientation). The proposed approach has been tested on a real-world vehicle dataset and the result benefits from its high robustness.

Improved motion correction in PROPELLER by using grouped blades as reference.

PubMed

Liu, Zhe; Zhang, Zhe; Ying, Kui; Yuan, Chun; Guo, Hua

2014-03-01

To develop a robust reference generation method for improving PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) reconstruction. A new reference generation method, grouped-blade reference (GBR), is proposed for calculating rotation angle and translation shift in PROPELLER. Instead of using a single-blade reference (SBR) or combined-blade reference (CBR), our method classifies blades by their relative correlations and groups similar blades together as the reference to prevent inconsistent data from interfering the correction process. Numerical simulations and in vivo experiments were used to evaluate the performance of GBR for PROPELLER, which was further compared with SBR and CBR in terms of error level and computation cost. Both simulation and in vivo experiments demonstrate that GBR-based PROPELLER provides better correction for random motion or bipolar motion comparing with SBR or CBR. It not only produces images with lower error level but also needs less iteration steps to converge. A grouped-blade for reference selection was investigated for PROPELLER MRI. It helps to improve the accuracy and robustness of motion correction for various motion patterns. Copyright © 2013 Wiley Periodicals, Inc.

Motion Evaluation for Rehabilitation Training of the Disabled

NASA Astrophysics Data System (ADS)

Kim, Tae-Young; Park, Jun; Lim, Cheol-Su

In this paper, a motion evaluation technique for rehabilitation training is introduced. Motion recognition technologies have been developed for determining matching motions in the training set. However, we need to measure how well and how much of the motion has been followed for training motion evaluation. We employed a Finite State Machine as a framework of motion evaluation. For similarity analysis, we used weighted angular value differences although any template matching algorithm may be used. For robustness under illumination changes, IR LED's and cameras with IR-pass filter were used. Developed technique was successfully used for rehabilitation training of the disabled. Therapists appraised the system as practically useful.

Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

NASA Technical Reports Server (NTRS)

Burken, John J.

2005-01-01

This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

Reservoir adaptive operating rules based on both of historical streamflow and future projections

NASA Astrophysics Data System (ADS)

Zhang, Wei; Liu, Pan; Wang, Hao; Chen, Jie; Lei, Xiaohui; Feng, Maoyuan

2017-10-01

Climate change is affecting hydrological variables and consequently is impacting water resources management. Historical strategies are no longer applicable under climate change. Therefore, adaptive management, especially adaptive operating rules for reservoirs, has been developed to mitigate the possible adverse effects of climate change. However, to date, adaptive operating rules are generally based on future projections involving uncertainties under climate change, yet ignoring historical information. To address this, we propose an approach for deriving adaptive operating rules considering both historical information and future projections, namely historical and future operating rules (HAFOR). A robustness index was developed by comparing benefits from HAFOR with benefits from conventional operating rules (COR). For both historical and future streamflow series, maximizations of both average benefits and the robustness index were employed as objectives, and four trade-offs were implemented to solve the multi-objective problem. Based on the integrated objective, the simulation-based optimization method was used to optimize the parameters of HAFOR. Using the Dongwushi Reservoir in China as a case study, HAFOR was demonstrated to be an effective and robust method for developing adaptive operating rules under the uncertain changing environment. Compared with historical or projected future operating rules (HOR or FPOR), HAFOR can reduce the uncertainty and increase the robustness for future projections, especially regarding results of reservoir releases and volumes. HAFOR, therefore, facilitates adaptive management in the context that climate change is difficult to predict accurately.

A Hypothetical Perspective on the Relative Contributions of Strategic and Adaptive Control Mechanisms in Plastic Recalibration of Locomotor Heading Direction

NASA Technical Reports Server (NTRS)

Richards, J. T.; Mulavara, A. P.; Ruttley, T.; Peters, B. T.; Warren, L. E.; Bloomberg, J. J.

2006-01-01

We have previously shown that viewing simulated rotary self-motion during treadmill locomotion causes adaptive modification of the control of position and trajectory during over-ground locomotion, which functionally reflects adaptive changes in the sensorimotor integration of visual, vestibular, and proprioceptive cues (Mulavara et al., 2005). The objective of this study was to investigate how strategic changes in torso control during exposure to simulated rotary self-motion during treadmill walking influences adaptive modification of locomotor heading direction during over-ground stepping.

Sculpting Pickering Emulsion Droplets by Arrest and Jamming

NASA Astrophysics Data System (ADS)

Burke, Christopher; Wei, Zengyi; Caggioni, Marco; Spicer, Patrick; Atherton, Tim

Pickering emulsion droplets can be arrested into non-spherical shapes--useful for applications such as active delivery--through a general mechanism of deformation followed by absorption of additional colloidal particles onto the interface, relaxation of the droplet caused by surface tension and arrest at some point due to crowding of the particles. We perform simulations of the arrest process to clarify the relative importance of diffusive rearrangement of particles and collective forcing due to surface evolution. Experiment and theory are compared, giving insight into the stability of the resulting capsules and the robustness of the production process for higher-throughput production in, for example, microfluidic systems. We adapt theoretical tools from the jamming literature to better understand the arrested configurations and long timescale evolution of the system: using linear programming and a penalty function approach, we identify unjamming motions in kinetically arrested states. We propose a paradigm of ``metric jamming'' to describe the limiting behavior of this class of system: a structure is metric-jammed if it is stable with respect to collective motion of the particles as well as evolution of the hypersurface on which the packing is embedded. Supported by a Cottrell Award from the Research Corporation for Science Advancement.

Full drive-by-wire dynamic control for four-wheel-steer all-wheel-drive vehicles

NASA Astrophysics Data System (ADS)

Fahimi, Farbod

2013-03-01

Most of the controllers introduced for four-wheel-steer (4WS) vehicles are derived with the assumption that the longitudinal speed of the vehicle is constant. However, in real applications, the longitudinal speed varies, and the longitudinal, lateral, and yaw dynamics are coupled. In this paper, the longitudinal dynamics of the vehicle as well as its lateral and yaw motions are controlled simultaneously. This way, the effect of driving/braking forces of the tires on the lateral and yaw motions of the vehicle are automatically included in the control laws. To address the dynamic parameter uncertainty of the vehicle, a chatter-free variable structure controller is introduced. Elimination of chatter is achieved by introducing a dynamically adaptive boundary layer thickness. It is shown via simulations that the proposed control approach performs more robustly than the controllers developed based on dynamic models, in which longitudinal speed is assumed to be constant, and only lateral speed and yaw rate are used as system states. Furthermore, this approach supports all-wheel-drive vehicles. Front-wheel-drive or rear-wheel-drive vehicles are also supported as special cases of an all-wheel-drive vehicle.

Human Interactive Triboelectric Nanogenerator as a Self-Powered Smart Seat.

PubMed

Chandrasekhar, Arunkumar; Alluri, Nagamalleswara Rao; Saravanakumar, Balasubramaniam; Selvarajan, Sophia; Kim, Sang-Jae

2016-04-20

A lightweight, flexible, cost-effective, and robust, single-electrode-based Smart Seat-Triboelectric Nanogenerator (SS-TENG) is introduced as a promising eco-friendly approach for harvesting energy from the living environment, for use in integrated self-powered systems. An effective method for harvesting biomechanical energy from human motion such as walking, running, and sitting, utilizing widely adaptable everyday contact materials (newspaper, denim, polyethylene covers, and bus cards) is demonstrated. The working mechanism of the SS-TENG is based on the generation and transfer of triboelectric charge carriers between the active layer and user-friendly contact materials. The performance of SS-TENG (52 V and 5.2 μA for a multiunit SS-TENG) is systematically studied and demonstrated in a range of applications including a self-powered passenger seat number indicator and a STOP-indicator using LEDs, using a simple logical circuit. Harvested energy is used as a direct power source to drive 60 blue and green commercially available LEDs and a monochrome LCD. This feasibility study confirms that triboelectric nanogenerators are a suitable technology for energy harvesting from human motion during transportation, which could be used to operate a variety of wireless devices, GPS systems, electronic devices, and other sensors during travel.

A computational procedure for large rotational motions in multibody dynamics

NASA Technical Reports Server (NTRS)

Park, K. C.; Chiou, J. C.

1987-01-01

A computational procedure suitable for the solution of equations of motion for multibody systems is presented. The present procedure adopts a differential partitioning of the translational motions and the rotational motions. The translational equations of motion are then treated by either a conventional explicit or an implicit direct integration method. A principle feature of this procedure is a nonlinearly implicit algorithm for updating rotations via the Euler four-parameter representation. This procedure is applied to the rolling of a sphere through a specific trajectory, which shows that it yields robust solutions.

INS integrated motion analysis for autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Roberts, Barry; Bazakos, Mike

1991-01-01

The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.

Design and Experimental Evaluation of a Robust Position Controller for an Electrohydrostatic Actuator Using Adaptive Antiwindup Sliding Mode Scheme

PubMed Central

Lee, Ji Min; Park, Sung Hwan; Kim, Jong Shik

2013-01-01

A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error, this paper proposes an adaptive antiwindup PID sliding mode scheme as a robust position controller for the EHA system. An optimal PID controller and an optimal anti-windup PID controller are also designed to compare control performance. An EHA prototype is developed, carrying out system modeling and parameter identification in designing the position controller. The simply identified linear model serves as the basis for the design of the position controllers, while the robustness of the control systems is compared by experiments. The adaptive anti-windup PID sliding mode controller has been found to have the desired performance and become robust against hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. PMID:23983640

Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity

PubMed Central

Kim, Minjae; Kim, Taewan; Kim, Dong Sung; Chung, Wan Kyun

2015-01-01

Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode. PMID:26153773

Robust, Causal, and Incremental Approaches to Investigating Linguistic Adaptation

PubMed Central

Roberts, Seán G.

2018-01-01

This paper discusses the maximum robustness approach for studying cases of adaptation in language. We live in an age where we have more data on more languages than ever before, and more data to link it with from other domains. This should make it easier to test hypotheses involving adaptation, and also to spot new patterns that might be explained by adaptation. However, there is not much discussion of the overall approach to research in this area. There are outstanding questions about how to formalize theories, what the criteria are for directing research and how to integrate results from different methods into a clear assessment of a hypothesis. This paper addresses some of those issues by suggesting an approach which is causal, incremental and robust. It illustrates the approach with reference to a recent claim that dry environments select against the use of precise contrasts in pitch. Study 1 replicates a previous analysis of the link between humidity and lexical tone with an alternative dataset and finds that it is not robust. Study 2 performs an analysis with a continuous measure of tone and finds no significant correlation. Study 3 addresses a more recent analysis of the link between humidity and vowel use and finds that it is robust, though the effect size is small and the robustness of the measurement of vowel use is low. Methodological robustness of the general theory is addressed by suggesting additional approaches including iterated learning, a historical case study, corpus studies, and studying individual speech. PMID:29515487

Neural Integration of Information Specifying Human Structure from Form, Motion, and Depth

PubMed Central

Jackson, Stuart; Blake, Randolph

2010-01-01

Recent computational models of biological motion perception operate on ambiguous two-dimensional representations of the body (e.g., snapshots, posture templates) and contain no explicit means for disambiguating the three-dimensional orientation of a perceived human figure. Are there neural mechanisms in the visual system that represent a moving human figure’s orientation in three dimensions? To isolate and characterize the neural mechanisms mediating perception of biological motion, we used an adaptation paradigm together with bistable point-light (PL) animations whose perceived direction of heading fluctuates over time. After exposure to a PL walker with a particular stereoscopically defined heading direction, observers experienced a consistent aftereffect: a bistable PL walker, which could be perceived in the adapted orientation or reversed in depth, was perceived predominantly reversed in depth. A phase-scrambled adaptor produced no aftereffect, yet when adapting and test walkers differed in size or appeared on opposite sides of fixation aftereffects did occur. Thus, this heading direction aftereffect cannot be explained by local, disparity-specific motion adaptation, and the properties of scale and position invariance imply higher-level origins of neural adaptation. Nor is disparity essential for producing adaptation: when suspended on top of a stereoscopically defined, rotating globe, a context-disambiguated “globetrotter” was sufficient to bias the bistable walker’s direction, as were full-body adaptors. In sum, these results imply that the neural signals supporting biomotion perception integrate information on the form, motion, and three-dimensional depth orientation of the moving human figure. Models of biomotion perception should incorporate mechanisms to disambiguate depth ambiguities in two-dimensional body representations. PMID:20089892

SDRE controller for motion design of cable-suspended robot with uncertainties and moving obstacles

NASA Astrophysics Data System (ADS)

Behboodi, Ahad; Salehi, Seyedmohammad

2017-10-01

In this paper an optimal control approach for nonlinear dynamical systems was proposed based on State Dependent Riccati Equation (SDRE) and its robustness against uncertainties is shown by simulation results. The proposed method was applied on a spatial six-cable suspended robot, which was designed to carry loads or perform different tasks in huge workspaces. Motion planning for cable-suspended robots in such a big workspace is subjected to uncertainties and obstacles. First, we emphasized the ability of SDRE to construct a systematic basis and efficient design of controller for wide variety of nonlinear dynamical systems. Then we showed how this systematic design improved the robustness of the system and facilitated the integration of motion planning techniques with the controller. In particular, obstacle avoidance technique based on artificial potential field (APF) can be easily combined with SDRE controller with efficient performance. Due to difficulties of exact solution for SDRE, an approximation method was used based on power series expansion. The efficiency and robustness of the SDRE controller was illustrated on a six-cable suspended robot with proper simulations.

An algorithm of adaptive scale object tracking in occlusion

NASA Astrophysics Data System (ADS)

Zhao, Congmei

2017-05-01

Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there are still some problems in handling scale variations, object occlusion, fast motions and so on. In this paper, a multi-scale kernel correlation filter algorithm based on random fern detector was proposed. The tracking task was decomposed into the target scale estimation and the translation estimation. At the same time, the Color Names features and HOG features were fused in response level to further improve the overall tracking performance of the algorithm. In addition, an online random fern classifier was trained to re-obtain the target after the target was lost. By comparing with some algorithms such as KCF, DSST, TLD, MIL, CT and CSK, experimental results show that the proposed approach could estimate the object state accurately and handle the object occlusion effectively.

Endocrine correlates of susceptibility to motion sickness

NASA Technical Reports Server (NTRS)

Kohl, R. L.

1985-01-01

Motion sickness releases ACTH, epinerphrine, and norepinephrine. The endocrine responses to motion sickness, adaptive responses leading to the resolution of the syndrome, and the way in which antimotion-sickness drugs influence the endocrine responses were studied. Susceptible or insusceptible subjects were administered antimotion-sickness drugs prior to stressful stimulation. Insusceptible subjects displayed more pronounced elevations of ACTH, epinephrine, and norepinephrine after stressful motion. Predrug levels of ACTH were higher in insusceptible subjects (p less than 0.01). Acute blockade of hormone responses to stressful motion or alteration of levels of ACTH by drugs were not correlated with individual susceptibility. No correlation was apparent between epinephrine and ACTH release. These endocrine differences may represent neurochemical markers for susceptibility to motion, stress, or general adaptability, and it may be that the chronic modulation of their levels might be more effective in preventing motion sickness than the acute blockage or stimulation of specific receptors.

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy

NASA Astrophysics Data System (ADS)

Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

2013-11-01

To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (∼1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization process is feasible and may yield improved OAR sparing compared to the standard margin approach.

Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy.

PubMed

Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

2013-11-07

To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (~1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization process is feasible and may yield improved OAR sparing compared to the standard margin approach.

Moving Faces

ERIC Educational Resources Information Center

Journal of College Science Teaching, 2005

2005-01-01

A recent study by Zara Ambadar and Jeffrey F. Cohn of the University of Pittsburgh and Jonathan W. Schooler of the University of British Columbia, examined how motion affects people's judgment of subtle facial expressions. Two experiments demonstrated robust effects of motion in facilitating the perception of subtle facial expressions depicting…

Performance analysis of visual tracking algorithms for motion-based user interfaces on mobile devices

NASA Astrophysics Data System (ADS)

Winkler, Stefan; Rangaswamy, Karthik; Tedjokusumo, Jefry; Zhou, ZhiYing

2008-02-01

Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping.

Kernelized correlation tracking with long-term motion cues

NASA Astrophysics Data System (ADS)

Lv, Yunqiu; Liu, Kai; Cheng, Fei

2018-04-01

Robust object tracking is a challenging task in computer vision due to interruptions such as deformation, fast motion and especially, occlusion of tracked object. When occlusions occur, image data will be unreliable and is insufficient for the tracker to depict the object of interest. Therefore, most trackers are prone to fail under occlusion. In this paper, an occlusion judgement and handling method based on segmentation of the target is proposed. If the target is occluded, the speed and direction of it must be different from the objects occluding it. Hence, the value of motion features are emphasized. Considering the efficiency and robustness of Kernelized Correlation Filter Tracking (KCF), it is adopted as a pre-tracker to obtain a predicted position of the target. By analyzing long-term motion cues of objects around this position, the tracked object is labelled. Hence, occlusion could be detected easily. Experimental results suggest that our tracker achieves a favorable performance and effectively handles occlusion and drifting problems.

Robust quantum logic in neutral atoms via adiabatic Rydberg dressing

DOE PAGES

Keating, Tyler; Cook, Robert L.; Hankin, Aaron M.; ...

2015-01-28

We study a scheme for implementing a controlled-Z (CZ) gate between two neutral-atom qubits based on the Rydberg blockade mechanism in a manner that is robust to errors caused by atomic motion. By employing adiabatic dressing of the ground electronic state, we can protect the gate from decoherence due to random phase errors that typically arise because of atomic thermal motion. In addition, the adiabatic protocol allows for a Doppler-free configuration that involves counterpropagating lasers in a σ +/σ - orthogonal polarization geometry that further reduces motional errors due to Doppler shifts. The residual motional error is dominated by dipole-dipolemore » forces acting on doubly-excited Rydberg atoms when the blockade is imperfect. As a result, for reasonable parameters, with qubits encoded into the clock states of 133Cs, we predict that our protocol could produce a CZ gate in < 10 μs with error probability on the order of 10 -3.« less

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition

PubMed Central

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-01-01

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation. PMID:27999337

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition.

PubMed

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-12-17

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation.

Inactivation of Semicircular Canals Causes Adaptive Increases in Otolith-driven Tilt Responses

NASA Technical Reports Server (NTRS)

Angelaki, Dora E.; Newlands, Shawn D.; Dickman, J. David

2002-01-01

Growing experimental and theoretical evidence suggests a functional synergy in the processing of otolith and semicircular canal signals for the generation of the vestibulo-ocular reflexes (VORs). In this study we have further tested this functional interaction by quantifying the adaptive changes in the otolith-ocular system during both rotational and translational movements after surgical inactivation of the semicircular canals. For 0.1- 0.5 Hz (stimuli for which there is no recovery of responses from the plugged canals), pitch and roll VOR gains recovered during earth- horizontal (but not earth-vertical) axis rotations. Corresponding changes were also observed in eye movements elicited by translational motion (0.1 - 5 Hz). Specifically, torsional eye movements increased during lateral motion, whereas vertical eye movements increased during fore-aft motion. The findings indicate that otolith signals can be adapted according to compromised strategy that leads to improved gaze stabilization during motion. Because canal-plugged animals permanently lose the ability to discriminate gravitoinertial accelerations, adapted animals can use the presence of gravity through otolith-driven tilt responses to assist gaze stabilization during earth-horizontal axis rotations.

Interocular velocity difference contributes to stereomotion speed perception

NASA Technical Reports Server (NTRS)

Brooks, Kevin R.

2002-01-01

Two experiments are presented assessing the contributions of the rate of change of disparity (CD) and interocular velocity difference (IOVD) cues to stereomotion speed perception. Using a two-interval forced-choice paradigm, the perceived speed of directly approaching and receding stereomotion and of monocular lateral motion in random dot stereogram (RDS) targets was measured. Prior adaptation using dysjunctively moving random dot stimuli induced a velocity aftereffect (VAE). The degree of interocular correlation in the adapting images was manipulated to assess the effectiveness of each cue. While correlated adaptation involved a conventional RDS stimulus, containing both IOVD and CD cues, uncorrelated adaptation featured an independent dot array in each monocular half-image, and hence lacked a coherent disparity signal. Adaptation produced a larger VAE for stereomotion than for monocular lateral motion, implying effects at neural sites beyond that of binocular combination. For motion passing through the horopter, correlated and uncorrelated adaptation stimuli produced equivalent stereomotion VAEs. The possibility that these results were due to the adaptation of a CD mechanism through random matches in the uncorrelated stimulus was discounted in a control experiment. Here both simultaneous and sequential adaptation of left and right eyes produced similar stereomotion VAEs. Motion at uncrossed disparities was also affected by both correlated and uncorrelated adaptation stimuli, but showed a significantly greater VAE in response to the former. These results show that (1) there are two separate, specialised mechanisms for encoding stereomotion: one through IOVD, the other through CD; (2) the IOVD cue dominates the perception of stereomotion speed for stimuli passing through the horopter; and (3) at a disparity pedestal both the IOVD and the CD cues have a significant influence.

An improved adaptive control for repetitive motion of robots

NASA Technical Reports Server (NTRS)

Pourboghrat, F.

1989-01-01

An adaptive control algorithm is proposed for a class of nonlinear systems, such as robotic manipulators, which is capable of improving its performance in repetitive motions. When the task is repeated, the error between the desired trajectory and that of the system is guaranteed to decrease. The design is based on the combination of a direct adaptive control and a learning process. This method does not require any knowledge of the dynamic parameters of the system.

The adaptation of GDL motion recognition system to sport and rehabilitation techniques analysis.

PubMed

Hachaj, Tomasz; Ogiela, Marek R

2016-06-01

The main novelty of this paper is presenting the adaptation of Gesture Description Language (GDL) methodology to sport and rehabilitation data analysis and classification. In this paper we showed that Lua language can be successfully used for adaptation of the GDL classifier to those tasks. The newly applied scripting language allows easily extension and integration of classifier with other software technologies and applications. The obtained execution speed allows using the methodology in the real-time motion capture data processing where capturing frequency differs from 100 Hz to even 500 Hz depending on number of features or classes to be calculated and recognized. Due to this fact the proposed methodology can be used to the high-end motion capture system. We anticipate that using novel, efficient and effective method will highly help both sport trainers and physiotherapist in they practice. The proposed approach can be directly applied to motion capture data kinematics analysis (evaluation of motion without regard to the forces that cause that motion). The ability to apply pattern recognition methods for GDL description can be utilized in virtual reality environment and used for sport training or rehabilitation treatment.

Adaptive Core Simulation Employing Discrete Inverse Theory - Part II: Numerical Experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abdel-Khalik, Hany S.; Turinsky, Paul J.

2005-07-15

Use of adaptive simulation is intended to improve the fidelity and robustness of important core attribute predictions such as core power distribution, thermal margins, and core reactivity. Adaptive simulation utilizes a selected set of past and current reactor measurements of reactor observables, i.e., in-core instrumentation readings, to adapt the simulation in a meaningful way. The companion paper, ''Adaptive Core Simulation Employing Discrete Inverse Theory - Part I: Theory,'' describes in detail the theoretical background of the proposed adaptive techniques. This paper, Part II, demonstrates several computational experiments conducted to assess the fidelity and robustness of the proposed techniques. The intentmore » is to check the ability of the adapted core simulator model to predict future core observables that are not included in the adaption or core observables that are recorded at core conditions that differ from those at which adaption is completed. Also, this paper demonstrates successful utilization of an efficient sensitivity analysis approach to calculate the sensitivity information required to perform the adaption for millions of input core parameters. Finally, this paper illustrates a useful application for adaptive simulation - reducing the inconsistencies between two different core simulator code systems, where the multitudes of input data to one code are adjusted to enhance the agreement between both codes for important core attributes, i.e., core reactivity and power distribution. Also demonstrated is the robustness of such an application.« less

The decay of motor adaptation to novel movement dynamics reveals an asymmetry in the stability of motion state-dependent learning

PubMed Central

Hosseini, Eghbal A.; Nguyen, Katrina P.; Joiner, Wilsaan M.

