Robust Foot Clearance Estimation Based on the Integration of Foot-Mounted IMU Acceleration Data

PubMed Central

Benoussaad, Mourad; Sijobert, Benoît; Mombaur, Katja; Azevedo Coste, Christine

2015-01-01

This paper introduces a method for the robust estimation of foot clearance during walking, using a single inertial measurement unit (IMU) placed on the subject’s foot. The proposed solution is based on double integration and drift cancellation of foot acceleration signals. The method is insensitive to misalignment of IMU axes with respect to foot axes. Details are provided regarding calibration and signal processing procedures. Experimental validation was performed on 10 healthy subjects under three walking conditions: normal, fast and with obstacles. Foot clearance estimation results were compared to measurements from an optical motion capture system. The mean error between them is significantly less than 15% under the various walking conditions. PMID:26703622

Bilateral step length estimation using a single inertial measurement unit attached to the pelvis

PubMed Central

2012-01-01

Background The estimation of the spatio-temporal gait parameters is of primary importance in both physical activity monitoring and clinical contexts. A method for estimating step length bilaterally, during level walking, using a single inertial measurement unit (IMU) attached to the pelvis is proposed. In contrast to previous studies, based either on a simplified representation of the human gait mechanics or on a general linear regressive model, the proposed method estimates the step length directly from the integration of the acceleration along the direction of progression. Methods The IMU was placed at pelvis level fixed to the subject's belt on the right side. The method was validated using measurements from a stereo-photogrammetric system as a gold standard on nine subjects walking ten laps along a closed loop track of about 25 m, varying their speed. For each loop, only the IMU data recorded in a 4 m long portion of the track included in the calibrated volume of the SP system, were used for the analysis. The method takes advantage of the cyclic nature of gait and it requires an accurate determination of the foot contact instances. A combination of a Kalman filter and of an optimally filtered direct and reverse integration applied to the IMU signals formed a single novel method (Kalman and Optimally filtered Step length Estimation - KOSE method). A correction of the IMU displacement due to the pelvic rotation occurring in gait was implemented to estimate the step length and the traversed distance. Results The step length was estimated for all subjects with less than 3% error. Traversed distance was assessed with less than 2% error. Conclusions The proposed method provided estimates of step length and traversed distance more accurate than any other method applied to measurements obtained from a single IMU that can be found in the literature. In healthy subjects, it is reasonable to expect that, errors in traversed distance estimation during daily monitoring activity would be of the same order of magnitude of those presented. PMID:22316235

A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors.

PubMed

Song, Yu; Nuske, Stephen; Scherer, Sebastian

2016-12-22

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight.

Environmental Data Collection Using Autonomous Wave Gliders

DTIC Science & Technology

2014-12-01

Observing System IMU Inertial Measurement Unit LRI Liquid Robotics, Inc. MASFlux Marine-Air-Sea-Flux METOC meteorological and oceanographic...position, velocity, heading, pitch, roll , and six-axis acceleration rates (Figure 11). A separate temperature probe also provides sea surface...Position, Velocity, and Magnetic declination True North Revolution Technologies GS Gyro Stabilized Electronic Compass Heading, Pitch, and Roll

LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter.

PubMed

Liu, Wanli

2017-03-08

The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated.

A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors

PubMed Central

Song, Yu; Nuske, Stephen; Scherer, Sebastian

2016-01-01

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight. PMID:28025524

Self-Alignment MEMS IMU Method Based on the Rotation Modulation Technique on a Swing Base

PubMed Central

Chen, Zhiyong; Yang, Haotian; Wang, Chengbin; Lin, Zhihui; Guo, Meifeng

2018-01-01

The micro-electro-mechanical-system (MEMS) inertial measurement unit (IMU) has been widely used in the field of inertial navigation due to its small size, low cost, and light weight, but aligning MEMS IMUs remains a challenge for researchers. MEMS IMUs have been conventionally aligned on a static base, requiring other sensors, such as magnetometers or satellites, to provide auxiliary information, which limits its application range to some extent. Therefore, improving the alignment accuracy of MEMS IMU as much as possible under swing conditions is of considerable value. This paper proposes an alignment method based on the rotation modulation technique (RMT), which is completely self-aligned, unlike the existing alignment techniques. The effect of the inertial sensor errors is mitigated by rotating the IMU. Then, inertial frame-based alignment using the rotation modulation technique (RMT-IFBA) achieved coarse alignment on the swing base. The strong tracking filter (STF) further improved the alignment accuracy. The performance of the proposed method was validated with a physical experiment, and the results of the alignment showed that the standard deviations of pitch, roll, and heading angle were 0.0140°, 0.0097°, and 0.91°, respectively, which verified the practicality and efficacy of the proposed method for the self-alignment of the MEMS IMU on a swing base. PMID:29649150

Predicting Sets and Lists: Theory and Practice

DTIC Science & Technology

2015-01-01

school. No work stands in isolation and this work would not have been possible without my co-authors: • “Contextual Optimization of Lists”: Tommy Liu... IMU Microstrain 3DM-GX3-25 PlayStation Eye camera (640x480 @ 30Hz) Onboard ARM-based Linux computer PlayStation Eye camera (640x480 @ 30Hz) Bumblebee...of the IMU integrated in the Ardupilot unit, we added a Microstrain 3DM-GX3-25 IMU which is used to aid real time pose estimation. There are two

LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter

PubMed Central

Liu, Wanli

2017-01-01

The time delay calibration between Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs) is an essential prerequisite for its applications. However, the correspondences between LiDAR and IMU measurements are usually unknown, and thus cannot be computed directly for the time delay calibration. In order to solve the problem of LiDAR-IMU time delay calibration, this paper presents a fusion method based on iterative closest point (ICP) and iterated sigma point Kalman filter (ISPKF), which combines the advantages of ICP and ISPKF. The ICP algorithm can precisely determine the unknown transformation between LiDAR-IMU; and the ISPKF algorithm can optimally estimate the time delay calibration parameters. First of all, the coordinate transformation from the LiDAR frame to the IMU frame is realized. Second, the measurement model and time delay error model of LiDAR and IMU are established. Third, the methodology of the ICP and ISPKF procedure is presented for LiDAR-IMU time delay calibration. Experimental results are presented that validate the proposed method and demonstrate the time delay error can be accurately calibrated. PMID:28282897

An enhanced inertial navigation system based on a low-cost IMU and laser scanner

NASA Astrophysics Data System (ADS)

Kim, Hyung-Soon; Baeg, Seung-Ho; Yang, Kwang-Woong; Cho, Kuk; Park, Sangdeok

2012-06-01

This paper describes an enhanced fusion method for an Inertial Navigation System (INS) based on a 3-axis accelerometer sensor, a 3-axis gyroscope sensor and a laser scanner. In GPS-denied environments, indoor or dense forests, a pure INS odometry is available for estimating the trajectory of a human or robot. However it has a critical implementation problem: a drift error of velocity, position and heading angles. Commonly the problem can be solved by fusing visual landmarks, a magnetometer or radio beacons. These methods are not robust in diverse environments: darkness, fog or sunlight, an unstable magnetic field and an environmental obstacle. We propose to overcome the drift problem using an Iterative Closest Point (ICP) scan matching algorithm with a laser scanner. This system consists of three parts. The first is the INS. It estimates attitude, velocity, position based on a 6-axis Inertial Measurement Unit (IMU) with both 'Heuristic Reduction of Gyro Drift' (HRGD) and 'Heuristic Reduction of Velocity Drift' (HRVD) methods. A frame-to-frame ICP matching algorithm for estimating position and attitude by laser scan data is the second. The third is an extended kalman filter method for multi-sensor data fusing: INS and Laser Range Finder (LRF). The proposed method is simple and robust in diverse environments, so we could reduce the drift error efficiently. We confirm the result comparing an odometry of the experimental result with ICP and LRF aided-INS in a long corridor.

Pose and Wind Estimation for Autonomous Parafoils

DTIC Science & Technology

2014-09-01

Communications GT Georgia Institute of Technology IDVD Inverse Dynamics in the Virtual Domain IMU inertial measurement unit INRIA Institut National de Recherche en...sensor. The method used is a nonlinear estimator that combines the visual sensor measurements with those of an inertial measurement unit ( IMU ) on... isolated on the left side of the equation. On the other hand, when the measurement equation of (3.27) is implemented, the probabil- 58 ity

Estimation of Antenna Pose in the Earth Frame Using Camera and IMU Data from Mobile Phones

PubMed Central

Wang, Zhen; Jin, Bingwen; Geng, Weidong

2017-01-01

The poses of base station antennas play an important role in cellular network optimization. Existing methods of pose estimation are based on physical measurements performed either by tower climbers or using additional sensors attached to antennas. In this paper, we present a novel non-contact method of antenna pose measurement based on multi-view images of the antenna and inertial measurement unit (IMU) data captured by a mobile phone. Given a known 3D model of the antenna, we first estimate the antenna pose relative to the phone camera from the multi-view images and then employ the corresponding IMU data to transform the pose from the camera coordinate frame into the Earth coordinate frame. To enhance the resulting accuracy, we improve existing camera-IMU calibration models by introducing additional degrees of freedom between the IMU sensors and defining a new error metric based on both the downtilt and azimuth angles, instead of a unified rotational error metric, to refine the calibration. In comparison with existing camera-IMU calibration methods, our method achieves an improvement in azimuth accuracy of approximately 1.0 degree on average while maintaining the same level of downtilt accuracy. For the pose estimation in the camera coordinate frame, we propose an automatic method of initializing the optimization solver and generating bounding constraints on the resulting pose to achieve better accuracy. With this initialization, state-of-the-art visual pose estimation methods yield satisfactory results in more than 75% of cases when plugged into our pipeline, and our solution, which takes advantage of the constraints, achieves even lower estimation errors on the downtilt and azimuth angles, both on average (0.13 and 0.3 degrees lower, respectively) and in the worst case (0.15 and 7.3 degrees lower, respectively), according to an evaluation conducted on a dataset consisting of 65 groups of data. We show that both of our enhancements contribute to the performance improvement offered by the proposed estimation pipeline, which achieves downtilt and azimuth accuracies of respectively 0.47 and 5.6 degrees on average and 1.38 and 12.0 degrees in the worst case, thereby satisfying the accuracy requirements for network optimization in the telecommunication industry. PMID:28397765

Loose fusion based on SLAM and IMU for indoor environment

NASA Astrophysics Data System (ADS)

Zhu, Haijiang; Wang, Zhicheng; Zhou, Jinglin; Wang, Xuejing

2018-04-01

The simultaneous localization and mapping (SLAM) method based on the RGB-D sensor is widely researched in recent years. However, the accuracy of the RGB-D SLAM relies heavily on correspondence feature points, and the position would be lost in case of scenes with sparse textures. Therefore, plenty of fusion methods using the RGB-D information and inertial measurement unit (IMU) data have investigated to improve the accuracy of SLAM system. However, these fusion methods usually do not take into account the size of matched feature points. The pose estimation calculated by RGB-D information may not be accurate while the number of correct matches is too few. Thus, considering the impact of matches in SLAM system and the problem of missing position in scenes with few textures, a loose fusion method combining RGB-D with IMU is proposed in this paper. In the proposed method, we design a loose fusion strategy based on the RGB-D camera information and IMU data, which is to utilize the IMU data for position estimation when the corresponding point matches are quite few. While there are a lot of matches, the RGB-D information is still used to estimate position. The final pose would be optimized by General Graph Optimization (g2o) framework to reduce error. The experimental results show that the proposed method is better than the RGB-D camera's method. And this method can continue working stably for indoor environment with sparse textures in the SLAM system.

Detection and Compensation of Degeneracy Cases for IMU-Kinect Integrated Continuous SLAM with Plane Features †

PubMed Central

Cho, HyunGi; Yeon, Suyong; Choi, Hyunga; Doh, Nakju

2018-01-01

In a group of general geometric primitives, plane-based features are widely used for indoor localization because of their robustness against noises. However, a lack of linearly independent planes may lead to a non-trivial estimation. This in return can cause a degenerate state from which all states cannot be estimated. To solve this problem, this paper first proposed a degeneracy detection method. A compensation method that could fix orientations by projecting an inertial measurement unit’s (IMU) information was then explained. Experiments were conducted using an IMU-Kinect v2 integrated sensor system prone to fall into degenerate cases owing to its narrow field-of-view. Results showed that the proposed framework could enhance map accuracy by successful detection and compensation of degenerated orientations. PMID:29565287

Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation

PubMed Central

Sabatini, Angelo Maria

2011-01-01

In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical. PMID:22163689

A Robust Nonlinear Observer for Real-Time Attitude Estimation Using Low-Cost MEMS Inertial Sensors

PubMed Central

Guerrero-Castellanos, José Fermi; Madrigal-Sastre, Heberto; Durand, Sylvain; Torres, Lizeth; Muñoz-Hernández, German Ardul

2013-01-01

This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS) based on low-cost MEMS (Micro-Electro-Mechanical Systems) Inertial Measure Unit (IMU) and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance. PMID:24201316

Real-time localization of mobile device by filtering method for sensor fusion

NASA Astrophysics Data System (ADS)

Fuse, Takashi; Nagara, Keita

2017-06-01

Most of the applications with mobile devices require self-localization of the devices. GPS cannot be used in indoor environment, the positions of mobile devices are estimated autonomously by using IMU. Since the self-localization is based on IMU of low accuracy, and then the self-localization in indoor environment is still challenging. The selflocalization method using images have been developed, and the accuracy of the method is increasing. This paper develops the self-localization method without GPS in indoor environment by integrating sensors, such as IMU and cameras, on mobile devices simultaneously. The proposed method consists of observations, forecasting and filtering. The position and velocity of the mobile device are defined as a state vector. In the self-localization, observations correspond to observation data from IMU and camera (observation vector), forecasting to mobile device moving model (system model) and filtering to tracking method by inertial surveying and coplanarity condition and inverse depth model (observation model). Positions of a mobile device being tracked are estimated by system model (forecasting step), which are assumed as linearly moving model. Then estimated positions are optimized referring to the new observation data based on likelihood (filtering step). The optimization at filtering step corresponds to estimation of the maximum a posterior probability. Particle filter are utilized for the calculation through forecasting and filtering steps. The proposed method is applied to data acquired by mobile devices in indoor environment. Through the experiments, the high performance of the method is confirmed.

Functional Data Analysis of Spaceflight-Induced Changes in Coordination and Phase in Head Pitch Acceleration During Treadmill Walking

NASA Technical Reports Server (NTRS)

Miller, Christopher; Peters, Brian; Feiveson, Alan; Bloomberg, Jacob

2011-01-01

Astronauts returning from spaceflight experience neurovestibular disturbances during head movements and attempt to mitigate them by limiting head motion. Analyses to date of the head movements made during walking have concentrated on amplitude and variability measures extracted from ensemble averages of individual gait cycles. Phase shifts within each gait cycle can be determined by functional data analysis through the computation of time-warping functions. Large, localized variations in the timing of peaks in head kinematics may indicate changes in coordination. The purpose of this study was to determine timing changes in head pitch acceleration of astronauts during treadmill walking before and after flight. Six astronauts (5M/1F; age = 43.5+/-6.4yr) participated in the study. Subjects walked at 1.8 m/sec (4 mph) on a motorized treadmill while reading optotypes displayed on a computer screen 4 m in front of their eyes. Three-dimensional motion of the subject s head was recorded with an Inertial Measurement Unit (IMU) device. Data were recorded twice before flight and four times after landing. The head pitch acceleration was calculated by taking the time derivative of the pitch velocity data from the IMU. Data for each session with each subject were time-normalized into gait cycles, then registered to align significant features and create a mean curve. The mean curves of each postflight session for each subject were re-registered based on their preflight mean curve to create time-warping functions. The root mean squares (RMS) of these warping functions were calculated to assess the deviation of head pitch acceleration mean curves in each postflight session from the preflight mean curve. After landing, most crewmembers exhibited localized shifts within their head pitch acceleration regimes, with the greatest deviations in RMS occurring on landing day or 1 day after landing. These results show that the alteration of head pitch coordination due to spaceflight may be assessed using an analysis of time-warping functions.

Navigation strategy and filter design for solar electric missions

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Hagar, H., Jr.

1972-01-01

Methods which have been proposed to improve the navigation accuracy for the low-thrust space vehicle include modifications to the standard Sequential- and Batch-type orbit determination procedures and the use of inertial measuring units (IMU) which measures directly the acceleration applied to the vehicle. The navigation accuracy obtained using one of the more promising modifications to the orbit determination procedures is compared with a combined IMU-Standard. The unknown accelerations are approximated as both first-order and second-order Gauss-Markov processes. The comparison is based on numerical results obtained in a study of the navigation requirements of a numerically simulated 152-day low-thrust mission to the asteroid Eros. The results obtained in the simulation indicate that the DMC algorithm will yield a significant improvement over the navigation accuracies achieved with previous estimation algorithms. In addition, the DMC algorithms will yield better navigation accuracies than the IMU-Standard Orbit Determination algorithm, except for extremely precise IMU measurements, i.e., gyroplatform alignment .01 deg and accelerometer signal-to-noise ratio .07. Unless these accuracies are achieved, the IMU navigation accuracies are generally unacceptable.

Calibration Procedures on Oblique Camera Setups

NASA Astrophysics Data System (ADS)

Kemper, G.; Melykuti, B.; Yu, C.

2016-06-01

Beside the creation of virtual animated 3D City models, analysis for homeland security and city planning, the accurately determination of geometric features out of oblique imagery is an important task today. Due to the huge number of single images the reduction of control points force to make use of direct referencing devices. This causes a precise camera-calibration and additional adjustment procedures. This paper aims to show the workflow of the various calibration steps and will present examples of the calibration flight with the final 3D City model. In difference to most other software, the oblique cameras are used not as co-registered sensors in relation to the nadir one, all camera images enter the AT process as single pre-oriented data. This enables a better post calibration in order to detect variations in the single camera calibration and other mechanical effects. The shown sensor (Oblique Imager) is based o 5 Phase One cameras were the nadir one has 80 MPIX equipped with a 50 mm lens while the oblique ones capture images with 50 MPix using 80 mm lenses. The cameras are mounted robust inside a housing to protect this against physical and thermal deformations. The sensor head hosts also an IMU which is connected to a POS AV GNSS Receiver. The sensor is stabilized by a gyro-mount which creates floating Antenna -IMU lever arms. They had to be registered together with the Raw GNSS-IMU Data. The camera calibration procedure was performed based on a special calibration flight with 351 shoots of all 5 cameras and registered the GPS/IMU data. This specific mission was designed in two different altitudes with additional cross lines on each flying heights. The five images from each exposure positions have no overlaps but in the block there are many overlaps resulting in up to 200 measurements per points. On each photo there were in average 110 well distributed measured points which is a satisfying number for the camera calibration. In a first step with the help of the nadir camera and the GPS/IMU data, an initial orientation correction and radial correction were calculated. With this approach, the whole project was calculated and calibrated in one step. During the iteration process the radial and tangential parameters were switched on individually for the camera heads and after that the camera constants and principal point positions were checked and finally calibrated. Besides that, the bore side calibration can be performed either on basis of the nadir camera and their offsets, or independently for each camera without correlation to the others. This must be performed in a complete mission anyway to get stability between the single camera heads. Determining the lever arms of the nodal-points to the IMU centre needs more caution than for a single camera especially due to the strong tilt angle. Prepared all these previous steps, you get a highly accurate sensor that enables a fully automated data extraction with a rapid update of you existing data. Frequently monitoring urban dynamics is then possible in fully 3D environment.

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

PubMed Central

Filippeschi, Alessandro; Schmitz, Norbert; Miezal, Markus; Bleser, Gabriele; Ruffaldi, Emanuele; Stricker, Didier

2017-01-01

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error). PMID:28587178

IMU: inertial sensing of vertical CoM movement.

PubMed

Esser, Patrick; Dawes, Helen; Collett, Johnny; Howells, Ken

2009-07-22

The purpose of this study was to use a quaternion rotation matrix in combination with an integration approach to transform translatory accelerations of the centre of mass (CoM) from an inertial measurement unit (IMU) during walking, from the object system onto the global frame. Second, this paper utilises double integration to determine the relative change in position of the CoM from the vertical acceleration data. Five participants were tested in which an IMU, consisting of accelerometers, gyroscopes and magnetometers was attached on the lower spine estimated centre of mass. Participants were asked to walk three times through a calibrated volume at their self-selected walking speed. Synchronized data were collected by an IMU and an optical motion capture system (OMCS); both measured at 100 Hz. Accelerations of the IMU were transposed onto the global frame using a quaternion rotation matrix. Translatory acceleration, speed and relative change in position from the IMU were compared with the derived data from the OMCS. Peak acceleration in vertical axis showed no significant difference (p> or =0.05). Difference between peak and trough speed showed significant difference (p<0.05) but relative peak-trough position between the IMU and OMCS did not show any significant difference (p> or =0.05). These results indicate that quaternions, in combination with Simpsons rule integration, can be used in transforming translatory acceleration from the object frame to the global frame and therefore obtain relative change in position, thus offering a solution for using accelerometers in accurate global frame kinematic gait analyses.

Validation of the angular measurements of a new inertial-measurement-unit based rehabilitation system: comparison with state-of-the-art gait analysis.

PubMed

Leardini, Alberto; Lullini, Giada; Giannini, Sandro; Berti, Lisa; Ortolani, Maurizio; Caravaggi, Paolo

2014-09-11

Several rehabilitation systems based on inertial measurement units (IMU) are entering the market for the control of exercises and to measure performance progression, particularly for recovery after lower limb orthopaedic treatments. IMU are easy to wear also by the patient alone, but the extent to which IMU's malpositioning in routine use can affect the accuracy of the measurements is not known. A new such system (Riablo™, CoRehab, Trento, Italy), using audio-visual biofeedback based on videogames, was assessed against state-of-the-art gait analysis as the gold standard. The sensitivity of the system to errors in the IMU's position and orientation was measured in 5 healthy subjects performing two hip joint motion exercises. Root mean square deviation was used to assess differences in the system's kinematic output between the erroneous and correct IMU position and orientation.In order to estimate the system's accuracy, thorax and knee joint motion of 17 healthy subjects were tracked during the execution of standard rehabilitation tasks and compared with the corresponding measurements obtained with an established gait protocol using stereophotogrammetry. A maximum mean error of 3.1 ± 1.8 deg and 1.9 ± 0.8 deg from the angle trajectory with correct IMU position was recorded respectively in the medio-lateral malposition and frontal-plane misalignment tests. Across the standard rehabilitation tasks, the mean distance between the IMU and gait analysis systems was on average smaller than 5°. These findings showed that the tested IMU based system has the necessary accuracy to be safely utilized in rehabilitation programs after orthopaedic treatments of the lower limb.

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning

PubMed Central

2018-01-01

Human body motion analysis based on wearable inertial measurement units (IMUs) receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation) and analysis, the IMU-to-segment (I2S) assignment and alignment are central issues to obtain biomechanical joint angles. Existing approaches for I2S assignment usually rely on hand crafted features and shallow classification approaches (e.g., support vector machines), with no agreement regarding the most suitable features for the assignment task. Moreover, estimating the complete orientation alignment of an IMU relative to the segment it is attached to using a machine learning approach has not been shown in literature so far. This is likely due to the high amount of training data that have to be recorded to suitably represent possible IMU alignment variations. In this work, we propose online approaches for solving the assignment and alignment tasks for an arbitrary amount of IMUs with respect to a biomechanical lower body model using a deep learning architecture and windows of 128 gyroscope and accelerometer data samples. For this, we combine convolutional neural networks (CNNs) for local filter learning with long-short-term memory (LSTM) recurrent networks as well as generalized recurrent units (GRUs) for learning time dynamic features. The assignment task is casted as a classification problem, while the alignment task is casted as a regression problem. In this framework, we demonstrate the feasibility of augmenting a limited amount of real IMU training data with simulated alignment variations and IMU data for improving the recognition/estimation accuracies. With the proposed approaches and final models we achieved 98.57% average accuracy over all segments for the I2S assignment task (100% when excluding left/right switches) and an average median angle error over all segments and axes of 2.91° for the I2S alignment task. PMID:29351262

Potential of IMU Sensors in Performance Analysis of Professional Alpine Skiers

PubMed Central

Yu, Gwangjae; Jang, Young Jae; Kim, Jinhyeok; Kim, Jin Hae; Kim, Hye Young; Kim, Kitae; Panday, Siddhartha Bikram

2016-01-01

In this paper, we present an analysis to identify a sensor location for an inertial measurement unit (IMU) on the body of a skier and propose the best location to capture turn motions for training. We also validate the manner in which the data from the IMU sensor on the proposed location can characterize ski turns and performance with a series of statistical analyses, including a comparison with data collected from foot pressure sensors. The goal of the study is to logically identify the ideal location on the skier’s body to attach the IMU sensor and the best use of the data collected for the skier. The statistical analyses and the hierarchical clustering method indicate that the pelvis is the best location for attachment of an IMU, and numerical validation shows that the data collected from this location can effectively estimate the performance and characteristics of the skier. Moreover, placement of the sensor at this location does not distract the skier’s motion, and the sensor can be easily attached and detached. The findings of this study can be used for the development of a wearable device for the routine training of professional skiers. PMID:27043579

Monocular camera/IMU/GNSS integration for ground vehicle navigation in challenging GNSS environments.

