Monte Carlo tree search -based non-coplanar trajectory design for station parameter optimized radiation therapy (SPORT).

PubMed

Dong, Peng; Liu, Hongcheng; Xing, Lei

2018-06-04

An important yet challenging problem in LINAC-based rotational arc radiation therapy is the design of beam trajectory, which requires simultaneous consideration of delivery efficiency and final dose distribution. In this work, we propose a novel trajectory selection strategy by developing a Monte Carlo tree search (MCTS) algorithm during the beam trajectory selection process. Methods: To search through the vast number of possible trajectories, MCTS algorithm was implemented. In this approach, a candidate trajectory is explored by starting from a leaf node and sequentially examining the next level of linked nodes with consideration of geometric and physical constraints. The maximum Upper Confidence Bounds for Trees, which is a function of average objective function value and the number of times the node under testing has been visited, was employed to intelligently select the trajectory. For each candidate trajectory, we run an inverse fluence map optimization with an infinity norm regularization. The ranking of the plan as measured by the corresponding objective function value was then fed back to update the statistics of the nodes on the trajectory. The method was evaluated with a chest wall and a brain case, and the results were compared with the coplanar and noncoplanar 4pi beam configurations. Results: For both clinical cases, the MCTS method found effective and easy-to-deliver trajectories within an hour. As compared with the coplanar plans, it offers much better sparing of the OARs while maintaining the PTV coverage. The quality of the MCTS-generated plan is found to be comparable to the 4pi plans. Conclusion: AI based on MCTS is valuable to facilitate the design of beam trajectory and paves the way for future clinical use of non-coplanar treatment delivery. . © 2018 Institute of Physics and Engineering in Medicine.

Diverse Planning for UAV Control and Remote Sensing

PubMed Central

Tožička, Jan; Komenda, Antonín

2016-01-01

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs. PMID:28009831

Diverse Planning for UAV Control and Remote Sensing.

PubMed

Tožička, Jan; Komenda, Antonín

2016-12-21

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

An Augmentation of G-Guidance Algorithms

NASA Technical Reports Server (NTRS)

Carson, John M. III; Acikmese, Behcet

2011-01-01

The original G-Guidance algorithm provided an autonomous guidance and control policy for small-body proximity operations that took into account uncertainty and dynamics disturbances. However, there was a lack of robustness in regards to object proximity while in autonomous mode. The modified GGuidance algorithm was augmented with a second operational mode that allows switching into a safety hover mode. This will cause a spacecraft to hover in place until a mission-planning algorithm can compute a safe new trajectory. No state or control constraints are violated. When a new, feasible state trajectory is calculated, the spacecraft will return to standard mode and maneuver toward the target. The main goal of this augmentation is to protect the spacecraft in the event that a landing surface or obstacle is closer or further than anticipated. The algorithm can be used for the mitigation of any unexpected trajectory or state changes that occur during standard mode operations

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

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

Caillet, V; Colvill, E; Royal North Shore Hospital, St Leonards, Sydney

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physicalmore » experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use of either algorithm for clinical implementation.« less

Operator-assisted planning and execution of proximity operations subject to operational constraints

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1991-01-01

Future multi-vehicle operations will involve multiple scenarios that will require a planning tool for the rapid, interactive creation of fuel-efficient trajectories. The planning process must deal with higher-order, non-linear processes involving dynamics that are often counter-intuitive. The optimization of resulting trajectories can be difficult to envision. An interaction proximity operations planning system is being developed to provide the operator with easily interpreted visual feedback of trajectories and constraints. This system is hosted on an IRIS 4D graphics platform and utilizes the Clohessy-Wiltshire equations. An inverse dynamics algorithm is used to remove non-linearities while the trajectory maneuvers are decoupled and separated in a geometric spreadsheet. The operator has direct control of the position and time of trajectory waypoints to achieve the desired end conditions. Graphics provide the operator with visualization of satisfying operational constraints such as structural clearance, plume impingement, approach velocity limits, and arrival or departure corridors. Primer vector theory is combined with graphical presentation to improve operator understanding of suggested automated system solutions and to allow the operator to review, edit, or provide corrective action to the trajectory plan.

Visual display aid for orbital maneuvering - Design considerations

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1993-01-01

This paper describes the development of an interactive proximity operations planning system that allows on-site planning of fuel-efficient multiburn maneuvers in a potential multispacecraft environment. Although this display system most directly assists planning by providing visual feedback to aid visualization of the trajectories and constraints, its most significant features include: (1) the use of an 'inverse dynamics' algorithm that removes control nonlinearities facing the operator, and (2) a trajectory planning technique that separates, through a 'geometric spreadsheet', the normally coupled complex problems of planning orbital maneuvers and allows solution by an iterative sequence of simple independent actions. The visual feedback of trajectory shapes and operational constraints, provided by user-transparent and continuously active background computations, allows the operator to make fast, iterative design changes that rapidly converge to fuel-efficient solutions. The planning tool provides an example of operator-assisted optimization of nonlinear cost functions.

Design Genetic Algorithm Optimization Education Software Based Fuzzy Controller for a Tricopter Fly Path Planning

ERIC Educational Resources Information Center

Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao

2016-01-01

In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…

Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping

2018-03-01

The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.

Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Sun, Zhenping; Cao, Dongpu; Liu, Daxue; He, Hangen

2017-03-01

This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.

Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles

NASA Astrophysics Data System (ADS)

Cowlagi, Raghvendra V.

Autonomous mobile robots---both aerial and terrestrial vehicles---have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical decomposition suffers a serious drawback: the geometric path planner has no information of the kinematical and dynamical constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates the geometric planner altogether by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematical model. We propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. The main contributions of this thesis are: 1. A motion planning framework based on history-dependent costs (H-costs) in cell decomposition graphs for incorporating vehicle dynamical constraints: this framework offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning, 2. An efficient and flexible algorithm for finding optimal H-cost paths, 3. A precise and general formulation of a local trajectory problem (the tile motion planning problem) that allows independent development of the discrete planner and the trajectory planner, while maintaining "compatibility" between the two planners, 4. A local trajectory generation algorithm using mpc, and the application of the concept of effective target sets for a significant simplification of the local trajectory generation problem, 5. The geometric analysis of curvature-bounded traversal of rectangular channels, leading to less conservative results in comparison with a result reported in the literature, and also to the efficient construction of effective target sets for the solution of the tile motion planning problem, 6. A wavelet-based multi-resolution path planning scheme, and a proof of completeness of the proposed scheme: such proofs are altogether absent from other works on multi-resolution path planning, 7. A technique for extracting all information about cells---namely, the locations, the sizes, and the associated image intensities---directly from the set of significant detail coefficients considered for path planning at a given iteration, and 8. The extension of the multi-resolution path planning scheme to include vehicle dynamical constraints using the aforementioned history-dependent costs approach. The future work includes an implementation of the proposed framework involving a discrete planner that solves classical planning problems more general than the single-query path planning problem considered thus far, and involving trajectory generation schemes for realistic vehicle dynamical models such as the bicycle model.

TU-AB-201-04: Optimizing the Number of Catheter Implants and Their Tracks for Prostate HDR Brachytherapy

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

Riofrio, D; Luan, S; Zhou, J

Purpose: In prostate HDR brachytherapy, interstitial implants are placed manually on the fly. The aim for this research is to develop a computer algorithm to find optimal and reliable implant trajectories using minimal number of implants. Methods: Our new algorithm mainly uses these key ideas: (1) positive charged static particles are uniformly placed on the surface of prostate and critical structures such as urethra, bladder, and rectum. (2) Positive charged kinetic particles are placed at a cross-section of the prostate with an initial velocity parallel to the principal implant direction. (3) The kinetic particles move through the prostate, interacting withmore » each other, spreading out, while staying away from the prostate surface and critical structures. The initial velocity ensures that the trajectories observe the curvature constraints of typical implant procedures. (4) The finial trajectories of kinetic particles are smoothed using a third-degree polynomial regression, which become the implant trajectories. (5) The dwelling times and final dose distribution are calculated using least-distance programming. Results: (1) We experimented with previously treated cases. Our plan achieves all prescription goals while reducing the number of implants by 41%! Our plan also has less uniform target dose, which implies a higher dose is delivered to the prostate. (2) We expect future implant procedures will be performed under the guidance of such pre-calculated trajectories. To assess the applicability, we randomly perturb the tracks to mimic the manual implant errors. Our studies showed the impact of these perturbations are negligible, which is compensated by the least distance programming. Conclusions: We developed a new inverse planning system for prostate HDR therapy that can find optimal implant trajectories while minimizing the number of implants. For future work, we plan to integrate our new inverse planning system with an existing needle tracking system.« less

Development of an analytical guidance algorithm for lunar descent

NASA Astrophysics Data System (ADS)

Chomel, Christina Tvrdik

In recent years, NASA has indicated a desire to return humans to the moon. With NASA planning manned missions within the next couple of decades, the concept development for these lunar vehicles has begun. The guidance, navigation, and control (GN&C) computer programs that will perform the function of safely landing a spacecraft on the moon are part of that development. The lunar descent guidance algorithm takes the horizontally oriented spacecraft from orbital speeds hundreds of kilometers from the desired landing point to the landing point at an almost vertical orientation and very low speed. Existing lunar descent GN&C algorithms date back to the Apollo era with little work available for implementation since then. Though these algorithms met the criteria of the 1960's, they are cumbersome today. At the basis of the lunar descent phase are two elements: the targeting, which generates a reference trajectory, and the real-time guidance, which forces the spacecraft to fly that trajectory. The Apollo algorithm utilizes a complex, iterative, numerical optimization scheme for developing the reference trajectory. The real-time guidance utilizes this reference trajectory in the form of a quartic rather than a more general format to force the real-time trajectory errors to converge to zero; however, there exist no guarantees under any conditions for this convergence. The proposed algorithm implements a purely analytical targeting algorithm used to generate two-dimensional trajectories "on-the-fly"' or to retarget the spacecraft to another landing site altogether. It is based on the analytical solutions to the equations for speed, downrange, and altitude as a function of flight path angle and assumes two constant thrust acceleration curves. The proposed real-time guidance algorithm has at its basis the three-dimensional non-linear equations of motion and a control law that is proven to converge under certain conditions through Lyapunov analysis to a reference trajectory formatted as a function of downrange, altitude, speed, and flight path angle. The two elements of the guidance algorithm are joined in Monte Carlo analysis to prove their robustness to initial state dispersions and mass and thrust errors. The robustness of the retargeting algorithm is also demonstrated.

Obstacle Detection using Binocular Stereo Vision in Trajectory Planning for Quadcopter Navigation

NASA Astrophysics Data System (ADS)

Bugayong, Albert; Ramos, Manuel, Jr.

2018-02-01

Quadcopters are one of the most versatile unmanned aerial vehicles due to its vertical take-off and landing as well as hovering capabilities. This research uses the Sum of Absolute Differences (SAD) block matching algorithm for stereo vision. A complementary filter was used in sensor fusion to combine obtained quadcopter orientation data from the accelerometer and the gyroscope. PID control was implemented for the motor control and VFH+ algorithm was implemented for trajectory planning. Results show that the quadcopter was able to consistently actuate itself in the roll, yaw and z-axis during obstacle avoidance but was however found to be inconsistent in the pitch axis during forward and backward maneuvers due to the significant noise present in the pitch axis angle outputs compared to the roll and yaw axes.

Application of Metaheuristic and Deterministic Algorithms for Aircraft Reference Trajectory Optimization =

NASA Astrophysics Data System (ADS)

Murrieta Mendoza, Alejandro

Aircraft reference trajectory is an alternative method to reduce fuel consumption, thus the pollution released to the atmosphere. Fuel consumption reduction is of special importance for two reasons: first, because the aeronautical industry is responsible of 2% of the CO2 released to the atmosphere, and second, because it will reduce the flight cost. The aircraft fuel model was obtained from a numerical performance database which was created and validated by our industrial partner from flight experimental test data. A new methodology using the numerical database was proposed in this thesis to compute the fuel burn for a given trajectory. Weather parameters such as wind and temperature were taken into account as they have an important effect in fuel burn. The open source model used to obtain the weather forecast was provided by Weather Canada. A combination of linear and bi-linear interpolations allowed finding the required weather data. The search space was modelled using different graphs: one graph was used for mapping the different flight phases such as climb, cruise and descent, and another graph was used for mapping the physical space in which the aircraft would perform its flight. The trajectory was optimized in its vertical reference trajectory using the Beam Search algorithm, and a combination of the Beam Search algorithm with a search space reduction technique. The trajectory was optimized simultaneously for the vertical and lateral reference navigation plans while fulfilling a Required Time of Arrival constraint using three different metaheuristic algorithms: the artificial bee's colony, and the ant colony optimization. Results were validated using the software FlightSIMRTM, a commercial Flight Management System, an exhaustive search algorithm, and as flown flights obtained from flightawareRTM. All algorithms were able to reduce the fuel burn, and the flight costs. None None None None None None None

Nonlinear dynamic analysis and optimal trajectory planning of a high-speed macro-micro manipulator

NASA Astrophysics Data System (ADS)

Yang, Yi-ling; Wei, Yan-ding; Lou, Jun-qiang; Fu, Lei; Zhao, Xiao-wei

2017-09-01

This paper reports the nonlinear dynamic modeling and the optimal trajectory planning for a flexure-based macro-micro manipulator, which is dedicated to the large-scale and high-speed tasks. In particular, a macro- micro manipulator composed of a servo motor, a rigid arm and a compliant microgripper is focused. Moreover, both flexure hinges and flexible beams are considered. By combining the pseudorigid-body-model method, the assumed mode method and the Lagrange equation, the overall dynamic model is derived. Then, the rigid-flexible-coupling characteristics are analyzed by numerical simulations. After that, the microscopic scale vibration excited by the large-scale motion is reduced through the trajectory planning approach. Especially, a fitness function regards the comprehensive excitation torque of the compliant microgripper is proposed. The reference curve and the interpolation curve using the quintic polynomial trajectories are adopted. Afterwards, an improved genetic algorithm is used to identify the optimal trajectory by minimizing the fitness function. Finally, the numerical simulations and experiments validate the feasibility and the effectiveness of the established dynamic model and the trajectory planning approach. The amplitude of the residual vibration reduces approximately 54.9%, and the settling time decreases 57.1%. Therefore, the operation efficiency and manipulation stability are significantly improved.

TU-CD-304-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Trajectory Modulated Arc Therapy: Development of Novel Arc Delivery Techniques Integrating Dynamic Table Motion for Extended Volume Treatments

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

Chin, E; Hoppe, R; Million, L

2015-06-15

Purpose: Integration of coordinated robotic table motion with inversely-planned arc delivery has the potential to resolve table-top delivery limitations of large-field treatments such as Total Body Irradiation (TBI), Total Lymphoid Irradiation (TLI), and Cranial-Spinal Irradiation (CSI). We formulate the foundation for Trajectory Modulated Arc Therapy (TMAT), and using Varian Developer Mode capabilities, experimentally investigate its practical implementation for such techniques. Methods: A MATLAB algorithm was developed for inverse planning optimization of the table motion, MLC positions, and gantry motion under extended-SSD geometry. To maximize the effective field size, delivery trajectories for TMAT TBI were formed with the table rotated atmore » 270° IEC and dropped vertically to 152.5cm SSD. Preliminary testing of algorithm parameters was done through retrospective planning analysis. Robotic delivery was programmed using custom XML scripting on the TrueBeam Developer Mode platform. Final dose was calculated using the Eclipse AAA algorithm. Initial verification of delivery accuracy was measured using OSLDs on a solid water phantom of varying thickness. Results: A comparison of DVH curves demonstrated that dynamic couch motion irradiation was sufficiently approximated by static control points spaced in intervals of less than 2cm. Optimized MLC motion decreased the average lung dose to 68.5% of the prescription dose. The programmed irradiation integrating coordinated table motion was deliverable on a TrueBeam STx linac in 6.7 min. With the couch translating under an open 10cmx20cm field angled at 10°, OSLD measurements along the midline of a solid water phantom at depths of 3, 5, and 9cm were within 3% of the TPS AAA algorithm with an average deviation of 1.2%. Conclusion: A treatment planning and delivery system for Trajectory Modulated Arc Therapy of extended volumes has been established and experimentally demonstrated for TBI. Extension to other treatment techniques such as TLI and CSI is readily achievable through the developed platform. Grant Funding by Varian Medical Systems.« less

A real-time dynamic-MLC control algorithm for delivering IMRT to targets undergoing 2D rigid motion in the beam's eye view.

PubMed

McMahon, Ryan; Berbeco, Ross; Nishioka, Seiko; Ishikawa, Masayori; Papiez, Lech

2008-09-01

An MLC control algorithm for delivering intensity modulated radiation therapy (IMRT) to targets that are undergoing two-dimensional (2D) rigid motion in the beam's eye view (BEV) is presented. The goal of this method is to deliver 3D-derived fluence maps over a moving patient anatomy. Target motion measured prior to delivery is first used to design a set of planned dynamic-MLC (DMLC) sliding-window leaf trajectories. During actual delivery, the algorithm relies on real-time feedback to compensate for target motion that does not agree with the motion measured during planning. The methodology is based on an existing one-dimensional (ID) algorithm that uses on-the-fly intensity calculations to appropriately adjust the DMLC leaf trajectories in real-time during exposure delivery [McMahon et al., Med. Phys. 34, 3211-3223 (2007)]. To extend the 1D algorithm's application to 2D target motion, a real-time leaf-pair shifting mechanism has been developed. Target motion that is orthogonal to leaf travel is tracked by appropriately shifting the positions of all MLC leaves. The performance of the tracking algorithm was tested for a single beam of a fractionated IMRT treatment, using a clinically derived intensity profile and a 2D target trajectory based on measured patient data. Comparisons were made between 2D tracking, 1D tracking, and no tracking. The impact of the tracking lag time and the frequency of real-time imaging were investigated. A study of the dependence of the algorithm's performance on the level of agreement between the motion measured during planning and delivery was also included. Results demonstrated that tracking both components of the 2D motion (i.e., parallel and orthogonal to leaf travel) results in delivered fluence profiles that are superior to those that track the component of motion that is parallel to leaf travel alone. Tracking lag time effects may lead to relatively large intensity delivery errors compared to the other sources of error investigated. However, the algorithm presented is robust in the sense that it does not rely on a high level of agreement between the target motion measured during treatment planning and delivery.

Integrated guidance and control for microsatellite real-time automated proximity operations

NASA Astrophysics Data System (ADS)

Chen, Ying; He, Zhen; Zhou, Ding; Yu, Zhenhua; Li, Shunli

2018-07-01

This paper investigates the trajectory planning and control of autonomous spacecraft proximity operations with impulsive dynamics. A new integrated guidance and control scheme is developed to perform automated close-range rendezvous for underactuated microsatellites. To efficiently prevent collision, a modified RRT* trajectory planning algorithm is proposed under this context. Several engineering constraints such as collision avoidance, plume impingement, field of view and control feasibility are considered simultaneously. Then, the feedback controller that employs a turn-burn-turn strategy with a combined impulsive orbital control and finite-time attitude control is designed to ensure the implementation of planned trajectory. Finally, the performance of trajectory planner and controller are evaluated through numerical tests. Simulation results indicate the real-time implementability of the proposed integrated guidance and control scheme with position control error less than 0.5 m and velocity control error less than 0.05 m/s. Consequently, the proposed scheme offers the potential for wide applications, such as on-orbit maintenance, space surveillance and debris removal.

Robot Trajectories Comparison: A Statistical Approach

PubMed Central

Ansuategui, A.; Arruti, A.; Susperregi, L.; Yurramendi, Y.; Jauregi, E.; Lazkano, E.; Sierra, B.

2014-01-01

The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM2 and WaveFront, using different environments, robots, and local planners. PMID:25525618

Dynamic Distributed Cooperative Control of Multiple Heterogeneous Resources

DTIC Science & Technology

2012-10-01

of the UAVs to maximize the total sensor footprint over the region of interest. The algorithm utilized to solve this problem was based on sampling a...and moving obstacles. Obstacle positions were assumed known a priori. Kingston and Beard [22] presented an algorithm to keep moving UAVs equally spaced...Planning Algorithms , Cambridge University Press, 2006. 11. Ma, C. S. and Miller, R. H., “Mixed integer linear programming trajectory generation for

4D BADA-based Trajectory Generator and 3D Guidance Algorithm

NASA Technical Reports Server (NTRS)

Palacios, Eduardo Sepulveda; Johnson, Marcus A.

2013-01-01

This paper presents a hybrid integration between aerodynamic, airline procedures and other BADA-based (Base of Aircraft Data) coefficients with a classical aircraft dynamic model. This paper also describes a three-dimensional guidance algorithm implemented in order to produce commands for the aircraft to follow a flight plan. The software chosen for this work is MATLAB.

A Turn-Projected State-Based Conflict Resolution Algorithm

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Lewis, Timothy A.

2013-01-01

State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.

Trajectory optimization for dynamic couch rotation during volumetric modulated arc radiotherapy

NASA Astrophysics Data System (ADS)

Smyth, Gregory; Bamber, Jeffrey C.; Evans, Philip M.; Bedford, James L.

2013-11-01

Non-coplanar radiation beams are often used in three-dimensional conformal and intensity modulated radiotherapy to reduce dose to organs at risk (OAR) by geometric avoidance. In volumetric modulated arc radiotherapy (VMAT) non-coplanar geometries are generally achieved by applying patient couch rotations to single or multiple full or partial arcs. This paper presents a trajectory optimization method for a non-coplanar technique, dynamic couch rotation during VMAT (DCR-VMAT), which combines ray tracing with a graph search algorithm. Four clinical test cases (partial breast, brain, prostate only, and prostate and pelvic nodes) were used to evaluate the potential OAR sparing for trajectory-optimized DCR-VMAT plans, compared with standard coplanar VMAT. In each case, ray tracing was performed and a cost map reflecting the number of OAR voxels intersected for each potential source position was generated. The least-cost path through the cost map, corresponding to an optimal DCR-VMAT trajectory, was determined using Dijkstra’s algorithm. Results show that trajectory optimization can reduce dose to specified OARs for plans otherwise comparable to conventional coplanar VMAT techniques. For the partial breast case, the mean heart dose was reduced by 53%. In the brain case, the maximum lens doses were reduced by 61% (left) and 77% (right) and the globes by 37% (left) and 40% (right). Bowel mean dose was reduced by 15% in the prostate only case. For the prostate and pelvic nodes case, the bowel V50 Gy and V60 Gy were reduced by 9% and 45% respectively. Future work will involve further development of the algorithm and assessment of its performance over a larger number of cases in site-specific cohorts.

Dynamic trajectory-based couch motion for improvement of radiation therapy trajectories in cranial SRT

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

MacDonald, R. Lee; Thomas, Christopher G., E-mail: Chris.Thomas@cdha.nshealth.ca; Department of Medical Physics, Nova Scotia Cancer Centre, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia B3H 1V7

2015-05-15

Purpose: To investigate potential improvement in external beam stereotactic radiation therapy plan quality for cranial cases using an optimized dynamic gantry and patient support couch motion trajectory, which could minimize exposure to sensitive healthy tissue. Methods: Anonymized patient anatomy and treatment plans of cranial cancer patients were used to quantify the geometric overlap between planning target volumes and organs-at-risk (OARs) based on their two-dimensional projection from source to a plane at isocenter as a function of gantry and couch angle. Published dose constraints were then used as weighting factors for the OARs to generate a map of couch-gantry coordinate space,more » indicating degree of overlap at each point in space. A couch-gantry collision space was generated by direct measurement on a linear accelerator and couch using an anthropomorphic solid-water phantom. A dynamic, fully customizable algorithm was written to generate a navigable ideal trajectory for the patient specific couch-gantry space. The advanced algorithm can be used to balance the implementation of absolute minimum values of overlap with the clinical practicality of large-scale couch motion and delivery time. Optimized cranial cancer treatment trajectories were compared to conventional treatment trajectories. Results: Comparison of optimized treatment trajectories with conventional treatment trajectories indicated an average decrease in mean dose to the OARs of 19% and an average decrease in maximum dose to the OARs of 12%. Degradation was seen for homogeneity index (6.14% ± 0.67%–5.48% ± 0.76%) and conformation number (0.82 ± 0.02–0.79 ± 0.02), but neither was statistically significant. Removal of OAR constraints from volumetric modulated arc therapy optimization reveals that reduction in dose to OARs is almost exclusively due to the optimized trajectory and not the OAR constraints. Conclusions: The authors’ study indicated that simultaneous couch and gantry motion during radiation therapy to minimize the geometrical overlap in the beams-eye-view of target volumes and the organs-at-risk can have an appreciable dose reduction to organs-at-risk.« less

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

Optimal guidance with obstacle avoidance for nap-of-the-earth flight

NASA Technical Reports Server (NTRS)

Pekelsma, Nicholas J.

1988-01-01

The development of automatic guidance is discussed for helicopter Nap-of-the-Earth (NOE) and near-NOE flight. It deals with algorithm refinements relating to automated real-time flight path planning and to mission planning. With regard to path planning, it relates rotorcraft trajectory characteristics to the NOE computation scheme and addresses real-time computing issues and both ride quality issues and pilot-vehicle interfaces. The automated mission planning algorithm refinements include route optimization, automatic waypoint generation, interactive applications, and provisions for integrating the results into the real-time path planning software. A microcomputer based mission planning workstation was developed and is described. Further, the application of Defense Mapping Agency (DMA) digital terrain to both the mission planning workstation and to automatic guidance is both discussed and illustrated.

Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Blackmore, James C.; Scharf, Daniel P.

2011-01-01

An enhanced algorithm is developed that builds on a previous innovation of fuel-optimal powered-descent guidance (PDG) for planetary pinpoint landing. The PDG problem is to compute constrained, fuel-optimal trajectories to land a craft at a prescribed target on a planetary surface, starting from a parachute cut-off point and using a throttleable descent engine. The previous innovation showed the minimal-fuel PDG problem can be posed as a convex optimization problem, in particular, as a Second-Order Cone Program, which can be solved to global optimality with deterministic convergence properties, and hence is a candidate for onboard implementation. To increase the speed and robustness of this convex PDG algorithm for possible onboard implementation, the following enhancements are incorporated: 1) Fast detection of infeasibility (i.e., control authority is not sufficient for soft-landing) for subsequent fault response. 2) The use of a piecewise-linear control parameterization, providing smooth solution trajectories and increasing computational efficiency. 3) An enhanced line-search algorithm for optimal time-of-flight, providing quicker convergence and bounding the number of path-planning iterations needed. 4) An additional constraint that analytically guarantees inter-sample satisfaction of glide-slope and non-sub-surface flight constraints, allowing larger discretizations and, hence, faster optimization. 5) Explicit incorporation of Mars rotation rate into the trajectory computation for improved targeting accuracy. These enhancements allow faster convergence to the fuel-optimal solution and, more importantly, remove the need for a "human-in-the-loop," as constraints will be satisfied over the entire path-planning interval independent of step-size (as opposed to just at the discrete time points) and infeasible initial conditions are immediately detected. Finally, while the PDG stage is typically only a few minutes, ignoring the rotation rate of Mars can introduce 10s of meters of error. By incorporating it, the enhanced PDG algorithm becomes capable of pinpoint targeting.

Optimal slew path planning for the Sino-French Space-based multiband astronomical Variable Objects Monitor mission

NASA Astrophysics Data System (ADS)

She, Yuchen; Li, Shuang

2018-01-01

The planning algorithm to calculate a satellite's optimal slew trajectory with a given keep-out constraint is proposed. An energy-optimal formulation is proposed for the Space-based multiband astronomical Variable Objects Monitor Mission Analysis and Planning (MAP) system. The innovative point of the proposed planning algorithm lies in that the satellite structure and control limitation are not considered as optimization constraints but are formulated into the cost function. This modification is able to relieve the burden of the optimizer and increases the optimization efficiency, which is the major challenge for designing the MAP system. Mathematical analysis is given to prove that there is a proportional mapping between the formulation and the satellite controller output. Simulations with different scenarios are given to demonstrate the efficiency of the developed algorithm.

Optimizing highly noncoplanar VMAT trajectories: the NoVo method.

PubMed

Langhans, Marco; Unkelbach, Jan; Bortfeld, Thomas; Craft, David

2018-01-16

We introduce a new method called NoVo (Noncoplanar VMAT Optimization) to produce volumetric modulated arc therapy (VMAT) treatment plans with noncoplanar trajectories. While the use of noncoplanar beam arrangements for intensity modulated radiation therapy (IMRT), and in particular high fraction stereotactic radiosurgery (SRS), is common, noncoplanar beam trajectories for VMAT are less common as the availability of treatment machines handling these is limited. For both IMRT and VMAT, the beam angle selection problem is highly nonconvex in nature, which is why automated beam angle selection procedures have not entered mainstream clinical usage. NoVo determines a noncoplanar VMAT solution (i.e. the simultaneous trajectories of the gantry and the couch) by first computing a [Formula: see text] solution (beams from every possible direction, suitably discretized) and then eliminating beams by examing fluence contributions. Also all beam angles are scored via geometrical considerations only to find out the usefulness of the whole beam space in a very short time. A custom path finding algorithm is applied to find an optimized, continuous trajectory through the most promising beam angles using the calculated score of the beam space. Finally, using this trajectory a VMAT plan is optimized. For three clinical cases, a lung, brain, and liver case, we compare NoVo to the ideal [Formula: see text] solution, nine beam noncoplanar IMRT, coplanar VMAT, and a recently published noncoplanar VMAT algorithm. NoVo comes closest to the [Formula: see text] solution considering the lung case (brain and liver case: second), as well as improving the solution time by using geometrical considerations, followed by a time effective iterative process reducing the [Formula: see text] solution. Compared to a recently published noncoplanar VMAT algorithm, using NoVo the computation time is reduced by a factor of 2-3 (depending on the case). Compared to coplanar VMAT, NoVo reduces the objective function value by 24%, 49% and 6% for the lung, brain and liver cases, respectively.

Optimizing highly noncoplanar VMAT trajectories: the NoVo method

NASA Astrophysics Data System (ADS)

Langhans, Marco; Unkelbach, Jan; Bortfeld, Thomas; Craft, David

2018-01-01

We introduce a new method called NoVo (Noncoplanar VMAT Optimization) to produce volumetric modulated arc therapy (VMAT) treatment plans with noncoplanar trajectories. While the use of noncoplanar beam arrangements for intensity modulated radiation therapy (IMRT), and in particular high fraction stereotactic radiosurgery (SRS), is common, noncoplanar beam trajectories for VMAT are less common as the availability of treatment machines handling these is limited. For both IMRT and VMAT, the beam angle selection problem is highly nonconvex in nature, which is why automated beam angle selection procedures have not entered mainstream clinical usage. NoVo determines a noncoplanar VMAT solution (i.e. the simultaneous trajectories of the gantry and the couch) by first computing a 4π solution (beams from every possible direction, suitably discretized) and then eliminating beams by examing fluence contributions. Also all beam angles are scored via geometrical considerations only to find out the usefulness of the whole beam space in a very short time. A custom path finding algorithm is applied to find an optimized, continuous trajectory through the most promising beam angles using the calculated score of the beam space. Finally, using this trajectory a VMAT plan is optimized. For three clinical cases, a lung, brain, and liver case, we compare NoVo to the ideal 4π solution, nine beam noncoplanar IMRT, coplanar VMAT, and a recently published noncoplanar VMAT algorithm. NoVo comes closest to the 4π solution considering the lung case (brain and liver case: second), as well as improving the solution time by using geometrical considerations, followed by a time effective iterative process reducing the 4π solution. Compared to a recently published noncoplanar VMAT algorithm, using NoVo the computation time is reduced by a factor of 2-3 (depending on the case). Compared to coplanar VMAT, NoVo reduces the objective function value by 24%, 49% and 6% for the lung, brain and liver cases, respectively.

A software architecture for hard real-time execution of automatically synthesized plans or control laws

NASA Technical Reports Server (NTRS)

Schoppers, Marcel

1994-01-01

The design of a flexible, real-time software architecture for trajectory planning and automatic control of redundant manipulators is described. Emphasis is placed on a technique of designing control systems that are both flexible and robust yet have good real-time performance. The solution presented involves an artificial intelligence algorithm that dynamically reprograms the real-time control system while planning system behavior.

TH-EF-BRB-10: Dosimetric Validation of a Trajectory Based Cranial SRS Treatment Technique On a Varian TrueBeam Linac

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

Wilson, B; Vancouver Cancer Centre, Vancouver, BC; Gete, E

2016-06-15

Purpose: This work investigates the dosimetric accuracy of a trajectory based delivery technique in which an optimized radiation beam is delivered along a Couch-Gantry trajectory that is formed by simultaneous rotation of the linac gantry and the treatment couch. Methods: Nine trajectory based cranial SRS treatment plans were created using in-house optimization software. The plans were calculated for delivery on the TrueBeam STx linac with 6MV photon beam. Dose optimization was performed along a user-defined trajectory using MLC modulation, dose rate modulation and jaw tracking. The pre-defined trajectory chosen for this study is formed by a couch rotation through itsmore » full range of 180 degrees while the gantry makes four partial arc sweeps which are 170 degrees each. For final dose calculation, the trajectory based plans were exported to the Varian Eclipse Treatment Planning System. The plans were calculated on a homogeneous cube phantom measuring 18.2×18.2×18.2 cm3 with the analytical anisotropic algorithm (AAA) using a 1mm3 calculation voxel. The plans were delivered on the TrueBeam linac via the developer’s mode. Point dose measurements were performed on 9 patients with the IBA CC01 mini-chamber with a sensitive volume of 0.01 cc. Gafchromic film measurements along the sagittal and coronal planes were performed on three of the 9 treatment plans. Point dose values were compared with ion chamber measurements. Gamma analysis comparing film measurement and AAA calculations was performed using FilmQA Pro. Results: The AAA calculations and measurements were in good agreement. The point dose difference between AAA and ion chamber measurements were within 2.2%. Gamma analysis test pass rates (2%, 2mm passing criteria) for the Gafchromic film measurements were >95%. Conclusion: We have successfully tested TrueBeam’s ability to deliver accurate trajectory based treatments involving simultaneous gantry and couch rotation with MLC and dose rate modulation along the trajectory.« less

Kinematics, controls, and path planning results for a redundant manipulator

NASA Technical Reports Server (NTRS)

Gretz, Bruce; Tilley, Scott W.

1989-01-01

The inverse kinematics solution, a modal position control algorithm, and path planning results for a 7 degree of freedom manipulator are presented. The redundant arm consists of two links with shoulder and elbow joints and a spherical wrist. The inverse kinematics problem for tip position is solved and the redundant joint is identified. It is also shown that a locus of tip positions exists in which there are kinematic limitations on self-motion. A computationally simple modal position control algorithm has been developed which guarantees a nearly constant closed-loop dynamic response throughout the workspace. If all closed-loop poles are assigned to the same location, the algorithm can be implemented with very little computation. To further reduce the required computation, the modal gains are updated only at discrete time intervals. Criteria are developed for the frequency of these updates. For commanding manipulator movements, a 5th-order spline which minimizes jerk provides a smooth tip-space path. Schemes for deriving a corresponding joint-space trajectory are discussed. Modifying the trajectory to avoid joint torque saturation when a tip payload is added is also considered. Simulation results are presented.

A modular approach to intensity-modulated arc therapy optimization with noncoplanar trajectories

NASA Astrophysics Data System (ADS)

Papp, Dávid; Bortfeld, Thomas; Unkelbach, Jan

2015-07-01

Utilizing noncoplanar beam angles in volumetric modulated arc therapy (VMAT) has the potential to combine the benefits of arc therapy, such as short treatment times, with the benefits of noncoplanar intensity modulated radiotherapy (IMRT) plans, such as improved organ sparing. Recently, vendors introduced treatment machines that allow for simultaneous couch and gantry motion during beam delivery to make noncoplanar VMAT treatments possible. Our aim is to provide a reliable optimization method for noncoplanar isocentric arc therapy plan optimization. The proposed solution is modular in the sense that it can incorporate different existing beam angle selection and coplanar arc therapy optimization methods. Treatment planning is performed in three steps. First, a number of promising noncoplanar beam directions are selected using an iterative beam selection heuristic; these beams serve as anchor points of the arc therapy trajectory. In the second step, continuous gantry/couch angle trajectories are optimized using a simple combinatorial optimization model to define a beam trajectory that efficiently visits each of the anchor points. Treatment time is controlled by limiting the time the beam needs to trace the prescribed trajectory. In the third and final step, an optimal arc therapy plan is found along the prescribed beam trajectory. In principle any existing arc therapy optimization method could be incorporated into this step; for this work we use a sliding window VMAT algorithm. The approach is demonstrated using two particularly challenging cases. The first one is a lung SBRT patient whose planning goals could not be satisfied with fewer than nine noncoplanar IMRT fields when the patient was treated in the clinic. The second one is a brain tumor patient, where the target volume overlaps with the optic nerves and the chiasm and it is directly adjacent to the brainstem. Both cases illustrate that the large number of angles utilized by isocentric noncoplanar VMAT plans can help improve dose conformity, homogeneity, and organ sparing simultaneously using the same beam trajectory length and delivery time as a coplanar VMAT plan.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

Automated trajectory planning for multiple-flyby interplanetary missions

NASA Astrophysics Data System (ADS)

Englander, Jacob

Many space mission planning problems may be formulated as hybrid optimal control problems (HOCP), i.e. problems that include both real-valued variables and categorical variables. In interplanetary trajectory design problems the categorical variables will typically specify the sequence of planets at which to perform flybys, and the real-valued variables will represent the launch date, ight times between planets, magnitudes and directions of thrust, flyby altitudes, etc. The contribution of this work is a framework for the autonomous optimization of multiple-flyby interplanetary trajectories. The trajectory design problem is converted into a HOCP with two nested loops: an "outer-loop" that finds the sequence of flybys and an "inner-loop" that optimizes the trajectory for each candidate yby sequence. The problem of choosing a sequence of flybys is posed as an integer programming problem and solved using a genetic algorithm (GA). This is an especially difficult problem to solve because GAs normally operate on a fixed-length set of decision variables. Since in interplanetary trajectory design the number of flyby maneuvers is not known a priori, it was necessary to devise a method of parameterizing the problem such that the GA can evolve a variable-length sequence of flybys. A novel "null gene" transcription was developed to meet this need. Then, for each candidate sequence of flybys, a trajectory must be found that visits each of the flyby targets and arrives at the final destination while optimizing some cost metric, such as minimizing ▵v or maximizing the final mass of the spacecraft. Three different classes of trajectory are described in this work, each of which requireda different physical model and optimization method. The choice of a trajectory model and optimization method is especially challenging because of the nature of the hybrid optimal control problem. Because the trajectory optimization problem is generated in real time by the outer-loop, the inner-loop optimization algorithm cannot require any a priori information and must always return a solution. In addition, the upper and lower bounds on each decision variable cannot be chosen a priori by the user because the user has no way to know what problem will be solved. Instead a method of choosing upper and lower bounds via a set of simple rules was developed and used for all three types of trajectory optimization problem. Many optimization algorithms were tested and discarded until suitable algorithms were found for each type of trajectory. The first class of trajectories use chemical propulsion and may only apply a ▵v at the periapse of each flyby. These Multiple Gravity Assist (MGA) trajectories are optimized using a cooperative algorithm of Differential Evolution (DE) and Particle Swarm Optimization (PSO). The second class of trajectories, known as Multiple Gravity Assist with one Deep Space Maneuver (MGA-DSM), also use chemical propulsion but instead of maneuvering at the periapse of each flyby as in the MGA case a maneuver is applied at a free point along each planet-to-planet arc, i.e. there is one maneuver for each pair of flybys. MGA-DSM trajectories are parameterized by more variables than MGA trajectories, and so the cooperative algorithm of DE and PSO that was used to optimize MGA trajectories was found to be less effective when applied to MGA-DSM. Instead, either PSO or DE alone were found to be more effective. The third class of trajectories addressed in this work are those using continuousthrust propulsion. Continuous-thrust trajectory optimization problems are more challenging than impulsive-thrust problems because the control variables are a continuous time series rather than a small set of parameters and because the spacecraft does not follow a conic section trajectory, leading to a large number of nonlinear constraints that must be satisfied to ensure that the spacecraft obeys the equations of motion. Many models and optimization algorithms were applied including direct transcription with nonlinear programming (DTNLP), the inverse-polynomial shapebased method, and feasible region analysis. However the only physical model and optimization method that proved reliable enough were the Sims-Flanagan transcription coupled with a nonlinear programming solver and the monotonic basin hopping (MBH) global search heuristic. The methods developed here are demonstrated to optimize a set of example trajectories, including a recreation of the Cassini mission, a Galileo-like mission, and conceptual continuous-thrust missions to Jupiter, Mercury, and Uranus.

Overview and Software Architecture of the Copernicus Trajectory Design and Optimization System

NASA Technical Reports Server (NTRS)

Williams, Jacob; Senent, Juan S.; Ocampo, Cesar; Mathur, Ravi; Davis, Elizabeth C.

2010-01-01

The Copernicus Trajectory Design and Optimization System represents an innovative and comprehensive approach to on-orbit mission design, trajectory analysis and optimization. Copernicus integrates state of the art algorithms in optimization, interactive visualization, spacecraft state propagation, and data input-output interfaces, allowing the analyst to design spacecraft missions to all possible Solar System destinations. All of these features are incorporated within a single architecture that can be used interactively via a comprehensive GUI interface, or passively via external interfaces that execute batch processes. This paper describes the Copernicus software architecture together with the challenges associated with its implementation. Additionally, future development and planned new capabilities are discussed. Key words: Copernicus, Spacecraft Trajectory Optimization Software.

Generate stepper motor linear speed profile in real time

NASA Astrophysics Data System (ADS)

Stoychitch, M. Y.

2018-01-01

In this paper we consider the problem of realization of linear speed profile of stepper motors in real time. We considered the general case when changes of speed in the phases of acceleration and deceleration are different. The new and practical algorithm of the trajectory planning is given. The algorithms of the real time speed control which are suitable for realization to the microcontroller and FPGA circuits are proposed. The practical realization one of these algorithms, using Arduino platform, is given also.

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

NASA Technical Reports Server (NTRS)

Baskaran, Subbiah; Noever, D.

1999-01-01

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Self-Organizing Map With Time-Varying Structure to Plan and Control Artificial Locomotion.

PubMed

Araujo, Aluizio F R; Santana, Orivaldo V

2015-08-01

This paper presents an algorithm, self-organizing map-state trajectory generator (SOM-STG), to plan and control legged robot locomotion. The SOM-STG is based on an SOM with a time-varying structure characterized by constructing autonomously close-state trajectories from an arbitrary number of robot postures. Each trajectory represents a cyclical movement of the limbs of an animal. The SOM-STG was designed to possess important features of a central pattern generator, such as rhythmic pattern generation, synchronization between limbs, and swapping between gaits following a single command. The acquisition of data for SOM-STG is based on learning by demonstration in which the data are obtained from different demonstrator agents. The SOM-STG can construct one or more gaits for a simulated robot with six legs, can control the robot with any of the gaits learned, and can smoothly swap gaits. In addition, SOM-STG can learn to construct a state trajectory form observing an animal in locomotion. In this paper, a dog is the demonstrator agent.

Minimum deltaV Burn Planning for the International Space Station Using a Hybrid Optimization Technique, Level 1

NASA Technical Reports Server (NTRS)

Brown, Aaron J.

2015-01-01

The International Space Station's (ISS) trajectory is coordinated and executed by the Trajectory Operations and Planning (TOPO) group at NASA's Johnson Space Center. TOPO group personnel routinely generate look-ahead trajectories for the ISS that incorporate translation burns needed to maintain its orbit over the next three to twelve months. The burns are modeled as in-plane, horizontal burns, and must meet operational trajectory constraints imposed by both NASA and the Russian Space Agency. In generating these trajectories, TOPO personnel must determine the number of burns to model, each burn's Time of Ignition (TIG), and magnitude (i.e. deltaV) that meet these constraints. The current process for targeting these burns is manually intensive, and does not take advantage of more modern techniques that can reduce the workload needed to find feasible burn solutions, i.e. solutions that simply meet the constraints, or provide optimal burn solutions that minimize the total DeltaV while simultaneously meeting the constraints. A two-level, hybrid optimization technique is proposed to find both feasible and globally optimal burn solutions for ISS trajectory planning. For optimal solutions, the technique breaks the optimization problem into two distinct sub-problems, one for choosing the optimal number of burns and each burn's optimal TIG, and the other for computing the minimum total deltaV burn solution that satisfies the trajectory constraints. Each of the two aforementioned levels uses a different optimization algorithm to solve one of the sub-problems, giving rise to a hybrid technique. Level 2, or the outer level, uses a genetic algorithm to select the number of burns and each burn's TIG. Level 1, or the inner level, uses the burn TIGs from Level 2 in a sequential quadratic programming (SQP) algorithm to compute a minimum total deltaV burn solution subject to the trajectory constraints. The total deltaV from Level 1 is then used as a fitness function by the genetic algorithm in Level 2 to select the number of burns and their TIGs for the next generation. In this manner, the two levels solve their respective sub-problems separately but collaboratively until a burn solution is found that globally minimizes the deltaV across the entire trajectory. Feasible solutions can also be found by simply using the SQP algorithm in Level 1 with a zero cost function. This paper discusses the formulation of the Level 1 sub-problem and the development of a prototype software tool to solve it. The Level 2 sub-problem will be discussed in a future work. Following the Level 1 formulation and solution, several look-ahead trajectory examples for the ISS are explored. In each case, the burn targeting results using the current process are compared against a feasible solution found using Level 1 in the proposed technique. Level 1 is then used to find a minimum deltaV solution given the fixed number of burns and burn TIGs. The optimal solution is compared with the previously found feasible solution to determine the deltaV (and therefore propellant) savings. The proposed technique seeks to both improve the current process for targeting ISS burns, and to add the capability to optimize ISS burns in a novel fashion. The optimal solutions found using this technique can potentially save hundreds of kilograms of propellant over the course of the ISS mission compared to feasible solutions alone. While the software tool being developed to implement this technique is specific to ISS, the concept is extensible to other long-duration, central-body orbiting missions that must perform orbit maintenance burns to meet operational trajectory constraints.

A six degree of freedom, plume-fuel optimal trajectory planner for spacecraft proximity operations using an A* node search. M.S. Thesis - MIT

NASA Technical Reports Server (NTRS)

Jackson, Mark Charles

1994-01-01

Spacecraft proximity operations are complicated by the fact that exhaust plume impingement from the reaction control jets of space vehicles can cause structural damage, contamination of sensitive arrays and instruments, or attitude misalignment during docking. The occurrence and effect of jet plume impingement can be reduced by planning approach trajectories with plume effects considered. An A* node search is used to find plume-fuel optimal trajectories through a discretized six dimensional attitude-translation space. A plume cost function which approximates jet plume isopressure envelopes is presented. The function is then applied to find relative costs for predictable 'trajectory altering' firings and unpredictable 'deadbanding' firings. Trajectory altering firings are calculated by running the spacecraft jet selection algorithm and summing the cost contribution from each jet fired. A 'deadbanding effects' function is defined and integrated to determine the potential for deadbanding impingement along candidate trajectories. Plume costs are weighed against fuel costs in finding the optimal solution. A* convergence speed is improved by solving approach trajectory problems in reverse time. Results are obtained on a high fidelity space shuttle/space station simulation. Trajectory following is accomplished by a six degree of freedom autopilot. Trajectories planned with, and without, plume costs are compared in terms of force applied to the target structure.

TH-EF-BRB-04: 4π Dynamic Conformal Arc Therapy Dynamic Conformal Arc Therapy (DCAT) for SBRT

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

Chiu, T; Long, T; Tian, Z.

2016-06-15

Purpose: To develop an efficient and effective trajectory optimization methodology for 4π dynamic conformal arc treatment (4π DCAT) with synchronized gantry and couch motion; and to investigate potential clinical benefits for stereotactic body radiation therapy (SBRT) to breast, lung, liver and spine tumors. Methods: The entire optimization framework for 4π DCAT inverse planning consists of two parts: 1) integer programming algorithm and 2) particle swarm optimization (PSO) algorithm. The integer programming is designed to find an optimal solution for arc delivery trajectory with both couch and gantry rotation, while PSO minimize a non-convex objective function based on the selected trajectorymore » and dose-volume constraints. In this study, control point interaction is explicitly taken into account. Beam trajectory was modeled as a series of control points connected together to form a deliverable path. With linear treatment planning objectives, a mixed-integer program (MIP) was formulated. Under mild assumptions, the MIP is tractable. Assigning monitor units to control points along the path can be integrated into the model and done by PSO. The developed 4π DCAT inverse planning strategy is evaluated on SBRT cases and compared to clinically treated plans. Results: The resultant dose distribution of this technique was evaluated between 3D conformal treatment plan generated by Pinnacle treatment planning system and 4π DCAT on a lung SBRT patient case. Both plans share the same scale of MU, 3038 and 2822 correspondingly to 3D conformal plan and 4π DCAT. The mean doses for most of OARs were greatly reduced at 32% (cord), 70% (esophagus), 2.8% (lung) and 42.4% (stomach). Conclusion: Initial results in this study show the proposed 4π DCAT treatment technique can achieve better OAR sparing and lower MUs, which indicates that the developed technique is promising for high dose SBRT to reduce the risk of secondary cancer.« less

NASP guidance design for vehicle autonomy

NASA Astrophysics Data System (ADS)

Wagner, E. A.; Li, I.; Nguyen, D. D.; Nguyen, P. L.

1990-10-01

Vehicle guidance for General Dynamics' NASP vehicle is planned to be self-contained onboard the vehicle, and independent of any ground support during the mission. It will include real-time onboard abort and ascent trajectory optimization capability. Although these features should be considered a natural outgrowth of research in guidance and trajectory optimization and advances in computation, facilitating full vehicle autonomy for NASP represents a significant advance relative to any flight-demonstrated guidance. Algorithms and processing requirements for autonomous NASP vehicle guidance are considered.

Advanced design for orbital debris removal in support of solar system exploration

NASA Technical Reports Server (NTRS)

1991-01-01

The development of an Autonomous Space Processor for Orbital Debris (ASPOD) is the ultimate goal. The craft will process, in situ, orbital debris using resources available in low Earth orbit (LEO). The serious problem of orbital debris is briefly described and the nature of the large debris population is outlined. This year, focus was on development of a versatile robotic manipulator to augment an existing robotic arm; incorporation of remote operation of robotic arms; and formulation of optimal (time and energy) trajectory planning algorithms for coordinating robotic arms. The mechanical design of the new arm is described in detail. The versatile work envelope is explained showing the flexibility of the new design. Several telemetry communication systems are described which will enable the remote operation of the robotic arms. The trajectory planning algorithms are fully developed for both the time-optimal and energy-optimal problem. The optimal problem is solved using phase plane techniques while the energy optimal problem is solved using dynamics programming.

Autonomous space processor for orbital debris

NASA Technical Reports Server (NTRS)

Ramohalli, Kumar; Marine, Micky; Colvin, James; Crockett, Richard; Sword, Lee; Putz, Jennifer; Woelfle, Sheri

1991-01-01

The development of an Autonomous Space Processor for Orbital Debris (ASPOD) was the goal. The nature of this craft, which will process, in situ, orbital debris using resources available in low Earth orbit (LEO) is explained. The serious problem of orbital debris is briefly described and the nature of the large debris population is outlined. The focus was on the development of a versatile robotic manipulator to augment an existing robotic arm, the incorporation of remote operation of the robotic arms, and the formulation of optimal (time and energy) trajectory planning algorithms for coordinated robotic arms. The mechanical design of the new arm is described in detail. The work envelope is explained showing the flexibility of the new design. Several telemetry communication systems are described which will enable the remote operation of the robotic arms. The trajectory planning algorithms are fully developed for both the time optimal and energy optimal problems. The time optimal problem is solved using phase plane techniques while the energy optimal problem is solved using dynamic programming.

Theory and algorithms for image reconstruction on chords and within regions of interest

NASA Astrophysics Data System (ADS)

Zou, Yu; Pan, Xiaochuan; Sidky, Emilâ Y.

2005-11-01

We introduce a formula for image reconstruction on a chord of a general source trajectory. We subsequently develop three algorithms for exact image reconstruction on a chord from data acquired with the general trajectory. Interestingly, two of the developed algorithms can accommodate data containing transverse truncations. The widely used helical trajectory and other trajectories discussed in literature can be interpreted as special cases of the general trajectory, and the developed theory and algorithms are thus directly applicable to reconstructing images exactly from data acquired with these trajectories. For instance, chords on a helical trajectory are equivalent to the n-PI-line segments. In this situation, the proposed algorithms become the algorithms that we proposed previously for image reconstruction on PI-line segments. We have performed preliminary numerical studies, which include the study on image reconstruction on chords of two-circle trajectory, which is nonsmooth, and on n-PI lines of a helical trajectory, which is smooth. Quantitative results of these studies verify and demonstrate the proposed theory and algorithms.

Encke-Beta Predictor for Orion Burn Targeting and Guidance

NASA Technical Reports Server (NTRS)

Robinson, Shane; Scarritt, Sara; Goodman, John L.

2016-01-01

The state vector prediction algorithm selected for Orion on-board targeting and guidance is known as the Encke-Beta method. Encke-Beta uses a universal anomaly (beta) as the independent variable, valid for circular, elliptical, parabolic, and hyperbolic orbits. The variable, related to the change in eccentric anomaly, results in integration steps that cover smaller arcs of the trajectory at or near perigee, when velocity is higher. Some burns in the EM-1 and EM-2 mission plans are much longer than burns executed with the Apollo and Space Shuttle vehicles. Burn length, as well as hyperbolic trajectories, has driven the use of the Encke-Beta numerical predictor by the predictor/corrector guidance algorithm in place of legacy analytic thrust and gravity integrals.

A Trajectory Generation Approach for Payload Directed Flight

NASA Technical Reports Server (NTRS)

Ippolito, Corey A.; Yeh, Yoo-Hsiu

2009-01-01

Presently, flight systems designed to perform payload-centric maneuvers require preconstructed procedures and special hand-tuned guidance modes. To enable intelligent maneuvering via strong coupling between the goals of payload-directed flight and the autopilot functions, there exists a need to rethink traditional autopilot design and function. Research into payload directed flight examines sensor and payload-centric autopilot modes, architectures, and algorithms that provide layers of intelligent guidance, navigation and control for flight vehicles to achieve mission goals related to the payload sensors, taking into account various constraints such as the performance limitations of the aircraft, target tracking and estimation, obstacle avoidance, and constraint satisfaction. Payload directed flight requires a methodology for accurate trajectory planning that lets the system anticipate expected return from a suite of onboard sensors. This paper presents an extension to the existing techniques used in the literature to quickly and accurately plan flight trajectories that predict and optimize the expected return of onboard payload sensors.