2017-01-01

Motor adaptation paradigms provide a quantitative method to study short-term modification of motor commands. Despite the growing understanding of the role motion states (e.g., velocity) play in this form of motor learning, there is little information on the relative stability of memories based on these movement characteristics, especially in comparison to the initial adaptation. Here, we trained subjects to make reaching movements perturbed by force patterns dependent upon either limb position or velocity. Following training, subjects were exposed to a series of error-clamp trials to measure the temporal characteristics of the feedforward motor output during the decay of learning. The compensatory force patterns were largely based on the perturbation kinematic (e.g., velocity), but also showed a small contribution from the other motion kinematic (e.g., position). However, the velocity contribution in response to the position-based perturbation decayed at a slower rate than the position contribution to velocity-based training, suggesting a difference in stability. Next, we modified a previous model of motor adaptation to reflect this difference and simulated the behavior for different learning goals. We were interested in the stability of learning when the perturbations were based on different combinations of limb position or velocity that subsequently resulted in biased amounts of motion-based learning. We trained additional subjects on these combined motion-state perturbations and confirmed the predictions of the model. Specifically, we show that (1) there is a significant separation between the observed gain-space trajectories for the learning and decay of adaptation and (2) for combined motion-state perturbations, the gain associated to changes in limb position decayed at a faster rate than the velocity-dependent gain, even when the position-dependent gain at the end of training was significantly greater. Collectively, these results suggest that the state-dependent adaptation associated with movement velocity is relatively more stable than that based on position. PMID:28481891

Spatial Cognitive Performance During Adaptation to Conflicting Tilt-Translation Stimuli as a Sensorimotor Spaceflight Analog

NASA Technical Reports Server (NTRS)

Kayanickupuram, A. J.; Ramos, K. A.; Cordova, M. L.; Wood, S. J.

2009-01-01

The need to resolve new patterns of sensory feedback in altered gravitoinertial environments requires cognitive processes to develop appropriate reference frames for spatial orientation awareness. The purpose of this study was to examine deficits in spatial cognitive performance during adaptation to conflicting tilt-translation stimuli. Fourteen subjects were tilted within a lighted enclosure that simultaneously translated at one of 3 frequencies. Tilt and translation motion was synchronized to maintain the resultant gravitoinertial force aligned with the longitudinal body axis, resulting in a mismatch analogous to spaceflight in which the canals and vision signal tilt while the otoliths do not. Changes in performance on different spatial cognitive tasks were compared 1) without motion, 2) with tilt motion alone (pitch at 0.15, 0.3 and 0.6 Hz or roll at 0.3 Hz), and 3) with conflicting tilt-translation motion. The adaptation paradigm was continued for up to 30 min or until the onset of nausea. The order of the adaptation conditions were counter-balanced across 4 different test sessions. There was a significant effect of stimulus frequency on both motion sickness and spatial cognitive performance. Only 3 of 14 were able to complete the full 30 min protocol at 0.15 Hz, while 7 of 14 completed 0.3 Hz and 13 of 14 completed 0.6 Hz. There were no changes in simple visual-spatial cognitive tests, e.g., mental rotation or match-to-sample. There were significant deficits during 0.15 Hz adaptation in both accuracy and reaction time during a spatial reference task in which subjects are asked to identify a match of a 3D reoriented cube assemblage. Our results are consistent with antidotal reports of cognitive impairment that are common during sensorimotor adaptation with G-transitions. We conclude that these cognitive deficits stem from the ambiguity of spatial reference frames for central processing of inertial motion cues.

Internal Coordinate Molecular Dynamics: A Foundation for Multiscale Dynamics

PubMed Central

2015-01-01

Internal coordinates such as bond lengths, bond angles, and torsion angles (BAT) are natural coordinates for describing a bonded molecular system. However, the molecular dynamics (MD) simulation methods that are widely used for proteins, DNA, and polymers are based on Cartesian coordinates owing to the mathematical simplicity of the equations of motion. However, constraints are often needed with Cartesian MD simulations to enhance the conformational sampling. This makes the equations of motion in the Cartesian coordinates differential-algebraic, which adversely impacts the complexity and the robustness of the simulations. On the other hand, constraints can be easily placed in BAT coordinates by removing the degrees of freedom that need to be constrained. Thus, the internal coordinate MD (ICMD) offers an attractive alternative to Cartesian coordinate MD for developing multiscale MD method. The torsional MD method is a special adaptation of the ICMD method, where all the bond lengths and bond angles are kept rigid. The advantages of ICMD simulation methods are the longer time step size afforded by freezing high frequency degrees of freedom and performing a conformational search in the more important low frequency torsional degrees of freedom. However, the advancements in the ICMD simulations have been slow and stifled by long-standing mathematical bottlenecks. In this review, we summarize the recent mathematical advancements we have made based on spatial operator algebra, in developing a robust long time scale ICMD simulation toolkit useful for various applications. We also present the applications of ICMD simulations to study conformational changes in proteins and protein structure refinement. We review the advantages of the ICMD simulations over the Cartesian simulations when used with enhanced sampling methods and project the future use of ICMD simulations in protein dynamics. PMID:25517406

Decentralized adaptive control of robot manipulators with robust stabilization design

NASA Technical Reports Server (NTRS)

Yuan, Bau-San; Book, Wayne J.

1988-01-01

Due to geometric nonlinearities and complex dynamics, a decentralized technique for adaptive control for multilink robot arms is attractive. Lyapunov-function theory for stability analysis provides an approach to robust stabilization. Each joint of the arm is treated as a component subsystem. The adaptive controller is made locally stable with servo signals including proportional and integral gains. This results in the bound on the dynamical interactions with other subsystems. A nonlinear controller which stabilizes the system with uniform boundedness is used to improve the robustness properties of the overall system. As a result, the robot tracks the reference trajectories with convergence. This strategy makes computation simple and therefore facilitates real-time implementation.

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex.

PubMed

McLelland, Douglas; Baker, Pamela M; Ahmed, Bashir; Kohn, Adam; Bair, Wyeth

2015-07-15

A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components. Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales. Copyright © 2015 the authors 0270-6474/15/3510268-13$15.00/0.

Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

2009-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Lateral control system design for VTOL landing on a DD963 in high sea states. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bodson, M.

1982-01-01

The problem of designing lateral control systems for the safe landing of VTOL aircraft on small ships is addressed. A ship model is derived. The issues of estimation and prediction of ship motions are discussed, using optimal linear linear estimation techniques. The roll motion is the most important of the lateral motions, and it is found that it can be predicted for up to 10 seconds in perfect conditions. The automatic landing of the VTOL aircraft is considered, and a lateral controller, defined as a ship motion tracker, is designed, using optimal control techniqes. The tradeoffs between the tracking errors and the control authority are obtained. The important couplings between the lateral motions and controls are demonstrated, and it is shown that the adverse couplings between the sway and the roll motion at the landing pad are significant constraints in the tracking of the lateral ship motions. The robustness of the control system, including the optimal estimator, is studied, using the singular values analysis. Through a robustification procedure, a robust control system is obtained, and the usefulness of the singular values to define stability margins that take into account general types of unstructured modelling errors is demonstrated. The minimal destabilizing perturbations indicated by the singular values analysis are interpreted and related to the multivariable Nyquist diagrams.

Adaptation disrupts motion integration in the primate dorsal stream

PubMed Central

Patterson, Carlyn A.; Wissig, Stephanie C.; Kohn, Adam

2014-01-01

Summary Sensory systems adjust continuously to the environment. The effects of recent sensory experience—or adaptation—are typically assayed by recording in a relevant subcortical or cortical network. However, adaptation effects cannot be localized to a single, local network. Adjustments in one circuit or area will alter the input provided to others, with unclear consequences for computations implemented in the downstream circuit. Here we show that prolonged adaptation with drifting gratings, which alters responses in the early visual system, impedes the ability of area MT neurons to integrate motion signals in plaid stimuli. Perceptual experiments reveal a corresponding loss of plaid coherence. A simple computational model shows how the altered representation of motion signals in early cortex can derail integration in MT. Our results suggest that the effects of adaptation cascade through the visual system, derailing the downstream representation of distinct stimulus attributes. PMID:24507198

Robust adaptive extended Kalman filtering for real time MR-thermometry guided HIFU interventions.

PubMed

Roujol, Sébastien; de Senneville, Baudouin Denis; Hey, Silke; Moonen, Chrit; Ries, Mario

2012-03-01

Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.

Autocalibrating motion-corrected wave-encoding for highly accelerated free-breathing abdominal MRI.

PubMed

Chen, Feiyu; Zhang, Tao; Cheng, Joseph Y; Shi, Xinwei; Pauly, John M; Vasanawala, Shreyas S

2017-11-01

To develop a motion-robust wave-encoding technique for highly accelerated free-breathing abdominal MRI. A comprehensive 3D wave-encoding-based method was developed to enable fast free-breathing abdominal imaging: (a) auto-calibration for wave-encoding was designed to avoid extra scan for coil sensitivity measurement; (b) intrinsic butterfly navigators were used to track respiratory motion; (c) variable-density sampling was included to enable compressed sensing; (d) golden-angle radial-Cartesian hybrid view-ordering was incorporated to improve motion robustness; and (e) localized rigid motion correction was combined with parallel imaging compressed sensing reconstruction to reconstruct the highly accelerated wave-encoded datasets. The proposed method was tested on six subjects and image quality was compared with standard accelerated Cartesian acquisition both with and without respiratory triggering. Inverse gradient entropy and normalized gradient squared metrics were calculated, testing whether image quality was improved using paired t-tests. For respiratory-triggered scans, wave-encoding significantly reduced residual aliasing and blurring compared with standard Cartesian acquisition (metrics suggesting P < 0.05). For non-respiratory-triggered scans, the proposed method yielded significantly better motion correction compared with standard motion-corrected Cartesian acquisition (metrics suggesting P < 0.01). The proposed methods can reduce motion artifacts and improve overall image quality of highly accelerated free-breathing abdominal MRI. Magn Reson Med 78:1757-1766, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Adaptive Control of Truss Structures for Gossamer Spacecraft

NASA Technical Reports Server (NTRS)

Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

2007-01-01

Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.

Decentralized digital adaptive control of robot motion

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

NASA Technical Reports Server (NTRS)

Rohrs, C. E.; Valavani, L.; Athans, M.; Stein, G.

1985-01-01

This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.

How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2015-04-01

In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the performance of a candidate plan with the performance of other candidate plans across a large ensemble of plausible futures. Initial results suggest that the simplest satisficing metric, inspired by the signal to noise ratio, results in very risk averse solutions. Other satisficing metrics, which handle the average performance and the dispersion around the average separately, provide substantial additional insights into the trade off between the average performance, and the dispersion around this average. In contrast, the regret-based metrics enhance insight into the relative merits of candidate plans, while being less clear on the average performance or the dispersion around this performance. These results suggest that it is beneficial to use multiple robustness metrics when doing a robust decision analysis study. Haasnoot, M., J. H. Kwakkel, W. E. Walker and J. Ter Maat (2013). "Dynamic Adaptive Policy Pathways: A New Method for Crafting Robust Decisions for a Deeply Uncertain World." Global Environmental Change 23(2): 485-498. Kwakkel, J. H., M. Haasnoot and W. E. Walker (2014). "Developing Dynamic Adaptive Policy Pathways: A computer-assisted approach for developing adaptive strategies for a deeply uncertain world." Climatic Change.

Anatomical robust optimization to account for nasal cavity filling variation during intensity-modulated proton therapy: a comparison with conventional and adaptive planning strategies

NASA Astrophysics Data System (ADS)

van de Water, Steven; Albertini, Francesca; Weber, Damien C.; Heijmen, Ben J. M.; Hoogeman, Mischa S.; Lomax, Antony J.

2018-01-01

The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 ‘synthetic’ CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system ‘Erasmus-iCycle’ was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 GyRBE treatment, assuming each synthetic CT to correspond to a 2 GyRBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V95%  ⩾  98% and V107%  ⩽  2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 GyRBE (20%) higher when using SFUD optimization and on average 3.6 GyRBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and OAR doses compared with conventional SFUD optimization. OAR doses can be further reduced by using online plan adaptation.

Short-term adaptation of the VOR: non-retinal-slip error signals and saccade substitution

NASA Technical Reports Server (NTRS)

Eggers, Sscott D Z.; De Pennington, Nick; Walker, Mark F.; Shelhamer, Mark; Zee, David S.

2003-01-01

We studied short-term (30 min) adaptation of the vestibulo-ocular reflex (VOR) in five normal humans using a "position error" stimulus without retinal image motion. Both before and after adaptation a velocity gain (peak slow-phase eye velocity/peak head velocity) and a position gain (total eye movement during chair rotation/amplitude of chair motion) were measured in darkness using search coils. The vestibular stimulus was a brief ( approximately 700 ms), 15 degrees chair rotation in darkness (peak velocity 43 degrees /s). To elicit adaptation, a straight-ahead fixation target disappeared during chair movement and when the chair stopped the target reappeared at a new location in front of the subject for gain-decrease (x0) adaptation, or 10 degrees opposite to chair motion for gain-increase (x1.67) adaptation. This position-error stimulus was effective at inducing VOR adaptation, though for gain-increase adaptation the primary strategy was to substitute augmenting saccades during rotation while for gain-decrease adaptation both corrective saccades and a decrease in slow-phase velocity occurred. Finally, the presence of the position-error signal alone, at the end of head rotation, without any attempt to fix upon it, was not sufficient to induce adaptation. Adaptation did occur, however, if the subject did make a saccade to the target after head rotation, or even if the subject paid attention to the new location of the target without actually looking at it.

Biological Motion Cues Trigger Reflexive Attentional Orienting

ERIC Educational Resources Information Center

Shi, Jinfu; Weng, Xuchu; He, Sheng; Jiang, Yi

2010-01-01

The human visual system is extremely sensitive to biological signals around us. In the current study, we demonstrate that biological motion walking direction can induce robust reflexive attentional orienting. Following a brief presentation of a central point-light walker walking towards either the left or right direction, observers' performance…

Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares.

PubMed

Zhou, Zhenyu; Liu, Wei; Cui, Jiali; Wang, Xunheng; Arias, Diana; Wen, Ying; Bansal, Ravi; Hao, Xuejun; Wang, Zhishun; Peterson, Bradley S; Xu, Dongrong

2011-02-01

Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and by spatially and temporally varying artifacts, such as rigid-body motion and cardiac pulsation. Motion artifacts are particularly prevalent when scanning difficult patient populations, such as human infants. Although some motion during data acquisition can be corrected using image coregistration procedures, frequently individual DWIs are corrupted beyond repair by sudden, large amplitude motion either within or outside of the imaging plane. We propose a novel approach to identify and reject outlier images automatically using local binary patterns (LBP) and 2D partial least square (2D-PLS) to estimate diffusion tensors robustly. This method uses an enhanced LBP algorithm to extract texture features from a local texture feature of the image matrix from the DWI data. Because the images have been transformed to local texture matrices, we are able to extract discriminating information that identifies outliers in the data set by extending a traditional one-dimensional PLS algorithm to a two-dimension operator. The class-membership matrix in this 2D-PLS algorithm is adapted to process samples that are image matrix, and the membership matrix thus represents varying degrees of importance of local information within the images. We also derive the analytic form of the generalized inverse of the class-membership matrix. We show that this method can effectively extract local features from brain images obtained from a large sample of human infants to identify images that are outliers in their textural features, permitting their exclusion from further processing when estimating tensors using the DWIs. This technique is shown to be superior in performance when compared with visual inspection and other common methods to address motion-related artifacts in DWI data. This technique is applicable to correct motion artifact in other magnetic resonance imaging (MRI) techniques (e.g., the bootstrapping estimation) that use univariate or multivariate regression methods to fit MRI data to a pre-specified model. Copyright © 2011 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henderson, C. B.; Gould, A.; Gaudi, B. S.

The mass of the lenses giving rise to Galactic microlensing events can be constrained by measuring the relative lens-source proper motion and lens flux. The flux of the lens can be separated from that of the source, companions to the source, and unrelated nearby stars with high-resolution images taken when the lens and source are spatially resolved. For typical ground-based adaptive optics (AO) or space-based observations, this requires either inordinately long time baselines or high relative proper motions. We provide a list of microlensing events toward the Galactic bulge with high relative lens-source proper motion that are therefore good candidatesmore » for constraining the lens mass with future high-resolution imaging. We investigate all events from 2004 to 2013 that display detectable finite-source effects, a feature that allows us to measure the proper motion. In total, we present 20 events with μ ≳ 8 mas yr{sup –1}. Of these, 14 were culled from previous analyses while 6 are new, including OGLE-2004-BLG-368, MOA-2005-BLG-36, OGLE-2012-BLG-0211, OGLE-2012-BLG-0456, MOA-2012-BLG-532, and MOA-2013-BLG-029. In ≲12 yr from the time of each event the lens and source of each event will be sufficiently separated for ground-based telescopes with AO systems or space telescopes to resolve each component and further characterize the lens system. Furthermore, for the most recent events, comparison of the lens flux estimates from images taken immediately to those estimated from images taken when the lens and source are resolved can be used to empirically check the robustness of the single-epoch method currently being used to estimate lens masses for many events.« less

Interactive Physical Simulation of Catheter Motion within Mayor Vessel Structures and Cavities for ASD/VSD Treatment

NASA Astrophysics Data System (ADS)

Becherer, Nico; Hesser, Jürgen; Kornmesser, Ulrike; Schranz, Dietmar; Männer, Reinhard

2007-03-01

Simulation systems are becoming increasingly essential in medical education. Hereby, capturing the physical behaviour of the real world requires a sophisticated modelling of instruments within the virtual environment. Most models currently used are not capable of user interactive simulations due to the computation of the complex underlying analytical equations. Alternatives are often based on simplifying mass-spring systems, being able to deliver high update rates that come at the cost of less realistic motion. In addition, most techniques are limited to narrow and tubular vessel structures or restrict shape alterations to two degrees of freedom, not allowing instrument deformations like torsion. In contrast, our approach combines high update rates with highly realistic motion and can in addition be used with respect to arbitrary structures like vessels or cavities (e.g. atrium, ventricle) without limiting the degrees of freedom. Based on energy minimization, bending energies and vessel structures are considered as linear elastic elements; energies are evaluated at regularly spaced points on the instrument, while the distance of the points is fixed, i.e. we simulate an articulated structure of joints with fixed connections between them. Arbitrary tissue structures are modeled through adaptive distance fields and are connected by nodes via an undirected graph system. The instrument points are linked to nodes by a system of rules. Energy minimization uses a Quasi Newton method without preconditioning and, hereby, gradients are estimated using a combination of analytical and numerical terms. Results show a high quality in motion simulation when compared to a phantom model. The approach is also robust and fast. Simulating an instrument with 100 joints runs at 100 Hz on a 3 GHz PC.

A Profile of Glenohumeral Internal and External Rotation Motion in the Uninjured High School Baseball Pitcher, Part I: Motion

PubMed Central

Hurd, Wendy J.; Kaplan, Kevin M.; ElAttrache, Neal S.; Jobe, Frank W.; Morrey, Bernard F.; Kaufman, Kenton R.

2011-01-01

Context: The magnitude of motion that is normal for the throwing shoulder in uninjured baseball pitchers has not been established. Chronologic factors contributing to adaptations in motion present in the thrower's shoulder also have not been established. Objectives: To develop a normative profile of glenohumeral rotation motion in uninjured high school baseball pitchers and to evaluate the effect of chronologic characteristics on the development of adaptations in shoulder rotation motion. Design: Cohort study. Setting: Baseball playing field. Patients or Other Participants: A total of 210 uninjured male high school baseball pitchers (age = 16±1.1 years, height = 1.8 + 0.1 m, mass = 77.5±11.2 kg, pitching experience = 6±2.3 years). Intervention(s): Using standard goniometric techniques, we measured passive rotational glenohumeral range of motion bilaterally with participants in the supine position. Main Outcome Measure(s): Paired t tests were performed to identify differences in motion between limbs for the group. Analysis of variance and post hoc Tukey tests were conducted to identify differences in motion by age. Linear regressions were performed to determine the influence of chronologic factors on limb motion. Results: Rotation motion characteristics for the population were established. We found no difference between sides for external rotation (ER) at 0° of abduction (t209 = 0.658, P = .51), but we found side-to-side differences in ER (t209 = −13.012, P<.001) and internal rotation (t209 = 15.304, P<.001) at 90° of abduction. Age at the time of testing was a significant negative predictor of ER motion for the dominant shoulder (R2 = 0.019, P = .049) because less ER motion occurred at the dominant shoulder with advancing age. We found no differences in rotation motion in the dominant shoulder across ages (F4,205 range, 0.451–1.730, P>.05). Conclusions: This range-of-motion profile might be used to assist with the interpretation of normal and atypical shoulder rotation motion in this population. Chronologic characteristics of athletes had no influence on range-of-motion adaptations in the thrower's shoulder. PMID:21669098

Effectiveness of ProTaper Universal retreatment instruments used with rotary or reciprocating adaptive motion in the removal of root canal filling material.

PubMed

Capar, I D; Arslan, H; Ertas, H; Gök, T; Saygılı, G

2015-01-01

To compare the effectiveness of ProTaper Universal retreatment instruments with continuous rotation and adaptive motion (AM; a modified reciprocating motion that combines rotational and reciprocating motion) in the removal of filling material. Mesiobuccal root canals in 36 mandibular first molars were instrumented up to size F2 with the ProTaper Universal instrument (Dentsply Maillefer, Ballaigues, Switzerland) and filled using sealer and ProTaper Universal F2 gutta-percha cones. Gutta-percha was then down-packed and the root canal backfilled using the extruder hand-piece of the Elements Obturation System (SybronEndo, Orange, CA, USA). The teeth were assigned to two groups (n = 18), and removal of the root fillings was performed using one of the following techniques: group 1) ProTaper Universal retreatment files used with rotational motion (RM) and group 2) ProTaper Universal retreatment files used with adaptive motion (AM) (600° clockwise/0° counter-clockwise to 370° clockwise/50° counter-clockwise). The teeth were sectioned, and both halves were analysed at 8 × magnification. The percentage of remaining filling material was recorded. The data were analysed statistically using the Student's t-test at a 95% confidence level (P < 0.05). There was no significant difference between the groups with respect to the total time required for retreatment (P = 0.481). The AM technique left significantly less filling material than the RM method (P = 0.013). The use of ProTaper Universal retreatment files with adaptive motion removed more filling materials from root canals than the rotational movement. © 2014 International Endodontic Journal. Published by John Wiley & Sons Ltd.

Adaptive nonsingular fast terminal sliding-mode control for the tracking problem of uncertain dynamical systems.

PubMed

Boukattaya, Mohamed; Mezghani, Neila; Damak, Tarak

2018-06-01

In this paper, robust and adaptive nonsingular fast terminal sliding-mode (NFTSM) control schemes for the trajectory tracking problem are proposed with known or unknown upper bound of the system uncertainty and external disturbances. The developed controllers take the advantage of the NFTSM theory to ensure fast convergence rate, singularity avoidance, and robustness against uncertainties and external disturbances. First, a robust NFTSM controller is proposed which guarantees that sliding surface and equilibrium point can be reached in a short finite-time from any initial state. Then, in order to cope with the unknown upper bound of the system uncertainty which may be occurring in practical applications, a new adaptive NFTSM algorithm is developed. One feature of the proposed control law is their adaptation techniques where the prior knowledge of parameters uncertainty and disturbances is not needed. However, the adaptive tuning law can estimate the upper bound of these uncertainties using only position and velocity measurements. Moreover, the proposed controller eliminates the chattering effect without losing the robustness property and the precision. Stability analysis is performed using the Lyapunov stability theory, and simulation studies are conducted to verify the effectiveness of the developed control schemes. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Incidence of Dentinal Cracks after Root Canal Preparation with Twisted File Adaptive Instruments Using Different Kinematics.