PubMed

Chu, Tianxing; Guo, Ningyan; Backén, Staffan; Akos, Dennis

2012-01-01

Low-cost MEMS-based IMUs, video cameras and portable GNSS devices are commercially available for automotive applications and some manufacturers have already integrated such facilities into their vehicle systems. GNSS provides positioning, navigation and timing solutions to users worldwide. However, signal attenuation, reflections or blockages may give rise to positioning difficulties. As opposed to GNSS, a generic IMU, which is independent of electromagnetic wave reception, can calculate a high-bandwidth navigation solution, however the output from a self-contained IMU accumulates errors over time. In addition, video cameras also possess great potential as alternate sensors in the navigation community, particularly in challenging GNSS environments and are becoming more common as options in vehicles. Aiming at taking advantage of these existing onboard technologies for ground vehicle navigation in challenging environments, this paper develops an integrated camera/IMU/GNSS system based on the extended Kalman filter (EKF). Our proposed integration architecture is examined using a live dataset collected in an operational traffic environment. The experimental results demonstrate that the proposed integrated system provides accurate estimations and potentially outperforms the tightly coupled GNSS/IMU integration in challenging environments with sparse GNSS observations.

Monocular Camera/IMU/GNSS Integration for Ground Vehicle Navigation in Challenging GNSS Environments

PubMed Central

Chu, Tianxing; Guo, Ningyan; Backén, Staffan; Akos, Dennis

2012-01-01

Low-cost MEMS-based IMUs, video cameras and portable GNSS devices are commercially available for automotive applications and some manufacturers have already integrated such facilities into their vehicle systems. GNSS provides positioning, navigation and timing solutions to users worldwide. However, signal attenuation, reflections or blockages may give rise to positioning difficulties. As opposed to GNSS, a generic IMU, which is independent of electromagnetic wave reception, can calculate a high-bandwidth navigation solution, however the output from a self-contained IMU accumulates errors over time. In addition, video cameras also possess great potential as alternate sensors in the navigation community, particularly in challenging GNSS environments and are becoming more common as options in vehicles. Aiming at taking advantage of these existing onboard technologies for ground vehicle navigation in challenging environments, this paper develops an integrated camera/IMU/GNSS system based on the extended Kalman filter (EKF). Our proposed integration architecture is examined using a live dataset collected in an operational traffic environment. The experimental results demonstrate that the proposed integrated system provides accurate estimations and potentially outperforms the tightly coupled GNSS/IMU integration in challenging environments with sparse GNSS observations. PMID:22736999

Mobile Gait Analysis System for Lower Limb Amputee High-Level Activity Rehabilitation

DTIC Science & Technology

2013-09-01

The direction of gravity can be used, along with trigonometry, to determine the pitch and roll orientations of the IMU . We are interested in the...are represented using direction cosine matrices so pitch and roll rotations can be isolated while rotations about the gravity vector are ignored...three signals from the gyroscope in the IMU frame and any drift associated with the gyroscope, and . An estimate of roll and pitch, and

Rate-gyro-integral constraint for ambiguity resolution in GNSS attitude determination applications.

PubMed

Zhu, Jiancheng; Li, Tao; Wang, Jinling; Hu, Xiaoping; Wu, Meiping

2013-06-21

In the field of Global Navigation Satellite System (GNSS) attitude determination, the constraints usually play a critical role in resolving the unknown ambiguities quickly and correctly. Many constraints such as the baseline length, the geometry of multi-baselines and the horizontal attitude angles have been used extensively to improve the performance of ambiguity resolution. In the GNSS/Inertial Navigation System (INS) integrated attitude determination systems using low grade Inertial Measurement Unit (IMU), the initial heading parameters of the vehicle are usually worked out by the GNSS subsystem instead of by the IMU sensors independently. However, when a rotation occurs, the angle at which vehicle has turned within a short time span can be measured accurately by the IMU. This measurement will be treated as a constraint, namely the rate-gyro-integral constraint, which can aid the GNSS ambiguity resolution. We will use this constraint to filter the candidates in the ambiguity search stage. The ambiguity search space shrinks significantly with this constraint imposed during the rotation, thus it is helpful to speeding up the initialization of attitude parameters under dynamic circumstances. This paper will only study the applications of this new constraint to land vehicles. The impacts of measurement errors on the effect of this new constraint will be assessed for different grades of IMU and current average precision level of GNSS receivers. Simulations and experiments in urban areas have demonstrated the validity and efficacy of the new constraint in aiding GNSS attitude determinations.

Validity of Hip-worn Inertial Measurement Unit Compared to Jump Mat for Jump Height Measurement in Adolescents.

PubMed

Rantalainen, T; Hesketh, K D; Rodda, C; Duckham, R L

2018-06-16

Jump tests assess lower body power production capacity, and can be used to evaluate athletic ability and development during growth. Wearable inertial measurement units (IMU) seem to offer a feasible alternative to laboratory-based equipment for jump height assessments. Concurrent validity of these devices for jump height assessments has only been established in adults. Therefore, the purpose of this study was to evaluate the concurrent validity of IMU-based jump height estimate compared to contact mat-based jump height estimate in adolescents. Ninety-five adolescents (10-13 years-of-age; girls N=41, height = 154 (SD 9) cm, weight = 44 (11) kg; boys N=54, height=156 (10) cm, weight = 46 (13) kg) completed three counter-movement jumps for maximal jump height on a contact mat. Inertial recordings (accelerations, rotations) were concurrently recorded with a hip-worn IMU (sampling at 256 Hz). Jump height was evaluated based on flight time. The mean IMU-derived jump height was 27.1 (SD 3.8) cm, and the corresponding mean jump-mat-derived value was 21.5 (3.4) cm. While a significant 26% mean difference was observed between the methods (5.5 [95% limits of agreement 2.2 to 8.9] cm, p = 0.006), the correspondence between methods was excellent (ICC = 0.89). The difference between methods was weakly positively associated with jump height (r = 0.28, P = 0.007). Take-off velocity derived jump height was also explored but produced only fair congruence. In conclusion, IMU-derived jump height exhibited excellent congruence to contact mat-based jump height and therefore presents a feasible alternative for jump height assessments in adolescents. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Angular motion estimation using dynamic models in a gyro-free inertial measurement unit.

PubMed

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters.

Angular Motion Estimation Using Dynamic Models in a Gyro-Free Inertial Measurement Unit

PubMed Central

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters. PMID:22778586

Gyroscope-reduced inertial navigation system for flight vehicle motion estimation

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiao, Lu

2017-01-01

In this paper, a novel configuration of strategically distributed accelerometer sensors with the aid of one gyro to infer a flight vehicle's angular motion is presented. The MEMS accelerometer and gyro sensors are integrated to form a gyroscope-reduced inertial measurement unit (GR-IMU). The motivation for gyro aided accelerometers array is to have direct measurements of angular rates, which is an improvement to the traditional gyroscope-free inertial system that employs only direct measurements of specific force. Some technical issues regarding error calibration in accelerometers and gyro in GR-IMU are put forward. The GR-IMU based inertial navigation system can be used to find a complete attitude solution for flight vehicle motion estimation. Results of numerical simulation are given to illustrate the effectiveness of the proposed configuration. The gyroscope-reduced inertial navigation system based on distributed accelerometer sensors can be developed into a cost effective solution for a fast reaction, MEMS based motion capture system. Future work will include the aid from external navigation references (e.g. GPS) to improve long time mission performance.

Admiralty Inlet Advanced Turbulence Measurements: June 2014

DOE Data Explorer

Kilcher, Levi

2014-06-30

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in June of 2014. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on Tidal Turbulence Mooring's (TTMs). The TTM positions the ADV head above the seafloor to make mid-depth turbulence measurements. The inertial measurements from the IMU allows for removal of mooring motion in post processing. The mooring motion has been removed from the stream-wise and vertical velocity signals (u, w). The lateral (v) velocity has some 'persistent motion contamination' due to mooring sway. Each ttm was deployed with two ADVs. The 'top' ADV head was positioned 0.5m above the 'bottom' ADV head. The TTMs were placed in 58m of water. The position of the TTMs were: ttm01 : (48.1525, -122.6867) ttm01b : (48.15256666, -122.68678333) ttm02b : (48.152783333, -122.686316666) Deployments TTM01b and TTM02b occurred simultaneously and were spaced approximately 50m apart in the cross-stream direction. Units ----- - Velocity data (_u, urot, uacc) is in m/s. - Acceleration (Accel) data is in m/s^2. - Angular rate (AngRt) data is in rad/s. - The components of all vectors are in 'ENU' orientation. That is, the first index is True East, the second is True North, and the third is Up (vertical). - All other quantities are in the units defined in the Nortek Manual. Motion correction and rotation into the ENU earth reference frame was performed using the Python-based open source DOLfYN library (http://lkilcher.github.io/dolfyn/). Details on motion correction can be found there. Additional details on TTM measurements at this site can be found in the included Marine Energy Technology Symposium paper.

Kinematic Model-Based Pedestrian Dead Reckoning for Heading Correction and Lower Body Motion Tracking.

PubMed

Lee, Min Su; Ju, Hojin; Song, Jin Woo; Park, Chan Gook

2015-11-06

In this paper, we present a method for finding the enhanced heading and position of pedestrians by fusing the Zero velocity UPdaTe (ZUPT)-based pedestrian dead reckoning (PDR) and the kinematic constraints of the lower human body. ZUPT is a well known algorithm for PDR, and provides a sufficiently accurate position solution for short term periods, but it cannot guarantee a stable and reliable heading because it suffers from magnetic disturbance in determining heading angles, which degrades the overall position accuracy as time passes. The basic idea of the proposed algorithm is integrating the left and right foot positions obtained by ZUPTs with the heading and position information from an IMU mounted on the waist. To integrate this information, a kinematic model of the lower human body, which is calculated by using orientation sensors mounted on both thighs and calves, is adopted. We note that the position of the left and right feet cannot be apart because of the kinematic constraints of the body, so the kinematic model generates new measurements for the waist position. The Extended Kalman Filter (EKF) on the waist data that estimates and corrects error states uses these measurements and magnetic heading measurements, which enhances the heading accuracy. The updated position information is fed into the foot mounted sensors, and reupdate processes are performed to correct the position error of each foot. The proposed update-reupdate technique consequently ensures improved observability of error states and position accuracy. Moreover, the proposed method provides all the information about the lower human body, so that it can be applied more effectively to motion tracking. The effectiveness of the proposed algorithm is verified via experimental results, which show that a 1.25% Return Position Error (RPE) with respect to walking distance is achieved.

A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.

PubMed

Vargas-Meléndez, Leandro; Boada, Beatriz L; Boada, María Jesús L; Gauchía, Antonio; Díaz, Vicente

2016-08-31

This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a "pseudo-roll angle" through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors' estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator.

A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation

PubMed Central

Vargas-Meléndez, Leandro; Boada, Beatriz L.; Boada, María Jesús L.; Gauchía, Antonio; Díaz, Vicente

2016-01-01

This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a “pseudo-roll angle” through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors’ estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator. PMID:27589763

Practical Application of Model-based Programming and State-based Architecture to Space Missions

NASA Technical Reports Server (NTRS)

Horvath, Gregory; Ingham, Michel; Chung, Seung; Martin, Oliver; Williams, Brian

2006-01-01

A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

PDR with a Foot-Mounted IMU and Ramp Detection

PubMed Central

Jiménez, Antonio R.; Seco, Fernando; Zampella, Francisco; Prieto, José C.; Guevara, Jorge

2011-01-01

The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps. PMID:22163701

Improving the Performance of MEMS GYROS via Redundant Measurements: Theory and Experiments

DTIC Science & Technology

2014-12-01

gyroscope arrays, improve performance inertial measurement unit ( IMU ), Sparkfun razor IMU , gyroscope, magnetometer, accelerometer, redundant IMU , angular...30 Figure 15 Sparkfun 9DOF razor IMU , after [21...43 Figure 27 Sparkfun razor IMU (bottom) connected to the FT232R breakout board (top) and then to a

Detection of chaotic dynamics in human gait signals from mobile devices

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Deng, Yunbin

2017-05-01

The ubiquity of mobile devices offers the opportunity to exploit device-generated signal data for biometric identification, health monitoring, and activity recognition. In particular, mobile devices contain an Inertial Measurement Unit (IMU) that produces acceleration and rotational rate information from the IMU accelerometers and gyros. These signals reflect motion properties of the human carrier. It is well-known that the complexity of bio-dynamical systems gives rise to chaotic dynamics. Knowledge of chaotic properties of these systems has shown utility, for example, in detecting abnormal medical conditions and neurological disorders. Chaotic dynamics has been found, in the lab, in bio-dynamical systems data such as electrocardiogram (heart), electroencephalogram (brain), and gait data. In this paper, we investigate the following question: can we detect chaotic dynamics in human gait as measured by IMU acceleration and gyro data from mobile phones? To detect chaotic dynamics, we perform recurrence analysis on real gyro and accelerometer signal data obtained from mobile devices. We apply the delay coordinate embedding approach from Takens' theorem to reconstruct the phase space trajectory of the multi-dimensional gait dynamical system. We use mutual information properties of the signal to estimate the appropriate delay value, and the false nearest neighbor approach to determine the phase space embedding dimension. We use a correlation dimension-based approach together with estimation of the largest Lyapunov exponent to make the chaotic dynamics detection decision. We investigate the ability to detect chaotic dynamics for the different one-dimensional IMU signals, across human subject and walking modes, and as a function of different phone locations on the human carrier.

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications

PubMed Central

Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser

2017-01-01

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service. PMID:28574471

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications.

PubMed

Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser

2017-06-02

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service.

On Inertial Body Tracking in the Presence of Model Calibration Errors

PubMed Central

Miezal, Markus; Taetz, Bertram; Bleser, Gabriele

2016-01-01

In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity. PMID:27455266

Estimating Thruster Impulses From IMU and Doppler Data

NASA Technical Reports Server (NTRS)

Lisano, Michael E.; Kruizinga, Gerhard L.

2009-01-01

A computer program implements a thrust impulse measurement (TIM) filter, which processes data on changes in velocity and attitude of a spacecraft to estimate the small impulsive forces and torques exerted by the thrusters of the spacecraft reaction control system (RCS). The velocity-change data are obtained from line-of-sight-velocity data from Doppler measurements made from the Earth. The attitude-change data are the telemetered from an inertial measurement unit (IMU) aboard the spacecraft. The TIM filter estimates the threeaxis thrust vector for each RCS thruster, thereby enabling reduction of cumulative navigation error attributable to inaccurate prediction of thrust vectors. The filter has been augmented with a simple mathematical model to compensate for large temperature fluctuations in the spacecraft thruster catalyst bed in order to estimate thrust more accurately at deadbanding cold-firing levels. Also, rigorous consider-covariance estimation is applied in the TIM to account for the expected uncertainty in the moment of inertia and the location of the center of gravity of the spacecraft. The TIM filter was built with, and depends upon, a sigma-point consider-filter algorithm implemented in a Python-language computer program.

Calibration Procedures in Mid Format Camera Setups

NASA Astrophysics Data System (ADS)

Pivnicka, F.; Kemper, G.; Geissler, S.

2012-07-01

A growing number of mid-format cameras are used for aerial surveying projects. To achieve a reliable and geometrically precise result also in the photogrammetric workflow, awareness on the sensitive parts is important. The use of direct referencing systems (GPS/IMU), the mounting on a stabilizing camera platform and the specific values of the mid format camera make a professional setup with various calibration and misalignment operations necessary. An important part is to have a proper camera calibration. Using aerial images over a well designed test field with 3D structures and/or different flight altitudes enable the determination of calibration values in Bingo software. It will be demonstrated how such a calibration can be performed. The direct referencing device must be mounted in a solid and reliable way to the camera. Beside the mechanical work especially in mounting the camera beside the IMU, 2 lever arms have to be measured in mm accuracy. Important are the lever arms from the GPS Antenna to the IMU's calibrated centre and also the lever arm from the IMU centre to the Camera projection centre. In fact, the measurement with a total station is not a difficult task but the definition of the right centres and the need for using rotation matrices can cause serious accuracy problems. The benefit of small and medium format cameras is that also smaller aircrafts can be used. Like that, a gyro bases stabilized platform is recommended. This causes, that the IMU must be mounted beside the camera on the stabilizer. The advantage is, that the IMU can be used to control the platform, the problematic thing is, that the IMU to GPS antenna lever arm is floating. In fact we have to deal with an additional data stream, the values of the movement of the stabiliser to correct the floating lever arm distances. If the post-processing of the GPS-IMU data by taking the floating levers into account, delivers an expected result, the lever arms between IMU and camera can be applied. However, there is a misalignment (bore side angle) that must be evaluated by photogrammetric process using advanced tools e.g. in Bingo. Once, all these parameters have been determined, the system is capable for projects without or with only a few ground control points. But which effect has the photogrammetric process when directly applying the achieved direct orientation values compared with an AT based on a proper tiepoint matching? The paper aims to show the steps to be done by potential users and gives a kind of quality estimation about the importance and quality influence of the various calibration and adjustment steps.

MEMS SoC: observer-based coplanar gyro-free inertial measurement unit

NASA Astrophysics Data System (ADS)

Chen, Tsung-Lin; Park, Sungsu

2005-09-01

This paper presents a novel design of a coplanar gyro-free inertial measurement unit (IMU) that consists of seven to nine single-axis linear accelerometers, and it can be utilized to perform the six DOF measurements for an object in motion. Unlike other gyro-fee IMUs, this design uses redundant accelerometers and state estimation techniques to facilitate the in situ and mass fabrication for the employed accelerometers. The alignment error from positioning accelerometers onto a measurement unit and the fabrication cost of an IMU can greatly be reduced. The outputs of the proposed design are three linear accelerations and three angular velocities. As compared to other gyro-free IMUs, the proposed design uses less integral operation and thus improves its sensing resolution and drifting problem. The sensing resolution of a gyro-free IMU depends on the sensing resolution of the employed accelerometers as well as the size of the measurement unit. Simulation results indicate that the sensing resolution of the proposed design is 2° s-1 for the angular velocity and 10 μg for the linear acceleration when nine single-axis accelerometers, each with 10 μg sensing resolution, are deployed on a 4 inch diameter disc. Also, thanks to the iterative EKF algorithm, the angle estimation error is within 10-3 deg at 2 s.

LOCO with a Shipboard Lidar

DTIC Science & Technology

2008-01-01

components attached. The laser is located on the far left corner of the bench the pulse chopper assembly and beam expansion optics are at center. The IMU...access to the computer and receivers. Modifications were also made to lock the alignment of the beam through the chopper to increase the output...Receiver 2 CPU & Digitizer Laser Head Pulse Chopper 100 cm 56 cm GPS & INS Therm al M anagem ent 56 cm INS Laser PC & Digitize TE cooler Page 6 of

Deep data fusion method for missile-borne inertial/celestial system

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Chen, Xiaofei; Lu, Jiazhen; Zhang, Hao

2018-05-01

Strap-down inertial-celestial integrated navigation system has the advantages of autonomy and high precision and is very useful for ballistic missiles. The star sensor installation error and inertial measurement error have a great influence for the system performance. Based on deep data fusion, this paper establishes measurement equations including star sensor installation error and proposes the deep fusion filter method. Simulations including misalignment error, star sensor installation error, IMU error are analyzed. Simulation results indicate that the deep fusion method can estimate the star sensor installation error and IMU error. Meanwhile, the method can restrain the misalignment errors caused by instrument errors.

Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.; Howard, Andrew B.; Aghazarian, Hrand; Rankin, Arturo L.

2012-01-01

PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

Statistical Sensor Fusion of a 9-DOF Mems Imu for Indoor Navigation

NASA Astrophysics Data System (ADS)

Chow, J. C. K.

2017-09-01

Sensor fusion of a MEMS IMU with a magnetometer is a popular system design, because such 9-DoF (degrees of freedom) systems are capable of achieving drift-free 3D orientation tracking. However, these systems are often vulnerable to ambient magnetic distortions and lack useful position information; in the absence of external position aiding (e.g. satellite/ultra-wideband positioning systems) the dead-reckoned position accuracy from a 9-DoF MEMS IMU deteriorates rapidly due to unmodelled errors. Positioning information is valuable in many satellite-denied geomatics applications (e.g. indoor navigation, location-based services, etc.). This paper proposes an improved 9-DoF IMU indoor pose tracking method using batch optimization. By adopting a robust in-situ user self-calibration approach to model the systematic errors of the accelerometer, gyroscope, and magnetometer simultaneously in a tightly-coupled post-processed least-squares framework, the accuracy of the estimated trajectory from a 9-DoF MEMS IMU can be improved. Through a combination of relative magnetic measurement updates and a robust weight function, the method is able to tolerate a high level of magnetic distortions. The proposed auto-calibration method was tested in-use under various heterogeneous magnetic field conditions to mimic a person walking with the sensor in their pocket, a person checking their phone, and a person walking with a smartwatch. In these experiments, the presented algorithm improved the in-situ dead-reckoning orientation accuracy by 79.8-89.5 % and the dead-reckoned positioning accuracy by 72.9-92.8 %, thus reducing the relative positioning error from metre-level to decimetre-level after ten seconds of integration, without making assumptions about the user's dynamics.

A suborbital IMU test mission

NASA Astrophysics Data System (ADS)

Lawman, Adam; Straub, Jeremy; Kerlin, Scott

2015-05-01

This paper presents work conducted in preparation for a suborbital test flight to test an inertial measurement unit's (IMU's) ability to serve as a position determination mechanism in a GPS-denied environment. Because the IMU could potentially be used at several points during flight, it is not guaranteed that a GPS fix can be used to reset the IMU after the stresses of launch. Due to this, the specific goal of this work is to characterize whether a rocket launch disrupts the IMU-based position knowledge to the extent that it is unusable. This paper discusses preparations for a sub-orbital launch mission to this end. It include a description of the hardware and software used. A discussion of the data logging mechanism and the onboard and post-flight processing which is required to compare the GPS fixes and IMU-generated positions is also presented. Finally, the utility of an IMU capable of maintaining position awareness during launch is discussed.

And the World Turned: Spin Testing the DG-1000S

DTIC Science & Technology

2015-10-01

were exceeded: 1) 30 degrees of pitch 2) 60 degrees of roll , or 3) 90 degrees of heading change. It is important to note that measurement of these post... roll or yaw angles were continuing to change at a steady or increasing rate when these criteria were exceeded. See Table 1 for adapted MIL-F-83691B...bulkhead immediately behind the rear cockpit. The pallet included a MEMSIC NAV-440 inertial measurement unit ( IMU ) which was capable of measuring

An IMU Evaluation Method Using a Signal Grafting Scheme

PubMed Central

Niu, Xiaoji; Wang, Qiang; Li, You; Zhang, Quan; Jiang, Peng

2016-01-01

As various inertial measurement units (IMUs) from different manufacturers appear every year, it is not affordable to evaluate every IMU through tests. Therefore, this paper presents an IMU evaluation method by grafting data from the tested IMU to the reference data from a higher-grade IMU. The signal grafting (SG) method has several benefits: (a) only one set of field tests with a higher-grade IMU is needed, and can be used to evaluate numerous IMUs. Thus, SG is effective and economic because all data from the tested IMU is collected in the lab; (b) it is a general approach to compare navigation performances of various IMUs by using the same reference data; and, finally, (c) through SG, one can first evaluate an IMU in the lab, and then decide whether to further test it. Moreover, this paper verified the validity of SG to both medium- and low-grade IMUs, and presents and compared two SG strategies, i.e., the basic-error strategy and the full-error strategy. SG provided results similar to field tests, with a difference of under 5% and 19.4%–26.7% for tested tactical-grade and MEMS IMUs. Meanwhile, it was found that dynamic IMU errors were essential to guarantee the effect of the SG method. PMID:27294932

A detailed description of the sequential probability ratio test for 2-IMU FDI

NASA Technical Reports Server (NTRS)

Rich, T. M.

1976-01-01

The sequential probability ratio test (SPRT) for 2-IMU FDI (inertial measuring unit failure detection/isolation) is described. The SPRT is a statistical technique for detecting and isolating soft IMU failures originally developed for the strapdown inertial reference unit. The flowchart of a subroutine incorporating the 2-IMU SPRT is included.