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madhu; Harwood, David

1989-01-01

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Optimizing Mars Airplane Trajectory with the Application Navigation System

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Riley, Derek

2004-01-01

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

CyberArc: a non-coplanar-arc optimization algorithm for CyberKnife

NASA Astrophysics Data System (ADS)

Kearney, Vasant; Cheung, Joey P.; McGuinness, Christopher; Solberg, Timothy D.

2017-07-01

The goal of this study is to demonstrate the feasibility of a novel non-coplanar-arc optimization algorithm (CyberArc). This method aims to reduce the delivery time of conventional CyberKnife treatments by allowing for continuous beam delivery. CyberArc uses a 4 step optimization strategy, in which nodes, beams, and collimator sizes are determined, source trajectories are calculated, intermediate radiation models are generated, and final monitor units are calculated, for the continuous radiation source model. The dosimetric results as well as the time reduction factors for CyberArc are presented for 7 prostate and 2 brain cases. The dosimetric quality of the CyberArc plans are evaluated using conformity index, heterogeneity index, local confined normalized-mutual-information, and various clinically relevant dosimetric parameters. The results indicate that the CyberArc algorithm dramatically reduces the treatment time of CyberKnife plans while simultaneously preserving the dosimetric quality of the original plans.

CyberArc: a non-coplanar-arc optimization algorithm for CyberKnife.

PubMed

Kearney, Vasant; Cheung, Joey P; McGuinness, Christopher; Solberg, Timothy D

2017-06-26

The goal of this study is to demonstrate the feasibility of a novel non-coplanar-arc optimization algorithm (CyberArc). This method aims to reduce the delivery time of conventional CyberKnife treatments by allowing for continuous beam delivery. CyberArc uses a 4 step optimization strategy, in which nodes, beams, and collimator sizes are determined, source trajectories are calculated, intermediate radiation models are generated, and final monitor units are calculated, for the continuous radiation source model. The dosimetric results as well as the time reduction factors for CyberArc are presented for 7 prostate and 2 brain cases. The dosimetric quality of the CyberArc plans are evaluated using conformity index, heterogeneity index, local confined normalized-mutual-information, and various clinically relevant dosimetric parameters. The results indicate that the CyberArc algorithm dramatically reduces the treatment time of CyberKnife plans while simultaneously preserving the dosimetric quality of the original plans.

Robot acting on moving bodies (RAMBO): Preliminary results

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madju; Harwood, David

1989-01-01

A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

NASA Technical Reports Server (NTRS)

Blackmore, Lars

2008-01-01

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

Flight evaluation of a computer aided low-altitude helicopter flight guidance system

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Jones, Raymond D.; Clark, Raymond

1993-01-01

The Flight Systems Development branch of the U.S. Army's Avionics Research and Development Activity (AVRADA) and NASA Ames Research Center developed for flight testing a Computer Aided Low-Altitude Helicopter Flight (CALAHF) guidance system. The system includes a trajectory-generation algorithm which uses dynamic programming and a helmet-mounted display (HMD) presentation of a pathway-in-the-sky, a phantom aircraft, and flight-path vector/predictor guidance symbology. The trajectory-generation algorithm uses knowledge of the global mission requirements, a digital terrain map, aircraft performance capabilities, and precision navigation information to determine a trajectory between mission waypoints that seeks valleys to minimize threat exposure. This system was developed and evaluated through extensive use of piloted simulation and has demonstrated a 'pilot centered' concept of automated and integrated navigation and terrain mission planning flight guidance. This system has shown a significant improvement in pilot situational awareness, and mission effectiveness as well as a decrease in training and proficiency time required for a near terrain, nighttime, adverse weather system.

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

NASA Technical Reports Server (NTRS)

Howell, Lauren R.; Allen, B. Danette

2016-01-01

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

A Sampling Based Approach to Spacecraft Autonomous Maneuvering with Safety Specifications

NASA Technical Reports Server (NTRS)

Starek, Joseph A.; Barbee, Brent W.; Pavone, Marco

2015-01-01

This paper presents a methods for safe spacecraft autonomous maneuvering that leverages robotic motion-planning techniques to spacecraft control. Specifically the scenario we consider is an in-plan rendezvous of a chaser spacecraft in proximity to a target spacecraft at the origin of the Clohessy Wiltshire Hill frame. The trajectory for the chaser spacecraft is generated in a receding horizon fashion by executing a sampling based robotic motion planning algorithm name Fast Marching Trees (FMT) which efficiently grows a tree of trajectories over a set of probabillistically drawn samples in the state space. To enforce safety the tree is only grown over actively safe samples for which there exists a one-burn collision avoidance maneuver that circularizes the spacecraft orbit along a collision-free coasting arc and that can be executed under potential thrusters failures. The overall approach establishes a provably correct framework for the systematic encoding of safety specifications into the spacecraft trajectory generations process and appears amenable to real time implementation on orbit. Simulation results are presented for a two-fault tolerant spacecraft during autonomous approach to a single client in Low Earth Orbit.

SU-F-T-288: Impact of Trajectory Log Files for Clarkson-Based Independent Dose Verification of IMRT and VMAT

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

Takahashi, R; Kamima, T; Tachibana, H

2016-06-15

Purpose: To investigate the effect of the trajectory files from linear accelerator for Clarkson-based independent dose verification in IMRT and VMAT plans. Methods: A CT-based independent dose verification software (Simple MU Analysis: SMU, Triangle Products, Japan) with a Clarksonbased algorithm was modified to calculate dose using the trajectory log files. Eclipse with the three techniques of step and shoot (SS), sliding window (SW) and Rapid Arc (RA) was used as treatment planning system (TPS). In this study, clinically approved IMRT and VMAT plans for prostate and head and neck (HN) at two institutions were retrospectively analyzed to assess the dosemore » deviation between DICOM-RT plan (PL) and trajectory log file (TJ). An additional analysis was performed to evaluate MLC error detection capability of SMU when the trajectory log files was modified by adding systematic errors (0.2, 0.5, 1.0 mm) and random errors (5, 10, 30 mm) to actual MLC position. Results: The dose deviations for prostate and HN in the two sites were 0.0% and 0.0% in SS, 0.1±0.0%, 0.1±0.1% in SW and 0.6±0.5%, 0.7±0.9% in RA, respectively. The MLC error detection capability shows the plans for HN IMRT were the most sensitive and 0.2 mm of systematic error affected 0.7% dose deviation on average. Effect of the MLC random error did not affect dose error. Conclusion: The use of trajectory log files including actual information of MLC location, gantry angle, etc should be more effective for an independent verification. The tolerance level for the secondary check using the trajectory file may be similar to that of the verification using DICOM-RT plan file. From the view of the resolution of MLC positional error detection, the secondary check could detect the MLC position error corresponding to the treatment sites and techniques. This research is partially supported by Japan Agency for Medical Research and Development (AMED)« less

A Review of Robotics Technologies for On-Orbit Services

DTIC Science & Technology

2013-01-01

The SpaceX vehicle has successfully accomplished its first docking with the ISS in May 2012, delivered about 1,200 lbs of water, food , and other...algorithms, which can generate collision-free robot motion paths. Recently, Franch et al [101] have employed flatness theory to plan trajectories...3713–3719 (2005). [101] Franch J, Agrawal S, Fattah A, "Design of Differentially Flat Planar Space Robots: a Step Forward in Their Planning and

A Formally Verified Conflict Detection Algorithm for Polynomial Trajectories

NASA Technical Reports Server (NTRS)

Narkawicz, Anthony; Munoz, Cesar

2015-01-01

In air traffic management, conflict detection algorithms are used to determine whether or not aircraft are predicted to lose horizontal and vertical separation minima within a time interval assuming a trajectory model. In the case of linear trajectories, conflict detection algorithms have been proposed that are both sound, i.e., they detect all conflicts, and complete, i.e., they do not present false alarms. In general, for arbitrary nonlinear trajectory models, it is possible to define detection algorithms that are either sound or complete, but not both. This paper considers the case of nonlinear aircraft trajectory models based on polynomial functions. In particular, it proposes a conflict detection algorithm that precisely determines whether, given a lookahead time, two aircraft flying polynomial trajectories are in conflict. That is, it has been formally verified that, assuming that the aircraft trajectories are modeled as polynomial functions, the proposed algorithm is both sound and complete.

A stochastic framework for spot-scanning particle therapy.

PubMed

Robini, Marc; Yuemin Zhu; Wanyu Liu; Magnin, Isabelle

2016-08-01

In spot-scanning particle therapy, inverse treatment planning is usually limited to finding the optimal beam fluences given the beam trajectories and energies. We address the much more challenging problem of jointly optimizing the beam fluences, trajectories and energies. For this purpose, we design a simulated annealing algorithm with an exploration mechanism that balances the conflicting demands of a small mixing time at high temperatures and a reasonable acceptance rate at low temperatures. Numerical experiments substantiate the relevance of our approach and open new horizons to spot-scanning particle therapy.

Accurate predictor-corrector skip entry guidance for low lift-to-drag ratio spacecraft

NASA Astrophysics Data System (ADS)

Enmi, Y.; Qian, W.; He, K.; Di, D.

2018-06-01

This paper develops numerical predictor-corrector skip en try guidance for vehicles with low lift-to-drag L/D ratio during the skip entry phase of a Moon return mission. The guidance method is composed of two parts: trajectory planning before entry and closed-loop gu idance during skip entry. The result of trajectory planning before entry is able to present an initial value for predictor-corrector algorithm in closed-loop guidance for fast convergence. The magnitude of bank angle, which is parameterized as a linear function of the range-to-go, is modulated to satisfy the downrange requirements. The sign of the bank ang le is determined by the bank-reversal logic. The predictor-corrector algorithm repeatedly applied onboard in each guidance cycle to realize closed-loop guidance in the skip entry phase. The effectivity of the proposed guidance is validated by simulations in nominal conditions, including skip entry, loft entry, and direct entry, as well as simulations in dispersion conditions considering the combination disturbance of the entry interface, the aerodynamic coefficients, the air density, and the mass of the vehicle.

Computing approximate random Delta v magnitude probability densities. [for spacecraft trajectory correction

NASA Technical Reports Server (NTRS)

Chadwick, C.

1984-01-01

This paper describes the development and use of an algorithm to compute approximate statistics of the magnitude of a single random trajectory correction maneuver (TCM) Delta v vector. The TCM Delta v vector is modeled as a three component Cartesian vector each of whose components is a random variable having a normal (Gaussian) distribution with zero mean and possibly unequal standard deviations. The algorithm uses these standard deviations as input to produce approximations to (1) the mean and standard deviation of the magnitude of Delta v, (2) points of the probability density function of the magnitude of Delta v, and (3) points of the cumulative and inverse cumulative distribution functions of Delta v. The approximates are based on Monte Carlo techniques developed in a previous paper by the author and extended here. The algorithm described is expected to be useful in both pre-flight planning and in-flight analysis of maneuver propellant requirements for space missions.

Design of Quiet Rotorcraft Approach Trajectories: Verification Phase

NASA Technical Reports Server (NTRS)

Padula, Sharon L.

2010-01-01

Flight testing that is planned for October 2010 will provide an opportunity to evaluate rotorcraft trajectory optimization techniques. The flight test will involve a fully instrumented MD-902 helicopter, which will be flown over an array of microphones. In this work, the helicopter approach trajectory is optimized via a multiobjective genetic algorithm to improve community noise, passenger comfort, and pilot acceptance. Previously developed optimization strategies are modified to accommodate new helicopter data and to increase pilot acceptance. This paper describes the MD-902 trajectory optimization plus general optimization strategies and modifications that are needed to reduce the uncertainty in noise predictions. The constraints that are imposed by the flight test conditions and characteristics of the MD-902 helicopter limit the testing possibilities. However, the insights that will be gained through this research will prove highly valuable.

A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.

PubMed

Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

2017-03-06

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

Single-step collision-free trajectory planning of biped climbing robots in spatial trusses.

PubMed

Zhu, Haifei; Guan, Yisheng; Chen, Shengjun; Su, Manjia; Zhang, Hong

For a biped climbing robot with dual grippers to climb poles, trusses or trees, feasible collision-free climbing motion is inevitable and essential. In this paper, we utilize the sampling-based algorithm, Bi-RRT, to plan single-step collision-free motion for biped climbing robots in spatial trusses. To deal with the orientation limit of a 5-DoF biped climbing robot, a new state representation along with corresponding operations including sampling, metric calculation and interpolation is presented. A simple but effective model of a biped climbing robot in trusses is proposed, through which the motion planning of one climbing cycle is transformed to that of a manipulator. In addition, the pre- and post-processes are introduced to expedite the convergence of the Bi-RRT algorithm and to ensure the safe motion of the climbing robot near poles as well. The piecewise linear paths are smoothed by utilizing cubic B-spline curve fitting. The effectiveness and efficiency of the presented Bi-RRT algorithm for climbing motion planning are verified by simulations.

A trajectory planning scheme for spacecraft in the space station environment. M.S. Thesis - University of California

NASA Technical Reports Server (NTRS)

Soller, Jeffrey Alan; Grunwald, Arthur J.; Ellis, Stephen R.

1991-01-01

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions.

Outcome of single-trajectory rigid endoscopic third ventriculostomy and biopsy in the management algorithm of pineal region tumors: a case series and review of the literature.

PubMed

Abbassy, Mahmoud; Aref, Khaled; Farhoud, Ahmed; Hekal, Anwar

2018-05-28

Tumors within the pineal region represent 1.5 to 8.5% of the pediatric brain tumors and 1.2% of all brain tumors. A management algorithm has been proposed in several publications. The algorithm includes endoscopic third ventriculostomy (ETV) and biopsy in cases presenting with hydrocephalus. In this series, we are presenting the efficacy of a single-trajectory approach for both ETV and biopsy. Eleven cases were admitted to Alexandria main university hospital from 2013 to 2016 presenting with pineal region tumors and hydrocephalus. Mean age at diagnosis was 11 years (1-27 years). All cases had ETV and biopsy using rigid ventriculoscope through a single trajectory from a burr hole planned on preoperative imaging. Follow-up period was 7-48 months. All 11 cases presented with hydrocephalus and increased intracranial pressure manifestations. Histopathological diagnosis was successful in 9 out of 11 cases (81.8%). Three cases were germ-cell tumors, two cases were pineoblastomas, two cases were pilocytic astrocytomas, and two cases were grade 2 tectal gliomas. Five of the ETV cases (45.5%) failed and required VPS later on. Other complications of ETV included one case of intraventricular hemorrhage and a case with tumor disseminated to the basal cisterns. In our series, we were able to achieve ETV and biopsy through a single trajectory and a rigid endoscope with results comparable to other studies in the literature.

Optimal trajectories of aircraft and spacecraft

NASA Technical Reports Server (NTRS)

Miele, A.

1990-01-01

Work done on algorithms for the numerical solutions of optimal control problems and their application to the computation of optimal flight trajectories of aircraft and spacecraft is summarized. General considerations on calculus of variations, optimal control, numerical algorithms, and applications of these algorithms to real-world problems are presented. The sequential gradient-restoration algorithm (SGRA) is examined for the numerical solution of optimal control problems of the Bolza type. Both the primal formulation and the dual formulation are discussed. Aircraft trajectories, in particular, the application of the dual sequential gradient-restoration algorithm (DSGRA) to the determination of optimal flight trajectories in the presence of windshear are described. Both take-off trajectories and abort landing trajectories are discussed. Take-off trajectories are optimized by minimizing the peak deviation of the absolute path inclination from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. The survival capability of an aircraft in a severe windshear is discussed, and the optimal trajectories are found to be superior to both constant pitch trajectories and maximum angle of attack trajectories. Spacecraft trajectories, in particular, the application of the primal sequential gradient-restoration algorithm (PSGRA) to the determination of optimal flight trajectories for aeroassisted orbital transfer are examined. Both the coplanar case and the noncoplanar case are discussed within the frame of three problems: minimization of the total characteristic velocity; minimization of the time integral of the square of the path inclination; and minimization of the peak heating rate. The solution of the second problem is called nearly-grazing solution, and its merits are pointed out as a useful engineering compromise between energy requirements and aerodynamics heating requirements.

Rapid Onboard Trajectory Design for Autonomous Spacecraft in Multibody Systems

NASA Astrophysics Data System (ADS)

Trumbauer, Eric Michael

This research develops automated, on-board trajectory planning algorithms in order to support current and new mission concepts. These include orbiter missions to Phobos or Deimos, Outer Planet Moon orbiters, and robotic and crewed missions to small bodies. The challenges stem from the limited on-board computing resources which restrict full trajectory optimization with guaranteed convergence in complex dynamical environments. The approach taken consists of leveraging pre-mission computations to create a large database of pre-computed orbits and arcs. Such a database is used to generate a discrete representation of the dynamics in the form of a directed graph, which acts to index these arcs. This allows the use of graph search algorithms on-board in order to provide good approximate solutions to the path planning problem. Coupled with robust differential correction and optimization techniques, this enables the determination of an efficient path between any boundary conditions with very little time and computing effort. Furthermore, the optimization methods developed here based on sequential convex programming are shown to have provable convergence properties, as well as generating feasible major iterates in case of a system interrupt -- a key requirement for on-board application. The outcome of this project is thus the development of an algorithmic framework which allows the deployment of this approach in a variety of specific mission contexts. Test cases related to missions of interest to NASA and JPL such as a Phobos orbiter and a Near Earth Asteroid interceptor are demonstrated, including the results of an implementation on the RAD750 flight processor. This method fills a gap in the toolbox being developed to create fully autonomous space exploration systems.

Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report

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

EISLER, G. RICHARD

This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstratemore » the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.« less

Real-time terminal area trajectory planning for runway independent aircraft

NASA Astrophysics Data System (ADS)

Xue, Min

The increasing demand for commercial air transportation results in delays due to traffic queues that form bottlenecks along final approach and departure corridors. In urban areas, it is often infeasible to build new runways, and regardless of automation upgrades traffic must remain separated to avoid the wakes of previous aircraft. Vertical or short takeoff and landing aircraft as Runway Independent Aircraft (RIA) can increase passenger throughput at major urban airports via the use of vertiports or stub runways. The concept of simultaneous non-interfering (SNI) operations has been proposed to reduce traffic delays by creating approach and departure corridors that do not intersect existing fixed-wing routes. However, SNI trajectories open new routes that may overfly noise-sensitive areas, and RIA may generate more noise than traditional jet aircraft, particularly on approach. In this dissertation, we develop efficient SNI noise abatement procedures applicable to RIA. First, we introduce a methodology based on modified approximated cell-decomposition and Dijkstra's search algorithm to optimize longitudinal plane (2-D) RIA trajectories over a cost function that minimizes noise, time, and fuel use. Then, we extend the trajectory optimization model to 3-D with a k-ary tree as the discrete search space. We incorporate geography information system (GIS) data, specifically population, into our objective function, and focus on a practical case study: the design of SNI RIA approach procedures to Baltimore-Washington International airport. Because solutions were represented as trim state sequences, we incorporated smooth transition between segments to enable more realistic cost estimates. Due to the significant computational complexity, we investigated alternative more efficient optimization techniques applicable to our nonlinear, non-convex, heavily constrained, and discontinuous objective function. Comparing genetic algorithm (GA) and adaptive simulated annealing (ASA) with our original Dijkstra's algorithm, ASA is identified as the most efficient algorithm for terminal area trajectory optimization. The effects of design parameter discretization are analyzed, with results indicating a SNI procedure with 3-4 segments effectively balances simplicity with cost minimization. Finally, pilot control commands were implemented and generated via optimization-base inverse simulation to validate execution of the optimal approach trajectories.

Reconfigurable manufacturing execution system for pipe cutting

NASA Astrophysics Data System (ADS)

Yin, Y. H.; Xie, J. Y.

2011-08-01

This article presents a reconfigurable manufacturing execution system (RMES) filling the gap between enterprise resource planning and resource layer for pipe-cutting production with mass customisation and rapid adaptation to dynamic market, which consists of planning and scheduling layer and executive control layer. Starting from customer's task and process requirements, the cutting trajectories are planned under generalised mathematical model able to reconfigure in accordance with various intersecting types' joint, and all tasks are scheduled by nesting algorithm to maximise the utilisation rate of rough material. This RMES for pipe cutting has been effectively implemented in more than 100 companies.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Autonomous Operations Planner: A Flexible Platform for Research in Flight-Deck Support for Airborne Self-Separation

NASA Technical Reports Server (NTRS)

Karr, David A.; Vivona, Robert A.; DePascale, Stephen M.; Wing, David J.

2012-01-01

The Autonomous Operations Planner (AOP), developed by NASA, is a flexible and powerful prototype of a flight-deck automation system to support self-separation of aircraft. The AOP incorporates a variety of algorithms to detect and resolve conflicts between the trajectories of its own aircraft and traffic aircraft while meeting route constraints such as required times of arrival and avoiding airspace hazards such as convective weather and restricted airspace. This integrated suite of algorithms provides flight crew support for strategic and tactical conflict resolutions and conflict-free trajectory planning while en route. The AOP has supported an extensive set of experiments covering various conditions and variations on the self-separation concept, yielding insight into the system s design and resolving various challenges encountered in the exploration of the concept. The design of the AOP will enable it to continue to evolve and support experimentation as the self-separation concept is refined.

Methodology and Results of the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS)

NASA Technical Reports Server (NTRS)

Barbee, Brent W.; Mink, Ronald G.; Adamo, Daniel R.; Alberding, Cassandra M.

2011-01-01

Near-Earth Asteroids (NEAs) have been identified by the Administration as potential destinations for human explorers during the mid-2020s. Planning such ambitious missions requires selecting potentially accessible targets from the growing known population of 8,008 NEAs. NASA is therefore conducting the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS), in which the trajectory opportunities to all known NEAs are being systematically evaluated with respect to a set of defined constraints. While the NHATS algorithms have identified hundreds of NEAs which satisfy purposely inclusive trajectory constraints, only a handful of them offer truly attractive mission opportunities in the time frame of greatest interest. In this paper we will describe the structure of the NHATS algorithms and the constraints utilized in the study, present current study results, and discuss various mission design considerations for future human space flight missions to NEAs.

A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments

PubMed Central

Yan, Zheping; Li, Jiyun; Zhang, Gengshi; Wu, Yi

2018-01-01

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle’s irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal. PMID:29393915

A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments.

PubMed

Yan, Zheping; Li, Jiyun; Zhang, Gengshi; Wu, Yi

2018-02-02

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle's irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal.

Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories

NASA Technical Reports Server (NTRS)

Burchett, Bradley T.

2003-01-01

The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.

The Natural-CCD Algorithm, a Novel Method to Solve the Inverse Kinematics of Hyper-redundant and Soft Robots.

PubMed

Martín, Andrés; Barrientos, Antonio; Del Cerro, Jaime

2018-03-22

This article presents a new method to solve the inverse kinematics problem of hyper-redundant and soft manipulators. From an engineering perspective, this kind of robots are underdetermined systems. Therefore, they exhibit an infinite number of solutions for the inverse kinematics problem, and to choose the best one can be a great challenge. A new algorithm based on the cyclic coordinate descent (CCD) and named as natural-CCD is proposed to solve this issue. It takes its name as a result of generating very harmonious robot movements and trajectories that also appear in nature, such as the golden spiral. In addition, it has been applied to perform continuous trajectories, to develop whole-body movements, to analyze motion planning in complex environments, and to study fault tolerance, even for both prismatic and rotational joints. The proposed algorithm is very simple, precise, and computationally efficient. It works for robots either in two or three spatial dimensions and handles a large amount of degrees-of-freedom. Because of this, it is aimed to break down barriers between discrete hyper-redundant and continuum soft robots.

Conception et analyse d'un systeme d'optimisation de plans de vol pour les avions

NASA Astrophysics Data System (ADS)

Maazoun, Wissem

The main objective of this thesis is to develop an optimization method for the preparation of flight plans for aircrafts. The flight plan minimizes all costs associated with the flight. We determine an optimal path for an airplane from a departure airport to a destination airport. The optimal path minimizes the sum of all costs, i.e. the cost of fuel added to the cost of time (wages, rental of the aircraft, arrival delays, etc.). The optimal trajectory is obtained by considering all possible trajectories on a 3D graph (longitude, latitude and altitude) where the altitude levels are separated by 2,000 feet, and by applying a shortest path algorithm. The main task was to accurately compute fuel consumption on each edge of the graph, making sure that each arc has a minimal cost and is covered in a realistic way from the point of view of control, i.e. in accordance with the rules of navigation. To compute the cost of an arc, we take into account weather conditions (temperature, pressure, wind components, etc.). The optimization of each arc is done via the evaluation of an optimum speed that takes all costs into account. Each arc of the graph typically includes several sub-phases of the flight, e.g. altitude change, speed change, and constant speed and altitude. In the initial climb and the final descent phases, the costs are determined by considering altitude changes at constant CAS (Calibrated Air Speed) or constant Mach number. CAS and Mach number are adjusted to minimize cost. The aerodynamic model used is the one proposed by Eurocontrol, which uses the BADA (Base of Aircraft Data) tables. This model is based on the total energy equation that determines the instantaneous fuel consumption. Calculations on each arc are done by solving a system of differential equations that systematically takes all costs into account. To compute the cost of an arc, we must know the time to go through it, which is generally unknown. To have well-posed boundary conditions, we use the horizontal displacement as the independent variable of the system of differential equations. We consider the velocity components of the wind in a 3D system of coordinates to compute the instantaneous ground speed of the aircraft. To consider the cost of time, we use the cost index. The cost of an arc depends on the aircraft mass at the beginning of this arc, and this mass depends on the path. As we consider all possible paths, the cost of an arc must be computed for each trajectory to which it belongs. For a long-distance flight, the number of arcs to be considered in the graph is large and therefore the cost of an arc is typically computed many times. Our algorithm computes the costs of one million arcs in seconds while having a high accuracy. The determination of the optimal trajectory can therefore be done in a short time. To get the optimal path, the mass of the aircraft at the departure point must also be optimal. It is therefore necessary to know the optimal amount of fuel for the journey. The aircraft mass is known only at the arrival point. This mass is the mass of the aircraft including passengers, cargo and reserve fuel mass. The optimal path is determined by calculating backwards, i.e. from the arrival point to the departure point. For the determination of the optimal trajectory, we use an elliptical grid that has focal points at the departure and arrival points. The use of this grid is essential for the construction of a direct and acyclic graph. We use the Bellman-Ford algorithm on a DAG to determine the shortest path. This algorithm is easy to implement and results in short computation times. Our algorithm computes an optimal trajectory with an optimal cost for each arc. Altitude changes are done optimally with respect to the mass of the aircraft and the cost of time. Our algorithm gives the mass, speed, altitude and total cost at any point of the trajectory as well as the optimal profiles of climb and descent. A prototype has been implemented in C. We made simulations of all types of possible arcs and of several complete trajectories to illustrate the behaviour of the algorithm.

Adaptive density trajectory cluster based on time and space distance

NASA Astrophysics Data System (ADS)

Liu, Fagui; Zhang, Zhijie

2017-10-01

There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

Trajectory Control of Rendezvous with Maneuver Target Spacecraft

NASA Technical Reports Server (NTRS)

Zhou, Zhinqiang

2012-01-01

In this paper, a nonlinear trajectory control algorithm of rendezvous with maneuvering target spacecraft is presented. The disturbance forces on the chaser and target spacecraft and the thrust forces on the chaser spacecraft are considered in the analysis. The control algorithm developed in this paper uses the relative distance and relative velocity between the target and chaser spacecraft as the inputs. A general formula of reference relative trajectory of the chaser spacecraft to the target spacecraft is developed and applied to four different proximity maneuvers, which are in-track circling, cross-track circling, in-track spiral rendezvous and cross-track spiral rendezvous. The closed-loop differential equations of the proximity relative motion with the control algorithm are derived. It is proven in the paper that the tracking errors between the commanded relative trajectory and the actual relative trajectory are bounded within a constant region determined by the control gains. The prediction of the tracking errors is obtained. Design examples are provided to show the implementation of the control algorithm. The simulation results show that the actual relative trajectory tracks the commanded relative trajectory tightly. The predicted tracking errors match those calculated in the simulation results. The control algorithm developed in this paper can also be applied to interception of maneuver target spacecraft and relative trajectory control of spacecraft formation flying.

Comparison of the Effects of Velocity and Range Triggers on Trajectory Dispersions for the Mars 2020 Mission

NASA Technical Reports Server (NTRS)

Dutta, Soumyo; Way, David W.

2017-01-01

Mars 2020, the next planned U.S. rover mission to land on Mars, is based on the design of the successful 2012 Mars Science Laboratory (MSL) mission. Mars 2020 retains most of the entry, descent, and landing (EDL) sequences of MSL, including the closed-loop entry guidance scheme based on the Apollo guidance algorithm. However, unlike MSL, Mars 2020 will trigger the parachute deployment and descent sequence on range trigger rather than the previously used velocity trigger. This difference will greatly reduce the landing ellipse sizes. Additionally, the relative contribution of each models to the total ellipse sizes have changed greatly due to the switch to range trigger. This paper considers the effect on trajectory dispersions due to changing the trigger schemes and the contributions of these various models to trajectory and EDL performance.

Treatment Planning and Image Guidance for Radiofrequency Ablations of Large Tumors

PubMed Central

Ren, Hongliang; Campos-Nanez, Enrique; Yaniv, Ziv; Banovac, Filip; Abeledo, Hernan; Hata, Nobuhiko; Cleary, Kevin

2014-01-01

This article addresses the two key challenges in computer-assisted percutaneous tumor ablation: planning multiple overlapping ablations for large tumors while avoiding critical structures, and executing the prescribed plan. Towards semi-automatic treatment planning for image-guided surgical interventions, we develop a systematic approach to the needle-based ablation placement task, ranging from pre-operative planning algorithms to an intra-operative execution platform. The planning system incorporates clinical constraints on ablations and trajectories using a multiple objective optimization formulation, which consists of optimal path selection and ablation coverage optimization based on integer programming. The system implementation is presented and validated in phantom studies and on an animal model. The presented system can potentially be further extended for other ablation techniques such as cryotherapy. PMID:24235279

Ares I-X Best Estimated Trajectory Analysis and Results

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Beck, Roger E.; Starr, Brett R.; Derry, Stephen D.; Brandon, Jay; Olds, Aaron D.

2011-01-01

The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air-data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.

Ares I-X Best Estimated Trajectory and Comparison with Pre-Flight Predictions

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Beck, Roger E.; Derry, Stephen D.; Brandon, Jay M.; Starr, Brett R.; Tartabini, Paul V.; Olds, Aaron D.

2011-01-01

The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air- data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.

Fast optimization of glide vehicle reentry trajectory based on genetic algorithm

NASA Astrophysics Data System (ADS)

Jia, Jun; Dong, Ruixing; Yuan, Xuejun; Wang, Chuangwei

2018-02-01

An optimization method of reentry trajectory based on genetic algorithm is presented to meet the need of reentry trajectory optimization for glide vehicle. The dynamic model for the glide vehicle during reentry period is established. Considering the constraints of heat flux, dynamic pressure, overload etc., the optimization of reentry trajectory is investigated by utilizing genetic algorithm. The simulation shows that the method presented by this paper is effective for the optimization of reentry trajectory of glide vehicle. The efficiency and speed of this method is comparative with the references. Optimization results meet all constraints, and the on-line fast optimization is potential by pre-processing the offline samples.

Search Problems in Mission Planning and Navigation of Autonomous Aircraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Krozel, James A.

1988-01-01

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

Machine Learning for Biological Trajectory Classification Applications

NASA Technical Reports Server (NTRS)

Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros

2002-01-01

Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

Trajectory data privacy protection based on differential privacy mechanism

NASA Astrophysics Data System (ADS)

Gu, Ke; Yang, Lihao; Liu, Yongzhi; Liao, Niandong

2018-05-01

In this paper, we propose a trajectory data privacy protection scheme based on differential privacy mechanism. In the proposed scheme, the algorithm first selects the protected points from the user’s trajectory data; secondly, the algorithm forms the polygon according to the protected points and the adjacent and high frequent accessed points that are selected from the accessing point database, then the algorithm calculates the polygon centroids; finally, the noises are added to the polygon centroids by the differential privacy method, and the polygon centroids replace the protected points, and then the algorithm constructs and issues the new trajectory data. The experiments show that the running time of the proposed algorithms is fast, the privacy protection of the scheme is effective and the data usability of the scheme is higher.

Planning and delivery of four-dimensional radiation therapy with multileaf collimators

NASA Astrophysics Data System (ADS)

McMahon, Ryan L.

This study is an investigation of the application of multileaf collimators (MLCs) to the treatment of moving anatomy with external beam radiation therapy. First, a method for delivering intensity modulated radiation therapy (IMRT) to moving tumors is presented. This method uses an MLC control algorithm that calculates appropriate MLC leaf speeds in response to feedback from real-time imaging. The algorithm does not require a priori knowledge of a tumor's motion, and is based on the concept of self-correcting DMLC leaf trajectories . This gives the algorithm the distinct advantage of allowing for correction of DMLC delivery errors without interrupting delivery. The algorithm is first tested for the case of one-dimensional (1D) rigid tumor motion in the beam's eye view (BEV). For this type of motion, it is shown that the real-time tracking algorithm results in more accurate deliveries, with respect to delivered intensity, than those which ignore motion altogether. This is followed by an appropriate extension of the algorithm to two-dimensional (2D) rigid motion in the BEV. For this type of motion, it is shown that the 2D real-time tracking algorithm results in improved accuracy (in the delivered intensity) in comparison to deliveries which ignore tumor motion or only account for tumor motion which is aligned with MLC leaf travel. Finally, a method is presented for designing DMLC leaf trajectories which deliver a specified intensity over a moving tumor without overexposing critical structures which exhibit motion patterns that differ from that of the tumor. In addition to avoiding overexposure of critical organs, the method can, in the case shown, produce deliveries that are superior to anything achievable using stationary anatomy. In this regard, the method represents a systematic way to include anatomical motion as a degree of freedom in the optimization of IMRT while producing treatment plans that are deliverable with currently available technology. These results, combined with those related to the real-time MLC tracking algorithm, show that an MLC is a promising tool to investigate for the delivery of four-dimensional radiation therapy.

Flight Deck Surface Trajectory-Based Operations

NASA Technical Reports Server (NTRS)

Foyle, David C.; Hooey, Becky L.; Bakowski, Deborah L.

2017-01-01

Surface Trajectory-Based Operations (STBO) is a future concept for surface operations where time requirements are incorporated into taxi operations to support surface planning and coordination. Pilot-in-the-loop flight deck simulations have been conducted to study flight deck displays algorithms to aid pilots in complying with the time requirements of time-based taxi operations (i.e., at discrete locations in 3 12 D operations or at all points along the route in 4DT operations). The results of these studies (conformance, time-of-arrival error, eye-tracking data, and safety ratings) are presented. Flight deck simulation work done in collaboration with DLR is described. Flight deck research issues in future auto-taxi operations are also introduced.

Adaptive Trajectory Prediction Algorithm for Climbing Flights

NASA Technical Reports Server (NTRS)

Schultz, Charles Alexander; Thipphavong, David P.; Erzberger, Heinz

2012-01-01

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Distributed autonomous systems: resource management, planning, and control algorithms

NASA Astrophysics Data System (ADS)

Smith, James F., III; Nguyen, ThanhVu H.

2005-05-01

Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

WE-AB-209-06: Dynamic Collimator Trajectory Algorithm for Use in VMAT Treatment Deliveries

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

MacDonald, L; Thomas, C; Syme, A

2016-06-15

Purpose: To develop advanced dynamic collimator positioning algorithms for optimal beam’s-eye-view (BEV) fitting of targets in VMAT procedures, including multiple metastases stereotactic radiosurgery procedures. Methods: A trajectory algorithm was developed, which can dynamically modify the angle of the collimator as a function of VMAT control point to provide optimized collimation of target volume(s). Central to this algorithm is a concept denoted “whitespace”, defined as area within the jaw-defined BEV field, outside of the PTV, and not shielded by the MLC when fit to the PTV. Calculating whitespace at all collimator angles and every control point, a two-dimensional topographical map depictingmore » the tightness-of-fit of the MLC was generated. A variety of novel searching algorithms identified a number of candidate trajectories of continuous collimator motion. Ranking these candidate trajectories according to their accrued whitespace value produced an optimal solution for navigation of this map. Results: All trajectories were normalized to minimum possible (i.e. calculated without consideration of collimator motion constraints) accrued whitespace. On an acoustic neuroma case, a random walk algorithm generated a trajectory with 151% whitespace; random walk including a mandatory anchor point improved this to 148%; gradient search produced a trajectory with 137%; and bi-directional gradient search generated a trajectory with 130% whitespace. For comparison, a fixed collimator angle of 30° and 330° accumulated 272% and 228% of whitespace, respectively. The algorithm was tested on a clinical case with two metastases (single isocentre) and identified collimator angles that allow for simultaneous irradiation of the PTVs while minimizing normal tissue irradiation. Conclusion: Dynamic collimator trajectories have the potential to improve VMAT deliveries through increased efficiency and reduced normal tissue dose, especially in treatment of multiple cranial metastases, without significant safety concerns that hinder immediate clinical implementation.« less

Region of Interest Imaging for a General Trajectory with the Rebinned BPF Algorithm*

PubMed Central

Bian, Junguo; Xia, Dan; Sidky, Emil Y; Pan, Xiaochuan

2010-01-01

The back-projection-filtration (BPF) algorithm has been applied to image reconstruction for cone-beam configurations with general source trajectories. The BPF algorithm can reconstruct 3-D region-of-interest (ROI) images from data containing truncations. However, like many other existing algorithms for cone-beam configurations, the BPF algorithm involves a back-projection with a spatially varying weighting factor, which can result in the non-uniform noise levels in reconstructed images and increased computation time. In this work, we propose a BPF algorithm to eliminate the spatially varying weighting factor by using a rebinned geometry for a general scanning trajectory. This proposed BPF algorithm has an improved noise property, while retaining the advantages of the original BPF algorithm such as minimum data requirement. PMID:20617122

Region of Interest Imaging for a General Trajectory with the Rebinned BPF Algorithm.

PubMed

Bian, Junguo; Xia, Dan; Sidky, Emil Y; Pan, Xiaochuan

2010-02-01

The back-projection-filtration (BPF) algorithm has been applied to image reconstruction for cone-beam configurations with general source trajectories. The BPF algorithm can reconstruct 3-D region-of-interest (ROI) images from data containing truncations. However, like many other existing algorithms for cone-beam configurations, the BPF algorithm involves a back-projection with a spatially varying weighting factor, which can result in the non-uniform noise levels in reconstructed images and increased computation time. In this work, we propose a BPF algorithm to eliminate the spatially varying weighting factor by using a rebinned geometry for a general scanning trajectory. This proposed BPF algorithm has an improved noise property, while retaining the advantages of the original BPF algorithm such as minimum data requirement.

Sampling-based real-time motion planning under state uncertainty for autonomous micro-aerial vehicles in GPS-denied environments.

PubMed

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-11-18

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints.

Sampling-Based Real-Time Motion Planning under State Uncertainty for Autonomous Micro-Aerial Vehicles in GPS-Denied Environments

PubMed Central

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-01-01

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints. PMID:25412217

Failure tolerance strategy of space manipulator for large load carrying tasks

NASA Astrophysics Data System (ADS)

Chen, Gang; Yuan, Bonan; Jia, Qingxuan; Sun, Hanxu; Guo, Wen

2018-07-01

During the execution of large load carrying tasks in long term service, there is a notable risk of space manipulator suffering from locked-joint failure, thus space manipulator should be with enough failure tolerance performance. A research on evaluating failure tolerance performance and re-planning feasible task trajectory for space manipulator performing large load carrying tasks is conducted in this paper. The effects of locked-joint failure on critical performance(reachability and load carrying capacity) of space manipulator are analyzed at first. According to the requirements of load carrying tasks, we further propose a new concept of failure tolerance workspace with load carrying capacity(FTWLCC) to evaluate failure tolerance performance, and improve the classic A* algorithm to search the feasible task trajectory. Through the normalized FTWLCC and the improved A* algorithm, the reachability and load carrying capacity of the degraded space manipulator are evaluated, and the reachable and capable trajectory can be obtained. The establishment of FTWLCC provides a novel idea that combines mathematical statistics with failure tolerance performance to illustrate the distribution of load carrying capacity in three-dimensional space, so multiple performance indices can be analyzed simultaneously and visually. And the full consideration of all possible failure situations and motion states makes FTWLCC and improved A* algorithm be universal and effective enough to be appropriate for random joint failure and variety of requirement of large load carrying tasks, so they can be extended to other types of manipulators.

Decomposition Algorithm for Global Reachability Analysis on a Time-Varying Graph with an Application to Planetary Exploration

NASA Technical Reports Server (NTRS)

Kuwata, Yoshiaki; Blackmore, Lars; Wolf, Michael; Fathpour, Nanaz; Newman, Claire; Elfes, Alberto

2009-01-01

Hot air (Montgolfiere) balloons represent a promising vehicle system for possible future exploration of planets and moons with thick atmospheres such as Venus and Titan. To go to a desired location, this vehicle can primarily use the horizontal wind that varies with altitude, with a small help of its own actuation. A main challenge is how to plan such trajectory in a highly nonlinear and time-varying wind field. This paper poses this trajectory planning as a graph search on the space-time grid and addresses its computational aspects. When capturing various time scales involved in the wind field over the duration of long exploration mission, the size of the graph becomes excessively large. We show that the adjacency matrix of the graph is block-triangular, and by exploiting this structure, we decompose the large planning problem into several smaller subproblems, whose memory requirement stays almost constant as the problem size grows. The approach is demonstrated on a global reachability analysis of a possible Titan mission scenario.

Guidance control of small UAV with energy and maneuverability limitations for a search and coverage mission

NASA Astrophysics Data System (ADS)

Gramajo, German G.

This thesis presents an algorithm for a search and coverage mission that has increased autonomy in generating an ideal trajectory while explicitly considering the available energy in the optimization. Further, current algorithms used to generate trajectories depend on the operator providing a discrete set of turning rate requirements to obtain an optimal solution. This work proposes an additional modification to the algorithm so that it optimizes the trajectory for a range of turning rates instead of a discrete set of turning rates. This thesis conducts an evaluation of the algorithm with variation in turn duration, entry-heading angle, and entry point. Comparative studies of the algorithm with existing method indicates improved autonomy in choosing the optimization parameters while producing trajectories with better coverage area and closer final distance to the desired terminal point.

Using external sensors in solution of SLAM task

NASA Astrophysics Data System (ADS)

Provkov, V. S.; Starodubtsev, I. S.

2018-05-01

This article describes the algorithms of spatial orientation of SLAM, PTAM and their positive and negative sides. Based on the SLAM method, a method that uses an RGBD camera and additional sensors was developed: an accelerometer, a gyroscope, and a magnetometer. The investigated orientation methods have their advantages when moving along a straight trajectory or when rotating a moving platform. As a result of experiments and a weighted linear combination of the positions obtained from data of the RGBD camera and the nine-axis sensor, it became possible to improve the accuracy of the original algorithm even using a constant as a weight function. In the future, it is planned to develop an algorithm for the dynamic construction of a weight function, as a result of which an increase in the accuracy of the algorithm is expected.

A manipulative instrument with simultaneous gesture and end-effector trajectory planning and controlling

NASA Astrophysics Data System (ADS)

Lin, Hsien-I.; Nguyen, Xuan-Anh

2017-05-01

To operate a redundant manipulator to accomplish the end-effector trajectory planning and simultaneously control its gesture in online programming, incorporating the human motion is a useful and flexible option. This paper focuses on a manipulative instrument that can simultaneously control its arm gesture and end-effector trajectory via human teleoperation. The instrument can be classified by two parts; first, for the human motion capture and data processing, marker systems are proposed to capture human gesture. Second, the manipulator kinematics control is implemented by an augmented multi-tasking method, and forward and backward reaching inverse kinematics, respectively. Especially, the local-solution and divergence problems of a multi-tasking method are resolved by the proposed augmented multi-tasking method. Computer simulations and experiments with a 7-DOF (degree of freedom) redundant manipulator were used to validate the proposed method. Comparison among the single-tasking, original multi-tasking, and augmented multi-tasking algorithms were performed and the result showed that the proposed augmented method had a good end-effector position accuracy and the most similar gesture to the human gesture. Additionally, the experimental results showed that the proposed instrument was realized online.

Automated Conflict Resolution For Air Traffic Control

NASA Technical Reports Server (NTRS)

Erzberger, Heinz

2005-01-01

The ability to detect and resolve conflicts automatically is considered to be an essential requirement for the next generation air traffic control system. While systems for automated conflict detection have been used operationally by controllers for more than 20 years, automated resolution systems have so far not reached the level of maturity required for operational deployment. Analytical models and algorithms for automated resolution have been traffic conditions to demonstrate that they can handle the complete spectrum of conflict situations encountered in actual operations. The resolution algorithm described in this paper was formulated to meet the performance requirements of the Automated Airspace Concept (AAC). The AAC, which was described in a recent paper [1], is a candidate for the next generation air traffic control system. The AAC's performance objectives are to increase safety and airspace capacity and to accommodate user preferences in flight operations to the greatest extent possible. In the AAC, resolution trajectories are generated by an automation system on the ground and sent to the aircraft autonomously via data link .The algorithm generating the trajectories must take into account the performance characteristics of the aircraft, the route structure of the airway system, and be capable of resolving all types of conflicts for properly equipped aircraft without requiring supervision and approval by a controller. Furthermore, the resolution trajectories should be compatible with the clearances, vectors and flight plan amendments that controllers customarily issue to pilots in resolving conflicts. The algorithm described herein, although formulated specifically to meet the needs of the AAC, provides a generic engine for resolving conflicts. Thus, it can be incorporated into any operational concept that requires a method for automated resolution, including concepts for autonomous air to air resolution.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments.

PubMed

Wu, Paul P-Y; Campbell, Duncan; Merz, Torsten

2011-06-01

This paper presents Multi-Step A∗ (MSA∗), a search algorithm based on A∗ for multi-objective 4-D vehicle motion planning (three spatial and one time dimensions). The research is principally motivated by the need for offline and online motion planning for autonomous unmanned aerial vehicles (UAVs). For UAVs operating in large dynamic uncertain 4-D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and a grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles, and the rules of the air. It is shown that MSA∗ finds a cost optimal solution using variable length, angle, and velocity trajectory segments. These segments are approximated with a grid-based cell sequence that provides an inherent tolerance to uncertainty. The computational efficiency is achieved by using variable successor operators to create a multiresolution memory-efficient lattice sampling structure. The simulation studies on the UAV flight planning problem show that MSA∗ meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of a vector neighborhood-based A∗.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

Algorithm for fuel conservative horizontal capture trajectories

NASA Technical Reports Server (NTRS)

Neuman, F.; Erzberger, H.

1981-01-01

A real time algorithm for computing constant altitude fuel-conservative approach trajectories for aircraft is described. The characteristics of the trajectory computed were chosen to approximate the extremal trajectories obtained from the optimal control solution to the problem and showed a fuel difference of only 0.5 to 2 percent for the real time algorithm in favor of the extremals. The trajectories may start at any initial position, heading, and speed and end at any other final position, heading, and speed. They consist of straight lines and a series of circular arcs of varying radius to approximate constant bank-angle decelerating turns. Throttle control is maximum thrust, nominal thrust, or zero thrust. Bank-angle control is either zero or aproximately 30 deg.

Spiral trajectory design: a flexible numerical algorithm and base analytical equations.

PubMed

Pipe, James G; Zwart, Nicholas R

2014-01-01

Spiral-based trajectories for magnetic resonance imaging can be advantageous, but are often cumbersome to design or create. This work presents a flexible numerical algorithm for designing trajectories based on explicit definition of radial undersampling, and also gives several analytical expressions for charactering the base (critically sampled) class of these trajectories. Expressions for the gradient waveform, based on slew and amplitude limits, are developed such that a desired pitch in the spiral k-space trajectory is followed. The source code for this algorithm, written in C, is publicly available. Analytical expressions approximating the spiral trajectory (ignoring the radial component) are given to characterize measurement time, gradient heating, maximum gradient amplitude, and off-resonance phase for slew-limited and gradient amplitude-limited cases. Several numerically calculated trajectories are illustrated, and base Archimedean spirals are compared with analytically obtained results. Several different waveforms illustrate that the desired slew and amplitude limits are reached, as are the desired undersampling patterns, using the numerical method. For base Archimedean spirals, the results of the numerical and analytical approaches are in good agreement. A versatile numerical algorithm was developed, and was written in publicly available code. Approximate analytical formulas are given that help characterize spiral trajectories. Copyright © 2013 Wiley Periodicals, Inc.

Detecting and Jamming Dynamic Communication Networks in Anti-Access Environments

DTIC Science & Technology

2011-03-01

P.M. Pardalos, Y. Ye. and C.W. Commander (eds) V. Boginski. Sensors: Theory , Algorithms, and Applications. Springer, to appear in 2009. [21] Joseph C...Sumeetpal S. Singh. Nikolaos Kantas , Ba-Ngu Vo, Arnaud Doucet, and Robin J. Evans. Simulation-based optimal sensor scheduling with application to...observer trajectory planning. Aotomatica, 43(5):817-830, 2007. [27] Anthony Man-Cho So and Yinyu Ye. Theory of semidefinite programming for sensor network

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Fourth Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2013-01-01

This paper presents an overview of the fourth major revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of-arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. Revisions to this algorithm were based on a change to the expected operational environment.

Guidance and control of swarms of spacecraft

NASA Astrophysics Data System (ADS)

Morgan, Daniel James

There has been considerable interest in formation flying spacecraft due to their potential to perform certain tasks at a cheaper cost than monolithic spacecraft. Formation flying enables the use of smaller, cheaper spacecraft that distribute the risk of the mission. Recently, the ideas of formation flying have been extended to spacecraft swarms made up of hundreds to thousands of 100-gram-class spacecraft known as femtosatellites. The large number of spacecraft and limited capabilities of each individual spacecraft present a significant challenge in guidance, navigation, and control. This dissertation deals with the guidance and control algorithms required to enable the flight of spacecraft swarms. The algorithms developed in this dissertation are focused on achieving two main goals: swarm keeping and swarm reconfiguration. The objectives of swarm keeping are to maintain bounded relative distances between spacecraft, prevent collisions between spacecraft, and minimize the propellant used by each spacecraft. Swarm reconfiguration requires the transfer of the swarm to a specific shape. Like with swarm keeping, minimizing the propellant used and preventing collisions are the main objectives. Additionally, the algorithms required for swarm keeping and swarm reconfiguration should be decentralized with respect to communication and computation so that they can be implemented on femtosats, which have limited hardware capabilities. The algorithms developed in this dissertation are concerned with swarms located in low Earth orbit. In these orbits, Earth oblateness and atmospheric drag have a significant effect on the relative motion of the swarm. The complicated dynamic environment of low Earth orbits further complicates the swarm-keeping and swarm-reconfiguration problems. To better develop and test these algorithms, a nonlinear, relative dynamic model with J2 and drag perturbations is developed. This model is used throughout this dissertation to validate the algorithms using computer simulations. The swarm-keeping problem can be solved by placing the spacecraft on J2-invariant relative orbits, which prevent collisions and minimize the drift of the swarm over hundreds of orbits using a single burn. These orbits are achieved by energy matching the spacecraft to the reference orbit. Additionally, these conditions can be repeatedly applied to minimize the drift of the swarm when atmospheric drag has a large effect (orbits with an altitude under 500 km). The swarm reconfiguration is achieved using two steps: trajectory optimization and assignment. The trajectory optimization problem can be written as a nonlinear, optimal control problem. This optimal control problem is discretized, decoupled, and convexified so that the individual femtosats can efficiently solve the optimization. Sequential convex programming is used to generate the control sequences and trajectories required to safely and efficiently transfer a spacecraft from one position to another. The sequence of trajectories is shown to converge to a Karush-Kuhn-Tucker point of the nonconvex problem. In the case where many of the spacecraft are interchangeable, a variable-swarm, distributed auction algorithm is used to determine the assignment of spacecraft to target positions. This auction algorithm requires only local communication and all of the bidding parameters are stored locally. The assignment generated using this auction algorithm is shown to be near optimal and to converge in a finite number of bids. Additionally, the bidding process is used to modify the number of targets used in the assignment so that the reconfiguration can be achieved even when there is a disconnected communication network or a significant loss of agents. Once the assignment is achieved, the trajectory optimization can be run using the terminal positions determined by the auction algorithm. To implement these algorithms in real time a model predictive control formulation is used. Model predictive control uses a finite horizon to apply the most up-to-date control sequence while simultaneously calculating a new assignment and trajectory based on updated state information. Using a finite horizon allows collisions to only be considered between spacecraft that are near each other at the current time. This relaxes the all-to-all communication assumption so that only neighboring agents need to communicate. Experimental validation is done using the formation flying testbed. The swarm-reconfiguration algorithms are tested using multiple quadrotors. Experiments have been performed using sequential convex programming for offline trajectory planning, model predictive control and sequential convex programming for real-time trajectory generation, and the variable-swarm, distributed auction algorithm for optimal assignment. These experiments show that the swarm-reconfiguration algorithms can be implemented in real time using actual hardware. In general, this dissertation presents guidance and control algorithms that maintain and reconfigure swarms of spacecraft while maintaining the shape of the swarm, preventing collisions between the spacecraft, and minimizing the amount of propellant used.

Towards a Formal Semantics of Flight Plans and Trajectories

NASA Technical Reports Server (NTRS)

Hagen, George E.; Butler, Ricky W.

2014-01-01

In the National Airspace System, ight plans are often used only as a planning tool by air trac controllers and aircraft operators. These plans are implicitly translated into trajectories by the pilot or by the ight management system, and subsequently own by the aircraft. This translation process inevitably introduces di erences between the plan and the trajectory. However, given the current intended usage, exact correspondence between the plan and the trajectory is not needed. To achieve greater capacity and eciency, future air trac management concepts are being designed around the use of trajectories where predictability is extremely important. In this paper, a mathematical relationship between ight plans and trajectories is explored with the goal of making feasible, highly accurate predictions of future positions and velocities of aircraft. The goal here is to describe, in mathematically precise detail, a formal language of trajectories, whereby all receivers of the trajectory information will be able to arrive at precisely the same trajectory predication and to do this without having aircraft broadcast a large amount of data. Although even a four-dimensional ight plan is simple in structure, this paper will show that it is inherently ambiguous and will explore these issues in detail. In e ect, we propose that a rigorous semantics for ight plans can be developed and this will serve as an important stepping stone towards trajectory-based operations in the National Airspace System.

Techniques for shuttle trajectory optimization

NASA Technical Reports Server (NTRS)

Edge, E. R.; Shieh, C. J.; Powers, W. F.