PubMed

Karataş, Ertuğrul; Arslan, Hakan; Alsancak, Meltem; Kırıcı, Damla Özsu; Ersoy, İbrahim

2015-07-01

The purpose of the present study was to assess the effect of root canal instrumentation using Twisted File Adaptive instruments (Axis/SybronEndo, Orange, CA) with different kinematics (adaptive motion, 90° clockwise [CW]-30° counterclockwise [CCW], 150° CW-30° CCW, 210° CW-30° CCW, and continuous rotation) on crack formation. One hundred five mandibular central incisor teeth were selected. Fifteen teeth were left unprepared (control group), and the remaining 90 teeth were assigned to the 5 root canal shaping groups as follows (n = 15): adaptive motion, 90° CW-30° CCW, 150° CW-30° CCW, 210° CW-30° CCW, continuous rotation, and hand file. All the roots were sectioned horizontally at 3, 6, and 9 mm from the apex with a low-speed saw under water cooling, and the slices were then viewed through a stereomicroscope at 25× magnification. Digital images of each slice were captured using a camera to determine the presence of dentinal cracks. No cracks were observed in the control group, and the continuous rotation group had more cracks than the reciprocation groups (90° CW-30° CCW, 150° CW-30° CCW, and 210° CW-30° CCW) (P < .05). Both the continuous rotation and adaptive motion groups had significantly more dentinal cracks than the hand file group (P < .05). Regarding the different sections (3, 6, and 9 mm), there was a significant difference between the experimental groups at the 9-mm level (P < .05). The incidence of dentinal cracks is less with TF Adaptive instruments working in 210° CW-30° CCW reciprocating motion compared with working in continuous rotation and adaptive motion. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique.

PubMed

Chen, Wen; Chowdhury, Fahmida N; Djuric, Ana; Yeh, Chih-Ping

2014-09-01

This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

NASA Astrophysics Data System (ADS)

Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.

2012-03-01

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

PubMed

Slater, Graham J; Pennell, Matthew W

2014-05-01

A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Souris, K; Sterpin, E; Lee, J

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than onemore » minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)« less

Sliding Mode Control of Dynamic Voltage Restorer by Using a New Adaptive Reaching Law

NASA Astrophysics Data System (ADS)

Pandey, Achala; Agrawal, Rekha; Mandloi, Ravindra S.; Sarkar, Biswaroop

2017-12-01

This paper presents a new kind of adaptive reaching law for sliding mode control of Dynamic Voltage Restorer (DVR). Such an adaptive reaching law follows under-damped sinusoidal nature that causes the initial state to reach the sliding regime in extremely less time with negligible chattering. Moreover, it is robust in the sense the trajectory does not deviate from the sliding surface. This new approach is developed and successfully applied to DVR. The simulation results are presented that show its robustness.

A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters.

PubMed

Liu, Hong; Wang, Jie; Xu, Xiangyang; Song, Enmin; Wang, Qian; Jin, Renchao; Hung, Chih-Cheng; Fei, Baowei

2014-11-01

A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod. Copyright © 2014 Elsevier Inc. All rights reserved.

GENERAL EARTHQUAKE-OBSERVATION SYSTEM (GEOS).

USGS Publications Warehouse

Borcherdt, R.D.; Fletcher, Joe B.; Jensen, E.G.; Maxwell, G.L.; VanSchaack, J.R.; Warrick, R.E.; Cranswick, E.; Johnston, M.J.S.; McClearn, R.

1985-01-01

Microprocessor technology has permitted the development of a General Earthquake-Observation System (GEOS) useful for most seismic applications. Central-processing-unit control via robust software of system functions that are isolated on hardware modules permits field adaptability of the system to a wide variety of active and passive seismic experiments and straightforward modification for incorporation of improvements in technology. Various laboratory tests and numerous deployments of a set of the systems in the field have confirmed design goals, including: wide linear dynamic range (16 bit/96 dB); broad bandwidth (36 hr to 600 Hz; greater than 36 hr available); selectable sensor-type (accelerometer, seismometer, dilatometer); selectable channels (1 to 6); selectable record mode (continuous, preset, trigger); large data capacity (1. 4 to 60 Mbytes); selectable time standard (WWVB, master, manual); automatic self-calibration; simple field operation; full capability to adapt system in the field to a wide variety of experiments; low power; portability; and modest costs. System design goals for a microcomputer-controlled system with modular software and hardware components as implemented on the GEOS are presented. The systems have been deployed for 15 experiments, including: studies of near-source strong motion; high-frequency microearthquakes; crustal structure; down-hole wave propagation; teleseismicity; and earth-tidal strains.

Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

NASA Astrophysics Data System (ADS)

Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

2016-01-01

Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.

Addressing Climate Change in Long-Term Water Planning Using Robust Decisionmaking

NASA Astrophysics Data System (ADS)

Groves, D. G.; Lempert, R.

2008-12-01

Addressing climate change in long-term natural resource planning is difficult because future management conditions are deeply uncertain and the range of possible adaptation options are so extensive. These conditions pose challenges to standard optimization decision-support techniques. This talk will describe a methodology called Robust Decisionmaking (RDM) that can complement more traditional analytic approaches by utilizing screening-level water management models to evaluate large numbers of strategies against a wide range of plausible future scenarios. The presentation will describe a recent application of the methodology to evaluate climate adaptation strategies for the Inland Empire Utilities Agency in Southern California. This project found that RDM can provide a useful way for addressing climate change uncertainty and identify robust adaptation strategies.

Evolution of motion uncertainty in rectal cancer: implications for adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Kleijnen, Jean-Paul J. E.; van Asselen, Bram; Burbach, Johannes P. M.; Intven, Martijn; Philippens, Marielle E. P.; Reerink, Onne; Lagendijk, Jan J. W.; Raaymakers, Bas W.

2016-01-01

Reduction of motion uncertainty by applying adaptive radiotherapy strategies depends largely on the temporal behavior of this motion. To fully optimize adaptive strategies, insight into target motion is needed. The purpose of this study was to analyze stability and evolution in time of motion uncertainty of both the gross tumor volume (GTV) and clinical target volume (CTV) for patients with rectal cancer. We scanned 16 patients daily during one week, on a 1.5 T MRI scanner in treatment position, prior to each radiotherapy fraction. Single slice sagittal cine MRIs were made at the beginning, middle, and end of each scan session, for one minute at 2 Hz temporal resolution. GTV and CTV motion were determined by registering a delineated reference frame to time-points later in time. The 95th percentile of observed motion (dist95%) was taken as a measure of motion. The stability of motion in time was evaluated within each cine-MRI separately. The evolution of motion was investigated between the reference frame and the cine-MRIs of a single scan session and between the reference frame and the cine-MRIs of several days later in the course of treatment. This observed motion was then converted into a PTV-margin estimate. Within a one minute cine-MRI scan, motion was found to be stable and small. Independent of the time-point within the scan session, the average dist95% remains below 3.6 mm and 2.3 mm for CTV and GTV, respectively 90% of the time. We found similar motion over time intervals from 18 min to 4 days. When reducing the time interval from 18 min to 1 min, a large reduction in motion uncertainty is observed. A reduction in motion uncertainty, and thus the PTV-margin estimate, of 71% and 75% for CTV and tumor was observed, respectively. Time intervals of 15 and 30 s yield no further reduction in motion uncertainty compared to a 1 min time interval.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

PubMed Central

Cho, Youngjun; Julier, Simon J.; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-01-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area. PMID:29082079

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

PubMed

Cho, Youngjun; Julier, Simon J; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

2017-10-01

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Deformation Estimation In Non-Urban Areas Exploiting High Resolution SAR Data

NASA Astrophysics Data System (ADS)

Goel, Kanika; Adam, Nico

2012-01-01

Advanced techniques such as the Small Baseline Subset Algorithm (SBAS) have been developed for terrain motion mapping in non-urban areas with a focus on extracting information from distributed scatterers (DSs). SBAS uses small baseline differential interferograms (to limit the effects of geometric decorrelation) and these are typically multilooked to reduce phase noise, resulting in loss of resolution. Various error sources e.g. phase unwrapping errors, topographic errors, temporal decorrelation and atmospheric effects also affect the interferometric phase. The aim of our work is an improved deformation monitoring in non-urban areas exploiting high resolution SAR data. The paper provides technical details and a processing example of a newly developed technique which incorporates an adaptive spatial phase filtering algorithm for an accurate high resolution differential interferometric stacking, followed by deformation retrieval via the SBAS approach where we perform the phase inversion using a more robust L1 norm minimization.

Advances in Domain Connectivity for Overset Grids Using the X-Rays Approach

NASA Technical Reports Server (NTRS)

Chan, William M.; Kim, Noah; Pandya, Shishir A.

2012-01-01

Advances in automation and robustness of the X-rays approach to domain connectivity for overset grids are presented. Given the surface definition for each component that makes up a complex configuration, the determination of hole points with appropriate hole boundaries is automatically and efficiently performed. Improvements made to the original X-rays approach for identifying the minimum hole include an automated closure scheme for hole-cutters with open boundaries, automatic determination of grid points to be considered for blanking by each hole-cutter, and an adaptive X-ray map to economically handle components in close proximity. Furthermore, an automated spatially varying offset of the hole boundary from the minimum hole is achieved using a dual wall-distance function and an orphan point removal iteration process. Results using the new scheme are presented for a number of static and relative motion test cases on a variety of aerospace applications.

An extended Lagrangian method

NASA Technical Reports Server (NTRS)

Liou, Meng-Sing

1992-01-01

A unique formulation of describing fluid motion is presented. The method, referred to as 'extended Lagrangian method', is interesting from both theoretical and numerical points of view. The formulation offers accuracy in numerical solution by avoiding numerical diffusion resulting from mixing of fluxes in the Eulerian description. Meanwhile, it also avoids the inaccuracy incurred due to geometry and variable interpolations used by the previous Lagrangian methods. Unlike the Lagrangian method previously imposed which is valid only for supersonic flows, the present method is general and capable of treating subsonic flows as well as supersonic flows. The method proposed in this paper is robust and stable. It automatically adapts to flow features without resorting to clustering, thereby maintaining rather uniform grid spacing throughout and large time step. Moreover, the method is shown to resolve multi-dimensional discontinuities with a high level of accuracy, similar to that found in one-dimensional problems.

A slowly moving foreground can capture an observer's self-motion--a report of a new motion illusion: inverted vection.

PubMed

Nakamura, S; Shimojo, S

2000-01-01

We investigated interactions between foreground and background stimuli during visually induced perception of self-motion (vection) by using a stimulus composed of orthogonally moving random-dot patterns. The results indicated that, when the foreground moves with a slower speed, a self-motion sensation with a component in the same direction as the foreground is induced. We named this novel component of self-motion perception 'inverted vection'. The robustness of inverted vection was confirmed using various measures of self-motion sensation and under different stimulus conditions. The mechanism underlying inverted vection is discussed with regard to potentially relevant factors, such as relative motion between the foreground and background, and the interaction between the mis-registration of eye-movement information and self-motion perception.

Opposite effects of high- and low-frequency transcranial random noise stimulation probed with visual motion adaptation

PubMed Central

Campana, Gianluca; Camilleri, Rebecca; Moret, Beatrice; Ghin, Filippo; Pavan, Andrea

2016-01-01

Transcranial random noise stimulation (tRNS) is a recent neuro-modulation technique whose effects at both behavioural and neural level are still debated. Here we employed the well-known phenomenon of motion after-effect (MAE) in order to investigate the effects of high- vs. low-frequency tRNS on motion adaptation and recovery. Participants were asked to estimate the MAE duration following prolonged adaptation (20 s) to a complex moving pattern, while being stimulated with either sham or tRNS across different blocks. Different groups were administered with either high- or low-frequency tRNS. Stimulation sites were either bilateral human MT complex (hMT+) or frontal areas. The results showed that, whereas no effects on MAE duration were induced by stimulating frontal areas, when applied to the bilateral hMT+, high-frequency tRNS caused a significant decrease in MAE duration whereas low-frequency tRNS caused a significant corresponding increase in MAE duration. These findings indicate that high- and low-frequency tRNS have opposed effects on the adaptation-dependent unbalance between neurons tuned to opposite motion directions, and thus on neuronal excitability. PMID:27934947

Motion sickness and development of synergy within the spatial orientation system. A hypothetical unifying concept

NASA Technical Reports Server (NTRS)

Guedry, F. E.; Rupert, A. R.; Reschke, M. F.

1998-01-01

Adaptation to research paradigms such as rotating rooms and optical alteration of visual feedback during movement results in development of perceptual-motor programs that provide the reflexive assistance that is necessary to skilled control of movement and balance. The discomfort and stomach awareness that occur during the adaptation process has been attributed to conflicting sensory information about the state of motion. Vestibular signals depend on the kinematics of head movements irrespective of the presence or absence of signals from other senses. We propose that sensory conflict when vestibular signals are at least one component of the conflict are innately disturbing and unpleasant. This innate reaction is part of a continuum that operates early in life to prevent development of inefficient perceptual-motor programs. This reaction operates irrespective of and in addition to reward and punishment from parental guidance or goal attainment to yield efficient control of whole body movement in the operating environment of the individual. The same mechanism is involved in adapting the spatial orientation system to strange environments. This conceptual model "explains" why motion sickness is associated with adaptation to novel environments and is in general consistent with motion sickness literature.

Analysis and improvements of Adaptive Particle Refinement (APR) through CPU time, accuracy and robustness considerations

NASA Astrophysics Data System (ADS)

Chiron, L.; Oger, G.; de Leffe, M.; Le Touzé, D.

2018-02-01

While smoothed-particle hydrodynamics (SPH) simulations are usually performed using uniform particle distributions, local particle refinement techniques have been developed to concentrate fine spatial resolutions in identified areas of interest. Although the formalism of this method is relatively easy to implement, its robustness at coarse/fine interfaces can be problematic. Analysis performed in [16] shows that the radius of refined particles should be greater than half the radius of unrefined particles to ensure robustness. In this article, the basics of an Adaptive Particle Refinement (APR) technique, inspired by AMR in mesh-based methods, are presented. This approach ensures robustness with alleviated constraints. Simulations applying the new formalism proposed achieve accuracy comparable to fully refined spatial resolutions, together with robustness, low CPU times and maintained parallel efficiency.

Rapid feedback responses correlate with reach adaptation and properties of novel upper limb loads.

PubMed

Cluff, Tyler; Scott, Stephen H

2013-10-02

A hallmark of voluntary motor control is the ability to adjust motor patterns for novel mechanical or visuomotor contexts. Recent work has also highlighted the importance of feedback for voluntary control, leading to the hypothesis that feedback responses should adapt when we learn new motor skills. We tested this prediction with a novel paradigm requiring that human subjects adapt to a viscous elbow load while reaching to three targets. Target 1 required combined shoulder and elbow motion, target 2 required only elbow motion, and target 3 (probe target) required shoulder but no elbow motion. This simple approach controlled muscle activity at the probe target before, during, and after the application of novel elbow loads. Our paradigm allowed us to perturb the elbow during reaching movements to the probe target and identify several key properties of adapted stretch responses. Adapted long-latency responses expressed (de-) adaptation similar to reaching errors observed when we introduced (removed) the elbow load. Moreover, reaching errors during learning correlated with changes in the long-latency response, showing subjects who adapted more to the elbow load displayed greater modulation of their stretch responses. These adapted responses were sensitive to the size and direction of the viscous training load. Our results highlight an important link between the adaptation of feedforward and feedback control and suggest a key part of motor adaptation is to adjust feedback responses to the requirements of novel motor skills.

Two case reports-Use of relative motion orthoses to manage extensor tendon zones III and IV and sagittal band injuries in adjacent fingers.

PubMed

Hirth, Melissa J; Howell, Julianne W; O'Brien, Lisa

Case report. Injuries to adjacent fingers with differing extensor tendon (ET) zones and/or sagittal band pose a challenge to therapists as no treatment guidelines exist. This report highlights how the relative motion flexion/extension (RMF/RME) concepts were combined into one orthosis to manage a zone IV ET repair (RME) and a zone III central slip repair (RMF) in adjacent fingers (Case 1); and how a single RME orthosis was adapted to limit proximal interphalangeal joint motion to manage multi-level ET zone III-IV injuries and a sagittal band repair in adjacent fingers (case 2). Adapted relative motion orthoses allowed early active motion and graded exercises based on clinical reasoning and evidence. Outcomes were standard TAM% and Miller's criteria. 'Excellent' and 'good' outcomes were achieved by twelve weeks post surgery. Both cases returned to unrestricted work at 6 and 7 weeks. Neither reported functional deficits at discharge. Outcomes in 2 cases involving multiple digit injuries exceeded those previously reported for ET zone III-IV repairs. Relative motion orthoses can be adapted and applied to multi-finger injuries, eliminating the need for multiple, bulky or functionally-limiting orthoses. 4. Copyright © 2017 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

Adaptation to low pH and lignocellulosic inhibitors resulting in ethanolic fermentation and growth of Saccharomyces cerevisiae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Narayanan, Venkatachalam; Sànchez i Nogué, Violeta; van Niel, Ed W. J.

Here, lignocellulosic bioethanol from renewable feedstocks using Saccharomyces cerevisiae is a promising alternative to fossil fuels owing to environmental challenges. S. cerevisiae is frequently challenged by bacterial contamination and a combination of lignocellulosic inhibitors formed during the pre-treatment, in terms of growth, ethanol yield and productivity. We investigated the phenotypic robustness of a brewing yeast strain TMB3500 and its ability to adapt to low pH thereby preventing bacterial contamination along with lignocellulosic inhibitors by short-term adaptation and adaptive lab evolution (ALE). The short-term adaptation strategy was used to investigate the inherent ability of strain TMB3500 to activate a robust phenotypemore » involving pre-culturing yeast cells in defined medium with lignocellulosic inhibitors at pH 5.0 until late exponential phase prior to inoculating them in defined media with the same inhibitor cocktail at pH 3.7. Adapted cells were able to grow aerobically, ferment anaerobically (glucose exhaustion by 19 +/- 5 h to yield 0.45 +/- 0.01 g ethanol g glucose -1) and portray significant detoxification of inhibitors at pH 3.7, when compared to non-adapted cells. ALE was performed to investigate whether a stable strain could be developed to grow and ferment at low pH with lignocellulosic inhibitors in a continuous suspension culture. Though a robust population was obtained after 3600 h with an ability to grow and ferment at pH 3.7 with inhibitors, inhibitor robustness was not stable as indicated by the characterisation of the evolved culture possibly due to phenotypic plasticity. With further research, this short-term adaptation and low pH strategy could be successfully applied in lignocellulosic ethanol plants to prevent bacterial contamination.« less

Adaptation to low pH and lignocellulosic inhibitors resulting in ethanolic fermentation and growth of Saccharomyces cerevisiae

DOE PAGES

Narayanan, Venkatachalam; Sànchez i Nogué, Violeta; van Niel, Ed W. J.; ...

2016-08-26

Here, lignocellulosic bioethanol from renewable feedstocks using Saccharomyces cerevisiae is a promising alternative to fossil fuels owing to environmental challenges. S. cerevisiae is frequently challenged by bacterial contamination and a combination of lignocellulosic inhibitors formed during the pre-treatment, in terms of growth, ethanol yield and productivity. We investigated the phenotypic robustness of a brewing yeast strain TMB3500 and its ability to adapt to low pH thereby preventing bacterial contamination along with lignocellulosic inhibitors by short-term adaptation and adaptive lab evolution (ALE). The short-term adaptation strategy was used to investigate the inherent ability of strain TMB3500 to activate a robust phenotypemore » involving pre-culturing yeast cells in defined medium with lignocellulosic inhibitors at pH 5.0 until late exponential phase prior to inoculating them in defined media with the same inhibitor cocktail at pH 3.7. Adapted cells were able to grow aerobically, ferment anaerobically (glucose exhaustion by 19 +/- 5 h to yield 0.45 +/- 0.01 g ethanol g glucose -1) and portray significant detoxification of inhibitors at pH 3.7, when compared to non-adapted cells. ALE was performed to investigate whether a stable strain could be developed to grow and ferment at low pH with lignocellulosic inhibitors in a continuous suspension culture. Though a robust population was obtained after 3600 h with an ability to grow and ferment at pH 3.7 with inhibitors, inhibitor robustness was not stable as indicated by the characterisation of the evolved culture possibly due to phenotypic plasticity. With further research, this short-term adaptation and low pH strategy could be successfully applied in lignocellulosic ethanol plants to prevent bacterial contamination.« less

Intelligent robust control for uncertain nonlinear time-varying systems and its application to robotic systems.

PubMed

Chang, Yeong-Chan

2005-12-01

This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

Efficient low-bit-rate adaptive mesh-based motion compensation technique

NASA Astrophysics Data System (ADS)

Mahmoud, Hanan A.; Bayoumi, Magdy A.

2001-08-01

This paper proposes a two-stage global motion estimation method using a novel quadtree block-based motion estimation technique and an active mesh model. In the first stage, motion parameters are estimated by fitting block-based motion vectors computed using a new efficient quadtree technique, that divides a frame into equilateral triangle blocks using the quad-tree structure. Arbitrary partition shapes are achieved by allowing 4-to-1, 3-to-1 and 2-1 merge/combine of sibling blocks having the same motion vector . In the second stage, the mesh is constructed using an adaptive triangulation procedure that places more triangles over areas with high motion content, these areas are estimated during the first stage. finally the motion compensation is achieved by using a novel algorithm that is carried by both the encoder and the decoder to determine the optimal triangulation of the resultant partitions followed by affine mapping at the encoder. Computer simulation results show that the proposed method gives better performance that the conventional ones in terms of the peak signal-to-noise ration (PSNR) and the compression ratio (CR).

Robust inter-subject audiovisual decoding in functional magnetic resonance imaging using high-dimensional regression.

PubMed

Raz, Gal; Svanera, Michele; Singer, Neomi; Gilam, Gadi; Cohen, Maya Bleich; Lin, Tamar; Admon, Roee; Gonen, Tal; Thaler, Avner; Granot, Roni Y; Goebel, Rainer; Benini, Sergio; Valente, Giancarlo

2017-12-01

Major methodological advancements have been recently made in the field of neural decoding, which is concerned with the reconstruction of mental content from neuroimaging measures. However, in the absence of a large-scale examination of the validity of the decoding models across subjects and content, the extent to which these models can be generalized is not clear. This study addresses the challenge of producing generalizable decoding models, which allow the reconstruction of perceived audiovisual features from human magnetic resonance imaging (fMRI) data without prior training of the algorithm on the decoded content. We applied an adapted version of kernel ridge regression combined with temporal optimization on data acquired during film viewing (234 runs) to generate standardized brain models for sound loudness, speech presence, perceived motion, face-to-frame ratio, lightness, and color brightness. The prediction accuracies were tested on data collected from different subjects watching other movies mainly in another scanner. Substantial and significant (Q FDR <0.05) correlations between the reconstructed and the original descriptors were found for the first three features (loudness, speech, and motion) in all of the 9 test movies (R¯=0.62, R¯ = 0.60, R¯ = 0.60, respectively) with high reproducibility of the predictors across subjects. The face ratio model produced significant correlations in 7 out of 8 movies (R¯=0.56). The lightness and brightness models did not show robustness (R¯=0.23, R¯ = 0). Further analysis of additional data (95 runs) indicated that loudness reconstruction veridicality can consistently reveal relevant group differences in musical experience. The findings point to the validity and generalizability of our loudness, speech, motion, and face ratio models for complex cinematic stimuli (as well as for music in the case of loudness). While future research should further validate these models using controlled stimuli and explore the feasibility of extracting more complex models via this method, the reliability of our results indicates the potential usefulness of the approach and the resulting models in basic scientific and diagnostic contexts. Copyright © 2017 Elsevier Inc. All rights reserved.