The processing of IMU data in ENTREE implementation and preliminary results

NASA Technical Reports Server (NTRS)

Heck, M. L.

1980-01-01

It is demonstrated that the shuttle entry trajectory can be accurately represented in ENTREE with IMU data available postflight. The IMU data consist of platform to body quaternions, and accumulated sensed velocities in mean of fifty (M50) coordinates approximately every second. The preprocessing software required to incorporate the IMU data in ENTREE is described as well as the relatively minor code changes to the ENTREE program itself required to process the IMU data. Code changes to the ENTREE program and input tape data format and content changes are described.

Adaptive Kalman filter for indoor localization using Bluetooth Low Energy and inertial measurement unit.

PubMed

Yoon, Paul K; Zihajehzadeh, Shaghayegh; Bong-Soo Kang; Park, Edward J

2015-08-01

This paper proposes a novel indoor localization method using the Bluetooth Low Energy (BLE) and an inertial measurement unit (IMU). The multipath and non-line-of-sight errors from low-power wireless localization systems commonly result in outliers, affecting the positioning accuracy. We address this problem by adaptively weighting the estimates from the IMU and BLE in our proposed cascaded Kalman filter (KF). The positioning accuracy is further improved with the Rauch-Tung-Striebel smoother. The performance of the proposed algorithm is compared against that of the standard KF experimentally. The results show that the proposed algorithm can maintain high accuracy for position tracking the sensor in the presence of the outliers.

Effect of SOS-induced levels of imuABC on spontaneous and damage-induced mutagenesis in Caulobacter crescentus.

PubMed

Alves, Ingrid R; Lima-Noronha, Marco A; Silva, Larissa G; Fernández-Silva, Frank S; Freitas, Aline Luiza D; Marques, Marilis V; Galhardo, Rodrigo S

2017-11-01

imuABC (imuAB dnaE2) genes are responsible for SOS-mutagenesis in Caulobacter crescentus and other bacterial species devoid of umuDC. In this work, we have constructed operator-constitutive mutants of the imuABC operon. We used this genetic tool to investigate the effect of SOS-induced levels of these genes upon both spontaneous and damage-induced mutagenesis. We showed that constitutive expression of imuABC does not increase spontaneous or damage-induced mutagenesis, nor increases cellular resistance to DNA-damaging agents. Nevertheless, the presence of the operator-constitutive mutation rescues mutagenesis in a recA background, indicating that imuABC are the only genes required at SOS-induced levels for translesion synthesis (TLS) in C. crescentus. Furthermore, these data also show that TLS mediated by ImuABC does not require RecA, unlike umuDC-dependent mutagenesis in E. coli. Copyright © 2017 Elsevier B.V. All rights reserved.

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles

PubMed Central

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe

2017-01-01

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work. PMID:28718788

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles.

PubMed

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe; Thom, Christian

2017-07-18

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l'information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N -th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

Miniaturized GPS/MEMS IMU integrated board

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang (Inventor)

2012-01-01

This invention documents the efforts on the research and development of a miniaturized GPS/MEMS IMU integrated navigation system. A miniaturized GPS/MEMS IMU integrated navigation system is presented; Laser Dynamic Range Imager (LDRI) based alignment algorithm for space applications is discussed. Two navigation cameras are also included to measure the range and range rate which can be integrated into the GPS/MEMS IMU system to enhance the navigation solution.

Concurrent validity and reliability of torso-worn inertial measurement unit for jump power and height estimation.

PubMed

Rantalainen, Timo; Gastin, Paul B; Spangler, Rhys; Wundersitz, Daniel

2018-09-01

The purpose of the present study was to evaluate the concurrent validity and test-retest repeatability of torso-worn IMU-derived power and jump height in a counter-movement jump test. Twenty-seven healthy recreationally active males (age, 21.9 [SD 2.0] y, height, 1.76 [0.7] m, mass, 73.7 [10.3] kg) wore an IMU and completed three counter-movement jumps a week apart. A force platform and a 3D motion analysis system were used to concurrently measure the jumps and subsequently derive power and jump height (based on take-off velocity and flight time). The IMU significantly overestimated power (mean difference = 7.3 W/kg; P < 0.001) compared to force-platform-derived power but good correspondence between methods was observed (Intra-class correlation coefficient [ICC] = 0.69). IMU-derived power exhibited good reliability (ICC = 0.67). Velocity-derived jump heights exhibited poorer concurrent validity (ICC = 0.72 to 0.78) and repeatability (ICC = 0.68) than flight-time-derived jump heights, which exhibited excellent validity (ICC = 0.93 to 0.96) and reliability (ICC = 0.91). Since jump height and power are closely related, and flight-time-derived jump height exhibits excellent concurrent validity and reliability, flight-time-derived jump height could provide a more desirable measure compared to power when assessing athletic performance in a counter-movement jump with IMUs.

Vision and dual IMU integrated attitude measurement system

NASA Astrophysics Data System (ADS)

Guo, Xiaoting; Sun, Changku; Wang, Peng; Lu, Huang

2018-01-01

To determination relative attitude between two space objects on a rocking base, an integrated system based on vision and dual IMU (inertial determination unit) is built up. The determination system fuses the attitude information of vision with the angular determinations of dual IMU by extended Kalman filter (EKF) to obtain the relative attitude. One IMU (master) is attached to the measured motion object and the other (slave) to the rocking base. As the determination output of inertial sensor is relative to inertial frame, thus angular rate of the master IMU includes not only motion of the measured object relative to inertial frame but also the rocking base relative to inertial frame, where the latter can be seen as redundant harmful movement information for relative attitude determination between the measured object and the rocking base. The slave IMU here assists to remove the motion information of rocking base relative to inertial frame from the master IMU. The proposed integrated attitude determination system is tested on practical experimental platform. And experiment results with superior precision and reliability show the feasibility and effectiveness of the proposed attitude determination system.

Magnetometer-enhanced personal locator for tunnels and GPS-denied outdoor environments

NASA Astrophysics Data System (ADS)

Kwanmuang, Surat; Ojeda, Lauro; Borenstein, Johann

2011-06-01

This paper describes recent advances with our earlier developed Personal Dead-reckoning (PDR) system for GPS-denied environments. The PDR system uses a foot-mounted Inertial Measurement Unit (IMU) that also houses a three axismagnetometer. In earlier work we developed methods for correcting the drift errors in the accelerometers, thereby allowing very accurate measurements of distance traveled. In addition, we developed a powerful heuristic method for correcting heading errors caused by gyro drift. The heuristics exploit the rectilinear features found in almost all manmade structures and therefore limit this technology to indoor use only. Most recently we integrated a three-axis magnetometer with the IMU, using a Kalman Filter. While it is well known that the ubiquitous magnetic disturbances found in most modern buildings render magnetometers almost completely useless indoors, these sensors are nonetheless very effective in pristine outdoor environments as well as in some tunnels and caves. The present paper describes the integrated magnetometer/IMU system and presents detailed experimental results. Specifically, the paper reports results of an objective test conducted by Firefighters of California's CAL-FIRE. In this particular test, two firefighters in full operational gear and one civilian hiked up a two-mile long mountain trail over rocky, sometimes steeply inclined terrain, each wearing one of our magnetometer-enhanced PDR systems but not using any GPS. During the hour-long hike the average position error was about 20 meters and the maximum error was less than 45 meters, which is about 1.4% of distance traveled for all three PDR systems.

HIFiRE-5 Flight Test Preliminary Results (Postprint)

DTIC Science & Technology

2013-11-01

DMARS-R) IMU and Ashtech DG14 Global Positioning System receiver. Results show that a tripped transition occurred on the test article leading edge...Reference System (DMARS-R) IMU and Ashtech DG14 Global Positioning System receiver. Results show that a tripped transition occurred on the test...pitch angle relative to earth as measured by IMU , or flight-path elevation angle as measured by GPS or IMU , degrees  = body-fixed angular coordinate

Radio/FADS/IMU integrated navigation for Mars entry

NASA Astrophysics Data System (ADS)

Jiang, Xiuqiang; Li, Shuang; Huang, Xiangyu

2018-03-01

Supposing future orbiting and landing collaborative exploration mission as the potential project background, this paper addresses the issue of Mars entry integrated navigation using radio beacon, flush air data sensing system (FADS), and inertial measurement unit (IMU). The range and Doppler information sensed from an orbiting radio beacon, the dynamic pressure and heating data sensed from flush air data sensing system, and acceleration and attitude angular rate outputs from an inertial measurement unit are integrated in an unscented Kalman filter to perform state estimation and suppress the system and measurement noise. Computer simulations show that the proposed integrated navigation scheme can enhance the navigation accuracy, which enables precise entry guidance for the given Mars orbiting and landing collaborative exploration mission.

Positioning in Time and Space - Cost-Effective Exterior Orientation for Airborne Archaeological Photographs

NASA Astrophysics Data System (ADS)

Verhoeven, G.; Wieser, M.; Briese, C.; Doneus, M.

2013-07-01

Since manned, airborne aerial reconnaissance for archaeological purposes is often characterised by more-or-less random photographing of archaeological features on the Earth, the exact position and orientation of the camera during image acquisition becomes very important in an effective inventorying and interpretation workflow of these aerial photographs. Although the positioning is generally achieved by simultaneously logging the flight path or directly recording the camera's position with a GNSS receiver, this approach does not allow to record the necessary roll, pitch and yaw angles of the camera. The latter are essential elements for the complete exterior orientation of the camera, which allows - together with the inner orientation of the camera - to accurately define the portion of the Earth recorded in the photograph. This paper proposes a cost-effective, accurate and precise GNSS/IMU solution (image position: 2.5 m and orientation: 2°, both at 1σ) to record all essential exterior orientation parameters for the direct georeferencing of the images. After the introduction of the utilised hardware, this paper presents the developed software that allows recording and estimating these parameters. Furthermore, this direct georeferencing information can be embedded into the image's metadata. Subsequently, the first results of the estimation of the mounting calibration (i.e. the misalignment between the camera and GNSS/IMU coordinate frame) are provided. Furthermore, a comparison with a dedicated commercial photographic GNSS/IMU solution will prove the superiority of the introduced solution. Finally, an outlook on future tests and improvements finalises this article.

Correction of static pressure on a research aircraft in accelerated flight using differential pressure measurements

NASA Astrophysics Data System (ADS)

Rodi, A. R.; Leon, D. C.

2012-05-01

Geometric altitude data from a combined Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) system on the University of Wyoming King Air research aircraft are used to estimate acceleration effects on static pressure measurement. Using data collected during periods of accelerated flight, comparison of measured pressure with that derived from GNSS/IMU geometric altitude show that errors exceeding 150 Pa can occur which is significant in airspeed and atmospheric air motion determination. A method is developed to predict static pressure errors from analysis of differential pressure measurements from a Rosemount model 858 differential pressure air velocity probe. The method was evaluated with a carefully designed probe towed on connecting tubing behind the aircraft - a "trailing cone" - in steady flight, and shown to have a precision of about ±10 Pa over a wide range of conditions including various altitudes, power settings, and gear and flap extensions. Under accelerated flight conditions, compared to the GNSS/IMU data, this algorithm predicts corrections to a precision of better than ±20 Pa. Some limiting factors affecting the precision of static pressure measurement on a research aircraft are examined.

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

Measurement of Infrasound from the Marine Environment

DTIC Science & Technology

2015-09-01

ocean heave, which are due to the change in the background atmospheric pressure as the sensor moves up and down. An external inertial measurement unit ... inertial measurement unit (IMU) was used to estimate the heave, and was highly correlated with the pressure interference signal. Mission area... MEASUREMENT UNIT ..................................................... 13 ADAPTIVE NOISE CANCELATION

Method for Estimating Three-Dimensional Knee Rotations Using Two Inertial Measurement Units: Validation with a Coordinate Measurement Machine

PubMed Central

Vitali, Rachel V.; Cain, Stephen M.; Zaferiou, Antonia M.; Ojeda, Lauro V.; Perkins, Noel C.

2017-01-01

Three-dimensional rotations across the human knee serve as important markers of knee health and performance in multiple contexts including human mobility, worker safety and health, athletic performance, and warfighter performance. While knee rotations can be estimated using optical motion capture, that method is largely limited to the laboratory and small capture volumes. These limitations may be overcome by deploying wearable inertial measurement units (IMUs). The objective of this study is to present a new IMU-based method for estimating 3D knee rotations and to benchmark the accuracy of the results using an instrumented mechanical linkage. The method employs data from shank- and thigh-mounted IMUs and a vector constraint for the medial-lateral axis of the knee during periods when the knee joint functions predominantly as a hinge. The method is carefully validated using data from high precision optical encoders in a mechanism that replicates 3D knee rotations spanning (1) pure flexion/extension, (2) pure internal/external rotation, (3) pure abduction/adduction, and (4) combinations of all three rotations. Regardless of the movement type, the IMU-derived estimates of 3D knee rotations replicate the truth data with high confidence (RMS error < 4° and correlation coefficient r≥0.94). PMID:28846613

77 FR 808 - Certain Components for Installation of Marine Autopilots With GPS or IMU; Termination of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-06

... United States after importation of certain components for installation of marine autopilots with GPS or IMU (i.e., devices for pointing and stabilizing marine navigation equipment) by reason of infringement... of Marine Autopilots With GPS or IMU; Termination of Investigation on the Basis of Settlement AGENCY...

Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

NASA Astrophysics Data System (ADS)

K., Nirmal; A. G., Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

2016-07-01

We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-07-24

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

Player Monitoring in Indoor Team Sports: Concurrent Validity of Inertial Measurement Units to Quantify Average and Peak Acceleration Values

PubMed Central

Roell, Mareike; Roecker, Kai; Gehring, Dominic; Mahler, Hubert; Gollhofer, Albert

2018-01-01

The increasing interest in assessing physical demands in team sports has led to the development of multiple sports related monitoring systems. Due to technical limitations, these systems primarily could be applied to outdoor sports, whereas an equivalent indoor locomotion analysis is not established yet. Technological development of inertial measurement units (IMU) broadens the possibilities for player monitoring and enables the quantification of locomotor movements in indoor environments. The aim of the current study was to validate an IMU measuring by determining average and peak human acceleration under indoor conditions in team sport specific movements. Data of a single wearable tracking device including an IMU (Optimeye S5, Catapult Sports, Melbourne, Australia) were compared to the results of a 3D motion analysis (MA) system (Vicon Motion Systems, Oxford, UK) during selected standardized movement simulations in an indoor laboratory (n = 56). A low-pass filtering method for gravity correction (LF) and two sensor fusion algorithms for orientation estimation [Complementary Filter (CF), Kalman-Filter (KF)] were implemented and compared with MA system data. Significant differences (p < 0.05) were found between LF and MA data but not between sensor fusion algorithms and MA. Higher precision and lower relative errors were found for CF (RMSE = 0.05; CV = 2.6%) and KF (RMSE = 0.15; CV = 3.8%) both compared to the LF method (RMSE = 1.14; CV = 47.6%) regarding the magnitude of the resulting vector and strongly emphasize the implementation of orientation estimation to accurately describe human acceleration. Comparing both sensor fusion algorithms, CF revealed slightly lower errors than KF and additionally provided valuable information about positive and negative acceleration values in all three movement planes with moderate to good validity (CV = 3.9 – 17.8%). Compared to x- and y-axis superior results were found for the z-axis. These findings demonstrate that IMU-based wearable tracking devices can successfully be applied for athlete monitoring in indoor team sports and provide potential to accurately quantify accelerations and decelerations in all three orthogonal axes with acceptable validity. An increase in accuracy taking magnetometers in account should be specifically pursued by future research. PMID:29535641

Image-Aided Navigation Using Cooperative Binocular Stereopsis

DTIC Science & Technology

2014-03-27

Global Postioning System . . . . . . . . . . . . . . . . . . . . . . . . . 1 IMU Inertial Measurement Unit...an intertial measurement unit ( IMU ). This technique capitalizes on an IMU’s ability to capture quick motion and the ability of GPS to constrain long...the sensor-aided IMU framework. Visual sensors provide a number of benefits, such as low cost and weight. These sensors are also able to measure

A New Filtering and Smoothing Algorithm for Railway Track Surveying Based on Landmark and IMU/Odometer

PubMed Central

Jiang, Qingan; Wu, Wenqi; Jiang, Mingming; Li, Yun

2017-01-01

High-accuracy railway track surveying is essential for railway construction and maintenance. The traditional approaches based on total station equipment are not efficient enough since high precision surveying frequently needs static measurements. This paper proposes a new filtering and smoothing algorithm based on the IMU/odometer and landmarks integration for the railway track surveying. In order to overcome the difficulty of estimating too many error parameters with too few landmark observations, a new model with completely observable error states is established by combining error terms of the system. Based on covariance analysis, the analytical relationship between the railway track surveying accuracy requirements and equivalent gyro drifts including bias instability and random walk noise are established. Experiment results show that the accuracy of the new filtering and smoothing algorithm for railway track surveying can reach 1 mm (1σ) when using a Ring Laser Gyroscope (RLG)-based Inertial Measurement Unit (IMU) with gyro bias instability of 0.03°/h and random walk noise of 0.005°/h while control points of the track control network (CPIII) position observations are provided by the optical total station in about every 60 m interval. The proposed approach can satisfy at the same time the demands of high accuracy and work efficiency for railway track surveying. PMID:28629191

Evaluation of low- and medium-cost IMUs for airborne gravimetry with UAVs

NASA Astrophysics Data System (ADS)

Deurloo, R. A.; Bastos, M. L.; Geng, Y.; Yan, W.

2011-12-01

The use of Unmanned Aerial Vehicles (UAVs) has increased in a large number of fields and is proving to be a good alternative to aerial surveys with traditional (manned) aircraft. In the scope of the PITVANT (Projecto de Investigação e Tecnologia em Veículos Aéreos Não-Tripulados) project, a research project funded by the Portuguese Ministry of Defence that aims at the development and demonstration of tools and technologies for UAVs, the Astronomical Observatory of the Faculty of Sciences of the University of Porto is investigating the use of UAVs for regional airborne gravimetry. The goal is to implement a so-called strapdown gravimetry system, based on the integrated use of GNSS and a low- to medium-cost IMU (Inertial Measurement Unit) that can be setup on board the UAVs developed within PITVANT. Two basic approaches exist in strapdown GNSS/IMU gravimetry: - to compute gravity disturbances directly from the combination of GNSS derived accelerations with accelerations measured by the IMU (the accelerometry approach); - to estimate the gravity disturbances as part of an inertial navigation solution using an (extended) Kalman filter (the inertial navigation approach). Because of the limitation of low- to medium-cost inertial systems the latter approach was used here. This method has proven to be effective in previous studies with this type of GNSS/IMU systems. To define the final system architecture, the performance of several different inertial systems was recently tested during an airborne survey with a regular aircraft, i.e. a CASA C212 from the Portuguese Air Force (PAF). Among the systems on board were a medium-cost Litton LN-200 and a low-cost Crossbow AHRS440, combined with a single GNSS receiver. Different Kalman filter configurations and GNSS processing options were investigated for each of the systems. The main goal was to assess the limits of the integrated GNSS/IMU systems to sense the gravity field (scalar gravimetry) and to evaluate their use and effectiveness in UAVs. The results of this analysis are presented here.

The Effects of Lever Arm (Instrument Offset) Error on GRAV-D Airborne Gravity Data

NASA Astrophysics Data System (ADS)

Johnson, J. A.; Youngman, M.; Damiani, T.

2017-12-01

High quality airborne gravity collection with a 2-axis, stabilized platform gravity instrument, such as with a Micro-g LaCoste Turnkey Airborne Gravity System (TAGS), is dependent on the aircraft's ability to maintain "straight and level" flight. However, during flight there is constant rotation about the aircraft's center of gravity. Standard practice is to install the scientific equipment close to the aircraft's estimated center of gravity to minimize the relative rotations with aircraft motion. However, there remain small offsets between the instruments. These distance offsets, the lever arm, are used to define the rigid-body, spatial relationship between the IMU, GPS antenna, and airborne gravimeter within the aircraft body frame. The Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, which is collecting airborne gravity data across the U.S., uses a commercial software package for coupled IMU-GNSS aircraft positioning. This software incorporates a lever arm correction to calculate a precise position for the airborne gravimeter. The positioning software must do a coordinate transformation to relate each epoch of the coupled GNSS-IMU derived position to the position of the gravimeter within the constantly-rotating aircraft. This transformation requires three inputs: accurate IMU-measured aircraft rotations, GNSS positions, and lever arm distances between instruments. Previous studies show that correcting for the lever arm distances improves gravity results, but no sensitivity tests have been done to investigate how error in the lever arm distances affects the final airborne gravity products. This research investigates the effects of lever arm measurement error on airborne gravity data. GRAV-D lever arms are nominally measured to the cm-level using surveying equipment. "Truth" data sets will be created by processing GRAV-D flight lines with both relatively small lever arms and large lever arms. Then negative and positive incremental errors will be introduced independently in the x, y, and z directions during GPS-IMU processing. Finally, the post-processed gravity data obtained using the erroneous lever arms will be compared to the post-processed truth sets to identify relationships between error in the lever arm measurement and the final gravity product.

Research into Kinect/Inertial Measurement Units Based on Indoor Robots.

PubMed

Li, Huixia; Wen, Xi; Guo, Hang; Yu, Min

2018-03-12

As indoor mobile navigation suffers from low positioning accuracy and accumulation error, we carried out research into an integrated location system for a robot based on Kinect and an Inertial Measurement Unit (IMU). In this paper, the close-range stereo images are used to calculate the attitude information and the translation amount of the adjacent positions of the robot by means of the absolute orientation algorithm, for improving the calculation accuracy of the robot's movement. Relying on the Kinect visual measurement and the strap-down IMU devices, we also use Kalman filtering to obtain the errors of the position and attitude outputs, in order to seek the optimal estimation and correct the errors. Experimental results show that the proposed method is able to improve the positioning accuracy and stability of the indoor mobile robot.

Localization from Visual Landmarks on a Free-Flying Robot

NASA Technical Reports Server (NTRS)

Coltin, Brian; Fusco, Jesse; Moratto, Zack; Alexandrov, Oleg; Nakamura, Robert

2016-01-01

We present the localization approach for Astrobee,a new free-flying robot designed to navigate autonomously on board the International Space Station (ISS). Astrobee will conduct experiments in microgravity, as well as assisst astronauts and ground controllers. Astrobee replaces the SPHERES robots which currently operate on the ISS, which were limited to operating in a small cube since their localization system relied on triangulation from ultrasonic transmitters. Astrobee localizes with only monocular vision and an IMU, enabling it to traverse the entire US segment of the station. Features detected on a previously-built map, optical flow information,and IMU readings are all integrated into an extended Kalman filter (EKF) to estimate the robot pose. We introduce several modifications to the filter to make it more robust to noise.Finally, we extensively evaluate the behavior of the filter on atwo-dimensional testing surface.

Localization from Visual Landmarks on a Free-Flying Robot

NASA Technical Reports Server (NTRS)

Coltin, Brian; Fusco, Jesse; Moratto, Zack; Alexandrov, Oleg; Nakamura, Robert

2016-01-01

We present the localization approach for Astrobee, a new free-flying robot designed to navigate autonomously on the International Space Station (ISS). Astrobee will accommodate a variety of payloads and enable guest scientists to run experiments in zero-g, as well as assist astronauts and ground controllers. Astrobee will replace the SPHERES robots which currently operate on the ISS, whose use of fixed ultrasonic beacons for localization limits them to work in a 2 meter cube. Astrobee localizes with monocular vision and an IMU, without any environmental modifications. Visual features detected on a pre-built map, optical flow information, and IMU readings are all integrated into an extended Kalman filter (EKF) to estimate the robot pose. We introduce several modifications to the filter to make it more robust to noise, and extensively evaluate the localization algorithm.

IMU-based Real-time Pose Measurement system for Anterior Pelvic Plane in Total Hip Replacement Surgeries.

PubMed

Zhe Cao; Shaojie Su; Hao Tang; Yixin Zhou; Zhihua Wang; Hong Chen

2017-07-01

With the aging of population, the number of Total Hip Replacement Surgeries (THR) increased year by year. In THR, inaccurate position of the implanted prosthesis may lead to the failure of the operation. In order to reduce the failure rate and acquire the real-time pose of Anterior Pelvic Plane (APP), we propose a measurement system in this paper. The measurement system includes two parts: Initial Pose Measurement Instrument (IPMI) and Real-time Pose Measurement Instrument (RPMI). IPMI is used to acquire the initial pose of the APP, and RPMI is used to estimate the real-time pose of the APP. Both are composed of an Inertial Measurement Unit (IMU) and magnetometer sensors. To estimate the attitude of the measurement system, the Extended Kalman Filter (EKF) is adopted in this paper. The real-time pose of the APP could be acquired together with the algorithm designed in the paper. The experiment results show that the Root Mean Square Error (RMSE) is within 1.6 degrees, which meets the requirement of THR operations.