1973-01-01

The application of recently developed function-space Davidon-type techniques to the shuttle ascent trajectory optimization problem is discussed along with an investigation of the recently developed PRAXIS algorithm for parameter optimization. At the outset of this analysis, the major deficiency of the function-space algorithms was their potential storage problems. Since most previous analyses of the methods were with relatively low-dimension problems, no storage problems were encountered. However, in shuttle trajectory optimization, storage is a problem, and this problem was handled efficiently. Topics discussed include: the shuttle ascent model and the development of the particular optimization equations; the function-space algorithms; the operation of the algorithm and typical simulations; variable final-time problem considerations; and a modification of Powell's algorithm.

Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

NASA Astrophysics Data System (ADS)

Goerres, J.; Uneri, A.; Jacobson, M.; Ramsay, B.; De Silva, T.; Ketcha, M.; Han, R.; Manbachi, A.; Vogt, S.; Kleinszig, G.; Wolinsky, J.-P.; Osgood, G.; Siewerdsen, J. H.

2017-12-01

Percutaneous pelvic screw placement is challenging due to narrow bone corridors surrounded by vulnerable structures and difficult visual interpretation of complex anatomical shapes in 2D x-ray projection images. To address these challenges, a system for planning, guidance, and quality assurance (QA) is presented, providing functionality analogous to surgical navigation, but based on robust 3D-2D image registration techniques using fluoroscopy images already acquired in routine workflow. Two novel aspects of the system are investigated: automatic planning of pelvic screw trajectories and the ability to account for deformation of surgical devices (K-wire deflection). Atlas-based registration is used to calculate a patient-specific plan of screw trajectories in preoperative CT. 3D-2D registration aligns the patient to CT within the projective geometry of intraoperative fluoroscopy. Deformable known-component registration (dKC-Reg) localizes the surgical device, and the combination of plan and device location is used to provide guidance and QA. A leave-one-out analysis evaluated the accuracy of automatic planning, and a cadaver experiment compared the accuracy of dKC-Reg to rigid approaches (e.g. optical tracking). Surgical plans conformed within the bone cortex by 3-4 mm for the narrowest corridor (superior pubic ramus) and  >5 mm for the widest corridor (tear drop). The dKC-Reg algorithm localized the K-wire tip within 1.1 mm and 1.4° and was consistently more accurate than rigid-body tracking (errors up to 9 mm). The system was shown to automatically compute reliable screw trajectories and accurately localize deformed surgical devices (K-wires). Such capability could improve guidance and QA in orthopaedic surgery, where workflow is impeded by manual planning, conventional tool trackers add complexity and cost, rigid tool assumptions are often inaccurate, and qualitative interpretation of complex anatomy from 2D projections is prone to trial-and-error with extended fluoroscopy time.

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

NASA Technical Reports Server (NTRS)

Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan

2014-01-01

Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance

Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

NASA Technical Reports Server (NTRS)

Colby, Mitchell; Knudson, Matthew D.; Tumer, Kagan

2014-01-01

Dynamic environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal paths through these environments. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially with the number of agents in the system. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance.

Trajectory Modulated Arc Therapy: A Fully Dynamic Delivery With Synchronized Couch and Gantry Motion Significantly Improves Dosimetric Indices Correlated With Poor Cosmesis in Accelerated Partial Breast Irradiation

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

Liang, Jieming; Atwood, Todd; Eyben, Rie von

2015-08-01

Purpose: To develop planning and delivery capabilities for linear accelerator–based nonisocentric trajectory modulated arc therapy (TMAT) and to evaluate the benefit of TMAT for accelerated partial breast irradiation (APBI) with the patient in prone position. Methods and Materials: An optimization algorithm for volumetrically modulated arc therapy (VMAT) was generalized to allow for user-defined nonisocentric TMAT trajectories combining couch rotations and translations. After optimization, XML scripts were automatically generated to program and subsequently deliver the TMAT plans. For 10 breast patients in the prone position, TMAT and 6-field noncoplanar intensity modulated radiation therapy (IMRT) plans were generated under equivalent objectives andmore » constraints. These plans were compared with regard to whole breast tissue volume receiving more than 100%, 80%, 50%, and 20% of the prescription dose. Results: For TMAT APBI, nonisocentric collision-free horizontal arcs with large angular span (251.5 ± 7.9°) were optimized and delivered with delivery time of ∼4.5 minutes. Percentage changes of whole breast tissue volume receiving more than 100%, 80%, 50%, and 20% of the prescription dose for TMAT relative to IMRT were −10.81% ± 6.91%, −27.81% ± 7.39%, −14.82% ± 9.67%, and 39.40% ± 10.53% (P≤.01). Conclusions: This is a first demonstration of end-to-end planning and delivery implementation of a fully dynamic APBI TMAT. Compared with IMRT, TMAT resulted in marked reduction of the breast tissue volume irradiated at high doses.« less

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Trajectory NG: portable, compressed, general molecular dynamics trajectories.

PubMed

Spångberg, Daniel; Larsson, Daniel S D; van der Spoel, David

2011-10-01

We present general algorithms for the compression of molecular dynamics trajectories. The standard ways to store MD trajectories as text or as raw binary floating point numbers result in very large files when efficient simulation programs are used on supercomputers. Our algorithms are based on the observation that differences in atomic coordinates/velocities, in either time or space, are generally smaller than the absolute values of the coordinates/velocities. Also, it is often possible to store values at a lower precision. We apply several compression schemes to compress the resulting differences further. The most efficient algorithms developed here use a block sorting algorithm in combination with Huffman coding. Depending on the frequency of storage of frames in the trajectory, either space, time, or combinations of space and time differences are usually the most efficient. We compare the efficiency of our algorithms with each other and with other algorithms present in the literature for various systems: liquid argon, water, a virus capsid solvated in 15 mM aqueous NaCl, and solid magnesium oxide. We perform tests to determine how much precision is necessary to obtain accurate structural and dynamic properties, as well as benchmark a parallelized implementation of the algorithms. We obtain compression ratios (compared to single precision floating point) of 1:3.3-1:35 depending on the frequency of storage of frames and the system studied.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Third Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2012-01-01

This paper presents an overview of the third major revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 11 (ASTAR11). This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required time-of-arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft.

Spatial-temporal travel pattern mining using massive taxi trajectory data

NASA Astrophysics Data System (ADS)

Zheng, Linjiang; Xia, Dong; Zhao, Xin; Tan, Longyou; Li, Hang; Chen, Li; Liu, Weining

2018-07-01

Deep understanding of residents' travel patterns would provide helpful insights into the mechanisms of many socioeconomic phenomena. With the rapid development of location-aware computing technologies, researchers have easy access to large quantities of travel data. As an important data source, taxi trajectory data are featured by their high quality, good continuity and wide distribution, making it suitable for travel pattern mining. In this paper, we use taxi trajectory data to study spatial-temporal characterization of urban residents' travel patterns from two aspects: attractive areas and hot paths. Firstly, a framework of trajectory preprocessing, including data cleaning and extracting the taxi passenger pick-up/drop-off points, is presented to reduce the noise and redundancy in raw trajectory data. Then, a grid density based clustering algorithm is proposed to discover travel attractive areas in different periods of a day. On this basis, we put forward a spatial-temporal trajectory clustering method to discover hot paths among travel attractive areas. Compared with previous algorithms, which only consider the spatial constraint between trajectories, temporal constraint is also considered in our method. Through the experiments, we discuss how to determine the optimal parameters of the two clustering algorithms and verify the effectiveness of the algorithms using real data. Furthermore, we analyze spatial-temporal characterization of Chongqing residents' travel pattern.

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

Liang, J; Kim, S; Hristov, D

Purpose: To assess the potential benefit of trajectory modulated arc therapy (TMAT) for treatments of small benign intracranial tumor, pituitary adenoma. Methods: A TMAT planning platform that incorporates complex source motion trajectory involving synchronized gantry rotation with translational and rotational couch movement was used for the study. The platform couples an interactive trajectory generation tool with a VMAT algorithm that performs multi-resolution, progressive sampling MLC optimization on a user-designed trajectory. A continuous couch rotation of 160° angular span with ±20° mini gantry arcs was used to emulate a non-coplanar horizontal arc-like trajectory. Compared to conventional non-coplanar gantry arcs (60°-100° gantrymore » rotation with couch kicks), TMAT limited the unnecessary low to medium dose spread in the anterior and posterior directions, where primary OARs (e.g., brainstem, optic chiasm, optic nerves, and lens) are in close proximity to the targeted pituitary tumor volume. For 5 standard fractionation pituitary adenoma cases (50.4Gy/28fractions), TMAT and non-coplanar VMAT plans were generated and compared under equivalent objectives/constraints. TMAT delivery was implemented and demonstrated on Varian TrueBeam via XML scripts. Results: Both techniques showed good target coverage while OARs were able to meet the constraints on QUANTEC guidelines. Notably, TMAT decreased the dose deposition in the anterior-to-posterior direction surrounding PTV. TMAT significantly reduced the mean doses on brainstem, optic nerves, eyes and lens by 47.29%±13.17%, 28.51%±8.68%, 80.82%±8.71% and 65.38%±19.99% compared with VMAT, all p≤0.01. Percentage reductions of maximum point dose in eyes and lens were 75.68%±10.30% and 70.72%±18.62% respectively for TMAT versus VMAT, all p≤0.01. A representative isocentric TMAT pituitary plan was delivered via an XML script with 200 control points and 282 MUs. Conclusion: Deliverable TMAT plans were achieved in developer mode in TrueBeam. TMAT was shown to be superior for pituitary adenoma irradiation in terms of OARs sparing.« less

On the analytic and numeric optimisation of airplane trajectories under real atmospheric conditions

NASA Astrophysics Data System (ADS)

Gonzalo, J.; Domínguez, D.; López, D.

2014-12-01

From the beginning of aviation era, economic constraints have forced operators to continuously improve the planning of the flights. The revenue is proportional to the cost per flight and the airspace occupancy. Many methods, the first started in the middle of last century, have explore analytical, numerical and artificial intelligence resources to reach the optimal flight planning. In parallel, advances in meteorology and communications allow an almost real-time knowledge of the atmospheric conditions and a reliable, error-bounded forecast for the near future. Thus, apart from weather risks to be avoided, airplanes can dynamically adapt their trajectories to minimise their costs. International regulators are aware about these capabilities, so it is reasonable to envisage some changes to allow this dynamic planning negotiation to soon become operational. Moreover, current unmanned airplanes, very popular and often small, suffer the impact of winds and other weather conditions in form of dramatic changes in their performance. The present paper reviews analytic and numeric solutions for typical trajectory planning problems. Analytic methods are those trying to solve the problem using the Pontryagin principle, where influence parameters are added to state variables to form a split condition differential equation problem. The system can be solved numerically -indirect optimisation- or using parameterised functions -direct optimisation-. On the other hand, numerical methods are based on Bellman's dynamic programming (or Dijkstra algorithms), where the fact that two optimal trajectories can be concatenated to form a new optimal one if the joint point is demonstrated to belong to the final optimal solution. There is no a-priori conditions for the best method. Traditionally, analytic has been more employed for continuous problems whereas numeric for discrete ones. In the current problem, airplane behaviour is defined by continuous equations, while wind fields are given in a discrete grid at certain time intervals. The research demonstrates advantages and disadvantages of each method as well as performance figures of the solutions found for typical flight conditions under static and dynamic atmospheres. This provides significant parameters to be used in the selection of solvers for optimal trajectories.

A manned maneuvering unit proximity operations planning and flight guidance display and control system

NASA Technical Reports Server (NTRS)

Gershzohn, Gary R.; Sirko, Robert J.; Zimmerman, K.; Jones, A. D.

1990-01-01

This task concerns the design, development, testing, and evaluation of a new proximity operations planning and flight guidance display and control system for manned space operations. A forecast, derivative manned maneuvering unit (MMU) was identified as a candidate for the application of a color, highway-in-the-sky display format for the presentation of flight guidance information. A silicon graphics 4D/20-based simulation is being developed to design and test display formats and operations concepts. The simulation includes the following: (1) real-time color graphics generation to provide realistic, dynamic flight guidance displays and control characteristics; (2) real-time graphics generation of spacecraft trajectories; (3) MMU flight dynamics and control characteristics; (4) control algorithms for rotational and translational hand controllers; (5) orbital mechanics effects for rendezvous and chase spacecraft; (6) inclusion of appropriate navigation aids; and (7) measurement of subject performance. The flight planning system under development provides for: (1) selection of appropriate operational modes, including minimum cost, optimum cost, minimum time, and specified ETA; (2) automatic calculation of rendezvous trajectories, en route times, and fuel requirements; (3) and provisions for manual override. Man/machine function allocations in planning and en route flight segments are being evaluated. Planning and en route data are presented on one screen composed of two windows: (1) a map display presenting a view perpendicular to the orbital plane, depicting flight planning trajectory and time data attitude display presenting attitude and course data for use en route; and (2) an attitude display presenting local vertical-local horizontal attitude data superimposed on a highway-in-the-sky or flight channel representation of the flight planned course. Both display formats are presented while the MMU is en route. In addition to these displays, several original display elements are being developed, including a 3DOF flight detector for attitude commanding, a different flight detector for translation commands, and a pictorial representation of velocity deviations.

A Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2007-01-01

This document describes an algorithm for the generation of a four dimensional aircraft trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival Route (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. Wind data at each waypoint are also inputs into this algorithm. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint.

TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy

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

Fix, MK; Frei, D; Volken, W

2016-06-15

Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, themore » fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.« less

Combing VFH with bezier for motion planning of an autonomous vehicle

NASA Astrophysics Data System (ADS)

Ye, Feng; Yang, Jing; Ma, Chao; Rong, Haijun

2017-08-01

Vector Field Histogram (VFH) is a method for mobile robot obstacle avoidance. However, due to the nonholonomic constraints of the vehicle, the algorithm is seldom applied to autonomous vehicles. Especially when we expect the vehicle to reach target location in a certain direction, the algorithm is often unsatisfactory. Fortunately, the Bezier Curve is defined by the states of the starting point and the target point. We can use this feature to make the vehicle in the expected direction. Therefore, we propose an algorithm to combine the Bezier Curve with the VFH algorithm, to search for the collision-free states with the VFH search method, and to select the optimal trajectory point with the Bezier Curve as the reference line. This means that we will improve the cost function in the VFH algorithm by comparing the distance between candidate directions and reference line. Finally, select the closest direction to the reference line to be the optimal motion direction.

Integration of Visual and Joint Information to Enable Linear Reaching Motions

NASA Astrophysics Data System (ADS)

Eberle, Henry; Nasuto, Slawomir J.; Hayashi, Yoshikatsu

2017-01-01

A new dynamics-driven control law was developed for a robot arm, based on the feedback control law which uses the linear transformation directly from work space to joint space. This was validated using a simulation of a two-joint planar robot arm and an optimisation algorithm was used to find the optimum matrix to generate straight trajectories of the end-effector in the work space. We found that this linear matrix can be decomposed into the rotation matrix representing the orientation of the goal direction and the joint relation matrix (MJRM) representing the joint response to errors in the Cartesian work space. The decomposition of the linear matrix indicates the separation of path planning in terms of the direction of the reaching motion and the synergies of joint coordination. Once the MJRM is numerically obtained, the feedfoward planning of reaching direction allows us to provide asymptotically stable, linear trajectories in the entire work space through rotational transformation, completely avoiding the use of inverse kinematics. Our dynamics-driven control law suggests an interesting framework for interpreting human reaching motion control alternative to the dominant inverse method based explanations, avoiding expensive computation of the inverse kinematics and the point-to-point control along the desired trajectories.

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

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

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE PAGES

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

2017-01-01

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

A Revised Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2010-01-01

This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates descent Mach values that are different from the cruise Mach values. Wind data at each waypoint are also inputs into this algorithm. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint.

Investigation of BPF algorithm in cone-beam CT with 2D general trajectories.

PubMed

Zou, Jing; Gui, Jianbao; Rong, Junyan; Hu, Zhanli; Zhang, Qiyang; Xia, Dan

2012-01-01

A mathematical derivation was conducted to illustrate that exact 3D image reconstruction could be achieved for z-homogeneous phantoms from data acquired with 2D general trajectories using the back projection filtration (BPF) algorithm. The conclusion was verified by computer simulation and experimental result with a circular scanning trajectory. Furthermore, the effect of the non-uniform degree along z-axis of the phantoms on the accuracy of the 3D reconstruction by BPF algorithm was investigated by numerical simulation with a gradual-phantom and a disk-phantom. The preliminary result showed that the performance of BPF algorithm improved with the z-axis homogeneity of the scanned object.

Fast Optimization for Aircraft Descent and Approach Trajectory

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry G.; Schuet, Stefan; Brenton, J.; Timucin, Dogan; Smith, David; Kaneshige, John

2017-01-01

We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.

A unified motion planning approach for redundant and non-redundant manipulators with actuator constraints. Ph.D. Thesis Final Report

NASA Technical Reports Server (NTRS)

Chung, Ching-Luan

1990-01-01

The term trajectory planning has been used to refer to the process of determining the time history of joint trajectory of each joint variable corresponding to a specified trajectory of the end effector. The trajectory planning problem was solved as a purely kinematic problem. The drawback is that there is no guarantee that the actuators can deliver the effort necessary to track the planned trajectory. To overcome this limitation, a motion planning approach which addresses the kinematics, dynamics, and feedback control of a manipulator in a unified framework was developed. Actuator constraints are taken into account explicitly and a priori in the synthesis of the feedback control law. Therefore the result of applying the motion planning approach described is not only the determination of the entire set of joint trajectories but also a complete specification of the feedback control strategy which would yield these joint trajectories without violating actuator constraints. The effectiveness of the unified motion planning approach is demonstrated on two problems which are of practical interest in manipulator robotics.

An Adaptive Nonlinear Aircraft Maneuvering Envelope Estimation Approach for Online Applications

NASA Technical Reports Server (NTRS)

Schuet, Stefan R.; Lombaerts, Thomas Jan; Acosta, Diana; Wheeler, Kevin; Kaneshige, John

2014-01-01

A nonlinear aircraft model is presented and used to develop an overall unified robust and adaptive approach to passive trim and maneuverability envelope estimation with uncertainty quantification. The concept of time scale separation makes this method suitable for the online characterization of altered safe maneuvering limitations after impairment. The results can be used to provide pilot feedback and/or be combined with flight planning, trajectory generation, and guidance algorithms to help maintain safe aircraft operations in both nominal and off-nominal scenarios.

A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs

NASA Astrophysics Data System (ADS)

Gudmundsson, Snorri

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.

Deconflicting Wind-Optimal Aircraft Trajectories in North Atlantic Oceanic Airspace

NASA Technical Reports Server (NTRS)

Rodionova, Olga; Delahaye, Daniel; Sridhar, Banavar; Ng, Hok K.

2016-01-01

North Atlantic oceanic airspace accommodates more than 1000 flights daily, and is subjected to very strong winds. Flying wind-optimal trajectories yields time and fuel savings for each individual flight. However, when taken together, these trajectories induce a large amount of potential en-route conflicts. This paper analyses the detected conflicts, figuring out conflict distribution in time and space. It further describes an optimization algorithm aimed at reducing the number of conflicts for a daily set of flights on strategic level. Several trajectory modification strategies are discussed, followed with simulation results. Finally, an algorithm improvement is presented aiming at better preserving the trajectory optimality.

Handling Trajectory Uncertainties for Airborne Conflict Management

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Doble, Nathan A.; Karr, David; Palmer, Michael T.

2005-01-01

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

On the calculation of low-thrust fail-safe trajectories

NASA Technical Reports Server (NTRS)

Sauer, C. G., Jr.

1975-01-01

A guidance algorithm is developed for a low-thrust spacecraft such that target intercept is possible in spite of premature thrust termination along the trajectory. Such a trajectory is called a 'fail-safe' trajectory and the spacecraft thrust is utilized to minimize the relative target-spacecraft approach speed. The fail-safe guidance algorithm is solved using the concept of a critical thrust plane and a non-critical thrust direction. Several examples of fail-safe guidance are presented for a solar-electric propulsion flyby mission to the comet Encke.

Target tracking and 3D trajectory acquisition of cabbage butterfly (P. rapae) based on the KCF-BS algorithm.

PubMed

Guo, Yang-Yang; He, Dong-Jian; Liu, Cong

2018-06-25

Insect behaviour is an important research topic in plant protection. To study insect behaviour accurately, it is necessary to observe and record their flight trajectory quantitatively and precisely in three dimensions (3D). The goal of this research was to analyse frames extracted from videos using Kernelized Correlation Filters (KCF) and Background Subtraction (BS) (KCF-BS) to plot the 3D trajectory of cabbage butterfly (P. rapae). Considering the experimental environment with a wind tunnel, a quadrature binocular vision insect video capture system was designed and applied in this study. The KCF-BS algorithm was used to track the butterfly in video frames and obtain coordinates of the target centroid in two videos. Finally the 3D trajectory was calculated according to the matching relationship in the corresponding frames of two angles in the video. To verify the validity of the KCF-BS algorithm, Compressive Tracking (CT) and Spatio-Temporal Context Learning (STC) algorithms were performed. The results revealed that the KCF-BS tracking algorithm performed more favourably than CT and STC in terms of accuracy and robustness.

Dose calculation of dynamic trajectory radiotherapy using Monte Carlo.

PubMed

Manser, P; Frauchiger, D; Frei, D; Volken, W; Terribilini, D; Fix, M K

2018-04-06

Using volumetric modulated arc therapy (VMAT) delivery technique gantry position, multi-leaf collimator (MLC) as well as dose rate change dynamically during the application. However, additional components can be dynamically altered throughout the dose delivery such as the collimator or the couch. Thus, the degrees of freedom increase allowing almost arbitrary dynamic trajectories for the beam. While the dose delivery of such dynamic trajectories for linear accelerators is technically possible, there is currently no dose calculation and validation tool available. Thus, the aim of this work is to develop a dose calculation and verification tool for dynamic trajectories using Monte Carlo (MC) methods. The dose calculation for dynamic trajectories is implemented in the previously developed Swiss Monte Carlo Plan (SMCP). SMCP interfaces the treatment planning system Eclipse with a MC dose calculation algorithm and is already able to handle dynamic MLC and gantry rotations. Hence, the additional dynamic components, namely the collimator and the couch, are described similarly to the dynamic MLC by defining data pairs of positions of the dynamic component and the corresponding MU-fractions. For validation purposes, measurements are performed with the Delta4 phantom and film measurements using the developer mode on a TrueBeam linear accelerator. These measured dose distributions are then compared with the corresponding calculations using SMCP. First, simple academic cases applying one-dimensional movements are investigated and second, more complex dynamic trajectories with several simultaneously moving components are compared considering academic cases as well as a clinically motivated prostate case. The dose calculation for dynamic trajectories is successfully implemented into SMCP. The comparisons between the measured and calculated dose distributions for the simple as well as for the more complex situations show an agreement which is generally within 3% of the maximum dose or 3mm. The required computation time for the dose calculation remains the same when the additional dynamic moving components are included. The results obtained for the dose comparisons for simple and complex situations suggest that the extended SMCP is an accurate dose calculation and efficient verification tool for dynamic trajectory radiotherapy. This work was supported by Varian Medical Systems. Copyright © 2018. Published by Elsevier GmbH.

Flatness-based model inverse for feed-forward braking control

NASA Astrophysics Data System (ADS)

de Vries, Edwin; Fehn, Achim; Rixen, Daniel

2010-12-01

For modern cars an increasing number of driver assistance systems have been developed. Some of these systems interfere/assist with the braking of a car. Here, a brake actuation algorithm for each individual wheel that can respond to both driver inputs and artificial vehicle deceleration set points is developed. The algorithm consists of a feed-forward control that ensures, within the modelled system plant, the optimal behaviour of the vehicle. For the quarter-car model with LuGre-tyre behavioural model, an inverse model can be derived using v x as the 'flat output', that is, the input for the inverse model. A number of time derivatives of the flat output are required to calculate the model input, brake torque. Polynomial trajectory planning provides the needed time derivatives of the deceleration request. The transition time of the planning can be adjusted to meet actuator constraints. It is shown that the output of the trajectory planning would ripple and introduce a time delay when a gradual continuous increase of deceleration is requested by the driver. Derivative filters are then considered: the Bessel filter provides the best symmetry in its step response. A filter of same order and with negative real-poles is also used, exhibiting no overshoot nor ringing. For these reasons, the 'real-poles' filter would be preferred over the Bessel filter. The half-car model can be used to predict the change in normal load on the front and rear axle due to the pitching of the vehicle. The anticipated dynamic variation of the wheel load can be included in the inverse model, even though it is based on a quarter-car. Brake force distribution proportional to normal load is established. It provides more natural and simpler equations than a fixed force ratio strategy.

Optimal helicopter trajectory planning for terrain following flight

NASA Technical Reports Server (NTRS)

Menon, P. K. A.

1990-01-01

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Generalized gradient algorithm for trajectory optimization

NASA Technical Reports Server (NTRS)

Zhao, Yiyuan; Bryson, A. E.; Slattery, R.

1990-01-01

The generalized gradient algorithm presented and verified as a basis for the solution of trajectory optimization problems improves the performance index while reducing path equality constraints, and terminal equality constraints. The algorithm is conveniently divided into two phases, of which the first, 'feasibility' phase yields a solution satisfying both path and terminal constraints, while the second, 'optimization' phase uses the results of the first phase as initial guesses.

Design and Implementation of the Automated Rendezvous Targeting Algorithms for Orion

NASA Technical Reports Server (NTRS)

DSouza, Christopher; Weeks, Michael

2010-01-01

The Orion vehicle will be designed to perform several rendezvous missions: rendezvous with the ISS in Low Earth Orbit (LEO), rendezvous with the EDS/Altair in LEO, a contingency rendezvous with the ascent stage of the Altair in Low Lunar Orbit (LLO) and a contingency rendezvous in LLO with the ascent and descent stage in the case of an aborted lunar landing. Therefore, it is not difficult to realize that each of these scenarios imposes different operational, timing, and performance constraints on the GNC system. To this end, a suite of on-board guidance and targeting algorithms have been designed to meet the requirement to perform the rendezvous independent of communications with the ground. This capability is particularly relevant for the lunar missions, some of which may occur on the far side of the moon. This paper will describe these algorithms which are designed to be structured and arranged in such a way so as to be flexible and able to safely perform a wide variety of rendezvous trajectories. The goal of the algorithms is not to merely fly one specific type of canned rendezvous profile. Conversely, it was designed from the start to be general enough such that any type of trajectory profile can be flown.(i.e. a coelliptic profile, a stable orbit rendezvous profile, and a expedited LLO rendezvous profile, etc) all using the same rendezvous suite of algorithms. Each of these profiles makes use of maneuver types which have been designed with dual goals of robustness and performance. They are designed to converge quickly under dispersed conditions and they are designed to perform many of the functions performed on the ground today. The targeting algorithms consist of a phasing maneuver (NC), an altitude adjust maneuver (NH), and plane change maneuver (NPC), a coelliptic maneuver (NSR), a Lambert targeted maneuver, and several multiple-burn targeted maneuvers which combine one of more of these algorithms. The derivation and implementation of each of these algorithms will be discussed in detail, as well and the Rendezvous Targeting "wrapper" which will sequentially tie them all together into a single onboard targeting tool which can produce a final integrated rendezvous trajectory. In a similar fashion, the various guidance modes available for flying out each of these maneuvers will be discussed as well. This paradigm of having the onboard guidance & targeting capability described above is different than the way the Space Shuttle has operated thus far. As a result, a discussion of these differences in terms of operations and ground and crew intervention will also be discussed. However, the general framework of how the mission designers on the ground first perform all mission design and planning functions, and then uplink that burn plan to the vehicle ensures that the ground will be involved to ensure safety and reliability. The only real difference is which of these functions will be done onboard vs. on the ground as done currently. Finally, this paper will describe the performance of each of these algorithms individually as well as the entire suite of algorithms as applied to the Orion ISS and EDS/Altair rendezvous missions in LEO. These algorithms have been incorporated in both a Linear Covariance environment and a Monte Carlo environment and the results of these dispersion analyses will be presented in the paper as well.

Optimal control and optimal trajectories of regional macroeconomic dynamics based on the Pontryagin maximum principle

NASA Astrophysics Data System (ADS)

Bulgakov, V. K.; Strigunov, V. V.

2009-05-01

The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.

A Sequential Linear Quadratic Approach for Constrained Nonlinear Optimal Control with Adaptive Time Discretization and Application to Higher Elevation Mars Landing Problem

NASA Astrophysics Data System (ADS)

Sandhu, Amit

A sequential quadratic programming method is proposed for solving nonlinear optimal control problems subject to general path constraints including mixed state-control and state only constraints. The proposed algorithm further develops on the approach proposed in [1] with objective to eliminate the use of a high number of time intervals for arriving at an optimal solution. This is done by introducing an adaptive time discretization to allow formation of a desirable control profile without utilizing a lot of intervals. The use of fewer time intervals reduces the computation time considerably. This algorithm is further used in this thesis to solve a trajectory planning problem for higher elevation Mars landing.

THREAD: A programming environment for interactive planning-level robotics applications

NASA Technical Reports Server (NTRS)

Beahan, John J., Jr.

1989-01-01

THREAD programming language, which was developed to meet the needs of researchers in developing robotics applications that perform such tasks as grasp, trajectory design, sensor data analysis, and interfacing with external subsystems in order to perform servo-level control of manipulators and real time sensing is discussed. The philosophy behind THREAD, the issues which entered into its design, and the features of the language are discussed from the viewpoint of researchers who want to develop algorithms in a simulation environment, and from those who want to implement physical robotics systems. The detailed functions of the many complex robotics algorithms and tools which are part of the language are not explained, but an overall impression of their capability is given.

Potential for Integrating Entry Guidance into the Multi-Disciplinary Entry Vehicle Optimization Environment

NASA Technical Reports Server (NTRS)

D'souza, Sarah N.; Kinney, David J.; Garcia, Joseph A.; Sarigul-Klijn, Nesrin

2014-01-01

The state-of-the-art in vehicle design decouples flight feasible trajectory generation from the optimization process of an entry spacecraft shape. The disadvantage to this decoupled process is seen when a particular aeroshell does not meet in-flight requirements when integrated into Guidance, Navigation, and Control simulations. It is postulated that the integration of a guidance algorithm into the design process will provide a real-time, rapid trajectory generation technique to enhance the robustness of vehicle design solutions. The potential benefit of this integration is a reduction in design cycles (possible cost savings) and increased accuracy in the aerothermal environment (possible mass savings). This work examines two aspects: 1) the performance of a reference tracking guidance algorithm for five different geometries with the same reference trajectory and 2) the potential of mass savings from improved aerothermal predictions. An Apollo Derived Guidance (ADG) algorithm is used in this study. The baseline geometry and five test case geometries were flown using the same baseline trajectory. The guided trajectory results are compared to separate trajectories determined in a vehicle optimization study conducted for NASA's Mars Entry, Descent, and Landing System Analysis. This study revealed several aspects regarding the potential gains and required developments for integrating a guidance algorithm into the vehicle optimization environment. First, the generation of flight feasible trajectories is only as good as the robustness of the guidance algorithm. The set of dispersed geometries modelled aerodynamic dispersions that ranged from +/-1% to +/-17% and a single extreme case was modelled where the aerodynamics were approximately 80% less than the baseline geometry. The ADG, as expected, was able to guide the vehicle into the aeroshell separation box at the target location for dispersions up to 17%, but failed for the 80% dispersion cases. Finally, the results revealed that including flight feasible trajectories for a set of dispersed geometries has the potential to save mass up to 430 kg.

A trajectory generation framework for modeling spacecraft entry in MDAO

NASA Astrophysics Data System (ADS)

D`Souza, Sarah N.; Sarigul-Klijn, Nesrin

2016-04-01

In this paper a novel trajectory generation framework was developed that optimizes trajectory event conditions for use in a Generalized Entry Guidance algorithm. The framework was developed to be adaptable via the use of high fidelity equations of motion and drag based analytical bank profiles. Within this framework, a novel technique was implemented that resolved the sensitivity of the bank profile to atmospheric non-linearities. The framework's adaptability was established by running two different entry bank conditions. Each case yielded a reference trajectory and set of transition event conditions that are flight feasible and implementable in a Generalized Entry Guidance algorithm.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Fifth Edition

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2015-01-01

This paper presents an overview of the fifth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 12 (ASTAR12). This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of- arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm includes a ground speed feedback term to compensate for slower than expected traffic aircraft speeds based on the accepted air traffic control tendency to slow aircraft below the nominal arrival speeds when they are farther from the airport.

NASA Langley's Formal Methods Research in Support of the Next Generation Air Transportation System

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Munoz, Cesar A.

2008-01-01

This talk will provide a brief introduction to the formal methods developed at NASA Langley and the National Institute for Aerospace (NIA) for air traffic management applications. NASA Langley's formal methods research supports the Interagency Joint Planning and Development Office (JPDO) effort to define and develop the 2025 Next Generation Air Transportation System (NGATS). The JPDO was created by the passage of the Vision 100 Century of Aviation Reauthorization Act in Dec 2003. The NGATS vision calls for a major transformation of the nation s air transportation system that will enable growth to 3 times the traffic of the current system. The transformation will require an unprecedented level of safety-critical automation used in complex procedural operations based on 4-dimensional (4D) trajectories that enable dynamic reconfiguration of airspace scalable to geographic and temporal demand. The goal of our formal methods research is to provide verification methods that can be used to insure the safety of the NGATS system. Our work has focused on the safety assessment of concepts of operation and fundamental algorithms for conflict detection and resolution (CD&R) and self- spacing in the terminal area. Formal analysis of a concept of operations is a novel area of application of formal methods. Here one must establish that a system concept involving aircraft, pilots, and ground resources is safe. The formal analysis of algorithms is a more traditional endeavor. However, the formal analysis of ATM algorithms involves reasoning about the interaction of algorithmic logic and aircraft trajectories defined over an airspace. These trajectories are described using 2D and 3D vectors and are often constrained by trigonometric relations. Thus, in many cases it has been necessary to unload the full power of an advanced theorem prover. The verification challenge is to establish that the safety-critical algorithms produce valid solutions that are guaranteed to maintain separation under all possible scenarios. Current research has assumed perfect knowledge of the location of other aircraft in the vicinity so absolute guarantees are possible, but increasingly we are relaxing the assumptions to allow incomplete, inaccurate, and/or faulty information from communication sources.

Detection of confinement and jumps in single-molecule membrane trajectories

NASA Astrophysics Data System (ADS)

Meilhac, N.; Le Guyader, L.; Salomé, L.; Destainville, N.

2006-01-01

We propose a variant of the algorithm by [R. Simson, E. D. Sheets, and K. Jacobson, Biophys. 69, 989 (1995)]. Their algorithm was developed to detect transient confinement zones in experimental single-particle tracking trajectories of diffusing membrane proteins or lipids. We show that our algorithm is able to detect confinement in a wider class of confining potential shapes than that of Simson Furthermore, it enables to detect not only temporary confinement but also jumps between confinement zones. Jumps are predicted by membrane skeleton fence and picket models. In the case of experimental trajectories of μ -opioid receptors, which belong to the family of G-protein-coupled receptors involved in a signal transduction pathway, this algorithm confirms that confinement cannot be explained solely by rigid fences.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Sixth Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2015-01-01

This paper presents an overview of the sixth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm adds the state-based capability in support of evolving industry standards relating to airborne self-spacing.

Operational space trajectory tracking control of robot manipulators endowed with a primary controller of synthetic joint velocity.

PubMed

Moreno-Valenzuela, Javier; González-Hernández, Luis

2011-01-01

In this paper, a new control algorithm for operational space trajectory tracking control of robot arms is introduced. The new algorithm does not require velocity measurement and is based on (1) a primary controller which incorporates an algorithm to obtain synthesized velocity from joint position measurements and (2) a secondary controller which computes the desired joint acceleration and velocity required to achieve operational space motion control. The theory of singularly perturbed systems is crucial for the analysis of the closed-loop system trajectories. In addition, the practical viability of the proposed algorithm is explored through real-time experiments in a two degrees-of-freedom horizontal planar direct-drive arm. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Simulation to Support Local Search in Trajectory Optimization Planning

NASA Technical Reports Server (NTRS)

Morris, Robert A.; Venable, K. Brent; Lindsey, James

2012-01-01

NASA and the international community are investing in the development of a commercial transportation infrastructure that includes the increased use of rotorcraft, specifically helicopters and civil tilt rotors. However, there is significant concern over the impact of noise on the communities surrounding the transportation facilities. One way to address the rotorcraft noise problem is by exploiting powerful search techniques coming from artificial intelligence coupled with simulation and field tests to design low-noise flight profiles which can be tested in simulation or through field tests. This paper investigates the use of simulation based on predictive physical models to facilitate the search for low-noise trajectories using a class of automated search algorithms called local search. A novel feature of this approach is the ability to incorporate constraints directly into the problem formulation that addresses passenger safety and comfort.

CAMELOT: Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox

NASA Astrophysics Data System (ADS)

Di Carlo, Marilena; Romero Martin, Juan Manuel; Vasile, Massimiliano

2018-03-01

Computational-Analytical Multi-fidElity Low-thrust Optimisation Toolbox (CAMELOT) is a toolbox for the fast preliminary design and optimisation of low-thrust trajectories. It solves highly complex combinatorial problems to plan multi-target missions characterised by long spirals including different perturbations. To do so, CAMELOT implements a novel multi-fidelity approach combining analytical surrogate modelling and accurate computational estimations of the mission cost. Decisions are then made using two optimisation engines included in the toolbox, a single-objective global optimiser, and a combinatorial optimisation algorithm. CAMELOT has been applied to a variety of case studies: from the design of interplanetary trajectories to the optimal de-orbiting of space debris and from the deployment of constellations to on-orbit servicing. In this paper, the main elements of CAMELOT are described and two examples, solved using the toolbox, are presented.

Information surfing with the JHU/APL coherent imager

NASA Astrophysics Data System (ADS)

Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.

2015-05-01

The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.

Army ants algorithm for rare event sampling of delocalized nonadiabatic transitions by trajectory surface hopping and the estimation of sampling errors by the bootstrap method.

PubMed

Nangia, Shikha; Jasper, Ahren W; Miller, Thomas F; Truhlar, Donald G

2004-02-22

The most widely used algorithm for Monte Carlo sampling of electronic transitions in trajectory surface hopping (TSH) calculations is the so-called anteater algorithm, which is inefficient for sampling low-probability nonadiabatic events. We present a new sampling scheme (called the army ants algorithm) for carrying out TSH calculations that is applicable to systems with any strength of coupling. The army ants algorithm is a form of rare event sampling whose efficiency is controlled by an input parameter. By choosing a suitable value of the input parameter the army ants algorithm can be reduced to the anteater algorithm (which is efficient for strongly coupled cases), and by optimizing the parameter the army ants algorithm may be efficiently applied to systems with low-probability events. To demonstrate the efficiency of the army ants algorithm, we performed atom-diatom scattering calculations on a model system involving weakly coupled electronic states. Fully converged quantum mechanical calculations were performed, and the probabilities for nonadiabatic reaction and nonreactive deexcitation (quenching) were found to be on the order of 10(-8). For such low-probability events the anteater sampling scheme requires a large number of trajectories ( approximately 10(10)) to obtain good statistics and converged semiclassical results. In contrast by using the new army ants algorithm converged results were obtained by running 10(5) trajectories. Furthermore, the results were found to be in excellent agreement with the quantum mechanical results. Sampling errors were estimated using the bootstrap method, which is validated for use with the army ants algorithm. (c) 2004 American Institute of Physics.

An Evaluation of a Flight Deck Interval Management Algorithm Including Delayed Target Trajectories

NASA Technical Reports Server (NTRS)

Swieringa, Kurt A.; Underwood, Matthew C.; Barmore, Bryan; Leonard, Robert D.

2014-01-01

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature air traffic management technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise timebased scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise in-trail spacing. During high demand operations, TMA-TM may produce a schedule and corresponding aircraft trajectories that include delay to ensure that a particular aircraft will be properly spaced from other aircraft at each schedule waypoint. These delayed trajectories are not communicated to the automation onboard the aircraft, forcing the IM aircraft to use the published speeds to estimate the target aircraft's estimated time of arrival. As a result, the aircraft performing IM operations may follow an aircraft whose TMA-TM generated trajectories have substantial speed deviations from the speeds expected by the spacing algorithm. Previous spacing algorithms were not designed to handle this magnitude of uncertainty. A simulation was conducted to examine a modified spacing algorithm with the ability to follow aircraft flying delayed trajectories. The simulation investigated the use of the new spacing algorithm with various delayed speed profiles and wind conditions, as well as several other variables designed to simulate real-life variability. The results and conclusions of this study indicate that the new spacing algorithm generally exhibits good performance; however, some types of target aircraft speed profiles can cause the spacing algorithm to command less than optimal speed control behavior.

Spacecraft Attitude Maneuver Planning Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Kornfeld, Richard P.

2004-01-01

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This approach for attitude path planning makes full use of a priori constraint knowledge and is computationally tractable enough to be executed onboard a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used as is or as an initial solution to initialize additional deterministic optimization algorithms. A number of representative case examples for time-fixed and time-varying conditions yielded search times that are typically on the order of minutes, thus demonstrating the viability of this method. This approach is applicable to all deep space and planet Earth missions requiring greater spacecraft autonomy, and greatly facilitates navigation and science observation planning.

Cross-Polar Aircraft Trajectory Optimization and the Potential Climate Impact

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Sridhar, Banavar; Grabbe, Shon; Chen, Neil

2011-01-01

Cross-Polar routes offer new opportunities for air travel markets. Transpolar flights reduce travel times, fuel burns, and associated environmental emissions by flying direct paths between many North American and Asian cities. This study evaluates the potential benefits of flying wind-optimal polar routes and assessed their potential impact on climate change. An optimization algorithm is developed for transpolar flights to generate wind-optimal trajectories that minimize climate impact of aircraft, in terms of global warming potentials (relative to warming by one kg of CO2) of several types of emissions, while avoiding regions of airspace that facilitate persistent contrail formation. Estimations of global warming potential are incorporated into the objective function of the optimization algorithm to assess the climate impact of aircraft emissions discharged at a given location and altitude. The regions of airspace with very low ambient temperature and areas favorable to persistent contrail formation are modeled as undesirable regions that aircraft should avoid and are formulated as soft state constraints. The fuel burn and climate impact of cross-polar air traffic flying various types of trajectory including flight plan, great circle, wind-optimal, and contrail-avoidance are computed for 15 origin-destination pairs between major international airports in the U.S. and Asia. Wind-optimal routes reduce average fuel burn of flight plan routes by 4.4% on December 4, 2010 and 8.0% on August 7, 2010, respectively. The tradeoff between persistent contrail formation and additional global warming potential of aircraft emissions is investigated with and without altitude optimization. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a one percent increase in additional global warming potential, a climate impact equivalent to that of 4070kg and 4220kg CO2 emission, reduces 135 and 105 minutes persistent contrail formation per flight during a day with medium and high contrail formation, respectively.

Alignment of cryo-EM movies of individual particles by optimization of image translations.

PubMed

Rubinstein, John L; Brubaker, Marcus A

2015-11-01

Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the specimen, due to both instabilities in the microscope specimen stage and electron beam-induced movement. Unlike specimen stage drift, beam-induced movement is not always homogeneous within an image. Local correlation in the trajectories of nearby particles suggests that beam-induced motion is due to deformation of the ice layer. Algorithms have already been described that can correct movement for large regions of frames and for >1 MDa protein particles. Another algorithm allows individual <1 MDa protein particle trajectories to be estimated, but requires rolling averages to be calculated from frames and fits linear trajectories for particles. Here we describe an algorithm that allows for individual <1 MDa particle images to be aligned without frame averaging or linear trajectories. The algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-EM. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimal Trajectories Generation in Robotic Fiber Placement Systems

NASA Astrophysics Data System (ADS)

Gao, Jiuchun; Pashkevich, Anatol; Caro, Stéphane

2017-06-01

The paper proposes a methodology for optimal trajectories generation in robotic fiber placement systems. A strategy to tune the parameters of the optimization algorithm at hand is also introduced. The presented technique transforms the original continuous problem into a discrete one where the time-optimal motions are generated by using dynamic programming. The developed strategy for the optimization algorithm tuning allows essentially reducing the computing time and obtaining trajectories satisfying industrial constraints. Feasibilities and advantages of the proposed methodology are confirmed by an application example.

Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1989-01-01

Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

Performance Analysis of the Enhanced Bio-Inspired Planning Algorithm for Rapid Situation Awareness Response

DTIC Science & Technology

2013-10-18

low cost robot testbed. 15. SUBJECT TERMS Bio-inspired trajectory generation, in-situ obstacle avoidance, low-cost LEGO robots, vision- based...will not affect the solution optimality and thus will be regarded as zero. Following the LP motion strategy Eq. (1), the position vector of the Lego ...Lobatto (LGL) method [14], the position of Lego robot can be further represented as ’ 1 ,( )j p jD   ζ ζ (6) in which ,0 ,,..., T j j j

Mystic: Implementation of the Static Dynamic Optimal Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design

NASA Technical Reports Server (NTRS)

Whiffen, Gregory J.

2006-01-01

Mystic software is designed to compute, analyze, and visualize optimal high-fidelity, low-thrust trajectories, The software can be used to analyze inter-planetary, planetocentric, and combination trajectories, Mystic also provides utilities to assist in the operation and navigation of low-thrust spacecraft. Mystic will be used to design and navigate the NASA's Dawn Discovery mission to orbit the two largest asteroids, The underlying optimization algorithm used in the Mystic software is called Static/Dynamic Optimal Control (SDC). SDC is a nonlinear optimal control method designed to optimize both 'static variables' (parameters) and dynamic variables (functions of time) simultaneously. SDC is a general nonlinear optimal control algorithm based on Bellman's principal.

Radiofrequency pulse design using nonlinear gradient magnetic fields.

PubMed

Kopanoglu, Emre; Constable, R Todd

2015-09-01

An iterative k-space trajectory and radiofrequency (RF) pulse design method is proposed for excitation using nonlinear gradient magnetic fields. The spatial encoding functions (SEFs) generated by nonlinear gradient fields are linearly dependent in Cartesian coordinates. Left uncorrected, this may lead to flip angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a matching pursuit algorithm, and the RF pulse is designed using a conjugate gradient algorithm. Three variants of the proposed approach are given: the full algorithm, a computationally cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. The method is compared with other iterative (matching pursuit and conjugate gradient) and noniterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity. An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. © 2014 Wiley Periodicals, Inc.

Efficient Optimization of Low-Thrust Spacecraft Trajectories

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Fink, Wolfgang; Russell, Ryan; Terrile, Richard; Petropoulos, Anastassios; vonAllmen, Paul

2007-01-01

A paper describes a computationally efficient method of optimizing trajectories of spacecraft driven by propulsion systems that generate low thrusts and, hence, must be operated for long times. A common goal in trajectory-optimization problems is to find minimum-time, minimum-fuel, or Pareto-optimal trajectories (here, Pareto-optimality signifies that no other solutions are superior with respect to both flight time and fuel consumption). The present method utilizes genetic and simulated-annealing algorithms to search for globally Pareto-optimal solutions. These algorithms are implemented in parallel form to reduce computation time. These algorithms are coupled with either of two traditional trajectory- design approaches called "direct" and "indirect." In the direct approach, thrust control is discretized in either arc time or arc length, and the resulting discrete thrust vectors are optimized. The indirect approach involves the primer-vector theory (introduced in 1963), in which the thrust control problem is transformed into a co-state control problem and the initial values of the co-state vector are optimized. In application to two example orbit-transfer problems, this method was found to generate solutions comparable to those of other state-of-the-art trajectory-optimization methods while requiring much less computation time.

An Optimized Trajectory Planning for Welding Robot

NASA Astrophysics Data System (ADS)

Chen, Zhilong; Wang, Jun; Li, Shuting; Ren, Jun; Wang, Quan; Cheng, Qunchao; Li, Wentao

2018-03-01

In order to improve the welding efficiency and quality, this paper studies the combined planning between welding parameters and space trajectory for welding robot and proposes a trajectory planning method with high real-time performance, strong controllability and small welding error. By adding the virtual joint at the end-effector, the appropriate virtual joint model is established and the welding process parameters are represented by the virtual joint variables. The trajectory planning is carried out in the robot joint space, which makes the control of the welding process parameters more intuitive and convenient. By using the virtual joint model combined with the B-spline curve affine invariant, the welding process parameters are indirectly controlled by controlling the motion curve of the real joint. To solve the optimal time solution as the goal, the welding process parameters and joint space trajectory joint planning are optimized.

Trajectory generation for an on-road autonomous vehicle

NASA Astrophysics Data System (ADS)

Horst, John; Barbera, Anthony

2006-05-01

We describe an algorithm that generates a smooth trajectory (position, velocity, and acceleration at uniformly sampled instants of time) for a car-like vehicle autonomously navigating within the constraints of lanes in a road. The technique models both vehicle paths and lane segments as straight line segments and circular arcs for mathematical simplicity and elegance, which we contrast with cubic spline approaches. We develop the path in an idealized space, warp the path into real space and compute path length, generate a one-dimensional trajectory along the path length that achieves target speeds and positions, and finally, warp, translate, and rotate the one-dimensional trajectory points onto the path in real space. The algorithm moves a vehicle in lane safely and efficiently within speed and acceleration maximums. The algorithm functions in the context of other autonomous driving functions within a carefully designed vehicle control hierarchy.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Seventh Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2015-01-01

This paper presents an overview of the seventh revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This paper supersedes the previous documentation and presents a modification to the algorithm referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm adds the state-based capability in support of evolving industry standards relating to airborne self-spacing.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Eighth Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.; Swieringa, Kurt S.

2017-01-01

This paper presents an overview of the eighth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This paper supersedes the previous documentation and presents a modification to the algorithm referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval with another aircraft. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm supports the evolving industry standards relating to airborne self-spacing.

Autonomous underwater vehicle adaptive path planning for target classification

NASA Astrophysics Data System (ADS)

Edwards, Joseph R.; Schmidt, Henrik

2002-11-01

Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.

Numerical approach of collision avoidance and optimal control on robotic manipulators

NASA Technical Reports Server (NTRS)

Wang, Jyhshing Jack

1990-01-01

Collision-free optimal motion and trajectory planning for robotic manipulators are solved by a method of sequential gradient restoration algorithm. Numerical examples of a two degree-of-freedom (DOF) robotic manipulator are demonstrated to show the excellence of the optimization technique and obstacle avoidance scheme. The obstacle is put on the midway, or even further inward on purpose, of the previous no-obstacle optimal trajectory. For the minimum-time purpose, the trajectory grazes by the obstacle and the minimum-time motion successfully avoids the obstacle. The minimum-time is longer for the obstacle avoidance cases than the one without obstacle. The obstacle avoidance scheme can deal with multiple obstacles in any ellipsoid forms by using artificial potential fields as penalty functions via distance functions. The method is promising in solving collision-free optimal control problems for robotics and can be applied to any DOF robotic manipulators with any performance indices and mobile robots as well. Since this method generates optimum solution based on Pontryagin Extremum Principle, rather than based on assumptions, the results provide a benchmark against which any optimization techniques can be measured.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

PubMed

Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

PubMed

Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando

2017-08-15

This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.

Anatomy-driven multiple trajectory planning (ADMTP) of intracranial electrodes for epilepsy surgery.

PubMed

Sparks, Rachel; Vakharia, Vejay; Rodionov, Roman; Vos, Sjoerd B; Diehl, Beate; Wehner, Tim; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sebastien

2017-08-01

Epilepsy is potentially curable with resective surgery if the epileptogenic zone (EZ) can be identified. If non-invasive imaging is unable to elucidate the EZ, intracranial electrodes may be implanted to identify the EZ as well as map cortical function. In current clinical practice, each electrode trajectory is determined by time-consuming manual inspection of preoperative imaging to find a path that avoids blood vessels while traversing appropriate deep and superficial regions of interest (ROIs). We present anatomy-driven multiple trajectory planning (ADMTP) to find safe trajectories from a list of user-defined ROIs within minutes rather than the hours required for manual planning. Electrode trajectories are automatically computed in three steps: (1) Target Point Selection to identify appropriate target points within each ROI; (2) Trajectory Risk Scoring to quantify the cumulative distance to critical structures (blood vessels) along each trajectory, defined as the skull entry point to target point. (3) Implantation Plan Computation: to determine a feasible combination of low-risk trajectories for all electrodes. ADMTP was evaluated on 20 patients (190 electrodes). ADMTP lowered the quantitative risk score in 83% of electrodes. Qualitative results show ADMTP found suitable trajectories for 70% of electrodes; a similar portion of manual trajectories were considered suitable. Trajectory suitability for ADMTP was 95% if traversing sulci was not included in the safety criteria. ADMTP is computationally efficient, computing between 7 and 12 trajectories in 54.5 (17.3-191.9) s. ADMTP efficiently compute safe and surgically feasible electrode trajectories.

A Trajectory Algorithm to Support En Route and Terminal Area Self-Spacing Concepts: Third Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2012-01-01

This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates constant radius turns and cruise altitude waypoints with calibrated airspeed, versus Mach, constraints. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint. Wind data at each of these waypoints are also used for the calculation of ground speed and turn radius.

Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories

NASA Technical Reports Server (NTRS)

Ng, Hok Kwan; Sridhar, Banavar

2016-01-01

This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.

Experimental study of trajectory planning and control of a high precision robot manipulator

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Antrazi, Sami S.

1991-01-01

The kinematic and trajectory planning is presented for a 6 DOF end-effector whose design was based on the Stewart Platform mechanism. The end-effector was used as a testbed for studying robotic assembly of NASA hardware with passive compliance. Vector analysis was employed to derive a closed-form solution for the end-effector inverse kinematic transformation. A computationally efficient numerical solution was obtained for the end-effector forward kinematic transformation using Newton-Raphson method. Three trajectory planning schemes, two for fine motion and one for gross motion, were developed for the end-effector. Experiments conducted to evaluate the performance of the trajectory planning schemes showed excellent tracking quality with minimal errors. Current activities focus on implementing the developed trajectory planning schemes on mating and demating space-rated connectors and using the compliant platform to acquire forces/torques applied on the end-effector during the assembly task.

Design and analysis of advanced flight planning concepts

NASA Technical Reports Server (NTRS)

Sorensen, John A.

1987-01-01

The objectives of this continuing effort are to develop and evaluate new algorithms and advanced concepts for flight management and flight planning. This includes the minimization of fuel or direct operating costs, the integration of the airborne flight management and ground-based flight planning processes, and the enhancement of future traffic management systems design. Flight management (FMS) concepts are for on-board profile computation and steering of transport aircraft in the vertical plane between a city pair and along a given horizontal path. Flight planning (FPS) concepts are for the pre-flight ground based computation of the three-dimensional reference trajectory that connects the city pair and specifies the horizontal path, fuel load, and weather profiles for initializing the FMS. As part of these objectives, a new computer program called EFPLAN has been developed and utilized to study advanced flight planning concepts. EFPLAN represents an experimental version of an FPS. It has been developed to generate reference flight plans compatible as input to an FMS and to provide various options for flight planning research. This report describes EFPLAN and the associated research conducted in its development.