Introductory review on `Flying Triangulation': a motion-robust optical 3D measurement principle

NASA Astrophysics Data System (ADS)

Ettl, Svenja

2015-04-01

'Flying Triangulation' (FlyTri) is a recently developed principle which allows for a motion-robust optical 3D measurement of rough surfaces. It combines a simple sensor with sophisticated algorithms: a single-shot sensor acquires 2D camera images. From each camera image, a 3D profile is generated. The series of 3D profiles generated are aligned to one another by algorithms, without relying on any external tracking device. It delivers real-time feedback of the measurement process which enables an all-around measurement of objects. The principle has great potential for small-space acquisition environments, such as the measurement of the interior of a car, and motion-sensitive measurement tasks, such as the intraoral measurement of teeth. This article gives an overview of the basic ideas and applications of FlyTri. The main challenges and their solutions are discussed. Measurement examples are also given to demonstrate the potential of the measurement principle.

Incremental inverse kinematics based vision servo for autonomous robotic capture of non-cooperative space debris

NASA Astrophysics Data System (ADS)

Dong, Gangqi; Zhu, Z. H.

2016-04-01

This paper proposed a new incremental inverse kinematics based vision servo approach for robotic manipulators to capture a non-cooperative target autonomously. The target's pose and motion are estimated by a vision system using integrated photogrammetry and EKF algorithm. Based on the estimated pose and motion of the target, the instantaneous desired position of the end-effector is predicted by inverse kinematics and the robotic manipulator is moved incrementally from its current configuration subject to the joint speed limits. This approach effectively eliminates the multiple solutions in the inverse kinematics and increases the robustness of the control algorithm. The proposed approach is validated by a hardware-in-the-loop simulation, where the pose and motion of the non-cooperative target is estimated by a real vision system. The simulation results demonstrate the effectiveness and robustness of the proposed estimation approach for the target and the incremental control strategy for the robotic manipulator.

Ambiguous Tilt and Translation Motion Cues in Astronauts After Space Flight (ZAG)

NASA Astrophysics Data System (ADS)

Clement, Guilles; Harm, Deborah; Rupert, Angus; Beaton, Kara; Wood, Scott

2008-06-01

Adaptive changes during space flight in how the brain integrates vestibular cues with visual, proprioceptive, and somatosensory information can lead to impaired movement coordination, vertigo, spatial disorientation, and perceptual illusions following transitions between gravity levels. This joint ESA-NASA pre- and post-flight experiment is designed to examine both the physiological basis and operational implications for disorientation and tilt-translation disturbances in astronauts following short-duration space flights. Specifically, this study addresses three questions: (1) What adaptive changes occur in eye movements and motion perception in response to different combinations of tilt and translation motion? (2) Do adaptive changes in tilt-translation responses impair ability to manually control vehicle orientation? (3) Can sensory substitution aids (e.g., tactile) mitigate risks associated with manual control of vehicle orientation?

Joint-space adaptive control of a 6 DOF end-effector with closed-kinematic chain mechanism

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Zhou, Zhen-Lei

1989-01-01

The development is presented for a joint-space adaptive scheme that controls the joint position of a six-degree-of-freedom (DOF) robot end-effector performing fine and precise motion within a very limited workspace. The end-effector was built to study autonomous assembly of NASA hardware in space. The design of the adaptive controller is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method. In the development, it is assumed that the end-effector performs slowly varying motion. Computer simulation is performed to investigate the performance of the developed control scheme on position control of the end-effector. Simulation results manifest that the adaptive control scheme provides excellent tracking of several test paths.

Dynamic control modification techniques in teleoperation of a flexible manipulator. M.S. Thesis

NASA Technical Reports Server (NTRS)

Magee, David Patrick

1991-01-01

The objective of this research is to reduce the end-point vibration of a large, teleoperated manipulator while preserving the usefulness of the system motion. A master arm is designed to measure desired joint angles as the user specifies a desired tip motion. The desired joint angles from the master arm are the inputs to an adaptive PD control algorithm that positions the end-point of the manipulator. As the user moves the tip of the master, the robot will vibrate at its natural frequencies which makes it difficult to position the end-point. To eliminate the tip vibration during teleoperated motions, an input shaping method is presented. The input shaping method transforms each sample of the desired input into a new set of impulses that do not excite the system resonances. The method is explained using the equation of motion for a simple, second-order system. The impulse response of such a system is derived and the constraint equations for vibrationless motion are presented. To evaluate the robustness of the method, a different residual vibration equation from Singer's is derived that more accurately represents the input shaping technique. The input shaping method is shown to actually increase the residual vibration in certain situations when the system parameters are not accurately specified. Finally, the implementation of the input shaping method to a system with varying parameters is shown to induce a vibration into the system. To eliminate this vibration, a modified command shaping technique is developed. The ability of the modified command shaping method to reduce vibration at the system resonances is tested by varying input perturbations to trajectories in a range of possible user inputs. By comparing the frequency responses of the transverse acceleration at the end-point of the manipulator, the modified method is compared to the original PD routine. The control scheme that produces the smaller magnitude of resonant vibration at the first natural frequency is considered the more effective control method.

Robust time and frequency domain estimation methods in adaptive control

NASA Technical Reports Server (NTRS)

Lamaire, Richard Orville

1987-01-01

A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

Cascade and parallel combination (CPC) of adaptive filters for estimating heart rate during intensive physical exercise from photoplethysmographic signal

PubMed Central

Islam, Mohammad Tariqul; Tanvir Ahmed, Sk.; Zabir, Ishmam; Shahnaz, Celia

2018-01-01

Photoplethysmographic (PPG) signal is getting popularity for monitoring heart rate in wearable devices because of simplicity of construction and low cost of the sensor. The task becomes very difficult due to the presence of various motion artefacts. In this study, an algorithm based on cascade and parallel combination (CPC) of adaptive filters is proposed in order to reduce the effect of motion artefacts. First, preliminary noise reduction is performed by averaging two channel PPG signals. Next in order to reduce the effect of motion artefacts, a cascaded filter structure consisting of three cascaded adaptive filter blocks is developed where three-channel accelerometer signals are used as references to motion artefacts. To further reduce the affect of noise, a scheme based on convex combination of two such cascaded adaptive noise cancelers is introduced, where two widely used adaptive filters namely recursive least squares and least mean squares filters are employed. Heart rates are estimated from the noise reduced PPG signal in spectral domain. Finally, an efficient heart rate tracking algorithm is designed based on the nature of the heart rate variability. The performance of the proposed CPC method is tested on a widely used public database. It is found that the proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach. PMID:29515812

Non-Invasive In Vivo Ultrasound Temperature Estimation

NASA Astrophysics Data System (ADS)

Bayat, Mahdi

New emerging technologies in thermal therapy require precise monitoring and control of the delivered thermal dose in a variety of situations. The therapeutic temperature changes in target tissues range from few degrees for releasing chemotherapy drugs encapsulated in the thermosensitive liposomes to boiling temperatures in complete ablation of tumors via cell necrosis. High intensity focused ultrasound (HIFU) has emerged as a promising modality for noninvasive surgery due to its ability to create precise mechanical and thermal effects at the target without affecting surrounding tissues. An essential element in all these procedures, however, is accurate estimation of the target tissue temperature during the procedure to ensure its safety and efficacy. The advent of diagnostic imaging tools for guidance of thermal therapy was a key factor in the clinical acceptance of these minimally invasive or noninvasive methods. More recently, ultrasound and magnetic resonance (MR) thermography techniques have been proposed for guidance, monitoring, and control of noninvasive thermal therapies. MR thermography has shown acceptable sensitivity and accuracy in imaging temperature change and it is currently FDA-approved on clinical HIFU units. However, it suffers from limitations like cost of integration with ultrasound therapy system and slow rate of imaging for real time guidance. Ultrasound, on the other hand, has the advantage of real time imaging and ease of integration with the therapy system. An infinitesimal model for imaging temperature change using pulse-echo ultrasound has been demonstrated, including in vivo small-animal imaging. However, this model suffers from limitations that prevent demonstration in more clinically-relevant settings. One limitation stems from the infinitesimal nature of the model, which results in spatial inconsistencies of the estimated temperature field. Another limitation is the sensitivity to tissue motion and deformation during in vivo, which could result in significant artifacts. The first part of this thesis addresses the first limitation by introducing the Recursive Echo Strain Filter (RESF) as a new temperature reconstruction model which largely corrects for the spatial inconsistencies resulting from the infinitesimal model. The performance of this model is validated using the data collected during sub therapeutic temperature changes in the tissue mimicking phantom as well as ex vivo tissue blocks. The second part of this thesis deals with in vivo ultrasound thermography. Tissue deformations caused by natural motions (e.g. respiration, gasping, blood pulsation etc) can create non-thermal changes to the ultrasound echoes which are not accounted for in the derivation of physical model for temperature estimation. These fluctuations can create severe artifacts in the estimated temperature field. Using statistical signal processing techniques an adaptive method is presented which takes advantage of the localized and global availability of these interference patterns and use this data to enhance the estimated temperature in the region of interest. We then propose a model based technique for continuous tracking of temperature in the presence of natural motion and deformation. The method uses the direct discretization of the transient bioheat equation to derive a state space model of temperature change. This model is then used to build a linear estimator based on the Kalman filtering capable of robust estimation of temperature change in the presence of tissue motion and deformation. The robustness of the adaptive and model-based models in removing motion and deformation artifacts is demonstrated using data from in vivo experiments. Both methods are shown to provide effective cancellation of the artifacts with minimal effect on the expected temperature dynamics.

Robust distributed control of spacecraft formation flying with adaptive network topology

NASA Astrophysics Data System (ADS)

Shasti, Behrouz; Alasty, Aria; Assadian, Nima

2017-07-01

In this study, the distributed six degree-of-freedom (6-DOF) coordinated control of spacecraft formation flying in low earth orbit (LEO) has been investigated. For this purpose, an accurate coupled translational and attitude relative dynamics model of the spacecraft with respect to the reference orbit (virtual leader) is presented by considering the most effective perturbation acceleration forces on LEO satellites, i.e. the second zonal harmonic and the atmospheric drag. Subsequently, the 6-DOF coordinated control of spacecraft in formation is studied. During the mission, the spacecraft communicate with each other through a switching network topology in which the weights of its graph Laplacian matrix change adaptively based on a distance-based connectivity function between neighboring agents. Because some of the dynamical system parameters such as spacecraft masses and moments of inertia may vary with time, an adaptive law is developed to estimate the parameter values during the mission. Furthermore, for the case that there is no knowledge of the unknown and time-varying parameters of the system, a robust controller has been developed. It is proved that the stability of the closed-loop system coupled with adaptation in network topology structure and optimality and robustness in control is guaranteed by the robust contraction analysis as an incremental stability method for multiple synchronized systems. The simulation results show the effectiveness of each control method in the presence of uncertainties and parameter variations. The adaptive and robust controllers show their superiority in reducing the state error integral as well as decreasing the control effort and settling time.

A multistage motion vector processing method for motion-compensated frame interpolation.

PubMed

Huang, Ai- Mei; Nguyen, Truong Q

2008-05-01

In this paper, a novel, low-complexity motion vector processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion vectors on different block sizes. Our method explicitly considers the reliability of each received motion vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion vectors. The motion vector reliability information is also used as a prior knowledge in motion vector refinement using a constrained vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.

Dosimetric evaluation of three adaptive strategies for prostate cancer treatment including pelvic lymph nodes irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cantin, Audrey; Gingras, Luc; Archambault, Louis, E-mail: louis.archambault@phy.ulaval.ca

Purpose: The movements of the prostate relative to the pelvic lymph nodes during intensity-modulated radiation therapy treatment can limit margin reduction and affect the protection of the organs at risk (OAR). In this study, the authors performed an analysis of three adaptive treatment strategies that combine information from both bony and gold marker registrations. The robustness of those treatments against the interfraction prostate movements was evaluated. Methods: A retrospective study was conducted on five prostate cancer patients with 7–13 daily cone-beam CTs (CBCTs). The clinical target volumes (CTVs) consisting of pelvic lymph nodes, prostate, and seminal vesicles as well asmore » the OARs were delineated on each CBCT and the initial CT. Three adaptive strategies were analyzed. Two of these methods relied on a two-step patient positioning at each fraction. First step: a bony registration was used to deliver the nodal CTV prescription. Second step: a gold marker registration was then used either to (1) complete the dose delivered to the prostate (complement); (2) or give almost the entire prescription to the prostate with a weak dose gradient between the targets to compensate for possible motions (gradient). The third method (COR) used a pool of precalculated plans based on images acquired at previous treatment fractions. At each new fraction, a plan is selected from that pool based on the daily position of prostate center-of-mass. The dosimetric comparison was conducted and results are presented with and without the systematic shift in the prostate position on the CT planning. The adaptive strategies were compared to the current clinical standard where all fractions are treated with the initial nonadaptive plan. Results: The minimum daily prostate D{sub 95%} is improved by 2%, 9%, and 6% for the complement, the gradient, and the COR approaches, respectively, compared to the nonadaptive method. The average nodal CTV D{sub 95%} remains constant across the strategies, except for the gradient approach where a reduction of 7% is observed. However, a correction of the systematic shift reduced the problem, and the adaptive strategies remain robust against the prostate movement across the fraction. The bladder V{sub 55Gy} is reduced by 35% on average for the adaptive strategies. Conclusions: Because they offer increased CTV coverage and OAR sparing, adaptive methods may be suitable candidates for simple and efficient adaptive treatment strategies for prostate cancer. Margin reduction and systematic error correction in the prostate position improve the protection of the OAR and the dose coverage. A cumulative dose to simulate a complete treatment would show real effects and allow a better comparison between each method.« less

Robust speech perception: Recognize the familiar, generalize to the similar, and adapt to the novel

PubMed Central

Kleinschmidt, Dave F.; Jaeger, T. Florian

2016-01-01

Successful speech perception requires that listeners map the acoustic signal to linguistic categories. These mappings are not only probabilistic, but change depending on the situation. For example, one talker’s /p/ might be physically indistinguishable from another talker’s /b/ (cf. lack of invariance). We characterize the computational problem posed by such a subjectively non-stationary world and propose that the speech perception system overcomes this challenge by (1) recognizing previously encountered situations, (2) generalizing to other situations based on previous similar experience, and (3) adapting to novel situations. We formalize this proposal in the ideal adapter framework: (1) to (3) can be understood as inference under uncertainty about the appropriate generative model for the current talker, thereby facilitating robust speech perception despite the lack of invariance. We focus on two critical aspects of the ideal adapter. First, in situations that clearly deviate from previous experience, listeners need to adapt. We develop a distributional (belief-updating) learning model of incremental adaptation. The model provides a good fit against known and novel phonetic adaptation data, including perceptual recalibration and selective adaptation. Second, robust speech recognition requires listeners learn to represent the structured component of cross-situation variability in the speech signal. We discuss how these two aspects of the ideal adapter provide a unifying explanation for adaptation, talker-specificity, and generalization across talkers and groups of talkers (e.g., accents and dialects). The ideal adapter provides a guiding framework for future investigations into speech perception and adaptation, and more broadly language comprehension. PMID:25844873

Experimental Validation of L1 Adaptive Control: Rohrs' Counterexample in Flight

NASA Technical Reports Server (NTRS)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Issac; Kitsios, Ioannis; Cao, Chengyu; Gregory, Irene M.; Valavani, Lena

2010-01-01

The paper presents new results on the verification and in-flight validation of an L1 adaptive flight control system, and proposes a general methodology for verification and validation of adaptive flight control algorithms. The proposed framework is based on Rohrs counterexample, a benchmark problem presented in the early 80s to show the limitations of adaptive controllers developed at that time. In this paper, the framework is used to evaluate the performance and robustness characteristics of an L1 adaptive control augmentation loop implemented onboard a small unmanned aerial vehicle. Hardware-in-the-loop simulations and flight test results confirm the ability of the L1 adaptive controller to maintain stability and predictable performance of the closed loop adaptive system in the presence of general (artificially injected) unmodeled dynamics. The results demonstrate the advantages of L1 adaptive control as a verifiable robust adaptive control architecture with the potential of reducing flight control design costs and facilitating the transition of adaptive control into advanced flight control systems.

Detecting Motion from a Moving Platform; Phase 2: Lightweight, Low Power Robust Means of Removing Image Jitter

DTIC Science & Technology

2011-11-01

common housefly , Musca domestica. “Lightweight, Low Power Robust Means of Removing Image Jitter,” (AFRL-RX-TY-TR-2011-0096-02) develops an optimal...biological vision system of the common housefly , Musca domestica. Several variations of this sensor were designed, simulated extensively, and hardware

A Robust Step Detection Algorithm and Walking Distance Estimation Based on Daily Wrist Activity Recognition Using a Smart Band.

PubMed

Trong Bui, Duong; Nguyen, Nhan Duc; Jeong, Gu-Min

2018-06-25

Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. Currently, these fields are facing many challenges, one of which is the lack of a robust algorithm with high performance. This paper proposes a new method to implement a robust step detection and adaptive distance estimation algorithm based on the classification of five daily wrist activities during walking at various speeds using a smart band. The key idea is that the non-parametric adaptive distance estimator is performed after two activity classifiers and a robust step detector. In this study, two classifiers perform two phases of recognizing five wrist activities during walking. Then, a robust step detection algorithm, which is integrated with an adaptive threshold, peak and valley correction algorithm, is applied to the classified activities to detect the walking steps. In addition, the misclassification activities are fed back to the previous layer. Finally, three adaptive distance estimators, which are based on a non-parametric model of the average walking speed, calculate the length of each strike. The experimental results show that the average classification accuracy is about 99%, and the accuracy of the step detection is 98.7%. The error of the estimated distance is 2.2⁻4.2% depending on the type of wrist activities.

Adaptive neural network motion control for aircraft under uncertainty conditions

NASA Astrophysics Data System (ADS)

Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

2018-02-01

We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

Geometric validation of self-gating k-space-sorted 4D-MRI vs 4D-CT using a respiratory motion phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Yong, E-mail: yong.yue@cshs.org; Yang, Wensha; McKenzie, Elizabeth

Purpose: MRI is increasingly being used for radiotherapy planning, simulation, and in-treatment-room motion monitoring. To provide more detailed temporal and spatial MR data for these tasks, we have recently developed a novel self-gated (SG) MRI technique with advantage of k-space phase sorting, high isotropic spatial resolution, and high temporal resolution. The current work describes the validation of this 4D-MRI technique using a MRI- and CT-compatible respiratory motion phantom and comparison to 4D-CT. Methods: The 4D-MRI sequence is based on a spoiled gradient echo-based 3D projection reconstruction sequence with self-gating for 4D-MRI at 3 T. Respiratory phase is resolved by usingmore » SG k-space lines as the motion surrogate. 4D-MRI images are reconstructed into ten temporal bins with spatial resolution 1.56 × 1.56 × 1.56 mm{sup 3}. A MRI-CT compatible phantom was designed to validate the performance of the 4D-MRI sequence and 4D-CT imaging. A spherical target (diameter 23 mm, volume 6.37 ml) filled with high-concentration gadolinium (Gd) gel is embedded into a plastic box (35 × 40 × 63 mm{sup 3}) and stabilized with low-concentration Gd gel. The phantom, driven by an air pump, is able to produce human-type breathing patterns between 4 and 30 respiratory cycles/min. 4D-CT of the phantom has been acquired in cine mode, and reconstructed into ten phases with slice thickness 1.25 mm. The 4D images sets were imported into a treatment planning software for target contouring. The geometrical accuracy of the 4D MRI and CT images has been quantified using target volume, flattening, and eccentricity. The target motion was measured by tracking the centroids of the spheres in each individual phase. Motion ground-truth was obtained from input signals and real-time video recordings. Results: The dynamic phantom has been operated in four respiratory rate (RR) settings, 6, 10, 15, and 20/min, and was scanned with 4D-MRI and 4D-CT. 4D-CT images have target-stretching, partial-missing, and other motion artifacts in various phases, whereas the 4D-MRI images are visually free of those artifacts. Volume percentage difference for the 6.37 ml target ranged from 5.3% ± 4.3% to 10.3% ± 5.9% for 4D-CT, and 1.47 ± 0.52 to 2.12 ± 1.60 for 4D-MRI. With an increase of respiratory rate, the target volumetric and geometric deviations increase for 4D-CT images while remaining stable for the 4D-MRI images. Target motion amplitude errors at different RRs were measured with a range of 0.66–1.25 mm for 4D-CT and 0.2–0.42 mm for 4D-MRI. The results of Mann–Whitney tests indicated that 4D-MRI significantly outperforms 4D-CT in phase-based target volumetric (p = 0.027) and geometric (p < 0.001) measures. Both modalities achieve equivalent accuracy in measuring motion amplitude (p = 0.828). Conclusions: The k-space self-gated 4D-MRI technique provides a robust method for accurately imaging phase-based target motion and geometry. Compared to 4D-CT, the current 4D-MRI technique demonstrates superior spatiotemporal resolution, and robust resistance to motion artifacts caused by fast target motion and irregular breathing patterns. The technique can be used extensively in abdominal targeting, motion gating, and toward implementing MRI-based adaptive radiotherapy.« less

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Robust local search for spacecraft operations using adaptive noise

NASA Technical Reports Server (NTRS)

Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve

2004-01-01

Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

Addressing uncertainty in adaptation planning for agriculture.

PubMed

Vermeulen, Sonja J; Challinor, Andrew J; Thornton, Philip K; Campbell, Bruce M; Eriyagama, Nishadi; Vervoort, Joost M; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J; Hawkins, Ed; Smith, Daniel R

2013-05-21

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

Addressing uncertainty in adaptation planning for agriculture

PubMed Central

Vermeulen, Sonja J.; Challinor, Andrew J.; Thornton, Philip K.; Campbell, Bruce M.; Eriyagama, Nishadi; Vervoort, Joost M.; Kinyangi, James; Jarvis, Andy; Läderach, Peter; Ramirez-Villegas, Julian; Nicklin, Kathryn J.; Hawkins, Ed; Smith, Daniel R.

2013-01-01

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty. PMID:23674681

Vivid Motor Imagery as an Adaptation Method for Head Turns on a Short-Arm Centrifuge

NASA Technical Reports Server (NTRS)

Newby, N. J.; Mast, F. W.; Natapoff, A.; Paloski, W. H.

2006-01-01

Artificial gravity (AG) has been proposed as a potential countermeasure to the debilitating physiological effects of long duration space flight. The most economical means of implementing AG may be through the use of a short-radius (2m or less) centrifuge. For such a device to produce gravitational forces comparable to those on earth requires rotation rates in excess of 20 revolutions per minute (rpm). Head turns made out of the plane of rotation at these rates, as may be necessary if exercise is combined with AG, result in cross-coupled stimuli (CCS) that cause adverse side effects including motion sickness, illusory sensations of motion, and inappropriate eye movements. Recent studies indicate that people can adapt to CCS and reduce these side effects by making multiple head turns during centrifuge sessions conducted over consecutive days. However, about 25% of the volunteers for these studies have difficulty tolerating the CCS adaptation paradigm and often drop out due to motion sickness symptoms. The goal of this investigation was to determine whether vivid motor imagery could be used as a pseudostimulus for adapting subjects to this unique environment. Twenty four healthy human subjects (14 males, 10 females), ranging in age from 21 to 48 years (mean 33, sd 7 years) took part in this study. The experimental stimuli were produced using the NASA JSC short-arm centrifuge (SAC). Subjects were oriented supinely on this device with the nose pointed toward the ceiling and head centered on the axis of rotation. Thus, centrifuge rotation was in the body roll plane. After ramp-up the SAC rotated clockwise at a constant rate of 23 rpm, producing a centrifugal force of approximately 1 g at the feet. Semicircular canal CCS were produced by having subjects make yaw head turns from the nose up (NU) position to the right ear down (RED) position and from RED to NU. Each head turn was completed in about one second, and a 30 second recovery period separated consecutive head movements. Participants were randomly assigned to one of three groups (n=8 per group): physical adapters (PA), mental adapters (MA), or a control group (CG). Each subject participated in a one hour test session on each of three consecutive days. Each test session consisted of an initial (preadaptation) period during which the subject performed six CCS maneuvers in the dark, followed by an adaptation period with internal lighting on the centrifuge, and a final (postadaptation) period during which six more CCS maneuvers were performed in the dark. For the PA group, the adaptation period consisted of performing 30 additional CCS maneuvers in the light. For the MA and CG group the centrifuge was ramped down to 0 rpm after the pre-adaptation period and ramped back up to 23 rpm before the post-adaptation period. For the both of these groups, the adaptation period consisted of making 30 CCS maneuvers in the light with the centrifuge stationary (so no cross-coupling occurred). MA group subjects were instructed to vividly imagine the provocative sensations produced by the preadaptation CCS maneuvers in terms of magnitude, duration, and direction of illusory body tilt, as well as any accompanying levels of motion sickness. CG group subjects were asked to answer low imagery content questions (trivial pursuit) during each adaptation period head turn. During the 30 second recovery following each head turn, psychophysical data were collected including self reports of motion sickness, magnitude and direction estimates of illusory body tilt, and the overall duration of these sensations. A multilevel mixed effects linear regression analysis performed on all response variables indicated that all three groups experienced some psychophysical adaptation across the three test sessions. For illusory tilt magnitude, the PA group exhibited the most overall adaptation, followed by the MA group, and the CG group. The slopes of these adaptation trajectories by group over day were significantly diffent from one another. For the perceived duration of sensations, the CG group again exhibited the least amount of adaptation. However, the rates of adaptation of the PA and the MA groups were indistinguishable, suggesting that the imagined pseudostimulus appeared to be just as effective a means of adaptation as the actual stimulus. The MA group's rate of adaptation to motion sickness symptoms was also comparable to the PA group. The use of vivid motor imagery may be an effective method for adapting to the illusory sensations and motion sickness symptoms produced by cross-coupled stimuli. For space-based AG applications, this technique may prove quite useful in retaining astronauts considered highly susceptible to motion sickness as it reduces the number of actual CCS required to attain adaptation.