Optimal Attitude Control of Agile Spacecraft Using Combined Reaction Wheel and Control Moment Gyroscope Arrays

DTIC Science & Technology

2015-12-01

10 IMU Inertial Measurement Unit . . . . . . . . . . . . . . . . . . . . . . . . . 11 PS Pseudo...filters to diminish the effect of gyro corruption in the inertial measurement unit ( IMU ) [32]. Therefore, s/c states determined by the hardware...simulator’s IMU hold the required level of accuracy for characterization of the RWCMG system in the current research. Future external state measurement systems

a Man-Portable Imu-Free Mobile Mapping System

NASA Astrophysics Data System (ADS)

Nüchter, A.; Borrmann, D.; Koch, P.; Kühn, M.; May, S.

2015-08-01

Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM in Freiburg in November 2014. In this paper, we present an IMU-free solution.

A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments.

PubMed

Allen, Marcus; Zhong, Qiang; Kirsch, Nicholas; Dani, Ashwin; Clark, William W; Sharma, Nitin

2017-12-01

Miniature inertial measurement units (IMUs) are wearable sensors that measure limb segment or joint angles during dynamic movements. However, IMUs are generally prone to drift, external magnetic interference, and measurement noise. This paper presents a new class of nonlinear state estimation technique called state-dependent coefficient (SDC) estimation to accurately predict joint angles from IMU measurements. The SDC estimation method uses limb dynamics, instead of limb kinematics, to estimate the limb state. Importantly, the nonlinear limb dynamic model is formulated into state-dependent matrices that facilitate the estimator design without performing a Jacobian linearization. The estimation method is experimentally demonstrated to predict knee joint angle measurements during functional electrical stimulation of the quadriceps muscle. The nonlinear knee musculoskeletal model was identified through a series of experiments. The SDC estimator was then compared with an extended kalman filter (EKF), which uses a Jacobian linearization and a rotation matrix method, which uses a kinematic model instead of the dynamic model. Each estimator's performance was evaluated against the true value of the joint angle, which was measured through a rotary encoder. The experimental results showed that the SDC estimator, the rotation matrix method, and EKF had root mean square errors of 2.70°, 2.86°, and 4.42°, respectively. Our preliminary experimental results show the new estimator's advantage over the EKF method but a slight advantage over the rotation matrix method. However, the information from the dynamic model allows the SDC method to use only one IMU to measure the knee angle compared with the rotation matrix method that uses two IMUs to estimate the angle.

Admiralty Inlet Advanced Turbulence Measurements: May 2015

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

Kilcher, Levi

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in May of 2015. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on a 'StableMoor' (Manufacturer: DeepWater Buoyancy) buoy and a Tidal Turbulence Mooring (TTM). These platforms position ADV heads above the seafloor to make mid-depth turbulence measurements. The inertial measurements from the IMU allows for removal of mooring motion in post processing. The mooring and buoy motion has been removed from the stream-wise and vertical velocity signals (u, w). The lateral (v) velocity has some 'persistent motion contamination' due to mooring sway.more » The TTM was deployed with one ADV, it's position was: 48 09.145', -122 41.209' The StableMoor was deployed twice, the first time it was deployed in 'wing-mode' with two ADVs ('Port' and 'Star') at: 48 09.166', -122 41.173' The second StableMoor deployment was in 'Nose' mode with one ADV at: 48 09.166', -122 41.174' Units ----- - Velocity data (_u, urot, uacc) is in m/s. - Acceleration (Accel) data is in m/s^2. - Angular rate (AngRt) data is in rad/s. - The components of all vectors are in 'ENU' orientation. That is, the first index is True East, the second is True North, and the third is Up (vertical). - All other quantities are in the units defined in the Nortek Manual. Motion correction and rotation into the ENU earth reference frame was performed using the Python-based open source DOLfYN library (http://lkilcher.github.io/dolfyn/). Details on motion correction can be found there. Additional details on TTM measurements at this site can be found in the included Marine Energy Technology Symposium paper.« less

Synthetic Air Data Estimation: A case study of model-aided estimation

NASA Astrophysics Data System (ADS)

Lie, F. Adhika Pradipta

A method for estimating airspeed, angle of attack, and sideslip without using conventional, pitot-static airdata system is presented. The method relies on measurements from GPS, an inertial measurement unit (IMU) and a low-fidelity model of the aircraft's dynamics which are fused using two, cascaded Extended Kalman Filters. In the cascaded architecture, the first filter uses information from the IMU and GPS to estimate the aircraft's absolute velocity and attitude. These estimates are used as the measurement updates for the second filter where they are fused with the aircraft dynamics model to generate estimates of airspeed, angle of attack and sideslip. Methods for dealing with the time and inter-state correlation in the measurements coming from the first filter are discussed. Simulation and flight test results of the method are presented. Simulation results using high fidelity nonlinear model show that airspeed, angle of attack, and sideslip angle estimation errors are less than 0.5 m/s, 0.1 deg, and 0.2 deg RMS, respectively. Factors that affect the accuracy including the implication and impact of using a low fidelity aircraft model are discussed. It is shown using flight tests that a single linearized aircraft model can be used in lieu of a high-fidelity, non-linear model to provide reasonably accurate estimates of airspeed (less than 2 m/s error), angle of attack (less than 3 deg error), and sideslip angle (less than 5 deg error). This performance is shown to be relatively insensitive to off-trim attitudes but very sensitive to off-trim velocity.

A Sensor Fusion Method for Tracking Vertical Velocity and Height Based on Inertial and Barometric Altimeter Measurements

PubMed Central

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-01-01

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04–0.24 m/s; height RMSE was in the range 5–68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

Vision Assisted Navigation for Miniature Unmanned Aerial Vehicles (MAVs)

DTIC Science & Technology

2009-11-01

commanded to orbit a target of known location. The error in target geolocation is shown for 200 frames with filtering (dashed line) and without (solid...so the performance of the filter was determined by using the estimated poses to solve a geolocation problem. An MAV flying at an altitude of 70 meters... geolocation as well as significantly reducing the short-term variance in the estimates based on the GPS/IMU alone. Due to the nature of the autopilot

Design and Analysis of an Attitude Determination and Control Subsystem (ADCS) for AFIT’s 6U Standard Bus

DTIC Science & Technology

2014-03-27

Fault Detection and Isolation GUI Graphical User Interface IGRF International Geomagnetic Reference Field IMU Inertial Measurement Unit IR infrared xv...ADCS hardware components were either commercially purchased or built in-house and include an Inertial Measurement Unit ( IMU ), external magnetometer, 4...3.2.1.3 IMU . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3.2.1.4 External Magnetometer . . . . . . . . . . . . . . . . . . 48 3.2.2

Validation of an inertial measurement unit for the measurement of jump count and height.

PubMed

MacDonald, Kerry; Bahr, Roald; Baltich, Jennifer; Whittaker, Jackie L; Meeuwisse, Willem H

2017-05-01

To validate the use of an inertial measurement unit (IMU) for the collection of total jump count and assess the validity of an IMU for the measurement of jump height against 3-D motion analysis. Cross sectional validation study. 3D motion-capture laboratory and field based settings. Thirteen elite adolescent volleyball players. Participants performed structured drills, played a 4 set volleyball match and performed twelve counter movement jumps. Jump counts from structured drills and match play were validated against visual count from recorded video. Jump height during the counter movement jumps was validated against concurrent 3-D motion-capture data. The IMU device captured more total jumps (1032) than visual inspection (977) during match play. During structured practice, device jump count sensitivity was strong (96.8%) while specificity was perfect (100%). The IMU underestimated jump height compared to 3D motion-capture with mean differences for maximal and submaximal jumps of 2.5 cm (95%CI: 1.3 to 3.8) and 4.1 cm (3.1-5.1), respectively. The IMU offers a valid measuring tool for jump count. Although the IMU underestimates maximal and submaximal jump height, our findings demonstrate its practical utility for field-based measurement of jump load. Copyright © 2016 Elsevier Ltd. All rights reserved.

Magnetometer-augmented IMU simulator: in-depth elaboration.

PubMed

Brunner, Thomas; Lauffenburger, Jean-Philippe; Changey, Sébastien; Basset, Michel

2015-03-04

The location of objects is a growing research topic due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromechanical systems (MEMS), inexpensive and miniaturized inertial sensors. In this context, this article describes the development of a new simulator which generates sensor measurements, giving a specific input trajectory. This will allow the comparison of pose estimation algorithms. To develop this simulator, the measurement equations of every type of sensor have to be analytically determined. To achieve this objective, classical kinematic equations are used for the more common sensors, i.e., accelerometers and rate gyroscopes. As nowadays, the MEMS inertial measurement units (IMUs) are generally magnetometer-augmented, an absolute world magnetic model is implemented. After the determination of the perfect measurement (through the error-free sensor models), realistic error models are developed to simulate real IMU behavior. Finally, the developed simulator is subjected to different validation tests.

Magnetometer-Augmented IMU Simulator: In-Depth Elaboration

PubMed Central

Brunner, Thomas; Lauffenburger, Jean-Philippe; Changey, Sébastien; Basset, Michel

2015-01-01

The location of objects is a growing research topic due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromechanical systems (MEMS), inexpensive and miniaturized inertial sensors. In this context, this article describes the development of a new simulator which generates sensor measurements, giving a specific input trajectory. This will allow the comparison of pose estimation algorithms. To develop this simulator, the measurement equations of every type of sensor have to be analytically determined. To achieve this objective, classical kinematic equations are used for the more common sensors, i.e., accelerometers and rate gyroscopes. As nowadays, the MEMS inertial measurement units (IMUs) are generally magnetometer-augmented, an absolute world magnetic model is implemented. After the determination of the perfect measurement (through the error-free sensor models), realistic error models are developed to simulate real IMU behavior. Finally, the developed simulator is subjected to different validation tests. PMID:25746095

LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing

NASA Technical Reports Server (NTRS)

Busnardo, David M.; Aitken, Matthew L.; Tolson, Robert H.; Pierrottet, Diego; Amzajerdian, Farzin

2011-01-01

In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.

An optimized Kalman filter for the estimate of trunk orientation from inertial sensors data during treadmill walking.

PubMed

Mazzà, Claudia; Donati, Marco; McCamley, John; Picerno, Pietro; Cappozzo, Aurelio

2012-01-01

The aim of this study was the fine tuning of a Kalman filter with the intent to provide optimal estimates of lower trunk orientation in the frontal and sagittal planes during treadmill walking at different speeds using measured linear acceleration and angular velocity components represented in a local system of reference. Data were simultaneously collected using both an inertial measurement unit (IMU) and a stereophotogrammetric system from three healthy subjects walking on a treadmill at natural, slow and fast speeds. These data were used to estimate the parameters of the Kalman filter that minimized the difference between the trunk orientations provided by the filter and those obtained through stereophotogrammetry. The optimized parameters were then used to process the data collected from a further 15 healthy subjects of both genders and different anthropometry performing the same walking tasks with the aim of determining the robustness of the filter set up. The filter proved to be very robust. The root mean square values of the differences between the angles estimated through the IMU and through stereophotogrammetry were lower than 1.0° and the correlation coefficients between the corresponding curves were greater than 0.91. The proposed filter design can be used to reliably estimate trunk lateral and frontal bending during walking from inertial sensor data. Further studies are needed to determine the filter parameters that are most suitable for other motor tasks. Copyright © 2011. Published by Elsevier B.V.

Admiralty Inlet Hub-Height Turbulence Measurements from June 2012

DOE Data Explorer

Kilcher, Levi

2012-06-18

This data is from measurements at Admiralty Head, in admiralty inlet. The measurements were made using an IMU equipped ADV mounted on a mooring, the 'Tidal Turbulence Mooring' or 'TTM'. The inertial measurements from the IMU allows for removal of mooring motion in post processing. The mooring motion has been removed from the stream-wise and vertical velocity signals (u, w). The lateral (v) velocity may have some 'persistent motion contamination' due to mooring sway. The ADV was positioned 11m above the seafloor in 58m of water at 48.1515N, 122.6858W. Units ----- - Velocity data (_u, urot, uacc) is in m/s. - Acceleration (Accel) data is in m/s^2. - Angular rate (AngRt) data is in rad/s. - The components of all vectors are in 'ENU' orientation. That is, the first index is True East, the second is True North, and the third is Up (vertical). - All other quantities are in the units defined in the Nortek Manual. Motion correction and rotation into the ENU earth reference frame was performed using the Python-based open source DOLfYN library (http://lkilcher.github.io/dolfyn/). Details on motion correction can be found there. For additional details on this dataset see the included Marine Energy Technology Symposium paper.

Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs

PubMed Central

Valenti, Roberto G.; Dryanovski, Ivan; Xiao, Jizhong

2015-01-01

Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the “tilt” quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter. PMID:26258778

Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs.

PubMed

Valenti, Roberto G; Dryanovski, Ivan; Xiao, Jizhong

2015-08-06

Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the "tilt" quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter.

The inertial attitude augmentation for ambiguity resolution in SF/SE-GNSS attitude determination.

PubMed

Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping

2014-06-26

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation.

The Inertial Attitude Augmentation for Ambiguity Resolution in SF/SE-GNSS Attitude Determination

PubMed Central

Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping

2014-01-01

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation. PMID:24971472

Failure Detection of a Pseudolite-Based Reference System Using Residual Monitoring

DTIC Science & Technology

2009-03-01

inertial measurements contain white Gaussian noise, wfins and w ! ins. f bins = f b + abias + w f ins (2.3) !bibins = ! b ib + !bias + w ! ins (2.4) A...type of IMU being used and the length of navigation. For a more accurate model the bias can estimated as a drift, shown as abias and !bias. The drift...to be estimated inside a Kalman lter. _abias = abias T + wabias (2.5) where T is the time constant. The strapdown mechanization for raw inertial

SeaVipers- Computer Vision and Inertial Position/Reference Sensor System (CVIPRSS)

DTIC Science & Technology

2015-08-01

uses an Inertial Measurement Unit (IMU) to detect changes in roll , pitch, and yaw (x-, y-, and z-axis movement). We use a 9DOF Razor IMU from SparkFun... inertial measurement unit (IMU) and cameras that are hardware synchronized to provide close coupling. Several fast food companies, Internet giants like...light cameras [32]. 4.1.4 Inertial Measurement Unit To assist the PTU in video stabilization for the camera and aiming the rangefinder, Sea- Vipers

Structural Acoustic UXO Detection and Identification in Marine Environments

DTIC Science & Technology

2016-05-01

BOSS Buried Object Scanning Sonar DVL Doppler Velocity Log EW East/West IMU Inertial Measurement Unit NRL Naval Research Laboratory NSWC-PCD... Inertial Measurement Unit (IMU) to time-delay and coherently sum matched-filtered phase histories from subsurface focal points over a large number of... Measurement Unit (IMU) systems. In our imaging algorithm, the 2D depth image of a target, i.e. one mapped over x and z or y and z, presents the

Trusted Remote Operation of Proximate Emergy Robots (TROOPER): DARPA Robotics Challenge

DTIC Science & Technology

2015-12-01

sensor in each of the robot’s feet. Additionally, there is a 6-axis IMU that sits in the robot’s pelvis cage. While testing before the Finals, the...Services. Many of the controllers in the autonomic layer have overlapping requirements, such as filtered IMU and force torque data from the robot...the following services during the DRC: • IMU Filtering • Force Torque Filtering • Joint State Publishing • TF (Transform) Broadcasting • Robot Pose

Trusted Remote Operation of Proximate Emergency Robots (TROOPER): DARPA Robotics Challenge

DTIC Science & Technology

2015-12-01

sensor in each of the robot’s feet. Additionally, there is a 6-axis IMU that sits in the robot’s pelvis cage. While testing before the Finals, the...Services. Many of the controllers in the autonomic layer have overlapping requirements, such as filtered IMU and force torque data from the robot...the following services during the DRC: • IMU Filtering • Force Torque Filtering • Joint State Publishing • TF (Transform) Broadcasting • Robot Pose

Position and Acceleration for Airborne Gravity; the Impact of IMU Data

NASA Astrophysics Data System (ADS)

Preaux, S. A.; Diehl, T. M.; Holmes, S. A.; Weil, C.

2012-12-01

Accurate measurements in airborne gravimetry require high quality position and acceleration information in order to remove the effects of aircraft motion from the gravimeter signal. This study examines the impact of including Inertial Measurement Unit (IMU) data in position and acceleration determination for high altitude gravimetry as part of NGS's GRAV-D project. Processing with the IMU data provides a higher rate position solution that includes aircraft attitude information. The IMU can also be a source for velocity and acceleration information but these must be used with care as they contain the aircraft motion and the gravity signal. Results from the GRAV-D project's 2008 survey season in Alaska are used as a test case for this study. The use of a tightly coupled IMU+GPS solution reduced the survey RMS and standard deviation with respect to EGM08 by an average of 0.23 mGal per data track and improved the correlation between the data tracks and EGM08 by 0.04%. While these improvements appear small they represent approximately 10% of the discrepancy. Turbulent tracks showed the biggest improvement with localized improvements larger than 5 mGal in some cases. The measured gravity processed with either a GPS only position solution or a tightly coupled GPS+IMU position solution compared with EGM08 for one data track from the GRAV-D AK08 survey.

Demonstration of Advanced Geophysics and Classification Methods on Munitions Response Sites: Closed Castner Range Fort Bliss, TX

DTIC Science & Technology

2016-04-01

Program ft foot/feet GPS Global Positioning System HE High Explosive ID Identification IDA Institute for Defense Analysis IMU Inertial Measurement Unit ISO...were replaced with two ski-shaped runners, and a new mount above the array was used to hold the Inertial Measurement Unit (IMU) and Trimble R8 Real...to collect a cued data measurement (Figure 9). The instrument’s pitch, roll , and yaw angles automatically were measured by the IMU. These angles and

Error Characterization of Flight Trajectories Reconstructed Using Structure from Motion

DTIC Science & Technology

2015-03-27

adjustment using IMU rotation information, the accuracy of the yaw, pitch and roll is limited and numerical errors can be as high as 1e-4 depending on...due to either zero mean, Gaussian noise and/or bias in the IMU measured yaw, pitch and roll angles. It is possible that when errors in these...requires both the information on how the camera is mounted to the IMU /aircraft and the measured yaw, pitch and roll at the time of the first image

Multiple IMU system test plan, volume 4. [subroutines for space shuttle requirements

NASA Technical Reports Server (NTRS)

Landey, M.; Vincent, K. T., Jr.; Whittredge, R. S.

1974-01-01

Operating procedures for this redundant system are described. A test plan is developed with two objectives. First, performance of the hardware and software delivered is demonstrated. Second, applicability of multiple IMU systems to the space shuttle mission is shown through detailed experiments with FDI algorithms and other multiple IMU software: gyrocompassing, calibration, and navigation. Gimbal flip is examined in light of its possible detrimental effects on FDI and navigation. For Vol. 3, see N74-10296.

Orbit IMU alinement interpretation of onboard display data

NASA Technical Reports Server (NTRS)

Corson, R.

1978-01-01

The space shuttle inertial measurement unit (IMU) alinement algorith was examined to determine the most important alinement starpair selection criterion. Three crew displayed parameters were considered: (1) the results of the separation angle difference (SAD) check for each starpair; (2) the separation angle of each starpair; and (3) the age of each star measurement. It was determined that the SAD for each pair cannot be used to predict the IMu alinement accuracy. If the age of each star measurement is less than approximately 30 minutes, time is a relatively unimportant factor and the most important alinement pair selection criterion is the starpair separation angle. Therefore, when there are three available alinement starpairs and all measurements were taken within the last 30 minutes, the pair with the separation angle closest to 90 degrees should be selected for IMU alinement.

A self-calibration method in single-axis rotational inertial navigation system with rotating mechanism

NASA Astrophysics Data System (ADS)

Chen, Yuanpei; Wang, Lingcao; Li, Kui

2017-10-01

Rotary inertial navigation modulation mechanism can greatly improve the inertial navigation system (INS) accuracy through the rotation. Based on the single-axis rotational inertial navigation system (RINS), a self-calibration method is put forward. The whole system is applied with the rotation modulation technique so that whole inertial measurement unit (IMU) of system can rotate around the motor shaft without any external input. In the process of modulation, some important errors can be decoupled. Coupled with the initial position information and attitude information of the system as the reference, the velocity errors and attitude errors in the rotation are used as measurement to perform Kalman filtering to estimate part of important errors of the system after which the errors can be compensated into the system. The simulation results show that the method can complete the self-calibration of the single-axis RINS in 15 minutes and estimate gyro drifts of three-axis, the installation error angle of the IMU and the scale factor error of the gyro on z-axis. The calibration accuracy of optic gyro drifts could be about 0.003°/h (1σ) as well as the scale factor error could be about 1 parts per million (1σ). The errors estimate reaches the system requirements which can effectively improve the longtime navigation accuracy of the vehicle or the boat.

GPS/MEMS IMU/Microprocessor Board for Navigation

NASA Technical Reports Server (NTRS)

Gender, Thomas K.; Chow, James; Ott, William E.

2009-01-01

A miniaturized instrumentation package comprising a (1) Global Positioning System (GPS) receiver, (2) an inertial measurement unit (IMU) consisting largely of surface-micromachined sensors of the microelectromechanical systems (MEMS) type, and (3) a microprocessor, all residing on a single circuit board, is part of the navigation system of a compact robotic spacecraft intended to be released from a larger spacecraft [e.g., the International Space Station (ISS)] for exterior visual inspection of the larger spacecraft. Variants of the package may also be useful in terrestrial collision-detection and -avoidance applications. The navigation solution obtained by integrating the IMU outputs is fed back to a correlator in the GPS receiver to aid in tracking GPS signals. The raw GPS and IMU data are blended in a Kalman filter to obtain an optimal navigation solution, which can be supplemented by range and velocity data obtained by use of (l) a stereoscopic pair of electronic cameras aboard the robotic spacecraft and/or (2) a laser dynamic range imager aboard the ISS. The novelty of the package lies mostly in those aspects of the design of the MEMS IMU that pertain to controlling mechanical resonances and stabilizing scale factors and biases.

Android Platform for Realtime Gait Tracking Using Inertial Measurement Units.

PubMed

Aqueveque, Pablo; Sobarzo, Sergio; Saavedra, Francisco; Maldonado, Claudio; Gómez, Britam

2016-06-13

One of the most important movements performed by the humans is gait. Biomechanical Gait analysis is usually by optical capture systems. However, such systems are expensive and sensitive to light and obstacles. In order to reduce those costs a system based on Inertial Measurements Units (IMU) is proposed. IMU are a good option to make movement analisys indoor with a low post-processing data, allowing to connect those systems to an Android platform. The design is based on two elements: a) The IMU sensors and the b) Android device. The IMU sensor is simple, small (35 x 35 mm), portable and autonomous (7.8 hrs). A resolution of 0.01° in their measurements is obtained, and sends data via Bluetooth link. The Android application works for Android 4.2 or higher, and it is compatible with Bluetooth devices 2.0 or higher. Three IMU sensors send data to a Tablet wirelessly, in order to evaluate the angles evolution for each joint of the leg (hip, knee and ankle). This information is used to calculate gait index and evaluate the gait quality online during the physical therapist is working with the patient.

An innovative localisation algorithm for railway vehicles

NASA Astrophysics Data System (ADS)

Allotta, B.; D'Adamio, P.; Malvezzi, M.; Pugi, L.; Ridolfi, A.; Rindi, A.; Vettori, G.

2014-11-01

In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the Italian Sistema Controllo Marcia Treno (SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and an Inertial Measurements Unit (IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements. The estimation strategy has good performance also under degraded adhesion conditions and could be put on board of high-speed railway vehicles; it represents an accurate and reliable solution. The IMU board is tested via a dedicated Hardware in the Loop (HIL) test rig: it includes an industrial robot able to replicate the motion of the railway vehicle. Through the generated experimental outputs the performances of the innovative localisation algorithm have been evaluated: the HIL test rig permitted to test the proposed algorithm, avoiding expensive (in terms of time and cost) on-track tests, obtaining encouraging results. In fact, the preliminary results show a significant improvement of the position and speed estimation performances compared to those obtained with SCMT algorithms, currently in use on the Italian railway network.

Assessing the Reliability and the Accuracy of Attitude Extracted from Visual Odometry for LIDAR Data Georeferencing

NASA Astrophysics Data System (ADS)

Leroux, B.; Cali, J.; Verdun, J.; Morel, L.; He, H.