Method and apparatus for optimizing a train trip using signal information

DOEpatents

Kumar, Ajith Kuttannair; Daum, Wolfgang; Otsubo, Tom; Hershey, John Erik; Hess, Gerald James

2014-06-10

A system is provided for operating a railway network including a first railway vehicle during a trip along track segments. The system includes a first element for determining travel parameters of the first railway vehicle, a second element for determining travel parameters of a second railway vehicle relative to the track segments to be traversed by the first vehicle during the trip, a processor for receiving information from the first and the second elements and for determining a relationship between occupation of a track segment by the second vehicle and later occupation of the same track segment by the first vehicle and an algorithm embodied within the processor having access to the information to create a trip plan that determines a speed trajectory for the first vehicle. The speed trajectory is responsive to the relationship and further in accordance with one or more operational criteria for the first vehicle.

Optimizing Aircraft Trajectories with Multiple Cruise Altitudes in the Presence of Winds

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Sridhar, Banavar; Grabbe, Shon

2014-01-01

This study develops a trajectory optimization algorithm for approximately minimizing aircraft travel time and fuel burn by combining a method for computing minimum-time routes in winds on multiple horizontal planes, and an aircraft fuel burn model for generating fuel-optimal vertical profiles. It is applied to assess the potential benefits of flying user-preferred routes for commercial cargo flights operating between Anchorage, Alaska and major airports in Asia and the contiguous United States. Flying wind optimal trajectories with a fuel-optimal vertical profile reduces average fuel burn of international flights cruising at a single altitude by 1-3 percent. The potential fuel savings of performing en-route step climbs are not significant for many shorter domestic cargo flights that have only one step climb. Wind-optimal trajectories reduce fuel burn and travel time relative to the flight plan route by up to 3 percent for the domestic cargo flights. However, for trans-oceanic traffic, the fuel burn savings could be as much as 10 percent. The actual savings in operations will vary from the simulation results due to differences in the aircraft models and user defined cost indices. In general, the savings are proportional to trip length, and depend on the en-route wind conditions and aircraft types.

Atmospheric Ascent Guidance for Rocket-Powered Launch Vehicles

NASA Technical Reports Server (NTRS)

Dukeman, Greg A.

2002-01-01

An advanced ascent guidance algorithm for rocket- powered launch vehicles is developed. This algorithm cyclically solves the calculus-of-variations two-point boundary-value problem starting at vertical rise completion through main engine cutoff. This is different from traditional ascent guidance algorithms which operate in a simple open-loop mode until high dynamic pressure (including the critical max-Q) portion of the trajectory is over, at which time guidance operates under the assumption of negligible aerodynamic acceleration (i.e., vacuum dynamics). The initial costate guess is corrected based on errors in the terminal state constraints and the transversality conditions. Judicious approximations are made to reduce the order and complexity of the state/costate system. Results comparing guided launch vehicle trajectories with POST open-loop trajectories are given verifying the basic formulation of the algorithm. Multiple shooting is shown to be a very effective numerical technique for this application. In particular, just one intermediate shooting point, in addition to the initial shooting point, is sufficient to significantly reduce sensitivity to the guessed initial costates. Simulation results from a high-fidelity trajectory simulation are given for the case of launch to sub-orbital cutoff conditions as well as launch to orbit conditions. An abort to downrange landing site formulation of the algorithm is presented.

On-board autonomous attitude maneuver planning for planetary spacecraft using genetic algorithms

NASA Technical Reports Server (NTRS)

Kornfeld, Richard P.

2003-01-01

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This paper presents an approach for attitude path planning that makes full use of a priori constraint knowledge and is computationally tractable enough to be executed on-board a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used 'as is' or as an initial solution to initialize additional deterministic optimization algorithms. A number of example simulations are presented including the case examples of a generic Europa Orbiter spacecraft in cruise as well as in orbit around Europa. The search times are typically on the order of minutes, thus demonstrating the viability of the presented approach. The results are applicable to all future deep space missions where greater spacecraft autonomy is required. In addition, onboard autonomous attitude planning greatly facilitates navigation and science observation planning, benefiting thus all missions to planet Earth as well.

Discovering shared segments on the migration route of the bar-headed goose by time-based plane-sweeping trajectory clustering

USGS Publications Warehouse

Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.

2012-01-01

We propose a new method to help ornithologists and ecologists discover shared segments on the migratory pathway of the bar-headed geese by time-based plane-sweeping trajectory clustering. We present a density-based time parameterized line segment clustering algorithm, which extends traditional comparable clustering algorithms from temporal and spatial dimensions. We present a time-based plane-sweeping trajectory clustering algorithm to reveal the dynamic evolution of spatial-temporal object clusters and discover common motion patterns of bar-headed geese in the process of migration. Experiments are performed on GPS-based satellite telemetry data from bar-headed geese and results demonstrate our algorithms can correctly discover shared segments of the bar-headed geese migratory pathway. We also present findings on the migratory behavior of bar-headed geese determined from this new analytical approach.

Penalized Multi-Way Partial Least Squares for Smooth Trajectory Decoding from Electrocorticographic (ECoG) Recording

PubMed Central

Eliseyev, Andrey; Aksenova, Tetiana

2016-01-01

In the current paper the decoding algorithms for motor-related BCI systems for continuous upper limb trajectory prediction are considered. Two methods for the smooth prediction, namely Sobolev and Polynomial Penalized Multi-Way Partial Least Squares (PLS) regressions, are proposed. The methods are compared to the Multi-Way Partial Least Squares and Kalman Filter approaches. The comparison demonstrated that the proposed methods combined the prediction accuracy of the algorithms of the PLS family and trajectory smoothness of the Kalman Filter. In addition, the prediction delay is significantly lower for the proposed algorithms than for the Kalman Filter approach. The proposed methods could be applied in a wide range of applications beyond neuroscience. PMID:27196417

On the Optimization of Aerospace Plane Ascent Trajectory

NASA Astrophysics Data System (ADS)

Al-Garni, Ahmed; Kassem, Ayman Hamdy

A hybrid heuristic optimization technique based on genetic algorithms and particle swarm optimization has been developed and tested for trajectory optimization problems with multi-constraints and a multi-objective cost function. The technique is used to calculate control settings for two types for ascending trajectories (constant dynamic pressure and minimum-fuel-minimum-heat) for a two-dimensional model of an aerospace plane. A thorough statistical analysis is done on the hybrid technique to make comparisons with both basic genetic algorithms and particle swarm optimization techniques with respect to convergence and execution time. Genetic algorithm optimization showed better execution time performance while particle swarm optimization showed better convergence performance. The hybrid optimization technique, benefiting from both techniques, showed superior robust performance compromising convergence trends and execution time.

An adaptive inverse kinematics algorithm for robot manipulators

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.; Seraji, H.

1990-01-01

An adaptive algorithm for solving the inverse kinematics problem for robot manipulators is presented. The algorithm is derived using model reference adaptive control (MRAC) theory and is computationally efficient for online applications. The scheme requires no a priori knowledge of the kinematics of the robot if Cartesian end-effector sensing is available, and it requires knowledge of only the forward kinematics if joint position sensing is used. Computer simulation results are given for the redundant seven-DOF robotics research arm, demonstrating that the proposed algorithm yields accurate joint angle trajectories for a given end-effector position/orientation trajectory.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing to Include Parallel Runway Operations

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2011-01-01

This paper presents an overview of an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. This implementation provides the ability to manage spacing against two traffic aircraft, with one of these aircraft operating to a parallel dependent runway. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of-arrival (RTA) operations

RF Pulse Design using Nonlinear Gradient Magnetic Fields

PubMed Central

Kopanoglu, Emre; Constable, R. Todd

2014-01-01

Purpose An iterative k-space trajectory and radio-frequency (RF) pulse design method is proposed for Excitation using Nonlinear Gradient Magnetic fields (ENiGMa). Theory and Methods The spatial encoding functions (SEFs) generated by nonlinear gradient fields (NLGFs) are linearly dependent in Cartesian-coordinates. Left uncorrected, this may lead to flip-angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a Matching-Pursuit algorithm, and the RF pulse is designed using a Conjugate-Gradient algorithm. Three variants of the proposed approach are given: the full-algorithm, a computationally-cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. Results The method is compared to other iterative (Matching-Pursuit and Conjugate Gradient) and non-iterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity significantly. Conclusion An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. PMID:25203286

MO-FG-CAMPUS-TeP2-05: Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions with Individualized Rotational Arc Trajectories

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

Dong, P; Xing, L; Ma, L

Purpose: Radiosurgery of multiple (n>4) brain metastasis lesions requires 3–4 noncoplanar VMAT arcs with excessively high monitor units and long delivery time. We investigated whether an improved optimization technique would decrease the needed arc numbers and increase the delivery efficiency, while improving or maintaining the plan quality. Methods: The proposed 4pi arc space optimization algorithm consists of two steps: automatic couch angle selection followed by aperture generation for each arc with optimized control points distribution. We use a greedy algorithm to select the couch angles. Starting from a single coplanar arc plan we search through the candidate noncoplanar arcs tomore » pick a single noncoplanar arc that will bring the best plan quality when added into the existing treatment plan. Each time, only one additional noncoplanar arc is considered making the calculation time tractable. This process repeats itself until desired number of arc is reached. The technique is first evaluated in coplanar arc delivery scheme with testing cases and then applied to noncoplanar treatments of a case with 12 brain metastasis lesions. Results: Clinically acceptable plans are created within minutes. For the coplanar testing cases the algorithm yields singlearc plans with better dose distributions than that of two-arc VMAT, simultaneously with a 12–17% reduction in the delivery time and a 14–21% reduction in MUs. For the treatment of 12 brain mets while Paddick conformity indexes of the two plans were comparable the SCG-optimization with 2 arcs (1 noncoplanar and 1 coplanar) significantly improved the conventional VMAT with 3 arcs (2 noncoplanar and 1 coplanar). Specifically V16 V10 and V5 of the brain were reduced by 11%, 11% and 12% respectively. The beam delivery time was shortened by approximately 30%. Conclusion: The proposed 4pi arc space optimization technique promises to significantly reduce the brain toxicity while greatly improving the treatment efficiency.« less

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

PubMed Central

Liu, Jingxian; Wu, Kefeng

2017-01-01

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with traditional spectral clustering and fast affinity propagation clustering. Experimental results have illustrated its superior performance in terms of quantitative and qualitative evaluations. PMID:28777353

Multi-Target Tracking via Mixed Integer Optimization

DTIC Science & Technology

2016-05-13

solving these two problems separately, however few algorithms attempt to solve these simultaneously and even fewer utilize optimization. In this paper we...introduce a new mixed integer optimization (MIO) model which solves the data association and trajectory estimation problems simultaneously by minimizing...Kalman filter [5], which updates the trajectory estimates before the algorithm progresses forward to the next scan. This process repeats sequentially

A comparison of time-optimal interception trajectories for the F-8 and F-15

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Pettengill, James B.

1990-01-01

The simulation results of a real time control algorithm for onboard computation of time-optimal intercept trajectories for the F-8 and F-15 aircraft are given. Due to the inherent aerodynamic and propulsion differences in the aircraft, there are major differences in their optimal trajectories. The significant difference in the two aircrafts are their flight envelopes. The F-8's optimal cruise velocity is thrust limited, while the F-15's optimal cruise velocity is at the intersection of the Mach and dynamic pressure constraint boundaries. This inherent difference necessitated the development of a proportional thrust controller for use as the F-15 approaches it's optimal cruise energy. Documented here is the application of singular perturbation theory to the trajectory optimization problem, along with a summary of the control algorithms. Numerical results for the two aircraft are compared to illustrate the performance of the minimum time algorithm, and to compute the resulting flight paths.

Simulation evaluation of a low-altitude helicopter flight guidance system adapted for a helmet-mounted display

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Zelenka, Richard E.; Hardy, Gordon H.; Dearing, Munro G.

1992-01-01

A computer aiding concept for low-altitude helicopter flight was developed and evaluated in a real-time piloted simulation. The concept included an optimal control trajectory-generation algorithm based upon dynamic programming and a helmet-mounted display (HMD) presentation of a pathway-in-the-sky, a phantom aircraft, and flight-path vector/predictor guidance symbology. The trajectory-generation algorithm uses knowledge of the global mission requirements, a digital terrain map, aircraft performance capabilities, and advanced navigation information to determine a trajectory between mission way points that seeks valleys to minimize threat exposure. The pilot evaluation was conducted at NASA ARC moving base Vertical Motion Simulator (VMS) by pilots representing NASA, the U.S. Army, the Air Force, and the helicopter industry. The pilots manually tracked the trajectory generated by the algorithm utilizing the HMD symbology. The pilots were able to satisfactorily perform the tracking tasks while maintaining a high degree of awareness of the outside world.

Computer aiding for low-altitude helicopter flight

NASA Technical Reports Server (NTRS)

Swenson, Harry N.

1991-01-01

A computer-aiding concept for low-altitude helicopter flight was developed and evaluated in a real-time piloted simulation. The concept included an optimal control trajectory-generated algorithm based on dynamic programming, and a head-up display (HUD) presentation of a pathway-in-the-sky, a phantom aircraft, and flight-path vector/predictor symbol. The trajectory-generation algorithm uses knowledge of the global mission requirements, a digital terrain map, aircraft performance capabilities, and advanced navigation information to determine a trajectory between mission waypoints that minimizes threat exposure by seeking valleys. The pilot evaluation was conducted at NASA Ames Research Center's Sim Lab facility in both the fixed-base Interchangeable Cab (ICAB) simulator and the moving-base Vertical Motion Simulator (VMS) by pilots representing NASA, the U.S. Army, and the U.S. Air Force. The pilots manually tracked the trajectory generated by the algorithm utilizing the HUD symbology. They were able to satisfactorily perform the tracking tasks while maintaining a high degree of awareness of the outside world.

Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2018-05-01

Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

Trajectory planning of free-floating space robot using Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Walter, Ulrich

2015-07-01

This paper investigates the application of Particle Swarm Optimization (PSO) strategy to trajectory planning of the kinematically redundant space robot in free-floating mode. Due to the path dependent dynamic singularities, the volume of available workspace of the space robot is limited and enormous joint velocities are required when such singularities are met. In order to overcome this effect, the direct kinematics equations in conjunction with PSO are employed for trajectory planning of free-floating space robot. The joint trajectories are parametrized with the Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) redundant manipulator mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

A Robot Trajectory Optimization Approach for Thermal Barrier Coatings Used for Free-Form Components

NASA Astrophysics Data System (ADS)

Cai, Zhenhua; Qi, Beichun; Tao, Chongyuan; Luo, Jie; Chen, Yuepeng; Xie, Changjun

2017-10-01

This paper is concerned with a robot trajectory optimization approach for thermal barrier coatings. As the requirements of high reproducibility of complex workpieces increase, an optimal thermal spraying trajectory should not only guarantee an accurate control of spray parameters defined by users (e.g., scanning speed, spray distance, scanning step, etc.) to achieve coating thickness homogeneity but also help to homogenize the heat transfer distribution on the coating surface. A mesh-based trajectory generation approach is introduced in this work to generate path curves on a free-form component. Then, two types of meander trajectories are generated by performing a different connection method. Additionally, this paper presents a research approach for introducing the heat transfer analysis into the trajectory planning process. Combining heat transfer analysis with trajectory planning overcomes the defects of traditional trajectory planning methods (e.g., local over-heating), which helps form the uniform temperature field by optimizing the time sequence of path curves. The influence of two different robot trajectories on the process of heat transfer is estimated by coupled FEM models which demonstrates the effectiveness of the presented optimization approach.

Lane changing trajectory planning and tracking control for intelligent vehicle on curved road.

PubMed

Wang, Lukun; Zhao, Xiaoying; Su, Hao; Tang, Gongyou

2016-01-01

This paper explores lane changing trajectory planning and tracking control for intelligent vehicle on curved road. A novel arcs trajectory is planned for the desired lane changing trajectory. A kinematic controller and a dynamics controller are designed to implement the trajectory tracking control. Firstly, the kinematic model and dynamics model of intelligent vehicle with non-holonomic constraint are established. Secondly, two constraints of lane changing on curved road in practice (LCCP) are proposed. Thirdly, two arcs with same curvature are constructed for the desired lane changing trajectory. According to the geometrical characteristics of arcs trajectory, equations of desired state can be calculated. Finally, the backstepping method is employed to design a kinematic trajectory tracking controller. Then the sliding-mode dynamics controller is designed to ensure that the motion of the intelligent vehicle can follow the desired velocity generated by kinematic controller. The stability of control system is proved by Lyapunov theory. Computer simulation demonstrates that the desired arcs trajectory and state curves with B-spline optimization can meet the requirements of LCCP constraints and the proposed control schemes can make tracking errors to converge uniformly.

Algorithm research for user trajectory matching across social media networks based on paragraph2vec

NASA Astrophysics Data System (ADS)

Xu, Qian; Chen, Hongchang; Zhi, Hongxin; Wang, Yanchuan

2018-04-01

Identifying users across different social media networks (SMN) is to link accounts of the same user that belong to the same individual across SMNs. The problem is fundamental and important, and its results can benefit many applications such as cross SMN user modeling and recommendation. With the development of GPS technology and mobile communication, more and more social networks provide location services. This provides a new opportunity for cross SMN user identification. In this paper, we solve cross SMN user identification problem in an unsupervised manner by utilizing user trajectory data in SMNs. A paragraph2vec based algorithm is proposed in which location sequence feature of user trajectory is captured in temporal and spatial dimensions. Our experimental results validate the effectiveness and efficiency of our algorithm.

A Global Approach to the Optimal Trajectory Based on an Improved Ant Colony Algorithm for Cold Spray

NASA Astrophysics Data System (ADS)

Cai, Zhenhua; Chen, Tingyang; Zeng, Chunnian; Guo, Xueping; Lian, Huijuan; Zheng, You; Wei, Xiaoxu

2016-12-01

This paper is concerned with finding a global approach to obtain the shortest complete coverage trajectory on complex surfaces for cold spray applications. A slicing algorithm is employed to decompose the free-form complex surface into several small pieces of simple topological type. The problem of finding the optimal arrangement of the pieces is translated into a generalized traveling salesman problem (GTSP). Owing to its high searching capability and convergence performance, an improved ant colony algorithm is then used to solve the GTSP. Through off-line simulation, a robot trajectory is generated based on the optimized result. The approach is applied to coat real components with a complex surface by using the cold spray system with copper as the spraying material.

Route Sanitizer: Connected Vehicle Trajectory De-Identification Tool

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

Carter, Jason M; Ferber, Aaron E

Route Sanitizer is ORNL's connected vehicle moving object database de-identification tool and a graphical user interface to ORNL's connected vehicle de-identification algorithm. It uses the Google Chrome (soon to be Electron) platform so it will run on different computing platforms. The basic de-identification strategy is record redaction: portions of a vehicle trajectory (e.g. sequences of precise temporal spatial records) are removed. It does not alter retained records. The algorithm uses custom techniques to find areas within trajectories that may be considered private, then it suppresses those in addition to enough of the trajectory surrounding those locations to protect against "inferencemore » attacks" in a mathematically sound way. Map data is integrated into the process to make this possible.« less

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Optimal path planning for video-guided smart munitions via multitarget tracking

NASA Astrophysics Data System (ADS)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

Dynamical structure of extreme ultraviolet macrospicules

NASA Technical Reports Server (NTRS)

Karovska, Margarita; Habbal, Shadia Rifai

1994-01-01

We describe the substructures forming the macrospicules and their temporal evolution, as revealed by the application of an image enhancement algorithm to extreme ultraviolet (EUV) observations of macrospicules. The enhanced images uncover, for the first time, the substructures forming the column-like structures within the macrospicules and the low-lying arches at their base. The spatial and temporal evolution of macrospicules clearly show continuous interaction between these substructures with occasional ejection of plasma following a ballistic trajectory. We comment on the importance of these results for planning near future space observations of macrospicules with better temporal and spatial resolution.

Interactive orbital proximity operations planning system

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1990-01-01

An interactive graphical planning system for on-site planning of proximity operations in the congested multispacecraft environment about the space station is presented. The system shows the astronaut a bird's eye perspective of the space station, the orbital plane, and the co-orbiting spacecraft. The system operates in two operational modes: (1) a viewpoint mode, in which the astronaut is able to move the viewpoint around in the orbital plane to range in on areas of interest; and (2) a trajectory design mode, in which the trajectory is planned. Trajectory design involves the composition of a set of waypoints which result in a fuel-optimal trajectory which satisfies all operational constraints, such as departure and arrival constraints, plume impingement constraints, and structural constraints. The main purpose of the system is to present the trajectory and the constraints in an easily interpretable graphical format. Through a graphical interactive process, the trajectory waypoints are edited until all operational constraints are satisfied. A series of experiments was conducted to evaluate the system. Eight airline pilots with no prior background in orbital mechanics participated in the experiments. Subject training included a stand-alone training session of about 6 hours duration, in which the subjects became familiar with orbital mechanics concepts and performed a series of exercises to familiarize themselves with the control and display features of the system. They then carried out a series of production runs in which 90 different trajectory design situations were randomly addressed. The purpose of these experiments was to investigate how the planning time, planning efforts, and fuel expenditures were affected by the planning difficulty. Some results of these experiments are presented.

Improved dense trajectories for action recognition based on random projection and Fisher vectors

NASA Astrophysics Data System (ADS)

Ai, Shihui; Lu, Tongwei; Xiong, Yudian

2018-03-01

As an important application of intelligent monitoring system, the action recognition in video has become a very important research area of computer vision. In order to improve the accuracy rate of the action recognition in video with improved dense trajectories, one advanced vector method is introduced. Improved dense trajectories combine Fisher Vector with Random Projection. The method realizes the reduction of the characteristic trajectory though projecting the high-dimensional trajectory descriptor into the low-dimensional subspace based on defining and analyzing Gaussian mixture model by Random Projection. And a GMM-FV hybrid model is introduced to encode the trajectory feature vector and reduce dimension. The computational complexity is reduced by Random Projection which can drop Fisher coding vector. Finally, a Linear SVM is used to classifier to predict labels. We tested the algorithm in UCF101 dataset and KTH dataset. Compared with existed some others algorithm, the result showed that the method not only reduce the computational complexity but also improved the accuracy of action recognition.

Gradient descent learning algorithm overview: a general dynamical systems perspective.

PubMed

Baldi, P

1995-01-01

Gives a unified treatment of gradient descent learning algorithms for neural networks using a general framework of dynamical systems. This general approach organizes and simplifies all the known algorithms and results which have been originally derived for different problems (fixed point/trajectory learning), for different models (discrete/continuous), for different architectures (forward/recurrent), and using different techniques (backpropagation, variational calculus, adjoint methods, etc.). The general approach can also be applied to derive new algorithms. The author then briefly examines some of the complexity issues and limitations intrinsic to gradient descent learning. Throughout the paper, the author focuses on the problem of trajectory learning.

Development of a Nonlinear Probability of Collision Tool for the Earth Observing System

NASA Technical Reports Server (NTRS)

McKinley, David P.

2006-01-01

The Earth Observing System (EOS) spacecraft Terra, Aqua, and Aura fly in constellation with several other spacecraft in 705-kilometer mean altitude sun-synchronous orbits. All three spacecraft are operated by the Earth Science Mission Operations (ESMO) Project at Goddard Space Flight Center (GSFC). In 2004, the ESMO project began assessing the probability of collision of the EOS spacecraft with other space objects. In addition to conjunctions with high relative velocities, the collision assessment method for the EOS spacecraft must address conjunctions with low relative velocities during potential collisions between constellation members. Probability of Collision algorithms that are based on assumptions of high relative velocities and linear relative trajectories are not suitable for these situations; therefore an algorithm for handling the nonlinear relative trajectories was developed. This paper describes this algorithm and presents results from its validation for operational use. The probability of collision is typically calculated by integrating a Gaussian probability distribution over the volume swept out by a sphere representing the size of the space objects involved in the conjunction. This sphere is defined as the Hard Body Radius. With the assumption of linear relative trajectories, this volume is a cylinder, which translates into simple limits of integration for the probability calculation. For the case of nonlinear relative trajectories, the volume becomes a complex geometry. However, with an appropriate choice of coordinate systems, the new algorithm breaks down the complex geometry into a series of simple cylinders that have simple limits of integration. This nonlinear algorithm will be discussed in detail in the paper. The nonlinear Probability of Collision algorithm was first verified by showing that, when used in high relative velocity cases, it yields similar answers to existing high relative velocity linear relative trajectory algorithms. The comparison with the existing high velocity/linear theory will also be used to determine at what relative velocity the analysis should use the new nonlinear theory in place of the existing linear theory. The nonlinear algorithm was also compared to a known exact solution for the probability of collision between two objects when the relative motion is strictly circular and the error covariance is spherically symmetric. Figure I shows preliminary results from this comparison by plotting the probabilities calculated from the new algorithm and those from the exact solution versus the Hard Body Radius to Covariance ratio. These results show about 5% error when the Hard Body Radius is equal to one half the spherical covariance magnitude. The algorithm was then combined with a high fidelity orbit state and error covariance propagator into a useful tool for analyzing low relative velocity nonlinear relative trajectories. The high fidelity propagator is capable of using atmospheric drag, central body gravitational, solar radiation, and third body forces to provide accurate prediction of the relative trajectories and covariance evolution. The covariance propagator also includes a process noise model to ensure realistic evolutions of the error covariance. This paper will describe the integration of the nonlinear probability algorithm and the propagators into a useful collision assessment tool. Finally, a hypothetical case study involving a low relative velocity conjunction between members of the Earth Observation System constellation will be presented.

The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion.

PubMed

Borkowski, Piotr

2017-06-20

It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship's current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships.

The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion

PubMed Central

Borkowski, Piotr

2017-01-01

It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship’s current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships. PMID:28632176

MATSurv: multisensor air traffic surveillance system

NASA Astrophysics Data System (ADS)

Yeddanapudi, Murali; Bar-Shalom, Yaakov; Pattipati, Krishna R.; Gassner, Richard R.

1995-09-01

This paper deals with the design and implementation of MATSurv 1--an experimental Multisensor Air Traffic Surveillance system. The proposed system consists of a Kalman filter based state estimator used in conjunction with a 2D sliding window assignment algorithm. Real data from two FAA radars is used to evaluate the performance of this algorithm. The results indicate that the proposed algorithm provides a superior classification of the measurements into tracks (i.e., the most likely aircraft trajectories) when compared to the aircraft trajectories obtained using the measurement IDs (squawk or IFF code).

Visual Uav Trajectory Plan System Based on Network Map

NASA Astrophysics Data System (ADS)

Li, X. L.; Lin, Z. J.; Su, G. Z.; Wu, B. Y.

2012-07-01

The base map of the current software UP-30 using in trajectory plan for Unmanned Aircraft Vehicle is vector diagram. UP-30 draws navigation points manually. But in the field of operation process, the efficiency and the quality of work is influenced because of insufficient information, screen reflection, calculate inconveniently and other factors. If we do this work in indoor, the effect of external factors on the results would be eliminated, the network earth users can browse the free world high definition satellite images through downloading a client software, and can export the high resolution image by standard file format. This brings unprecedented convenient of trajectory plan. But the images must be disposed by coordinate transformation, geometric correction. In addition, according to the requirement of mapping scale ,camera parameters and overlap degree we can calculate exposure hole interval and trajectory distance between the adjacent trajectory automatically . This will improve the degree of automation of data collection. Software will judge the position of next point according to the intersection of the trajectory and the survey area and ensure the position of point according to trajectory distance. We can undertake the points artificially. So the trajectory plan is automatic and flexible. Considering safety, the date can be used in flying after simulating flight. Finally we can export all of the date using a key

Optimal short-range trajectories for helicopters

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

Slater, G.L.; Erzberger, H.

1982-12-01

An optimal flight path algorithm using a simplified altitude state model and a priori climb cruise descent flight profile was developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. In addition, a method was developed for obtaining a performance model in simplified form which is based on standard flight manual data and which is applicable to the computation of optimal trajectories. The entire performance optimization algorithm is simple enough that on line trajectory optimization is feasible with a relatively small computer. The helicopter model used is the Silorsky S-61N. Themore » results show that for this vehicle the optimal flight path and optimal cruise altitude can represent a 10% fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability because of helicopter weight, ambient winds, and the relative cost trade off between time and fuel. In general, reasonable variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost. For fuel optimal trajectories, the optimum cruise altitude varies from the maximum (12,000 ft) to the minimum (0 ft) depending on helicopter weight.« less

White matter fiber tracking computation based on diffusion tensor imaging for clinical applications.

PubMed

Dellani, Paulo R; Glaser, Martin; Wille, Paulo R; Vucurevic, Goran; Stadie, Axel; Bauermann, Thomas; Tropine, Andrei; Perneczky, Axel; von Wangenheim, Aldo; Stoeter, Peter

2007-03-01

Fiber tracking allows the in vivo reconstruction of human brain white matter fiber trajectories based on magnetic resonance diffusion tensor imaging (MR-DTI), but its application in the clinical routine is still in its infancy. In this study, we present a new software for fiber tracking, developed on top of a general-purpose DICOM (digital imaging and communications in medicine) framework, which can be easily integrated into existing picture archiving and communication system (PACS) of radiological institutions. Images combining anatomical information and the localization of different fiber tract trajectories can be encoded and exported in DICOM and Analyze formats, which are valuable resources in the clinical applications of this method. Fiber tracking was implemented based on existing line propagation algorithms, but it includes a heuristic for fiber crossings in the case of disk-shaped diffusion tensors. We successfully performed fiber tracking on MR-DTI data sets from 26 patients with different types of brain lesions affecting the corticospinal tracts. In all cases, the trajectories of the central spinal tract (pyramidal tract) were reconstructed and could be applied at the planning phase of the surgery as well as in intraoperative neuronavigation.

Trajectory Planning by Preserving Flexibility: Metrics and Analysis

NASA Technical Reports Server (NTRS)

Idris, Husni R.; El-Wakil, Tarek; Wing, David J.

2008-01-01

In order to support traffic management functions, such as mitigating traffic complexity, ground and airborne systems may benefit from preserving or optimizing trajectory flexibility. To help support this hypothesis trajectory flexibility metrics have been defined in previous work to represent the trajectory robustness and adaptability to the risk of violating safety and traffic management constraints. In this paper these metrics are instantiated in the case of planning a trajectory with the heading degree of freedom. A metric estimation method is presented based on simplifying assumptions, namely discrete time and heading maneuvers. A case is analyzed to demonstrate the estimation method and its use in trajectory planning in a situation involving meeting a time constraint and avoiding loss of separation with nearby traffic. The case involves comparing path-stretch trajectories, in terms of adaptability and robustness along each, deduced from a map of estimated flexibility metrics over the solution space. The case demonstrated anecdotally that preserving flexibility may result in enhancing certain factors that contribute to traffic complexity, namely reducing proximity and confrontation.

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

NASA Astrophysics Data System (ADS)

Gardi, Alessandro; Sabatini, Roberto; Ramasamy, Subramanian

2016-05-01

The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of automation were proposed for integrated flight planning and re-routing functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is provided. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, airspace and airport operations. A brief overview of atmospheric and weather modelling is also included. Key equations describing the optimality criteria are presented, with a focus on the latest advancements in the respective application areas. In the sixth section, a number of MOTO implementations in the CNS+A systems context are mentioned with relevant simulation case studies addressing different operational tasks. The final section draws some conclusions and outlines guidelines for future research on MOTO and associated CNS+A system implementations.

An Energy-Aware Trajectory Optimization Layer for sUAS

NASA Astrophysics Data System (ADS)

Silva, William A.

The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between EA-DDDAS components. Results also demonstrate the usage of the trajectory optimization layer in conjunction with a lattice-based path planner as a method of guiding the optimization layer and stitching together subsequent trajectories.

Registration of 4D time-series of cardiac images with multichannel Diffeomorphic Demons.

PubMed

Peyrat, Jean-Marc; Delingette, Hervé; Sermesant, Maxime; Pennec, Xavier; Xu, Chenyang; Ayache, Nicholas

2008-01-01

In this paper, we propose a generic framework for intersubject non-linear registration of 4D time-series images. In this framework, spatio-temporal registration is defined by mapping trajectories of physical points as opposed to spatial registration that solely aims at mapping homologous points. First, we determine the trajectories we want to register in each sequence using a motion tracking algorithm based on the Diffeomorphic Demons algorithm. Then, we perform simultaneously pairwise registrations of corresponding time-points with the constraint to map the same physical points over time. We show this trajectory registration can be formulated as a multichannel registration of 3D images. We solve it using the Diffeomorphic Demons algorithm extended to vector-valued 3D images. This framework is applied to the inter-subject non-linear registration of 4D cardiac CT sequences.

Modified Hyperspheres Algorithm to Trace Homotopy Curves of Nonlinear Circuits Composed by Piecewise Linear Modelled Devices

PubMed Central

Vazquez-Leal, H.; Jimenez-Fernandez, V. M.; Benhammouda, B.; Filobello-Nino, U.; Sarmiento-Reyes, A.; Ramirez-Pinero, A.; Marin-Hernandez, A.; Huerta-Chua, J.

2014-01-01

We present a homotopy continuation method (HCM) for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL) representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation. PMID:25184157

Neural correlates of learning and trajectory planning in the posterior parietal cortex

PubMed Central

Torres, Elizabeth B.; Quian Quiroga, Rodrigo; Cui, He; Buneo, Christopher A.

2013-01-01

The posterior parietal cortex (PPC) is thought to play an important role in the planning of visually-guided reaching movements. However, the relative roles of the various subdivisions of the PPC in this function are still poorly understood. For example, studies of dorsal area 5 point to a representation of reaches in both extrinsic (endpoint) and intrinsic (joint or muscle) coordinates, as evidenced by partial changes in preferred directions and positional discharge with changes in arm posture. In contrast, recent findings suggest that the adjacent medial intraparietal area (MIP) is involved in more abstract representations, e.g., encoding reach target in visual coordinates. Such a representation is suitable for planning reach trajectories involving shortest distance paths to targets straight ahead. However, it is currently unclear how MIP contributes to the planning of other types of trajectories, including those with various degrees of curvature. Such curved trajectories recruit different joint excursions and might help us address whether their representation in the PPC is purely in extrinsic coordinates or in intrinsic ones as well. Here we investigated the role of the PPC in these processes during an obstacle avoidance task for which the animals had not been explicitly trained. We found that PPC planning activity was predictive of both the spatial and temporal aspects of upcoming trajectories. The same PPC neurons predicted the upcoming trajectory in both endpoint and joint coordinates. The predictive power of these neurons remained stable and accurate despite concomitant motor learning across task conditions. These findings suggest the role of the PPC can be extended from specifying abstract movement goals to expressing these plans as corresponding trajectories in both endpoint and joint coordinates. Thus, the PPC appears to contribute to reach planning and approach-avoidance arm motions at multiple levels of representation. PMID:23730275

Planning strategies for the Ambler walking robot

NASA Technical Reports Server (NTRS)

Wettergreen, David; Thomas, Hans; Thorpe, Chuck

1990-01-01

A hierarchy of planning strategies is proposed and explained for a walking robot called the Ambler. The hierarchy decomposes planning into levels of trajectory, gait, and footfall. An abstraction of feasible traversability allows the Ambler's trajectory planner to identify acceptable trajectories by finding paths that guarantee footfalls without specifying exactly which footfalls. Leg and body moves that achieve this trajectory can be generated by the Ambler's gait planner, which incorporates pattern constraints and measures of utility to search for the best next move. By combining constraints from the quality and details of the terrain, the Ambler's footfall planner can select footfalls that insure stability and remain within the tolerances of the gait.

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

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

Boardman, Beth Leigh

The common theme of this dissertation is sampling-based motion planning with the two key contributions being in the area of replanning and spatial load balancing for robotic systems. Here, we begin by recalling two sampling-based motion planners: the asymptotically optimal rapidly-exploring random tree (RRT*), and the asymptotically optimal probabilistic roadmap (PRM*). We also provide a brief background on collision cones and the Distributed Reactive Collision Avoidance (DRCA) algorithm. The next four chapters detail novel contributions for motion replanning in environments with unexpected static obstacles, for multi-agent collision avoidance, and spatial load balancing. First, we show improved performance of the RRT*more » when using the proposed Grandparent-Connection (GP) or Focused-Refinement (FR) algorithms. Next, the Goal Tree algorithm for replanning with unexpected static obstacles is detailed and proven to be asymptotically optimal. A multi-agent collision avoidance problem in obstacle environments is approached via the RRT*, leading to the novel Sampling-Based Collision Avoidance (SBCA) algorithm. The SBCA algorithm is proven to guarantee collision free trajectories for all of the agents, even when subject to uncertainties in the knowledge of the other agents’ positions and velocities. Given that a solution exists, we prove that livelocks and deadlock will lead to the cost to the goal being decreased. We introduce a new deconfliction maneuver that decreases the cost-to-come at each step. This new maneuver removes the possibility of livelocks and allows a result to be formed that proves convergence to the goal configurations. Finally, we present a limited range Graph-based Spatial Load Balancing (GSLB) algorithm which fairly divides a non-convex space among multiple agents that are subject to differential constraints and have a limited travel distance. The GSLB is proven to converge to a solution when maximizing the area covered by the agents. The analysis for each of the above mentioned algorithms is confirmed in simulations.« less

Learning by Demonstration for Motion Planning of Upper-Limb Exoskeletons

PubMed Central

Lauretti, Clemente; Cordella, Francesca; Ciancio, Anna Lisa; Trigili, Emilio; Catalan, Jose Maria; Badesa, Francisco Javier; Crea, Simona; Pagliara, Silvio Marcello; Sterzi, Silvia; Vitiello, Nicola; Garcia Aracil, Nicolas; Zollo, Loredana

2018-01-01

The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesian motion planners and inverse kinematics algorithms with the inverse Jacobian; this approach allows exploiting the available Degrees of Freedom (i.e. DoFs) of the robot kinematic chain to achieve the desired end-effector pose; however, if used to operate non-redundant exoskeletons, it does not ensure that anthropomorphic criteria are satisfied in the whole human-robot workspace. This paper proposes a motion planning system, based on Learning by Demonstration, for upper-limb exoskeletons that allow successfully assisting patients during Activities of Daily Living (ADLs) in unstructured environment, while ensuring that anthropomorphic criteria are satisfied in the whole human-robot workspace. The motion planning system combines Learning by Demonstration with the computation of Dynamic Motion Primitives and machine learning techniques to construct task- and patient-specific joint trajectories based on the learnt trajectories. System validation was carried out in simulation and in a real setting with a 4-DoF upper-limb exoskeleton, a 5-DoF wrist-hand exoskeleton and four patients with Limb Girdle Muscular Dystrophy. Validation was addressed to (i) compare the performance of the proposed motion planning with traditional methods; (ii) assess the generalization capabilities of the proposed method with respect to the environment variability. Three ADLs were chosen to validate the system: drinking, pouring and lifting a light sphere. The achieved results showed a 100% success rate in the task fulfillment, with a high level of generalization with respect to the environment variability. Moreover, an anthropomorphic configuration of the exoskeleton is always ensured. PMID:29527161

Learning by Demonstration for Motion Planning of Upper-Limb Exoskeletons.

PubMed

Lauretti, Clemente; Cordella, Francesca; Ciancio, Anna Lisa; Trigili, Emilio; Catalan, Jose Maria; Badesa, Francisco Javier; Crea, Simona; Pagliara, Silvio Marcello; Sterzi, Silvia; Vitiello, Nicola; Garcia Aracil, Nicolas; Zollo, Loredana

2018-01-01

The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesian motion planners and inverse kinematics algorithms with the inverse Jacobian; this approach allows exploiting the available Degrees of Freedom (i.e. DoFs) of the robot kinematic chain to achieve the desired end-effector pose; however, if used to operate non-redundant exoskeletons, it does not ensure that anthropomorphic criteria are satisfied in the whole human-robot workspace. This paper proposes a motion planning system, based on Learning by Demonstration, for upper-limb exoskeletons that allow successfully assisting patients during Activities of Daily Living (ADLs) in unstructured environment, while ensuring that anthropomorphic criteria are satisfied in the whole human-robot workspace. The motion planning system combines Learning by Demonstration with the computation of Dynamic Motion Primitives and machine learning techniques to construct task- and patient-specific joint trajectories based on the learnt trajectories. System validation was carried out in simulation and in a real setting with a 4-DoF upper-limb exoskeleton, a 5-DoF wrist-hand exoskeleton and four patients with Limb Girdle Muscular Dystrophy. Validation was addressed to (i) compare the performance of the proposed motion planning with traditional methods; (ii) assess the generalization capabilities of the proposed method with respect to the environment variability. Three ADLs were chosen to validate the system: drinking, pouring and lifting a light sphere. The achieved results showed a 100% success rate in the task fulfillment, with a high level of generalization with respect to the environment variability. Moreover, an anthropomorphic configuration of the exoskeleton is always ensured.

Global, Multi-Objective Trajectory Optimization With Parametric Spreading

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.

2017-01-01

Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

A Parallel Processing and Diversified-Hidden-Gene-Based Genetic Algorithm Framework for Fuel-Optimal Trajectory Design for Interplanetary Spacecraft Missions

NASA Astrophysics Data System (ADS)

Somavarapu, Dhathri H.

This thesis proposes a new parallel computing genetic algorithm framework for designing fuel-optimal trajectories for interplanetary spacecraft missions. The framework can capture the deep search space of the problem with the use of a fixed chromosome structure and hidden-genes concept, can explore the diverse set of candidate solutions with the use of the adaptive and twin-space crowding techniques and, can execute on any high-performance computing (HPC) platform with the adoption of the portable message passing interface (MPI) standard. The algorithm is implemented in C++ with the use of the MPICH implementation of the MPI standard. The algorithm uses a patched-conic approach with two-body dynamics assumptions. New procedures are developed for determining trajectories in the Vinfinity-leveraging legs of the flight from the launch and non-launch planets and, deep-space maneuver legs of the flight from the launch and non-launch planets. The chromosome structure maintains the time of flight as a free parameter within certain boundaries. The fitness or the cost function of the algorithm uses only the mission Delta V, and does not include time of flight. The optimization is conducted with two variations for the minimum mission gravity-assist sequence, the 4-gravity-assist, and the 3-gravity-assist, with a maximum of 5 gravity-assists allowed in both the cases. The optimal trajectories discovered using the framework in both of the cases demonstrate the success of this framework.

Noncoplanar VMAT for nasopharyngeal tumors: Plan quality versus treatment time.

PubMed

Wild, Esther; Bangert, Mark; Nill, Simeon; Oelfke, Uwe

2015-05-01

The authors investigated the potential of optimized noncoplanar irradiation trajectories for volumetric modulated arc therapy (VMAT) treatments of nasopharyngeal patients and studied the trade-off between treatment plan quality and delivery time in radiation therapy. For three nasopharyngeal patients, the authors generated treatment plans for nine different delivery scenarios using dedicated optimization methods. They compared these scenarios according to dose characteristics, number of beam directions, and estimated delivery times. In particular, the authors generated the following treatment plans: (1) a 4π plan, which is a not sequenced, fluence optimized plan that uses beam directions from approximately 1400 noncoplanar directions and marks a theoretical upper limit of the treatment plan quality, (2) a coplanar 2π plan with 72 coplanar beam directions as pendant to the noncoplanar 4π plan, (3) a coplanar VMAT plan, (4) a coplanar step and shoot (SnS) plan, (5) a beam angle optimized (BAO) coplanar SnS IMRT plan, (6) a noncoplanar BAO SnS plan, (7) a VMAT plan with rotated treatment couch, (8) a noncoplanar VMAT plan with an optimized great circle around the patient, and (9) a noncoplanar BAO VMAT plan with an arbitrary trajectory around the patient. VMAT using optimized noncoplanar irradiation trajectories reduced the mean and maximum doses in organs at risk compared to coplanar VMAT plans by 19% on average while the target coverage remains constant. A coplanar BAO SnS plan was superior to coplanar SnS or VMAT; however, noncoplanar plans like a noncoplanar BAO SnS plan or noncoplanar VMAT yielded a better plan quality than the best coplanar 2π plan. The treatment plan quality of VMAT plans depended on the length of the trajectory. The delivery times of noncoplanar VMAT plans were estimated to be 6.5 min in average; 1.6 min longer than a coplanar plan but on average 2.8 min faster than a noncoplanar SnS plan with comparable treatment plan quality. The authors' study reconfirms the dosimetric benefits of noncoplanar irradiation of nasopharyngeal tumors. Both SnS using optimized noncoplanar beam ensembles and VMAT using an optimized, arbitrary, noncoplanar trajectory enabled dose reductions in organs at risk compared to coplanar SnS and VMAT. Using great circles or simple couch rotations to implement noncoplanar VMAT, however, was not sufficient to yield meaningful improvements in treatment plan quality. The authors estimate that noncoplanar VMAT using arbitrary optimized irradiation trajectories comes at an increased delivery time compared to coplanar VMAT yet at a decreased delivery time compared to noncoplanar SnS IMRT.

Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

NASA Astrophysics Data System (ADS)

Khoshahval, S.; Farnaghi, M.; Taleai, M.

2017-09-01

Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

Exercise recognition for Kinect-based telerehabilitation.

PubMed

Antón, D; Goñi, A; Illarramendi, A

2015-01-01

An aging population and people's higher survival to diseases and traumas that leave physical consequences are challenging aspects in the context of an efficient health management. This is why telerehabilitation systems are being developed, to allow monitoring and support of physiotherapy sessions at home, which could reduce healthcare costs while also improving the quality of life of the users. Our goal is the development of a Kinect-based algorithm that provides a very accurate real-time monitoring of physical rehabilitation exercises and that also provides a friendly interface oriented both to users and physiotherapists. The two main constituents of our algorithm are the posture classification method and the exercises recognition method. The exercises consist of series of movements. Each movement is composed of an initial posture, a final posture and the angular trajectories of the limbs involved in the movement. The algorithm was designed and tested with datasets of real movements performed by volunteers. We also explain in the paper how we obtained the optimal values for the trade-off values for posture and trajectory recognition. Two relevant aspects of the algorithm were evaluated in our tests, classification accuracy and real-time data processing. We achieved 91.9% accuracy in posture classification and 93.75% accuracy in trajectory recognition. We also checked whether the algorithm was able to process the data in real-time. We found that our algorithm could process more than 20,000 postures per second and all the required trajectory data-series in real-time, which in practice guarantees no perceptible delays. Later on, we carried out two clinical trials with real patients that suffered shoulder disorders. We obtained an exercise monitoring accuracy of 95.16%. We present an exercise recognition algorithm that handles the data provided by Kinect efficiently. The algorithm has been validated in a real scenario where we have verified its suitability. Moreover, we have received a positive feedback from both users and the physiotherapists who took part in the tests.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

PubMed

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of these two fields results in a safe path planning algorithm, with a deterministic outcome, to navigate agents to their desired goals.

A Centered Projective Algorithm for Linear Programming

DTIC Science & Technology

1988-02-01

zx/l to (PA Karmarkar’s algorithm iterates this procedure. An alternative method, the so-called affine variant (first proposed by Dikin [6] in 1967...trajectories, II. Legendre transform coordinates . central trajectories," manuscripts, to appear in Transactions of the American [6] I.I. Dikin ...34Iterative solution of problems of linear and quadratic programming," Soviet Mathematics Dokladv 8 (1967), 674-675. [7] I.I. Dikin , "On the speed of an

Automatic segmentation of the facial nerve and chorda tympani using image registration and statistical priors

NASA Astrophysics Data System (ADS)

Noble, Jack H.; Warren, Frank M.; Labadie, Robert F.; Dawant, Benoit M.

2008-03-01

In cochlear implant surgery, an electrode array is permanently implanted in the cochlea to stimulate the auditory nerve and allow deaf people to hear. A minimally invasive surgical technique has recently been proposed--percutaneous cochlear access--in which a single hole is drilled from the skull surface to the cochlea. For the method to be feasible, a safe and effective drilling trajectory must be determined using a pre-operative CT. Segmentation of the structures of the ear would improve trajectory planning safety and efficiency and enable the possibility of automated planning. Two important structures of the ear, the facial nerve and chorda tympani, present difficulties in intensity based segmentation due to their diameter (as small as 1.0 and 0.4 mm) and adjacent inter-patient variable structures of similar intensity in CT imagery. A multipart, model-based segmentation algorithm is presented in this paper that accomplishes automatic segmentation of the facial nerve and chorda tympani. Segmentation results are presented for 14 test ears and are compared to manually segmented surfaces. The results show that mean error in structure wall localization is 0.2 and 0.3 mm for the facial nerve and chorda, proving the method we propose is robust and accurate.

Conflict-free trajectory planning for air traffic control automation

NASA Technical Reports Server (NTRS)

Slattery, Rhonda; Green, Steve

1994-01-01

As the traffic demand continues to grow within the National Airspace System (NAS), the need for long-range planning (30 minutes plus) of arrival traffic increases greatly. Research into air traffic control (ATC) automation at ARC has led to the development of the Center-TRACON Automation System (CTAS). CTAS determines optimum landing schedules for arrival traffic and assists controllers in meeting those schedules safely and efficiently. One crucial element in the development of CTAS is the capability to perform long-range (20 minutes) and short-range (5 minutes) conflict prediction and resolution once landing schedules are determined. The determination of conflict-free trajectories within the Center airspace is particularly difficult because of large variations in speed and altitude. The paper describes the current design and implementation of the conflict prediction and resolution tools used to generate CTAS advisories in Center airspace. Conflict criteria (separation requirements) are defined and the process of separation prediction is described. The major portion of the paper will describe the current implementation of CTAS conflict resolution algorithms in terms of the degrees of freedom for resolutions as well as resolution search techniques. The tools described in this paper have been implemented in a research system designed to rapidly develop and evaluate prototype concepts and will form the basis for an operational ATC automation system.

Motion control of the rabbit ankle joint with a flat interface nerve electrode.

PubMed

Park, Hyun-Joo; Durand, Dominique M

2015-12-01

A flat interface nerve electrode (FINE) has been shown to improve fascicular and subfascicular selectivity. A recently developed novel control algorithm for FINE was applied to motion control of the rabbit ankle. A 14-contact FINE was placed on the rabbit sciatic nerve (n = 8), and ankle joint motion was controlled for sinusoidal trajectories and filtered random trajectories. To this end, a real-time controller was implemented with a multiple-channel current stimulus isolator. The performance test results showed good tracking performance of rabbit ankle joint motion for filtered random trajectories and sinusoidal trajectories (0.5 Hz and 1.0 Hz) with <10% average root-mean-square (RMS) tracking error, whereas the average range of ankle joint motion was between -20.0 ± 9.3° and 18.1 ± 8.8°. The proposed control algorithm enables the use of a multiple-contact nerve electrode for motion trajectory tracking control of musculoskeletal systems. © 2015 Wiley Periodicals, Inc.

Rapid design and optimization of low-thrust rendezvous/interception trajectory for asteroid deflection missions

NASA Astrophysics Data System (ADS)

Li, Shuang; Zhu, Yongsheng; Wang, Yukai

2014-02-01

Asteroid deflection techniques are essential in order to protect the Earth from catastrophic impacts by hazardous asteroids. Rapid design and optimization of low-thrust rendezvous/interception trajectories is considered as one of the key technologies to successfully deflect potentially hazardous asteroids. In this paper, we address a general framework for the rapid design and optimization of low-thrust rendezvous/interception trajectories for future asteroid deflection missions. The design and optimization process includes three closely associated steps. Firstly, shape-based approaches and genetic algorithm (GA) are adopted to perform preliminary design, which provides a reasonable initial guess for subsequent accurate optimization. Secondly, Radau pseudospectral method is utilized to transcribe the low-thrust trajectory optimization problem into a discrete nonlinear programming (NLP) problem. Finally, sequential quadratic programming (SQP) is used to efficiently solve the nonlinear programming problem and obtain the optimal low-thrust rendezvous/interception trajectories. The rapid design and optimization algorithms developed in this paper are validated by three simulation cases with different performance indexes and boundary constraints.

Decentralized control algorithms of a group of vehicles in 2D space

NASA Astrophysics Data System (ADS)

Pshikhopov, V. K.; Medvedev, M. Y.; Fedorenko, R. V.; Gurenko, B. V.

2017-02-01

The problem of decentralized control of group of robots, described by kinematic and dynamic equations of motion in the plane, is considered. Group performs predetermined rectangular area passing at a fixed speed, keeping the line and a uniform distribution. The environment may contain a priori unknown moving or stationary obstacles. Decentralized control algorithms, based on the formation of repellers in the state space of robots, are proposed. These repellers form repulsive forces generated by dynamic subsystems that extend the state space of robots. These repulsive forces are dynamic functions of distances and velocities of robots in the area of operation of the group. The process of formation of repellers allows to take into account the dynamic properties of robots, such as the maximum speed and acceleration. The robots local control law formulas are derived based on positionally-trajectory control method, which allows to operate with non-linear models. Lyapunov function in the form of a quadratic function of the state variables is constructed to obtain a nonlinear closed-loop control system. Due to the fact that a closed system is decomposed into two independent subsystems Lyapunov function is also constructed as two independent functions. Numerical simulation of the motion of a group of five robots is presented. In this simulation obstacles are presented by the boundaries of working area and a movable object of a given radius, moving rectilinear and uniform. Obstacle speed is comparable to the speeds of the robots in a group. The advantage of the proposed method is ensuring the stability of the trajectories and consideration of the limitations on the speed and acceleration at the trajectory planning stage. Proposed approach can be used for more general robots' models, including robots in the three-dimensional environment.

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

PubMed

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the proposed methodology results in fewer catheters without a clinically significant loss in plan quality. The proposed approach can be used as a decision support tool that guides the user to find the ideal number and configuration of catheters. © 2017 American Association of Physicists in Medicine.

A New Technique for Compensating Joint Limits in a Robot Manipulator

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Hickman, Andre; Guo, Ten-Huei

1996-01-01

A new robust, optimal, adaptive technique for compensating rate and position limits in the joints of a six degree-of-freedom elbow manipulator is presented. In this new algorithm, the unmet demand as a result of actuator saturation is redistributed among the remaining unsaturated joints. The scheme is used to compensate for inadequate path planning, problems such as joint limiting, joint freezing, or even obstacle avoidance, where a desired position and orientation are not attainable due to an unrealizable joint command. Once a joint encounters a limit, supplemental commands are sent to other joints to best track, according to a selected criterion, the desired trajectory.

An analytic model for footprint dispersions and its application to mission design

NASA Technical Reports Server (NTRS)

Rao, J. R. Jagannatha; Chen, Yi-Chao

1992-01-01

This is the final report on our recent research activities that are complementary to those conducted by our colleagues, Professor Farrokh Mistree and students, in the context of the Taguchi method. We have studied the mathematical model that forms the basis of the Simulation and Optimization of Rocket Trajectories (SORT) program and developed an analytic method for determining mission reliability with a reduced number of flight simulations. This method can be incorporated in a design algorithm to mathematically optimize different performance measures of a mission, thus leading to a robust and easy-to-use methodology for mission planning and design.