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

NASA Technical Reports Server (NTRS)

Canfield, Stephen

1999-01-01

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Motion-robust intensity-modulated proton therapy for distal esophageal cancer.

PubMed

Yu, Jen; Zhang, Xiaodong; Liao, Li; Li, Heng; Zhu, Ronald; Park, Peter C; Sahoo, Narayan; Gillin, Michael; Li, Yupeng; Chang, Joe Y; Komaki, Ritsuko; Lin, Steven H

2016-03-01

To develop methods for evaluation and mitigation of dosimetric impact due to respiratory and diaphragmatic motion during free breathing in treatment of distal esophageal cancers using intensity-modulated proton therapy (IMPT). This was a retrospective study on 11 patients with distal esophageal cancer. For each patient, four-dimensional computed tomography (4D CT) data were acquired, and a nominal dose was calculated on the average phase of the 4D CT. The changes of water equivalent thickness (ΔWET) to cover the treatment volume from the peak of inspiration to the valley of expiration were calculated for a full range of beam angle rotation. Two IMPT plans were calculated: one at beam angles corresponding to small ΔWET and one at beam angles corresponding to large ΔWET. Four patients were selected for the calculation of 4D-robustness-optimized IMPT plans due to large motion-induced dose errors generated in conventional IMPT. To quantitatively evaluate motion-induced dose deviation, the authors calculated the lowest dose received by 95% (D95) of the internal clinical target volume for the nominal dose, the D95 calculated on the maximum inhale and exhale phases of 4D CT DCT0 andDCT50 , the 4D composite dose, and the 4D dynamic dose for a single fraction. The dose deviation increased with the average ΔWET of the implemented beams, ΔWETave. When ΔWETave was less than 5 mm, the dose error was less than 1 cobalt gray equivalent based on DCT0 and DCT50 . The dose deviation determined on the basis of DCT0 and DCT50 was proportionally larger than that determined on the basis of the 4D composite dose. The 4D-robustness-optimized IMPT plans notably reduced the overall dose deviation of multiple fractions and the dose deviation caused by the interplay effect in a single fraction. In IMPT for distal esophageal cancer, ΔWET analysis can be used to select the beam angles that are least affected by respiratory and diaphragmatic motion. To further reduce dose deviation, the 4D-robustness optimization can be implemented for IMPT planning. Calculation of DCT0 and DCT50 is a conservative method to estimate the motion-induced dose errors.

Perceived self-orientation and self-motion in microgravity, after landing and during preflight adaptation training

NASA Technical Reports Server (NTRS)

Harm, D. L.; Parker, D. E.

1993-01-01

The research described in this paper is intended to support development and evaluation of preflight adaptation training (PAT) apparatus and procedures. Successful training depends on appropriate manipulation of visual and inertial stimuli that control perception of self-motion and self-orientation. For one part of this process, astronauts are trained to report their self-motion and self-orientation experiences. Before their space mission, they are exposed to the altered sensory environments produced by the PAT trainers. During and after the mission, they report their motion and orientation experiences. Subsequently, they are again exposed to the PAT trainers and are asked to describe relationships between their experiences in microgravity and following entry and their experiences in the trainers.

Inverse dynamics of adaptive structures used as space cranes

NASA Technical Reports Server (NTRS)

Das, S. K.; Utku, S.; Wada, B. K.

1990-01-01

As a precursor to the real-time control of fast moving adaptive structures used as space cranes, a formulation is given for the flexibility induced motion relative to the nominal motion (i.e., the motion that assumes no flexibility) and for obtaining the open loop time varying driving forces. An algorithm is proposed for the computation of the relative motion and driving forces. The governing equations are given in matrix form with explicit functional dependencies. A simulator is developed to implement the algorithm on a digital computer. In the formulations, the distributed mass of the crane is lumped by two schemes, vz., 'trapezoidal' lumping and 'Simpson's rule' lumping. The effects of the mass lumping schemes are shown by simulator runs.

Adaptive identification of vessel's added moments of inertia with program motion

NASA Astrophysics Data System (ADS)

Alyshev, A. S.; Melnikov, V. G.

2018-05-01

In this paper, we propose a new experimental method for determining the moments of inertia of the ship model. The paper gives a brief review of existing methods, a description of the proposed method and experimental stand, test procedures and calculation formulas and experimental results. The proposed method is based on the energy approach with special program motions. The ship model is fixed in a special rack consisting of a torsion element and a set of additional servo drives with flywheels (reactive wheels), which correct the motion. The servo drives with an adaptive controller provide the symmetry of the motion, which is necessary for the proposed identification procedure. The effectiveness of the proposed approach is confirmed by experimental results.

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

SU-E-J-57: First Development of Adapting to Intrafraction Relative Motion Between Prostate and Pelvic Lymph Nodes Targets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ge, Y; Colvill, E; O’Brien, R

2015-06-15

Purpose Large intrafraction relative motion of multiple targets is common in advanced head and neck, lung, abdominal, gynaecological and urological cancer, jeopardizing the treatment outcomes. The objective of this study is to develop a real-time adaptation strategy, for the first time, to accurately correct for the relative motion of multiple targets by reshaping the treatment field using the multi-leaf collimator (MLC). Methods The principle of tracking the simultaneously treated but differentially moving tumor targets is to determine the new aperture shape that conforms to the shifted targets. Three dimensional volumes representing the individual targets are projected to the beam’s eyemore » view. The leaf openings falling inside each 2D projection will be shifted according to the measured motion of each target to form the new aperture shape. Based on the updated beam shape, new leaf positions will be determined with optimized trade-off between the target underdose and healthy tissue overdose, and considerations of the physical constraints of the MLC. Taking a prostate cancer patient with pelvic lymph node involvement as an example, a preliminary dosimetric study was conducted to demonstrate the potential treatment improvement compared to the state-of- art adaptation technique which shifts the whole beam to track only one target. Results The world-first intrafraction adaptation system capable of reshaping the beam to correct for the relative motion of multiple targets has been developed. The dose in the static nodes and small bowel are closer to the planned distribution and the V45 of small bowel is decreased from 110cc to 75cc, corresponding to a 30% reduction by this technique compared to the state-of-art adaptation technique. Conclusion The developed adaptation system to correct for intrafraction relative motion of multiple targets will guarantee the tumour coverage and thus enable PTV margin reduction to minimize the high target dose to the adjacent organs-at-risk. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship and NHMRC Project Grant No. APP1042375.« less

Sensorimotor Adaptation Following Exposure to Ambiguous Inertial Motion Cues

NASA Technical Reports Server (NTRS)

Wood, S. J.; Clement, G. R.; Rupert, A. H.; Reschke, M. F.; Harm, D. L.; Guedry, F. E.

2007-01-01

The central nervous system must resolve the ambiguity of inertial motion sensory cues in order to derive accurate spatial orientation awareness. Adaptive changes in how inertial cues from the otolith system are integrated with other sensory information lead to perceptual and postural disturbances upon return to Earth s gravity. The primary goals of this ground-based research investigation are to explore physiological mechanisms and operational implications of tilt-translation disturbances during and following re-entry, and to evaluate a tactile prosthesis as a countermeasure for improving control of whole-body orientation during tilt and translation motion.

Motion planning for an adaptive wing structure with macro-fiber composite actuators

NASA Astrophysics Data System (ADS)

Schröck, J.; Meurer, T.; Kugi, A.

2009-05-01

A systematic approach for flatness-based motion planning and feedforward control is presented for the transient shaping of a piezo-actuated rectangular cantilevered plate modeling an adaptive wing. In the first step the consideration of an idealized infinite-dimensional input allows to determine the state and input parametrization in terms of a flat or basic output, which is used for a systematic motion planning approach. Subsequently, the obtained idealized input function is projected onto a finite number of suitably placed Macro-fiber Composite (MFC) patch actuators. The tracking performance of the proposed approach is evaluated in a simulation scenario.

A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems.

PubMed

Lyu, Weiwei; Cheng, Xianghong

2017-11-28

Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method.

Adapting to Adaptations: Behavioural Strategies that are Robust to Mutations and Other Organisational-Transformations

PubMed Central

Egbert, Matthew D.; Pérez-Mercader, Juan

2016-01-01

Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism’s internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving “interoceptively,” i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms. PMID:26743579

Preflight Adaptation Training for Spatial Orientation and Space Motion Sickness

NASA Technical Reports Server (NTRS)

Harm, Deborah L.; Parker, Donald E.

1994-01-01

Two part-task preflight adaptation trainers (PATs) are being developed at the NASA Johnson Space Center to preadapt astronauts to novel sensory stimulus conditions similar to those present in microgravity to facilitate adaptation to microgravity and readaptation to Earth. This activity is a major component of a general effort to develop countermeasures aimed at minimizing sensory and sensorimotor disturbances and Space Motion Sickness (SMS) associated with adaptation to microgravity and readaptation to Earth. Design principles for the development of the two trainers are discussed, along with a detailed description of both devices. In addition, a summary of four ground-based investigations using one of the trainers to determine the extent to which various novel sensory stimulus conditions produce changes in compensatory eye movement responses, postural equilibrium, motion sickness symptoms, and electrogastric responses are presented. Finally, a brief description of the general concept of dual-adopted states that underly the development of the PATs, and ongoing and future operational and basic research activities are presented.

Adaptive independent joint control of manipulators - Theory and experiment

NASA Technical Reports Server (NTRS)

Seraji, H.

1988-01-01

The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

Violent Interaction Detection in Video Based on Deep Learning

NASA Astrophysics Data System (ADS)

Zhou, Peipei; Ding, Qinghai; Luo, Haibo; Hou, Xinglin

2017-06-01

Violent interaction detection is of vital importance in some video surveillance scenarios like railway stations, prisons or psychiatric centres. Existing vision-based methods are mainly based on hand-crafted features such as statistic features between motion regions, leading to a poor adaptability to another dataset. En lightened by the development of convolutional networks on common activity recognition, we construct a FightNet to represent the complicated visual violence interaction. In this paper, a new input modality, image acceleration field is proposed to better extract the motion attributes. Firstly, each video is framed as RGB images. Secondly, optical flow field is computed using the consecutive frames and acceleration field is obtained according to the optical flow field. Thirdly, the FightNet is trained with three kinds of input modalities, i.e., RGB images for spatial networks, optical flow images and acceleration images for temporal networks. By fusing results from different inputs, we conclude whether a video tells a violent event or not. To provide researchers a common ground for comparison, we have collected a violent interaction dataset (VID), containing 2314 videos with 1077 fight ones and 1237 no-fight ones. By comparison with other algorithms, experimental results demonstrate that the proposed model for violent interaction detection shows higher accuracy and better robustness.

Design and control of a multi-DOF micromanipulator dedicated to multiscale micromanipulation

NASA Astrophysics Data System (ADS)

Yang, Yi-Ling; Wei, Yan-Ding; Lou, Jun-Qiang; Fu, Lei; Fang, Sheng

2017-11-01

This paper presents the design, implementation and control of a new piezoelectrically actuated compliant micromanipulator dedicated to multiscale, precision and reliable operations. To begin with, the manipulator is devised to obtain multi degrees of freedom and large workspace ranges. Two-stage amplification mechanisms (consists of the leverage and the rocker mechanisms) and composite parallelogram mechanisms are combined to construct the lower microstage. Meanwhile, the structure design of the upper dual-driven microgripper is based on the bridge-type mechanism and the unilateral parallelogram mechanism. Through finite-element analysis, the structural parameters of the micromanipulator are optimized and the structural interaction performances are examined. Moreover, a cooperative control strategy is proposed to achieve the synchronous control of the motion trajectory, the gripper position and the contact force. Precision motion control in terms of the hysteresis phenomenon and system disturbances is ensured by using an adaptive sliding mode control (SMC). In particular, an improved nonsymmetrical Bouc-Wen model and a fuzzy regulator are proposed in the SMC. Several experimental investigations are conducted to validate the effectiveness of the developed micromanipulator by performing transferring operations of a micro-object. Experimental results demonstrate that the micromanipulator presents good characteristics, and precision and robust operation can be acquired using the cooperative controller.

Variable Neural Adaptive Robust Control: A Switched System Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

2015-05-01

Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less

Reciprocity Between Robustness of Period and Plasticity of Phase in Biological Clocks

NASA Astrophysics Data System (ADS)

Hatakeyama, Tetsuhiro S.; Kaneko, Kunihiko

2015-11-01

Circadian clocks exhibit the robustness of period and plasticity of phase against environmental changes such as temperature and nutrient conditions. Thus far, however, it is unclear how both are simultaneously achieved. By investigating distinct models of circadian clocks, we demonstrate reciprocity between robustness and plasticity: higher robustness in the period implies higher plasticity in the phase, where changes in period and in phase follow a linear relationship with a negative coefficient. The robustness of period is achieved by the adaptation on the limit cycle via a concentration change of a buffer molecule, whose temporal change leads to a phase shift following a shift of the limit-cycle orbit in phase space. Generality of reciprocity in clocks with the adaptation mechanism is confirmed with theoretical analysis of simple models, while biological significance is discussed.

A Robust Self-Alignment Method for Ship's Strapdown INS Under Mooring Conditions

PubMed Central

Sun, Feng; Lan, Haiyu; Yu, Chunyang; El-Sheimy, Naser; Zhou, Guangtao; Cao, Tong; Liu, Hang

2013-01-01

Strapdown inertial navigation systems (INS) need an alignment process to determine the initial attitude matrix between the body frame and the navigation frame. The conventional alignment process is to compute the initial attitude matrix using the gravity and Earth rotational rate measurements. However, under mooring conditions, the inertial measurement unit (IMU) employed in a ship's strapdown INS often suffers from both the intrinsic sensor noise components and the external disturbance components caused by the motions of the sea waves and wind waves, so a rapid and precise alignment of a ship's strapdown INS without any auxiliary information is hard to achieve. A robust solution is given in this paper to solve this problem. The inertial frame based alignment method is utilized to adapt the mooring condition, most of the periodical low-frequency external disturbance components could be removed by the mathematical integration and averaging characteristic of this method. A novel prefilter named hidden Markov model based Kalman filter (HMM-KF) is proposed to remove the relatively high-frequency error components. Different from the digital filters, the HMM-KF barely cause time-delay problem. The turntable, mooring and sea experiments favorably validate the rapidness and accuracy of the proposed self-alignment method and the good de-noising performance of HMM-KF. PMID:23799492

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

PubMed

Yang, Yehui; Hu, Wenrui; Xie, Yuan; Zhang, Wensheng; Zhang, Tianzhu

2017-02-01

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l 1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

Adaptation to visual or auditory time intervals modulates the perception of visual apparent motion

PubMed Central

Zhang, Huihui; Chen, Lihan; Zhou, Xiaolin

2012-01-01

It is debated whether sub-second timing is subserved by a centralized mechanism or by the intrinsic properties of task-related neural activity in specific modalities (Ivry and Schlerf, 2008). By using a temporal adaptation task, we investigated whether adapting to different time intervals conveyed through stimuli in different modalities (i.e., frames of a visual Ternus display, visual blinking discs, or auditory beeps) would affect the subsequent implicit perception of visual timing, i.e., inter-stimulus interval (ISI) between two frames in a Ternus display. The Ternus display can induce two percepts of apparent motion (AM), depending on the ISI between the two frames: “element motion” for short ISIs, in which the endmost disc is seen as moving back and forth while the middle disc at the overlapping or central position remains stationary; “group motion” for longer ISIs, in which both discs appear to move in a manner of lateral displacement as a whole. In Experiment 1, participants adapted to either the typical “element motion” (ISI = 50 ms) or the typical “group motion” (ISI = 200 ms). In Experiments 2 and 3, participants adapted to a time interval of 50 or 200 ms through observing a series of two paired blinking discs at the center of the screen (Experiment 2) or hearing a sequence of two paired beeps (with pitch 1000 Hz). In Experiment 4, participants adapted to sequences of paired beeps with either low pitches (500 Hz) or high pitches (5000 Hz). After adaptation in each trial, participants were presented with a Ternus probe in which the ISI between the two frames was equal to the transitional threshold of the two types of motions, as determined by a pretest. Results showed that adapting to the short time interval in all the situations led to more reports of “group motion” in the subsequent Ternus probes; adapting to the long time interval, however, caused no aftereffect for visual adaptation but significantly more reports of group motion for auditory adaptation. These findings, suggesting amodal representation for sub-second timing across modalities, are interpreted in the framework of temporal pacemaker model. PMID:23133408

Magnitude Estimation for the 2011 Tohoku-Oki Earthquake Based on Ground Motion Prediction Equations

NASA Astrophysics Data System (ADS)

Eshaghi, Attieh; Tiampo, Kristy F.; Ghofrani, Hadi; Atkinson, Gail M.

2015-08-01

This study investigates whether real-time strong ground motion data from seismic stations could have been used to provide an accurate estimate of the magnitude of the 2011 Tohoku-Oki earthquake in Japan. Ultimately, such an estimate could be used as input data for a tsunami forecast and would lead to more robust earthquake and tsunami early warning. We collected the strong motion accelerograms recorded by borehole and free-field (surface) Kiban Kyoshin network stations that registered this mega-thrust earthquake in order to perform an off-line test to estimate the magnitude based on ground motion prediction equations (GMPEs). GMPEs for peak ground acceleration and peak ground velocity (PGV) from a previous study by Eshaghi et al. in the Bulletin of the Seismological Society of America 103. (2013) derived using events with moment magnitude ( M) ≥ 5.0, 1998-2010, were used to estimate the magnitude of this event. We developed new GMPEs using a more complete database (1998-2011), which added only 1 year but approximately twice as much data to the initial catalog (including important large events), to improve the determination of attenuation parameters and magnitude scaling. These new GMPEs were used to estimate the magnitude of the Tohoku-Oki event. The estimates obtained were compared with real time magnitude estimates provided by the existing earthquake early warning system in Japan. Unlike the current operational magnitude estimation methods, our method did not saturate and can provide robust estimates of moment magnitude within ~100 s after earthquake onset for both catalogs. It was found that correcting for average shear-wave velocity in the uppermost 30 m () improved the accuracy of magnitude estimates from surface recordings, particularly for magnitude estimates of PGV (Mpgv). The new GMPEs also were used to estimate the magnitude of all earthquakes in the new catalog with at least 20 records. Results show that the magnitude estimate from PGV values using borehole recordings had the smallest standard deviation among the estimated magnitudes and produced more stable and robust magnitude estimates. This suggests that incorporating borehole strong ground-motion records immediately available after the occurrence of large earthquakes can provide robust and accurate magnitude estimation.

Comparison of Shoulder Range of Motion, Strength, and Playing Time in Uninjured High School Baseball Pitchers Who Reside in Warm- and Cold-Weather Climates

PubMed Central

Kaplan, Kevin M.; ElAttrache, Neal S.; Jobe, Frank W.; Morrey, Bernard F.; Kaufman, Kenton R.; Hurd, Wendy J.

2014-01-01

Background There is an assumption that baseball athletes who reside in warm-weather climates experience larger magnitude adaptations in throwing shoulder motion and strength compared with their peers who reside in cold-weather climates. Hypotheses (1) The warm-weather climate (WWC) group would exhibit more pronounced shoulder motion and strength adaptations than the cold-weather climate (CWC) group, and (2) the WWC group would participate in pitching activities for a greater proportion of the year than the CWC group, with the time spent pitching predicting throwing shoulder motion and strength in both groups. Study Design Cross-sectional study; Level of evidence, 3. Methods One hundred uninjured high school pitchers (50 each WWC, CWC) were recruited. Rotational shoulder motion and isometric strength were measured and participants reported the number of months per year they pitched. To identify differences between groups, t tests were performed; linear regression was used to determine the influence of pitching volume on shoulder motion and strength. Results The WWC group pitched more months per year than athletes from the CWC group, with the number of months spent pitching negatively related to internal rotation motion and external rotation strength. The WWC group exhibited greater shoulder range of motion in all planes compared with the CWC group, as well as significantly lower external rotation strength and external/internal rotation strength ratios. There was no difference in internal rotation strength between groups, nor a difference in the magnitude of side-to-side differences for strength or motion measures. Conclusion Athletes who reside in cold- and warm-weather climates exhibit differences in throwing shoulder motion and strength, related in part to the number of months spent participating in pitching activities. The amount of time spent participating in pitching activities and the magnitude of range of motion and strength adaptations in athletes who reside in warm-weather climates may make these athletes more susceptible to throwing-related injuries. PMID:21051421

Space motion sickness

NASA Technical Reports Server (NTRS)

Homick, J. L.

1979-01-01

Research on the etiology, prediction, treatment and prevention of space motion sickness, designed to minimize the impact of this syndrome which was experienced frequently and with severity by individuals on the Skylab missions, on Space Shuttle crews is reviewed. Theories of the cause of space motion sickness currently under investigation by NASA include sensory conflict, which argues that motion sickness symptoms result from a mismatch between the total pattern of information from the spatial senses and that stored from previous experiences, and fluid shift, based upon the redistribution of bodily fluids that occurs upon continued exposure to weightlessness. Attempts are underway to correlate space motion sickness susceptibility to different provocative environments, vestibular and nonvestibular responses, and the rate of acquisition and length of retention of sensory adaptation. Space motion sickness countermeasures under investigation include various drug combinations, of which the equal combination of promethazine and ephedrine has been found to be as effective as the scopolomine and dexedrine combination, and vestibular adaptation and biofeedback training and autogenic therapy.

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

PubMed Central

Yuan, Amy; Wei, Jie; Gaebler, Carl P.; Huang, Hailiang; Olek, Devin; Li, Guang

2016-01-01

Purpose To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. Methods and Materials A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. Results The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm3 (−26% to 61%), and the ΔBP ranged from 0 to 0.2 (−71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P = .0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P = .72) predicted with the 5-dimensional model. Conclusions A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation. PMID:27745981

A Novel Respiratory Motion Perturbation Model Adaptable to Patient Breathing Irregularities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, Amy; Wei, Jie; Gaebler, Carl P.