2017-08-01

Airborne LiDAR systems require the use of Direct Georeferencing (DG) in order to compute the coordinates of the surveyed point in the mapping frame. An UAV platform does not derogate to this need, but its payload has to be lighter than this installed onboard so the manufacturer needs to find an alternative to heavy sensors and navigation systems. For the georeferencing of these data, a possible solution could be to replace the Inertial Measurement Unit (IMU) by a camera and record the optical flow. The different frames would then be processed thanks to photogrammetry so as to extract the External Orientation Parameters (EOP) and, therefore, the path of the camera. The major advantages of this method called Visual Odometry (VO) is low cost, no drifts IMU-induced, option for the use of Ground Control Points (GCPs) such as on airborne photogrammetry surveys. In this paper we shall present a test bench designed to assess the reliability and accuracy of the attitude estimated from VO outputs. The test bench consists of a trolley which embeds a GNSS receiver, an IMU sensor and a camera. The LiDAR is replaced by a tacheometer in order to survey the control points already known. We have also developped a methodology applied to this test bench for the calibration of the external parameters and the computation of the surveyed point coordinates. Several tests have revealed a difference about 2-3 centimeters between the control point coordinates measured and those already known.

Enhanced Video-Oculography System

NASA Technical Reports Server (NTRS)

Moore, Steven T.; MacDougall, Hamish G.

2009-01-01

A previously developed video-oculography system has been enhanced for use in measuring vestibulo-ocular reflexes of a human subject in a centrifuge, motor vehicle, or other setting. The system as previously developed included a lightweight digital video camera mounted on goggles. The left eye was illuminated by an infrared light-emitting diode via a dichroic mirror, and the camera captured images of the left eye in infrared light. To extract eye-movement data, the digitized video images were processed by software running in a laptop computer. Eye movements were calibrated by having the subject view a target pattern, fixed with respect to the subject s head, generated by a goggle-mounted laser with a diffraction grating. The system as enhanced includes a second camera for imaging the scene from the subject s perspective, and two inertial measurement units (IMUs) for measuring linear accelerations and rates of rotation for computing head movements. One IMU is mounted on the goggles, the other on the centrifuge or vehicle frame. All eye-movement and head-motion data are time-stamped. In addition, the subject s point of regard is superimposed on each scene image to enable analysis of patterns of gaze in real time.

Towards an IMU Evaluation Framework for Human Body Tracking.

PubMed

Venek, Verena; Kremser, Wolfgang; Schneider, Cornelia

2018-01-01

Existing full-body tracking systems, which use Inertial Measurement Units (IMUs) as sensing unit, require expert knowledge for setup and data collection. Thus, the daily application for human body tracking is difficult. In particular, in the field of active and assisted living (AAL), tracking human movements would enable novel insights not only into the quantity but also into the quality of human movement, for example by monitoring functional training. While the current market offers a wide range of products with vastly different properties, literature lacks guidelines for choosing IMUs for body tracking applications. Therefore, this paper introduces developments towards an IMU evaluation framework for human body tracking which compares IMUs against five requirement areas that consider device features and data quality. The data quality is assessed by conducting a static and a dynamic error analysis. In a first application to four IMUs of different component consumption, the IMU evaluation framework convinced as promising tool for IMU selection.

Pricise Target Geolocation Based on Integeration of Thermal Video Imagery and Rtk GPS in Uavs

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadras Javan, F.

2015-12-01

There are an increasingly large number of uses for Unmanned Aerial Vehicles (UAVs) from surveillance, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy which implicates that it cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using a linear Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors and Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process.

Kinematic Determination of an Unmodeled Serial Manipulator by Means of an IMU

NASA Astrophysics Data System (ADS)

Ciarleglio, Constance A.

Kinematic determination for an unmodeled manipulator is usually done through a-priori knowledge of the manipulator physical characteristics or external sensor information. The mathematics of the kinematic estimation, often based on Denavit- Hartenberg convention, are complex and have high computation requirements, in addition to being unique to the manipulator for which the method is developed. Analytical methods that can compute kinematics on-the fly have the potential to be highly beneficial in dynamic environments where different configurations and variable manipulator types are often required. This thesis derives a new screw theory based method of kinematic determination, using a single inertial measurement unit (IMU), for use with any serial, revolute manipulator. The method allows the expansion of reconfigurable manipulator design and simplifies the kinematic process for existing manipulators. A simulation is presented where the theory of the method is verified and characterized with error. The method is then implemented on an existing manipulator as a verification of functionality.

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

PubMed Central

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-01-01

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions. PMID:26184191

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation.

PubMed

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-07-08

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions.

Guidance of Autonomous Aerospace Vehicles for Vertical Soft Landing using Nonlinear Control Theory

DTIC Science & Technology

2015-08-11

Measured and Kalman filter Estimate of the Roll Attitude of the Quad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.4...and faster Hart- ley et al. [2013]. With availability of small, light, high fidelity sensors (Inertial Measurement Units IMU ) and processors on board...is a product of inverse of rotation matrix and inertia matrix for the quad frame. Since both the matrix are invertible at all times except when roll

Light Detection and Ranging-Based Terrain Navigation: A Concept Exploration

NASA Technical Reports Server (NTRS)

Campbell, Jacob; UijtdeHaag, Maarten; vanGraas, Frank; Young, Steve

2003-01-01

This paper discusses the use of Airborne Light Detection And Ranging (LiDAR) equipment for terrain navigation. Airborne LiDAR is a relatively new technology used primarily by the geo-spatial mapping community to produce highly accurate and dense terrain elevation maps. In this paper, the term LiDAR refers to a scanning laser ranger rigidly mounted to an aircraft, as opposed to an integrated sensor system that consists of a scanning laser ranger integrated with Global Positioning System (GPS) and Inertial Measurement Unit (IMU) data. Data from the laser range scanner and IMU will be integrated with a terrain database to estimate the aircraft position and data from the laser range scanner will be integrated with GPS to estimate the aircraft attitude. LiDAR data was collected using NASA Dryden's DC-8 flying laboratory in Reno, NV and was used to test the proposed terrain navigation system. The results of LiDAR-based terrain navigation shown in this paper indicate that airborne LiDAR is a viable technology enabler for fully autonomous aircraft navigation. The navigation performance is highly dependent on the quality of the terrain databases used for positioning and therefore high-resolution (2 m post-spacing) data was used as the terrain reference.

Final STS-35 Columbia descent BET products and results for LaRC OEX investigations

NASA Technical Reports Server (NTRS)

Oakes, Kevin F.; Findlay, John T.; Jasinski, Rachel A.; Wood, James S.

1991-01-01

Final STS-35 'Columbia' descent Best Estimate Trajectory (BET) products have been developed for Langley Research Center (LaRC) Orbiter Experiments (OEX) investigations. Included are the reconstructed inertial trajectory profile; the Extended BET, which combines the inertial data and, in this instance, the National Weather Service atmospheric information obtained via Johnson Space Center; and the Aerodynamic BET. The inertial BET utilized Inertial Measurement Unit 1 (IMU1) dynamic measurements for deterministic propagation during the ENTREE estimation process. The final estimate was based on the considerable ground based C-band tracking coverage available as well as Tracking Data and Relay Satellite System (TDRSS) Doppler data, a unique use of the latter for endo-atmospheric flight determinations. The actual estimate required simultaneous solutions for the spacecraft position and velocity, spacecraft attitude, and six IMU parameters - three gyro biases and three accelerometer scale factor correction terms. The anchor epoch for this analysis was 19,200 Greenwich Mean Time (GMT) seconds which corresponds to an initial Shuttle altitude of approximately 513 kft. The atmospheric data incorporated were evaluated based on Shuttle derived considerations as well as comparisons with other models. The AEROBET was developed based on the Extended BET, the measured spacecraft configuration information, final mass properties, and the final Orbiter preoperation databook. The latter was updated based on aerodynamic consensus incrementals derived by the latest published FAD. The rectified predictions were compared versus the flight computed values and the resultant differences were correlated versus ensemble results for twenty-two previous STS entry flights.

Validation of distal limb mounted inertial measurement unit sensors for stride detection in Warmblood horses at walk and trot.

PubMed

Bragança, F M; Bosch, S; Voskamp, J P; Marin-Perianu, M; Van der Zwaag, B J; Vernooij, J C M; van Weeren, P R; Back, W

2017-07-01

Inertial measurement unit (IMU) sensor-based techniques are becoming more popular in horses as a tool for objective locomotor assessment. To describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU sensors. Prospective validation study comparing IMU sensors and motion capture with force plate data. A total of seven Warmblood horses equipped with metacarpal/metatarsal IMU sensors and reflective markers for motion capture were hand walked and trotted over a force plate. Using four custom built algorithms hoof-on/hoof-off timing over the force plate were calculated for each trial from the IMU data. Accuracy of the computed parameters was calculated as the mean difference in milliseconds between the IMU or motion capture generated data and the data from the force plate, precision as the s.d. of these differences and percentage of error with accuracy of the calculated parameter as a percentage of the force plate stance duration. Accuracy, precision and percentage of error of the best performing IMU algorithm for stance duration at walk were 28.5, 31.6 ms and 3.7% for the forelimbs and -5.5, 20.1 ms and -0.8% for the hindlimbs, respectively. At trot the best performing algorithm achieved accuracy, precision and percentage of error of -27.6/8.8 ms/-8.4% for the forelimbs and 6.3/33.5 ms/9.1% for the hindlimbs. The described algorithms have not been assessed on different surfaces. Inertial measurement unit technology can be used to determine temporal kinematic stride variables at walk and trot justifying its use in gait and performance analysis. However, precision of the method may not be sufficient to detect all possible lameness-related changes. These data seem promising enough to warrant further research to evaluate whether this approach will be useful for appraising the majority of clinically relevant gait changes encountered in practice. © 2016 The Authors. Equine Veterinary Journal published by John Wiley & Sons Ltd on behalf of EVJ Ltd.

120. INERTIAL MEASUREMENT UNIT (IMU) NITROGEN PURGE REGULATOR PANEL FOR ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

120. INERTIAL MEASUREMENT UNIT (IMU) NITROGEN PURGE REGULATOR PANEL FOR DEFENSE METEOROLOGICAL SYSTEM PROGRAM (DMSP) PAYLOADS IN SOUTHWEST CORNER OF VEHICLE MECHANICAL SYSTEMS ROOM (111), LSB (BLDG. 770) - Vandenberg Air Force Base, Space Launch Complex 3, Launch Pad 3 West, Napa & Alden Roads, Lompoc, Santa Barbara County, CA

Orion Exploration Flight Test-1 Post-Flight Navigation Performance Assessment Relative to the Best Estimated Trajectory

NASA Technical Reports Server (NTRS)

Gay, Robert S.; Holt, Greg N.; Zanetti, Renato

2016-01-01

This paper details the post-flight navigation performance assessment of the Orion Exploration Flight Test-1 (EFT-1). Results of each flight phase are presented: Ground Align, Ascent, Orbit, and Entry Descent and Landing. This study examines the on-board Kalman Filter uncertainty along with state deviations relative to the Best Estimated Trajectory (BET). Overall the results show that the Orion Navigation System performed as well or better than expected. Specifically, the Global Positioning System (GPS) measurement availability was significantly better than anticipated at high altitudes. In addition, attitude estimation via processing GPS measurements along with Inertial Measurement Unit (IMU) data performed very well and maintained good attitude throughout the mission.

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients.

PubMed

Massé, Fabien; Gonzenbach, Roman R; Arami, Arash; Paraschiv-Ionescu, Anisoara; Luft, Andreas R; Aminian, Kamiar

2015-08-25

Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients' mobility in daily life. Physical activity performance in daily-life can be assessed using unobtrusive monitoring, for example with a single sensor module fixed on the trunk. Existing approaches based on inertial sensors have limited performance, particularly in detecting transitions between different activities and postures, due to the inherent inter-patient variability of kinematic patterns. To overcome these limitations, one possibility is to use additional information from a barometric pressure (BP) sensor. Our study aims at integrating BP and inertial sensor data into an activity classifier in order to improve the activity (sitting, standing, walking, lying) recognition and the corresponding body elevation (during climbing stairs or when taking an elevator). Taking into account the trunk elevation changes during postural transitions (sit-to-stand, stand-to-sit), we devised an event-driven activity classifier based on fuzzy-logic. Data were acquired from 12 stroke patients with impaired mobility, using a trunk-worn inertial and BP sensor. Events, including walking and lying periods and potential postural transitions, were first extracted. These events were then fed into a double-stage hierarchical Fuzzy Inference System (H-FIS). The first stage processed the events to infer activities and the second stage improved activity recognition by applying behavioral constraints. Finally, the body elevation was estimated using a pattern-enhancing algorithm applied on BP. The patients were videotaped for reference. The performance of the algorithm was estimated using the Correct Classification Rate (CCR) and F-score. The BP-based classification approach was benchmarked against a previously-published fuzzy-logic classifier (FIS-IMU) and a conventional epoch-based classifier (EPOCH). The algorithm performance for posture/activity detection, in terms of CCR was 90.4 %, with 3.3 % and 5.6 % improvements against FIS-IMU and EPOCH, respectively. The proposed classifier essentially benefits from a better recognition of standing activity (70.3 % versus 61.5 % [FIS-IMU] and 42.5 % [EPOCH]) with 98.2 % CCR for body elevation estimation. The monitoring and recognition of daily activities in mobility-impaired stoke patients can be significantly improved using a trunk-fixed sensor that integrates BP, inertial sensors, and an event-based activity classifier.

Pricise Target Geolocation and Tracking Based on Uav Video Imagery

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadrasjavan, F.

2016-06-01

There is an increasingly large number of applications for Unmanned Aerial Vehicles (UAVs) from monitoring, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using an extended Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors, Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process. The results of this study compared with code-based ordinary GPS, indicate that RTK observation with proposed method shows more than 10 times improvement of accuracy in target geolocation.

GPS aiding of ocean current determination. [Global Positioning System

NASA Technical Reports Server (NTRS)

Mohan, S. N.

1981-01-01

The navigational accuracy of an oceangoing vessel using conventional GPS p-code data is examined. The GPS signal is transmitted over two carrier frequencies in the L-band at 1575.42 and 1227.6 MHz. Achievable navigational uncertainties of differenced positional estimates are presented as a function of the parameters of the problem, with particular attention given to the effect of sea-state, user equivalent range error, uncompensated antenna motion, varying delay intervals, and reduced data rate examined in the unaided mode. The unmodeled errors resulting from satellite ephemeris uncertainties are shown to be negligible for the GPS-NDS (Navigation Development) satellites. Requirements are met in relatively calm seas, but accuracy degradation by a factor of at least 2 must be anticipated in heavier sea states. The aided mode of operation is examined, and it is shown that requirements can be met by using an inertial measurement unit (IMU) to aid the GPS receiver operation. Since the use of an IMU would mean higher costs, direct Doppler from the GPS satellites is presented as a viable alternative.

Automated Driftmeter Fused with Inertial Navigation

DTIC Science & Technology

2014-03-27

6 IMU Inertial Measurement Unit . . . . . . . . . . . . . . . . . . . . . . . 7 SLAM Simultaneous...timing lines to remain horizontal at all times, regardless of turbulence and within 20 degrees of roll , pitch, and yaw of the aircraft. It had two...introduced in 1960 [2]. The Kalman filter algorithm has been used to merge inertial navigational data from Inertial Measurement Units ( IMU ) with

Implementation of a Real-Time Stacking Algorithm in a Photogrammetric Digital Camera for Uavs

NASA Astrophysics Data System (ADS)

Audi, A.; Pierrot-Deseilligny, M.; Meynard, C.; Thom, C.

2017-08-01

In the recent years, unmanned aerial vehicles (UAVs) have become an interesting tool in aerial photography and photogrammetry activities. In this context, some applications (like cloudy sky surveys, narrow-spectral imagery and night-vision imagery) need a longexposure time where one of the main problems is the motion blur caused by the erratic camera movements during image acquisition. This paper describes an automatic real-time stacking algorithm which produces a high photogrammetric quality final composite image with an equivalent long-exposure time using several images acquired with short-exposure times. Our method is inspired by feature-based image registration technique. The algorithm is implemented on the light-weight IGN camera, which has an IMU sensor and a SoC/FPGA. To obtain the correct parameters for the resampling of images, the presented method accurately estimates the geometrical relation between the first and the Nth image, taking into account the internal parameters and the distortion of the camera. Features are detected in the first image by the FAST detector, than homologous points on other images are obtained by template matching aided by the IMU sensors. The SoC/FPGA in the camera is used to speed up time-consuming parts of the algorithm such as features detection and images resampling in order to achieve a real-time performance as we want to write only the resulting final image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images, as well as block diagrams of the described architecture. The resulting stacked image obtained on real surveys doesn't seem visually impaired. Timing results demonstrate that our algorithm can be used in real-time since its processing time is less than the writing time of an image in the storage device. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real-time the gyrometers of the IMU.

Pushbroom Hyperspectral Imaging from AN Unmanned Aircraft System (uas) - Geometric Processingworkflow and Accuracy Assessment

NASA Astrophysics Data System (ADS)

Turner, D.; Lucieer, A.; McCabe, M.; Parkes, S.; Clarke, I.

2017-08-01

In this study, we assess two push broom hyperspectral sensors as carried by small (10-15 kg) multi-rotor Unmanned Aircraft Systems (UAS). We used a Headwall Photonics micro-Hyperspec push broom sensor with 324 spectral bands (4-5 nm FWHM) and a Headwall Photonics nano-Hyperspec sensor with 270 spectral bands (6 nm FWHM) both in the VNIR spectral range (400-1000 nm). A gimbal was used to stabilise the sensors in relation to the aircraft flight dynamics, and for the micro-Hyperspec a tightly coupled dual frequency Global Navigation Satellite System (GNSS) receiver, an Inertial Measurement Unit (IMU), and Machine Vision Camera (MVC) were used for attitude and position determination. For the nano-Hyperspec, a navigation grade GNSS system and IMU provided position and attitude data. This study presents the geometric results of one flight over a grass oval on which a dense Ground Control Point (GCP) network was deployed. The aim being to ascertain the geometric accuracy achievable with the system. Using the PARGE software package (ReSe - Remote Sensing Applications) we ortho-rectify the push broom hyperspectral image strips and then quantify the accuracy of the ortho-rectification by using the GCPs as check points. The orientation (roll, pitch, and yaw) of the sensor is measured by the IMU. Alternatively imagery from a MVC running at 15 Hz, with accurate camera position data can be processed with Structure from Motion (SfM) software to obtain an estimated camera orientation. In this study, we look at which of these data sources will yield a flight strip with the highest geometric accuracy.

Space shuttle navigation analysis. Volume 2: Baseline system navigation

NASA Technical Reports Server (NTRS)

Jones, H. L.; Luders, G.; Matchett, G. A.; Rains, R. G.

1980-01-01

Studies related to the baseline navigation system for the orbiter are presented. The baseline navigation system studies include a covariance analysis of the Inertial Measurement Unit calibration and alignment procedures, postflight IMU error recovery for the approach and landing phases, on-orbit calibration of IMU instrument biases, and a covariance analysis of entry and prelaunch navigation system performance.

Development and Flight Test of a Robust Optical-Inertial Navigation System Using Low-Cost Sensors

DTIC Science & Technology

2008-03-01

for this test. Though, marketed as a GPS/INS, it was in fact used simply as an IMU for this test. The raw inertial measurement data (from the...Performance Evaluation of Low Cost MEMS-Based IMU Integrated With GPS for Land Vehicle Navigation Application. MS Thesis, UCGE Reports Number

Redundancy management of multiple KT-70 inertial measurement units applicable to the space shuttle

NASA Technical Reports Server (NTRS)

Cook, L. J.

1975-01-01

Results of an investigation of velocity failure detection and isolation for 3 inertial measuring units (IMU) and 2 inertial measuring units (IMU) configurations are presented. The failure detection and isolation algorithm performance was highly successful and most types of velocity errors were detected and isolated. The failure detection and isolation algorithm also included attitude FDI but was not evaluated because of the lack of time and low resolution in the gimbal angle synchro outputs. The shuttle KT-70 IMUs will have dual-speed resolvers and high resolution gimbal angle readouts. It was demonstrated by these tests that a single computer utilizing a serial data bus can successfully control a redundant 3-IMU system and perform FDI.

Pointing System Simulation Toolbox with Application to a Balloon Mission Simulator

NASA Technical Reports Server (NTRS)

Maringolo Baldraco, Rosana M.; Aretskin-Hariton, Eliot D.; Swank, Aaron J.

2017-01-01

The development of attitude estimation and pointing-control algorithms is necessary in order to achieve high-fidelity modeling for a Balloon Mission Simulator (BMS). A pointing system simulation toolbox was developed to enable this. The toolbox consists of a star-tracker (ST) and Inertial Measurement Unit (IMU) signal generator, a UDP (User Datagram Protocol) communication le (bridge), and an indirect-multiplicative extended Kalman filter (imEKF). This document describes the Python toolbox developed and the results of its implementation in the imEKF.

Tightly-Coupled Integration of Multi-GNSS Single-Frequency RTK and MEMS-IMU for Enhanced Positioning Performance

PubMed Central

Li, Tuan; Zhang, Hongping; Niu, Xiaoji; Gao, Zhouzheng

2017-01-01

Dual-frequency Global Positioning System (GPS) Real-time Kinematics (RTK) has been proven in the past few years to be a reliable and efficient technique to obtain high accuracy positioning. However, there are still challenges for GPS single-frequency RTK, such as low reliability and ambiguity resolution (AR) success rate, especially in kinematic environments. Recently, multi-Global Navigation Satellite System (multi-GNSS) has been applied to enhance the RTK performance in terms of availability and reliability of AR. In order to further enhance the multi-GNSS single-frequency RTK performance in terms of reliability, continuity and accuracy, a low-cost micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) is adopted in this contribution. We tightly integrate the single-frequency GPS/BeiDou/GLONASS and MEMS-IMU through the extended Kalman filter (EKF), which directly fuses the ambiguity-fixed double-differenced (DD) carrier phase observables and IMU data. A field vehicular test was carried out to evaluate the impacts of the multi-GNSS and IMU on the AR and positioning performance in different system configurations. Test results indicate that the empirical success rate of single-epoch AR for the tightly-coupled single-frequency multi-GNSS RTK/INS integration is over 99% even at an elevation cut-off angle of 40°, and the corresponding position time series is much more stable in comparison with the GPS solution. Besides, GNSS outage simulations show that continuous positioning with certain accuracy is possible due to the INS bridging capability when GNSS positioning is not available. PMID:29077070

Tightly-Coupled Integration of Multi-GNSS Single-Frequency RTK and MEMS-IMU for Enhanced Positioning Performance.

PubMed

Li, Tuan; Zhang, Hongping; Niu, Xiaoji; Gao, Zhouzheng

2017-10-27

Dual-frequency Global Positioning System (GPS) Real-time Kinematics (RTK) has been proven in the past few years to be a reliable and efficient technique to obtain high accuracy positioning. However, there are still challenges for GPS single-frequency RTK, such as low reliability and ambiguity resolution (AR) success rate, especially in kinematic environments. Recently, multi-Global Navigation Satellite System (multi-GNSS) has been applied to enhance the RTK performance in terms of availability and reliability of AR. In order to further enhance the multi-GNSS single-frequency RTK performance in terms of reliability, continuity and accuracy, a low-cost micro-electro-mechanical system (MEMS) inertial measurement unit (IMU) is adopted in this contribution. We tightly integrate the single-frequency GPS/BeiDou/GLONASS and MEMS-IMU through the extended Kalman filter (EKF), which directly fuses the ambiguity-fixed double-differenced (DD) carrier phase observables and IMU data. A field vehicular test was carried out to evaluate the impacts of the multi-GNSS and IMU on the AR and positioning performance in different system configurations. Test results indicate that the empirical success rate of single-epoch AR for the tightly-coupled single-frequency multi-GNSS RTK/INS integration is over 99% even at an elevation cut-off angle of 40°, and the corresponding position time series is much more stable in comparison with the GPS solution. Besides, GNSS outage simulations show that continuous positioning with certain accuracy is possible due to the INS bridging capability when GNSS positioning is not available.

A Multimodal Adaptive Wireless Control Interface for People With Upper-Body Disabilities.