Drivers’ Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving

PubMed Central

Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

2016-01-01

This paper describes a real-time motion planner based on the drivers’ visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers’ visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers’ visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms. PMID:26784203

Drivers' Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving.

PubMed

Du, Mingbo; Mei, Tao; Liang, Huawei; Chen, Jiajia; Huang, Rulin; Zhao, Pan

2016-01-15

This paper describes a real-time motion planner based on the drivers' visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers' visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers' visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms.

Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration

NASA Technical Reports Server (NTRS)

Scott, James R.; Martini, Michael C.

2011-01-01

A variable-order, variable-step Taylor series integration algorithm was implemented in NASA Glenn's SNAP (Spacecraft N-body Analysis Program) code. SNAP is a high-fidelity trajectory propagation program that can propagate the trajectory of a spacecraft about virtually any body in the solar system. The Taylor series algorithm's very high order accuracy and excellent stability properties lead to large reductions in computer time relative to the code's existing 8th order Runge-Kutta scheme. Head-to-head comparison on near-Earth, lunar, Mars, and Europa missions showed that Taylor series integration is 15.8 times faster than Runge- Kutta on average, and is more accurate. These speedups were obtained for calculations involving central body, other body, thrust, and drag forces. Similar speedups have been obtained for calculations that include J2 spherical harmonic for central body gravitation. The algorithm includes a step size selection method that directly calculates the step size and never requires a repeat step. High-order Taylor series integration algorithms have been shown to provide major reductions in computer time over conventional integration methods in numerous scientific applications. The objective here was to directly implement Taylor series integration in an existing trajectory analysis code and demonstrate that large reductions in computer time (order of magnitude) could be achieved while simultaneously maintaining high accuracy. This software greatly accelerates the calculation of spacecraft trajectories. At each time level, the spacecraft position, velocity, and mass are expanded in a high-order Taylor series whose coefficients are obtained through efficient differentiation arithmetic. This makes it possible to take very large time steps at minimal cost, resulting in large savings in computer time. The Taylor series algorithm is implemented primarily through three subroutines: (1) a driver routine that automatically introduces auxiliary variables and sets up initial conditions and integrates; (2) a routine that calculates system reduced derivatives using recurrence relations for quotients and products; and (3) a routine that determines the step size and sums the series. The order of accuracy used in a trajectory calculation is arbitrary and can be set by the user. The algorithm directly calculates the motion of other planetary bodies and does not require ephemeris files (except to start the calculation). The code also runs with Taylor series and Runge-Kutta used interchangeably for different phases of a mission.

Guidance and Control Algorithms for the Mars Entry, Descent and Landing Systems Analysis

NASA Technical Reports Server (NTRS)

Davis, Jody L.; CwyerCianciolo, Alicia M.; Powell, Richard W.; Shidner, Jeremy D.; Garcia-Llama, Eduardo

2010-01-01

The purpose of the Mars Entry, Descent and Landing Systems Analysis (EDL-SA) study was to identify feasible technologies that will enable human exploration of Mars, specifically to deliver large payloads to the Martian surface. This paper focuses on the methods used to guide and control two of the contending technologies, a mid- lift-to-drag (L/D) rigid aeroshell and a hypersonic inflatable aerodynamic decelerator (HIAD), through the entry portion of the trajectory. The Program to Optimize Simulated Trajectories II (POST2) is used to simulate and analyze the trajectories of the contending technologies and guidance and control algorithms. Three guidance algorithms are discussed in this paper: EDL theoretical guidance, Numerical Predictor-Corrector (NPC) guidance and Analytical Predictor-Corrector (APC) guidance. EDL-SA also considered two forms of control: bank angle control, similar to that used by Apollo and the Space Shuttle, and a center-of-gravity (CG) offset control. This paper presents the performance comparison of these guidance algorithms and summarizes the results as they impact the technology recommendations for future study.

Aircraft path planning for optimal imaging using dynamic cost functions

NASA Astrophysics Data System (ADS)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

Trajectory planning and control of a 6 DOF manipulator with Stewart platform-based mechanism

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Antrazi, Sami

1990-01-01

The trajectory planning and control was studied of a robot manipulator that has 6 degrees of freedom and was designed based on the mechanism of the Stewart Platform. First the main components of the manipulator is described along with its operation. The solutions are briefly prescribed for the forward and inverse kinematics of the manipulator. After that, two trajectory planning schemes are developed using the manipulator inverse kinematics to track straight lines and circular paths. Finally experiments conducted to study the performance of the developed planning schemes in tracking a straight line and a circle are presented and discussed.

OPTIMAL AIRCRAFT TRAJECTORIES FOR SPECIFIED RANGE

NASA Technical Reports Server (NTRS)

Lee, H.

1994-01-01

For an aircraft operating over a fixed range, the operating costs are basically a sum of fuel cost and time cost. While minimum fuel and minimum time trajectories are relatively easy to calculate, the determination of a minimum cost trajectory can be a complex undertaking. This computer program was developed to optimize trajectories with respect to a cost function based on a weighted sum of fuel cost and time cost. As a research tool, the program could be used to study various characteristics of optimum trajectories and their comparison to standard trajectories. It might also be used to generate a model for the development of an airborne trajectory optimization system. The program could be incorporated into an airline flight planning system, with optimum flight plans determined at takeoff time for the prevailing flight conditions. The use of trajectory optimization could significantly reduce the cost for a given aircraft mission. The algorithm incorporated in the program assumes that a trajectory consists of climb, cruise, and descent segments. The optimization of each segment is not done independently, as in classical procedures, but is performed in a manner which accounts for interaction between the segments. This is accomplished by the application of optimal control theory. The climb and descent profiles are generated by integrating a set of kinematic and dynamic equations, where the total energy of the aircraft is the independent variable. At each energy level of the climb and descent profiles, the air speed and power setting necessary for an optimal trajectory are determined. The variational Hamiltonian of the problem consists of the rate of change of cost with respect to total energy and a term dependent on the adjoint variable, which is identical to the optimum cruise cost at a specified altitude. This variable uniquely specifies the optimal cruise energy, cruise altitude, cruise Mach number, and, indirectly, the climb and descent profiles. If the optimum cruise cost is specified, an optimum trajectory can easily be generated; however, the range obtained for a particular optimum cruise cost is not known a priori. For short range flights, the program iteratively varies the optimum cruise cost until the computed range converges to the specified range. For long-range flights, iteration is unnecessary since the specified range can be divided into a cruise segment distance and full climb and descent distances. The user must supply the program with engine fuel flow rate coefficients and an aircraft aerodynamic model. The program currently includes coefficients for the Pratt-Whitney JT8D-7 engine and an aerodynamic model for the Boeing 727. Input to the program consists of the flight range to be covered and the prevailing flight conditions including pressure, temperature, and wind profiles. Information output by the program includes: optimum cruise tables at selected weights, optimal cruise quantities as a function of cruise weight and cruise distance, climb and descent profiles, and a summary of the complete synthesized optimal trajectory. This program is written in FORTRAN IV for batch execution and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 100K (octal) of 60 bit words. This aircraft trajectory optimization program was developed in 1979.

Design factors and considerations for a time-based flight management system

NASA Technical Reports Server (NTRS)

Vicroy, D. D.; Williams, D. H.; Sorensen, J. A.

1986-01-01

Recent NASA Langley Research Center research to develop a technology data base from which an advanced Flight Management System (FMS) design might evolve is reviewed. In particular, the generation of fixed range cruise/descent reference trajectories which meet predefined end conditions of altitude, speed, and time is addressed. Results on the design and theoretical basis of the trajectory generation algorithm are presented, followed by a brief discussion of a series of studies that are being conducted to determine the accuracy requirements of the aircraft and weather models resident in the trajectory generation algorithm. Finally, studies to investigate the interface requirements between the pilot and an advanced FMS are considered.

A Probabilistic Framework for Constructing Temporal Relations in Replica Exchange Molecular Trajectories.

PubMed

Chattopadhyay, Aditya; Zheng, Min; Waller, Mark Paul; Priyakumar, U Deva

2018-05-23

Knowledge of the structure and dynamics of biomolecules is essential for elucidating the underlying mechanisms of biological processes. Given the stochastic nature of many biological processes, like protein unfolding, it's almost impossible that two independent simulations will generate the exact same sequence of events, which makes direct analysis of simulations difficult. Statistical models like Markov Chains, transition networks etc. help in shedding some light on the mechanistic nature of such processes by predicting long-time dynamics of these systems from short simulations. However, such methods fall short in analyzing trajectories with partial or no temporal information, for example, replica exchange molecular dynamics or Monte Carlo simulations. In this work we propose a probabilistic algorithm, borrowing concepts from graph theory and machine learning, to extract reactive pathways from molecular trajectories in the absence of temporal data. A suitable vector representation was chosen to represent each frame in the macromolecular trajectory (as a series of interaction and conformational energies) and dimensionality reduction was performed using principal component analysis (PCA). The trajectory was then clustered using a density-based clustering algorithm, where each cluster represents a metastable state on the potential energy surface (PES) of the biomolecule under study. A graph was created with these clusters as nodes with the edges learnt using an iterative expectation maximization algorithm. The most reactive path is conceived as the widest path along this graph. We have tested our method on RNA hairpin unfolding trajectory in aqueous urea solution. Our method makes the understanding of the mechanism of unfolding in RNA hairpin molecule more tractable. As this method doesn't rely on temporal data it can be used to analyze trajectories from Monte Carlo sampling techniques and replica exchange molecular dynamics (REMD).

A path planning method for robot end effector motion using the curvature theory of the ruled surfaces

NASA Astrophysics Data System (ADS)

Güler, Fatma; Kasap, Emin

Using the curvature theory for the ruled surfaces a technique for robot trajectory planning is presented. This technique ensures the calculation of robot’s next path. The positional variation of the Tool Center Point (TCP), linear velocity, angular velocity are required in the work area of the robot. In some circumstances, it may not be physically achievable and a re-computation of the robot trajectory might be necessary. This technique is suitable for re-computation of the robot trajectory. We obtain different robot trajectories which change depending on the darboux angle function and define trajectory ruled surface family with a common trajectory curve with the rotation trihedron. Also, the motion of robot end effector is illustrated with examples.

Automated maneuver planning using a fuzzy logic algorithm

NASA Technical Reports Server (NTRS)

Conway, D.; Sperling, R.; Folta, D.; Richon, K.; Defazio, R.

1994-01-01

Spacecraft orbital control requires intensive interaction between the analyst and the system used to model the spacecraft trajectory. For orbits with right mission constraints and a large number of maneuvers, this interaction is difficult or expensive to accomplish in a timely manner. Some automation of maneuver planning can reduce these difficulties for maneuver-intensive missions. One approach to this automation is to use fuzzy logic in the control mechanism. Such a prototype system currently under development is discussed. The Tropical Rainfall Measurement Mission (TRMM) is one of several missions that could benefit from automated maneuver planning. TRMM is scheduled for launch in August 1997. The spacecraft is to be maintained in a 350-km circular orbit throughout the 3-year lifetime of the mission, with very small variations in this orbit allowed. Since solar maximum will occur as early as 1999, the solar activity during the TRMM mission will be increasing. The increasing solar activity will result in orbital maneuvers being performed as often as every other day. The results of automated maneuver planning for the TRMM mission will be presented to demonstrate the prototype of the fuzzy logic tool.

Learning from Demonstration: Generalization via Task Segmentation

NASA Astrophysics Data System (ADS)

Ettehadi, N.; Manaffam, S.; Behal, A.

2017-10-01

In this paper, a motion segmentation algorithm design is presented with the goal of segmenting a learned trajectory from demonstration such that each segment is locally maximally different from its neighbors. This segmentation is then exploited to appropriately scale (dilate/squeeze and/or rotate) a nominal trajectory learned from a few demonstrations on a fixed experimental setup such that it is applicable to different experimental settings without expanding the dataset and/or retraining the robot. The algorithm is computationally efficient in the sense that it allows facile transition between different environments. Experimental results using the Baxter robotic platform showcase the ability of the algorithm to accurately transfer a feeding task.

Noncoplanar VMAT for nasopharyngeal tumors: Plan quality versus treatment time

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

Wild, Esther, E-mail: e.wild@dkfz.de; Bangert, Mark; Nill, Simeon

Purpose: The authors investigated the potential of optimized noncoplanar irradiation trajectories for volumetric modulated arc therapy (VMAT) treatments of nasopharyngeal patients and studied the trade-off between treatment plan quality and delivery time in radiation therapy. Methods: For three nasopharyngeal patients, the authors generated treatment plans for nine different delivery scenarios using dedicated optimization methods. They compared these scenarios according to dose characteristics, number of beam directions, and estimated delivery times. In particular, the authors generated the following treatment plans: (1) a 4π plan, which is a not sequenced, fluence optimized plan that uses beam directions from approximately 1400 noncoplanar directionsmore » and marks a theoretical upper limit of the treatment plan quality, (2) a coplanar 2π plan with 72 coplanar beam directions as pendant to the noncoplanar 4π plan, (3) a coplanar VMAT plan, (4) a coplanar step and shoot (SnS) plan, (5) a beam angle optimized (BAO) coplanar SnS IMRT plan, (6) a noncoplanar BAO SnS plan, (7) a VMAT plan with rotated treatment couch, (8) a noncoplanar VMAT plan with an optimized great circle around the patient, and (9) a noncoplanar BAO VMAT plan with an arbitrary trajectory around the patient. Results: VMAT using optimized noncoplanar irradiation trajectories reduced the mean and maximum doses in organs at risk compared to coplanar VMAT plans by 19% on average while the target coverage remains constant. A coplanar BAO SnS plan was superior to coplanar SnS or VMAT; however, noncoplanar plans like a noncoplanar BAO SnS plan or noncoplanar VMAT yielded a better plan quality than the best coplanar 2π plan. The treatment plan quality of VMAT plans depended on the length of the trajectory. The delivery times of noncoplanar VMAT plans were estimated to be 6.5 min in average; 1.6 min longer than a coplanar plan but on average 2.8 min faster than a noncoplanar SnS plan with comparable treatment plan quality. Conclusions: The authors’ study reconfirms the dosimetric benefits of noncoplanar irradiation of nasopharyngeal tumors. Both SnS using optimized noncoplanar beam ensembles and VMAT using an optimized, arbitrary, noncoplanar trajectory enabled dose reductions in organs at risk compared to coplanar SnS and VMAT. Using great circles or simple couch rotations to implement noncoplanar VMAT, however, was not sufficient to yield meaningful improvements in treatment plan quality. The authors estimate that noncoplanar VMAT using arbitrary optimized irradiation trajectories comes at an increased delivery time compared to coplanar VMAT yet at a decreased delivery time compared to noncoplanar SnS IMRT.« less

An Efficient Universal Trajectory Language

NASA Technical Reports Server (NTRS)

Hagen, George E.; Guerreiro, Nelson M.; Maddalon, Jeffrey M.; Butler, Ricky W.

2017-01-01

The Efficient Universal Trajectory Language (EUTL) is a language for specifying and representing trajectories for Air Traffic Management (ATM) concepts such as Trajectory-Based Operations (TBO). In these concepts, the communication of a trajectory between an aircraft and ground automation is fundamental. Historically, this trajectory exchange has not been done, leading to trajectory definitions that have been centered around particular application domains and, therefore, are not well suited for TBO applications. The EUTL trajectory language has been defined in the Prototype Verification System (PVS) formal specification language, which provides an operational semantics for the EUTL language. The hope is that EUTL will provide a foundation for mathematically verified algorithms that manipulate trajectories. Additionally, the EUTL language provides well-defined methods to unambiguously determine position and velocity information between the reported trajectory points. In this paper, we present the EUTL trajectory language in mathematical detail.

Planification de trajectoires pour placement automatise de fibres sur surfaces de geometries complexes

NASA Astrophysics Data System (ADS)

Hely, Clement

During the past 50 years, the use of composite materials drastically increase, mainly thanks to the interest of aeronautical industries for these strong and lightweight materials. To improve the productivity of composite materials manufacturing some of the largest aeronautics companies began to develop automated processes such as Automated Fibre Placement (AFP). The AFP workcells currently used by the industry were mainly developed for production of large, nearly flat, plates with low curvatures such as aircraft fuselages. However, the fields of aeronautics and sport goods production begin nowadays to show an interest for manufacturing of smaller and more complex parts. The aim of the project in which this research takes place is to design a new AFP workcell and to develop new techniques allowing production of parts with small size and complex geometry. The work presented in this thesis focuses on the path planning on multi-axial revolution surfaces, e.g. Y-shaped tubes of constant circular cross section. Several path planning algorithms will be presented aiming at the exhaustive coverage of a mandrel with pre-impregnated (prepreg) composite tape. The methodology used in two of these algorithms is to individually cover each branch of the Y-shaped part with paths deriving from a helix. In the first one, the helix will be cut at the boundary between a branch and the junction region (algorithm HD) while in the second (algorithm HA) the pseudo-helix path can be adjusted to follow this boundary. These two methods were shown to have some drawbacks compromising their practical use and possibly leading to parts with diminished mechanical properties. To avoid these drawbacks, two others algorithms were developed with a new methodology. With them, the aim is to cover two branches of the Y-shape with a continuous course (i.e. without cut). The first one uses a well known strategy which defines plies with a constant fibre orientation. Parallel paths are then computed to generate a full and uniform ply covering two branches. Once again this method suffers from a main drawback, namely that it can produce highly curved paths leading to manufacturing defects. To overcome this limitation, a last algorithm is proposed ensuring that the maximal curvature of a trajectory stays below a fixed threshold. However, fulfilling this constraint prevents to predict the complete shape of the path and to ensure a perfectly uniform coverage. It is thus proposed to generate an exhaustive set of trajectories having different shapes and covering all the part. Then, a selection algorithm is used to choose the ones which are best suited according to selection criteria. To help the definition of these criteria, a finite element analysis is conducted to give some insight concerning the best suited shapes for specific loading cases. Finally, simulations were carried out with a workcell constituted by a robotic manipulator associated with a rotary table to verify the feasibility of the paths generated by the different algorithms.

Game of thrown bombs in 3D: using high speed cameras and photogrammetry techniques to reconstruct bomb trajectories at Stromboli (Italy)

NASA Astrophysics Data System (ADS)

Gaudin, D.; Taddeucci, J.; Scarlato, P.; Del Bello, E.; Houghton, B. F.; Orr, T. R.; Andronico, D.; Kueppers, U.

2015-12-01

Large juvenile bombs and lithic clasts, produced and ejected during explosive volcanic eruptions, follow ballistic trajectories. Of particular interest are: 1) the determination of ejection velocity and launch angle, which give insights into shallow conduit conditions and geometry; 2) particle trajectories, with an eye on trajectory evolution caused by collisions between bombs, as well as the interaction between bombs and ash/gas plumes; and 3) the computation of the final emplacement of bomb-sized clasts, which is important for hazard assessment and risk management. Ground-based imagery from a single camera only allows the reconstruction of bomb trajectories in a plan perpendicular to the line of sight, which may lead to underestimation of bomb velocities and does not allow the directionality of the ejections to be studied. To overcome this limitation, we adapted photogrammetry techniques to reconstruct 3D bomb trajectories from two or three synchronized high-speed video cameras. In particular, we modified existing algorithms to consider the errors that may arise from the very high velocity of the particles and the impossibility of measuring tie points close to the scene. Our method was tested during two field campaigns at Stromboli. In 2014, two high-speed cameras with a 500 Hz frame rate and a ~2 cm resolution were set up ~350m from the crater, 10° apart and synchronized. The experiment was repeated with similar parameters in 2015, but using three high-speed cameras in order to significantly reduce uncertainties and allow their estimation. Trajectory analyses for tens of bombs at various times allowed for the identification of shifts in the mean directivity and dispersal angle of the jets during the explosions. These time evolutions are also visible on the permanent video-camera monitoring system, demonstrating the applicability of our method to all kinds of explosive volcanoes.

A simple Lagrangian forecast system with aviation forecast potential

NASA Technical Reports Server (NTRS)

Petersen, R. A.; Homan, J. H.

1983-01-01

A trajectory forecast procedure is developed which uses geopotential tendency fields obtained from a simple, multiple layer, potential vorticity conservative isentropic model. This model can objectively account for short-term advective changes in the mass field when combined with fine-scale initial analyses. This procedure for producing short-term, upper-tropospheric trajectory forecasts employs a combination of a detailed objective analysis technique, an efficient mass advection model, and a diagnostically proven trajectory algorithm, none of which require extensive computer resources. Results of initial tests are presented, which indicate an exceptionally good agreement for trajectory paths entering the jet stream and passing through an intensifying trough. It is concluded that this technique not only has potential for aiding in route determination, fuel use estimation, and clear air turbulence detection, but also provides an example of the types of short range forecasting procedures which can be applied at local forecast centers using simple algorithms and a minimum of computer resources.

Non-Rigid Structure Estimation in Trajectory Space from Monocular Vision

PubMed Central

Wang, Yaming; Tong, Lingling; Jiang, Mingfeng; Zheng, Junbao

2015-01-01

In this paper, the problem of non-rigid structure estimation in trajectory space from monocular vision is investigated. Similar to the Point Trajectory Approach (PTA), based on characteristic points’ trajectories described by a predefined Discrete Cosine Transform (DCT) basis, the structure matrix was also calculated by using a factorization method. To further optimize the non-rigid structure estimation from monocular vision, the rank minimization problem about structure matrix is proposed to implement the non-rigid structure estimation by introducing the basic low-rank condition. Moreover, the Accelerated Proximal Gradient (APG) algorithm is proposed to solve the rank minimization problem, and the initial structure matrix calculated by the PTA method is optimized. The APG algorithm can converge to efficient solutions quickly and lessen the reconstruction error obviously. The reconstruction results of real image sequences indicate that the proposed approach runs reliably, and effectively improves the accuracy of non-rigid structure estimation from monocular vision. PMID:26473863

Departure Trajectory Synthesis and the Intercept Problem

NASA Technical Reports Server (NTRS)

Bolender, Michael A.; Slater, G. L.

1997-01-01

Two areas of the departure problem in air traffic control are discussed. The first topic is the generation of climb-out trajectories to a fix. The trajectories would be utilized by a scheduling algorithm to allocate runways, sequence the proposed departures, and assign a departure time. The second area is concerned with finding horizontal trajectories to merge aircraft from the TRACON to an open slot in the en-route environment. Solutions are presented for the intercept problem for two cases: (1) the aircraft is traveling at the speed of the aircraft in the jetway; (2) the merging aircraft has to accelerate to reach the speed of the aircraft in the en-route stream. An algorithm is given regarding the computation of a solution for the latter case. For the former, a set of equations is given that allows us to numerically solve for the coordinate where the merge will occur.

Geometrically derived difference formulae for the numerical integration of trajectory problems

NASA Technical Reports Server (NTRS)

Mcleod, R. J. Y.; Sanz-Serna, J. M.

1982-01-01

An initial value problem for the autonomous system of ordinary differential equations dy/dt = f(y), where y is a vector, is considered. In a number of practical applications the interest lies in obtaining the curve traced by the solution y. These applications include the computation of trajectories in mechanical problems. The term 'trajectory problem' is employed to refer to these cases. Lambert and McLeod (1979) have introduced a method involving local rotation of the axes in the y-plane for the two-dimensional case. The present investigation continues the study of difference schemes specifically derived for trajectory problems. A simple geometrical way of constructing such methods is presented, and the local accuracy of the schemes is investigated. A circularly exact, fixed-step predictor-corrector algorithm is defined, and a variable-step version of a circularly exact algorithm is presented.

A wavefront reconstruction method for 3-D cylindrical subsurface radar imaging.

PubMed

Flores-Tapia, Daniel; Thomas, Gabriel; Pistorius, Stephen

2008-10-01

In recent years, the use of radar technology has been proposed in a wide range of subsurface imaging applications. Traditionally, linear scan trajectories are used to acquire data in most subsurface radar applications. However, novel applications, such as breast microwave imaging and wood inspection, require the use of nonlinear scan trajectories in order to adjust to the geometry of the scanned area. This paper proposes a novel reconstruction algorithm for subsurface radar data acquired along cylindrical scan trajectories. The spectrum of the collected data is processed in order to locate the spatial origin of the target reflections and remove the spreading of the target reflections which results from the different signal travel times along the scan trajectory. The proposed algorithm was successfully tested using experimental data collected from phantoms that mimic high contrast subsurface radar scenarios, yielding promising results. Practical considerations such as spatial resolution and sampling constraints are discussed and illustrated as well.

A multicolour graph as a complete topological invariant for \\Omega-stable flows without periodic trajectories on surfaces

NASA Astrophysics Data System (ADS)

Kruglov, V. E.; Malyshev, D. S.; Pochinka, O. V.

2018-01-01

Studying the dynamics of a flow on surfaces by partitioning the phase space into cells with the same limit behaviour of trajectories within a cell goes back to the classical papers of Andronov, Pontryagin, Leontovich and Maier. The types of cells (the number of which is finite) and how the cells adjoin one another completely determine the topological equivalence class of a flow with finitely many special trajectories. If one trajectory is chosen in every cell of a rough flow without periodic orbits, then the cells are partitioned into so-called triangular regions of the same type. A combinatorial description of such a partition gives rise to the three-colour Oshemkov-Sharko graph, the vertices of which correspond to the triangular regions, and the edges to separatrices connecting them. Oshemkov and Sharko proved that such flows are topologically equivalent if and only if the three-colour graphs of the flows are isomorphic, and described an algorithm of distinguishing three-colour graphs. But their algorithm is not efficient with respect to graph theory. In the present paper, we describe the dynamics of Ω-stable flows without periodic trajectories on surfaces in the language of four-colour graphs, present an efficient algorithm for distinguishing such graphs, and develop a realization of a flow from some abstract graph. Bibliography: 17 titles.

Path planning for assembly of strut-based structures. Thesis

NASA Technical Reports Server (NTRS)

Muenger, Rolf

1991-01-01

A path planning method with collision avoidance for a general single chain nonredundant or redundant robot is proposed. Joint range boundary overruns are also avoided. The result is a sequence of joint vectors which are passed to a trajectory planner. A potential field algorithm in joint space computes incremental joint vectors delta-q = delta-q(sub a) + delta-q(sub c) + delta-q(sub r). Adding delta-q to the robot's current joint vector leads to the next step in the path. Delta-q(sub a) is obtained by computing the minimum norm solution of the underdetermined linear system J delta-q(sub a) = x(sub a) where x(sub a) is a translational and rotational force vector that attracts the robot to its goal position and orientation. J is the manipulator Jacobian. Delta-q(sub c) is a collision avoidance term encompassing collisions between the robot (links and payload) and obstacles in the environment as well as collisions among links and payload of the robot themselves. It is obtained in joint space directly. Delta-q(sub r) is a function of the current joint vector and avoids joint range overruns. A higher level discrete search over candidate safe positions is used to provide alternatives in case the potential field algorithm encounters a local minimum and thus fails to reach the goal. The best first search algorithm A* is used for graph search. Symmetry properties of the payload and equivalent rotations are exploited to further enlarge the number of alternatives passed to the potential field algorithm.

FPGA Implementation of an Efficient Algorithm for the Calculation of Charged Particle Trajectories in Cosmic Ray Detectors

NASA Astrophysics Data System (ADS)

Villar, Xabier; Piso, Daniel; Bruguera, Javier D.

2014-02-01

This paper presents an FPGA implementation of an algorithm, previously published, for the the reconstruction of cosmic rays' trajectories and the determination of the time of arrival and velocity of the particles. The accuracy and precision issues of the algorithm have been analyzed to propose a suitable implementation. Thus, a 32-bit fixed-point format has been used for the representation of the data values. Moreover, the dependencies among the different operations have been taken into account to obtain a highly parallel and efficient hardware implementation. The final hardware architecture requires 18 cycles to process every particle, and has been exhaustively simulated to validate all the design decisions. The architecture has been mapped over different commercial FPGAs, with a frequency of operation ranging from 300 MHz to 1.3 GHz, depending on the FPGA being used. Consequently, the number of particle trajectories processed per second is between 16 million and 72 million. The high number of particle trajectories calculated per second shows that the proposed FPGA implementation might be used also in high rate environments such as those found in particle and nuclear physics experiments.

Visiting Vehicle Ground Trajectory Tool

NASA Technical Reports Server (NTRS)

Hamm, Dustin

2013-01-01

The International Space Station (ISS) Visiting Vehicle Group needed a targeting tool for vehicles that rendezvous with the ISS. The Visiting Vehicle Ground Trajectory targeting tool provides the ability to perform both realtime and planning operations for the Visiting Vehicle Group. This tool provides a highly reconfigurable base, which allows the Visiting Vehicle Group to perform their work. The application is composed of a telemetry processing function, a relative motion function, a targeting function, a vector view, and 2D/3D world map type graphics. The software tool provides the ability to plan a rendezvous trajectory for vehicles that visit the ISS. It models these relative trajectories using planned and realtime data from the vehicle. The tool monitors ongoing rendezvous trajectory relative motion, and ensures visiting vehicles stay within agreed corridors. The software provides the ability to update or re-plan a rendezvous to support contingency operations. Adding new parameters and incorporating them into the system was previously not available on-the-fly. If an unanticipated capability wasn't discovered until the vehicle was flying, there was no way to update things.

Equilibrium point control of a monkey arm simulator by a fast learning tree structured artificial neural network.

PubMed

Dornay, M; Sanger, T D

1993-01-01

A planar 17 muscle model of the monkey's arm based on realistic biomechanical measurements was simulated on a Symbolics Lisp Machine. The simulator implements the equilibrium point hypothesis for the control of arm movements. Given initial and final desired positions, it generates a minimum-jerk desired trajectory of the hand and uses the backdriving algorithm to determine an appropriate sequence of motor commands to the muscles (Flash 1987; Mussa-Ivaldi et al. 1991; Dornay 1991b). These motor commands specify a temporal sequence of stable (attractive) equilibrium positions which lead to the desired hand movement. A strong disadvantage of the simulator is that it has no memory of previous computations. Determining the desired trajectory using the minimum-jerk model is instantaneous, but the laborious backdriving algorithm is slow, and can take up to one hour for some trajectories. The complexity of the required computations makes it a poor model for biological motor control. We propose a computationally simpler and more biologically plausible method for control which achieves the benefits of the backdriving algorithm. A fast learning, tree-structured network (Sanger 1991c) was trained to remember the knowledge obtained by the backdriving algorithm. The neural network learned the nonlinear mapping from a 2-dimensional cartesian planar hand position (x,y) to a 17-dimensional motor command space (u1, . . ., u17). Learning 20 training trajectories, each composed of 26 sample points [[x,y], [u1, . . ., u17] took only 20 min on a Sun-4 Sparc workstation. After the learning stage, new, untrained test trajectories as well as the original trajectories of the hand were given to the neural network as input. The network calculated the required motor commands for these movements. The resulting movements were close to the desired ones for both the training and test cases.

Experimental validation of the van Herk margin formula for lung radiation therapy

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

Ecclestone, Gillian; Heath, Emily; Bissonnette, Jean-Pierre

2013-11-15

Purpose: To validate the van Herk margin formula for lung radiation therapy using realistic dose calculation algorithms and respiratory motion modeling. The robustness of the margin formula against variations in lesion size, peak-to-peak motion amplitude, tissue density, treatment technique, and plan conformity was assessed, along with the margin formula assumption of a homogeneous dose distribution with perfect plan conformity.Methods: 3DCRT and IMRT lung treatment plans were generated within the ORBIT treatment planning platform (RaySearch Laboratories, Sweden) on 4DCT datasets of virtual phantoms. Random and systematic respiratory motion induced errors were simulated using deformable registration and dose accumulation tools available withinmore » ORBIT for simulated cases of varying lesion sizes, peak-to-peak motion amplitudes, tissue densities, and plan conformities. A detailed comparison between the margin formula dose profile model, the planned dose profiles, and penumbra widths was also conducted to test the assumptions of the margin formula. Finally, a correction to account for imperfect plan conformity was tested as well as a novel application of the margin formula that accounts for the patient-specific motion trajectory.Results: The van Herk margin formula ensured full clinical target volume coverage for all 3DCRT and IMRT plans of all conformities with the exception of small lesions in soft tissue. No dosimetric trends with respect to plan technique or lesion size were observed for the systematic and random error simulations. However, accumulated plans showed that plan conformity decreased with increasing tumor motion amplitude. When comparing dose profiles assumed in the margin formula model to the treatment plans, discrepancies in the low dose regions were observed for the random and systematic error simulations. However, the margin formula respected, in all experiments, the 95% dose coverage required for planning target volume (PTV) margin derivation, as defined by the ICRU; thus, suitable PTV margins were estimated. The penumbra widths calculated in lung tissue for each plan were found to be very similar to the 6.4 mm value assumed by the margin formula model. The plan conformity correction yielded inconsistent results which were largely affected by image and dose grid resolution while the trajectory modified PTV plans yielded a dosimetric benefit over the standard internal target volumes approach with up to a 5% decrease in the V20 value.Conclusions: The margin formula showed to be robust against variations in tumor size and motion, treatment technique, plan conformity, as well as low tissue density. This was validated by maintaining coverage of all of the derived PTVs by 95% dose level, as required by the formal definition of the PTV. However, the assumption of perfect plan conformity in the margin formula derivation yields conservative margin estimation. Future modifications to the margin formula will require a correction for plan conformity. Plan conformity can also be improved by using the proposed trajectory modified PTV planning approach. This proves especially beneficial for tumors with a large anterior–posterior component of respiratory motion.« less

Flash trajectory imaging of target 3D motion

NASA Astrophysics Data System (ADS)

Wang, Xinwei; Zhou, Yan; Fan, Songtao; He, Jun; Liu, Yuliang

2011-03-01

We present a flash trajectory imaging technique which can directly obtain target trajectory and realize non-contact measurement of motion parameters by range-gated imaging and time delay integration. Range-gated imaging gives the range of targets and realizes silhouette detection which can directly extract targets from complex background and decrease the complexity of moving target image processing. Time delay integration increases information of one single frame of image so that one can directly gain the moving trajectory. In this paper, we have studied the algorithm about flash trajectory imaging and performed initial experiments which successfully obtained the trajectory of a falling badminton. Our research demonstrates that flash trajectory imaging is an effective approach to imaging target trajectory and can give motion parameters of moving targets.

PTM Along Track Algorithm to Maintain Spacing During Same Direction Pair-Wise Trajectory Management Operations

NASA Technical Reports Server (NTRS)

Carreno, Victor A.

2015-01-01

Pair-wise Trajectory Management (PTM) is a cockpit based delegated responsibility separation standard. When an air traffic service provider gives a PTM clearance to an aircraft and the flight crew accepts the clearance, the flight crew will maintain spacing and separation from a designated aircraft. A PTM along track algorithm will receive state information from the designated aircraft and from the own ship to produce speed guidance for the flight crew to maintain spacing and separation

Cone-beam reconstruction for the two-circles-plus-one-line trajectory

NASA Astrophysics Data System (ADS)

Lu, Yanbin; Yang, Jiansheng; Emerson, John W.; Mao, Heng; Zhou, Tie; Si, Yuanzheng; Jiang, Ming

2012-05-01

The Kodak Image Station In-Vivo FX has an x-ray module with cone-beam configuration for radiographic imaging but lacks the functionality of tomography. To introduce x-ray tomography into the system, we choose the two-circles-plus-one-line trajectory by mounting one translation motor and one rotation motor. We establish a reconstruction algorithm by applying the M-line reconstruction method. Numerical studies and preliminary physical phantom experiment demonstrate the feasibility of the proposed design and reconstruction algorithm.

Arbitrary Symmetric Running Gait Generation for an Underactuated Biped Model.

PubMed

Dadashzadeh, Behnam; Esmaeili, Mohammad; Macnab, Chris

2017-01-01

This paper investigates generating symmetric trajectories for an underactuated biped during the stance phase of running. We use a point mass biped (PMB) model for gait analysis that consists of a prismatic force actuator on a massless leg. The significance of this model is its ability to generate more general and versatile running gaits than the spring-loaded inverted pendulum (SLIP) model, making it more suitable as a template for real robots. The algorithm plans the necessary leg actuator force to cause the robot center of mass to undergo arbitrary trajectories in stance with any arbitrary attack angle and velocity angle. The necessary actuator forces follow from the inverse kinematics and dynamics. Then these calculated forces become the control input to the dynamic model. We compare various center-of-mass trajectories, including a circular arc and polynomials of the degrees 2, 4 and 6. The cost of transport and maximum leg force are calculated for various attack angles and velocity angles. The results show that choosing the velocity angle as small as possible is beneficial, but the angle of attack has an optimum value. We also find a new result: there exist biped running gaits with double-hump ground reaction force profiles which result in less maximum leg force than single-hump profiles.

Arbitrary Symmetric Running Gait Generation for an Underactuated Biped Model

PubMed Central

Esmaeili, Mohammad; Macnab, Chris

2017-01-01

This paper investigates generating symmetric trajectories for an underactuated biped during the stance phase of running. We use a point mass biped (PMB) model for gait analysis that consists of a prismatic force actuator on a massless leg. The significance of this model is its ability to generate more general and versatile running gaits than the spring-loaded inverted pendulum (SLIP) model, making it more suitable as a template for real robots. The algorithm plans the necessary leg actuator force to cause the robot center of mass to undergo arbitrary trajectories in stance with any arbitrary attack angle and velocity angle. The necessary actuator forces follow from the inverse kinematics and dynamics. Then these calculated forces become the control input to the dynamic model. We compare various center-of-mass trajectories, including a circular arc and polynomials of the degrees 2, 4 and 6. The cost of transport and maximum leg force are calculated for various attack angles and velocity angles. The results show that choosing the velocity angle as small as possible is beneficial, but the angle of attack has an optimum value. We also find a new result: there exist biped running gaits with double-hump ground reaction force profiles which result in less maximum leg force than single-hump profiles. PMID:28118401

Real-time trajectory optimization on parallel processors

NASA Technical Reports Server (NTRS)

Psiaki, Mark L.

1993-01-01

A parallel algorithm has been developed for rapidly solving trajectory optimization problems. The goal of the work has been to develop an algorithm that is suitable to do real-time, on-line optimal guidance through repeated solution of a trajectory optimization problem. The algorithm has been developed on an INTEL iPSC/860 message passing parallel processor. It uses a zero-order-hold discretization of a continuous-time problem and solves the resulting nonlinear programming problem using a custom-designed augmented Lagrangian nonlinear programming algorithm. The algorithm achieves parallelism of function, derivative, and search direction calculations through the principle of domain decomposition applied along the time axis. It has been encoded and tested on 3 example problems, the Goddard problem, the acceleration-limited, planar minimum-time to the origin problem, and a National Aerospace Plane minimum-fuel ascent guidance problem. Execution times as fast as 118 sec of wall clock time have been achieved for a 128-stage Goddard problem solved on 32 processors. A 32-stage minimum-time problem has been solved in 151 sec on 32 processors. A 32-stage National Aerospace Plane problem required 2 hours when solved on 32 processors. A speed-up factor of 7.2 has been achieved by using 32-nodes instead of 1-node to solve a 64-stage Goddard problem.

Complex Road Intersection Modelling Based on Low-Frequency GPS Track Data

NASA Astrophysics Data System (ADS)

Huang, J.; Deng, M.; Zhang, Y.; Liu, H.

2017-09-01

It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing images. At present, a large number of GPS trajectory data collected by floating vehicles makes it a reality to extract high-detailed and up-to-date road network information. Road intersections are often accident-prone areas and very critical to route planning and the connectivity of road networks is mainly determined by the topological geometry of road intersections. A few studies paid attention on detecting complex road intersections and mining the attached traffic information (e.g., connectivity, topology and turning restriction) from massive GPS traces. To the authors' knowledge, recent studies mainly used high frequency (1 s sampling rate) trajectory data to detect the crossroads regions or extract rough intersection models. It is still difficult to make use of low frequency (20-100 s) and easily available trajectory data to modelling complex road intersections geometrically and semantically. The paper thus attempts to construct precise models for complex road intersection by using low frequency GPS traces. We propose to firstly extract the complex road intersections by a LCSS-based (Longest Common Subsequence) trajectory clustering method, then delineate the geometry shapes of complex road intersections by a K-segment principle curve algorithm, and finally infer the traffic constraint rules inside the complex intersections.

Learning Trajectories, Lesson Planning, Affordances, and Constraints in the Design and Enactment of Mathematics Teaching

ERIC Educational Resources Information Center

Amador, Julie; Lamberg, Teruni

2013-01-01

Recent reform efforts in mathematics education have stimulated a focus on learning trajectories. At the same time, a global increase in high-stakes testing has influenced instructional practices. This study investigated how four fourth grade teachers within a school planned and enacted lessons to understand what mediated their planning and…

Post-processing interstitialcy diffusion from molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Bhardwaj, U.; Bukkuru, S.; Warrier, M.

2016-01-01

An algorithm to rigorously trace the interstitialcy diffusion trajectory in crystals is developed. The algorithm incorporates unsupervised learning and graph optimization which obviate the need to input extra domain specific information depending on crystal or temperature of the simulation. The algorithm is implemented in a flexible framework as a post-processor to molecular dynamics (MD) simulations. We describe in detail the reduction of interstitialcy diffusion into known computational problems of unsupervised clustering and graph optimization. We also discuss the steps, computational efficiency and key components of the algorithm. Using the algorithm, thermal interstitialcy diffusion from low to near-melting point temperatures is studied. We encapsulate the algorithms in a modular framework with functionality to calculate diffusion coefficients, migration energies and other trajectory properties. The study validates the algorithm by establishing the conformity of output parameters with experimental values and provides detailed insights for the interstitialcy diffusion mechanism. The algorithm along with the help of supporting visualizations and analysis gives convincing details and a new approach to quantifying diffusion jumps, jump-lengths, time between jumps and to identify interstitials from lattice atoms.

Post-processing interstitialcy diffusion from molecular dynamics simulations

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

Bhardwaj, U., E-mail: haptork@gmail.com; Bukkuru, S.; Warrier, M.

2016-01-15

An algorithm to rigorously trace the interstitialcy diffusion trajectory in crystals is developed. The algorithm incorporates unsupervised learning and graph optimization which obviate the need to input extra domain specific information depending on crystal or temperature of the simulation. The algorithm is implemented in a flexible framework as a post-processor to molecular dynamics (MD) simulations. We describe in detail the reduction of interstitialcy diffusion into known computational problems of unsupervised clustering and graph optimization. We also discuss the steps, computational efficiency and key components of the algorithm. Using the algorithm, thermal interstitialcy diffusion from low to near-melting point temperatures ismore » studied. We encapsulate the algorithms in a modular framework with functionality to calculate diffusion coefficients, migration energies and other trajectory properties. The study validates the algorithm by establishing the conformity of output parameters with experimental values and provides detailed insights for the interstitialcy diffusion mechanism. The algorithm along with the help of supporting visualizations and analysis gives convincing details and a new approach to quantifying diffusion jumps, jump-lengths, time between jumps and to identify interstitials from lattice atoms. -- Graphical abstract:.« less

A 2D chaotic path planning for mobile robots accomplishing boundary surveillance missions in adversarial conditions

NASA Astrophysics Data System (ADS)

Curiac, Daniel-Ioan; Volosencu, Constantin

2014-10-01

The path-planning algorithm represents a crucial issue for every autonomous mobile robot. In normal circumstances a patrol robot will compute an optimal path to ensure its task accomplishment, but in adversarial conditions the problem is getting more complicated. Here, the robot’s trajectory needs to be altered into a misleading and unpredictable path to cope with potential opponents. Chaotic systems provide the needed framework for obtaining unpredictable motion in all of the three basic robot surveillance missions: area, points of interests and boundary monitoring. Proficient approaches have been provided for the first two surveillance tasks, but for boundary patrol missions no method has been reported yet. This paper addresses the mentioned research gap by proposing an efficient method, based on chaotic dynamic of the Hénon system, to ensure unpredictable boundary patrol on any shape of chosen closed contour.

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberger, Mark

2015-01-01

This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms.

Exact and explicit optimal solutions for trajectory planning and control of single-link flexible-joint manipulators

NASA Technical Reports Server (NTRS)

Chen, Guanrong

1991-01-01

An optimal trajectory planning problem for a single-link, flexible joint manipulator is studied. A global feedback-linearization is first applied to formulate the nonlinear inequality-constrained optimization problem in a suitable way. Then, an exact and explicit structural formula for the optimal solution of the problem is derived and the solution is shown to be unique. It turns out that the optimal trajectory planning and control can be done off-line, so that the proposed method is applicable to both theoretical analysis and real time tele-robotics control engineering.

Implementation of a Low-Thrust Trajectory Optimization Algorithm for Preliminary Design

NASA Technical Reports Server (NTRS)

Sims, Jon A.; Finlayson, Paul A.; Rinderle, Edward A.; Vavrina, Matthew A.; Kowalkowski, Theresa D.

2006-01-01

A tool developed for the preliminary design of low-thrust trajectories is described. The trajectory is discretized into segments and a nonlinear programming method is used for optimization. The tool is easy to use, has robust convergence, and can handle many intermediate encounters. In addition, the tool has a wide variety of features, including several options for objective function and different low-thrust propulsion models (e.g., solar electric propulsion, nuclear electric propulsion, and solar sail). High-thrust, impulsive trajectories can also be optimized.

ANALYTiC: An Active Learning System for Trajectory Classification.

PubMed

Soares Junior, Amilcar; Renso, Chiara; Matwin, Stan

2017-01-01

The increasing availability and use of positioning devices has resulted in large volumes of trajectory data. However, semantic annotations for such data are typically added by domain experts, which is a time-consuming task. Machine-learning algorithms can help infer semantic annotations from trajectory data by learning from sets of labeled data. Specifically, active learning approaches can minimize the set of trajectories to be annotated while preserving good performance measures. The ANALYTiC web-based interactive tool visually guides users through this annotation process.

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Variational Trajectory Optimization Tool Set: Technical description and user's manual

NASA Technical Reports Server (NTRS)

Bless, Robert R.; Queen, Eric M.; Cavanaugh, Michael D.; Wetzel, Todd A.; Moerder, Daniel D.

1993-01-01

The algorithms that comprise the Variational Trajectory Optimization Tool Set (VTOTS) package are briefly described. The VTOTS is a software package for solving nonlinear constrained optimal control problems from a wide range of engineering and scientific disciplines. The VTOTS package was specifically designed to minimize the amount of user programming; in fact, for problems that may be expressed in terms of analytical functions, the user needs only to define the problem in terms of symbolic variables. This version of the VTOTS does not support tabular data; thus, problems must be expressed in terms of analytical functions. The VTOTS package consists of two methods for solving nonlinear optimal control problems: a time-domain finite-element algorithm and a multiple shooting algorithm. These two algorithms, under the VTOTS package, may be run independently or jointly. The finite-element algorithm generates approximate solutions, whereas the shooting algorithm provides a more accurate solution to the optimization problem. A user's manual, some examples with results, and a brief description of the individual subroutines are included.

A Comparison of Two Skip Entry Guidance Algorithms

NASA Technical Reports Server (NTRS)

Rea, Jeremy R.; Putnam, Zachary R.

2007-01-01

The Orion capsule vehicle will have a Lift-to-Drag ratio (L/D) of 0.3-0.35. For an Apollo-like direct entry into the Earth's atmosphere from a lunar return trajectory, this L/D will give the vehicle a maximum range of about 2500 nm and a maximum crossrange of 216 nm. In order to y longer ranges, the vehicle lift must be used to loft the trajectory such that the aerodynamic forces are decreased. A Skip-Trajectory results if the vehicle leaves the sensible atmosphere and a second entry occurs downrange of the atmospheric exit point. The Orion capsule is required to have landing site access (either on land or in water) inside the Continental United States (CONUS) for lunar returns anytime during the lunar month. This requirement means the vehicle must be capable of flying ranges of at least 5500 nm. For the L/D of the vehicle, this is only possible with the use of a guided Skip-Trajectory. A skip entry guidance algorithm is necessary to achieve this requirement. Two skip entry guidance algorithms have been developed: the Numerical Skip Entry Guidance (NSEG) algorithm was developed at NASA/JSC and PredGuid was developed at Draper Laboratory. A comparison of these two algorithms will be presented in this paper. Each algorithm has been implemented in a high-fidelity, 6 degree-of-freedom simulation called the Advanced NASA Technology Architecture for Exploration Studies (ANTARES). NASA and Draper engineers have completed several monte carlo analyses in order to compare the performance of each algorithm in various stress states. Each algorithm has been tested for entry-to-target ranges to include direct entries and skip entries of varying length. Dispersions have been included on the initial entry interface state, vehicle mass properties, vehicle aerodynamics, atmosphere, and Reaction Control System (RCS). Performance criteria include miss distance to the target, RCS fuel usage, maximum g-loads and heat rates for the first and second entry, total heat load, and control system saturation. The comparison of the performance criteria has led to a down select and guidance merger that will take the best ideas from each algorithm to create one skip entry guidance algorithm for the Orion vehicle.

Trajectory planning and optimal tracking for an industrial mobile robot

NASA Astrophysics Data System (ADS)

Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

1994-02-01

This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

Splash: a software tool for stereotactic planning of recording chamber placement and electrode trajectories.

PubMed

Sperka, Daniel J; Ditterich, Jochen

2011-01-01

While computer-aided planning of human neurosurgeries is becoming more and more common, animal researchers still largely rely on paper atlases for planning their approach before implanting recording chambers to perform invasive recordings of neural activity, which makes this planning process tedious and error-prone. Here we present SPLASh (Stereotactic PLAnning Software), an interactive software tool for the stereotactic planning of recording chamber placement and electrode trajectories. SPLASh has been developed for monkey cortical recordings and relies on a combination of structural MRIs and electronic brain atlases. Since SPLASh is based on the neuroanatomy software Caret, it should also be possible to use it for other parts of the brain or other species for which Caret atlases are available. The tool allows the user to interactively evaluate different possible placements of recording chambers and to simulate electrode trajectories.

Splash: A Software Tool for Stereotactic Planning of Recording Chamber Placement and Electrode Trajectories

PubMed Central

Sperka, Daniel J.; Ditterich, Jochen

2011-01-01

While computer-aided planning of human neurosurgeries is becoming more and more common, animal researchers still largely rely on paper atlases for planning their approach before implanting recording chambers to perform invasive recordings of neural activity, which makes this planning process tedious and error-prone. Here we present SPLASh (Stereotactic PLAnning Software), an interactive software tool for the stereotactic planning of recording chamber placement and electrode trajectories. SPLASh has been developed for monkey cortical recordings and relies on a combination of structural MRIs and electronic brain atlases. Since SPLASh is based on the neuroanatomy software Caret, it should also be possible to use it for other parts of the brain or other species for which Caret atlases are available. The tool allows the user to interactively evaluate different possible placements of recording chambers and to simulate electrode trajectories. PMID:21472085

TOPTRAC: Topical Trajectory Pattern Mining

PubMed Central

Kim, Younghoon; Han, Jiawei; Yuan, Cangzhou

2015-01-01

With the increasing use of GPS-enabled mobile phones, geo-tagging, which refers to adding GPS information to media such as micro-blogging messages or photos, has seen a surge in popularity recently. This enables us to not only browse information based on locations, but also discover patterns in the location-based behaviors of users. Many techniques have been developed to find the patterns of people's movements using GPS data, but latent topics in text messages posted with local contexts have not been utilized effectively. In this paper, we present a latent topic-based clustering algorithm to discover patterns in the trajectories of geo-tagged text messages. We propose a novel probabilistic model to capture the semantic regions where people post messages with a coherent topic as well as the patterns of movement between the semantic regions. Based on the model, we develop an efficient inference algorithm to calculate model parameters. By exploiting the estimated model, we next devise a clustering algorithm to find the significant movement patterns that appear frequently in data. Our experiments on real-life data sets show that the proposed algorithm finds diverse and interesting trajectory patterns and identifies the semantic regions in a finer granularity than the traditional geographical clustering methods. PMID:26709365

Self-guided training for deep brain stimulation planning using objective assessment.

PubMed

Holden, Matthew S; Zhao, Yulong; Haegelen, Claire; Essert, Caroline; Fernandez-Vidal, Sara; Bardinet, Eric; Ungi, Tamas; Fichtinger, Gabor; Jannin, Pierre

2018-04-04

Deep brain stimulation (DBS) is an increasingly common treatment for neurodegenerative diseases. Neurosurgeons must have thorough procedural, anatomical, and functional knowledge to plan electrode trajectories and thus ensure treatment efficacy and patient safety. Developing this knowledge requires extensive training. We propose a training approach with objective assessment of neurosurgeon proficiency in DBS planning. To assess proficiency, we propose analyzing both the viability of the planned trajectory and the manner in which the operator arrived at the trajectory. To improve understanding, we suggest a self-guided training course for DBS planning using real-time feedback. To validate the proposed measures of proficiency and training course, two experts and six novices followed the training course, and we monitored their proficiency measures throughout. At baseline, experts planned higher quality trajectories and did so more efficiently. As novices progressed through the training course, their proficiency measures increased significantly, trending toward expert measures. We developed and validated measures which reliably discriminate proficiency levels. These measures are integrated into a training course, which quantitatively improves trainee performance. The proposed training course can be used to improve trainees' proficiency, and the quantitative measures allow trainees' progress to be monitored.

A trajectory generation and system characterization model for cislunar low-thrust spacecraft. Volume 2: Technical manual

NASA Technical Reports Server (NTRS)

Korsmeyer, David J.; Pinon, Elfego, III; Oconnor, Brendan M.; Bilby, Curt R.

1990-01-01

The documentation of the Trajectory Generation and System Characterization Model for the Cislunar Low-Thrust Spacecraft is presented in Technical and User's Manuals. The system characteristics and trajectories of low thrust nuclear electric propulsion spacecraft can be generated through the use of multiple system technology models coupled with a high fidelity trajectory generation routine. The Earth to Moon trajectories utilize near Earth orbital plane alignment, midcourse control dependent upon the spacecraft's Jacobian constant, and capture to target orbit utilizing velocity matching algorithms. The trajectory generation is performed in a perturbed two-body equinoctial formulation and the restricted three-body formulation. A single control is determined by the user for the interactive midcourse portion of the trajectory. The full spacecraft system characteristics and trajectory are provided as output.

Particle Swarm Optimization of Low-Thrust, Geocentric-to-Halo-Orbit Transfers

NASA Astrophysics Data System (ADS)

Abraham, Andrew J.