Purpose: To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. Methods and Materials: A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2more » amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. Results: The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm{sup 3} (−26% to 61%), and the ΔBP ranged from 0 to 0.2 (−71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model. Conclusions: A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.« less

Active eye-tracking for an adaptive optics scanning laser ophthalmoscope

PubMed Central

Sheehy, Christy K.; Tiruveedhula, Pavan; Sabesan, Ramkumar; Roorda, Austin

2015-01-01

We demonstrate a system that combines a tracking scanning laser ophthalmoscope (TSLO) and an adaptive optics scanning laser ophthalmoscope (AOSLO) system resulting in both optical (hardware) and digital (software) eye-tracking capabilities. The hybrid system employs the TSLO for active eye-tracking at a rate up to 960 Hz for real-time stabilization of the AOSLO system. AOSLO videos with active eye-tracking signals showed, at most, an amplitude of motion of 0.20 arcminutes for horizontal motion and 0.14 arcminutes for vertical motion. Subsequent real-time digital stabilization limited residual motion to an average of only 0.06 arcminutes (a 95% reduction). By correcting for high amplitude, low frequency drifts of the eye, the active TSLO eye-tracking system enabled the AOSLO system to capture high-resolution retinal images over a larger range of motion than previously possible with just the AOSLO imaging system alone. PMID:26203370

Information fusion performance evaluation for motion imagery data using mutual information: initial study

NASA Astrophysics Data System (ADS)

Grieggs, Samuel M.; McLaughlin, Michael J.; Ezekiel, Soundararajan; Blasch, Erik

2015-06-01

As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. Various techniques such as Wide Area Motion imagery (WAMI), Full Motion Video (FMV), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image Fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics; experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.

Ensemble framework based real-time respiratory motion prediction for adaptive radiotherapy applications.

PubMed

Tatinati, Sivanagaraja; Nazarpour, Kianoush; Tech Ang, Wei; Veluvolu, Kalyana C

2016-08-01

Successful treatment of tumors with motion-adaptive radiotherapy requires accurate prediction of respiratory motion, ideally with a prediction horizon larger than the latency in radiotherapy system. Accurate prediction of respiratory motion is however a non-trivial task due to the presence of irregularities and intra-trace variabilities, such as baseline drift and temporal changes in fundamental frequency pattern. In this paper, to enhance the accuracy of the respiratory motion prediction, we propose a stacked regression ensemble framework that integrates heterogeneous respiratory motion prediction algorithms. We further address two crucial issues for developing a successful ensemble framework: (1) selection of appropriate prediction methods to ensemble (level-0 methods) among the best existing prediction methods; and (2) finding a suitable generalization approach that can successfully exploit the relative advantages of the chosen level-0 methods. The efficacy of the developed ensemble framework is assessed with real respiratory motion traces acquired from 31 patients undergoing treatment. Results show that the developed ensemble framework improves the prediction performance significantly compared to the best existing methods. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Discrimination of Human Forearm Motions on the Basis of Myoelectric Signals by Using Adaptive Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Kiso, Atsushi; Seki, Hirokazu

This paper describes a method for discriminating of the human forearm motions based on the myoelectric signals using an adaptive fuzzy inference system. In conventional studies, the neural network is often used to estimate motion intention by the myoelectric signals and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signals. This study designs the membership function and the fuzzy rules using the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. In addition, the characteristics of the myoelectric potential gradually change as a result of the muscle fatigue. Therefore, the motion discrimination should be performed by taking muscle fatigue into consideration. This study proposes a method to redesign the fuzzy inference system such that dynamic change of the myoelectric potential because of the muscle fatigue will be taken into account. Some experiments carried out using a myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.

Advances in Adaptive Control Methods

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2009-01-01

This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

Illusory object motion in the centre of a radial pattern: The Pursuit-Pursuing illusion.

PubMed

Ito, Hiroyuki

2012-01-01

A circular object placed in the centre of a radial pattern consisting of thin sectors was found to cause a robust motion illusion. During eye-movement pursuit of a moving target, the presently described stimulus produced illusory background-object motion in the same direction as that of the eye movement. In addition, the display induced illusory stationary perception of a moving object against the whole display motion. In seven experiments, the characteristics of the illusion were examined in terms of luminance relationships and figural characteristics of the radial pattern. Some potential explanations for these findings are discussed.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

NASA Astrophysics Data System (ADS)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

Climate Change: From Science to Practice.

PubMed

Wheeler, Nicola; Watts, Nick

2018-03-01

Climate change poses a significant threat to human health. Understanding how climate science can be translated into public health practice is an essential first step in enabling robust adaptation and improving resiliency to climate change. Recent research highlights the importance of iterative approaches to public health adaptation to climate change, enabling uncertainties of health impacts and barriers to adaptation to be accounted for. There are still significant barriers to adaptation, which are context-specific and thus present unique challenges to public health practice. The implementation of flexible adaptation approaches, using frameworks targeted for public health, is key to ensuring robust adaptation to climate change in public health practice. The BRACE framework provides an excellent approach for health adaptation to climate change. Combining this with the insights provided and by the adaptation pathways approach allows for more deliberate accounting of long-term uncertainties. The mainstreaming of climate change adaptation into public health practice and planning is important in facilitating this approach and overcoming the significant barriers to effective adaptation. Yet, the immediate and future limits to adaptation provide clear justification for urgent and accelerated efforts to mitigate climate change.

Accurate respiration measurement using DC-coupled continuous-wave radar sensor for motion-adaptive cancer radiotherapy.

PubMed

Gu, Changzhan; Li, Ruijiang; Zhang, Hualiang; Fung, Albert Y C; Torres, Carlos; Jiang, Steve B; Li, Changzhi

2012-11-01

Accurate respiration measurement is crucial in motion-adaptive cancer radiotherapy. Conventional methods for respiration measurement are undesirable because they are either invasive to the patient or do not have sufficient accuracy. In addition, measurement of external respiration signal based on conventional approaches requires close patient contact to the physical device which often causes patient discomfort and undesirable motion during radiation dose delivery. In this paper, a dc-coupled continuous-wave radar sensor was presented to provide a noncontact and noninvasive approach for respiration measurement. The radar sensor was designed with dc-coupled adaptive tuning architectures that include RF coarse-tuning and baseband fine-tuning, which allows the radar sensor to precisely measure movement with stationary moment and always work with the maximum dynamic range. The accuracy of respiration measurement with the proposed radar sensor was experimentally evaluated using a physical phantom, human subject, and moving plate in a radiotherapy environment. It was shown that respiration measurement with radar sensor while the radiation beam is on is feasible and the measurement has a submillimeter accuracy when compared with a commercial respiration monitoring system which requires patient contact. The proposed radar sensor provides accurate, noninvasive, and noncontact respiration measurement and therefore has a great potential in motion-adaptive radiotherapy.

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

PubMed

Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

2016-01-01

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

PubMed Central

Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

2016-01-01

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion. PMID:26881743

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Roberts, Barry; Bhanu, Bir

1992-01-01

Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.

Robust adaptive uniform exact tracking control for uncertain Euler-Lagrange system

NASA Astrophysics Data System (ADS)

Yang, Yana; Hua, Changchun; Li, Junpeng; Guan, Xinping

2017-12-01

This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler-Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.

Robust optimization model and algorithm for railway freight center location problem in uncertain environment.

PubMed

Liu, Xing-Cai; He, Shi-Wei; Song, Rui; Sun, Yang; Li, Hao-Dong

2014-01-01

Railway freight center location problem is an important issue in railway freight transport programming. This paper focuses on the railway freight center location problem in uncertain environment. Seeing that the expected value model ignores the negative influence of disadvantageous scenarios, a robust optimization model was proposed. The robust optimization model takes expected cost and deviation value of the scenarios as the objective. A cloud adaptive clonal selection algorithm (C-ACSA) was presented. It combines adaptive clonal selection algorithm with Cloud Model which can improve the convergence rate. Design of the code and progress of the algorithm were proposed. Result of the example demonstrates the model and algorithm are effective. Compared with the expected value cases, the amount of disadvantageous scenarios in robust model reduces from 163 to 21, which prove the result of robust model is more reliable.

A comparative evaluation of adaptive noise cancellation algorithms for minimizing motion artifacts in a forehead-mounted wearable pulse oximeter.

PubMed

Comtois, Gary; Mendelson, Yitzhak; Ramuka, Piyush

2007-01-01

Wearable physiological monitoring using a pulse oximeter would enable field medics to monitor multiple injuries simultaneously, thereby prioritizing medical intervention when resources are limited. However, a primary factor limiting the accuracy of pulse oximetry is poor signal-to-noise ratio since photoplethysmographic (PPG) signals, from which arterial oxygen saturation (SpO2) and heart rate (HR) measurements are derived, are compromised by movement artifacts. This study was undertaken to quantify SpO2 and HR errors induced by certain motion artifacts utilizing accelerometry-based adaptive noise cancellation (ANC). Since the fingers are generally more vulnerable to motion artifacts, measurements were performed using a custom forehead-mounted wearable pulse oximeter developed for real-time remote physiological monitoring and triage applications. This study revealed that processing motion-corrupted PPG signals by least mean squares (LMS) and recursive least squares (RLS) algorithms can be effective to reduce SpO2 and HR errors during jogging, but the degree of improvement depends on filter order. Although both algorithms produced similar improvements, implementing the adaptive LMS algorithm is advantageous since it requires significantly less operations.

Predicting 2D target velocity cannot help 2D motion integration for smooth pursuit initiation.

PubMed

Montagnini, Anna; Spering, Miriam; Masson, Guillaume S

2006-12-01

Smooth pursuit eye movements reflect the temporal dynamics of bidimensional (2D) visual motion integration. When tracking a single, tilted line, initial pursuit direction is biased toward unidimensional (1D) edge motion signals, which are orthogonal to the line orientation. Over 200 ms, tracking direction is slowly corrected to finally match the 2D object motion during steady-state pursuit. We now show that repetition of line orientation and/or motion direction does not eliminate the transient tracking direction error nor change the time course of pursuit correction. Nonetheless, multiple successive presentations of a single orientation/direction condition elicit robust anticipatory pursuit eye movements that always go in the 2D object motion direction not the 1D edge motion direction. These results demonstrate that predictive signals about target motion cannot be used for an efficient integration of ambiguous velocity signals at pursuit initiation.

Robust dynamic 3-D measurements with motion-compensated phase-shifting profilometry

NASA Astrophysics Data System (ADS)

Feng, Shijie; Zuo, Chao; Tao, Tianyang; Hu, Yan; Zhang, Minliang; Chen, Qian; Gu, Guohua

2018-04-01

Phase-shifting profilometry (PSP) is a widely used approach to high-accuracy three-dimensional shape measurements. However, when it comes to moving objects, phase errors induced by the movement often result in severe artifacts even though a high-speed camera is in use. From our observations, there are three kinds of motion artifacts: motion ripples, motion-induced phase unwrapping errors, and motion outliers. We present a novel motion-compensated PSP to remove the artifacts for dynamic measurements of rigid objects. The phase error of motion ripples is analyzed for the N-step phase-shifting algorithm and is compensated using the statistical nature of the fringes. The phase unwrapping errors are corrected exploiting adjacent reliable pixels, and the outliers are removed by comparing the original phase map with a smoothed phase map. Compared with the three-step PSP, our method can improve the accuracy by more than 95% for objects in motion.

Robust cardiac motion estimation using ultrafast ultrasound data: a low-rank topology-preserving approach

NASA Astrophysics Data System (ADS)

Aviles, Angelica I.; Widlak, Thomas; Casals, Alicia; Nillesen, Maartje M.; Ammari, Habib

2017-06-01

Cardiac motion estimation is an important diagnostic tool for detecting heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate cardiac motion using ultrafast ultrasound data. Our solution is based on a variational formulation characterized by the L 2-regularized class. Displacement is represented by a lattice of b-splines and we ensure robustness, in the sense of eliminating outliers, by applying a maximum likelihood type estimator. While this is an important part of our solution, the main object of this work is to combine low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows one to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. The low-rank constraint speeds up the convergence of the optimization problem while topology preservation ensures a more accurate displacement. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that exhibit motion.

Robust control of accelerators

NASA Astrophysics Data System (ADS)

Joel, W.; Johnson, D.; Chaouki, Abdallah T.

1991-07-01

The problem of controlling the variations in the rf power system can be effectively cast as an application of modern control theory. Two components of this theory are obtaining a model and a feedback structure. The model inaccuracies influence the choice of a particular controller structure. Because of the modelling uncertainty, one has to design either a variable, adaptive controller or a fixed, robust controller to achieve the desired objective. The adaptive control scheme usually results in very complex hardware; and, therefore, shall not be pursued in this research. In contrast, the robust control method leads to simpler hardware. However, robust control requires a more accurate mathematical model of the physical process than is required by adaptive control. Our research at the Los Alamos National Laboratory (LANL) and the University of New Mexico (UNM) has led to the development and implementation of a new robust rf power feedback system. In this article, we report on our research progress. In section 1, the robust control problem for the rf power system and the philosophy adopted for the beginning phase of our research is presented. In section 2, the results of our proof-of-principle experiments are presented. In section 3, we describe the actual controller configuration that is used in LANL FEL physics experiments. The novelty of our approach is that the control hardware is implemented directly in rf. without demodulating, compensating, and then remodulating.

Control algorithms for aerobraking in the Martian atmosphere

NASA Technical Reports Server (NTRS)

Ward, Donald T.; Shipley, Buford W., Jr.

1991-01-01

The Analytic Predictor Corrector (APC) and Energy Controller (EC) atmospheric guidance concepts were adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. Changes are made to the APC to improve its robustness to density variations. These changes include adaptation of a new exit phase algorithm, an adaptive transition velocity to initiate the exit phase, refinement of the reference dynamic pressure calculation and two improved density estimation techniques. The modified controller with the hybrid density estimation technique is called the Mars Hybrid Predictor Corrector (MHPC), while the modified controller with a polynomial density estimator is called the Mars Predictor Corrector (MPC). A Lyapunov Steepest Descent Controller (LSDC) is adapted to control the vehicle. The LSDC lacked robustness, so a Lyapunov tracking exit phase algorithm is developed to guide the vehicle along a reference trajectory. This algorithm, when using the hybrid density estimation technique to define the reference path, is called the Lyapunov Hybrid Tracking Controller (LHTC). With the polynomial density estimator used to define the reference trajectory, the algorithm is called the Lyapunov Tracking Controller (LTC). These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. The MHPC, MPC, LHTC, and LTC show dramatic improvements in robustness over the APC and EC.

Robust Mean and Covariance Structure Analysis through Iteratively Reweighted Least Squares.

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2000-01-01

Adapts robust schemes to mean and covariance structures, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is weighted according to its distance, based on first and second order moments. Test statistics and standard error estimators are given. (SLD)

A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives.

PubMed

Li, Cai; Lowe, Robert; Ziemke, Tom

2014-01-01

In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a "reshaping" function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal "reshaping" functions). In this article, we use this architecture with the actor-critic algorithms for finding a good "reshaping" function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion.

Correction of respiratory motion for IMRT using aperture adaptive technique and visual guidance: A feasibility study

NASA Astrophysics Data System (ADS)

Chen, Ho-Hsing; Wu, Jay; Chuang, Keh-Shih; Kuo, Hsiang-Chi

2007-07-01

Intensity-modulated radiation therapy (IMRT) utilizes nonuniform beam profile to deliver precise radiation doses to a tumor while minimizing radiation exposure to surrounding normal tissues. However, the problem of intrafraction organ motion distorts the dose distribution and leads to significant dosimetric errors. In this research, we applied an aperture adaptive technique with a visual guiding system to toggle the problem of respiratory motion. A homemade computer program showing a cyclic moving pattern was projected onto the ceiling to visually help patients adjust their respiratory patterns. Once the respiratory motion becomes regular, the leaf sequence can be synchronized with the target motion. An oscillator was employed to simulate the patient's breathing pattern. Two simple fields and one IMRT field were measured to verify the accuracy. Preliminary results showed that after appropriate training, the amplitude and duration of volunteer's breathing can be well controlled by the visual guiding system. The sharp dose gradient at the edge of the radiation fields was successfully restored. The maximum dosimetric error in the IMRT field was significantly decreased from 63% to 3%. We conclude that the aperture adaptive technique with the visual guiding system can be an inexpensive and feasible alternative without compromising delivery efficiency in clinical practice.

A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives

PubMed Central

Li, Cai; Lowe, Robert; Ziemke, Tom

2014-01-01

In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a “reshaping” function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal “reshaping” functions). In this article, we use this architecture with the actor-critic algorithms for finding a good “reshaping” function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion. PMID:25324773

Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

NASA Astrophysics Data System (ADS)

Carvalho, Schubert R.; Boulic, Ronan; Thalmann, Daniel

The growth of motion capture systems have contributed to the proliferation of human motion database, mainly because human motion is important in many applications, ranging from games entertainment and films to sports and medicine. However, the captured motions normally attend specific needs. As an effort for adapting and reusing captured human motions in new tasks and environments and improving the animator's work, we present and discuss a new data-driven constraint-based animation system for interactive human motion editing. This method offers the compelling advantage that it provides faster deformations and more natural-looking motion results compared to goal-directed constraint-based methods found in the literature.

Optimized respiratory-resolved motion-compensated 3D Cartesian coronary MR angiography.

PubMed

Correia, Teresa; Ginami, Giulia; Cruz, Gastão; Neji, Radhouene; Rashid, Imran; Botnar, René M; Prieto, Claudia

2018-04-22

To develop a robust and efficient reconstruction framework that provides high-quality motion-compensated respiratory-resolved images from free-breathing 3D whole-heart Cartesian coronary magnetic resonance angiography (CMRA) acquisitions. Recently, XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel MRI) was proposed to achieve 100% scan efficiency and provide respiratory-resolved 3D radial CMRA images by exploiting sparsity in the respiratory dimension. Here, a reconstruction framework for Cartesian CMRA imaging is proposed, which provides respiratory-resolved motion-compensated images by incorporating 2D beat-to-beat translational motion information to increase sparsity in the respiratory dimension. The motion information is extracted from interleaved image navigators and is also used to compensate for 2D translational motion within each respiratory phase. The proposed Optimized Respiratory-resolved Cartesian Coronary MR Angiography (XD-ORCCA) method was tested on 10 healthy subjects and 2 patients with cardiovascular disease, and compared against XD-GRASP. The proposed XD-ORCCA provides high-quality respiratory-resolved images, allowing clear visualization of the right and left coronary arteries, even for irregular breathing patterns. Compared with XD-GRASP, the proposed method improves the visibility and sharpness of both coronaries. Significant differences (p < .05) in visible vessel length and proximal vessel sharpness were found between the 2 methods. The XD-GRASP method provides good-quality images in the absence of intraphase motion. However, motion blurring is observed in XD-GRASP images for respiratory phases with larger motion amplitudes and subjects with irregular breathing patterns. A robust respiratory-resolved motion-compensated framework for Cartesian CMRA has been proposed and tested in healthy subjects and patients. The proposed XD-ORCCA provides high-quality images for all respiratory phases, independently of the regularity of the breathing pattern. © 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Robust motion artefact resistant circuit for calculation of Mean Arterial Pressure from pulse transit time.

PubMed

Bhattacharya, Tinish; Gupta, Ankesh; Singh, Salam ThoiThoi; Roy, Sitikantha; Prasad, Anamika

2017-07-01

Cuff-less and non-invasive methods of Blood Pressure (BP) monitoring have faced a lot of challenges like stability, noise, motion artefact and requirement for calibration. These factors are the major reasons why such devices do not get approval from the medical community easily. One such method is calculating Blood Pressure indirectly from pulse transit time (PTT) obtained from electrocardiogram (ECG) and Photoplethysmogram (PPG). In this paper we have proposed two novel analog signal conditioning circuits for ECG and PPG that increase stability, remove motion artefacts, remove the sinusoidal wavering of the ECG baseline due to respiration and provide consistent digital pulses corresponding to blood pulses/heart-beat. We have combined these two systems to obtain the PTT and then correlated it with the Mean Arterial Pressure (MAP). The aim was to perform major part of the processing in analog domain to decrease processing load over microcontroller so as to reduce cost and make it simple and robust. We have found from our experiments that the proposed circuits can calculate the Heart Rate (HR) with a maximum error of ~3.0% and MAP with a maximum error of ~2.4% at rest and ~4.6% in motion.

Stability analysis of multiple-robot control systems

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz, Kenneth

1989-01-01

In a space telerobotic service scenario, cooperative motion and force control of multiple robot arms are of fundamental importance. Three paradigms to study this problem are proposed. They are distinguished by the set of variables used for control design. They are joint torques, arm tip force vectors, and an accelerated generalized coordinate set. Control issues related to each case are discussed. The latter two choices require complete model information, which presents practical modeling, computational, and robustness problems. Therefore, focus is on the joint torque control case to develop relatively model independent motion and internal force control laws. The rigid body assumption allows the motion and force control problems to be independently addressed. By using an energy motivated Lyapunov function, a simple proportional derivative plus gravity compensation type of motion control law is always shown to be stabilizing. The asymptotic convergence of the tracing error to zero requires the use of a generalized coordinate with the contact constraints taken into account. If a non-generalized coordinate is used, only convergence to a steady state manifold can be concluded. For the force control, both feedforward and feedback schemes are analyzed. The feedback control, if proper care has been taken, exhibits better robustness and transient performance.

A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems

PubMed Central

Lyu, Weiwei

2017-01-01

Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method. PMID:29182592

Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal

2006-01-01

This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.

Multiframe video coding for improved performance over wireless channels.

PubMed

Budagavi, M; Gibson, J D

2001-01-01

We propose and evaluate a multi-frame extension to block motion compensation (BMC) coding of videoconferencing-type video signals for wireless channels. The multi-frame BMC (MF-BMC) coder makes use of the redundancy that exists across multiple frames in typical videoconferencing sequences to achieve additional compression over that obtained by using the single frame BMC (SF-BMC) approach, such as in the base-level H.263 codec. The MF-BMC approach also has an inherent ability of overcoming some transmission errors and is thus more robust when compared to the SF-BMC approach. We model the error propagation process in MF-BMC coding as a multiple Markov chain and use Markov chain analysis to infer that the use of multiple frames in motion compensation increases robustness. The Markov chain analysis is also used to devise a simple scheme which randomizes the selection of the frame (amongst the multiple previous frames) used in BMC to achieve additional robustness. The MF-BMC coders proposed are a multi-frame extension of the base level H.263 coder and are found to be more robust than the base level H.263 coder when subjected to simulated errors commonly encountered on wireless channels.

2-tier in-plane motion correction and out-of-plane motion filtering for contrast-enhanced ultrasound.

PubMed

Ta, Casey N; Eghtedari, Mohammad; Mattrey, Robert F; Kono, Yuko; Kummel, Andrew C

2014-11-01

Contrast-enhanced ultrasound (CEUS) cines of focal liver lesions (FLLs) can be quantitatively analyzed to measure tumor perfusion on a pixel-by-pixel basis for diagnostic indication. However, CEUS cines acquired freehand and during free breathing cause nonuniform in-plane and out-of-plane motion from frame to frame. These motions create fluctuations in the time-intensity curves (TICs), reducing the accuracy of quantitative measurements. Out-of-plane motion cannot be corrected by image registration in 2-dimensional CEUS and degrades the quality of in-plane motion correction (IPMC). A 2-tier IPMC strategy and adaptive out-of-plane motion filter (OPMF) are proposed to provide a stable correction of nonuniform motion to reduce the impact of motion on quantitative analyses. A total of 22 cines of FLLs were imaged with dual B-mode and contrast specific imaging to acquire a 3-minute TIC. B-mode images were analyzed for motion, and the motion correction was applied to both B-mode and contrast images. For IPMC, the main reference frame was automatically selected for each cine, and subreference frames were selected in each respiratory cycle and sequentially registered toward the main reference frame. All other frames were sequentially registered toward the local subreference frame. Four OPMFs were developed and tested: subsample normalized correlation (NC), subsample sum of absolute differences, mean frame NC, and histogram. The frames that were most dissimilar to the OPMF reference frame using 1 of the 4 above criteria in each respiratory cycle were adaptively removed by thresholding against the low-pass filter of the similarity curve. Out-of-plane motion filter was quantitatively evaluated by an out-of-plane motion metric (OPMM) that measured normalized variance in the high-pass filtered TIC within the tumor region-of-interest with low OPMM being the goal. Results for IPMC and OPMF were qualitatively evaluated by 2 blinded observers who ranked the motion in the cines before and after various combinations of motion correction steps. Quantitative measurements showed that 2-tier IPMC and OPMF improved imaging stability. With IPMC, the NC B-mode metric increased from 0.504 ± 0.149 to 0.585 ± 0.145 over all cines (P < 0.001). Two-tier IPMC also produced better fits on the contrast-specific TIC than industry standard IPMC techniques did (P < 0.02). In-plane motion correction and OPMF were shown to improve goodness of fit for pixel-by-pixel analysis (P < 0.001). Out-of-plane motion filter reduced variance in the contrast-specific signal as shown by a median decrease of 49.8% in the OPMM. Two-tier IPMC and OPMF were also shown to qualitatively reduce motion. Observers consistently ranked cines with IPMC higher than the same cine before IPMC (P < 0.001) as well as ranked cines with OPMF higher than when they were uncorrected. The 2-tier sequential IPMC and adaptive OPMF significantly reduced motion in 3-minute CEUS cines of FLLs, thereby overcoming the challenges of drift and irregular breathing motion in long cines. The 2-tier IPMC strategy provided stable motion correction tolerant of out-of-plane motion throughout the cine by sequentially registering subreference frames that bypassed the motion cycles, thereby overcoming the lack of a nearly stationary reference point in long cines. Out-of-plane motion filter reduced apparent motion by adaptively removing frames imaged off-plane from the automatically selected OPMF reference frame, thereby tolerating nonuniform breathing motion. Selection of the best OPMF by minimizing OPMM effectively reduced motion under a wide variety of motion patterns applicable to clinical CEUS. These semiautomated processes only required user input for region-of-interest selection and can improve the accuracy of quantitative perfusion measurements.

Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

PubMed

Ye, Jinzuo; Chi, Chongwei; Xue, Zhenwen; Wu, Ping; An, Yu; Xu, Han; Zhang, Shuang; Tian, Jie

2014-02-01

Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

ADAPTATION AND GENERALIZATION TO OPPOSING PERTURBATIONS IN WALKING

PubMed Central

Bhatt, T.; Wang, T.-Y.; Yang, F.; Pai, Y.-C.

2013-01-01

Little is known on how the CNS would select its movement options when a person faces a novel or recurring perturbation of two opposing types (slip or trip) while walking. The purposes of this study were (1) to determine whether young adults’ adaptation to repeated slips would interfere with their recovery from a novel trip, and (2) to investigate the generalized strategies after they were exposed to a mixed training with both types of perturbation. Thirty-two young adults were assigned to either the training group, which first underwent repeated-slip training before encountering a novel, unannounced trip while walking, or to the control group, which only experienced the same novel, unannounced trip. The former group would then experience a mix of repeated trips and slips. The results indicated that prior adaptation to slips had only limited interference during the initial phase of trip recovery. In fact, the prior repeated-slip exposure had primed their reaction, which mitigated any error resulting from early interference. As a result, they did not have to take a longer compensatory step for trip recovery than did the controls. After the mixed training, subjects were able to converge effectively the motion state of their center of mass (in its position and velocity space) to a stable and generalized “middle ground” steady-state. Such movement strategies not only further strengthened their robust reactive control of stability, but also reduced the CNS’ overall reliance on accurate context prediction and on feedback correction of perturbation-induced movement error. PMID:23603517

Brownian motion with adaptive drift for remaining useful life prediction: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2018-01-01

Linear Brownian motion with constant drift is widely used in remaining useful life predictions because its first hitting time follows the inverse Gaussian distribution. State space modelling of linear Brownian motion was proposed to make the drift coefficient adaptive and incorporate on-line measurements into the first hitting time distribution. Here, the drift coefficient followed the Gaussian distribution, and it was iteratively estimated by using Kalman filtering once a new measurement was available. Then, to model nonlinear degradation, linear Brownian motion with adaptive drift was extended to nonlinear Brownian motion with adaptive drift. However, in previous studies, an underlying assumption used in the state space modelling was that in the update phase of Kalman filtering, the predicted drift coefficient at the current time exactly equalled the posterior drift coefficient estimated at the previous time, which caused a contradiction with the predicted drift coefficient evolution driven by an additive Gaussian process noise. In this paper, to alleviate such an underlying assumption, a new state space model is constructed. As a result, in the update phase of Kalman filtering, the predicted drift coefficient at the current time evolves from the posterior drift coefficient at the previous time. Moreover, the optimal Kalman filtering gain for iteratively estimating the posterior drift coefficient at any time is mathematically derived. A discussion that theoretically explains the main reasons why the constructed state space model can result in high remaining useful life prediction accuracies is provided. Finally, the proposed state space model and its associated Kalman filtering gain are applied to battery prognostics.

Robust 2-Qubit Gates in a Linear Ion Crystal Using a Frequency-Modulated Driving Force

NASA Astrophysics Data System (ADS)

Leung, Pak Hong; Landsman, Kevin A.; Figgatt, Caroline; Linke, Norbert M.; Monroe, Christopher; Brown, Kenneth R.

2018-01-01

In an ion trap quantum computer, collective motional modes are used to entangle two or more qubits in order to execute multiqubit logical gates. Any residual entanglement between the internal and motional states of the ions results in loss of fidelity, especially when there are many spectator ions in the crystal. We propose using a frequency-modulated driving force to minimize such errors. In simulation, we obtained an optimized frequency-modulated 2-qubit gate that can suppress errors to less than 0.01% and is robust against frequency drifts over ±1 kHz . Experimentally, we have obtained a 2-qubit gate fidelity of 98.3(4)%, a state-of-the-art result for 2-qubit gates with five ions.

Guidance and Control of a Small Unmanned Aerial Vehicle and Autonomous Flight Experiments

NASA Astrophysics Data System (ADS)

Fujinaga, Jin; Tokutake, Hiroshi; Sunada, Shigeru

This paper describes the development of a fixed-wing small-size UAV and the design of its flight controllers. The developed UAV’s wing span is 0.6m, and gross weight is 0.27kg. In order to ensure robust performances of the longitudinal and lateral-directional motions of the UAV, flight controllers are designed for these motions with μ-synthesis. Numerical simulations show that the designed controllers attain good robust stabilities and performances, and have good tracking performance for command. After an order-reduction and discretization, the designed flight controllers were implemented in the UAV. A flight test was performed, and the ability of the UAV to fly autonomously, passing over waypoints, was demonstrated.

Robustness analysis of elastoplastic structure subjected to double impulse

NASA Astrophysics Data System (ADS)

Kanno, Yoshihiro; Takewaki, Izuru

2016-11-01

The double impulse has extensively been used to evaluate the critical response of an elastoplastic structure against a pulse-type input, including near-fault earthquake ground motions. In this paper, we propose a robustness assessment method for elastoplastic single-degree-of-freedom structures subjected to the double impulse input. Uncertainties in the initial velocity of the input, as well as the natural frequency and the strength of the structure, are considered. As fundamental properties of the structural robustness, we show monotonicity of the robustness measure with respect to the natural frequency. In contrast, we show that robustness is not necessarily improved even if the structural strength is increased. Moreover, the robustness preference between two structures with different values of structural strength can possibly reverse when the performance requirement is changed.

Illusory object motion in the centre of a radial pattern: The Pursuit–Pursuing illusion

PubMed Central

Ito, Hiroyuki

2012-01-01

A circular object placed in the centre of a radial pattern consisting of thin sectors was found to cause a robust motion illusion. During eye-movement pursuit of a moving target, the presently described stimulus produced illusory background-object motion in the same direction as that of the eye movement. In addition, the display induced illusory stationary perception of a moving object against the whole display motion. In seven experiments, the characteristics of the illusion were examined in terms of luminance relationships and figural characteristics of the radial pattern. Some potential explanations for these findings are discussed. PMID:23145267

Mobile Motion Capture--MiMiC.

PubMed

Harbert, Simeon D; Jaiswal, Tushar; Harley, Linda R; Vaughn, Tyler W; Baranak, Andrew S

2013-01-01

The low cost, simple, robust, mobile, and easy to use Mobile Motion Capture (MiMiC) system is presented and the constraints which guided the design of MiMiC are discussed. The MiMiC Android application allows motion data to be captured from kinematic modules such as Shimmer 2r sensors over Bluetooth. MiMiC is cost effective and can be used for an entire day in a person's daily routine without being intrusive. MiMiC is a flexible motion capture system which can be used for many applications including fall detection, detection of fatigue in industry workers, and analysis of individuals' work patterns in various environments.

Example-based human motion denoising.

PubMed

Lou, Hui; Chai, Jinxiang

2010-01-01

With the proliferation of motion capture data, interest in removing noise and outliers from motion capture data has increased. In this paper, we introduce an efficient human motion denoising technique for the simultaneous removal of noise and outliers from input human motion data. The key idea of our approach is to learn a series of filter bases from precaptured motion data and use them along with robust statistics techniques to filter noisy motion data. Mathematically, we formulate the motion denoising process in a nonlinear optimization framework. The objective function measures the distance between the noisy input and the filtered motion in addition to how well the filtered motion preserves spatial-temporal patterns embedded in captured human motion data. Optimizing the objective function produces an optimal filtered motion that keeps spatial-temporal patterns in captured motion data. We also extend the algorithm to fill in the missing values in input motion data. We demonstrate the effectiveness of our system by experimenting with both real and simulated motion data. We also show the superior performance of our algorithm by comparing it with three baseline algorithms and to those in state-of-art motion capture data processing software such as Vicon Blade.

Motion Adaptation, its Role in Motion Detection Under Natural Image Conditions and Target Detection

DTIC Science & Technology

2005-06-02

Ibbotson, M.R. & Goodman, L.J. (1990) “Response characteristics of four wide-field motion sensitive descending interneurons in Apis mellifera ,” J. Exp...libraries (in particular a module, PyGame, original designed as an API for computer games applications). Andrew’s contribution to this effort was a

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Using an external surrogate for predictor model training in real-time motion management of lung tumors.

PubMed

Rottmann, Joerg; Berbeco, Ross

2014-12-01

Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal-external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.

Patch-based frame interpolation for old films via the guidance of motion paths

NASA Astrophysics Data System (ADS)

Xia, Tianran; Ding, Youdong; Yu, Bing; Huang, Xi

2018-04-01

Due to improper preservation, traditional films will appear frame loss after digital. To deal with this problem, this paper presents a new adaptive patch-based method of frame interpolation via the guidance of motion paths. Our method is divided into three steps. Firstly, we compute motion paths between two reference frames using optical flow estimation. Then, the adaptive bidirectional interpolation with holes filled is applied to generate pre-intermediate frames. Finally, using patch match to interpolate intermediate frames with the most similar patches. Since the patch match is based on the pre-intermediate frames that contain the motion paths constraint, we show a natural and inartificial frame interpolation. We test different types of old film sequences and compare with other methods, the results prove that our method has a desired performance without hole or ghost effects.

Adaptive fuzzy sliding control of single-phase PV grid-connected inverter.

PubMed

Fei, Juntao; Zhu, Yunkai

2017-01-01

In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV) grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with adaptive step is adopted to track the maximum power point (MPP) by controlling the duty cycle of the controllable power switch of the boost DC-DC converter. An adaptive fuzzy sliding mode controller with an integral sliding surface is developed for the grid-connected inverter where a fuzzy system is used to approach the upper bound of the system nonlinearities. The proposed strategy has strong robustness for the sliding mode control can be designed independently and disturbances can be adaptively compensated. Simulation results of a PV grid-connected system verify the effectiveness of the proposed method, demonstrating the satisfactory robustness and performance.

A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements

NASA Astrophysics Data System (ADS)

Kilicarslan, Atilla; Grossman, Robert G.; Contreras-Vidal, Jose Luis

2016-04-01

Objective. Non-invasive measurement of human neural activity based on the scalp electroencephalogram (EEG) allows for the development of biomedical devices that interface with the nervous system for scientific, diagnostic, therapeutic, or restorative purposes. However, EEG recordings are often considered as prone to physiological and non-physiological artifacts of different types and frequency characteristics. Among them, ocular artifacts and signal drifts represent major sources of EEG contamination, particularly in real-time closed-loop brain-machine interface (BMI) applications, which require effective handling of these artifacts across sessions and in natural settings. Approach. We extend the usage of a robust adaptive noise cancelling (ANC) scheme ({H}∞ filtering) for removal of eye blinks, eye motions, amplitude drifts and recording biases simultaneously. We also characterize the volume conduction, by estimating the signal propagation levels across all EEG scalp recording areas due to ocular artifact generators. We find that the amplitude and spatial distribution of ocular artifacts vary greatly depending on the electrode location. Therefore, fixed filtering parameters for all recording areas would naturally hinder the true overall performance of an ANC scheme for artifact removal. We treat each electrode as a separate sub-system to be filtered, and without the loss of generality, they are assumed to be uncorrelated and uncoupled. Main results. Our results show over 95-99.9% correlation between the raw and processed signals at non-ocular artifact regions, and depending on the contamination profile, 40-70% correlation when ocular artifacts are dominant. We also compare our results with the offline independent component analysis and artifact subspace reconstruction methods, and show that some local quantities are handled better by our sample-adaptive real-time framework. Decoding performance is also compared with multi-day experimental data from 2 subjects, totaling 19 sessions, with and without {H}∞ filtering of the raw data. Significance. The proposed method allows real-time adaptive artifact removal for EEG-based closed-loop BMI applications and mobile EEG studies in general, thereby increasing the range of tasks that can be studied in action and context while reducing the need for discarding data due to artifacts. Significant increase in decoding performances also justify the effectiveness of the method to be used in real-time closed-loop BMI applications.

Adaptive weld control for high-integrity welding applications

NASA Technical Reports Server (NTRS)

Powell, Bradley W.

1993-01-01

An advanced adaptive control weld system for high-integrity welding applications is presented. The system consists of a state-of-the-art weld control subsystem, motion control subsystem, and sensor subsystem which closes the loop on the process. The adaptive control subsystem (ACS), which is required to totally close the loop on weld process control, consists of a multiprocessor system, data acquisition hardware, and three welding sensors which provide measurements from all areas around the torch in real time. The ACS acquires all 'measurables' and feeds offset trims back into the weld control and motion control subsystems to modify the 'controllables' in order to maintain a previously defined weld quality.

Time and motion, experiment M151. [human performance and space flight stress

NASA Technical Reports Server (NTRS)

Kubis, J. F.; Elrod, J. T.; Rusnak, R.; Mcbride, G. H.; Barnes, J. E.; Saxon, S. C.

1973-01-01

Astronaut work performance during the preparation and execution of experiments in simulated Skylab tests was analyzed according to time and motion in order to evaluate the efficiency and consistency of performance (adaptation function) for several different types of activity over the course of the mission; to evaluate the procedures to be used by the same experiment in Skylab; to generate characteristic adaptation functions for later comparison with Skylab data; and to examine astronaut performance for any behavioral stress due to the environment. The overall results indicate that the anticipated adaptation function was obtained both for individual and for averaged data.

The surface and deep structure of the waterfall illusion.

PubMed

Wade, Nicholas J; Ziefle, Martina

2008-11-01

The surface structure of the waterfall illusion or motion aftereffect (MAE) is its phenomenal visibility. Its deep structure will be examined in the context of a model of space and motion perception. The MAE can be observed following protracted observation of a pattern that is translating, rotating, or expanding/contracting, a static pattern appears to move in the opposite direction. The phenomenon has long been known, and it continues to present novel properties. One of the novel features of MAEs is that they can provide an ideal visual assay for distinguishing local from global processes. Motion during adaptation can be induced in a static central grating by moving surround gratings; the MAE is observed in the static central grating but not in static surrounds. The adaptation phase is local and the test phase is global. That is, localised adaptation can be expressed in different ways depending on the structure of the test display. These aspects of MAEs can be exploited to determine a variety of local/global interactions. Six experiments on MAEs are reported. The results indicated that relational motion is required to induce an MAE; the region adapted extends beyond that stimulated; storage can be complete when the MAE is not seen during the storage period; interocular transfer (IOT) is around 30% of monocular MAEs with phase alternation; large field spiral patterns yield MAEs with characteristic monocular and binocular interactions.

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yi, Jianbing, E-mail: yijianbing8@163.com; Yang, Xuan, E-mail: xyang0520@263.net; Li, Yan-Ran, E-mail: lyran@szu.edu.cn

2015-10-15

Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered atmore » points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors’ method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors’ method ranks 24 of 39. According to the index of the maximum shear stretch, the authors’ method is also efficient to describe the discontinuous motion at the lung boundaries. Conclusions: By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors’ method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.« less

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm.

PubMed

Yi, Jianbing; Yang, Xuan; Chen, Guoliang; Li, Yan-Ran

2015-10-01

Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. The performances of the authors' method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors' method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors' method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors' method ranks 24 of 39. According to the index of the maximum shear stretch, the authors' method is also efficient to describe the discontinuous motion at the lung boundaries. By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors' method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.

Dense motion estimation using regularization constraints on local parametric models.

PubMed

Patras, Ioannis; Worring, Marcel; van den Boomgaard, Rein

2004-11-01

This paper presents a method for dense optical flow estimation in which the motion field within patches that result from an initial intensity segmentation is parametrized with models of different order. We propose a novel formulation which introduces regularization constraints between the model parameters of neighboring patches. In this way, we provide the additional constraints for very small patches and for patches whose intensity variation cannot sufficiently constrain the estimation of their motion parameters. In order to preserve motion discontinuities, we use robust functions as a regularization mean. We adopt a three-frame approach and control the balance between the backward and forward constraints by a real-valued direction field on which regularization constraints are applied. An iterative deterministic relaxation method is employed in order to solve the corresponding optimization problem. Experimental results show that the proposed method deals successfully with motions large in magnitude, motion discontinuities, and produces accurate piecewise-smooth motion fields.

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

NASA Astrophysics Data System (ADS)

Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

2017-12-01

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Machine Vision for Relative Spacecraft Navigation During Approach to Docking

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong; Baker, Kenneth

2011-01-01

This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

PROPELLER for motion-robust imaging of in vivo mouse abdomen at 9.4 T.

PubMed

Teh, Irvin; Golay, Xavier; Larkman, David J

2010-11-01

In vivo high-field MRI in the abdomen of small animals is technically challenging because of the small voxel sizes, short T(2) and physiological motion. In standard Cartesian sampling, respiratory and gastrointestinal motion can lead to ghosting artefacts. Although respiratory triggering and navigator echoes can either avoid or compensate for motion, they can lead to variable TRs, require invasive intubation and ventilation, or extend TEs. A self-navigated fast spin echo (FSE)-based periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) acquisition was implemented at 9.4 T to enable high-resolution in vivo MRI of mouse abdomen without the use of additional navigators or triggering. T(2)-weighted FSE-PROPELLER data were compared with single-shot FSE and multi-shot FSE data with and without triggering. Single-shot methods, although rapid and robust to motion, demonstrated strong blurring. Multi-shot FSE data showed better resolution, but suffered from marked blurring in the phase-encoding direction and motion in between shots, leading to ghosting artefacts. When respiratory triggering was used, motion artefacts were largely avoided. However, TRs and acquisition times were lengthened by up to approximately 20%. The PROPELLER data showed a 25% and 61% improvement in signal-to-noise ratio and contrast-to-noise ratio, respectively, compared with multi-shot FSE data, together with a 35% reduction in artefact power. A qualitative comparison between acquisition methods using diffusion-weighted imaging was performed. The results were similar, with the exception that respiratory triggering was unable to exclude major motion artefacts as a result of the sensitisation to motion by the diffusion gradients. The PROPELLER data were of consistently higher quality. Considerations specific to the use of PROPELLER at high field are discussed, including the selection of practical blade widths and the effects on contrast, resolution and artefacts.

Improved Shear Wave Motion Detection Using Pulse-Inversion Harmonic Imaging with a Phased Array Transducer

PubMed Central

Song, Pengfei; Zhao, Heng; Urban, Matthew W.; Manduca, Armando; Pislaru, Sorin V.; Kinnick, Randall R.; Pislaru, Cristina; Greenleaf, James F.; Chen, Shigao

2013-01-01

Ultrasound tissue harmonic imaging is widely used to improve ultrasound B-mode imaging quality thanks to its effectiveness in suppressing imaging artifacts associated with ultrasound reverberation, phase aberration, and clutter noise. In ultrasound shear wave elastography (SWE), because the shear wave motion signal is extracted from the ultrasound signal, these noise sources can significantly deteriorate the shear wave motion tracking process and consequently result in noisy and biased shear wave motion detection. This situation is exacerbated in in vivo SWE applications such as heart, liver, and kidney. This paper, therefore, investigated the possibility of implementing harmonic imaging, specifically pulse-inversion harmonic imaging, in shear wave tracking, with the hypothesis that harmonic imaging can improve shear wave motion detection based on the same principles that apply to general harmonic B-mode imaging. We first designed an experiment with a gelatin phantom covered by an excised piece of pork belly and show that harmonic imaging can significantly improve shear wave motion detection by producing less underestimated shear wave motion and more consistent shear wave speed measurements than fundamental imaging. Then, a transthoracic heart experiment on a freshly sacrificed pig showed that harmonic imaging could robustly track the shear wave motion and give consistent shear wave speed measurements while fundamental imaging could not. Finally, an in vivo transthoracic study of seven healthy volunteers showed that the proposed harmonic imaging tracking sequence could provide consistent estimates of the left ventricular myocardium stiffness in end-diastole with a general success rate of 80% and a success rate of 93.3% when excluding the subject with Body Mass Index (BMI) higher than 25. These promising results indicate that pulse-inversion harmonic imaging can significantly improve shear wave motion tracking and thus potentially facilitate more robust assessment of tissue elasticity by SWE. PMID:24021638

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rottmann, Joerg; Berbeco, Ross

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable tomore » overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of 8 s and history vector length of 3 s achieve maximal performance. Sampling frequency appears to have little impact on performance confirming previously published work. By using the linear predictor, a relative geometric 3D error reduction of about 50% was achieved (using adaptive retraining, a history vector length of 3 s and with results averaged over all investigated lookahead times and signal sampling frequencies). The absolute mean error could be reduced from (2.0 ± 1.6) mm when using no prediction at all to (0.9 ± 0.8) mm and (1.0 ± 0.9) mm when using the predictor trained with internal tumor motion training data and external surrogate motion training data, respectively (for a typical lookahead time of 250 ms and sampling frequency of 15 Hz). Conclusions: A linear prediction model can reduce latency induced tracking errors by an average of about 50% in real-time image guided radiotherapy systems with system latencies of up to 300 ms. Training a linear model for lung tumor motion prediction with an external surrogate signal alone is feasible and results in similar performance as training with (internal) tumor motion. Particularly for scenarios where motion data are extracted from fluoroscopic imaging with ionizing radiation, this may alleviate the need for additional imaging dose during the collection of model training data.« less

Transfer of perceptual adaptation to space sickness: What enhances an individual's ability to adapt?

NASA Technical Reports Server (NTRS)

1993-01-01

The objectives of this project were to explore systematically the determiners of transfer of perceptual adaptation as these principles might apply to the space adaptation syndrome. The perceptual experience of an astronaut exposed to the altered gravitational forces involved in spaceflight shares much with that of the subject exposed in laboratory experiments to optically induced visual rearrangement with tilt and dynamic motion illusions such as vection; and experiences and symptoms reported by the trainee who is exposed to the compellingly realistic visual imagery of flight simulators and virtual reality systems. In both of these cases the observer is confronted with a variety of inter- and intrasensory conflicts that initially disrupt perception, as well as behavior, and also produce symptoms of motion sickness.

An adaptive mesh-moving and refinement procedure for one-dimensional conservation laws

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Flaherty, Joseph E.; Arney, David C.