PubMed

Fall, Cheikh Latyr; Quevillon, Francis; Blouin, Martine; Latour, Simon; Campeau-Lecours, Alexandre; Gosselin, Clement; Gosselin, Benoit

2018-06-01

This paper describes a multimodal body-machine interface (BoMI) to help individuals with upper-limb disabilities using advanced assistive technologies, such as robotic arms. The proposed system uses a wearable and wireless body sensor network (WBSN) supporting up to six sensor nodes to measure the natural upper-body gesture of the users and translate it into control commands. Natural gesture of the head and upper-body parts, as well as muscular activity, are measured using inertial measurement units (IMUs) and surface electromyography (sEMG) using custom-designed multimodal wireless sensor nodes. An IMU sensing node is attached to a headset worn by the user. It has a size of 2.9 cm 2.9 cm, a maximum power consumption of 31 mW, and provides angular precision of 1. Multimodal patch sensor nodes, including both IMU and sEMG sensing modalities are placed over the user able-body parts to measure the motion and muscular activity. These nodes have a size of 2.5 cm 4.0 cm and a maximum power consumption of 11 mW. The proposed BoMI runs on a Raspberry Pi. It can adapt to several types of users through different control scenarios using the head and shoulder motion, as well as muscular activity, and provides a power autonomy of up to 24 h. JACO, a 6-DoF assistive robotic arm, is used as a testbed to evaluate the performance of the proposed BoMI. Ten able-bodied subjects performed ADLs while operating the AT device, using the Test d'Évaluation des Membres Supérieurs de Personnes Âgées to evaluate and compare the proposed BoMI with the conventional joystick controller. It is shown that the users can perform all tasks with the proposed BoMI, almost as fast as with the joystick controller, with only 30% time overhead on average, while being potentially more accessible to the upper-body disabled who cannot use the conventional joystick controller. Tests show that control performance with the proposed BoMI improved by up to 17% on average, after three trials.

75 FR 74127 - In the Matter of the Review of the Designation of Islamic Movement of Uzbekistan (IMU and Other...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-30

... DEPARTMENT OF STATE [Public Notice: 7250] In the Matter of the Review of the Designation of Islamic Movement of Uzbekistan (IMU and Other Aliases) as a Foreign Terrorist Organization Pursuant to Section 219 of the Immigration and Nationality Act, as Amended Based upon a review of the Administrative...

POF-IMU sensor system: A fusion between inertial measurement units and POF sensors for low-cost and highly reliable systems

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Vargas-Valencia, Laura; dos Santos, Wilian M.; Schneider, Felipe B. A.; Siqueira, Adriano A. G.; Pontes, Maria José; Frizera, Anselmo

2018-07-01

This paper presents a low cost and highly reliable system for angle measurement based on a sensor fusion between inertial and fiber optic sensors. The system consists of the sensor fusion through Kalman filter of two inertial measurement units (IMUs) and an intensity variation-based polymer optical fiber (POF) curvature sensor. In addition, the IMU was applied as a reference for a compensation technique of POF curvature sensor hysteresis. The proposed system was applied on the knee angle measurement of a lower limb exoskeleton in flexion/extension cycles and in gait analysis. Results show the accuracy of the system, where the Root Mean Square Error (RMSE) between the POF-IMU sensor system and the encoder was below 4° in the worst case and about 1° in the best case. Then, the POF-IMU sensor system was evaluated as a wearable sensor for knee joint angle assessment without the exoskeleton, where its suitability for this purpose was demonstrated. The results obtained in this paper pave the way for future applications of sensor fusion between electronic and fiber optic sensors in movement analysis.

Alignment Jig for the Precise Measurement of THz Radiation

NASA Technical Reports Server (NTRS)

Javadi, Hamid H.

2009-01-01

A miniaturized instrumentation package comprising a (1) Global Positioning System (GPS) receiver, (2) an inertial measurement unit (IMU) consisting largely of surface-micromachined sensors of the microelectromechanical systems (MEMS) type, and (3) a microprocessor, all residing on a single circuit board, is part of the navigation system of a compact robotic spacecraft intended to be released from a larger spacecraft [e.g., the International Space Station (ISS)] for exterior visual inspection of the larger spacecraft. Variants of the package may also be useful in terrestrial collision-detection and -avoidance applications. The navigation solution obtained by integrating the IMU outputs is fed back to a correlator in the GPS receiver to aid in tracking GPS signals. The raw GPS and IMU data are blended in a Kalman filter to obtain an optimal navigation solution, which can be supplemented by range and velocity data obtained by use of (l) a stereoscopic pair of electronic cameras aboard the robotic spacecraft and/or (2) a laser dynamic range imager aboard the ISS. The novelty of the package lies mostly in those aspects of the design of the MEMS IMU that pertain to controlling mechanical resonances and stabilizing scale factors and biases.

Performance analysis of an IMU-augmented GNSS tracking system on board the MAIUS-1 sounding rocket

NASA Astrophysics Data System (ADS)

Braun, Benjamin; Grillenberger, Andreas; Markgraf, Markus

2018-05-01

Satellite navigation receivers are adequate tracking sensors for range safety of both orbital launch vehicles and suborbital sounding rockets. Due to high accuracy and its low system complexity, satellite navigation is seen as well-suited supplement or replacement of conventional tracking systems like radar. Having the well-known shortcomings of satellite navigation like deliberate or unintentional interferences in mind, it is proposed to augment the satellite navigation receiver by an inertial measurement unit (IMU) to enhance continuity and availability of localization. The augmented receiver is thus enabled to output at least an inertial position solution in case of signal outages. In a previous study, it was shown by means of simulation using the example of Ariane 5 that the performance of a low-grade microelectromechanical IMU is sufficient to bridge expected outages of some ten seconds, and still meeting the range safety requirements in effect. In this publication, these theoretical findings shall be substantiated by real flight data that were recorded on MAIUS-1, a sounding rocket launched from Esrange, Sweden, in early 2017. The analysis reveals that the chosen representative of a microelectromechanical IMU is suitable to bridge outages of up to thirty seconds.

GPS/INS Sensor Fusion Using GPS Wind up Model

NASA Technical Reports Server (NTRS)

Williamson, Walton R. (Inventor)

2013-01-01

A method of stabilizing an inertial navigation system (INS), includes the steps of: receiving data from an inertial navigation system; and receiving a finite number of carrier phase observables using at least one GPS receiver from a plurality of GPS satellites; calculating a phase wind up correction; correcting at least one of the finite number of carrier phase observables using the phase wind up correction; and calculating a corrected IMU attitude or velocity or position using the corrected at least one of the finite number of carrier phase observables; and performing a step selected from the steps consisting of recording, reporting, or providing the corrected IMU attitude or velocity or position to another process that uses the corrected IMU attitude or velocity or position. A GPS stabilized inertial navigation system apparatus is also described.

Intelligent Behavioral Action Aiding for Improved Autonomous Image Navigation

DTIC Science & Technology

2012-09-13

odometry, SICK laser scanning unit ( Lidar ), Inertial Measurement Unit (IMU) and ultrasonic distance measurement system (Figure 32). The Lidar , IMU...2010, July) GPS world. [Online]. http://www.gpsworld.com/tech-talk- blog/gnss-independent-navigation-solution-using-integrated- lidar -data-11378 [4...Milford, David McKinnon, Michael Warren, Gordon Wyeth, and Ben Upcroft, "Feature-based Visual Odometry and Featureless Place Recognition for SLAM in

Autonomous Navigation of Small Uavs Based on Vehicle Dynamic Model

NASA Astrophysics Data System (ADS)

Khaghani, M.; Skaloud, J.

2016-03-01

This paper presents a novel approach to autonomous navigation for small UAVs, in which the vehicle dynamic model (VDM) serves as the main process model within the navigation filter. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs on-board. This is achieved with no extra sensor added to the conventional INS/GNSS setup. This improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The VDM is also fed with the control input to the UAV, which is available within the control/autopilot system. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS navigation system during the autonomous phase, when satellite signals are not available due to physical obstruction or electromagnetic interference for example. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to inertial coasting. It means that during such scenario, the position-velocity-attitude (PVA) determination is sufficiently accurate to navigate the UAV to a home position without any signal that depends on vehicle environment.

Post-flight BET products for the 2nd discovery entry, STS-19 (51-A)

NASA Technical Reports Server (NTRS)

Kelly, G. M.; Mcconnell, J. G.; Heck, M. L.; Troutman, P. A.; Waters, L. A.; Findlay, J. T.

1985-01-01

The post-flight products for the second Discovery flight, STS-19 (51-A), are summarized. The inertial best estimate trajectory (BET), BT19D19/UN=169750N, was developed using spacecraft dynamic measurements from Inertial Measurement Unit 2 (IMU2) in conjunction with the best tracking coverage available for any of the earlier Shuttle entries. As a consequence of the latter, an anchor epoch was selected which conforms to an initial altitude of greater than a million feet. The Extended BET, ST19BET/UN=274885C, incorporated the previously mentioned inertial reconstructed state information and the Langley Atmospheric Information Retrieval System (LAIRS) atmosphere, ST19MET/UN=712662N, with some minor exceptions. Primary and back-up AEROBET reels are NK0165 and NK0201, respectively. This product was only developed over the lowermost 360 kft altitude range due to atmosphere problems but this relates to altitudes well above meaningful signal in the IMUs. Summary results generated from the AEROBET for this flight are presented with meaningful configuration and statistical comparisons from the previous thirteen flights. Modified maximum likelihood estimation (MMLE) files were generated based on IMU2 and the Rate Gyro Assembly/Accelerometer Assembly (RGA/AA), respectively. Appendices attached define spacecraft and physical constants utilized, show plots of the final tracking data residuals from the post-flight fit, list relevant parameters from the BET at a two second spacing, and retain for archival purpose all relevant input and output tapes and files generated.

Practical method for estimating road curvatures using onboard GPS and IMU equipment

NASA Astrophysics Data System (ADS)

Zamfir, S.; Drosescu, R.; Gaiginschi, R.

2016-08-01

This paper describes an experimental method to determine with high accuracy the curvature of a road segment, the turning radius of a car, and the discomfort level perceived by the passengers in the vehicle cabin when passing through a curve. For these experiments we used professional equipment provided with two GPS active antennas with 13 dB gain featuring non-contact 100 Hz speed and distance measurement, and a ten degree Inertial Measurement Unit (IMU) with dynamic orientation outputs. The same experimental measurements also usedthe low cost GPS equipment available on smartphones, domestic vehicle GPS devices, as well as an Arduino GPS shield in order to compare the results generated by professional equipment. The purpose of these experiments was also to establish if certain road curve sections were correctly executed in order to ensure the safety and comfort of passengers. Another use of the proposed method relates to the road accident reconstruction field, providing experts and forensics with an accurate method of measuring the roadway curvature at accident scenes or traffic events. The research and equipment described in this paper have been acquired and developed under a PhD studyand a European funded project won and elaborated by the authors.

A New Continuous Rotation IMU Alignment Algorithm Based on Stochastic Modeling for Cost Effective North-Finding Applications

PubMed Central

Li, Yun; Wu, Wenqi; Jiang, Qingan; Wang, Jinling

2016-01-01

Based on stochastic modeling of Coriolis vibration gyros by the Allan variance technique, this paper discusses Angle Random Walk (ARW), Rate Random Walk (RRW) and Markov process gyroscope noises which have significant impacts on the North-finding accuracy. A new continuous rotation alignment algorithm for a Coriolis vibration gyroscope Inertial Measurement Unit (IMU) is proposed in this paper, in which the extended observation equations are used for the Kalman filter to enhance the estimation of gyro drift errors, thus improving the north-finding accuracy. Theoretical and numerical comparisons between the proposed algorithm and the traditional ones are presented. The experimental results show that the new continuous rotation alignment algorithm using the extended observation equations in the Kalman filter is more efficient than the traditional two-position alignment method. Using Coriolis vibration gyros with bias instability of 0.1°/h, a north-finding accuracy of 0.1° (1σ) is achieved by the new continuous rotation alignment algorithm, compared with 0.6° (1σ) north-finding accuracy for the two-position alignment and 1° (1σ) for the fixed-position alignment. PMID:27983585

Stereo and IMU-Assisted Visual Odometry for Small Robots

NASA Technical Reports Server (NTRS)

2012-01-01

This software performs two functions: (1) taking stereo image pairs as input, it computes stereo disparity maps from them by cross-correlation to achieve 3D (three-dimensional) perception; (2) taking a sequence of stereo image pairs as input, it tracks features in the image sequence to estimate the motion of the cameras between successive image pairs. A real-time stereo vision system with IMU (inertial measurement unit)-assisted visual odometry was implemented on a single 750 MHz/520 MHz OMAP3530 SoC (system on chip) from TI (Texas Instruments). Frame rates of 46 fps (frames per second) were achieved at QVGA (Quarter Video Graphics Array i.e. 320 240), or 8 fps at VGA (Video Graphics Array 640 480) resolutions, while simultaneously tracking up to 200 features, taking full advantage of the OMAP3530's integer DSP (digital signal processor) and floating point ARM processors. This is a substantial advancement over previous work as the stereo implementation produces 146 Mde/s (millions of disparities evaluated per second) in 2.5W, yielding a stereo energy efficiency of 58.8 Mde/J, which is 3.75 better than prior DSP stereo while providing more functionality.

Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots

PubMed Central

Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

2013-01-01

This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments. PMID:24152933

Determination Method of Bridge Rotation Angle Response Using MEMS IMU.

PubMed

Sekiya, Hidehiko; Kinomoto, Takeshi; Miki, Chitoshi

2016-11-09

To implement steel bridge maintenance, especially that related to fatigue damage, it is important to monitor bridge deformations under traffic conditions. Bridges deform and rotate differently under traffic load conditions because their structures differ in terms of length and flexibility. Such monitoring enables the identification of the cause of stress concentrations that cause fatigue damage and the proposal of appropriate countermeasures. However, although bridge deformation monitoring requires observations of bridge angle response as well as the bridge displacement response, measuring the rotation angle response of a bridge subject to traffic loads is difficult. Theoretically, the rotation angle response can be calculated by integrating the angular velocity, but for field measurements of actual in-service bridges, estimating the necessary boundary conditions would be difficult due to traffic-induced vibration. To solve the problem, this paper proposes a method for determining the rotation angle response of an in-service bridge from its angular velocity, as measured by a inertial measurement unit (IMU). To verify our proposed method, field measurements were conducted using nine micro-electrical mechanical systems (MEMS) IMUs and two contact displacement gauges. The results showed that our proposed method provided high accuracy when compared to the reference responses calculated by the contact displacement gauges.

Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots.

PubMed

Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

2013-10-21

This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.

Tracking Control of Mobile Robots Localized via Chained Fusion of Discrete and Continuous Epipolar Geometry, IMU and Odometry.

PubMed

Tick, David; Satici, Aykut C; Shen, Jinglin; Gans, Nicholas

2013-08-01

This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.

Testing the Dependence of Airborne Gravity Results on Three Variables in Kinematic GPS Processing

NASA Astrophysics Data System (ADS)

Weil, C.; Diehl, T. M.

2011-12-01

The National Geodetic Survey's Gravity for the Redefinition of the American Vertical Datum (GRAV-D) program plans to collect airborne gravity data across the entire U.S. and its holdings over the next decade. The goal is to build a geoid accurate to 1-2 cm, for which the airborne gravity data is key. The first phase is underway, with > 13% of data collection completed in: parts of Alaska, parts of California, most of the Gulf Coast, Puerto Rico, and the Virgin Islands. Obtaining accurate airborne gravity survey results depends on the quality of the GPS/IMU position solution used in the processing. There are many factors that could have an influence on the positioning results. First, we will investigate how an increased data sampling rate for the GPS/IMU affects the position solution and accelerations derived from those positions. Second we will test the hypothesis that, for differential kinematic processing a better solution is obtained using both a base and a rover GPS unit that contain an additional rubidium clock that is reported to sync better with GPS time. Finally, we will look at a few different GPS+IMU processing methods available in commercial software. This includes comparing GPS-only solutions with loosely coupled GPS/IMU solutions from the Applanix POSAV-510 system and tightly coupled solutions with our newly-acquired NovAtel SPAN system (micro-IRS IMU). Differential solutions are compared with PPP (Precise Point Positioning) solutions along with multi-pass and advanced tropospheric corrections available with the NovAtel Inertial Explorer software. Based on preliminary research, we expect that the tightly-coupled solutions with either better troposphere and/or multi-pass solutions will provide superior position (and gravity) results.

Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface- and age-related differences in walking.

PubMed

Hu, B; Dixon, P C; Jacobs, J V; Dennerlein, J T; Schiffman, J M

2018-04-11

The aim of this study was to investigate if a machine learning algorithm utilizing triaxial accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could detect surface- and age-related differences in walking. Seventeen older (71.5 ± 4.2 years) and eighteen young (27.0 ± 4.7 years) healthy adults walked over flat and uneven brick surfaces wearing an inertial measurement unit (IMU) over the L5 vertebra. IMU data were binned into smaller data segments using 4-s sliding windows with 1-s step lengths. Ninety percent of the data were used as training inputs and the remaining ten percent were saved for testing. A deep learning network with long short-term memory units was used for training (fully supervised), prediction, and implementation. Four models were trained using the following inputs: all nine channels from every sensor in the IMU (fully trained model), accelerometer signals alone, gyroscope signals alone, and magnetometer signals alone. The fully trained models for surface and age outperformed all other models (area under the receiver operator curve, AUC = 0.97 and 0.96, respectively; p ≤ .045). The fully trained models for surface and age had high accuracy (96.3, 94.7%), precision (96.4, 95.2%), recall (96.3, 94.7%), and f1-score (96.3, 94.6%). These results demonstrate that processing the signals of a single IMU device with machine-learning algorithms enables the detection of surface conditions and age-group status from an individual's walking behavior which, with further learning, may be utilized to facilitate identifying and intervening on fall risk. Copyright © 2018 Elsevier Ltd. All rights reserved.

Patient-reported outcome measures versus inertial performance-based outcome measures: A prospective study in patients undergoing primary total knee arthroplasty.

PubMed

Bolink, S A A N; Grimm, B; Heyligers, I C

2015-12-01

Outcome assessment of total knee arthroplasty (TKA) by subjective patient reported outcome measures (PROMs) may not fully capture the functional (dis-)abilities of relevance. Objective performance-based outcome measures could provide distinct information. An ambulant inertial measurement unit (IMU) allows kinematic assessment of physical performance and could potentially be used for routine follow-up. To investigate the responsiveness of IMU measures in patients following TKA and compare outcomes with conventional PROMs. Patients with end stage knee OA (n=20, m/f=7/13; age=67.4 standard deviation 7.7 years) were measured preoperatively and one year postoperatively. IMU measures were derived during gait, sit-stand transfers and block step-up transfers. PROMs were assessed by using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Knee Society Score (KSS). Responsiveness was calculated by the effect size, correlations were calculated with Spearman's rho correlation coefficient. One year after TKA, patients performed significantly better at gait, sit-to-stand transfers and block step-up transfers. Measures of time and kinematic IMU measures demonstrated significant improvements postoperatively for each performance-based test. The largest improvement was found in block step-up transfers (effect size=0.56-1.20). WOMAC function score and KSS function score demonstrated moderate correlations (Spearman's rho=0.45-0.74) with some of the physical performance-based measures pre- and postoperatively. To characterize the changes in physical function after TKA, PROMs could be supplemented by performance-based measures, assessing function during different activities and allowing kinematic characterization with an ambulant IMU. Copyright © 2015 Elsevier B.V. All rights reserved.

Painting recognition with smartphones equipped with inertial measurement unit

NASA Astrophysics Data System (ADS)

Masiero, Andrea; Guarnieri, Alberto; Pirotti, Francesco; Vettore, Antonio

2015-06-01

Recently, several works have been proposed in the literature to take advantage of the diffusion of smartphones to improve people experience during museum visits. The rationale is that of substituting traditional written/audio guides with interactive electronic guides usable on a mobile phone. Augmented reality systems are usually considered to make the use of such electronic guides more effective for the user. The main goal of such augmented reality system (i.e. providing the user with the information of his/her interest) is usually achieved by properly executing the following three tasks: recognizing the object of interest to the user, retrieving the most relevant information about it, properly presenting the retrieved information. This paper focuses on the first task: we consider the problem of painting recognition by means of measure- ments provided by a smartphone. We assume that the user acquires one image of the painting of interest with the standard camera of the device. This image is compared with a set of reference images of the museum objects in order to recognize the object of interest to the user. Since comparing images taken in different conditions can lead to unsatisfactory recognition results, the acquired image is typically properly transformed in order to improve the results of the recognition system: first, the system estimates the homography between properly matched features in the two images. Then, the user image is transformed accordingly to the estimated homography. Finally, it is compared with the reference one. This work proposes a novel method to exploit inertial measurement unit (IMU) measurements to improve the system performance, in particular in terms of computational load reduction: IMU measurements are exploited to reduce both the computational burden required to estimate the transformation to be applied to the user image, and the number of reference images to be compared with it.

A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification

PubMed Central

Kumar, G. Ajay; Patil, Ashok Kumar; Patil, Rekha; Park, Seong Sill; Chai, Young Ho

2017-01-01

Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors. Considering the advantage of the typical geometric structure of indoor environments, the planar position of UAVs can be efficiently calculated from a point-to-point scan matching algorithm using measurements from a horizontally scanning primary LiDAR. The altitude of the UAV with respect to the floor can be estimated accurately using a vertically scanning secondary LiDAR scanner, which is mounted orthogonally to the primary LiDAR. Furthermore, a Kalman filter is used to derive the 3D position by fusing primary and secondary LiDAR data. Additionally, this work presents a novel method for its application in the real-time classification of a pipeline in an indoor map by integrating the proposed navigation approach. Classification of the pipeline is based on the pipe radius estimation considering the region of interest (ROI) and the typical angle. The ROI is selected by finding the nearest neighbors of the selected seed point in the pipeline point cloud, and the typical angle is estimated with the directional histogram. Experimental results are provided to determine the feasibility of the proposed navigation system and its integration with real-time application in industrial plant engineering. PMID:28574474

Design considerations for a suboptimal Kalman filter

NASA Astrophysics Data System (ADS)

Difilippo, D. J.

1995-06-01

In designing a suboptimal Kalman filter, the designer must decide how to simplify the system error model without causing the filter estimation errors to increase to unacceptable levels. Deletion of certain error states and decoupling of error state dynamics are the two principal model simplifications that are commonly used in suboptimal filter design. For the most part, the decisions as to which error states can be deleted or decoupled are based on the designer's understanding of the physics of the particular system. Consequently, the details of a suboptimal design are usually unique to the specific application. In this paper, the process of designing a suboptimal Kalman filter is illustrated for the case of an airborne transfer-of-alignment (TOA) system used for synthetic aperture radar (SAR) motion compensation. In this application, the filter must continuously transfer the alignment of an onboard Doppler-damped master inertial navigation system (INS) to a strapdown navigator that processes information from a less accurate inertial measurement unit (IMU) mounted on the radar antenna. The IMU is used to measure spurious antenna motion during the SAR imaging interval, so that compensating phase corrections can be computed and applied to the radar returns, thereby presenting image degradation that would otherwise result from such motions. The principles of SAR are described in many references, for instance. The primary function of the TOA Kalman filter in a SAR motion compensation system is to control strapdown navigator attitude errors, and to a less degree, velocity and heading errors. Unlike a classical navigation application, absolute positional accuracy is not important. The motion compensation requirements for SAR imaging are discussed in some detail. This TOA application is particularly appropriate as a vehicle for discussing suboptimal filter design, because the system contains features that can be exploited to allow both deletion and decoupling of error states. In Section 2, a high-level background description of a SAR motion compensation system that incorporates a TOA Kalman filter is given. The optimal TOA filter design is presented in Section 3 with some simulation results to indicate potential filter performance. In Section 4, the suboptimal Kalman filter configuration is derived. Simulation results are also shown in this section to allow comparision between suboptimal and optimal filter performances. Conclusions are contained in Section 5.