Missions to Lagrange points are becoming increasingly popular amongst spacecraft mission planners. Lagrange points are locations in space where the gravity force from two bodies, and the centrifugal force acting on a third body, cancel. To date, all spacecraft that have visited a Lagrange point have done so using high-thrust, chemical propulsion. Due to the increasing availability of low-thrust (high efficiency) propulsive devices, and their increasing capability in terms of fuel efficiency and instantaneous thrust, it has now become possible for a spacecraft to reach a Lagrange point orbit without the aid of chemical propellant. While at any given time there are many paths for a low-thrust trajectory to take, only one is optimal. The traditional approach to spacecraft trajectory optimization utilizes some form of gradient-based algorithm. While these algorithms offer numerous advantages, they also have a few significant shortcomings. The three most significant shortcomings are: (1) the fact that an initial guess solution is required to initialize the algorithm, (2) the radius of convergence can be quite small and can allow the algorithm to become trapped in local minima, and (3) gradient information is not always assessable nor always trustworthy for a given problem. To avoid these problems, this dissertation is focused on optimizing a low-thrust transfer trajectory from a geocentric orbit to an Earth-Moon, L1, Lagrange point orbit using the method of Particle Swarm Optimization (PSO). The PSO method is an evolutionary heuristic that was originally written to model birds swarming to locate hidden food sources. This PSO method will enable the exploration of the invariant stable manifold of the target Lagrange point orbit in an effort to optimize the spacecraft's low-thrust trajectory. Examples of these optimized trajectories are presented and contrasted with those found using traditional, gradient-based approaches. In summary, the results of this dissertation find that the PSO method does, indeed, successfully optimize the low-thrust trajectory transfer problem without the need for initial guessing. Furthermore, a two-degree-of-freedom PSO problem formulation significantly outperformed a one-degree-of-freedom formulation by at least an order of magnitude, in terms of CPU time. Finally, the PSO method is also used to solve a traditional, two-burn, impulsive transfer to a Lagrange point orbit using a hybrid optimization algorithm that incorporates a gradient-based shooting algorithm as a pre-optimizer. Surprisingly, the results of this study show that "fast" transfers outperform "slow" transfers in terms of both Deltav and time of flight.

Simulation analysis of adaptive cruise prediction control

NASA Astrophysics Data System (ADS)

Zhang, Li; Cui, Sheng Min

2017-09-01

Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.

Strategies for the sustained human exploration of Mars

NASA Astrophysics Data System (ADS)

Landau, Damon Frederick

A variety of mission scenarios are compared in this thesis to assess the strengths and weaknesses of options for Mars exploration. The mission design space is modeled along two dimensions: trajectory architectures and propulsion system technologies. Direct, semi-direct, stop-over, semi-cycler, and cycler architectures are examined, and electric propulsion, nuclear thermal rockets, methane and oxygen production on Mars, Mars water excavation, aerocapture, and reusable propulsion systems are included in the technology assessment. The mission sensitivity to crew size, vehicle masses, and crew travel time is also examined. The primary figure of merit for a mission scenario is the injected mass to low-Earth orbit (IMLEO), though technology readiness levels (TRL) are also included. Several elements in the architecture dimension are explored in more detail. The Earth-Mars semi-cycler architecture is introduced and five families of Earth-Mars semi-cycler trajectories are presented along with optimized itineraries. Optimized cycler trajectories are also presented. In addition to Earth-Mars semi-cycler and cycler trajectories, conjunction-class, free-return, Mars-Earth semi-cycler, and low-thrust trajectories are calculated. Design parameters for optimal DeltaV trajectories are provided over a range of flight times (from 120 to 270 days) and launch years (between 2009 and 2022). Unlike impulsive transfers, the mass-optimal low-thrust trajectory depends strongly on the thrust and specific impulse of the propulsion system. A low-thrust version of the rocket equation is provided where the initial mass or thrust may be minimized by varying the initial acceleration and specific impulse. Planet-centered operations are also examined. A method to rotate a parking orbit about the line of apsides to achieve the proper orientation at departure is discussed, thus coupling the effects of parking-orbit orientation with the interplanetary trajectories. Also, a guidance algorithm for rendezvous during flybys in semi-cycler and cycler missions is presented with a control law for final approach. A forty-year plan to establish a permanent base on Mars is detailed and methods to expand the base are discussed. Once a large base is established, one-, two-, or three-vehicle systems may sustain the colonization of Mars.

Querying databases of trajectories of differential equations: Data structures for trajectories

NASA Technical Reports Server (NTRS)

Grossman, Robert

1989-01-01

One approach to qualitative reasoning about dynamical systems is to extract qualitative information by searching or making queries on databases containing very large numbers of trajectories. The efficiency of such queries depends crucially upon finding an appropriate data structure for trajectories of dynamical systems. Suppose that a large number of parameterized trajectories gamma of a dynamical system evolving in R sup N are stored in a database. Let Eta is contained in set R sup N denote a parameterized path in Euclidean Space, and let the Euclidean Norm denote a norm on the space of paths. A data structure is defined to represent trajectories of dynamical systems, and an algorithm is sketched which answers queries.

Gait planning for a quadruped robot with one faulty actuator

NASA Astrophysics Data System (ADS)

Chen, Xianbao; Gao, Feng; Qi, Chenkun; Tian, Xinghua

2015-01-01

Fault tolerance is essential for quadruped robots when they work in remote areas or hazardous environments. Many fault-tolerant gaits planning method proposed in the past decade constrained more degrees of freedom(DOFs) of a robot than necessary. Thus a novel method to realize the fault-tolerant walking is proposed. The mobility of the robot is analyzed first by using the screw theory. The result shows that the translation of the center of body(CoB) can be kept with one faulty actuator if the rotations of the body are controlled. Thus the DOFs of the robot body are divided into two parts: the translation of the CoB and the rotation of the body. The kinematic model of the whole robot is built, the algorithm is developed to actively control the body orientations at the velocity level so that the planned CoB trajectory can be realized in spite of the constraint of the faulty actuator. This gait has a similar generation sequence with the normal gait and can be applied to the robot at any position. Simulations and experiments of the fault-tolerant gait with one faulty actuator are carried out. The CoB errors and the body rotation angles are measured. Comparing to the traditional fault-tolerant gait they can be reduced by at least 50%. A fault-tolerant gait planning algorithm is presented, which not only realizes the walking of a quadruped robot with a faulty actuator, but also efficiently improves the walking performances by taking full advantage of the remaining operational actuators according to the results of the simulations and experiments.

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

NASA Astrophysics Data System (ADS)

Chatzidakis, Stylianos; Liu, Zhengzhi; Hayward, Jason P.; Scaglione, John M.

2018-03-01

This work presents a generalized muon trajectory estimation algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguard verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstruction algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS is explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm's precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm root mean square (RMS) for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. The effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.

Research of maneuvering target prediction and tracking technology based on IMM algorithm

NASA Astrophysics Data System (ADS)

Cao, Zheng; Mao, Yao; Deng, Chao; Liu, Qiong; Chen, Jing

2016-09-01

Maneuvering target prediction and tracking technology is widely used in both military and civilian applications, the study of those technologies is all along the hotspot and difficulty. In the Electro-Optical acquisition-tracking-pointing system (ATP), the primary traditional maneuvering targets are ballistic target, large aircraft and other big targets. Those targets have the features of fast velocity and a strong regular trajectory and Kalman Filtering and polynomial fitting have good effects when they are used to track those targets. In recent years, the small unmanned aerial vehicles developed rapidly for they are small, nimble and simple operation. The small unmanned aerial vehicles have strong maneuverability in the observation system of ATP although they are close-in, slow and small targets. Moreover, those vehicles are under the manual operation, therefore, the acceleration of them changes greatly and they move erratically. So the prediction and tracking precision is low when traditional algorithms are used to track the maneuvering fly of those targets, such as speeding up, turning, climbing and so on. The interacting multiple model algorithm (IMM) use multiple models to match target real movement trajectory, there are interactions between each model. The IMM algorithm can switch model based on a Markov chain to adapt to the change of target movement trajectory, so it is suitable to solve the prediction and tracking problems of the small unmanned aerial vehicles because of the better adaptability of irregular movement. This paper has set up model set of constant velocity model (CV), constant acceleration model (CA), constant turning model (CT) and current statistical model. And the results of simulating and analyzing the real movement trajectory data of the small unmanned aerial vehicles show that the prediction and tracking technology based on the interacting multiple model algorithm can get relatively lower tracking error and improve tracking precision comparing with traditional algorithms.

Optimization of dynamic soaring maneuvers to enhance endurance of a versatile UAV

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

Dynamic soaring is a process of acquiring energy available in atmospheric wind shears and is commonly exhibited by soaring birds to perform long distance flights. This paper aims to demonstrate a viable algorithm which can be implemented in near real time environment to formulate optimal trajectories for dynamic soaring maneuvers for a small scale Unmanned Aerial Vehicle (UAV). The objective is to harness maximum energy from atmosphere wind shear to improve loiter time for Intelligence, Surveillance and Reconnaissance (ISR) missions. Three-dimensional point-mass UAV equations of motion and linear wind gradient profile are used to model flight dynamics. Utilizing UAV states, controls, operational constraints, initial and terminal conditions that enforce a periodic flight, dynamic soaring problem is formulated as an optimal control problem. Optimized trajectories of the maneuver are subsequently generated employing pseudo spectral techniques against distant UAV performance parameters. The discussion also encompasses the requirement for generation of optimal trajectories for dynamic soaring in real time environment and the ability of the proposed algorithm for speedy solution generation. Coupled with the fact that dynamic soaring is all about immediately utilizing the available energy from the wind shear encountered, the proposed algorithm promises its viability for practical on board implementations requiring computation of trajectories in near real time.

Coherent structure coloring: identification of coherent structures from sparse flow trajectories using graph theory

NASA Astrophysics Data System (ADS)

Schlueter, Kristy; Dabiri, John

2016-11-01

Coherent structure identification is important in many fluid dynamics applications, including transport phenomena in ocean flows and mixing and diffusion in turbulence. However, many of the techniques currently available for measuring such flows, including ocean drifter datasets and particle tracking velocimetry, only result in sparse velocity data. This is often insufficient for the use of current coherent structure detection algorithms based on analysis of the deformation gradient. Here, we present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number. The method, based on principles used in graph coloring algorithms, examines a measure of the kinematic dissimilarity of all pairs of flow trajectories, either measured experimentally, e.g. using particle tracking velocimetry; or numerically, by advecting fluid particles in the Eulerian velocity field. Coherence is assigned to groups of particles whose kinematics remain similar throughout the time interval for which trajectory data is available, regardless of their physical proximity to one another. Through the use of several analytical and experimental validation cases, this algorithm is shown to robustly detect coherent structures using significantly less flow data than is required by existing methods. This research was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Predicting drifter trajectories and particle dispersion in the Caribbean using a high resolution coastal ocean forecasting system

NASA Astrophysics Data System (ADS)

Solano, M.

2016-02-01

The present study discusses the accuracy of a high-resolution ocean forecasting system in predicting floating drifter trajectories and the uncertainty of modeled particle dispersion in coastal areas. Trajectories were calculated using an offline particle-tracking algorithm coupled to the operational model developed for the region of Puerto Rico by CariCOOS. Both, a simple advection algorithm as well as the Larval TRANSport (LTRANS) model, a more sophisticated offline particle-tracking application, were coupled to the ocean model. Numerical results are compared with 12 floating drifters deployed in the near-shore of Puerto Rico during February and March 2015, and tracked for several days using Global Positioning Systems mounted on the drifters. In addition the trajectories have also been calculated with the AmSeas Navy Coastal Ocean Model (NCOM). The operational model is based on the Regional Ocean Modeling System (ROMS) with a uniform horizontal resolution of 1/100 degrees (1.1km). Initial, surface and open boundary conditions are taken from NCOM, except for wind stress, which is computed using winds from the National Digital Forecasting Database. Probabilistic maps were created to quantify the uncertainty of particle trajectories at different locations. Results show that the forecasted trajectories are location dependent, with tidally active regions having the largest error. The predicted trajectories by both the ROMS and NCOM models show good agreement on average, however both perform differently at particular locations. The effect of wind stress on the drifter trajectories is investigated to account for wind slippage. Furthermore, a real case scenario is presented where simulated trajectories show good agreement when compared to the actual drifter trajectories.

Research on large spatial coordinate automatic measuring system based on multilateral method

NASA Astrophysics Data System (ADS)

Miao, Dongjing; Li, Jianshuan; Li, Lianfu; Jiang, Yuanlin; Kang, Yao; He, Mingzhao; Deng, Xiangrui

2015-10-01

To measure the spatial coordinate accurately and efficiently in large size range, a manipulator automatic measurement system which based on multilateral method is developed. This system is divided into two parts: The coordinate measurement subsystem is consists of four laser tracers, and the trajectory generation subsystem is composed by a manipulator and a rail. To ensure that there is no laser beam break during the measurement process, an optimization function is constructed by using the vectors between the laser tracers measuring center and the cat's eye reflector measuring center, then an orientation automatically adjust algorithm for the reflector is proposed, with this algorithm, the laser tracers are always been able to track the reflector during the entire measurement process. Finally, the proposed algorithm is validated by taking the calibration of laser tracker for instance: the actual experiment is conducted in 5m × 3m × 3.2m range, the algorithm is used to plan the orientations of the reflector corresponding to the given 24 points automatically. After improving orientations of some minority points with adverse angles, the final results are used to control the manipulator's motion. During the actual movement, there are no beam break occurs. The result shows that the proposed algorithm help the developed system to measure the spatial coordinates over a large range with efficiency.

Machine Learning for Discriminating Quantum Measurement Trajectories and Improving Readout.

PubMed

Magesan, Easwar; Gambetta, Jay M; Córcoles, A D; Chow, Jerry M

2015-05-22

Current methods for classifying measurement trajectories in superconducting qubit systems produce fidelities systematically lower than those predicted by experimental parameters. Here, we place current classification methods within the framework of machine learning (ML) algorithms and improve on them by investigating more sophisticated ML approaches. We find that nonlinear algorithms and clustering methods produce significantly higher assignment fidelities that help close the gap to the fidelity possible under ideal noise conditions. Clustering methods group trajectories into natural subsets within the data, which allows for the diagnosis of systematic errors. We find large clusters in the data associated with T1 processes and show these are the main source of discrepancy between our experimental and ideal fidelities. These error diagnosis techniques help provide a path forward to improve qubit measurements.

Adaptive Trajectory Tracking of Nonholonomic Mobile Robots Using Vision-Based Position and Velocity Estimation.

PubMed

Li, Luyang; Liu, Yun-Hui; Jiang, Tianjiao; Wang, Kai; Fang, Mu

2018-02-01

Despite tremendous efforts made for years, trajectory tracking control (TC) of a nonholonomic mobile robot (NMR) without global positioning system remains an open problem. The major reason is the difficulty to localize the robot by using its onboard sensors only. In this paper, a newly designed adaptive trajectory TC method is proposed for the NMR without its position, orientation, and velocity measurements. The controller is designed on the basis of a novel algorithm to estimate position and velocity of the robot online from visual feedback of an omnidirectional camera. It is theoretically proved that the proposed algorithm yields the TC errors to asymptotically converge to zero. Real-world experiments are conducted on a wheeled NMR to validate the feasibility of the control system.

Aircraft Trajectories Computation-Prediction-Control. Volume 1 (La Trajectoire de l’Avion Calcul-Prediction-Controle)

DTIC Science & Technology

1990-03-01

knowledge covering problems of this type is called calculus of variations or optimal control theory (Refs. 1-8). As stated before, appli - cations occur...to the optimality conditions and the feasibility equations of Problem (GP), respectively. Clearly, after the transformation (26) is applied , the...trajectories, the primal sequential gradient-restoration algorithm (PSGRA) is applied to compute optimal trajectories for aeroassisted orbital transfer

Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

PubMed

Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong

2018-01-31

Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory

PubMed Central

Zhou, Rui; Hu, Yuxin; Qi, Yaolong

2018-01-01

Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm. PMID:29385059

SU-E-T-473: A Patient-Specific QC Paradigm Based On Trajectory Log Files and DICOM Plan Files

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

DeMarco, J; McCloskey, S; Low, D

Purpose: To evaluate a remote QC tool for monitoring treatment machine parameters and treatment workflow. Methods: The Varian TrueBeamTM linear accelerator is a digital machine that records machine axis parameters and MLC leaf positions as a function of delivered monitor unit or control point. This information is saved to a binary trajectory log file for every treatment or imaging field in the patient treatment session. A MATLAB analysis routine was developed to parse the trajectory log files for a given patient, compare the expected versus actual machine and MLC positions as well as perform a cross-comparison with the DICOM-RT planmore » file exported from the treatment planning system. The parsing routine sorts the trajectory log files based on the time and date stamp and generates a sequential report file listing treatment parameters and provides a match relative to the DICOM-RT plan file. Results: The trajectory log parsing-routine was compared against a standard record and verify listing for patients undergoing initial IMRT dosimetry verification and weekly and final chart QC. The complete treatment course was independently verified for 10 patients of varying treatment site and a total of 1267 treatment fields were evaluated including pre-treatment imaging fields where applicable. In the context of IMRT plan verification, eight prostate SBRT plans with 4-arcs per plan were evaluated based on expected versus actual machine axis parameters. The average value for the maximum RMS MLC error was 0.067±0.001mm and 0.066±0.002mm for leaf bank A and B respectively. Conclusion: A real-time QC analysis program was tested using trajectory log files and DICOM-RT plan files. The parsing routine is efficient and able to evaluate all relevant machine axis parameters during a patient treatment course including MLC leaf positions and table positions at time of image acquisition and during treatment.« less

Representing and selecting vibrational angular momentum states for quasiclassical trajectory chemical dynamics simulations.

PubMed

Lourderaj, Upakarasamy; Martínez-Núñez, Emilio; Hase, William L

2007-10-18

Linear molecules with degenerate bending modes have states, which may be represented by the quantum numbers N and L. The former gives the total energy for these modes and the latter identifies their vibrational angular momentum jz. In this work, the classical mechanical analog of the N,L-quantum states is reviewed, and an algorithm is presented for selecting initial conditions for these states in quasiclassical trajectory chemical dynamics simulations. The algorithm is illustrated by choosing initial conditions for the N = 3 and L = 3 and 1 states of CO2. Applications of this algorithm are considered for initial conditions without and with zero-point energy (zpe) included in the vibrational angular momentum states and the C-O stretching modes. The O-atom motions in the x,y-plane are determined for these states from classical trajectories in Cartesian coordinates and are compared with the motion predicted by the normal-mode model. They are only in agreement for the N = L = 3 state without vibrational angular momentum zpe. For the remaining states, the Cartesian O-atom motions are considerably different from the elliptical motion predicted by the normal-mode model. This arises from bend-stretch coupling, including centrifugal distortion, in the Cartesian trajectories, which results in tubular instead of elliptical motion. Including zpe in the C-O stretch modes introduces considerable complexity into the O-atom motions for the vibrational angular momentum states. The short-time O-atom motions for these trajectories are highly irregular and do not appear to have any identifiable characteristics. However, the O-atom motions for trajectories integrated for substantially longer period of times acquire unique properties. With C-O stretch zpe included, the long-time O-atom motion becomes tubular for trajectories integrated to approximately 14 ps for the L = 3 states and to approximately 44 ps for the L = 1 states.

Capturing Complexities of Relationship-Level Family Planning Trajectories in Malawi.

PubMed

Furnas, Hannah E

2016-09-01

In a transitioning fertility climate, preferences and decisions surrounding family planning are constantly in flux. Malawi provides an ideal case study of family planning complexities as fertility preferences are flexible, the relationship context is unstable, and childbearing begins early. I use intensive longitudinal data from Tsogolo la Thanzi-a research project in Malawi that follows young adults in romantic partnerships through the course of their relationship. I examine two questions: (1) What are the typical patterns of family planning as young adults transition through a relationship? (2) How are family planning trajectories related to individual and relationship-level characteristics? I use sequence analysis to order family planning across time and to contextualize it within each relationship. I generate and cluster the family planning trajectories and find six distinct groups of young adults who engage in family planning in similar ways. I find that family planning is complex, dynamic, and unique to each relationship. I argue that (a) family planning research should use the relationship as the unit of analysis and (b) family planning behaviors and preferences should be sequenced over time for a better understanding of key concepts, such as unmet need. © 2016 The Population Council, Inc.

Capturing Complexities of Relationship-Level Family Planning Trajectories in Malawi

PubMed Central

Furnas, Hannah E.

2017-01-01

In a transitioning fertility climate, preferences and decisions surrounding family planning are constantly in flux. Malawi provides an ideal case study of family planning complexities as fertility preferences are flexible, the relationship context is unstable, and childbearing begins early. I use intensive longitudinal data from Tsogolo la Thanzi—a research project in Malawi that follows young adults in romantic partnerships through the course of their relationship and allows me to ask two questions: (1) What are the typical patterns of family planning as young adults transition through a relationship? (2) How are family planning trajectories related to individual and relationship-level characteristics? I use sequence analysis to order family planning across time and to contextualize it within each relationship. I generate and cluster the family planning trajectories and find six distinct groups of young adults who engage in family planning in similar ways. I find that family planning is complex, dynamic, and unique to each relationship. I argue that (a) family planning research should use the relationship as the unit of analysis and (b) family planning behaviors and preferences should be sequenced over time for a better understanding of key concepts, such as unmet need. PMID:27517867

Uncovering urban human mobility from large scale taxi GPS data

NASA Astrophysics Data System (ADS)

Tang, Jinjun; Liu, Fang; Wang, Yinhai; Wang, Hua

2015-11-01

Taxi GPS trajectories data contain massive spatial and temporal information of urban human activity and mobility. Taking taxi as mobile sensors, the information derived from taxi trips benefits the city and transportation planning. The original data used in study are collected from more than 1100 taxi drivers in Harbin city. We firstly divide the city area into 400 different transportation districts and analyze the origin and destination distribution in urban area on weekday and weekend. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to cluster pick-up and drop-off locations. Furthermore, four spatial interaction models are calibrated and compared based on trajectories in shopping center of Harbin city to study the pick-up location searching behavior. By extracting taxi trips from GPS data, travel distance, time and average speed in occupied and non-occupied status are then used to investigate human mobility. Finally, we use observed OD matrix of center area in Harbin city to model the traffic distribution patterns based on entropy-maximizing method, and the estimation performance verify its effectiveness in case study.

Method and apparatus for optimizing a train trip using signal information

DOEpatents

Kumar, Ajith Kuttannair; Daum, Wolfgang; Otsubo, Tom; Hershey, John Erik; Hess, Gerald James

2013-02-05

One embodiment of the invention includes a system for operating a railway network comprising a first railway vehicle (400) during a trip along track segments (401/412/420). The system comprises a first element (65) for determining travel parameters of the first railway vehicle (400), a second element (65) for determining travel parameters of a second railway vehicle (418) relative to the track segments to be traversed by the first vehicle during the trip, a processor (62) for receiving information from the first (65) and the second (65) elements and for determining a relationship between occupation of a track segment (401/412/420) by the second vehicle (418) and later occupation of the same track segment by the first vehicle (400) and an algorithm embodied within the processor (62) having access to the information to create a trip plan that determines a speed trajectory for the first vehicle (400), wherein the speed trajectory is responsive to the relationship and further in accordance with one or more operational criteria for the first vehicle (400).

Geomagnetic matching navigation algorithm based on robust estimation

NASA Astrophysics Data System (ADS)

Xie, Weinan; Huang, Liping; Qu, Zhenshen; Wang, Zhenhuan

2017-08-01

The outliers in the geomagnetic survey data seriously affect the precision of the geomagnetic matching navigation and badly disrupt its reliability. A novel algorithm which can eliminate the outliers influence is investigated in this paper. First, the weight function is designed and its principle of the robust estimation is introduced. By combining the relation equation between the matching trajectory and the reference trajectory with the Taylor series expansion for geomagnetic information, a mathematical expression of the longitude, latitude and heading errors is acquired. The robust target function is obtained by the weight function and the mathematical expression. Then the geomagnetic matching problem is converted to the solutions of nonlinear equations. Finally, Newton iteration is applied to implement the novel algorithm. Simulation results show that the matching error of the novel algorithm is decreased to 7.75% compared to the conventional mean square difference (MSD) algorithm, and is decreased to 18.39% to the conventional iterative contour matching algorithm when the outlier is 40nT. Meanwhile, the position error of the novel algorithm is 0.017° while the other two algorithms fail to match when the outlier is 400nT.

An industrial robot singular trajectories planning based on graphs and neural networks

NASA Astrophysics Data System (ADS)

Łęgowski, Adrian; Niezabitowski, Michał

2016-06-01

Singular trajectories are rarely used because of issues during realization. A method of planning trajectories for given set of points in task space with use of graphs and neural networks is presented. In every desired point the inverse kinematics problem is solved in order to derive all possible solutions. A graph of solutions is made. The shortest path is determined to define required nodes in joint space. Neural networks are used to define the path between these nodes.

Dimensioning appropriate technical and economic parameters of elements in urban distribution power nets based on discrete fast marching method

NASA Astrophysics Data System (ADS)

Afanasyev, A. P.; Bazhenov, R. I.; Luchaninov, D. V.

2018-05-01

The main purpose of the research is to develop techniques for defining the best technical and economic trajectories of cables in urban power systems. The proposed algorithms of calculation of the routes for laying cables take into consideration topological, technical and economic features of the cabling. The discrete option of an algorithm Fast marching method is applied as a calculating tool. It has certain advantages compared to other approaches. In particular, this algorithm is cost-effective to compute, therefore, it is not iterative. Trajectories of received laying cables are considered as optimal ones from the point of view of technical and economic criteria. They correspond to the present rules of modern urban development.

Safe Onboard Guidance and Control Under Probabilistic Uncertainty

NASA Technical Reports Server (NTRS)

Blackmore, Lars James

2011-01-01

An algorithm was developed that determines the fuel-optimal spacecraft guidance trajectory that takes into account uncertainty, in order to guarantee that mission safety constraints are satisfied with the required probability. The algorithm uses convex optimization to solve for the optimal trajectory. Convex optimization is amenable to onboard solution due to its excellent convergence properties. The algorithm is novel because, unlike prior approaches, it does not require time-consuming evaluation of multivariate probability densities. Instead, it uses a new mathematical bounding approach to ensure that probability constraints are satisfied, and it is shown that the resulting optimization is convex. Empirical results show that the approach is many orders of magnitude less conservative than existing set conversion techniques, for a small penalty in computation time.

Robust control algorithms for Mars aerobraking

NASA Technical Reports Server (NTRS)

Shipley, Buford W., Jr.; Ward, Donald T.

1992-01-01

Four atmospheric guidance concepts have been adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. The first two offer improvements to the Analytic Predictor Corrector (APC) to increase its robustness to density variations. The second two are variations of a new Liapunov tracking exit phase algorithm, developed to guide the vehicle along a reference trajectory. These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. MARSGRAM is used to develop realistic atmospheres for the study. When square wave density pulses perturb the atmosphere all four controllers are successful. The algorithms are tested against atmospheres where the inbound and outbound density functions are different. Square wave density pulses are again used, but only for the outbound leg of the trajectory. Additionally, sine waves are used to perturb the density function. The new algorithms are found to be more robust than any previously tested and a Liapunov controller is selected as the most robust control algorithm overall examined.

Autonomous Rover Traverse and Precise Arm Placement on Remotely Designated Targets

NASA Technical Reports Server (NTRS)

Nesnas, Issa A.; Pivtoraiko, Mihail N.; Kelly, Alonzo; Fleder, Michael

2012-01-01

This software controls a rover platform to traverse rocky terrain autonomously, plan paths, and avoid obstacles using its stereo hazard and navigation cameras. It does so while continuously tracking a target of interest selected from 10 20 m away. The rover drives and tracks the target until it reaches the vicinity of the target. The rover then positions itself to approach the target, deploys its robotic arm, and places the end effector instrument on the designated target to within 2-3-cm accuracy of the originally selected target. This software features continuous navigation in a fairly rocky field in an outdoor environment and the ability to enable the rover to avoid large rocks and traverse over smaller ones. Using point-and-click mouse commands, a scientist designates targets in the initial imagery acquired from the rover s mast cameras. The navigation software uses stereo imaging, traversability analysis, path planning, trajectory generation, and trajectory execution. It also includes visual target tracking of a designated target selected from 10 m away while continuously navigating the rocky terrain. Improvements in this design include steering while driving, which uses continuous curvature paths. There are also several improvements to the traversability analyzer, including improved data fusion of traversability maps that result from pose estimation uncertainties, dealing with boundary effects to enable tighter maneuvers, and handling a wider range of obstacles. This work advances what has been previously developed and integrated on the Mars Exploration Rovers by using algorithms that are capable of traversing more rock-dense terrains, enabling tight, thread-the-needle maneuvers. These algorithms were integrated on the newly refurbished Athena Mars research rover, and were fielded in the JPL Mars Yard. Forty-three runs were conducted with targets at distances ranging from 5 to 15 m, and a success rate of 93% was achieved for placement of the instrument within 2-3 cm of the target.

Motion Planning of Two Stacker Cranes in a Large-Scale Automated Storage/Retrieval System

NASA Astrophysics Data System (ADS)

Kung, Yiheng; Kobayashi, Yoshimasa; Higashi, Toshimitsu; Ota, Jun

We propose a method for reducing the computational time of motion planning for stacker cranes. Most automated storage/retrieval systems (AS/RSs) are only equipped with one stacker crane. However, this is logistically challenging, and greater work efficiency in warehouses, such as those using two stacker cranes, is required. In this paper, a warehouse with two stacker cranes working simultaneously is proposed. Unlike warehouses with only one crane, trajectory planning in those with two cranes is very difficult. Since there are two cranes working together, a proper trajectory must be considered to avoid collision. However, verifying collisions is complicated and requires a considerable amount of computational time. As transport work in AS/RSs occurs randomly, motion planning cannot be conducted in advance. Planning an appropriate trajectory within a restricted duration would be a difficult task. We thereby address the current problem of motion planning requiring extensive calculation time. As a solution, we propose a “free-step” to simplify the procedure of collision verification and reduce the computational time. On the other hand, we proposed a method to reschedule the order of collision verification in order to find an appropriate trajectory in less time. By the proposed method, we reduce the calculation time to less than 1/300 of that achieved in former research.

Algorithm for Determination of Orion Ascent Abort Mode Achievability

NASA Technical Reports Server (NTRS)

Tedesco, Mark B.

2011-01-01

For human spaceflight missions, a launch vehicle failure poses the challenge of returning the crew safely to earth through environments that are often much more stressful than the nominal mission. Manned spaceflight vehicles require continuous abort capability throughout the ascent trajectory to protect the crew in the event of a failure of the launch vehicle. To provide continuous abort coverage during the ascent trajectory, different types of Orion abort modes have been developed. If a launch vehicle failure occurs, the crew must be able to quickly and accurately determine the appropriate abort mode to execute. Early in the ascent, while the Launch Abort System (LAS) is attached, abort mode selection is trivial, and any failures will result in a LAS abort. For failures after LAS jettison, the Service Module (SM) effectors are employed to perform abort maneuvers. Several different SM abort mode options are available depending on the current vehicle location and energy state. During this region of flight the selection of the abort mode that maximizes the survivability of the crew becomes non-trivial. To provide the most accurate and timely information to the crew and the onboard abort decision logic, on-board algorithms have been developed to propagate the abort trajectories based on the current launch vehicle performance and to predict the current abort capability of the Orion vehicle. This paper will provide an overview of the algorithm architecture for determining abort achievability as well as the scalar integration scheme that makes the onboard computation possible. Extension of the algorithm to assessing abort coverage impacts from Orion design modifications and launch vehicle trajectory modifications is also presented.

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

PubMed Central

De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

Planning nonlinear access paths for temporal bone surgery.

PubMed

Fauser, Johannes; Sakas, Georgios; Mukhopadhyay, Anirban

2018-05-01

Interventions at the otobasis operate in the narrow region of the temporal bone where several highly sensitive organs define obstacles with minimal clearance for surgical instruments. Nonlinear trajectories for potential minimally invasive interventions can provide larger distances to risk structures and optimized orientations of surgical instruments, thus improving clinical outcomes when compared to existing linear approaches. In this paper, we present fast and accurate planning methods for such nonlinear access paths. We define a specific motion planning problem in [Formula: see text] with notable constraints in computation time and goal pose that reflect the requirements of temporal bone surgery. We then present [Formula: see text]-RRT-Connect: two suitable motion planners based on bidirectional Rapidly exploring Random Tree (RRT) to solve this problem efficiently. The benefits of [Formula: see text]-RRT-Connect are demonstrated on real CT data of patients. Their general performance is shown on a large set of realistic synthetic anatomies. We also show that these new algorithms outperform state-of-the-art methods based on circular arcs or Bézier-Splines when applied to this specific problem. With this work, we demonstrate that preoperative and intra-operative planning of nonlinear access paths is possible for minimally invasive surgeries at the otobasis.

Direct model reference adaptive control of robotic arms

NASA Technical Reports Server (NTRS)

Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.

1993-01-01

The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Lee, Seungwon; vonAllmen, Paul; Fink, Wolfgang; Petropoulos, Anastassios; Terrile, Richard

2005-01-01

Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.

The Superior Lambert Algorithm

NASA Astrophysics Data System (ADS)

der, G.

2011-09-01

Lambert algorithms are used extensively for initial orbit determination, mission planning, space debris correlation, and missile targeting, just to name a few applications. Due to the significance of the Lambert problem in Astrodynamics, Gauss, Battin, Godal, Lancaster, Gooding, Sun and many others (References 1 to 15) have provided numerous formulations leading to various analytic solutions and iterative methods. Most Lambert algorithms and their computer programs can only work within one revolution, break down or converge slowly when the transfer angle is near zero or 180 degrees, and their multi-revolution limitations are either ignored or barely addressed. Despite claims of robustness, many Lambert algorithms fail without notice, and the users seldom have a clue why. The DerAstrodynamics lambert2 algorithm, which is based on the analytic solution formulated by Sun, works for any number of revolutions and converges rapidly at any transfer angle. It provides significant capability enhancements over every other Lambert algorithm in use today. These include improved speed, accuracy, robustness, and multirevolution capabilities as well as implementation simplicity. Additionally, the lambert2 algorithm provides a powerful tool for solving the angles-only problem without artificial singularities (pointed out by Gooding in Reference 16), which involves 3 lines of sight captured by optical sensors, or systems such as the Air Force Space Surveillance System (AFSSS). The analytic solution is derived from the extended Godal’s time equation by Sun, while the iterative method of solution is that of Laguerre, modified for robustness. The Keplerian solution of a Lambert algorithm can be extended to include the non-Keplerian terms of the Vinti algorithm via a simple targeting technique (References 17 to 19). Accurate analytic non-Keplerian trajectories can be predicted for satellites and ballistic missiles, while performing at least 100 times faster in speed than most numerical integration methods.

Trajectory control of an articulated robot with a parallel drive arm based on splines under tension

NASA Astrophysics Data System (ADS)

Yi, Seung-Jong

Today's industrial robots controlled by mini/micro computers are basically simple positioning devices. The positioning accuracy depends on the mathematical description of the robot configuration to place the end-effector at the desired position and orientation within the workspace and on following the specified path which requires the trajectory planner. In addition, the consideration of joint velocity, acceleration, and jerk trajectories are essential for trajectory planning of industrial robots to obtain smooth operation. The newly designed 6 DOF articulated robot with a parallel drive arm mechanism which permits the joint actuators to be placed in the same horizontal line to reduce the arm inertia and to increase load capacity and stiffness is selected. First, the forward kinematic and inverse kinematic problems are examined. The forward kinematic equations are successfully derived based on Denavit-Hartenberg notation with independent joint angle constraints. The inverse kinematic problems are solved using the arm-wrist partitioned approach with independent joint angle constraints. Three types of curve fitting methods used in trajectory planning, i.e., certain degree polynomial functions, cubic spline functions, and cubic spline functions under tension, are compared to select the best possible method to satisfy both smooth joint trajectories and positioning accuracy for a robot trajectory planner. Cubic spline functions under tension is the method selected for the new trajectory planner. This method is implemented for a 6 DOF articulated robot with a parallel drive arm mechanism to improve the smoothness of the joint trajectories and the positioning accuracy of the manipulator. Also, this approach is compared with existing trajectory planners, 4-3-4 polynomials and cubic spline functions, via circular arc motion simulations. The new trajectory planner using cubic spline functions under tension is implemented into the microprocessor based robot controller and motors to produce combined arc and straight-line motion. The simulation and experiment show interesting results by demonstrating smooth motion in both acceleration and jerk and significant improvements of positioning accuracy in trajectory planning.

2-Dimensional B-Spline Algorithms with Applications to Ray Tracing in Media of Spatially-Varying Refractive Index

DTIC Science & Technology

2007-08-01

In the approach, photon trajectories are computed using a solution of the Eikonal equation (ray-tracing methods) rather than linear trajectories. The...coupling the radiative transport solution into heat transfer and damage models. 15. SUBJECT TERMS: B-Splines, Ray-Tracing, Eikonal Equation...multi-layer biological tissue model. In the approach, photon trajectories are computed using a solution of the Eikonal equation (ray-tracing methods

A preliminary investigation of ROI-image reconstruction with the rebinned BPF algorithm

NASA Astrophysics Data System (ADS)

Bian, Junguo; Xia, Dan; Yu, Lifeng; Sidky, Emil Y.; Pan, Xiaochuan

2008-03-01

The back-projection filtration (BPF)algorithm is capable of reconstructing ROI images from truncated data acquired with a wide class of general trajectories. However, it has been observed that, similar to other algorithms for convergent beam geometries, the BPF algorithm involves a spatially varying weighting factor in the backprojection step. This weighting factor can not only increase the computation load, but also amplify the noise in reconstructed images The weighting factor can be eliminated by appropriately rebinning the measured cone-beam data into fan-parallel-beam data. Such an appropriate data rebinning not only removes the weighting factor, but also retain other favorable properties of the BPF algorithm. In this work, we conduct a preliminary study of the rebinned BPF algorithm and its noise property. Specifically, we consider an application in which the detector and source can move in several directions for achieving ROI data acquisition. The combined motion of the detector and source generally forms a complex trajectory. We investigate in this work image reconstruction within an ROI from data acquired in this kind of applications.

Querying databases of trajectories of differential equations 2: Index functions

NASA Technical Reports Server (NTRS)

Grossman, Robert

1991-01-01

Suppose that a large number of parameterized trajectories (gamma) of a dynamical system evolving in R sup N are stored in a database. Let eta is contained R sup N denote a parameterized path in Euclidean space, and let parallel to center dot parallel to denote a norm on the space of paths. A data structures and indices for trajectories are defined and algorithms are given to answer queries of the following forms: Query 1. Given a path eta, determine whether eta occurs as a subtrajectory of any trajectory gamma from the database. If so, return the trajectory; otherwise, return null. Query 2. Given a path eta, return the trajectory gamma from the database which minimizes the norm parallel to eta - gamma parallel.

.

NASA Astrophysics Data System (ADS)

Liu, Yuan; Zhu, Qing

2017-07-01

In order to achieve the simulation of elaborate stroke trajectories in Chinese calligraphy, this paper puts forward the innovative researching on writing momentum in the field of non-photorealistic rendering in the first time. Through the analysis of using pen in Chinese calligraphy, the writing momentum is divided into three parts: the center, the side and the back of writing brush by the judgment of the angle of brush holder. We design an algorithm for dynamic outputting writing rendering based on brush model. According to monitoring parameters such as the direction, position and normalized pressure of using pen, we calculate parameters like the footprint direction, the shape, size and nib bending after writing. The algorithm can also judge the dynamic writing trend of stroke trajectories, even automatic generate stroke trajectories by the algorithm forecasted. We achieve a more delicate rendering of Chinese calligraphy to enhance the user's operating results. And we finish the unique writing effect separated the Chinese calligraphy form other general writing results, which greatly enhances the Chinese calligraphy simulation. So that people who lack of writing skills can easily draw a beautiful charm font.

Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)

PubMed Central

Tang, Hong; Li, Liangzhi; Xiao, Nanfeng

2017-01-01

Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem in mobile robotics. However, traditional methods are not suited for robotic sensors, because of their low efficiency, instability, and non-smooth-generated paths. This paper adopts an optimizing function to generate several intermediate points and regress these discrete points to a quintic polynomial which can output a smooth trajectory for the robotic sensor. Simulations demonstrate that our approach is robust and efficient, and can be well applied in the CPSS field. PMID:28218649

Indoor Autonomous Control of a Two-Wheeled Inverted Pendulum Vehicle Using Ultra Wide Band Technology.

PubMed

Xia, Dunzhu; Yao, Yanhong; Cheng, Limei

2017-06-15

In this paper, we aimed to achieve the indoor tracking control of a two-wheeled inverted pendulum (TWIP) vehicle. The attitude data are acquired from a low cost micro inertial measurement unit (IMU), and the ultra-wideband (UWB) technology is utilized to obtain an accurate estimation of the TWIP's position. We propose a dual-loop control method to realize the simultaneous balance and trajectory tracking control for the TWIP vehicle. A robust adaptive second-order sliding mode control (2-RASMC) method based on an improved super-twisting (STW) algorithm is investigated to obtain the control laws, followed by several simulations to verify its robustness. The outer loop controller is designed using the idea of backstepping. Moreover, three typical trajectories, including a circle, a trifolium and a hexagon, have been designed to prove the adaptability of the control combinations. Six different combinations of inner and outer loop control algorithms have been compared, and the characteristics of inner and outer loop algorithm combinations have been analyzed. Simulation results demonstrate its tracking performance and thus verify the validity of the proposed control methods. Trajectory tracking experiments in a real indoor environment have been performed using our experimental vehicle to further validate the feasibility of the proposed algorithm in practice.

Indoor Autonomous Control of a Two-Wheeled Inverted Pendulum Vehicle Using Ultra Wide Band Technology

PubMed Central

Xia, Dunzhu; Yao, Yanhong; Cheng, Limei

2017-01-01

In this paper, we aimed to achieve the indoor tracking control of a two-wheeled inverted pendulum (TWIP) vehicle. The attitude data are acquired from a low cost micro inertial measurement unit (IMU), and the ultra-wideband (UWB) technology is utilized to obtain an accurate estimation of the TWIP’s position. We propose a dual-loop control method to realize the simultaneous balance and trajectory tracking control for the TWIP vehicle. A robust adaptive second-order sliding mode control (2-RASMC) method based on an improved super-twisting (STW) algorithm is investigated to obtain the control laws, followed by several simulations to verify its robustness. The outer loop controller is designed using the idea of backstepping. Moreover, three typical trajectories, including a circle, a trifolium and a hexagon, have been designed to prove the adaptability of the control combinations. Six different combinations of inner and outer loop control algorithms have been compared, and the characteristics of inner and outer loop algorithm combinations have been analyzed. Simulation results demonstrate its tracking performance and thus verify the validity of the proposed control methods. Trajectory tracking experiments in a real indoor environment have been performed using our experimental vehicle to further validate the feasibility of the proposed algorithm in practice. PMID:28617338

Rapid near-optimal aerospace plane trajectory generation and guidance

NASA Technical Reports Server (NTRS)

Calise, A. J.; Corban, J. E.; Markopoulos, N.

1991-01-01

Effort was directed toward the problems of the real time trajectory optimization and guidance law development for the National Aerospace Plane (NASP) applications. In particular, singular perturbation methods were used to develop guidance algorithms suitable for onboard, real time implementation. The progress made in this research effort is reported.

Numerical study and ex vivo assessment of HIFU treatment time reduction through optimization of focal point trajectory

NASA Astrophysics Data System (ADS)

Grisey, A.; Yon, S.; Pechoux, T.; Letort, V.; Lafitte, P.

2017-03-01

Treatment time reduction is a key issue to expand the use of high intensity focused ultrasound (HIFU) surgery, especially for benign pathologies. This study aims at quantitatively assessing the potential reduction of the treatment time arising from moving the focal point during long pulses. In this context, the optimization of the focal point trajectory is crucial to achieve a uniform thermal dose repartition and avoid boiling. At first, a numerical optimization algorithm was used to generate efficient trajectories. Thermal conduction was simulated in 3D with a finite difference code and damages to the tissue were modeled using the thermal dose formula. Given an initial trajectory, the thermal dose field was first computed, then, making use of Pontryagin's maximum principle, the trajectory was iteratively refined. Several initial trajectories were tested. Then, an ex vivo study was conducted in order to validate the efficicency of the resulting optimized strategies. Single pulses were performed at 3MHz on fresh veal liver samples with an Echopulse and the size of each unitary lesion was assessed by cutting each sample along three orthogonal planes and measuring the dimension of the whitened area based on photographs. We propose a promising approach to significantly shorten HIFU treatment time: the numerical optimization algorithm was shown to provide a reliable insight on trajectories that can improve treatment strategies. The model must now be improved in order to take in vivo conditions into account and extensively validated.

Finite-Time and -Size Scalings in the Evaluation of Large Deviation Functions. Numerical Analysis in Continuous Time

NASA Astrophysics Data System (ADS)

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provide a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to a selection rule that favors the rare trajectories of interest. However, such algorithms are plagued by finite simulation time- and finite population size- effects that can render their use delicate. Using the continuous-time cloning algorithm, we analyze the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of the rare trajectories. We use these scalings in order to propose a numerical approach which allows to extract the infinite-time and infinite-size limit of these estimators.

Spinal pedicle screw planning using deformable atlas registration.

PubMed

Goerres, J; Uneri, A; De Silva, T; Ketcha, M; Reaungamornrat, S; Jacobson, M; Vogt, S; Kleinszig, G; Osgood, G; Wolinsky, J-P; Siewerdsen, J H

2017-04-07

Spinal screw placement is a challenging task due to small bone corridors and high risk of neurological or vascular complications, benefiting from precision guidance/navigation and quality assurance (QA). Implicit to both guidance and QA is the definition of a surgical plan-i.e. the desired trajectories and device selection for target vertebrae-conventionally requiring time-consuming manual annotations by a skilled surgeon. We propose automation of such planning by deriving the pedicle trajectory and device selection from a patient's preoperative CT or MRI. An atlas of vertebrae surfaces was created to provide the underlying basis for automatic planning-in this work, comprising 40 exemplary vertebrae at three levels of the spine (T7, T8, and L3). The atlas was enriched with ideal trajectory annotations for 60 pedicles in total. To define trajectories for a given patient, sparse deformation fields from the atlas surfaces to the input (CT or MR image) are applied on the annotated trajectories. Mean value coordinates are used to interpolate dense deformation fields. The pose of a straight trajectory is optimized by image-based registration to an accumulated volume of the deformed annotations. For evaluation, input deformation fields were created using coherent point drift (CPD) to perform a leave-one-out analysis over the atlas surfaces. CPD registration demonstrated surface error of 0.89  ±  0.10 mm (median  ±  interquartile range) for T7/T8 and 1.29  ±  0.15 mm for L3. At the pedicle center, registered trajectories deviated from the expert reference by 0.56  ±  0.63 mm (T7/T8) and 1.12  ±  0.67 mm (L3). The predicted maximum screw diameter differed by 0.45  ±  0.62 mm (T7/T8), and 1.26  ±  1.19 mm (L3). The automated planning method avoided screw collisions in all cases and demonstrated close agreement overall with expert reference plans, offering a potentially valuable tool in support of surgical guidance and QA.

Management by Trajectory: Trajectory Management Study Report

NASA Technical Reports Server (NTRS)

Leiden, Kenneth; Atkins, Stephen; Fernandes, Alicia D.; Kaler, Curt; Bell, Alan; Kilbourne, Todd; Evans, Mark

2017-01-01

In order to realize the full potential of the Next Generation Air Transportation System (NextGen), improved management along planned trajectories between air navigation service providers (ANSPs) and system users (e.g., pilots and airline dispatchers) is needed. Future automation improvements and increased data communications between aircraft and ground automation would make the concept of Management by Trajectory (MBT) possible.

Stereoelectroencephalography Using Magnetic Resonance Angiography for Avascular Trajectory Planning: Technical Report.

PubMed

Minkin, Krasimir; Gabrovski, Kaloyan; Penkov, Marin; Todorov, Yuri; Tanova, Rositsa; Milenova, Yoana; Romansky, Kiril; Dimova, Petia

2017-10-01

Stereoelectroencephalography (SEEG) requires high-quality angiographic studies because avascular trajectory planning is a prerequisite for the safety of this procedure. Some epilepsy surgery groups have begun to use computed tomography angiography and magnetic resonance T1-weighted sequence with contrast enhancement for this purpose. To present the first series of patients with avascular trajectory planning of SEEG based on magnetic resonance angiography (MRA). Thirty-six SEEG explorations for drug-resistant focal epilepsy were performed from January 2013 to December 2015. A retrospective analysis of this consecutive surgical series was then performed. Magnetic resonance imaging included MRA with a modified contrast-enhanced magnetic resonance venography (MRV) protocol with a short acquisition delay, which allowed simultaneous arterial and venous visualization. Our criteria for satisfactory MRA were the visualization of at least first-order branches of the angular artery, paracentral and calcarine artery, and third-order tributaries of the superficial Sylvian vein, vein of Labbe, and vein of Trolard. Thirty-four patients underwent 36 SEEG explorations with 369 electrodes carrying 4321 contacts. Contrast-enhanced MRA using the MRV protocol was judged satisfactory for SEEG planning in all explorations. Postoperative complications were not observed in our series of 36 SEEG explorations, which included 50 transopercular insular trajectories. MRA using an MRV protocol may be applied for avascular trajectory planning during SEEG procedures. This technique provides a simultaneous visualization of cortical arteries and veins without the need for additional radiation exposure or intra-arterial catheter placement. Copyright © 2017 by the Congress of Neurological Surgeons

Cross-Polar Aircraft Trajectory Optimization and Potential Climate Impact

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Chen, Neil; Ng, Hok

2011-01-01

Cross-Polar routes offer new opportunities for air travel markets. Transpolar flights reduce travel times, fuel burns, and associated environmental emissions by flying direct paths between many North American and Asian cities. This study evaluates the potential benefits of flying wind-optimal polar routes and assessed their potential impact on climate change. An optimization algorithm is developed for transpolar flights to generate wind-optimal trajectories that minimize climate impact of aircraft, in terms of global warming potentials (relative to warming by one kg of CO2) of several types of emissions, while avoiding regions of airspace that facilitate persistent contrail formation. Estimations of global warming potential are incorporated into the objective function of the optimization algorithm to assess the climate impact of aircraft emissions discharged at a given location and altitude. The regions of airspace with very low ambient temperature and areas favorable to persistent contrail formation are modeled as undesirable regions that aircraft should avoid and are formulated as soft state constraints. The fuel burn and climate impact of cross-polar air traffic flying various types of trajectory including flightplan, great circle, wind-optimal, and contrail-avoidance are computed for 15 origin-destination pairs between major international airports in the U.S. and Asia. Wind-optimal routes reduce average fuel burn of flight plan routes by 4.4% on December 4, 2010 and 8.0% on August 7, 2010, respectively. The tradeoff between persistent contrail formation and additional global warming potential of aircraft emissions is investigated with and without altitude optimization. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a one percent increase in additional global warming potential, a climate impact equivalent to that of 4070kg and 4220kg CO2 emission, reduces 135 and 105 minutes persistent contrail formation per flight during a day with medium and high contrail formation, respectively.

SELENE Translunar Trajectory Reconfiguration Plan Provided for the Case of Main Engine Anomaly

NASA Technical Reports Server (NTRS)

Kawakatsu, Yasuhiro

2007-01-01

In this paper, the reconfiguration of translunar trajectory in case of main engine anomaly is investigated. The objectives of the trajectory design are to reduce the excessive velocity at the Lunar encounter as well as to reduce the total required Delta-v to complete the sequence. 3-impulse Hohmann transfer based trajectory is adopted and possible trajectories are categorized under 2-body approximation. The solutions obtained are applied to more sophisticated models (3-body approximation and 4-body) and yields feasible trajectory.

Targeting Ballistic Lunar Capture Trajectories Using Periodic Orbits in the Sun-Earth CRTBP

NASA Technical Reports Server (NTRS)

Cooley, D.S.; Griesemer, Paul Ricord; Ocampo, Cesar

2009-01-01

A particular periodic orbit in the Earth-Sun circular restricted three body problem is shown to have the characteristics needed for a ballistic lunar capture transfer. An injection from a circular parking orbit into the periodic orbit serves as an initial guess for a targeting algorithm. By targeting appropriate parameters incrementally in increasingly complicated force models and using precise derivatives calculated from the state transition matrix, a reliable algorithm is produced. Ballistic lunar capture trajectories in restricted four body systems are shown to be able to be produced in a systematic way.

Multi-rendezvous low-thrust trajectory optimization using costate transforming and homotopic approach

NASA Astrophysics Data System (ADS)

Chen, Shiyu; Li, Haiyang; Baoyin, Hexi

2018-06-01

This paper investigates a method for optimizing multi-rendezvous low-thrust trajectories using indirect methods. An efficient technique, labeled costate transforming, is proposed to optimize multiple trajectory legs simultaneously rather than optimizing each trajectory leg individually. Complex inner-point constraints and a large number of free variables are one main challenge in optimizing multi-leg transfers via shooting algorithms. Such a difficulty is reduced by first optimizing each trajectory leg individually. The results may be, next, utilized as an initial guess in the simultaneous optimization of multiple trajectory legs. In this paper, the limitations of similar techniques in previous research is surpassed and a homotopic approach is employed to improve the convergence efficiency of the shooting process in multi-rendezvous low-thrust trajectory optimization. Numerical examples demonstrate that newly introduced techniques are valid and efficient.

Dynamics and control of robot for capturing objects in space

NASA Astrophysics Data System (ADS)

Huang, Panfeng

Space robots are expected to perform intricate tasks in future space services, such as satellite maintenance, refueling, and replacing the orbital replacement unit (ORU). To realize these missions, the capturing operation may not be avoided. Such operations will encounter some challenges because space robots have some unique characteristics unfound on ground-based robots, such as, dynamic singularities, dynamic coupling between manipulator and space base, limited energy supply and working without a fixed base, and so on. In addition, since contacts and impacts may not be avoided during capturing operation. Therefore, dynamics and control problems of space robot for capturing objects are significant research topics if the robots are to be deployed for the space services. A typical servicing operation mainly includes three phases: capturing the object, berthing and docking the object, then repairing the target. Therefore, this thesis will focus on resolving some challenging problems during capturing the object, berthing and docking, and so on. In this thesis, I study and analyze the dynamics and control problems of space robot for capturing objects. This work has potential impact in space robotic applications. I first study the contact and impact dynamics of space robot and objects. I specifically focus on analyzing the impact dynamics and mapping the relationship of influence and speed. Then, I develop the fundamental theory for planning the minimum-collision based trajectory of space robot and designing the configuration of space robot at the moment of capture. To compensate for the attitude of the space base during the capturing approach operation, a new balance control concept which can effectively balance the attitude of the space base using the dynamic couplings is developed. The developed balance control concept helps to understand of the nature of space dynamic coupling, and can be readily applied to compensate or minimize the disturbance to the space base. After capturing the object, the space robot must complete the following two tasks: one is to berth the object, and the other is to re-orientate the attitude of the whole robot system for communication and power supply. Therefore, I propose a method to accomplish these two tasks simultaneously using manipulator motion only. The ultimate goal of space services is to realize the capture and manipulation autonomously. Therefore, I propose an affective approach based on learning human skill to track and capture the objects automatically in space. With human-teaching demonstration, the space robot is able to learn and abstract human tracking and capturing skill using an efficient neural-network learning architecture that combines flexible Cascade Neural Networks with Node Decoupled Extended Kalman Filtering (CNN-NDEKF). The simulation results attest that this approach is useful and feasible in tracking trajectory planning and capturing of space robot. Finally I propose a novel approach based on Genetic Algorithms (GAs) to optimize the approach trajectory of space robots in order to realize effective and stable operations. I complete the minimum-torque path planning in order to save the limited energy in space, and design the minimum jerk trajectory for the stabilization of the space manipulator and its space base. These optimal algorithms are very important and useful for the application of space robot.