1993-01-01

We examine the performance of an adaptive mesh-moving and /or local mesh refinement procedure for the finite difference solution of one-dimensional hyperbolic systems of conservation laws. Adaptive motion of a base mesh is designed to isolate spatially distinct phenomena, and recursive local refinement of the time step and cells of the stationary or moving base mesh is performed in regions where a refinement indicator exceeds a prescribed tolerance. These adaptive procedures are incorporated into a computer code that includes a MacCormack finite difference scheme wih Davis' artificial viscosity model and a discretization error estimate based on Richardson's extrapolation. Experiments are conducted on three problems in order to qualify the advantages of adaptive techniques relative to uniform mesh computations and the relative benefits of mesh moving and refinement. Key results indicate that local mesh refinement, with and without mesh moving, can provide reliable solutions at much lower computational cost than possible on uniform meshes; that mesh motion can be used to improve the results of uniform mesh solutions for a modest computational effort; that the cost of managing the tree data structure associated with refinement is small; and that a combination of mesh motion and refinement reliably produces solutions for the least cost per unit accuracy.

Higher-order neural processing tunes motion neurons to visual ecology in three species of hawkmoths.

PubMed

Stöckl, A L; O'Carroll, D; Warrant, E J

2017-06-28

To sample information optimally, sensory systems must adapt to the ecological demands of each animal species. These adaptations can occur peripherally, in the anatomical structures of sensory organs and their receptors; and centrally, as higher-order neural processing in the brain. While a rich body of investigations has focused on peripheral adaptations, our understanding is sparse when it comes to central mechanisms. We quantified how peripheral adaptations in the eyes, and central adaptations in the wide-field motion vision system, set the trade-off between resolution and sensitivity in three species of hawkmoths active at very different light levels: nocturnal Deilephila elpenor, crepuscular Manduca sexta , and diurnal Macroglossum stellatarum. Using optical measurements and physiological recordings from the photoreceptors and wide-field motion neurons in the lobula complex, we demonstrate that all three species use spatial and temporal summation to improve visual performance in dim light. The diurnal Macroglossum relies least on summation, but can only see at brighter intensities. Manduca, with large sensitive eyes, relies less on neural summation than the smaller eyed Deilephila , but both species attain similar visual performance at nocturnal light levels. Our results reveal how the visual systems of these three hawkmoth species are intimately matched to their visual ecologies. © 2017 The Author(s).

Multi-application controls: Robust nonlinear multivariable aerospace controls applications

NASA Technical Reports Server (NTRS)

Enns, Dale F.; Bugajski, Daniel J.; Carter, John; Antoniewicz, Bob

1994-01-01

This viewgraph presentation describes the general methodology used to apply Honywell's Multi-Application Control (MACH) and the specific application to the F-18 High Angle-of-Attack Research Vehicle (HARV) including piloted simulation handling qualities evaluation. The general steps include insertion of modeling data for geometry and mass properties, aerodynamics, propulsion data and assumptions, requirements and specifications, e.g. definition of control variables, handling qualities, stability margins and statements for bandwidth, control power, priorities, position and rate limits. The specific steps include choice of independent variables for least squares fits to aerodynamic and propulsion data, modifications to the management of the controls with regard to integrator windup and actuation limiting and priorities, e.g. pitch priority over roll, and command limiting to prevent departures and/or undesirable inertial coupling or inability to recover to a stable trim condition. The HARV control problem is characterized by significant nonlinearities and multivariable interactions in the low speed, high angle-of-attack, high angular rate flight regime. Systematic approaches to the control of vehicle motions modeled with coupled nonlinear equations of motion have been developed. This paper will discuss the dynamic inversion approach which explicity accounts for nonlinearities in the control design. Multiple control effectors (including aerodynamic control surfaces and thrust vectoring control) and sensors are used to control the motions of the vehicles in several degrees-of-freedom. Several maneuvers will be used to illustrate performance of MACH in the high angle-of-attack flight regime. Analytical methods for assessing the robust performance of the multivariable control system in the presence of math modeling uncertainty, disturbances, and commands have reached a high level of maturity. The structured singular value (mu) frequency response methodology is presented as a method for analyzing robust performance and the mu-synthesis method will be presented as a method for synthesizing a robust control system. The paper concludes with the author's expectations regarding future applications of robust nonlinear multivariable controls.

4D ML reconstruction as a tool for volumetric PET-based treatment verification in ion beam radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Bernardi, E., E-mail: elisabetta.debernardi@unimib.it; Ricotti, R.; Riboldi, M.

2016-02-15

Purpose: An innovative strategy to improve the sensitivity of positron emission tomography (PET)-based treatment verification in ion beam radiotherapy is proposed. Methods: Low counting statistics PET images acquired during or shortly after the treatment (Measured PET) and a Monte Carlo estimate of the same PET images derived from the treatment plan (Expected PET) are considered as two frames of a 4D dataset. A 4D maximum likelihood reconstruction strategy was adapted to iteratively estimate the annihilation events distribution in a reference frame and the deformation motion fields that map it in the Expected PET and Measured PET frames. The outputs generatedmore » by the proposed strategy are as follows: (1) an estimate of the Measured PET with an image quality comparable to the Expected PET and (2) an estimate of the motion field mapping Expected PET to Measured PET. The details of the algorithm are presented and the strategy is preliminarily tested on analytically simulated datasets. Results: The algorithm demonstrates (1) robustness against noise, even in the worst conditions where 1.5 × 10{sup 4} true coincidences and a random fraction of 73% are simulated; (2) a proper sensitivity to different kind and grade of mismatches ranging between 1 and 10 mm; (3) robustness against bias due to incorrect washout modeling in the Monte Carlo simulation up to 1/3 of the original signal amplitude; and (4) an ability to describe the mismatch even in presence of complex annihilation distributions such as those induced by two perpendicular superimposed ion fields. Conclusions: The promising results obtained in this work suggest the applicability of the method as a quantification tool for PET-based treatment verification in ion beam radiotherapy. An extensive assessment of the proposed strategy on real treatment verification data is planned.« less

Disentangling Random Motion and Flow in a Complex Medium

PubMed Central

Koslover, Elena F.; Chan, Caleb K.; Theriot, Julie A.

2016-01-01

We describe a technique for deconvolving the stochastic motion of particles from large-scale fluid flow in a dynamic environment such as that found in living cells. The method leverages the separation of timescales to subtract out the persistent component of motion from single-particle trajectories. The mean-squared displacement of the resulting trajectories is rescaled so as to enable robust extraction of the diffusion coefficient and subdiffusive scaling exponent of the stochastic motion. We demonstrate the applicability of the method for characterizing both diffusive and fractional Brownian motion overlaid by flow and analytically calculate the accuracy of the method in different parameter regimes. This technique is employed to analyze the motion of lysosomes in motile neutrophil-like cells, showing that the cytoplasm of these cells behaves as a viscous fluid at the timescales examined. PMID:26840734

A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

PubMed

Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

2017-01-01

In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H ∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles

NASA Astrophysics Data System (ADS)

Kobravi, Hamid-Reza; Erfanian, Abbas

2009-08-01

A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist-antagonist muscles.

PubMed

Kobravi, Hamid-Reza; Erfanian, Abbas

2009-08-01

A decentralized control methodology is designed for the control of ankle dorsiflexion and plantarflexion in paraplegic subjects with electrical stimulation of tibialis anterior and calf muscles. Each muscle joint is considered as a subsystem and individual controllers are designed for each subsystem. Each controller operates solely on its associated subsystem, with no exchange of information between the subsystems. The interactions between the subsystems are taken as external disturbances for each isolated subsystem. In order to achieve robustness with respect to external disturbances, unmodeled dynamics, model uncertainty and time-varying properties of muscle-joint dynamics, a robust control framework is proposed which is based on the synergistic combination of an adaptive nonlinear compensator with a sliding mode control and is referred to as an adaptive robust control. Extensive simulations and experiments on healthy and paraplegic subjects were performed to demonstrate the robustness against the time-varying properties of muscle-joint dynamics, day-to-day variations, subject-to-subject variations, fast convergence, stability and tracking accuracy of the proposed method. The results indicate that the decentralized robust control provides excellent tracking control for different reference trajectories and can generate control signals to compensate the muscle fatigue and reject the external disturbance. Moreover, the controller is able to automatically regulate the interaction between agonist and antagonist muscles under different conditions of operating without any preprogrammed antagonist activities.

Verification and Tuning of an Adaptive Controller for an Unmanned Air Vehicle

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.

2010-01-01

This paper focuses on the analysis and tuning of a controller based on the Adaptive Control Technology for Safe Flight (ACTS) architecture. The ACTS architecture consists of a nominal, non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off-nominal ones. A framework unifying control verification and gain tuning is used to make the controller s ability to satisfy the closed-loop requirements more robust to uncertainty. In this paper we tune the gains of both controllers using this approach. Some advantages and drawbacks of adaptation are identified by performing a global robustness assessment of both the adaptive controller and its non-adaptive counterpart. The analyses used to determine these characteristics are based on evaluating the degradation in closed-loop performance resulting from uncertainties having increasing levels of severity. The specific adverse conditions considered can be grouped into three categories: aerodynamic uncertainties, structural damage, and actuator failures. These failures include partial and total loss of control effectiveness, locked-in-place control surface deflections, and engine out conditions. The requirements considered are the peak structural loading, the ability of the controller to track pilot commands, the ability of the controller to keep the aircraft s state within the reliable flight envelope, and the handling/riding qualities of the aircraft. The nominal controller resulting from these tuning strategies was successfully validated using the NASA GTM Flight Test Vehicle.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

PubMed Central

Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-01-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information. PMID:27304526

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

PubMed

Huang, Chao; Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-06-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

Efficient robust doubly adaptive regularized regression with applications.

PubMed

Karunamuni, Rohana J; Kong, Linglong; Tu, Wei

2018-01-01

We consider the problem of estimation and variable selection for general linear regression models. Regularized regression procedures have been widely used for variable selection, but most existing methods perform poorly in the presence of outliers. We construct a new penalized procedure that simultaneously attains full efficiency and maximum robustness. Furthermore, the proposed procedure satisfies the oracle properties. The new procedure is designed to achieve sparse and robust solutions by imposing adaptive weights on both the decision loss and the penalty function. The proposed method of estimation and variable selection attains full efficiency when the model is correct and, at the same time, achieves maximum robustness when outliers are present. We examine the robustness properties using the finite-sample breakdown point and an influence function. We show that the proposed estimator attains the maximum breakdown point. Furthermore, there is no loss in efficiency when there are no outliers or the error distribution is normal. For practical implementation of the proposed method, we present a computational algorithm. We examine the finite-sample and robustness properties using Monte Carlo studies. Two datasets are also analyzed.

An adaptive discontinuous Galerkin solver for aerodynamic flows

NASA Astrophysics Data System (ADS)

Burgess, Nicholas K.

This work considers the accuracy, efficiency, and robustness of an unstructured high-order accurate discontinuous Galerkin (DG) solver for computational fluid dynamics (CFD). Recently, there has been a drive to reduce the discretization error of CFD simulations using high-order methods on unstructured grids. However, high-order methods are often criticized for lacking robustness and having high computational cost. The goal of this work is to investigate methods that enhance the robustness of high-order discontinuous Galerkin (DG) methods on unstructured meshes, while maintaining low computational cost and high accuracy of the numerical solutions. This work investigates robustness enhancement of high-order methods by examining effective non-linear solvers, shock capturing methods, turbulence model discretizations and adaptive refinement techniques. The goal is to develop an all encompassing solver that can simulate a large range of physical phenomena, where all aspects of the solver work together to achieve a robust, efficient and accurate solution strategy. The components and framework for a robust high-order accurate solver that is capable of solving viscous, Reynolds Averaged Navier-Stokes (RANS) and shocked flows is presented. In particular, this work discusses robust discretizations of the turbulence model equation used to close the RANS equations, as well as stable shock capturing strategies that are applicable across a wide range of discretization orders and applicable to very strong shock waves. Furthermore, refinement techniques are considered as both efficiency and robustness enhancement strategies. Additionally, efficient non-linear solvers based on multigrid and Krylov subspace methods are presented. The accuracy, efficiency, and robustness of the solver is demonstrated using a variety of challenging aerodynamic test problems, which include turbulent high-lift and viscous hypersonic flows. Adaptive mesh refinement was found to play a critical role in obtaining a robust and efficient high-order accurate flow solver. A goal-oriented error estimation technique has been developed to estimate the discretization error of simulation outputs. For high-order discretizations, it is shown that functional output error super-convergence can be obtained, provided the discretization satisfies a property known as dual consistency. The dual consistency of the DG methods developed in this work is shown via mathematical analysis and numerical experimentation. Goal-oriented error estimation is also used to drive an hp-adaptive mesh refinement strategy, where a combination of mesh or h-refinement, and order or p-enrichment, is employed based on the smoothness of the solution. The results demonstrate that the combination of goal-oriented error estimation and hp-adaptation yield superior accuracy, as well as enhanced robustness and efficiency for a variety of aerodynamic flows including flows with strong shock waves. This work demonstrates that DG discretizations can be the basis of an accurate, efficient, and robust CFD solver. Furthermore, enhancing the robustness of DG methods does not adversely impact the accuracy or efficiency of the solver for challenging and complex flow problems. In particular, when considering the computation of shocked flows, this work demonstrates that the available shock capturing techniques are sufficiently accurate and robust, particularly when used in conjunction with adaptive mesh refinement . This work also demonstrates that robust solutions of the Reynolds Averaged Navier-Stokes (RANS) and turbulence model equations can be obtained for complex and challenging aerodynamic flows. In this context, the most robust strategy was determined to be a low-order turbulence model discretization coupled to a high-order discretization of the RANS equations. Although RANS solutions using high-order accurate discretizations of the turbulence model were obtained, the behavior of current-day RANS turbulence models discretized to high-order was found to be problematic, leading to solver robustness issues. This suggests that future work is warranted in the area of turbulence model formulation for use with high-order discretizations. Alternately, the use of Large-Eddy Simulation (LES) subgrid scale models with high-order DG methods offers the potential to leverage the high accuracy of these methods for very high fidelity turbulent simulations. This thesis has developed the algorithmic improvements that will lay the foundation for the development of a three-dimensional high-order flow solution strategy that can be used as the basis for future LES simulations.

Failure of Anisotropic Unstructured Mesh Adaption Based on Multidimensional Residual Minimization

NASA Technical Reports Server (NTRS)

Wood, William A.; Kleb, William L.

2003-01-01

An automated anisotropic unstructured mesh adaptation strategy is proposed, implemented, and assessed for the discretization of viscous flows. The adaption criteria is based upon the minimization of the residual fluctuations of a multidimensional upwind viscous flow solver. For scalar advection, this adaption strategy has been shown to use fewer grid points than gradient based adaption, naturally aligning mesh edges with discontinuities and characteristic lines. The adaption utilizes a compact stencil and is local in scope, with four fundamental operations: point insertion, point deletion, edge swapping, and nodal displacement. Evaluation of the solution-adaptive strategy is performed for a two-dimensional blunt body laminar wind tunnel case at Mach 10. The results demonstrate that the strategy suffers from a lack of robustness, particularly with regard to alignment of the bow shock in the vicinity of the stagnation streamline. In general, constraining the adaption to such a degree as to maintain robustness results in negligible improvement to the solution. Because the present method fails to consistently or significantly improve the flow solution, it is rejected in favor of simple uniform mesh refinement.

Adaptive radiation therapy for postprostatectomy patients using real-time electromagnetic target motion tracking during external beam radiation therapy.

PubMed

Zhu, Mingyao; Bharat, Shyam; Michalski, Jeff M; Gay, Hiram A; Hou, Wei-Hsien; Parikh, Parag J

2013-03-15

Using real-time electromagnetic (EM) transponder tracking data recorded by the Calypso 4D Localization System, we report inter- and intrafractional target motion of the prostate bed, describe a strategy to evaluate treatment adequacy in postprostatectomy patients receiving intensity modulated radiation therapy (IMRT), and propose an adaptive workflow. Tracking data recorded by Calypso EM transponders was analyzed for postprostatectomy patients that underwent step-and-shoot IMRT. Rigid target motion parameters during beam delivery were calculated from recorded transponder positions in 16 patients with rigid transponder geometry. The delivered doses to the clinical target volume (CTV) were estimated from the planned dose matrix and the target motion for the first 3, 5, 10, and all fractions. Treatment adequacy was determined by comparing the delivered minimum dose (Dmin) with the planned Dmin to the CTV. Treatments were considered adequate if the delivered CTV Dmin is at least 95% of the planned CTV Dmin. Translational target motion was minimal for all 16 patients (mean: 0.02 cm; range: -0.12 cm to 0.07 cm). Rotational motion was patient-specific, and maximum pitch, yaw, and roll were 12.2, 4.1, and 10.5°, respectively. We observed inadequate treatments in 5 patients. In these treatments, we observed greater target rotations along with large distances between the CTV centroid and transponder centroid. The treatment adequacy from the initial 10 fractions successfully predicted the overall adequacy in 4 of 5 inadequate treatments and 10 of 11 adequate treatments. Target rotational motion could cause underdosage to partial volume of the postprostatectomy targets. Our adaptive treatment strategy is applicable to post-prostatectomy patients receiving IMRT to evaluate and improve radiation therapy delivery. Copyright © 2013 Elsevier Inc. All rights reserved.

Adaptive Animation of Human Motion for E-Learning Applications

ERIC Educational Resources Information Center

Li, Frederick W. B.; Lau, Rynson W. H.; Komura, Taku; Wang, Meng; Siu, Becky

2007-01-01

Human motion animation has been one of the major research topics in the field of computer graphics for decades. Techniques developed in this area help present human motions in various applications. This is crucial for enhancing the realism as well as promoting the user interest in the applications. To carry this merit to e-learning applications,…

Moving vehicles segmentation based on Gaussian motion model

NASA Astrophysics Data System (ADS)

Zhang, Wei; Fang, Xiang Z.; Lin, Wei Y.

2005-07-01

Moving objects segmentation is a challenge in computer vision. This paper focuses on the segmentation of moving vehicles in dynamic scene. We analyses the psychology of human vision and present a framework for segmenting moving vehicles in the highway. The proposed framework consists of two parts. Firstly, we propose an adaptive background update method in which the background is updated according to the change of illumination conditions and thus can adapt to the change of illumination sensitively. Secondly, we construct a Gaussian motion model to segment moving vehicles, in which the motion vectors of the moving pixels are modeled as a Gaussian model and an on-line EM algorithm is used to update the model. The Gaussian distribution of the adaptive model is elevated to determine which moving vectors result from moving vehicles and which from other moving objects such as waving trees. Finally, the pixels with motion vector result from the moving vehicles are segmented. Experimental results of several typical scenes show that the proposed model can detect the moving vehicles correctly and is immune from influence of the moving objects caused by the waving trees and the vibration of camera.

How MAP kinase modules function as robust, yet adaptable, circuits.

PubMed

Tian, Tianhai; Harding, Angus

2014-01-01

Genetic and biochemical studies have revealed that the diversity of cell types and developmental patterns evident within the animal kingdom is generated by a handful of conserved, core modules. Core biological modules must be robust, able to maintain functionality despite perturbations, and yet sufficiently adaptable for random mutations to generate phenotypic variation during evolution. Understanding how robust, adaptable modules have influenced the evolution of eukaryotes will inform both evolutionary and synthetic biology. One such system is the MAP kinase module, which consists of a 3-tiered kinase circuit configuration that has been evolutionarily conserved from yeast to man. MAP kinase signal transduction pathways are used across eukaryotic phyla to drive biological functions that are crucial for life. Here we ask the fundamental question, why do MAPK modules follow a conserved 3-tiered topology rather than some other number? Using computational simulations, we identify a fundamental 2-tiered circuit topology that can be readily reconfigured by feedback loops and scaffolds to generate diverse signal outputs. When this 2-kinase circuit is connected to proximal input kinases, a 3-tiered modular configuration is created that is both robust and adaptable, providing a biological circuit that can regulate multiple phenotypes and maintain functionality in an uncertain world. We propose that the 3-tiered signal transduction module has been conserved through positive selection, because it facilitated the generation of phenotypic variation during eukaryotic evolution.

How MAP kinase modules function as robust, yet adaptable, circuits

PubMed Central

Tian, Tianhai; Harding, Angus

2014-01-01

Genetic and biochemical studies have revealed that the diversity of cell types and developmental patterns evident within the animal kingdom is generated by a handful of conserved, core modules. Core biological modules must be robust, able to maintain functionality despite perturbations, and yet sufficiently adaptable for random mutations to generate phenotypic variation during evolution. Understanding how robust, adaptable modules have influenced the evolution of eukaryotes will inform both evolutionary and synthetic biology. One such system is the MAP kinase module, which consists of a 3-tiered kinase circuit configuration that has been evolutionarily conserved from yeast to man. MAP kinase signal transduction pathways are used across eukaryotic phyla to drive biological functions that are crucial for life. Here we ask the fundamental question, why do MAPK modules follow a conserved 3-tiered topology rather than some other number? Using computational simulations, we identify a fundamental 2-tiered circuit topology that can be readily reconfigured by feedback loops and scaffolds to generate diverse signal outputs. When this 2-kinase circuit is connected to proximal input kinases, a 3-tiered modular configuration is created that is both robust and adaptable, providing a biological circuit that can regulate multiple phenotypes and maintain functionality in an uncertain world. We propose that the 3-tiered signal transduction module has been conserved through positive selection, because it facilitated the generation of phenotypic variation during eukaryotic evolution. PMID:25483189

The influence of sleep deprivation and oscillating motion on sleepiness, motion sickness, and cognitive and motor performance.

PubMed

Kaplan, Janna; Ventura, Joel; Bakshi, Avijit; Pierobon, Alberto; Lackner, James R; DiZio, Paul

2017-01-01

Our goal was to determine how sleep deprivation, nauseogenic motion, and a combination of motion and sleep deprivation affect cognitive vigilance, visual-spatial perception, motor learning and retention, and balance. We exposed four groups of subjects to different combinations of normal 8h sleep or 4h sleep for two nights combined with testing under stationary conditions or during 0.28Hz horizontal linear oscillation. On the two days following controlled sleep, all subjects underwent four test sessions per day that included evaluations of fatigue, motion sickness, vigilance, perceptual discrimination, perceptual learning, motor performance and learning, and balance. Sleep loss and exposure to linear oscillation had additive or multiplicative relationships to sleepiness, motion sickness severity, decreases in vigilance and in perceptual discrimination and learning. Sleep loss also decelerated the rate of adaptation to motion sickness over repeated sessions. Sleep loss degraded the capacity to compensate for novel robotically induced perturbations of reaching movements but did not adversely affect adaptive recovery of accurate reaching. Overall, tasks requiring substantial attention to cognitive and motor demands were degraded more than tasks that were more automatic. Our findings indicate that predicting performance needs to take into account in addition to sleep loss, the attentional demands and novelty of tasks, the motion environment in which individuals will be performing and their prior susceptibility to motion sickness during exposure to provocative motion stimulation. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploring critical pathways for urban water management to identify robust strategies under deep uncertainties.

PubMed

Urich, Christian; Rauch, Wolfgang

2014-12-01

Long-term projections for key drivers needed in urban water infrastructure planning such as climate change, population growth, and socio-economic changes are deeply uncertain. Traditional planning approaches heavily rely on these projections, which, if a projection stays unfulfilled, can lead to problematic infrastructure decisions causing high operational costs and/or lock-in effects. New approaches based on exploratory modelling take a fundamentally different view. Aim of these is, to identify an adaptation strategy that performs well under many future scenarios, instead of optimising a strategy for a handful. However, a modelling tool to support strategic planning to test the implication of adaptation strategies under deeply uncertain conditions for urban water management does not exist yet. This paper presents a first step towards a new generation of such strategic planning tools, by combing innovative modelling tools, which coevolve the urban environment and urban water infrastructure under many different future scenarios, with robust decision making. The developed approach is applied to the city of Innsbruck, Austria, which is spatially explicitly evolved 20 years into the future under 1000 scenarios to test the robustness of different adaptation strategies. Key findings of this paper show that: (1) Such an approach can be used to successfully identify parameter ranges of key drivers in which a desired performance criterion is not fulfilled, which is an important indicator for the robustness of an adaptation strategy; and (2) Analysis of the rich dataset gives new insights into the adaptive responses of agents to key drivers in the urban system by modifying a strategy. Copyright © 2014 Elsevier Ltd. All rights reserved.