University of Pennsylvania MAGIC 2010 Final Report

DTIC Science & Technology

2011-01-10

and mapping ( SLAM ) techniques are employed to build a local map of the environment surrounding the robot. Readings from the two complementary LIDAR sen...IMU, LIDAR , Cameras Localization Disrupter UGV Local Navigation Sensors: GPS, IMU, LIDAR , Cameras Laser Control Localization Task Planner Strategy/Plan...various components shown in Figure 2. This is comprised of the following subsystems: • Sensor UGV: Mobile UGVs with LIDAR and camera sensors, GPS, and

A Personal Inertial Navigation System Based on Multiple Distributed, Nine-Degrees-Of-Freedom, Inertial Measurement Units

DTIC Science & Technology

2016-12-01

based complementary filter developed at the Naval Postgraduate School, is developed. The performance of a consumer-grade nine-degrees-of-freedom IMU...measurement unit, complementary filter , gait phase detection, zero velocity update, MEMS, IMU, AHRS, GPS denied, distributed sensor, virtual sensor...algorithm and quaternion-based complementary filter developed at the Naval Postgraduate School, is developed. The performance of a consumer-grade nine

Development of a 3-D Pen Input Device

DTIC Science & Technology

2008-09-01

of a unistroke which can be written on any surface or in the air while correcting integration errors from the...navigation frame of a unistroke, which can be written on any surface or in the air while correcting integration errors from the measurements of the IMU... be written on any surface or in the air while correcting integration errors from the measurements of the IMU (Inertial Measurement Unit) of the

Development of a Novel, Two-Processor Architecture for a Small UAV Autopilot System,

DTIC Science & Technology

2006-07-26

is, and the control laws the user implements to control it. The flight control system board will contain the processor selected for this system...Unit (IMU). The IMU contains solid-state gyros and accelerometers and uses these to determine the attitude of the UAV within the three dimensions of...multiple-UAV swarming for combat support operations. The mission processor board will contain the processor selected to execute the mission

Utilizing Glove-Based Gestures and a Tactile Vest Display for Covert Communications and Robot Control

DTIC Science & Technology

2014-06-01

transmitted from a controller mechanism that contains inertial measurement unit ( IMU ) sensors to sense rotation and acceleration of movement. Earlier...assets, and standard hand signal commands can be presented to human team members via a variety of modalities. IMU sensor technologies placed on the body...obstacle event (e.g., climbing, crawling, combat roll , running) and between obstacles (i.e., walking). The following analyses are for each task

A Motion Tracking and Sensor Fusion Module for Medical Simulation.

PubMed

Shen, Yunhe; Wu, Fan; Tseng, Kuo-Shih; Ye, Ding; Raymond, John; Konety, Badrinath; Sweet, Robert

2016-01-01

Here we introduce a motion tracking or navigation module for medical simulation systems. Our main contribution is a sensor fusion method for proximity or distance sensors integrated with inertial measurement unit (IMU). Since IMU rotation tracking has been widely studied, we focus on the position or trajectory tracking of the instrument moving freely within a given boundary. In our experiments, we have found that this module reliably tracks instrument motion.

Autonomous orbital navigation using Kepler's equation

NASA Technical Reports Server (NTRS)

Boltz, F. W.

1974-01-01

A simple method of determining the six elements of elliptic satellite orbits has been developed for use aboard manned and unmanned spacecraft orbiting the earth, moon, or any planet. The system requires the use of a horizon sensor or other device for determining the local vertical, a precision clock or timing device, and Apollo-type navigation equipment including an inertial measurement unit (IMU), a digital computer, and a coupling data unit. The three elements defining the in-plane motion are obtained from simultaneous measurements of central angle traversed around the planet and elapsed flight time using a linearization of Kepler's equation about a reference orbit. It is shown how Kalman filter theory may also be used to determine the in-plane orbital elements. The three elements defining the orbit orientation are obtained from position angles in celestial coordinates derived from the IMU with the spacecraft vertically oriented after alignment of the IMU to a known inertial coordinate frame.

Proof of concept for turbulence measurements with the RPAS SUMO during the BLLAST campaign

NASA Astrophysics Data System (ADS)

Båserud, Line; Reuder, Joachim; Jonassen, Marius O.; Kral, Stephan T.; Paskyabi, Mostafa B.; Lothon, Marie

2016-10-01

The micro-RPAS (remotely piloted aircraft system) SUMO (Small Unmanned Meteorological Observer) equipped with a five-hole-probe (5HP) system for turbulent flow measurements was operated in 49 flight missions during the BLLAST (Boundary-Layer Late Afternoon and Sunset Turbulence) field campaign in 2011. Based on data sets from these flights, we investigate the potential and limitations of airborne velocity variance and TKE (turbulent kinetic energy) estimations by an RPAS with a take-off weight below 1 kg. The integration of the turbulence probe in the SUMO system was still in an early prototype stage during this campaign, and therefore extensive post-processing of the data was required. In order to be able to calculate the three-dimensional wind vector, flow probe measurements were first synchronized with the autopilot's attitude and velocity data. Clearly visible oscillations were detected in the resulting vertical velocity, w, even after correcting for the aircraft motion. The oscillations in w were identified as the result of an internal time shift between the inertial measurement unit (IMU) and the GPS sensors, leading to insufficient motion correction, especially for the vertical wind component, causing large values of σw. Shifting the IMU 1-1.5 s forward in time with respect to the GPS yields a minimum for σw and maximum covariance between the IMU pitch angle and the GPS climb angle. The SUMO data show a good agreement to sonic anemometer data from a 60 m tower for σu, but show slightly higher values for σv and σw. Vertical TKE profiles, obtained from consecutive flight legs at different altitudes, show reasonable results, both with respect to the overall TKE level and the temporal variation. A thorough discussion of the methods used and the identified uncertainties and limitations of the system for turbulence measurements is included and should help the developers and users of other systems with similar problems.

Intent of Study on the Use of a Dual Airborne Laser Scanner (ALS) in Conjunction with a Tactical Grade Inertial Measurement Unit (IMU) for Unmanned Aerial Vehicle (UAV) Navigation and Mapping in Unknown, Non-Global Positioning System (GPS), Environments

DTIC Science & Technology

2006-08-05

ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) AF Office of Scientific h Researc 875 N. Randolph St. Room 3112 11. SPONSOR/MONITOR’S REPORT...the process is often time-consuming and expensive. As the IMU market is experiencing a migration trend towards Micro Electro-Mechanical System (MEMS

Micro Autonomous Systems Research: A Methodology for Quantitative Technology Assessment and Prototyping of Unmanned Vehicles

DTIC Science & Technology

2014-06-06

Structure Flex Joints 6828 68% Power Primary: Lithium-Ion 7530 75% Secondary: Fuel Cells (miniature) 8843 88% Sensors IMU /LIDAR 7713 77...mission requirements taken into account; the payload included a LIDAR, sonar, and an IMU . Moreover, the focus moved to the integration of the entire...negligible for any pitch or roll angle less than 15 degrees. The small deflection assumption utilized instead seeks to minimize momentum generation. To

Improved motor control method with measurements of fiber optics gyro (FOG) for dual-axis rotational inertial navigation system (RINS).

PubMed

Song, Tianxiao; Wang, Xueyun; Liang, Wenwei; Xing, Li

2018-05-14

Benefiting from frame structure, RINS can improve the navigation accuracy by modulating the inertial sensor errors with proper rotation scheme. In the traditional motor control method, the measurements of the photoelectric encoder are always adopted to drive inertial measurement unit (IMU) to rotate. However, when carrier conducts heading motion, the inertial sensor errors may no longer be zero-mean in navigation coordinate. Meanwhile, some high-speed carriers like aircraft need to roll a certain angle to balance the centrifugal force during the heading motion, which may result in non-negligible coupling errors, caused by the FOG installation errors and scale factor errors. Moreover, the error parameters of FOG are susceptible to the temperature and magnetic field, and the pre-calibration is a time-consuming process which is difficult to completely suppress the FOG-related errors. In this paper, an improved motor control method with the measurements of FOG is proposed to address these problems, with which the outer frame can insulate the carrier's roll motion and the inner frame can simultaneously achieve the rotary modulation on the basis of insulating the heading motion. The results of turntable experiments indicate that the navigation performance of dual-axis RINS has been significantly improved over the traditional method, which could still be maintained even with large FOG installation errors and scale factor errors, proving that the proposed method can relax the requirements for the accuracy of FOG-related errors.

Comparison of a standalone consumer grade smartphone with a specialist inertial measurement unit for quantification of movement symmetry in the trotting horse.

PubMed

Pfau, T; Weller, R

2017-01-01

Equine inertial measurement unit (IMU) gait analysis has gained in popularity for use in horses. Similar transducers are now found in consumer grade smartphones. However, to date there are no scientific data evaluating their use for assessment of movement (a)symmetry in the horse. To establish limits of agreement (LoA, mean difference ±2 s.d.) between a validated specialist IMU system and IMU data collected with a consumer grade smartphone for quantification of movement symmetry and range of motion (ROM) of pelvic movement in the trotting horse. Method comparison study based on quantitative gait data. Twenty horses were equipped with a specialist IMU (MTw, Xsens) and a consumer grade smartphone (Apple iPhone6), both securely attached immediately in front of one another in the midline over the sacrum. Horses were trotted in-hand and lunged on both reins on a soft arena surface. Median values for movement symmetry and ROM were determined over a series of strides for each exercise condition. Data collection was repeated in 6 horses to determine the effect of mediolateral sensor positioning on outcome parameters. Valid data from 17 horses resulted in LoA values of -3.7 ± 9.2 mm for MinDiff (difference between left and right hind mid stance), -0.6 ± 6.0 mm for MaxDiff (difference between left and right hind propulsion) and -0.8 ± 7.4 mm for ROM across horses and exercises. LoAs were narrower for straight line exercise and the negative bias was considerably reduced when moving the smartphone to the right of the midline. The consumer grade smartphone provided meaningful gait data in horses: LoAs in particular for in-hand exercise and when adjusting the mediolateral positioning are similar to published asymmetry thresholds. Owing to the sensitivity to mediolateral positioning, particular care should be taken when placing an IMU over the midline of the horse. © 2015 EVJ Ltd.

Determination Method of Bridge Rotation Angle Response Using MEMS IMU

PubMed Central

Sekiya, Hidehiko; Kinomoto, Takeshi; Miki, Chitoshi

2016-01-01

To implement steel bridge maintenance, especially that related to fatigue damage, it is important to monitor bridge deformations under traffic conditions. Bridges deform and rotate differently under traffic load conditions because their structures differ in terms of length and flexibility. Such monitoring enables the identification of the cause of stress concentrations that cause fatigue damage and the proposal of appropriate countermeasures. However, although bridge deformation monitoring requires observations of bridge angle response as well as the bridge displacement response, measuring the rotation angle response of a bridge subject to traffic loads is difficult. Theoretically, the rotation angle response can be calculated by integrating the angular velocity, but for field measurements of actual in-service bridges, estimating the necessary boundary conditions would be difficult due to traffic-induced vibration. To solve the problem, this paper proposes a method for determining the rotation angle response of an in-service bridge from its angular velocity, as measured by a inertial measurement unit (IMU). To verify our proposed method, field measurements were conducted using nine micro-electrical mechanical systems (MEMS) IMUs and two contact displacement gauges. The results showed that our proposed method provided high accuracy when compared to the reference responses calculated by the contact displacement gauges. PMID:27834871

Force Method Optimization II. Volume II. User’s Manual.

DTIC Science & Technology

1982-11-01

column labels ICC Iteration counter ICHECK Vector for intermediate output, identifying the convergence status of unknowns, 0 = has not converged, 1...NDC,NW,SIG,ND,IDYN,UP,LOW,IAREA,IMU, ALAMBDW,WARAY,NSN.,NDCNL,NXNL,NWNL,NDNNL, NSENLIRST, ICHECK ,WDYN,PR1,MAXIT,WS,ARAY) 8. Input Tapes: None 9. Output...IMUSL,IMUDL,IAREA, IMU, P,NDN,UP,LOW,IX,IDYN,NW,IMUXL,IMUWL,ICC,ALAMBD, AMIN,WT,KL,NODE,ND,COND, IDEL .NSNL,NDCNL, NXNL, NWNL, ICHECK ,WDYN,PRI,WS,MAXT

Manual Optical Attitude Re-initialization of a Crew Vehicle in Space Using Bias Corrected Gyro Data

NASA Astrophysics Data System (ADS)

Gioia, Christopher J.

NASA and other space agencies have shown interest in sending humans on missions beyond low Earth orbit. Proposed is an algorithm that estimates the attitude of a manned spacecraft using measured line-of-sight (LOS) vectors to stars and gyroscope measurements. The Manual Optical Attitude Reinitialization (MOAR) algorithm and corresponding device draw inspiration from existing technology from the Gemini, Apollo and Space Shuttle programs. The improvement over these devices is the capability of estimating gyro bias completely independent from re-initializing attitude. It may be applied to the lost-in-space problem, where the spacecraft's attitude is unknown. In this work, a model was constructed that simulated gyro data using the Farrenkopf gyro model, and LOS measurements from a spotting scope were then computed from it. Using these simulated measurements, gyro bias was estimated by comparing measured interior star angles to those derived from a star catalog and then minimizing the difference using an optimization technique. Several optimization techniques were analyzed, and it was determined that the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm performed the best when combined with a grid search technique. Once estimated, the gyro bias was removed and attitude was determined by solving the Wahba Problem via the Singular Value Decomposition (SVD) approach. Several Monte Carlo simulations were performed that looked at different operating conditions for the MOAR algorithm. These included the effects of bias instability, using different constellations for data collection, sampling star measurements in different orders, and varying the time between measurements. A common method of estimating gyro bias and attitude in a Multiplicative Extended Kalman Filter (MEKF) was also explored and disproven for use in the MOAR algorithm. A prototype was also constructed to validate the proposed concepts. It was built using a simple spotting scope, MEMS grade IMU, and a Raspberry Pi computer. It was mounted on a tripod, used to target stars with the scope and measure the rotation between them using the IMU. The raw measurements were then post-processed using the MOAR algorithm, and attitude estimates were determined. Two different constellations---the Big Dipper and Orion---were used for experimental data collection. The results suggest that the novel method of estimating gyro bias independently from attitude in this document is credible for use onboard a spacecraft.

Non-verbal communication through sensor fusion

NASA Astrophysics Data System (ADS)

Tairych, Andreas; Xu, Daniel; O'Brien, Benjamin M.; Anderson, Iain A.

2016-04-01

When we communicate face to face, we subconsciously engage our whole body to convey our message. In telecommunication, e.g. during phone calls, this powerful information channel cannot be used. Capturing nonverbal information from body motion and transmitting it to the receiver parallel to speech would make these conversations feel much more natural. This requires a sensing device that is capable of capturing different types of movements, such as the flexion and extension of joints, and the rotation of limbs. In a first embodiment, we developed a sensing glove that is used to control a computer game. Capacitive dielectric elastomer (DE) sensors measure finger positions, and an inertial measurement unit (IMU) detects hand roll. These two sensor technologies complement each other, with the IMU allowing the player to move an avatar through a three-dimensional maze, and the DE sensors detecting finger flexion to fire weapons or open doors. After demonstrating the potential of sensor fusion in human-computer interaction, we take this concept to the next level and apply it in nonverbal communication between humans. The current fingerspelling glove prototype uses capacitive DE sensors to detect finger gestures performed by the sending person. These gestures are mapped to corresponding messages and transmitted wirelessly to another person. A concept for integrating an IMU into this system is presented. The fusion of the DE sensor and the IMU combines the strengths of both sensor types, and therefore enables very comprehensive body motion sensing, which makes a large repertoire of gestures available to nonverbal communication over distances.

Graph SLAM correction for single scanner MLS forest data under boreal forest canopy

NASA Astrophysics Data System (ADS)

Kukko, Antero; Kaijaluoto, Risto; Kaartinen, Harri; Lehtola, Ville V.; Jaakkola, Anttoni; Hyyppä, Juha

2017-10-01

Mobile laser scanning (MLS) provides kinematic means to collect three dimensional data from surroundings for various mapping and environmental analysis purposes. Vehicle based MLS has been used for road and urban asset surveys for about a decade. The equipment to derive the trajectory information for the point cloud generation from the laser data is almost without exception based on GNSS-IMU (Global Navigation Satellite System - Inertial Measurement Unit) technique. That is because of the GNSS ability to maintain global accuracy, and IMU to produce the attitude information needed to orientate the laser scanning and imaging sensor data. However, there are known challenges in maintaining accurate positioning when GNSS signal is weak or even absent over long periods of time. The duration of the signal loss affects the severity of degradation of the positioning solution depending on the quality/performance level of the IMU in use. The situation could be improved to a certain extent with higher performance IMUs, but increasing system expenses make such approach unsustainable in general. Another way to tackle the problem is to attach additional sensors to the system to overcome the degrading position accuracy: such that observe features from the environment to solve for short term system movements accurately enough to prevent the IMU solution to drift. This results in more complex system integration with need for more calibration and synchronization of multiple sensors into an operational approach. In this paper we study operation of an ATV (All -terrain vehicle) mounted, GNSS-IMU based single scanner MLS system in boreal forest conditions. The data generated by RoamerR2 system is targeted for generating 3D terrain and tree maps for optimizing harvester operations and forest inventory purposes at individual tree level. We investigate a process-flow and propose a graph optimization based method which uses data from a single scanner MLS for correcting the post-processed GNSS-IMU trajectory for positional drift under mature boreal forest canopy conditions. The result shows that we can improve the internal conformity of the data significantly from 0.7 m to 1 cm based on tree stem feature location data. When the optimization result is compared to reference at plot level we reach down to 6 cm mean error in absolute tree stem locations. The approach can be generalized to any MLS point cloud data, and provides as such a remarkable contribution to harness MLS for practical forestry and high precision terrain and structural modeling in GNSS obstructed environments.

A comparison of the performance of two types of inertial systems for strapdown airborne gravimetry

NASA Astrophysics Data System (ADS)

Deurloo, R. A.; Martin, J.; Bastos, M. L.; Becker, M. H.

2012-12-01

Over the past two decades so-called strapdown airborne gravimetry systems have proven to have the potential to compete with more traditional measurement systems such as modified spring gravimeters (e.g. LaCoste & Romberg Air-Sea gravimeters). Strapdown gravimetry systems rely on the integration of high-accuracy data from a GNSS (Global Navigation Satellite System) receiver and from a strapdown IMU (Inertial Measurement Unit). These GNSS/IMU integrated systems have the advantage of being less expensive and more compact, while being easier to use and install than spring gravimeters, which tend to be bulky and require specialized human resources for its operation. In the scope of a research project developed through the collaboration of the University of Porto and the Portuguese Air Force (PAF), an airborne survey was recently performed over the middle and southern area of Continental Portugal using a CASA C212 aircraft. The goal of this survey was to acquire data to assess the performance of different GNSS/IMU systems and associated processing approaches to determine the gravity field and evaluate their potential and effectiveness for airborne gravimetry using different types of airborne platforms, including UAVs (Unmanned Airborne Vehicles). Among the systems on board were a medium-quality (tactical grade) IMU with fiber-optic gyros (FOG), a Litton LN-200, and a high-quality (navigation grade) IMU with ring-laser gyros (RLG), an iMAR RHQ-1003, which are the focus of the present comparison. The advantage of using a strapdown airborne gravimetry system with high-quality inertial sensor is that it allows the complete gravity vector to be determined from the triads of accelerometers and gyros in the IMU (vector gravimetry). On the other hand a medium-quality inertial system is limited to determining only the magnitude of the gravity vector (scalar gravimetry). The limited quality of the gyros of the medium-quality inertial systems does not allow the horizontal components of the gravity vector to be determined. In spite of that, this type of system has been shown to still deliver very useful results in the range of a few mGal for resolutions below 10km. In this work we describe the setup used for our airborne test and we present a comparison and analysis of the performance of the medium- and high-quality inertial systems. This includes an analysis of the results of overlapping flight lines obtained with both systems. Considerations about the suitability of each of the systems for different types of applications are also discussed.

Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

PubMed

Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

2018-05-01

High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach

PubMed Central

Girrbach, Fabian; Hol, Jeroen D.; Bellusci, Giovanni; Diehl, Moritz

2017-01-01

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem. PMID:28534857

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach.

PubMed

Girrbach, Fabian; Hol, Jeroen D; Bellusci, Giovanni; Diehl, Moritz

2017-05-19

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem.

Wavelet based automated postural event detection and activity classification with single imu - biomed 2013.

PubMed

Lockhart, Thurmon E; Soangra, Rahul; Zhang, Jian; Wu, Xuefan

2013-01-01

Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person’s activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient’s home. In order to provide a low-cost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment – TEMPO (Technology Enabled Medical Precision Observation). Using this IMU system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection and classification algorithm using denoised signals from single wireless IMU placed at sternum. The algorithm was further validated and verified with motion capture system in laboratory environment. Wavelet denoising highlighted postural events and transition durations that further provided clinical information on postural control and motor coordination. The presented method can be applied in real life ambulatory monitoring approaches for assessing condition of elderly.

Study of the Navigation Method for a Snake Robot Based on the Kinematics Model with MEMS IMU.

PubMed

Zhao, Xu; Dou, Lihua; Su, Zhong; Liu, Ning

2018-03-16

A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot's motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot's motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot's navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots.

Georeferencing in Gnss-Challenged Environment: Integrating Uwb and Imu Technologies

NASA Astrophysics Data System (ADS)

Toth, C. K.; Koppanyi, Z.; Navratil, V.; Grejner-Brzezinska, D.

2017-05-01

Acquiring geospatial data in GNSS compromised environments remains a problem in mapping and positioning in general. Urban canyons, heavily vegetated areas, indoor environments represent different levels of GNSS signal availability from weak to no signal reception. Even outdoors, with multiple GNSS systems, with an ever-increasing number of satellites, there are many situations with limited or no access to GNSS signals. Independent navigation sensors, such as IMU can provide high-data rate information but their initial accuracy degrades quickly, as the measurement data drift over time unless positioning fixes are provided from another source. At The Ohio State University's Satellite Positioning and Inertial Navigation (SPIN) Laboratory, as one feasible solution, Ultra- Wideband (UWB) radio units are used to aid positioning and navigating in GNSS compromised environments, including indoor and outdoor scenarios. Here we report about experiences obtained with georeferencing a pushcart based sensor system under canopied areas. The positioning system is based on UWB and IMU sensor integration, and provides sensor platform orientation for an electromagnetic inference (EMI) sensor. Performance evaluation results are provided for various test scenarios, confirming acceptable results for applications where high accuracy is not required.

Testing of the high accuracy inertial navigation system in the Shuttle Avionics Integration Lab

NASA Technical Reports Server (NTRS)

Strachan, Russell L.; Evans, James M.

1991-01-01

The description, results, and interpretation is presented of comparison testing between the High Accuracy Inertial Navigation System (HAINS) and KT-70 Inertial Measurement Unit (IMU). The objective was to show the HAINS can replace the KT-70 IMU in the space shuttle Orbiter, both singularly and totally. This testing was performed in the Guidance, Navigation, and Control Test Station (GTS) of the Shuttle Avionics Integration Lab (SAIL). A variety of differences between the two instruments are explained. Four, 5 day test sessions were conducted varying the number and slot position of the HAINS and KT-70 IMUs. The various steps in the calibration and alignment procedure are explained. Results and their interpretation are presented. The HAINS displayed a high level of performance accuracy previously unseen with the KT-70 IMU. The most significant improvement of the performance came in the Tuned Inertial/Extended Launch Hold tests. The HAINS exceeded the 4 hr specification requirement. The results obtained from the SAIL tests were generally well beyond the requirements of the procurement specification.

Time-frequency analysis of human motion during rhythmic exercises.

PubMed

Omkar, S N; Vyas, Khushi; Vikranth, H N

2011-01-01

Biomechanical signals due to human movements during exercise are represented in time-frequency domain using Wigner Distribution Function (WDF). Analysis based on WDF reveals instantaneous spectral and power changes during a rhythmic exercise. Investigations were carried out on 11 healthy subjects who performed 5 cycles of sun salutation, with a body-mounted Inertial Measurement Unit (IMU) as a motion sensor. Variance of Instantaneous Frequency (I.F) and Instantaneous Power (I.P) for performance analysis of the subject is estimated using one-way ANOVA model. Results reveal that joint Time-Frequency analysis of biomechanical signals during motion facilitates a better understanding of grace and consistency during rhythmic exercise.

SmallSat Precision Navigation with Low-Cost MEMS IMU Swarms

NASA Technical Reports Server (NTRS)

Christian, John; Bishop, Robert; Martinez, Andres; Petro, Andrew

2015-01-01

The continued advancement of small satellite-based science missions requires the solution to a number of important technical challenges. Of particular note is that small satellite missions are characterized by tight constraints on cost, mass, power, and volume that make them unable to fly the high-quality Inertial Measurement Units (IMUs) required for orbital missions demanding precise orientation and positioning. Instead, small satellite missions typically fly low-cost Micro-Electro-Mechanical System (MEMS) IMUs. Unfortunately, the performance characteristics of these MEMS IMUs make them ineffectual in many spaceflight applications when employed in a single IMU system configuration.

Evaluation of HRI Payloads for Rapid Precision Target Localization to Provide Information to the Tactical Warfighter

DTIC Science & Technology

2011-09-01

supply for the IMU  switching 5, 12V ATX power supply for the computer and hard drive  An L1/L2 active antenna on small back plane  USB to serial...switching 5, 12V ATX power supply for the computer and hard drive Figure 4. UAS Target Location Technology for Ground Based Observers (TLGBO...15V power supply for the IMU H. switching 5, 12V ATX power supply for the computer & hard drive I. An L1/L2 active antenna on a small back

NA-241_Quarterly Report_SBLibby - 12.31.2017_v2

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

Libby, Stephen B.