LINEAR LATTICE AND TRAJECTORY RECONSTRUCTION AND CORRECTION AT FAST LINEAR ACCELERATOR

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

Romanov, A.; Edstrom, D.; Halavanau, A.

2017-07-16

The low energy part of the FAST linear accelerator based on 1.3 GHz superconducting RF cavities was successfully commissioned [1]. During commissioning, beam based model dependent methods were used to correct linear lattice and trajectory. Lattice correction algorithm is based on analysis of beam shape from profile monitors and trajectory responses to dipole correctors. Trajectory responses to field gradient variations in quadrupoles and phase variations in superconducting RF cavities were used to correct bunch offsets in quadrupoles and accelerating cavities relative to their magnetic axes. Details of used methods and experimental results are presented.

Highly efficient, very low-thrust transfer to geosynchronous orbit - Exact and approximate solutions

NASA Astrophysics Data System (ADS)

Redding, D. C.

1984-04-01

An overview is provided of the preflight, postflight, and accuracy analysis of the Titan IIIC launch vehicle that injects payloads into geosynchronous orbits. The postflight trajectory reconstruction plays an important role in determining payload injection accuracy. Furthermore, the postflight analysis provides useful information about the characteristics of measuring instruments subjected to a flight environment. Suitable approaches for meeting mission specifications, trajectory requirements, and instrument constraints are considered, taking into account the importance of preflight trajectory analysis activities. Gimbal flip avoidance algorithms in the flight software, and considerable beta gimbal analysis ensures a singularity-free trajectory.

Parallel Monotonic Basin Hopping for Low Thrust Trajectory Optimization

NASA Technical Reports Server (NTRS)

McCarty, Steven L.; McGuire, Melissa L.

2018-01-01

Monotonic Basin Hopping has been shown to be an effective method of solving low thrust trajectory optimization problems. This paper outlines an extension to the common serial implementation by parallelizing it over any number of available compute cores. The Parallel Monotonic Basin Hopping algorithm described herein is shown to be an effective way to more quickly locate feasible solutions, and improve locally optimal solutions in an automated way without requiring a feasible initial guess. The increased speed achieved through parallelization enables the algorithm to be applied to more complex problems that would otherwise be impractical for a serial implementation. Low thrust cislunar transfers and a hybrid Mars example case demonstrate the effectiveness of the algorithm. Finally, a preliminary scaling study quantifies the expected decrease in solve time compared to a serial implementation.,

A spatial operator algebra for manipulator modeling and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.; Jain, A.

1989-01-01

A spatial operator algebra for modeling the control and trajectory design of manipulation is discussed, with emphasis on its analytical formulation and implementation in the Ada programming language. The elements of this algebra are linear operators whose domain and range spaces consist of forces, moments, velocities, and accelerations. The effect of these operators is equivalent to a spatial recursion along the span of the manipulator. Inversion is obtained using techniques of recursive filtering and smoothing. The operator alegbra provides a high-level framework for describing the dynamic and kinematic behavior of a manipulator and control and trajectory design algorithms. Implementable recursive algorithms can be immediately derived from the abstract operator expressions by inspection, thus greatly simplifying the transition from an abstract problem formulation and solution to the detailed mechanization of a specific algorithm.

A Primer on Autonomous Aerial Vehicle Design

PubMed Central

Coppejans, Hugo H. G.; Myburgh, Herman C.

2015-01-01

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers. PMID:26633410

A Primer on Autonomous Aerial Vehicle Design.

PubMed

Coppejans, Hugo H G; Myburgh, Herman C

2015-12-02

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers.

Collision-free coordination of fiber positioners in multi-object spectrographs

NASA Astrophysics Data System (ADS)

Makarem, Laleh; Kneib, Jean-Paul; Gillet, Denis

2016-07-01

Many fiber-fed spectroscopic survey projects, such as DESI, PFS and MOONS, will use thousands of fiber positioners packed at a focal plane. To maximize observation time, the positioners need to move simultaneously and reach their targets swiftly. We have previously presented a motion planning method based on a decentralized navigation function for the collision-free coordination of the fiber positioners in DESI. In MOONS, the end effector of each positioner handling the fiber can reach the centre of its neighbours. There is therefore a risk of collision with up to 18 surrounding positioners in the chosen dense hexagonal configuration. Moreover, the length of the second arm of the positioner is almost twice the length of the first one. As a result, the geometry of the potential collision zone between two positioners is not limited to the extremity of their end-effector, but surrounds the second arm. In this paper, we modify the navigation function to take into account the larger collision zone resulting from the extended geometrical shape of the positioners. The proposed navigation function takes into account the configuration of the positioners as well as the constraints on the actuators, such as their maximal velocity and their mechanical clearance. Considering the fact that all the positioners' bases are fixed to the focal plane, collisions can occur locally and the risk of collision is limited to the 18 surrounding positioners. The decentralizing motion planning and trajectory generation takes advantage of this limited number of positioners and the locality of collisions, hence significantly reduces the complexity of the algorithm to a linear order. The linear complexity ensures short computation time. In addition, the time needed to move all the positioners to their targets is independent of the number of positioners. These two key advantages of the chosen decentralization approach turn this method to a promising solution for the collision-free motion-planning problem in the next- generation spectroscopic survey projects. A motion planning simulator, exploited as a software prototype, has been developed in Python. The pre-computed collision-free trajectories of the actuators of all the positioners are fed directly from the simulator to the electronics controlling the motors. A successful demonstration of the effectiveness of these trajectories on the real positioners as well as their simulated counterparts are put side by side in the following online video sequence (https://goo.gl/YuwwsE).

Fast direct fourier reconstruction of radial and PROPELLER MRI data using the chirp transform algorithm on graphics hardware.

PubMed

Feng, Yanqiu; Song, Yanli; Wang, Cong; Xin, Xuegang; Feng, Qianjin; Chen, Wufan

2013-10-01

To develop and test a new algorithm for fast direct Fourier transform (DrFT) reconstruction of MR data on non-Cartesian trajectories composed of lines with equally spaced points. The DrFT, which is normally used as a reference in evaluating the accuracy of other reconstruction methods, can reconstruct images directly from non-Cartesian MR data without interpolation. However, DrFT reconstruction involves substantially intensive computation, which makes the DrFT impractical for clinical routine applications. In this article, the Chirp transform algorithm was introduced to accelerate the DrFT reconstruction of radial and Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI data located on the trajectories that are composed of lines with equally spaced points. The performance of the proposed Chirp transform algorithm-DrFT algorithm was evaluated by using simulation and in vivo MRI data. After implementing the algorithm on a graphics processing unit, the proposed Chirp transform algorithm-DrFT algorithm achieved an acceleration of approximately one order of magnitude, and the speed-up factor was further increased to approximately three orders of magnitude compared with the traditional single-thread DrFT reconstruction. Implementation the Chirp transform algorithm-DrFT algorithm on the graphics processing unit can efficiently calculate the DrFT reconstruction of the radial and PROPELLER MRI data. Copyright © 2012 Wiley Periodicals, Inc.

A Novel Zero Velocity Interval Detection Algorithm for Self-Contained Pedestrian Navigation System with Inertial Sensors

PubMed Central

Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan

2016-01-01

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

DOE PAGES

Chatzidakis, Stylianos; Liu, Zhengzhi; Hayward, Jason P.; ...

2018-03-28

Here, this work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstructionmore » algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS are explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm’s precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm RMS for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. Finally, the effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.« less

A generalized muon trajectory estimation algorithm with energy loss for application to muon tomography

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

Chatzidakis, Stylianos; Liu, Zhengzhi; Hayward, Jason P.

Here, this work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification applications has recently gained attention due to the non-intrusive and passive nature of the inspection, penetrating capabilities, as well as recent advances in detectors that measure position and direction of the individual muons before and after traversing the imaged object. However, muon image reconstruction techniques are limited in resolution due to low muon flux and the effects of multiple Coulomb scattering (MCS). Current reconstructionmore » algorithms, e.g., point of closest approach (PoCA) or straight-line path (SLP), rely on overly simple assumptions for muon path estimation through the imaged object. For robust muon tomography, efficient and flexible physics-based algorithms are needed to model the MCS process and accurately estimate the most probable trajectory of a muon as it traverses an object. In the present work, the use of a Bayesian framework and a Gaussian approximation of MCS are explored for estimation of the most likely path of a cosmic ray muon traversing uniform or nonuniform media and undergoing MCS. The algorithm’s precision is compared to Monte Carlo simulated muon trajectories. It was found that the algorithm is expected to be able to predict muon tracks to less than 1.5 mm RMS for 0.5 GeV muons and 0.25 mm RMS for 3 GeV muons, a 50% improvement compared to SLP and 15% improvement when compared to PoCA. Further, a 30% increase in useful muon flux was observed relative to PoCA. Muon track prediction improved for higher muon energies or smaller penetration depth where energy loss is not significant. Finally, the effect of energy loss due to ionization is investigated, and a linear energy loss relation that is easy to use is proposed.« less

A composite controller for trajectory tracking applied to the Furuta pendulum.

PubMed

Aguilar-Avelar, Carlos; Moreno-Valenzuela, Javier

2015-07-01

In this paper, a new composite scheme is proposed, where the total control action is composed of the sum of a feedback-linearization-based controller and an energy-based compensation. This new proposition is applied to the rotary inverted pendulum or Furuta pendulum. The Furuta pendulum is a well-known underactuated mechanical system with two degrees of freedom. The control objective in this case is the tracking of a desired periodic trajectory in the actuated joint, while the unactuated link is regulated at the upward position. The closed-loop system is analyzed showing uniformly ultimately boundedness of the error trajectories. The design procedure is shown in a constructive form, such that it may be applied to other underactuated mechanical systems, with the proper definitions of the output function and the energy function. Numerical simulations and real-time experiments show the practical viability of the controller. Finally, the proposed algorithm is compared with a tracking controller previously reported in the literature. The new algorithm shows better performance in both arm trajectory tracking and pendulum regulation. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Towards Assessing the Human Trajectory Planning Horizon

PubMed Central

Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models. PMID:27936015

Towards Assessing the Human Trajectory Planning Horizon.

PubMed

Carton, Daniel; Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models.

Testing of advanced technique for linear lattice and closed orbit correction by modeling its application for iota ring at Fermilab

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

Romanov, A.

Many modern and most future accelerators rely on precise configuration of lattice and trajectory. The Integrable Optics Test Accelerator (IOTA) at Fermilab that is coming to final stages of construction will be used to test advanced approaches of control over particles dynamics. Various experiments planned at IOTA require high flexibility of lattice configuration as well as high precision of lattice and closed orbit control. Dense element placement does not allow to have ideal configuration of diagnostics and correctors for all planned experiments. To overcome this limitations advanced method of lattice an beneficial for other machines. Developed algorithm is based onmore » LOCO approach, extended with various sets of other experimental data, such as dispersion, BPM BPM phase advances, beam shape information from synchrotron light monitors, responses of closed orbit bumps to variations of focusing elements and other. Extensive modeling of corrections for a big number of random seed errors is used to illustrate benefits from developed approach.« less

Planning and executing motions for multibody systems in free-fall. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Cameron, Jonathan M.

1991-01-01

The purpose of this research is to develop an end-to-end system that can be applied to a multibody system in free-fall to analyze its possible motions, save those motions in a database, and design a controller that can execute those motions. A goal is for the process to be highly automated and involve little human intervention. Ideally, the output of the system would be data and algorithms that could be put in ROM to control the multibody system in free-fall. The research applies to more than just robots in space. It applies to any multibody system in free-fall. Mathematical techniques from nonlinear control theory were used to study the nature of the system dynamics and its possible motions. Optimization techniques were applied to plan motions. Image compression techniques were proposed to compress the precomputed motion data for storage. A linearized controller was derived to control the system while it executes preplanned trajectories.

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

PubMed

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

Flight Dynamics Operations: Methods and Lessons Learned from Space Shuttle Orbit Operations

NASA Technical Reports Server (NTRS)

Cutri-Kohart, Rebecca M.

2011-01-01

The Flight Dynamics Officer is responsible for trajectory maintenance of the Space Shuttle. This paper will cover high level operational considerations, methodology, procedures, and lessons learned involved in performing the functions of orbit and rendezvous Flight Dynamics Officer and leading the team of flight dynamics specialists during different phases of flight. The primary functions that will be address are: onboard state vector maintenance, ground ephemeris maintenance, calculation of ground and spacecraft acquisitions, collision avoidance, burn targeting for the primary mission, rendezvous, deorbit and contingencies, separation sequences, emergency deorbit preparation, mass properties coordination, payload deployment planning, coordination with the International Space Station, and coordination with worldwide trajectory customers. Each of these tasks require the Flight Dynamics Officer to have cognizance of the current trajectory state as well as the impact of future events on the trajectory plan in order to properly analyze and react to real-time changes. Additionally, considerations are made to prepare flexible alternative trajectory plans in the case timeline changes or a systems failure impact the primary plan. The evolution of the methodology, procedures, and techniques used by the Flight Dynamics Officer to perform these tasks will be discussed. Particular attention will be given to how specific Space Shuttle mission and training simulation experiences, particularly off-nominal or unexpected events such as shortened mission durations, tank failures, contingency deorbit, navigation errors, conjunctions, and unexpected payload deployments, have influenced the operational procedures and training for performing Space Shuttle flight dynamics operations over the history of the program. These lessons learned can then be extended to future vehicle trajectory operations.

Use of automated rendezvous trajectory planning to improve spacecraft operations efficiency

NASA Technical Reports Server (NTRS)

Mulder, Tom A.

1991-01-01

The current planning process for space shuttle rendezvous with a second Earth-orbiting vehicle is time consuming and costly. It is a labor-intensive, manual process performed pre-mission with the aid of specialized maneuver processing tools. Real-time execution of a rendezvous plan must closely follow a predicted trajectory, and targeted solutions leading up to the terminal phase are computed on the ground. Despite over 25 years of Gemini, Apollo, Skylab, and shuttle vehicle-to-vehicle rendezvous missions flown to date, rendezvous in Earth orbit still requires careful monitoring and cannot be taken for granted. For example, a significant trajectory offset was experienced during terminal phase rendezvous of the STS-32 Long Duration Exposure Facility retrieval mission. Several improvements can be introduced to the present rendezvous planning process to reduce costs, produce more fuel-efficient profiles, and increase the probability of mission success.

Development of an Interval Management Algorithm Using Ground Speed Feedback for Delayed Traffic

NASA Technical Reports Server (NTRS)

Barmore, Bryan E.; Swieringa, Kurt A.; Underwood, Matthew C.; Abbott, Terence; Leonard, Robert D.

2016-01-01

One of the goals of NextGen is to enable frequent use of Optimized Profile Descents (OPD) for aircraft, even during periods of peak traffic demand. NASA is currently testing three new technologies that enable air traffic controllers to use speed adjustments to space aircraft during arrival and approach operations. This will allow an aircraft to remain close to their OPD. During the integration of these technologies, it was discovered that, due to a lack of accurate trajectory information for the leading aircraft, Interval Management aircraft were exhibiting poor behavior. NASA's Interval Management algorithm was modified to address the impact of inaccurate trajectory information and a series of studies were performed to assess the impact of this modification. These studies show that the modification provided some improvement when the Interval Management system lacked accurate trajectory information for the leading aircraft.

Toward autonomous avian-inspired grasping for micro aerial vehicles.

PubMed

Thomas, Justin; Loianno, Giuseppe; Polin, Joseph; Sreenath, Koushil; Kumar, Vijay

2014-06-01

Micro aerial vehicles, particularly quadrotors, have been used in a wide range of applications. However, the literature on aerial manipulation and grasping is limited and the work is based on quasi-static models. In this paper, we draw inspiration from agile, fast-moving birds such as raptors, that are able to capture moving prey on the ground or in water, and develop similar capabilities for quadrotors. We address dynamic grasping, an approach to prehensile grasping in which the dynamics of the robot and its gripper are significant and must be explicitly modeled and controlled for successful execution. Dynamic grasping is relevant for fast pick-and-place operations, transportation and delivery of objects, and placing or retrieving sensors. We show how this capability can be realized (a) using a motion capture system and (b) without external sensors relying only on onboard sensors. In both cases we describe the dynamic model, and trajectory planning and control algorithms. In particular, we present a methodology for flying and grasping a cylindrical object using feedback from a monocular camera and an inertial measurement unit onboard the aerial robot. This is accomplished by mapping the dynamics of the quadrotor to a level virtual image plane, which in turn enables dynamically-feasible trajectory planning for image features in the image space, and a vision-based controller with guaranteed convergence properties. We also present experimental results obtained with a quadrotor equipped with an articulated gripper to illustrate both approaches.

Preliminary clinical trial in percutaneous nephrolithotomy using a real-time navigation system for percutaneous kidney access

NASA Astrophysics Data System (ADS)

Rodrigues, Pedro L.; Moreira, António H. J.; Rodrigues, Nuno F.; Pinho, A. C. M.; Fonseca, Jaime C.; Lima, Estevão.; Vilaça, João. L.

2014-03-01

Background: Precise needle puncture of renal calyces is a challenging and essential step for successful percutaneous nephrolithotomy. This work tests and evaluates, through a clinical trial, a real-time navigation system to plan and guide percutaneous kidney puncture. Methods: A novel system, entitled i3DPuncture, was developed to aid surgeons in establishing the desired puncture site and the best virtual puncture trajectory, by gathering and processing data from a tracked needle with optical passive markers. In order to navigate and superimpose the needle to a preoperative volume, the patient, 3D image data and tracker system were previously registered intraoperatively using seven points that were strategically chosen based on rigid bone structures and nearby kidney area. In addition, relevant anatomical structures for surgical navigation were automatically segmented using a multi-organ segmentation algorithm that clusters volumes based on statistical properties and minimum description length criterion. For each cluster, a rendering transfer function enhanced the visualization of different organs and surrounding tissues. Results: One puncture attempt was sufficient to achieve a successful kidney puncture. The puncture took 265 seconds, and 32 seconds were necessary to plan the puncture trajectory. The virtual puncture path was followed correctively until the needle tip reached the desired kidney calyceal. Conclusions: This new solution provided spatial information regarding the needle inside the body and the possibility to visualize surrounding organs. It may offer a promising and innovative solution for percutaneous punctures.

Design of the VISITOR Tool: A Versatile ImpulSive Interplanetary Trajectory OptimizeR

NASA Technical Reports Server (NTRS)

Corpaccioli, Luca; Linskens, Harry; Komar, David R.

2014-01-01

The design of trajectories for interplanetary missions represents one of the most complex and important problems to solve during conceptual space mission design. To facilitate conceptual mission sizing activities, it is essential to obtain sufficiently accurate trajectories in a fast and repeatable manner. To this end, the VISITOR tool was developed. This tool modularly augments a patched conic MGA-1DSM model with a mass model, launch window analysis, and the ability to simulate more realistic arrival and departure operations. This was implemented in MATLAB, exploiting the built-in optimization tools and vector analysis routines. The chosen optimization strategy uses a grid search and pattern search, an iterative variable grid method. A genetic algorithm can be selectively used to improve search space pruning, at the cost of losing the repeatability of the results and increased computation time. The tool was validated against seven flown missions: the average total mission (Delta)V offset from the nominal trajectory was 9.1%, which was reduced to 7.3% when using the genetic algorithm at the cost of an increase in computation time by a factor 5.7. It was found that VISITOR was well-suited for the conceptual design of interplanetary trajectories, while also facilitating future improvements due to its modular structure.

Cherry-picking functionally relevant substates from long md trajectories using a stratified sampling approach.

PubMed

Chandramouli, Balasubramanian; Mancini, Giordano

2016-01-01

Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

WE-G-BRF-07: Non-Circular Scanning Trajectories with Varian Developer Mode

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

Davis, A; Pearson, E; Pan, X

2014-06-15

Purpose: Cone-beam CT (CBCT) in image-guide radiation therapy (IGRT) typicallyacquires scan data via the circular trajectory of the linearaccelerator's (linac) gantry rotation. Though this lends itself toanalytic reconstruction algorithms like FDK, iterative reconstructionalgorithms allow for a broader range of scanning trajectories. Weimplemented a non-circular scanning trajectory with Varian's TrueBeamDeveloper Mode and performed some preliminary reconstructions toverify the geometry. Methods: We used TrueBeam Developer Mode to program a new scanning trajectorythat increases the field of view (FOV) along the gantry rotation axiswithout moving the patient. This trajectory consisted of moving thegantry in a circle, then translating the source and detector alongmore » theaxial direction before acquiring another circular scan 19 cm away fromthe first. The linear portion of the trajectory includes an additional4.5 cm above and below the axial planes of the source's circularrotation. We scanned a calibration phantom consisting of a lucite tubewith a spiral pattern of CT spots and used the maximum-likelihoodalgorithm to iteratively reconstruct the CBCT volume. Results: With the TrueBeam trajectory definition, we acquired projection dataof the calibration phantom using the previously described trajectory.We obtained a scan of the treatment couch for log normalization byscanning with the same trajectory but without the phantom present.Using the nominal geometric parameters reported in the projectionheaders with our iterative reconstruction algorithm, we obtained acorrect reconstruction of the calibration phantom. Conclusion: The ability to implement new scanning trajectories with the TrueBeamDeveloper Mode enables us access to a new parameter space for imagingwith CBCT for IGRT. Previous simulations and simple dual circle scanshave shown iterative reconstruction with non-circular trajectories canincrease the axial FOV with CBCT. Use of Developer Mode allowsexperimentally testing these and other new scanning trajectories. Support was provided in part by the University of Chicago Research Computing Center, Varian Medical Systems, and NIH Grants 1RO1CA120540, T32EB002103, S10 RR021039 and P30 CA14599. The contents of this work are solely the responsibility of the authors and do not necessarily represent the official views of the supporting organizations.« less

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberger, Mark

2016-01-01

This paper describes an algorithm for atmospheric state estimation based on a coupling between inertial navigation and flush air data-sensing pressure measurements. The navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to estimate the atmosphere using a nonlinear weighted least-squares algorithm. The approach uses a high-fidelity model of atmosphere stored in table-lookup form, along with simplified models propagated along the trajectory within the algorithm to aid the solution. Thus, the method is a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content. The algorithm is applied to the design of the pressure measurement system for the Mars 2020 mission. A linear covariance analysis is performed to assess estimator performance. The results indicate that the new estimator produces more precise estimates of atmospheric states than existing algorithms.

An adaptive guidance algorithm for an aerodynamically assisted orbital plane change maneuver. M.S. Thesis

NASA Technical Reports Server (NTRS)

Blissit, J. A.

1986-01-01

Using analysis results from the post trajectory optimization program, an adaptive guidance algorithm is developed to compensate for density, aerodynamic and thrust perturbations during an atmospheric orbital plane change maneuver. The maneuver offers increased mission flexibility along with potential fuel savings for future reentry vehicles. Although designed to guide a proposed NASA Entry Research Vehicle, the algorithm is sufficiently generic for a range of future entry vehicles. The plane change analysis provides insight suggesting a straight-forward algorithm based on an optimized nominal command profile. Bank angle, angle of attack, and engine thrust level, ignition and cutoff times are modulated to adjust the vehicle's trajectory to achieve the desired end-conditions. A performance evaluation of the scheme demonstrates a capability to guide to within 0.05 degrees of the desired plane change and five nautical miles of the desired apogee altitude while maintaining heating constraints. The algorithm is tested under off-nominal conditions of + or -30% density biases, two density profile models, + or -15% aerodynamic uncertainty, and a 33% thrust loss and for various combinations of these conditions.

Multi Sector Planning Tools for Trajectory-Based Operations

NASA Technical Reports Server (NTRS)

Prevot, Thomas; Mainini, Matthew; Brasil, Connie

2010-01-01

This paper discusses a suite of multi sector planning tools for trajectory-based operations that were developed and evaluated in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. The toolset included tools for traffic load and complexity assessment as well as trajectory planning and coordination. The situation assessment tools included an integrated suite of interactive traffic displays, load tables, load graphs, and dynamic aircraft filters. The planning toolset allowed for single and multi aircraft trajectory planning and data communication-based coordination of trajectories between operators. Also newly introduced was a real-time computation of sector complexity into the toolset that operators could use in lieu of aircraft count to better estimate and manage sector workload, especially in situations with convective weather. The tools were used during a joint NASA/FAA multi sector planner simulation in the AOL in 2009 that had multiple objectives with the assessment of the effectiveness of the tools being one of them. Current air traffic control operators who were experienced as area supervisors and traffic management coordinators used the tools throughout the simulation and provided their usefulness and usability ratings in post simulation questionnaires. This paper presents these subjective assessments as well as the actual usage data that was collected during the simulation. The toolset was rated very useful and usable overall. Many elements received high scores by the operators and were used frequently and successfully. Other functions were not used at all, but various requests for new functions and capabilities were received that could be added to the toolset.

Orbiter/carrier separation for the ALT free flight no. 1 reference trajectories. Mission planning, mission analysis and software formulation

NASA Technical Reports Server (NTRS)

Glenn, G. M.

1976-01-01

Details of the generation of the separation trajectories are discussed. The analysis culminated in definition of separation trajectories between physical separation and orbiter/carrier vortex clearance. Specifications, assumptions and analytical approach used to generate the separation trajectories are presented. Results of the analytical approach are evaluated. Conclusions and recommendations are summarized. Supporting references are listed.

Minimum time acceleration of aircraft turbofan engines by using an algorithm based on nonlinear programming

NASA Technical Reports Server (NTRS)

Teren, F.

1977-01-01

Minimum time accelerations of aircraft turbofan engines are presented. The calculation of these accelerations was made by using a piecewise linear engine model, and an algorithm based on nonlinear programming. Use of this model and algorithm allows such trajectories to be readily calculated on a digital computer with a minimal expenditure of computer time.

Enhancements on the Convex Programming Based Powered Descent Guidance Algorithm for Mars Landing

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Blackmore, Lars; Scharf, Daniel P.; Wolf, Aron

2008-01-01

In this paper, we present enhancements on the powered descent guidance algorithm developed for Mars pinpoint landing. The guidance algorithm solves the powered descent minimum fuel trajectory optimization problem via a direct numerical method. Our main contribution is to formulate the trajectory optimization problem, which has nonconvex control constraints, as a finite dimensional convex optimization problem, specifically as a finite dimensional second order cone programming (SOCP) problem. SOCP is a subclass of convex programming, and there are efficient SOCP solvers with deterministic convergence properties. Hence, the resulting guidance algorithm can potentially be implemented onboard a spacecraft for real-time applications. Particularly, this paper discusses the algorithmic improvements obtained by: (i) Using an efficient approach to choose the optimal time-of-flight; (ii) Using a computationally inexpensive way to detect the feasibility/ infeasibility of the problem due to the thrust-to-weight constraint; (iii) Incorporating the rotation rate of the planet into the problem formulation; (iv) Developing additional constraints on the position and velocity to guarantee no-subsurface flight between the time samples of the temporal discretization; (v) Developing a fuel-limited targeting algorithm; (vi) Initial result on developing an onboard table lookup method to obtain almost fuel optimal solutions in real-time.

Acoustic window planning for ultrasound acquisition.

PubMed

Göbl, Rüdiger; Virga, Salvatore; Rackerseder, Julia; Frisch, Benjamin; Navab, Nassir; Hennersperger, Christoph

2017-06-01

Autonomous robotic ultrasound has recently gained considerable interest, especially for collaborative applications. Existing methods for acquisition trajectory planning are solely based on geometrical considerations, such as the pose of the transducer with respect to the patient surface. This work aims at establishing acoustic window planning to enable autonomous ultrasound acquisitions of anatomies with restricted acoustic windows, such as the liver or the heart. We propose a fully automatic approach for the planning of acquisition trajectories, which only requires information about the target region as well as existing tomographic imaging data, such as X-ray computed tomography. The framework integrates both geometrical and physics-based constraints to estimate the best ultrasound acquisition trajectories with respect to the available acoustic windows. We evaluate the developed method using virtual planning scenarios based on real patient data as well as for real robotic ultrasound acquisitions on a tissue-mimicking phantom. The proposed method yields superior image quality in comparison with a naive planning approach, while maintaining the necessary coverage of the target. We demonstrate that by taking image formation properties into account acquisition planning methods can outperform naive plannings. Furthermore, we show the need for such planning techniques, since naive approaches are not sufficient as they do not take the expected image quality into account.

Results of the Magnetometer Navigation (MAGNAV)lnflight Experiment

NASA Technical Reports Server (NTRS)

Thienel, Julie K.; Harman, Richard R.; Bar-Itzhack, Itzhack Y.; Lambertson, Mike

2004-01-01

The Magnetometer Navigation (MAGNAV) algorithm is currently running as a flight experiment as part of the Wide Field Infrared Explorer (WIRE) Post-Science Engineering Testbed. Initialization of MAGNAV occurred on September 4, 2003. MAGNAV is designed to autonomously estimate the spacecraft orbit, attitude, and rate using magnetometer and sun sensor data. Since the Earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computed magnetic field and measured magnetic field components, as measured by the magnetometer throughout the entire spacecraft orbit, are a function of the spacecraft trajectory and attitude errors. Therefore, these errors are used to estimate both trajectory and attitude. In addition, the time rate of change of the magnetic field vector is used to estimate the spacecraft rotation rate. The estimation of the attitude and trajectory is augmented with the rate estimation into an Extended Kalman filter blended with a pseudo-linear Kalman filter. Sun sensor data is also used to improve the accuracy and observability of the attitude and rate estimates. This test serves to validate MAGNAV as a single low cost navigation system which utilizes reliable, flight qualified sensors. MAGNAV is intended as a backup algorithm, an initialization algorithm, or possibly a prime navigation algorithm for a mission with coarse requirements. Results from the first six months of operation are presented.

Study of recognizing multiple persons' complicated hand gestures from the video sequence acquired by a moving camera

NASA Astrophysics Data System (ADS)

Dan, Luo; Ohya, Jun

2010-02-01

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.

Improving Cancer Detection and Dose Efficiency in Dedicated Breast Cancer CT

DTIC Science & Technology

2010-02-01

source trajectory and data truncation, which can however be solved with the back-projection filtration ( BPF ) algorithm [6,7]. I have used the BPF ...high to low radiation dose levels. I have investigated noise properties in images reconstructed by use of FDK and BPF algorithms at different noise...analytic algorithms such as the FDK and BPF algorithms are applied to sparse-view data, the reconstruction images will contain artifacts such as streak

A General Event Location Algorithm with Applications to Eclipse and Station Line-of-Sight

NASA Technical Reports Server (NTRS)

Parker, Joel J. K.; Hughes, Steven P.

2011-01-01

A general-purpose algorithm for the detection and location of orbital events is developed. The proposed algorithm reduces the problem to a global root-finding problem by mapping events of interest (such as eclipses, station access events, etc.) to continuous, differentiable event functions. A stepping algorithm and a bracketing algorithm are used to detect and locate the roots. Examples of event functions and the stepping/bracketing algorithms are discussed, along with results indicating performance and accuracy in comparison to commercial tools across a variety of trajectories.

A General Event Location Algorithm with Applications to Eclispe and Station Line-of-Sight

NASA Technical Reports Server (NTRS)

Parker, Joel J. K.; Hughes, Steven P.

2011-01-01

A general-purpose algorithm for the detection and location of orbital events is developed. The proposed algorithm reduces the problem to a global root-finding problem by mapping events of interest (such as eclipses, station access events, etc.) to continuous, differentiable event functions. A stepping algorithm and a bracketing algorithm are used to detect and locate the roots. Examples of event functions and the stepping/bracketing algorithms are discussed, along with results indicating performance and accuracy in comparison to commercial tools across a variety of trajectories.

Vectorization of a classical trajectory code on a floating point systems, Inc. Model 164 attached processor.

PubMed

Kraus, Wayne A; Wagner, Albert F

1986-04-01

A triatomic classical trajectory code has been modified by extensive vectorization of the algorithms to achieve much improved performance on an FPS 164 attached processor. Extensive timings on both the FPS 164 and a VAX 11/780 with floating point accelerator are presented as a function of the number of trajectories simultaneously run. The timing tests involve a potential energy surface of the LEPS variety and trajectories with 1000 time steps. The results indicate that vectorization results in timing improvements on both the VAX and the FPS. For larger numbers of trajectories run simultaneously, up to a factor of 25 improvement in speed occurs between VAX and FPS vectorized code. Copyright © 1986 John Wiley & Sons, Inc.

Interactive orbital proximity operations planning system instruction and training guide

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1994-01-01

This guide instructs users in the operation of a Proximity Operations Planning System. This system uses an interactive graphical method for planning fuel-efficient rendezvous trajectories in the multi-spacecraft environment of the space station and allows the operator to compose a multi-burn transfer trajectory between orbit initial chaser and target trajectories. The available task time (window) of the mission is predetermined and the maneuver is subject to various operational constraints, such as departure, arrival, spatial, plume impingement, and en route passage constraints. The maneuvers are described in terms of the relative motion experienced in a space station centered coordinate system. Both in-orbital plane as well as out-of-orbital plane maneuvering is considered. A number of visual optimization aids are used for assisting the operator in reaching fuel-efficient solutions. These optimization aids are based on the Primer Vector theory. The visual feedback of trajectory shapes, operational constraints, and optimization functions, provided by user-transparent and continuously active background computations, allows the operator to make fast, iterative design changes that rapidly converge to fuel-efficient solutions. The planning tool is an example of operator-assisted optimization of nonlinear cost functions.

A ballistic mission to fly by Comet Halley

NASA Technical Reports Server (NTRS)

Boain, R. J.; Hastrup, R. C.

1980-01-01

The paper describes the available options, ballistic trajectory opportunities, and a preliminary reference trajectory that were selected as a basis for spacecraft design studies and programmatic planning for a Halley ballistic intercept mission in 1986. The paper also presents trajectory, performance, and navigation data which support the preliminary selection.

Novel algorithm and MATLAB-based program for automated power law analysis of single particle, time-dependent mean-square displacement

NASA Astrophysics Data System (ADS)

Umansky, Moti; Weihs, Daphne

2012-08-01

In many physical and biophysical studies, single-particle tracking is utilized to reveal interactions, diffusion coefficients, active modes of driving motion, dynamic local structure, micromechanics, and microrheology. The basic analysis applied to those data is to determine the time-dependent mean-square displacement (MSD) of particle trajectories and perform time- and ensemble-averaging of similar motions. The motion of particles typically exhibits time-dependent power-law scaling, and only trajectories with qualitatively and quantitatively comparable MSD should be ensembled. Ensemble averaging trajectories that arise from different mechanisms, e.g., actively driven and diffusive, is incorrect and can result inaccurate correlations between structure, mechanics, and activity. We have developed an algorithm to automatically and accurately determine power-law scaling of experimentally measured single-particle MSD. Trajectories can then categorized and grouped according to user defined cutoffs of time, amplitudes, scaling exponent values, or combinations. Power-law fits are then provided for each trajectory alongside categorized groups of trajectories, histograms of power laws, and the ensemble-averaged MSD of each group. The codes are designed to be easily incorporated into existing user codes. We expect that this algorithm and program will be invaluable to anyone performing single-particle tracking, be it in physical or biophysical systems. Catalogue identifier: AEMD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMD_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 25 892 No. of bytes in distributed program, including test data, etc.: 5 572 780 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.11 (2010b) or higher, program should also be backwards compatible. Symbolic Math Toolboxes (5.5) is required. The Curve Fitting Toolbox (3.0) is recommended. Computer: Tested on Windows only, yet should work on any computer running MATLAB. In Windows 7, should be used as administrator, if the user is not the administrator the program may not be able to save outputs and temporary outputs to all locations. Operating system: Any supporting MATLAB (MathWorks Inc.) v7.11 / 2010b or higher. Supplementary material: Sample output files (approx. 30 MBytes) are available. Classification: 12 External routines: Several MATLAB subfunctions (m-files), freely available on the web, were used as part of and included in, this code: count, NaN suite, parseArgs, roundsd, subaxis, wcov, wmean, and the executable pdfTK.exe. Nature of problem: In many physical and biophysical areas employing single-particle tracking, having the time-dependent power-laws governing the time-averaged meansquare displacement (MSD) of a single particle is crucial. Those power laws determine the mode-of-motion and hint at the underlying mechanisms driving motion. Accurate determination of the power laws that describe each trajectory will allow categorization into groups for further analysis of single trajectories or ensemble analysis, e.g. ensemble and time-averaged MSD. Solution method: The algorithm in the provided program automatically analyzes and fits time-dependent power laws to single particle trajectories, then group particles according to user defined cutoffs. It accepts time-dependent trajectories of several particles, each trajectory is run through the program, its time-averaged MSD is calculated, and power laws are determined in regions where the MSD is linear on a log-log scale. Our algorithm searches for high-curvature points in experimental data, here time-dependent MSD. Those serve as anchor points for determining the ranges of the power-law fits. Power-law scaling is then accurately determined and error estimations of the parameters and quality of fit are provided. After all single trajectory time-averaged MSDs are fit, we obtain cutoffs from the user to categorize and segment the power laws into groups; cutoff are either in exponents of the power laws, time of appearance of the fits, or both together. The trajectories are sorted according to the cutoffs and the time- and ensemble-averaged MSD of each group is provided, with histograms of the distributions of the exponents in each group. The program then allows the user to generate new trajectory files with trajectories segmented according to the determined groups, for any further required analysis. Additional comments: README file giving the names and a brief description of all the files that make-up the package and clear instructions on the installation and execution of the program is included in the distribution package. Running time: On an i5 Windows 7 machine with 4 GB RAM the automated parts of the run (excluding data loading and user input) take less than 45 minutes to analyze and save all stages for an 844 trajectory file, including optional PDF save. Trajectory length did not affect run time (tested up to 3600 frames/trajectory), which was on average 3.2±0.4 seconds per trajectory.

A real-time guidance algorithm for aerospace plane optimal ascent to low earth orbit

NASA Technical Reports Server (NTRS)

Calise, A. J.; Flandro, G. A.; Corban, J. E.

1989-01-01

Problems of onboard trajectory optimization and synthesis of suitable guidance laws for ascent to low Earth orbit of an air-breathing, single-stage-to-orbit vehicle are addressed. A multimode propulsion system is assumed which incorporates turbojet, ramjet, Scramjet, and rocket engines. An algorithm for generating fuel-optimal climb profiles is presented. This algorithm results from the application of the minimum principle to a low-order dynamic model that includes angle-of-attack effects and the normal component of thrust. Maximum dynamic pressure and maximum aerodynamic heating rate constraints are considered. Switching conditions are derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another. A nonlinear transformation technique is employed to derived a feedback controller for tracking the computed trajectory. Numerical results illustrate the nature of the resulting fuel-optimal climb paths.

Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberger, Mark; Shidner, Jeremy; Munk, Michelle

2013-01-01

The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012.

Estimation of flow properties using surface deformation and head data: A trajectory-based approach

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

Vasco, D.W.

2004-07-12

A trajectory-based algorithm provides an efficient and robust means to infer flow properties from surface deformation and head data. The algorithm is based upon the concept of an ''arrival time'' of a drawdown front, which is defined as the time corresponding to the maximum slope of the drawdown curve. The technique involves three steps: the inference of head changes as a function of position and time, the use of the estimated head changes to define arrival times, and the inversion of the arrival times for flow properties. Trajectories, computed from the output of a numerical simulator, are used to relatemore » the drawdown arrival times to flow properties. The inversion algorithm is iterative, requiring one reservoir simulation for each iteration. The method is applied to data from a set of 14 tiltmeters, located at the Raymond Quarry field site in California. Using the technique, I am able to image a high-conductivity channel which extends to the south of the pumping well. The presence of th is permeable pathway is supported by an analysis of earlier cross-well transient pressure test data.« less

Autonomous proximity operations using machine vision for trajectory control and pose estimation

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Sternberg, Stanley R.

1991-01-01

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

Comparison between Mean Forces and Swarms-of-Trajectories String Methods.

PubMed

Maragliano, Luca; Roux, Benoît; Vanden-Eijnden, Eric

2014-02-11

The original formulation of the string method in collective variable space is compared with a recent variant called string method with swarms-of-trajectories. The assumptions made in the original method are revisited and the significance of the minimum free energy path (MFEP) is discussed in the context of reactive events. These assumptions are compared to those made in the string method with swarms-of-trajectories, and shown to be equivalent in a certain regime: in particular an expression for the path identified by the swarms-of-trajectories method is given and shown to be closely related to the MFEP. Finally, the algorithmic aspects of both methods are compared.

Trajectories for a Near Term Mission to the Interstellar Medium

NASA Technical Reports Server (NTRS)

Arora, Nitin; Strange, Nathan; Alkalai, Leon

2015-01-01

Trajectories for rapid access to the interstellar medium (ISM) with a Kuiper Belt Object (KBO) flyby, launching between 2022 and 2030, are described. An impulsive-patched-conic broad search algorithm combined with a local optimizer is used for the trajectory computations. Two classes of trajectories, (1) with a powered Jupiter flyby and (2) with a perihelion maneuver, are studied and compared. Planetary flybys combined with leveraging maneuvers reduce launch C3 requirements (by factor of 2 or more) and help satisfy mission-phasing constraints. Low launch C3 combined with leveraging and a perihelion maneuver is found to be enabling for a near-term potential mission to the ISM.

The analysis of control trajectories using symbolic and database computing

NASA Technical Reports Server (NTRS)

Grossman, Robert

1995-01-01

This final report comprises the formal semi-annual status reports for this grant for the periods June 30-December 31, 1993, January 1-June 30, 1994, and June 1-December 31, 1994. The research supported by this grant is broadly concerned with the symbolic computation, mixed numeric-symbolic computation, and database computation of trajectories of dynamical systems, especially control systems. A review of work during the report period covers: trajectories and approximating series, the Cayley algebra of trees, actions of differential operators, geometrically stable integration algorithms, hybrid systems, trajectory stores, PTool, and other activities. A list of publications written during the report period is attached.

Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment.

PubMed

Liu, Hai-Ying; Skjetne, Erik; Kobernus, Mike

2013-11-04

We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations.

Interactive orbital proximity operations planning system

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1989-01-01

An interactive, graphical proximity operations planning system was developed which allows on-site design of efficient, complex, multiburn maneuvers in the dynamic multispacecraft environment about the space station. Maneuvering takes place in, as well as out of, the orbital plane. The difficulty in planning such missions results from the unusual and counterintuitive character of relative orbital motion trajectories and complex operational constraints, which are both time varying and highly dependent on the mission scenario. This difficulty is greatly overcome by visualizing the relative trajectories and the relative constraints in an easily interpretable, graphical format, which provides the operator with immediate feedback on design actions. The display shows a perspective bird's-eye view of the space station and co-orbiting spacecraft on the background of the station's orbital plane. The operator has control over two modes of operation: (1) a viewing system mode, which enables him or her to explore the spatial situation about the space station and thus choose and frame in on areas of interest; and (2) a trajectory design mode, which allows the interactive editing of a series of way-points and maneuvering burns to obtain a trajectory which complies with all operational constraints. Through a graphical interactive process, the operator will continue to modify the trajectory design until all operational constraints are met. The effectiveness of this display format in complex trajectory design is presently being evaluated in an ongoing experimental program.

Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment

PubMed Central

2013-01-01

We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations. PMID:24188173

SU-F-J-133: Adaptive Radiation Therapy with a Four-Dimensional Dose Calculation Algorithm That Optimizes Dose Distribution Considering Breathing Motion

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

Ali, I; Algan, O; Ahmad, S

Purpose: To model patient motion and produce four-dimensional (4D) optimized dose distributions that consider motion-artifacts in the dose calculation during the treatment planning process. Methods: An algorithm for dose calculation is developed where patient motion is considered in dose calculation at the stage of the treatment planning. First, optimal dose distributions are calculated for the stationary target volume where the dose distributions are optimized considering intensity-modulated radiation therapy (IMRT). Second, a convolution-kernel is produced from the best-fitting curve which matches the motion trajectory of the patient. Third, the motion kernel is deconvolved with the initial dose distribution optimized for themore » stationary target to produce a dose distribution that is optimized in four-dimensions. This algorithm is tested with measured doses using a mobile phantom that moves with controlled motion patterns. Results: A motion-optimized dose distribution is obtained from the initial dose distribution of the stationary target by deconvolution with the motion-kernel of the mobile target. This motion-optimized dose distribution is equivalent to that optimized for the stationary target using IMRT. The motion-optimized and measured dose distributions are tested with the gamma index with a passing rate of >95% considering 3% dose-difference and 3mm distance-to-agreement. If the dose delivery per beam takes place over several respiratory cycles, then the spread-out of the dose distributions is only dependent on the motion amplitude and not affected by motion frequency and phase. This algorithm is limited to motion amplitudes that are smaller than the length of the target along the direction of motion. Conclusion: An algorithm is developed to optimize dose in 4D. Besides IMRT that provides optimal dose coverage for a stationary target, it extends dose optimization to 4D considering target motion. This algorithm provides alternative to motion management techniques such as beam-gating or breath-holding and has potential applications in adaptive radiation therapy.« less

The symbolic computation and automatic analysis of trajectories

NASA Technical Reports Server (NTRS)

Grossman, Robert

1991-01-01

Research was generally done on computation of trajectories of dynamical systems, especially control systems. Algorithms were further developed for rewriting expressions involving differential operators. The differential operators involved arise in the local analysis of nonlinear control systems. An initial design was completed of the system architecture for software to analyze nonlinear control systems using data base computing.

Hierarchical Control and Trajectory Planning

NASA Technical Reports Server (NTRS)

Martin, Clyde F.; Horn, P. W.

1994-01-01

Most of the time on this project was spent on the trajectory planning problem. The construction is equivalent to the classical spline construction in the case that the system matrix is nilpotent. If the dimension of the system is n then the spline of degree 2n-1 is constructed. This gives a new approach to the construction of splines that is more efficient than the usual construction and at the same time allows the construction of a much larger class of splines. All known classes of splines are reconstructed using the approach of linear control theory. As a numerical analysis tool control theory gives a very good tool for constructing splines. However, for the purposes of trajectory planning it is quite another story. Enclosed in this document are four reports done under this grant.

Statistical methods for launch vehicle guidance, navigation, and control (GN&C) system design and analysis

NASA Astrophysics Data System (ADS)

Rose, Michael Benjamin

A novel trajectory and attitude control and navigation analysis tool for powered ascent is developed. The tool is capable of rapid trade-space analysis and is designed to ultimately reduce turnaround time for launch vehicle design, mission planning, and redesign work. It is streamlined to quickly determine trajectory and attitude control dispersions, propellant dispersions, orbit insertion dispersions, and navigation errors and their sensitivities to sensor errors, actuator execution uncertainties, and random disturbances. The tool is developed by applying both Monte Carlo and linear covariance analysis techniques to a closed-loop, launch vehicle guidance, navigation, and control (GN&C) system. The nonlinear dynamics and flight GN&C software models of a closed-loop, six-degree-of-freedom (6-DOF), Monte Carlo simulation are formulated and developed. The nominal reference trajectory (NRT) for the proposed lunar ascent trajectory is defined and generated. The Monte Carlo truth models and GN&C algorithms are linearized about the NRT, the linear covariance equations are formulated, and the linear covariance simulation is developed. The performance of the launch vehicle GN&C system is evaluated using both Monte Carlo and linear covariance techniques and their trajectory and attitude control dispersion, propellant dispersion, orbit insertion dispersion, and navigation error results are validated and compared. Statistical results from linear covariance analysis are generally within 10% of Monte Carlo results, and in most cases the differences are less than 5%. This is an excellent result given the many complex nonlinearities that are embedded in the ascent GN&C problem. Moreover, the real value of this tool lies in its speed, where the linear covariance simulation is 1036.62 times faster than the Monte Carlo simulation. Although the application and results presented are for a lunar, single-stage-to-orbit (SSTO), ascent vehicle, the tools, techniques, and mathematical formulations that are discussed are applicable to ascent on Earth or other planets as well as other rocket-powered systems such as sounding rockets and ballistic missiles.

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

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

Levine, Benjamin G., E-mail: ben.levine@temple.ed; Stone, John E., E-mail: johns@ks.uiuc.ed; Kohlmeyer, Axel, E-mail: akohlmey@temple.ed

2011-05-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU's memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm aremore » presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 s per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis.« less

Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units—Radial Distribution Function Histogramming

PubMed Central

Stone, John E.; Kohlmeyer, Axel

2011-01-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU’s memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm are presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 seconds per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis. PMID:21547007

A Search Algorithm for Generating Alternative Process Plans in Flexible Manufacturing System

NASA Astrophysics Data System (ADS)

Tehrani, Hossein; Sugimura, Nobuhiro; Tanimizu, Yoshitaka; Iwamura, Koji

Capabilities and complexity of manufacturing systems are increasing and striving for an integrated manufacturing environment. Availability of alternative process plans is a key factor for integration of design, process planning and scheduling. This paper describes an algorithm for generation of alternative process plans by extending the existing framework of the process plan networks. A class diagram is introduced for generating process plans and process plan networks from the viewpoint of the integrated process planning and scheduling systems. An incomplete search algorithm is developed for generating and searching the process plan networks. The benefit of this algorithm is that the whole process plan network does not have to be generated before the search algorithm starts. This algorithm is applicable to large and enormous process plan networks and also to search wide areas of the network based on the user requirement. The algorithm can generate alternative process plans and to select a suitable one based on the objective functions.

Aeroassisted orbit transfer vehicle trajectory analysis

NASA Technical Reports Server (NTRS)

Braun, Robert D.; Suit, William T.

1988-01-01

The emphasis in this study was on the use of multiple pass trajectories for aerobraking. However, for comparison, single pass trajectories, trajectories using ballutes, and trajectories corrupted by atmospheric anomolies were run. A two-pass trajectory was chosen to determine the relation between sensitivity to errors and payload to orbit. Trajectories that used only aerodynamic forces for maneuvering could put more weight into the target orbits but were very sensitive to variations from the planned trajectors. Using some thrust control resulted in less payload to orbit, but greatly reduced the sensitivity to variations from nominal trajectories. When compared to the non-thrusting trajectories investigated, the judicious use of thrusting resulted in multiple pass trajectories that gave 97 percent of the payload to orbit with almost none of the sensitivity to variations from the nominal.

Testing algorithms for critical slowing down

NASA Astrophysics Data System (ADS)

Cossu, Guido; Boyle, Peter; Christ, Norman; Jung, Chulwoo; Jüttner, Andreas; Sanfilippo, Francesco

2018-03-01

We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC) algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among physical observables thus tackling the critical slowing down towards the continuum limit. We present a comparison of costs of the new algorithms with the standard HMC evolution for pure gauge fields, studying the autocorrelation times for various quantities including the topological charge.

Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management

NASA Technical Reports Server (NTRS)

Kaplan, Carolyn; Dahm, Johann; Oran, Elaine; Alexandrov, Natalia; Boris, Jay

2011-01-01

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.

Dynamic whole-body robotic manipulation

NASA Astrophysics Data System (ADS)

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

2013-05-01

The creation of dynamic manipulation behaviors for high degree of freedom, mobile robots will allow them to accomplish increasingly difficult tasks in the field. We are investigating how the coordinated use of the body, legs, and integrated manipulator, on a mobile robot, can improve the strength, velocity, and workspace when handling heavy objects. We envision that such a capability would aid in a search and rescue scenario when clearing obstacles from a path or searching a rubble pile quickly. Manipulating heavy objects is especially challenging because the dynamic forces are high and a legged system must coordinate all its degrees of freedom to accomplish tasks while maintaining balance. To accomplish these types of manipulation tasks, we use trajectory optimization techniques to generate feasible open-loop behaviors for our 28 dof quadruped robot (BigDog) by planning trajectories in a 13 dimensional space. We apply the Covariance Matrix Adaptation (CMA) algorithm to solve for trajectories that optimize task performance while also obeying important constraints such as torque and velocity limits, kinematic limits, and center of pressure location. These open-loop behaviors are then used to generate desired feed-forward body forces and foot step locations, which enable tracking on the robot. Some hardware results for cinderblock throwing are demonstrated on the BigDog quadruped platform augmented with a human-arm-like manipulator. The results are analogous to how a human athlete maximizes distance in the discus event by performing a precise sequence of choreographed steps.

Computer program documentation user information for the MPAD trajectory tape print program (TRJPR1)

NASA Technical Reports Server (NTRS)

Gibbs, P. M.

1981-01-01

The Trajectory Tape Print Program (TRJPR1) was developed to print applicable information from a Space Trajectory tape created by the Mission Planning and Analysis Division (MPAD) in the MPAD Common Format for the on-orbit phase of the Mission. Instructions for TRJPR1's use are given.

Visual display aid for orbital maneuvering - Experimental evaluation

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Ellis, Stephen R.

1993-01-01

An interactive proximity operations planning system, which allows on-site planning of fuel-efficient, multiburn maneuvers in a potential multispacecraft environment, has been experimentally evaluated. An experiment has been carried out in which nonastronaut operators with brief initial training were required to plan a trajectory to retrieve an object accidentally separated from a dual-keel Space Station, for a variety of different orbital situations. The experiments have shown that these operators were able to plan workable trajectories, satisfying a number of operational constraints. Fuel use and planning time were strongly correlated, both with the angle at which the object was separated and with the existence of spatial constraints. Planning behavior was found to be strongly operator-dependent. This finding calls for the need for standardizing planning strategies through operator training or the use of semiautomated planning schemes.

Performance Assessment of Model-Based Optimal Feedforward and Feedback Current Profile Control in NSTX-U using the TRANSP Code

NASA Astrophysics Data System (ADS)

Ilhan, Z.; Wehner, W. P.; Schuster, E.; Boyer, M. D.; Gates, D. A.; Gerhardt, S.; Menard, J.

2015-11-01

Active control of the toroidal current density profile is crucial to achieve and maintain high-performance, MHD-stable plasma operation in NSTX-U. A first-principles-driven, control-oriented model describing the temporal evolution of the current profile has been proposed earlier by combining the magnetic diffusion equation with empirical correlations obtained at NSTX-U for the electron density, electron temperature, and non-inductive current drives. A feedforward + feedback control scheme for the requlation of the current profile is constructed by embedding the proposed nonlinear, physics-based model into the control design process. Firstly, nonlinear optimization techniques are used to design feedforward actuator trajectories that steer the plasma to a desired operating state with the objective of supporting the traditional trial-and-error experimental process of advanced scenario planning. Secondly, a feedback control algorithm to track a desired current profile evolution is developed with the goal of adding robustness to the overall control scheme. The effectiveness of the combined feedforward + feedback control algorithm for current profile regulation is tested in predictive simulations carried out in TRANSP. Supported by PPPL.

Meshless Modeling of Deformable Shapes and their Motion

PubMed Central

Adams, Bart; Ovsjanikov, Maks; Wand, Michael; Seidel, Hans-Peter; Guibas, Leonidas J.

2010-01-01

We present a new framework for interactive shape deformation modeling and key frame interpolation based on a meshless finite element formulation. Starting from a coarse nodal sampling of an object’s volume, we formulate rigidity and volume preservation constraints that are enforced to yield realistic shape deformations at interactive frame rates. Additionally, by specifying key frame poses of the deforming shape and optimizing the nodal displacements while targeting smooth interpolated motion, our algorithm extends to a motion planning framework for deformable objects. This allows reconstructing smooth and plausible deformable shape trajectories in the presence of possibly moving obstacles. The presented results illustrate that our framework can handle complex shapes at interactive rates and hence is a valuable tool for animators to realistically and efficiently model and interpolate deforming 3D shapes. PMID:24839614

Keeping up appearances: the role of identity concealment in the workplace among adults with degenerative eye conditions and its relationship with wellbeing and career outcomes.

PubMed

Spiegel, Tali; De Bel, Vera; Steverink, Nardi

2016-01-01

This study aims to describe the interplay between the work trajectories and the passing patterns of individuals with degenerative eye conditions in different phases of their career, as well as the disease progression and the career and well-being outcomes associated with different works and passing trajectories. Qualitative interviews on the topic of work trajectories were conducted with 36 working or retired individuals with degenerative eye conditions. The "bigger picture" method was used to explore passing and concealment behavioral patterns, and their associations with various work trajectories. Five patterns of passing and concealment behavior in the workplace were identified and were linked with various work trajectories among visually impaired study participants: (1) no career adjustments, concealed condition throughout career; (2) revealed condition after adjusting career plans; (3) increasingly open about their condition over the course of their career; (4) engaged in career planning, always open about their condition; and (5) engaged in limited career planning, always open about their condition. Patterns characterized by less planning and more identity concealment were associated with more stress and lower levels of self-acceptance, while patterns characterized by more planning for vision deterioration and less passing behavior were associated with higher levels self-acceptance and fewer obstacles over the course of an individual's career. The study's findings can serve as a guide for health professionals. Many individuals with degenerative eye conditions try to conceal their identity as visually impaired in the professional setting. Different aspects of career outcomes (e.g. age of retirement) and wellbeing outcomes (e.g. self-acceptance and stress) associate with identity concealment patterns of individuals throughout their careers. Identifying concealment patterns will allow health professionals to tackle particular adverse outcomes and challenges associated with these patterns.

Optimal flight trajectories in the presence of windshear, 1984-86

NASA Technical Reports Server (NTRS)

Miele, A.

1986-01-01

Optimal flight trajectories were determined in the presence of windshear and guidance schemes were developed for near optimum flight in a windshear. This is a wind characterized by sharp change in intensity and direction over a relatively small region of space. This problem is important in the takeoff and landing of both civilian airplanes and military airplanes and is key to aircraft saftey. The topics covered in reference to takeoff problems are: equations of motion, problem formulation, algorithms, optimal flight trajectories, advanced guidance schemes, simplified guidance schemes, and piloting strategies.

Human arm stiffness and equilibrium-point trajectory during multi-joint movement.

PubMed

Gomi, H; Kawato, M

1997-03-01

By using a newly designed high-performance manipulandum and a new estimation algorithm, we measured human multi-joint arm stiffness parameters during multi-joint point-to-point movements on a horizontal plane. This manipulandum allows us to apply a sufficient perturbation to subject's arm within a brief period during movement. Arm stiffness parameters were reliably estimated using a new algorithm, in which all unknown structural parameters could be estimated independent of arm posture (i.e., constant values under any arm posture). Arm stiffness during transverse movement was considerably greater than that during corresponding posture, but not during a longitudinal movement. Although the ratios of elbow, shoulder, and double-joint stiffness were varied in time, the orientation of stiffness ellipses during the movement did not change much. Equilibrium-point trajectories that were predicted from measured stiffness parameters and actual trajectories were slightly sinusoidally curved in Cartesian space and their velocity profiles were quite different from the velocity profiles of actual hand trajectories. This result contradicts the hypothesis that the brain does not take the dynamics into account in movement control depending on the neuromuscular servo mechanism; rather, it implies that the brain needs to acquire some internal models of controlled objects.

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Development of a Stereo Vision Measurement System for a 3D Three-Axial Pneumatic Parallel Mechanism Robot Arm

PubMed Central

Chiang, Mao-Hsiung; Lin, Hao-Ting; Hou, Chien-Lun

2011-01-01

In this paper, a stereo vision 3D position measurement system for a three-axial pneumatic parallel mechanism robot arm is presented. The stereo vision 3D position measurement system aims to measure the 3D trajectories of the end-effector of the robot arm. To track the end-effector of the robot arm, the circle detection algorithm is used to detect the desired target and the SAD algorithm is used to track the moving target and to search the corresponding target location along the conjugate epipolar line in the stereo pair. After camera calibration, both intrinsic and extrinsic parameters of the stereo rig can be obtained, so images can be rectified according to the camera parameters. Thus, through the epipolar rectification, the stereo matching process is reduced to a horizontal search along the conjugate epipolar line. Finally, 3D trajectories of the end-effector are computed by stereo triangulation. The experimental results show that the stereo vision 3D position measurement system proposed in this paper can successfully track and measure the fifth-order polynomial trajectory and sinusoidal trajectory of the end-effector of the three- axial pneumatic parallel mechanism robot arm. PMID:22319408

Best-Fit Conic Approximation of Spacecraft Trajectory

NASA Technical Reports Server (NTRS)

Singh, Gurkipal

2005-01-01

A computer program calculates a best conic fit of a given spacecraft trajectory. Spacecraft trajectories are often propagated as conics onboard. The conic-section parameters as a result of the best-conic-fit are uplinked to computers aboard the spacecraft for use in updating predictions of the spacecraft trajectory for operational purposes. In the initial application for which this program was written, there is a requirement to fit a single conic section (necessitated by onboard memory constraints) accurate within 200 microradians to a sequence of positions measured over a 4.7-hour interval. The present program supplants a prior one that could not cover the interval with fewer than four successive conic sections. The present program is based on formulating the best-fit conic problem as a parameter-optimization problem and solving the problem numerically, on the ground, by use of a modified steepest-descent algorithm. For the purpose of this algorithm, optimization is defined as minimization of the maximum directional propagation error across the fit interval. In the specific initial application, the program generates a single 4.7-hour conic, the directional propagation of which is accurate to within 34 microradians easily exceeding the mission constraints by a wide margin.

Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Chen, Neil Y.

2010-01-01

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

White matter tractography using diffusion tensor deflection.

PubMed

Lazar, Mariana; Weinstein, David M; Tsuruda, Jay S; Hasan, Khader M; Arfanakis, Konstantinos; Meyerand, M Elizabeth; Badie, Benham; Rowley, Howard A; Haughton, Victor; Field, Aaron; Alexander, Andrew L

2003-04-01

Diffusion tensor MRI provides unique directional diffusion information that can be used to estimate the patterns of white matter connectivity in the human brain. In this study, the behavior of an algorithm for white matter tractography is examined. The algorithm, called TEND, uses the entire diffusion tensor to deflect the estimated fiber trajectory. Simulations and imaging experiments on in vivo human brains were performed to investigate the behavior of the tractography algorithm. The simulations show that the deflection term is less sensitive than the major eigenvector to image noise. In the human brain imaging experiments, estimated tracts were generated in corpus callosum, corticospinal tract, internal capsule, corona radiata, superior longitudinal fasciculus, inferior longitudinal fasciculus, fronto-occipital fasciculus, and uncinate fasciculus. This approach is promising for mapping the organizational patterns of white matter in the human brain as well as mapping the relationship between major fiber trajectories and the location and extent of brain lesions. Copyright 2003 Wiley-Liss, Inc.

Optimal trajectories for aeroassisted orbital transfer

NASA Technical Reports Server (NTRS)

Miele, A.; Venkataraman, P.

1983-01-01

Consideration is given to classical and minimax problems involved in aeroassisted transfer from high earth orbit (HEO) to low earth orbit (LEO). The transfer is restricted to coplanar operation, with trajectory control effected by means of lift modulation. The performance of the maneuver is indexed to the energy expenditure or, alternatively, the time integral of the heating rate. Firist-order optimality conditions are defined for the classical approach, as are a sequential gradient-restoration algorithm and a combined gradient-restoration algorithm. Minimization techniques are presented for the aeroassisted transfer energy consumption and time-delay integral of the heating rate, as well as minimization of the pressure. It is shown that the eigenvalues of the Jacobian matrix of the differential system is both stiff and unstable, implying that the sequential gradient restoration algorithm in its present version is unsuitable. A new method, involving a multipoint approach to the two-poing boundary value problem, is recommended.

High-precision tracking of brownian boomerang colloidal particles confined in quasi two dimensions.

PubMed

Chakrabarty, Ayan; Wang, Feng; Fan, Chun-Zhen; Sun, Kai; Wei, Qi-Huo

2013-11-26

In this article, we present a high-precision image-processing algorithm for tracking the translational and rotational Brownian motion of boomerang-shaped colloidal particles confined in quasi-two-dimensional geometry. By measuring mean square displacements of an immobilized particle, we demonstrate that the positional and angular precision of our imaging and image-processing system can achieve 13 nm and 0.004 rad, respectively. By analyzing computer-simulated images, we demonstrate that the positional and angular accuracies of our image-processing algorithm can achieve 32 nm and 0.006 rad. Because of zero correlations between the displacements in neighboring time intervals, trajectories of different videos of the same particle can be merged into a very long time trajectory, allowing for long-time averaging of different physical variables. We apply this image-processing algorithm to measure the diffusion coefficients of boomerang particles of three different apex angles and discuss the angle dependence of these diffusion coefficients.

Stochastic algorithm for simulating gas transport coefficients

NASA Astrophysics Data System (ADS)

Rudyak, V. Ya.; Lezhnev, E. V.

2018-02-01

The aim of this paper is to create a molecular algorithm for modeling the transport processes in gases that will be more efficient than molecular dynamics method. To this end, the dynamics of molecules are modeled stochastically. In a rarefied gas, it is sufficient to consider the evolution of molecules only in the velocity space, whereas for a dense gas it is necessary to model the dynamics of molecules also in the physical space. Adequate integral characteristics of the studied system are obtained by averaging over a sufficiently large number of independent phase trajectories. The efficiency of the proposed algorithm was demonstrated by modeling the coefficients of self-diffusion and the viscosity of several gases. It was shown that the accuracy comparable to the experimental one can be obtained on a relatively small number of molecules. The modeling accuracy increases with the growth of used number of molecules and phase trajectories.

Control of mechanical systems with rolling constraints: Application to dynamic control of mobile robots

NASA Technical Reports Server (NTRS)

Sarkar, Nilanjan; Yun, Xiaoping; Kumar, Vijay

1994-01-01

There are many examples of mechanical systems that require rolling contacts between two or more rigid bodies. Rolling contacts engender nonholonomic constraints in an otherwise holonomic system. In this article, we develop a unified approach to the control of mechanical systems subject to both holonomic and nonholonomic constraints. We first present a state space realization of a constrained system. We then discuss the input-output linearization and zero dynamics of the system. This approach is applied to the dynamic control of mobile robots. Two types of control algorithms for mobile robots are investigated: trajectory tracking and path following. In each case, a smooth nonlinear feedback is obtained to achieve asymptotic input-output stability and Lagrange stability of the overall system. Simulation results are presented to demonstrate the effectiveness of the control algorithms and to compare the performane of trajectory-tracking and path-following algorithms.

Development of Complexity Science and Technology Tools for NextGen Airspace Research and Applications

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.; Sawhill, Bruce K.; Herriot, James; Seehart, Ken; Zellweger, Dres; Shay, Rick

2012-01-01

The objective of this research by NextGen AeroSciences, LLC is twofold: 1) to deliver an initial "toolbox" of algorithms, agent-based structures, and method descriptions for introducing trajectory agency as a methodology for simulating and analyzing airspace states, including bulk properties of large numbers of heterogeneous 4D aircraft trajectories in a test airspace -- while maintaining or increasing system safety; and 2) to use these tools in a test airspace to identify possible phase transition structure to predict when an airspace will approach the limits of its capacity. These 4D trajectories continuously replan their paths in the presence of noise and uncertainty while optimizing performance measures and performing conflict detection and resolution. In this approach, trajectories are represented as extended objects endowed with pseudopotential, maintaining time and fuel-efficient paths by bending just enough to accommodate separation while remaining inside of performance envelopes. This trajectory-centric approach differs from previous aircraft-centric distributed approaches to deconfliction. The results of this project are the following: 1) we delivered a toolbox of algorithms, agent-based structures and method descriptions as pseudocode; and 2) we corroborated the existence of phase transition structure in simulation with the addition of "early warning" detected prior to "full" airspace. This research suggests that airspace "fullness" can be anticipated and remedied before the airspace becomes unsafe.

Embedding Human Expert Cognition Into Autonomous UAS Trajectory Planning.

PubMed

Narayan, Pritesh; Meyer, Patrick; Campbell, Duncan

2013-04-01

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

Application of Modern Fortran to Spacecraft Trajectory Design and Optimization

NASA Technical Reports Server (NTRS)

Williams, Jacob; Falck, Robert D.; Beekman, Izaak B.

2018-01-01

In this paper, applications of the modern Fortran programming language to the field of spacecraft trajectory optimization and design are examined. Modern object-oriented Fortran has many advantages for scientific programming, although many legacy Fortran aerospace codes have not been upgraded to use the newer standards (or have been rewritten in other languages perceived to be more modern). NASA's Copernicus spacecraft trajectory optimization program, originally a combination of Fortran 77 and Fortran 95, has attempted to keep up with modern standards and makes significant use of the new language features. Various algorithms and methods are presented from trajectory tools such as Copernicus, as well as modern Fortran open source libraries and other projects.

Pteros: fast and easy to use open-source C++ library for molecular analysis.

PubMed

Yesylevskyy, Semen O

2012-07-15

An open-source Pteros library for molecular modeling and analysis of molecular dynamics trajectories for C++ programming language is introduced. Pteros provides a number of routine analysis operations ranging from reading and writing trajectory files and geometry transformations to structural alignment and computation of nonbonded interaction energies. The library features asynchronous trajectory reading and parallel execution of several analysis routines, which greatly simplifies development of computationally intensive trajectory analysis algorithms. Pteros programming interface is very simple and intuitive while the source code is well documented and easily extendible. Pteros is available for free under open-source Artistic License from http://sourceforge.net/projects/pteros/. Copyright © 2012 Wiley Periodicals, Inc.

Orbit computation of the TELECOM-2D satellite with a Genetic Algorithm

NASA Astrophysics Data System (ADS)

Deleflie, Florent; Coulot, David; Vienne, Alain; Decosta, Romain; Richard, Pascal; Lasri, Mohammed Amjad

2014-07-01

In order to test a preliminary orbit determination method, we fit an orbit of the geostationary satellite TELECOM-2D, as if we did not know any a priori information on its trajectory. The method is based on a genetic algorithm coupled to an analytical propagator of the trajectory, that is used over a couple of days, and that uses a whole set of altazimutal data that are acquired by the tracking network made up of the two TAROT telescopes. The adjusted orbit is then compared to a numerical reference. The method is described, and the results are analyzed, as a step towards an operational method of preliminary orbit determination for uncatalogued objects.

Ku-band antenna acquisition and tracking performance study, volume 4

NASA Technical Reports Server (NTRS)

Huang, T. C.; Lindsey, W. C.

1977-01-01

The results pertaining to the tradeoff analysis and performance of the Ku-band shuttle antenna pointing and signal acquisition system are presented. The square, hexagonal and spiral antenna trajectories were investigated assuming the TDRS postulated uncertainty region and a flexible statistical model for the location of the TDRS within the uncertainty volume. The scanning trajectories, shuttle/TDRS signal parameters and dynamics, and three signal acquisition algorithms were integrated into a hardware simulation. The hardware simulation is quite flexible in that it allows for the evaluation of signal acquisition performance for an arbitrary (programmable) antenna pattern, a large range of C/N sub O's, various TDRS/shuttle a priori uncertainty distributions, and three distinct signal search algorithms.

Effect of driving experience on anticipatory look-ahead fixations in real curve driving.

PubMed

Lehtonen, Esko; Lappi, Otto; Koirikivi, Iivo; Summala, Heikki

2014-09-01

Anticipatory skills are a potential factor for novice drivers' curve accidents. Behavioural data show that steering and speed regulation are affected by forward planning of the trajectory. When approaching a curve, the relevant visual information for online steering control and for planning is located at different eccentricities, creating a need to disengage the gaze from the guidance of steering to anticipatory look-ahead fixations over curves. With experience, peripheral vision can be increasingly used in the visual guidance of steering. This could leave experienced drivers more gaze time to invest on look-ahead fixations over curves, facilitating the trajectory planning. Eighteen drivers (nine novices, nine experienced) drove an instrumented vehicle on a rural road four times in both directions. Their eye movements were analyzed in six curves. The trajectory of the car was modelled and divided to approach, entry and exit phases. Experienced drivers spent less time on the road-ahead and more time on the look-ahead fixations over the curves. Look-ahead fixations were also more common in the approach than in the entry phase of the curve. The results suggest that with experience drivers allocate greater part of their visual attention to trajectory planning. Copyright © 2014 Elsevier Ltd. All rights reserved.

KmL3D: a non-parametric algorithm for clustering joint trajectories.

PubMed

Genolini, C; Pingault, J B; Driss, T; Côté, S; Tremblay, R E; Vitaro, F; Arnaud, C; Falissard, B

2013-01-01

In cohort studies, variables are measured repeatedly and can be considered as trajectories. A classic way to work with trajectories is to cluster them in order to detect the existence of homogeneous patterns of evolution. Since cohort studies usually measure a large number of variables, it might be interesting to study the joint evolution of several variables (also called joint-variable trajectories). To date, the only way to cluster joint-trajectories is to cluster each trajectory independently, then to cross the partitions obtained. This approach is unsatisfactory because it does not take into account a possible co-evolution of variable-trajectories. KmL3D is an R package that implements a version of k-means dedicated to clustering joint-trajectories. It provides facilities for the management of missing values, offers several quality criteria and its graphic interface helps the user to select the best partition. KmL3D can work with any number of joint-variable trajectories. In the restricted case of two joint trajectories, it proposes 3D tools to visualize the partitioning and then export 3D dynamic rotating-graphs to PDF format. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Automatic Multiple-Needle Surgical Planning of Robotic-Assisted Microwave Coagulation in Large Liver Tumor Therapy

PubMed Central

Liu, Shaoli; Xia, Zeyang; Liu, Jianhua; Xu, Jing; Ren, He; Lu, Tong; Yang, Xiangdong

2016-01-01

The “robotic-assisted liver tumor coagulation therapy” (RALTCT) system is a promising candidate for large liver tumor treatment in terms of accuracy and speed. A prerequisite for effective therapy is accurate surgical planning. However, it is difficult for the surgeon to perform surgical planning manually due to the difficulties associated with robot-assisted large liver tumor therapy. These main difficulties include the following aspects: (1) multiple needles are needed to destroy the entire tumor, (2) the insertion trajectories of the needles should avoid the ribs, blood vessels, and other tissues and organs in the abdominal cavity, (3) the placement of multiple needles should avoid interference with each other, (4) an inserted needle will cause some deformation of liver, which will result in changes in subsequently inserted needles’ operating environment, and (5) the multiple needle-insertion trajectories should be consistent with the needle-driven robot’s movement characteristics. Thus, an effective multiple-needle surgical planning procedure is needed. To overcome these problems, we present an automatic multiple-needle surgical planning of optimal insertion trajectories to the targets, based on a mathematical description of all relevant structure surfaces. The method determines the analytical expression of boundaries of every needle “collision-free reachable workspace” (CFRW), which are the feasible insertion zones based on several constraints. Then, the optimal needle insertion trajectory within the optimization criteria will be chosen in the needle CFRW automatically. Also, the results can be visualized with our navigation system. In the simulation experiment, three needle-insertion trajectories were obtained successfully. In the in vitro experiment, the robot successfully achieved insertion of multiple needles. The proposed automatic multiple-needle surgical planning can improve the efficiency and safety of robot-assisted large liver tumor therapy, significantly reduce the surgeon’s workload, and is especially helpful for an inexperienced surgeon. The methodology should be easy to adapt in other body parts. PMID:26982341

A Comparative Study of Interval Management Control Law Capabilities

NASA Technical Reports Server (NTRS)

Barmore, Bryan E.; Smith, Colin L.; Palmer, Susan O.; Abbott, Terence S.

2012-01-01

This paper presents a new tool designed to allow for rapid development and testing of different control algorithms for airborne spacing. This tool, Interval Management Modeling and Spacing Tool (IM MAST), is a fast-time, low-fidelity tool created to model the approach of aircraft to a runway, with a focus on their interactions with each other. Errors can be induced between pairs of aircraft by varying initial positions, winds, speed profiles, and altitude profiles. Results to-date show that only a few of the algorithms tested had poor behavior in the arrival and approach environment. The majority of the algorithms showed only minimal variation in performance under the test conditions. Trajectory-based algorithms showed high susceptibility to wind forecast errors, while performing marginally better than the other algorithms under other conditions. Trajectory-based algorithms have a sizable advantage, however, of being able to perform relative spacing operations between aircraft on different arrival routes and flight profiles without employing ghosting. methods. This comes at the higher cost of substantially increased complexity, however. Additionally, it was shown that earlier initiation of relative spacing operations provided more time for corrections to be made without any significant problems in the spacing operation itself. Initiating spacing farther out, however, would require more of the aircraft to begin spacing before they merge onto a common route.

Observability-Based Guidance and Sensor Placement

NASA Astrophysics Data System (ADS)

Hinson, Brian T.

Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.

78 FR 57639 - Request for Comments on Pediatric Planned Procedure Algorithm

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-19

... Comments on Pediatric Planned Procedure Algorithm AGENCY: Agency for Healthcare Research and Quality (AHRQ), HHS. ACTION: Notice of request for comments on pediatric planned procedure algorithm from the members... Quality (AHRQ) is requesting comments from the public on an algorithm for identifying pediatric planned...

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Broad-search algorithms for finding triple-and quadruple-satellite-aided captures at Jupiter from 2020 to 2080

NASA Astrophysics Data System (ADS)

Lynam, Alfred E.

2015-04-01

Multiple-satellite-aided capture is a -efficient technique for capturing a spacecraft into orbit at Jupiter. However, finding the times when the Galilean moons of Jupiter align such that three or four of them can be encountered in a single pass is difficult using standard astrodynamics algorithms such as Lambert's problem. In this paper, we present simple but powerful techniques that simplify the dynamics and geometry of the Galilean satellites so that many of these triple- and quadruple-satellite-aided capture sequences can be found quickly over an extended 60-year time period from 2020 to 2080. The techniques find many low-fidelity trajectories that could be used as initial guesses for future high-fidelity optimization. Results indicate the existence of approximately 3,100 unique triple-satellite-aided capture trajectories and 6 unique quadruple-satellite-aided capture trajectories during the 60-year time period. The entire search takes less than one minute of computational time.

Research on the magnetorheological finishing of large aperture off-axis aspheric optical surfaces for zinc sulfide

NASA Astrophysics Data System (ADS)

Zhang, Yunfei; Huang, Wen; Zheng, Yongcheng; Ji, Fang; Xu, Min; Duan, Zhixin; Luo, Qing; Liu, Qian; Xiao, Hong

2016-03-01

Zinc sulfide is a kind of typical infrared optical material, commonly produced using single point diamond turning (SPDT). SPDT can efficiently produce zinc sulfide aspheric surfaces with micro-roughness and acceptable figure error. However the tool marks left by the diamond turning process cause high micro-roughness that degrades the optical performance when used in the visible region of the spectrum. Magnetorheological finishing (MRF) is a deterministic, sub-aperture polishing technology that is very helpful in improving both surface micro-roughness and surface figure.This paper mainly investigates the MRF technology of large aperture off-axis aspheric optical surfaces for zinc sulfide. The topological structure and coordinate transformation of a MRF machine tool PKC1200Q2 are analyzed and its kinematics is calculated, then the post-processing algorithm model of MRF for an optical lens is established. By taking the post-processing of off-axis aspheric surfacefor example, a post-processing algorithm that can be used for a raster tool path is deduced and the errors produced by the approximate treatment are analyzed. A polishing algorithm of trajectory planning and dwell time based on matrix equation and optimization theory is presented in this paper. Adopting this algorithm an experiment is performed to machining a large-aperture off-axis aspheric surface on the MRF machine developed by ourselves. After several times' polishing, the figure accuracy PV is proved from 3.3λ to 2.0λ and RMS from 0.451λ to 0.327λ. This algorithm is used to polish the other shapes including spheres, aspheres and prisms.

Analysis of direct transfer trajectories from LL2 halo orbits to LLOs

NASA Astrophysics Data System (ADS)

Cao, Pengfei; He, Boyong; Li, Haiyang

2017-09-01

A convenient procedure for designing the direct transfer trajectory from lunar L2 point (LL2) halo orbit to a low lunar orbit (LLO) is presented in this paper. The trajectory characteristics are analyzed to support the manned lunar missions design aimed at lunar surface global access. The concise procedure is established based on the circular restricted three-body problem (CR3BP) model. An analytical algorithm is employed to estimate an initial maneuver vector for approaching the Moon in its close vicinity. An iteration process is adopted to generate favorable trajectory that satisfies the constraints at perilune. By introducing a number of intermediate coordinate frames, an algorithm to compute the arriving LLO inclination and right ascension of ascending node (RAAN) is proposed. The orbital inclination and RAAN in this paper are defined and established in the J2000 frame rather than in the synodical frame. Numerical results show that, regardless of value of out-of-plane amplitude (Az) of the halo orbit, the overall maneuver cost of the trajectory largely depends on departure position, and it has two minima around 0.65 km/s. Further study shows that the values of the arriving LLO inclination and RAAN largely depend on the choices of the departure time and the value of Az. The periodicity, due to the natural motion of the Moon, is discovered to play a role in this time dependency. It is concluded that the fuel optimal trajectory permits access to almost any final lunar orbit, including a polar orbit, by means of varying the departure time and Az value.

Implicit assumptions underlying simple harvest models of marine bird populations can mislead environmental management decisions.

PubMed

O'Brien, Susan H; Cook, Aonghais S C P; Robinson, Robert A

2017-10-01

Assessing the potential impact of additional mortality from anthropogenic causes on animal populations requires detailed demographic information. However, these data are frequently lacking, making simple algorithms, which require little data, appealing. Because of their simplicity, these algorithms often rely on implicit assumptions, some of which may be quite restrictive. Potential Biological Removal (PBR) is a simple harvest model that estimates the number of additional mortalities that a population can theoretically sustain without causing population extinction. However, PBR relies on a number of implicit assumptions, particularly around density dependence and population trajectory that limit its applicability in many situations. Among several uses, it has been widely employed in Europe in Environmental Impact Assessments (EIA), to examine the acceptability of potential effects of offshore wind farms on marine bird populations. As a case study, we use PBR to estimate the number of additional mortalities that a population with characteristics typical of a seabird population can theoretically sustain. We incorporated this level of additional mortality within Leslie matrix models to test assumptions within the PBR algorithm about density dependence and current population trajectory. Our analyses suggest that the PBR algorithm identifies levels of mortality which cause population declines for most population trajectories and forms of population regulation. Consequently, we recommend that practitioners do not use PBR in an EIA context for offshore wind energy developments. Rather than using simple algorithms that rely on potentially invalid implicit assumptions, we recommend use of Leslie matrix models for assessing the impact of additional mortality on a population, enabling the user to explicitly define assumptions and test their importance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tactical Conflict Detection in Terminal Airspace

NASA Technical Reports Server (NTRS)

Tang, Huabin; Robinson, John E.; Denery, Dallas G.

2010-01-01

Air traffic systems have long relied on automated short-term conflict prediction algorithms to warn controllers of impending conflicts (losses of separation). The complexity of terminal airspace has proven difficult for such systems as it often leads to excessive false alerts. Thus, the legacy system, called Conflict Alert, which provides short-term alerts in both en-route and terminal airspace currently, is often inhibited or degraded in areas where frequent false alerts occur, even though the alerts are provided only when an aircraft is in dangerous proximity of other aircraft. This research investigates how a minimal level of flight intent information may be used to improve short-term conflict detection in terminal airspace such that it can be used by the controller to maintain legal aircraft separation. The flight intent information includes a site-specific nominal arrival route and inferred altitude clearances in addition to the flight plan that includes the RNAV (Area Navigation) departure route. A new tactical conflict detection algorithm is proposed, which uses a single analytic trajectory, determined by the flight intent and the current state information of the aircraft, and includes a complex set of current, dynamic separation standards for terminal airspace to define losses of separation. The new algorithm is compared with an algorithm that imitates a known en-route algorithm and another that imitates Conflict Alert by analysis of false-alert rate and alert lead time with recent real-world data of arrival and departure operations and a large set of operational error cases from Dallas/Fort Worth TRACON (Terminal Radar Approach Control). The new algorithm yielded a false-alert rate of two per hour and an average alert lead time of 38 seconds.

NEOPROP: A NEO Propagator for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Zuccarelli, Valentino; Bancelin, David; Weikert, Sven; Thuillot, William; Hestroffer, Daniel; Yabar Valle, Celia; Koschny, Detlef

2013-09-01

The overall aim of the Space Situational Awareness (SSA) Preparatory Programme is to support the European independent utilisation of and access to space for research or services, through providing timely and quality data, information, services and knowledge regarding the environment, the threats and the sustainable exploitation of the outer space surrounding our planet Earth. The SSA system will comprise three main segments:• Space Weather (SWE) monitoring and forecast• Near-Earth Objects (NEO) survey and follow-up• Space Surveillance and Tracking (SST) of man-made space objectsCurrently, there are over 600.000 asteroids known in our Solar System, where more than 9.500 of these are NEOs. These could potentially hit our planet and depending on their size could produce considerable damage. For this reason NEOs deserve active detection and tracking efforts.The role of the SSA programme is to provide warning services against potential asteroid impact hazards, including discovery, identification, orbit prediction and civil alert capabilities. ESA is now working to develop a NEO Coordination Centre which will later evolve into a SSA-NEO Small Bodies Data Centre (SBDC), located at ESA/ESRIN, Italy. The Software prototype developed in the frame of this activity may be later implemented as a part of the SSA-NEO programme simulators aimed at assessing the trajectory of asteroids. There already exist different algorithms to predict orbits for NEOs. The objective of this activity is to come up with a different trajectory prediction algorithm, which allows an independent validation of the current algorithms within the SSA-NEO segment (e.g. NEODyS, JPL Sentry System).The key objective of this activity was to design, develop, test, verify, and validate trajectory prediction algorithm of NEOs in order to be able to computeanalytically and numerically the minimum orbital intersection distances (MOIDs).The NEOPROP software consists of two separate modules/tools:1. The Analytical Module makes use of analytical algorithms in order to rapidly assess the impact risk of a NEO. It is responsible for the preliminary analysis. Orbit Determination algorithms, as the Gauss and the Linear Least Squares (LLS) methods, will determine the initial state (from MPC observations), along with its uncertainty, and the MOID of the NEO (analytically).2. The Numerical Module makes use of numerical algorithms in order to refine and to better assess the impact probabilities. The initial state provided by the orbit determination process will be used to numerically propagate the trajectory. The numerical propagation can be run in two modes: one faster ("fast analysis"), in order to get a fast evaluation of the trajectory and one more precise ("complete analysis") taking into consideration more detailed perturbation models. Moreover, a configurable number of Virtual Asteroids (VAs) will be numerically propagated in order to determine the Earth closest approach. This new "MOID" computation differs from the analytical one since it takes into consideration the full dynamics of the problem.

Nerve Fiber Flux Analysis Using Wide-Field Swept-Source Optical Coherence Tomography.

PubMed

Tan, Ou; Liu, Liang; Liu, Li; Huang, David

2018-02-01

To devise a method to quantify nerve fibers over their arcuate courses over an extended peripapillary area using optical coherence tomography (OCT). Participants were imaged with 8 × 8-mm volumetric OCT scans centered at the optic disc. A new quantity, nerve fiber flux (NFF), represents the cross-sectional area transected perpendicular to the nerve fibers. The peripapillary area was divided into 64 tracks with equal flux. An iterative algorithm traced the trajectory of the tracks assuming that the relative distribution of the NFF was conserved with compensation for fiber connections to ganglion cells on the macular side. Average trajectory was averaged from normal eyes and use to calculate the NFF maps for glaucomatous eyes. The NFF maps were divided into eight sectors that correspond to visual field regions. There were 24 healthy and 10 glaucomatous eyes enrolled. The algorithm converged on similar patterns of NFL tracks for all healthy eyes. In glaucomatous eyes, NFF correlated with visual field sensitivity in the arcuate sectors (Spearman ρ = 0.53-0.62). Focal nerve fiber loss in glaucomatous eyes appeared as uniform tracks of NFF defects that followed the expected arcuate fiber trajectory. Using an algorithm based on the conservation of flux, we derived nerve fiber trajectories in the peripapillary area. The NFF map is useful for the visualization of focal defects and quantification of sector nerve fiber loss from wide-area volumetric OCT scans. NFF provides a cumulative measure of volumetric loss along nerve fiber tracks and could improve the detection of focal glaucoma damage.

A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

NASA Astrophysics Data System (ADS)

Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

2016-09-01

This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

New method for finding multiple meaningful trajectories

NASA Astrophysics Data System (ADS)

Bao, Zhonghao; Flachs, Gerald M.; Jordan, Jay B.

1995-07-01

Mathematical foundations and algorithms for efficiently finding multiple meaningful trajectories (FMMT) in a sequence of digital images are presented. A meaningful trajectory is motion created by a sentient being or by a device under the control of a sentient being. It is smooth and predictable over short time intervals. A meaningful trajectory can suddenly appear or disappear in sequence images. The development of the FMMT is based on these assumptions. A finite state machine in the FMMT is used to model the trajectories under the conditions of occlusions and false targets. Each possible trajectory is associated with an initial state of a finite state machine. When two frames of data are available, a linear predictor is used to predict the locations of all possible trajectories. All trajectories within a certain error bound are moved to a monitoring trajectory state. When trajectories attain three consecutive good predictions, they are moved to a valid trajectory state and considered to be locked into a tracking mode. If an object is occluded while in the valid trajectory state, the predicted position is used to continue to track; however, the confidence in the trajectory is lowered. If the trajectory confidence falls below a lower limit, the trajectory is terminated. Results are presented that illustrate the FMMT applied to track multiple munitions fired from a missile in a sequence of images. Accurate trajectories are determined even in poor images where the probabilities of miss and false alarm are very high.

Structure Inference from Mobility Encounters

DTIC Science & Technology

2013-10-20

world dataset, which contains 230K trajectories of taxi cabs in Beijing . Our algorithm extracts a pathlet dictionary containing around 130K...data set, frequently used pathlets in the dictionary represent driving segments chosen by many taxi cab drivers in Beijing , reflecting the joint wisdom...limitations on storage and communication bandwidth. For instance, 50% of the Beijing Taxi Trajectories we employed in this study have at most one

Efficient hybrid non-equilibrium molecular dynamics--Monte Carlo simulations with symmetric momentum reversal.

PubMed

Chen, Yunjie; Roux, Benoît

2014-09-21

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Efficient hybrid non-equilibrium molecular dynamics - Monte Carlo simulations with symmetric momentum reversal

NASA Astrophysics Data System (ADS)

Chen, Yunjie; Roux, Benoît

2014-09-01

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Voltage control on a train system

DOEpatents

Gordon, Susanna P.; Evans, John A.

2004-01-20

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

Method of managing interference during delay recovery on a train system

DOEpatents

Gordon, Susanna P.; Evans, John A.

2005-12-27

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

Efficient high density train operations

DOEpatents

Gordon, Susanna P.; Evans, John A.

2001-01-01

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference. During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

An Information-Centric Approach to Autonomous Trajectory Planning Utilizing Optimal Control Techniques

DTIC Science & Technology

2009-09-01

to promote one way as the best, but to show there are several ways to define the problem. 107 Figure 71. Final Orientation/Obstacle Scenario...a comparison of the running cost vs. distance from an obstacle for varying values of p. Simulations have shown that for 4p  , the running cost...sliding door example. This scenario shows a major weakness when conducting trajectory planning using snapshots in a dynamic environment

Using simplified Chaos Theory to manage nursing services.

PubMed

Haigh, Carol A

2008-04-01

The purpose of this study was to evaluate the part simplified chaos theory could play in the management of nursing services. As nursing care becomes more complex, practitioners need to become familiar with business planning and objective time management. There are many time-limited methods that facilitate this type of planning but few that can help practitioners to forecast the end-point outcome of the service they deliver. A growth model was applied to a specialist service to plot service trajectory. Components of chaos theory can play a role in forecasting service outcomes and consequently the impact upon the management of such services. The ability to (1) track the trajectory of a service and (2) manipulate that trajectory by introducing new variables can allow managers to forward plan for service development and to evaluate the effectiveness of a service by plotting its end-point state.

A novel method for trajectory planning of cooperative mobile manipulators.

PubMed

Bolandi, Hossein; Ehyaei, Amir Farhad

2011-01-01

We have designed a two-stage scheme to consider the trajectory planning problem of two mobile manipulators for cooperative transportation of a rigid body in the presence of static obstacles. In the first stage, with regard to the static obstacles, we develop a method that searches the workspace for the shortest possible path between the start and goal configurations, by constructing a graph on a portion of the configuration space that satisfies the collision and closure constraints. The final stage is to calculate a sequence of time-optimal trajectories to go between the consecutive points of the path, with regard to the nonholonomic constraints and the maximum allowed joint accelerations. This approach allows geometric constraints such as joint limits and closed-chain constraints, along with differential constraints such as nonholonomic velocity constraints and acceleration limits, to be incorporated into the planning scheme. The simulation results illustrate the effectiveness of the proposed method.

A Novel Method for Trajectory Planning of Cooperative Mobile Manipulators

PubMed Central

Bolandi, Hossein; Ehyaei, Amir Farhad

2011-01-01

We have designed a two-stage scheme to consider the trajectory planning problem of two mobile manipulators for cooperative transportation of a rigid body in the presence of static obstacles. In the first stage, with regard to the static obstacles, we develop a method that searches the workspace for the shortest possible path between the start and goal configurations, by constructing a graph on a portion of the configuration space that satisfies the collision and closure constraints. The final stage is to calculate a sequence of time-optimal trajectories to go between the consecutive points of the path, with regard to the nonholonomic constraints and the maximum allowed joint accelerations. This approach allows geometric constraints such as joint limits and closed-chain constraints, along with differential constraints such as nonholonomic velocity constraints and acceleration limits, to be incorporated into the planning scheme. The simulation results illustrate the effectiveness of the proposed method. PMID:22606656

Examination of the gamma equilibrium point hypothesis when applied to single degree of freedom movements performed with different inertial loads.

PubMed

Bellomo, A; Inbar, G

1997-01-01

One of the theories of human motor control is the gamma Equilibrium Point Hypothesis. It is an attractive theory since it offers an easy control scheme where the planned trajectory shifts monotionically from an initial to a final equilibrium state. The feasibility of this model was tested by reconstructing the virtual trajectory and the stiffness profiles for movements performed with different inertial loads and examining them. Three types of movements were tested: passive movements, targeted movements, and repetitive movements. Each of the movements was performed with five different inertial loads. Plausible virtual trajectories and stiffness profiles were reconstructed based on the gamma Equilibrium Point Hypothesis for the three different types of movements performed with different inertial loads. However, the simple control strategy supported by the model, where the planned trajectory shifts monotonically from an initial to a final equilibrium state, could not be supported for targeted movements performed with added inertial load. To test the feasibility of the model further we must examine the probability that the human motor control system would choose a trajectory more complicated than the actual trajectory to control.

Prototype Flight Management Capabilities to Explore Temporal RNP Concepts

NASA Technical Reports Server (NTRS)

Ballin, Mark G.; Williams, David H.; Allen, Bonnie Danette; Palmer, Michael T.

2008-01-01

Next Generation Air Transportation System (NextGen) concepts of operation may require aircraft to fly planned trajectories in four dimensions three spatial dimensions and time. A prototype 4D flight management capability is being developed by NASA to facilitate the development of these concepts. New trajectory generation functions extend today's flight management system (FMS) capabilities that meet a single Required Time of Arrival (RTA) to trajectory solutions that comply with multiple RTA constraints. When a solution is not possible, a constraint management capability relaxes constraints to achieve a trajectory solution that meets the most important constraints as specified by candidate NextGen concepts. New flight guidance functions provide continuous guidance to the aircraft s flight control system to enable it to fly specified 4D trajectories. Guidance options developed for research investigations include a moving time window with varying tolerances that are a function of proximity to imposed constraints, and guidance that recalculates the aircraft s planned trajectory as a function of the estimation of current compliance. Compliance tolerances are related to required navigation performance (RNP) through the extension of existing RNP concepts for lateral containment. A conceptual temporal RNP implementation and prototype display symbology are proposed.

Software for Project-Based Learning of Robot Motion Planning

ERIC Educational Resources Information Center

Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.

2013-01-01

Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can…

The design of transfer trajectory for Ivar asteroid exploration mission

NASA Astrophysics Data System (ADS)

Qiao, Dong; Cui, Hutao; Cui, Pingyuan

2009-12-01

An impending demand for exploring the small bodies, such as the comets and the asteroids, envisioned the Chinese Deep Space exploration mission to the Near Earth asteroid Ivar. A design and optimal method of transfer trajectory for asteroid Ivar is discussed in this paper. The transfer trajectory for rendezvous with asteroid Ivar is designed by means of Earth gravity assist with deep space maneuver (Delta-VEGA) technology. A Delta-VEGA transfer trajectory is realized by several trajectory segments, which connect the deep space maneuver and swingby point. Each trajectory segment is found by solving Lambert problem. Through adjusting deep maneuver and arrival time, the match condition of swingby is satisfied. To reduce the total mission velocity increments further, a procedure is developed which minimizes total velocity increments for this scheme of transfer trajectory for asteroid Ivar. The trajectory optimization problem is solved with a quasi-Newton algorithm utilizing analytic first derivatives, which are derived from the transversality conditions associated with the optimization formulation and primer vector theory. The simulation results show the scheme for transfer trajectory causes C3 and total velocity increments decrease of 48.80% and 13.20%, respectively.

Navigation Algorithms for Formation Flying Missions

NASA Technical Reports Server (NTRS)

Huxel, Paul J.; Bishop, Robert H.

2004-01-01

The objective of the investigations is to develop navigation algorithms to support formation flying missions. In particular, we examine the advantages and concerns associated with the use of combinations of inertial and relative measurements, as well as address observability issues. In our analysis we consider the interaction between measurement types, update frequencies, and trajectory geometry and their cumulative impact on observability. Furthermore, we investigate how relative measurements affect inertial navigation in terms of algorithm performance.

Identification of damage in plates using full-field measurement with a continuously scanning laser Doppler vibrometer system

NASA Astrophysics Data System (ADS)

Chen, Da-Ming; Xu, Y. F.; Zhu, W. D.

2018-05-01

An effective and reliable damage identification method for plates with a continuously scanning laser Doppler vibrometer (CSLDV) system is proposed. A new constant-speed scan algorithm is proposed to create a two-dimensional (2D) scan trajectory and automatically scan a whole plate surface. Full-field measurement of the plate can be achieved by applying the algorithm to the CSLDV system. Based on the new scan algorithm, the demodulation method is extended from one dimension for beams to two dimensions for plates to obtain a full-field operating deflection shape (ODS) of the plate from velocity response measured by the CSLDV system. The full-field ODS of an associated undamaged plate is obtained by using polynomials with proper orders to fit the corresponding full-field ODS from the demodulation method. A curvature damage index (CDI) using differences between curvatures of ODSs (CODSs) associated with ODSs that are obtained by the demodulation method and the polynomial fit is proposed to identify damage. An auxiliary CDI obtained by averaging CDIs at different excitation frequencies is defined to further assist damage identification. An experiment of an aluminum plate with damage in the form of 10.5% thickness reduction in a damage area of 0.86% of the whole scan area is conducted to investigate the proposed method. Six frequencies close to natural frequencies of the plate and one randomly selected frequency are used as sinusoidal excitation frequencies. Two 2D scan trajectories, i.e., a horizontally moving 2D scan trajectory and a vertically moving 2D scan trajectory, are used to obtain ODSs, CODSs, and CDIs of the plate. The damage is successfully identified near areas with consistently high values of CDIs at different excitation frequencies along the two 2D scan trajectories; the damage area is also identified by auxiliary CDIs.

Experiences in Delta mission planning

NASA Technical Reports Server (NTRS)

Kork, J.

1981-01-01

The Delta launch vehicle has experienced 153 successful launches since 1960 and 40 more are scheduled. Relying on up-to-date technology and proven flight hardware, the Delta vehicle has been used for low to high circular and geosynchronous transfer orbits, high elliptic probes, and lunar and planetary missions. A history of Delta launches and configuration modifications is presented, noting a 92-95% success rate and its cost effective role in reimbursable missions. Elements of mission planning such as feasibility studies (1-3 yrs), spacecraft restraints manuals, reference trajectories, preliminary mission analysis, detailed test objectives, range/safety studies, guided nominal trajectory, and mission specific studies are discussed. Trajectory shaping determines vehicle and spacecraft restraints, optimizes the trajectory, and maximizes the payload capabilities. Improvements in the Delta vehicle have boosted payloads from 100 to 2890 lbs., improving the price per pound ratio, as costs have risen, only by a factor of three. Current launch schedules extend well into 1985.

SeGRAm - A practical and versatile tool for spacecraft trajectory optimization

NASA Technical Reports Server (NTRS)

Rishikof, Brian H.; Mccormick, Bernell R.; Pritchard, Robert E.; Sponaugle, Steven J.

1991-01-01

An implementation of the Sequential Gradient/Restoration Algorithm, SeGRAm, is presented along with selected examples. This spacecraft trajectory optimization and simulation program uses variational calculus to solve problems of spacecraft flying under the influence of one or more gravitational bodies. It produces a series of feasible solutions to problems involving a wide range of vehicles, environments and optimization functions, until an optimal solution is found. The examples included highlight the various capabilities of the program and emphasize in particular its versatility over a wide spectrum of applications from ascent to interplanetary trajectories.

Winding trajectories of noncircular composite shells

NASA Astrophysics Data System (ADS)

Nikityuk, V. A.; Fedorov, V. V.

1995-07-01

An approach has been proposed for determination of the trajectory parameters of a layer formed by winding of continuous ribbons on a complicated surface. An algorithm has been developed for determining the geodesic trajectories of the reinforcement fiber arrangement, reinforcement angles, and geodesic deviation angles. Conditions have been formulated for positional stability of the ribbons on the surface and avoidance of gaps and overlapping between the ribbons along with restrictions to the surface form. Results are given for a calculation of the geodesic turn parameters on a fuselage surface, which is not a surface of revolution, of a light airplane.

High-Speed Printing Process Characterization using the Lissajous Trajectory Method

NASA Astrophysics Data System (ADS)

Lee, Sangwon; Kim, Daekeun

2018-04-01

We present a novel stereolithographic three-dimensional (3D) printing process that uses Lissajous trajectories. By using Lissajous trajectories, this 3D printing process allows two laser-scanning mirrors to operate at similar high-speed frequencies simultaneously, and the printing speed can be faster than that of raster scanning used in conventional stereolithography. In this paper, we first propose the basic theoretical background for this printing process based on Lissajous trajectories. We also characterize its printing conditions, such as printing size, laser spot size, and minimum printing resolution, with respect to the operating frequencies of the scanning mirrors and the capability of the laser modulation. Finally, we demonstrate simulation results for printing basic 2D shapes by using a noble printing process algorithm.

The Development of NASA's Low Thrust Trajectory Tool Set

NASA Technical Reports Server (NTRS)

Sims, Jon; Artis, Gwen; Kos, Larry

2006-01-01

Highly efficient electric propulsion systems can enable interesting classes of missions; unfortunately, they provide only a limited amount of thrust. Low-thrust (LT) trajectories are much more difficult to design than impulsive-type (chemical propulsion) trajectories. Previous low-thrust (LT) trajectory optimization software was often difficult to use, often had difficulties converging, and was somewhat limited in the types of missions it could support. A new state-of-the-art suite (toolbox) of low-thrust (LT) tools along with improved algorithms and methods was developed by NASA's MSFC, JPL, JSC, and GRC to address the needs of our customers to help foster technology development in the areas of advanced LT propulsion systems, and to facilitate generation of similar results by different analysts.

EIVAN - AN INTERACTIVE ORBITAL TRAJECTORY PLANNING TOOL

NASA Technical Reports Server (NTRS)

Brody, A. R.

1994-01-01

The Interactive Orbital Trajectory planning Tool, EIVAN, is a forward looking interactive orbit trajectory plotting tool for use with Proximity Operations (operations occurring within a one kilometer sphere of the space station) and other maneuvers. The result of vehicle burns on-orbit is very difficult to anticipate because of non-linearities in the equations of motion governing orbiting bodies. EIVAN was developed to plot resulting trajectories, to provide a better comprehension of orbital mechanics effects, and to help the user develop heuristics for onorbit mission planning. EIVAN comprises a worksheet and a chart from Microsoft Excel on a Macintosh computer. The orbital path for a user-specified time interval is plotted given operator burn inputs. Fuel use is also calculated. After the thrust parameters (magnitude, direction, and time) are input, EIVAN plots the resulting trajectory. Up to five burns may be inserted at any time in the mission. Twenty data points are plotted for each burn and the time interval can be varied to accommodate any desired time frame or degree of resolution. Since the number of data points for each burn is constant, the mission duration can be increased or decreased by increasing or decreasing the time interval. The EIVAN program runs with Microsoft's Excel for execution on a Macintosh running Macintosh OS. A working knowledge of Excel is helpful, but not imperative, for interacting with EIVAN. The program was developed in 1989.

Summarizing Simulation Results using Causally-relevant States

PubMed Central

Parikh, Nidhi; Marathe, Madhav; Swarup, Samarth

2016-01-01

As increasingly large-scale multiagent simulations are being implemented, new methods are becoming necessary to make sense of the results of these simulations. Even concisely summarizing the results of a given simulation run is a challenge. Here we pose this as the problem of simulation summarization: how to extract the causally-relevant descriptions of the trajectories of the agents in the simulation. We present a simple algorithm to compress agent trajectories through state space by identifying the state transitions which are relevant to determining the distribution of outcomes at the end of the simulation. We present a toy-example to illustrate the working of the algorithm, and then apply it to a complex simulation of a major disaster in an urban area. PMID:28042620

Path integral learning of multidimensional movement trajectories

NASA Astrophysics Data System (ADS)

André, João; Santos, Cristina; Costa, Lino

2013-10-01

This paper explores the use of Path Integral Methods, particularly several variants of the recent Path Integral Policy Improvement (PI2) algorithm in multidimensional movement parametrized policy learning. We rely on Dynamic Movement Primitives (DMPs) to codify discrete and rhythmic trajectories, and apply the PI2-CMA and PIBB methods in the learning of optimal policy parameters, according to different cost functions that inherently encode movement objectives. Additionally we merge both of these variants and propose the PIBB-CMA algorithm, comparing all of them with the vanilla version of PI2. From the obtained results we conclude that PIBB-CMA surpasses all other methods in terms of convergence speed and iterative final cost, which leads to an increased interest in its application to more complex robotic problems.

On the Formal Verification of Conflict Detection Algorithms

NASA Technical Reports Server (NTRS)

Munoz, Cesar; Butler, Ricky W.; Carreno, Victor A.; Dowek, Gilles

2001-01-01

Safety assessment of new air traffic management systems is a main issue for civil aviation authorities. Standard techniques such as testing and simulation have serious limitations in new systems that are significantly more autonomous than the older ones. In this paper, we present an innovative approach, based on formal verification, for establishing the correctness of conflict detection systems. Fundamental to our approach is the concept of trajectory, which is a continuous path in the x-y plane constrained by physical laws and operational requirements. From the Model of trajectories, we extract, and formally prove, high level properties that can serve as a framework to analyze conflict scenarios. We use the Airborne Information for Lateral Spacing (AILS) alerting algorithm as a case study of our approach.

Spinal pedicle screw planning using deformable atlas registration

NASA Astrophysics Data System (ADS)

Goerres, J.; Uneri, A.; De Silva, T.; Ketcha, M.; Reaungamornrat, S.; Jacobson, M.; Vogt, S.; Kleinszig, G.; Osgood, G.; Wolinsky, J.-P.; Siewerdsen, J. H.

2017-04-01

Spinal screw placement is a challenging task due to small bone corridors and high risk of neurological or vascular complications, benefiting from precision guidance/navigation and quality assurance (QA). Implicit to both guidance and QA is the definition of a surgical plan—i.e. the desired trajectories and device selection for target vertebrae—conventionally requiring time-consuming manual annotations by a skilled surgeon. We propose automation of such planning by deriving the pedicle trajectory and device selection from a patient’s preoperative CT or MRI. An atlas of vertebrae surfaces was created to provide the underlying basis for automatic planning—in this work, comprising 40 exemplary vertebrae at three levels of the spine (T7, T8, and L3). The atlas was enriched with ideal trajectory annotations for 60 pedicles in total. To define trajectories for a given patient, sparse deformation fields from the atlas surfaces to the input (CT or MR image) are applied on the annotated trajectories. Mean value coordinates are used to interpolate dense deformation fields. The pose of a straight trajectory is optimized by image-based registration to an accumulated volume of the deformed annotations. For evaluation, input deformation fields were created using coherent point drift (CPD) to perform a leave-one-out analysis over the atlas surfaces. CPD registration demonstrated surface error of 0.89  ±  0.10 mm (median  ±  interquartile range) for T7/T8 and 1.29  ±  0.15 mm for L3. At the pedicle center, registered trajectories deviated from the expert reference by 0.56  ±  0.63 mm (T7/T8) and 1.12  ±  0.67 mm (L3). The predicted maximum screw diameter differed by 0.45  ±  0.62 mm (T7/T8), and 1.26  ±  1.19 mm (L3). The automated planning method avoided screw collisions in all cases and demonstrated close agreement overall with expert reference plans, offering a potentially valuable tool in support of surgical guidance and QA.

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.