This is an evaluation of candidate navigation solutions for GPS free inspection tools that can be used in tours of large building interiors. In principle, COTS portable inertial motion unit (IMU) sensors with satisfactory accuracy, SWAP (size, weight, power), low error, and bias drift can provide sufficiently accurate dead reckoning navigation in a large building in the absence of GPS. To explore this assumption, the capabilities of representative IMU navigation sensors to meet these requirements will be evaluated, starting with a market survey, and then carrying out a basic analysis of these sensors using LLNL’s navigation codes.

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

INS/EKF-based stride length, height and direction intent detection for walking assistance robots.

PubMed

Brescianini, Dario; Jung, Jun-Young; Jang, In-Hun; Park, Hyun Sub; Riener, Robert

2011-01-01

We propose an algorithm used to obtain the information on stride length, height difference, and direction based on user's intent during walking. For exoskeleton robots used to assist paraplegic patients' walking, this information is used to generate gait patterns by themselves in on-line. To obtain this information, we attach an inertial measurement unit(IMU) on crutches and apply an extended kalman filter-based error correction method to reduce the phenomena of drift due to bias of the IMU. The proposed method is verifed in real walking scenarios including walking, climbing up-stairs, and changing direction of walking with normal. © 2011 IEEE

Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

PubMed

Whiteside, David; Cant, Olivia; Connolly, Molly; Reid, Machar

2017-10-01

Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not possible given players' heavy travel schedules. To develop an automated stroke-classification system to help quantify hitting load in tennis. Nineteen athletes wore an inertial measurement unit (IMU) on their wrist during 66 video-recorded training sessions. Video footage was manually notated such that known shot type (serve, rally forehand, slice forehand, forehand volley, rally backhand, slice backhand, backhand volley, smash, or false positive) was associated with the corresponding IMU data for 28,582 shots. Six types of machine-learning models were then constructed to classify true shot type from the IMU signals. Across 10-fold cross-validation, a cubic-kernel support vector machine classified binned shots (overhead, forehand, or backhand) with an accuracy of 97.4%. A second cubic-kernel support vector machine achieved 93.2% accuracy when classifying all 9 shot types. With a view to monitoring external load, the combination of miniature inertial sensors and machine learning offers a practical and automated method of quantifying shot counts and discriminating shot types in elite tennis players.

A Wearable Inertial Measurement Unit for Long-Term Monitoring in the Dependency Care Area

PubMed Central

Rodríguez-Martín, Daniel; Pérez-López, Carlos; Samà, Albert; Cabestany, Joan; Català, Andreu

2013-01-01

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A μSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson's disease symptoms, in gait analysis, and in a fall detection system. PMID:24145917

A wearable inertial measurement unit for long-term monitoring in the dependency care area.

PubMed

Rodríguez-Martín, Daniel; Pérez-López, Carlos; Samà, Albert; Cabestany, Joan; Català, Andreu

2013-10-18

Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A µSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson's disease symptoms, in gait analysis, and in a fall detection system.

Mars Entry Atmospheric Data System Modelling and Algorithm Development

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Beck, Roger E.; OKeefe, Stephen A.; Siemers, Paul; White, Brady; Engelund, Walter C.; Munk, Michelle M.

2009-01-01

The Mars Entry Atmospheric Data System (MEADS) is being developed as part of the Mars Science Laboratory (MSL), Entry, Descent, and Landing Instrumentation (MEDLI) project. The MEADS project involves installing an array of seven pressure transducers linked to ports on the MSL forebody to record the surface pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the total pressure, dynamic pressure, Mach number, angle of attack, and angle of sideslip. Secondary objectives are to estimate atmospheric winds by coupling the pressure measurements with the on-board Inertial Measurement Unit (IMU) data. This paper provides details of the algorithm development, MEADS system performance based on calibration, and uncertainty analysis for the aerodynamic and atmospheric quantities of interest. The work presented here is part of the MEDLI performance pre-flight validation and will culminate with processing flight data after Mars entry in 2012.

Analysis and design of second-order sliding-mode algorithms for quadrotor roll and pitch estimation.

PubMed

Chang, Jing; Cieslak, Jérôme; Dávila, Jorge; Zolghadri, Ali; Zhou, Jun

2017-11-01

The problem addressed in this paper is that of quadrotor roll and pitch estimation without any assumption about the knowledge of perturbation bounds when Inertial Measurement Units (IMU) data or position measurements are available. A Smooth Sliding Mode (SSM) algorithm is first designed to provide reliable estimation under a smooth disturbance assumption. This assumption is next relaxed with the second proposed Adaptive Sliding Mode (ASM) algorithm that deals with disturbances of unknown bounds. In addition, the analysis of the observers are extended to the case where measurements are corrupted by bias and noise. The gains of the proposed algorithms were deduced from the Lyapunov function. Furthermore, some useful guidelines are provided for the selection of the observer turning parameters. The performance of these two approaches is evaluated using a nonlinear simulation model and considering either accelerometer or position measurements. The simulation results demonstrate the benefits of the proposed solutions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Human motion characteristics in relation to feeling familiar or frightened during an announced short interaction with a proactive humanoid.

PubMed

Baddoura, Ritta; Venture, Gentiane

2014-01-01

During an unannounced encounter between two humans and a proactive humanoid (NAO, Aldebaran Robotics), we study the dependencies between the human partners' affective experience (measured via the answers to a questionnaire) particularly regarding feeling familiar and feeling frightened, and their arm and head motion [frequency and smoothness using Inertial Measurement Units (IMU)]. NAO starts and ends its interaction with its partners by non-verbally greeting them hello (bowing) and goodbye (moving its arm). The robot is invested with a real and useful task to perform: handing each participant an envelope containing a questionnaire they need to answer. NAO's behavior varies from one partner to the other (Smooth with X vs. Resisting with Y). The results show high positive correlations between feeling familiar while interacting with the robot and: the frequency and smoothness of the human arm movement when waving back goodbye, as well as the smoothness of the head during the whole encounter. Results also show a negative dependency between feeling frightened and the frequency of the human arm movement when waving back goodbye. The principal component analysis (PCA) suggests that, in regards to the various motion measures examined in this paper, the head smoothness and the goodbye gesture frequency are the most reliable measures when it comes to considering the familiar experienced by the participants. The PCA also points out the irrelevance of the goodbye motion frequency when investigating the participants' experience of fear in its relation to their motion characteristics. The results are discussed in light of the major findings of studies on body movements and postures accompanying specific emotions.

Human motion characteristics in relation to feeling familiar or frightened during an announced short interaction with a proactive humanoid

PubMed Central

Baddoura, Ritta; Venture, Gentiane

2014-01-01

During an unannounced encounter between two humans and a proactive humanoid (NAO, Aldebaran Robotics), we study the dependencies between the human partners' affective experience (measured via the answers to a questionnaire) particularly regarding feeling familiar and feeling frightened, and their arm and head motion [frequency and smoothness using Inertial Measurement Units (IMU)]. NAO starts and ends its interaction with its partners by non-verbally greeting them hello (bowing) and goodbye (moving its arm). The robot is invested with a real and useful task to perform: handing each participant an envelope containing a questionnaire they need to answer. NAO's behavior varies from one partner to the other (Smooth with X vs. Resisting with Y). The results show high positive correlations between feeling familiar while interacting with the robot and: the frequency and smoothness of the human arm movement when waving back goodbye, as well as the smoothness of the head during the whole encounter. Results also show a negative dependency between feeling frightened and the frequency of the human arm movement when waving back goodbye. The principal component analysis (PCA) suggests that, in regards to the various motion measures examined in this paper, the head smoothness and the goodbye gesture frequency are the most reliable measures when it comes to considering the familiar experienced by the participants. The PCA also points out the irrelevance of the goodbye motion frequency when investigating the participants' experience of fear in its relation to their motion characteristics. The results are discussed in light of the major findings of studies on body movements and postures accompanying specific emotions. PMID:24688466

Online Kinematic and Dynamic-State Estimation for Constrained Multibody Systems Based on IMUs

PubMed Central

Torres-Moreno, José Luis; Blanco-Claraco, José Luis; Giménez-Fernández, Antonio; Sanjurjo, Emilio; Naya, Miguel Ángel

2016-01-01

This article addresses the problems of online estimations of kinematic and dynamic states of a mechanism from a sequence of noisy measurements. In particular, we focus on a planar four-bar linkage equipped with inertial measurement units (IMUs). Firstly, we describe how the position, velocity, and acceleration of all parts of the mechanism can be derived from IMU signals by means of multibody kinematics. Next, we propose the novel idea of integrating the generic multibody dynamic equations into two variants of Kalman filtering, i.e., the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), in a way that enables us to handle closed-loop, constrained mechanisms, whose state space variables are not independent and would normally prevent the direct use of such estimators. The proposal in this work is to apply those estimators over the manifolds of allowed positions and velocities, by means of estimating a subset of independent coordinates only. The proposed techniques are experimentally validated on a testbed equipped with encoders as a means of establishing the ground-truth. Estimators are run online in real-time, a feature not matched by any previous procedure of those reported in the literature on multibody dynamics. PMID:26959027

A Virtual Blind Cane Using a Line Laser-Based Vision System and an Inertial Measurement Unit

PubMed Central

Dang, Quoc Khanh; Chee, Youngjoon; Pham, Duy Duong; Suh, Young Soo

2016-01-01

A virtual blind cane system for indoor application, including a camera, a line laser and an inertial measurement unit (IMU), is proposed in this paper. Working as a blind cane, the proposed system helps a blind person find the type of obstacle and the distance to it. The distance from the user to the obstacle is estimated by extracting the laser coordinate points on the obstacle, as well as tracking the system pointing angle. The paper provides a simple method to classify the obstacle’s type by analyzing the laser intersection histogram. Real experimental results are presented to show the validity and accuracy of the proposed system. PMID:26771618

STS-8 bet results

NASA Technical Reports Server (NTRS)

Findlay, J. T.; Kelly, G. M.; Heck, M. L.; Mcconnell, J. G.

1983-01-01

The final Best Estimate Trajectory (BET) products, i.e., the reconstructed trajectory, the Extended BET, AEROBET and MMLE input files, generated for the eighth NASA Space Shuttle flight are documented. The reconstructed trajectory (inertial BET) for this Challenger flight, the first night landing is discussed. State (position, velocity, and attitude) plus three accelerometer scale factors were determined from fitting the Guam S-band data, seven C-band passes, and pseudo Doppler and altimeter during rollout on Runway 22. The anchor epoch utilized for the batch weighted-least-squares determination was Sept. 5, 1983 7h1m50s.0 (25310 GMT seconds). The spacecraft altitude at epoch is approx. 617 kft. IMU2 data were selected for the reconstruction.

Study of the Navigation Method for a Snake Robot Based on the Kinematics Model with MEMS IMU

PubMed Central

Dou, Lihua; Su, Zhong; Liu, Ning

2018-01-01

A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot’s motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU). First, it studies the snake robot’s motion characteristics, builds the kinematics model, and then analyses the motion constraint characteristics and motion error propagation properties. Second, it explores the snake robot’s navigation layout, proposes a constraint criterion and the fixed relationship, and makes zero-state constraints based on the motion features and control modes of a snake robot. Finally, it realizes autonomous navigation positioning based on the Extended-Kalman-Filter (EKF) position estimation method under the constraints of its motion characteristics. With the self-developed snake robot, the test verifies the proposed method, and the position error is less than 5% of Total-Traveled-Distance (TDD). In a short-distance environment, this method is able to meet the requirements of a snake robot in order to perform autonomous navigation and positioning in traditional applications and can be extended to other familiar multi-link robots. PMID:29547515

Ground moving target geo-location from monocular camera mounted on a micro air vehicle

NASA Astrophysics Data System (ADS)

Guo, Li; Ang, Haisong; Zheng, Xiangming

2011-08-01

The usual approaches to unmanned air vehicle(UAV)-to-ground target geo-location impose some severe constraints to the system, such as stationary objects, accurate geo-reference terrain database, or ground plane assumption. Micro air vehicle(MAV) works with characteristics including low altitude flight, limited payload and onboard sensors' low accuracy. According to these characteristics, a method is developed to determine the location of ground moving target which imaged from the air using monocular camera equipped on MAV. This method eliminates the requirements for terrain database (elevation maps) and altimeters that can provide MAV's and target's altitude. Instead, the proposed method only requires MAV flight status provided by its inherent onboard navigation system which includes inertial measurement unit(IMU) and global position system(GPS). The key is to get accurate information on the altitude of the ground moving target. First, Optical flow method extracts background static feature points. Setting a local region around the target in the current image, The features which are on the same plane with the target in this region are extracted, and are retained as aided features. Then, inverse-velocity method calculates the location of these points by integrated with aircraft status. The altitude of object, which is calculated by using position information of these aided features, combining with aircraft status and image coordinates, geo-locate the target. Meanwhile, a framework with Bayesian estimator is employed to eliminate noise caused by camera, IMU and GPS. Firstly, an extended Kalman filter(EKF) provides a simultaneous localization and mapping solution for the estimation of aircraft states and aided features location which defines the moving target local environment. Secondly, an unscented transformation(UT) method determines the estimated mean and covariance of target location from aircraft states and aided features location, and then exports them for the moving target Kalman filter(KF). Experimental results show that our method can instantaneously geo-locate the moving target by operator's single click and can reach 15 meters accuracy for an MAV flying at 200 meters above the ground.

A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles

PubMed Central

Meng, Xiaoli

2017-01-01

Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization. PMID:28926996

A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles.

PubMed

Meng, Xiaoli; Wang, Heng; Liu, Bingbing

2017-09-18

Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.

Integrity monitoring of vehicle positioning in urban environment using RTK-GNSS, IMU and speedometer

NASA Astrophysics Data System (ADS)

El-Mowafy, Ahmed; Kubo, Nobuaki

2017-05-01

Continuous and trustworthy positioning is a critical capability for advanced driver assistance systems (ADAS). To achieve continuous positioning, methods such as global navigation satellite systems real-time kinematic (RTK), Doppler-based positioning, and positioning using low-cost inertial measurement unit (IMU) with car speedometer data are combined in this study. To ensure reliable positioning, the system should have integrity monitoring above a certain level, such as 99%. Achieving this level when combining different types of measurements that have different characteristics and different types of errors is a challenge. In this study, a novel integrity monitoring approach is presented for the proposed integrated system. A threat model of the measurements of the system components is discussed, which includes both the nominal performance and possible fault modes. A new protection level is presented to bound the maximum directional position error. The proposed approach was evaluated through a kinematic test in an urban area in Japan with a focus on horizontal positioning. Test results show that by integrating RTK, Doppler with IMU/speedometer, 100% positioning availability was achieved. The integrity monitoring availability was assessed and found to meet the target value where the position errors were bounded by the protection level, which was also less than an alert level, indicating the effectiveness of the proposed approach.

PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition.

PubMed

Zuo, Yongchun; Li, Yuan; Chen, Yingli; Li, Guangpeng; Yan, Zhenhe; Yang, Lei

2017-01-01

The reduced amino acids perform powerful ability for both simplifying protein complexity and identifying functional conserved regions. However, dealing with different protein problems may need different kinds of cluster methods. Encouraged by the success of pseudo-amino acid composition algorithm, we developed a freely available web server, called PseKRAAC (the pseudo K-tuple reduced amino acids composition). By implementing reduced amino acid alphabets, the protein complexity can be significantly simplified, which leads to decrease chance of overfitting, lower computational handicap and reduce information redundancy. PseKRAAC delivers more capability for protein research by incorporating three crucial parameters that describes protein composition. Users can easily generate many different modes of PseKRAAC tailored to their needs by selecting various reduced amino acids alphabets and other characteristic parameters. It is anticipated that the PseKRAAC web server will become a very useful tool in computational proteomics and protein sequence analysis. Freely available on the web at http://bigdata.imu.edu.cn/psekraac CONTACTS: yczuo@imu.edu.cn or imu.hema@foxmail.com or yanglei_hmu@163.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Using groundwater temperature data to constrain parameter estimation in a groundwater flow model of a wetland system

USGS Publications Warehouse

Bravo, Hector R.; Jiang, Feng; Hunt, Randall J.

2002-01-01

Parameter estimation is a powerful way to calibrate models. While head data alone are often insufficient to estimate unique parameters due to model nonuniqueness, flow‐and‐heat‐transport modeling can constrain estimation and allow simultaneous estimation of boundary fluxes and hydraulic conductivity. In this work, synthetic and field models that did not converge when head data were used did converge when head and temperature were used. Furthermore, frequency domain analyses of head and temperature data allowed selection of appropriate modeling timescales. Inflows in the Wilton, Wisconsin, wetlands could be estimated over periods such as a growing season and over periods of a few days when heads were nearly steady and groundwater temperature varied during the day. While this methodology is computationally more demanding than traditional head calibration, the results gained are unobtainable using the traditional approach. These results suggest that temperature can efficiently supplement head data in systems where accurate flux calibration targets are unavailable.

Exploring Unsteady Sail Propulsion in Olympic Class Sailboats

NASA Astrophysics Data System (ADS)

Schutt, Riley; Williamson, C. H. K.

2014-11-01

Unsteady sailing techniques, defined as ``flicking,'' ``roll-tacking'' and ``roll-gybing'' are used by athletes to propel their boats on an Olympic race course faster than using the wind alone. Body weight movements induce unsteady sail motion, increasing driving force and enhancing maneuvering performance. In this research, we explore the dynamics of an Olympic class Laser sailboat equipped with a GPS, IMU, wind sensor, and camera array. The velocity heading of a sailing boat is oriented at an apparent wind angle to the flow. In contrast to classic flapping propulsion, the heaving of the sail section (induced by the sailor's body movement) is not perpendicular to the sail's motion through the air. This leads to an ``exotic heave,'' with components parallel and perpendicular to the incident flow. The characteristic motion is recreated in a towing tank where the vortex structures generated by a representative 2-D sail section are observed, along with a measurement of thrust and lift forces. When combined with turning maneuvers, these heaving sail motions can lead to significant increases in velocity made good, a critical variable used when assessing racing performance.

Field Programmable Gate Array (FPGA) Respiratory Monitoring System Using a Flow Microsensor and an Accelerometer

NASA Astrophysics Data System (ADS)

Mellal, Idir; Laghrouche, Mourad; Bui, Hung Tien

2017-04-01

This paper describes a non-invasive system for respiratory monitoring using a Micro Electro Mechanical Systems (MEMS) flow sensor and an IMU (Inertial Measurement Unit) accelerometer. The designed system is intended to be wearable and used in a hospital or at home to assist people with respiratory disorders. To ensure the accuracy of our system, we proposed a calibration method based on ANN (Artificial Neural Network) to compensate the temperature drift of the silicon flow sensor. The sigmoid activation functions used in the ANN model were computed with the CORDIC (COordinate Rotation DIgital Computer) algorithm. This algorithm was also used to estimate the tilt angle in body position. The design was implemented on reconfigurable platform FPGA.

Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System

PubMed Central

Chen, Jing; Zhou, Zixiang; Leng, Zhen; Fan, Lei

2018-01-01

The fusion of monocular visual and inertial cues has become popular in robotics, unmanned vehicles and augmented reality fields. Recent results have shown that optimization-based fusion strategies outperform filtering strategies. Robust state estimation is the core capability for optimization-based visual–inertial Simultaneous Localization and Mapping (SLAM) systems. As a result of the nonlinearity of visual–inertial systems, the performance heavily relies on the accuracy of initial values (visual scale, gravity, velocity and Inertial Measurement Unit (IMU) biases). Therefore, this paper aims to propose a more accurate initial state estimation method. On the basis of the known gravity magnitude, we propose an approach to refine the estimated gravity vector by optimizing the two-dimensional (2D) error state on its tangent space, then estimate the accelerometer bias separately, which is difficult to be distinguished under small rotation. Additionally, we propose an automatic termination criterion to determine when the initialization is successful. Once the initial state estimation converges, the initial estimated values are used to launch the nonlinear tightly coupled visual–inertial SLAM system. We have tested our approaches with the public EuRoC dataset. Experimental results show that the proposed methods can achieve good initial state estimation, the gravity refinement approach is able to efficiently speed up the convergence process of the estimated gravity vector, and the termination criterion performs well. PMID:29419751

Challenger STS-17 (41-G) post-flight best estimate trajectory products: Development and summary results

NASA Technical Reports Server (NTRS)

Kelly, G. M.; Heck, M. L.; Mcconnell, J. G.; Waters, L. A.; Troutman, P. A.; Findlay, J. T.

1985-01-01

Results from the STS-17 (41-G) post-flight products are presented. Operational Instrumentation recorder gaps, coupled with the limited tracking coverage available for this high inclination entry profile, necessitated selection of an anchor epoch for reconstruction corresponding to an unusually low altitude of h approx. 297 kft. The final inertial trajectory obtained, BT17N26/UN=169750N, is discussed in Section I, i.e., relative to the problems encountered with the OI and ACIP recorded data on this Challenger flight. Atmospheric selection, again in view of the ground track displacement from the remote meteorological sites, constituted a major problem area as discussed in Section II. The LAIRS file provided by Langley was adopted, with NOAA data utilized over the lowermost approx. 7 kft. As discussed in Section II, the Extended BET, ST17BET/UN=274885C, suggests a limited upper altitude (H approx. 230 kft) for which meaningful flight extraction can be expected. This is further demonstrated, though not considered a limitation, in Section III wherein summary results from the AEROBET (NJ0333 with NJ0346 as duplicate) are presented. GTFILEs were generated only for the selected IMU (IMU2) and the Rate Gyro Assembly/Accelerometer Assembly data due to the loss of ACIP data. Appendices attached present inputs for the generation of the post-flight products (Appendix A), final residual plots (Appendix B), a two second spaced listing of the relevant parameters from the Extended BET (Appendix C), and an archival section (Appendix D) devoting input (source) and output files and/or physical reels.

An Artificial Neural Network Embedded Position and Orientation Determination Algorithm for Low Cost MEMS INS/GPS Integrated Sensors

PubMed Central

Chiang, Kai-Wei; Chang, Hsiu-Wen; Li, Chia-Yuan; Huang, Yun-Wen

2009-01-01

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated. PMID:22574034

Trajectory Reconstruction and Uncertainty Analysis Using Mars Science Laboratory Pre-Flight Scale Model Aeroballistic Testing

NASA Technical Reports Server (NTRS)

Lugo, Rafael A.; Tolson, Robert H.; Schoenenberger, Mark

2013-01-01

As part of the Mars Science Laboratory (MSL) trajectory reconstruction effort at NASA Langley Research Center, free-flight aeroballistic experiments of instrumented MSL scale models was conducted at Aberdeen Proving Ground in Maryland. The models carried an inertial measurement unit (IMU) and a flush air data system (FADS) similar to the MSL Entry Atmospheric Data System (MEADS) that provided data types similar to those from the MSL entry. Multiple sources of redundant data were available, including tracking radar and on-board magnetometers. These experimental data enabled the testing and validation of the various tools and methodologies that will be used for MSL trajectory reconstruction. The aerodynamic parameters Mach number, angle of attack, and sideslip angle were estimated using minimum variance with a priori to combine the pressure data and pre-flight computational fluid dynamics (CFD) data. Both linear and non-linear pressure model terms were also estimated for each pressure transducer as a measure of the errors introduced by CFD and transducer calibration. Parameter uncertainties were estimated using a "consider parameters" approach.

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

PubMed Central

Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

2015-01-01

Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

Designing and Testing a UAV Mapping System for Agricultural Field Surveying

PubMed Central

Skovsen, Søren

2017-01-01

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35–0.58 m are correlated to the applied nitrogen treatments of 0–300 kgNha. The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations. PMID:29168783

Designing and Testing a UAV Mapping System for Agricultural Field Surveying.

PubMed

Christiansen, Martin Peter; Laursen, Morten Stigaard; Jørgensen, Rasmus Nyholm; Skovsen, Søren; Gislum, René

2017-11-23

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35-0.58 m are correlated to the applied nitrogen treatments of 0-300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.

Approach for Improving the Integrated Sensor Orientation

NASA Astrophysics Data System (ADS)

Mitishita, E.; Ercolin Filho, L.; Graça, N.; Centeno, J.

2016-06-01

The direct determination of exterior orientation parameters (EOP) of aerial images via integration of the Inertial Measurement Unit (IMU) and GPS is often used in photogrammetric mapping nowadays. The accuracies of the EOP depend on the accurate parameters related to sensors mounting when the job is performed (offsets of the IMU relative to the projection centre and the angles of boresigth misalignment between the IMU and the photogrammetric coordinate system). In principle, when the EOP values do not achieve the required accuracies for the photogrammetric application, the approach, known as Integrated Sensor Orientation (ISO), is used to refine the direct EOP. ISO approach requires accurate Interior Orientation Parameters (IOP) and standard deviation of the EOP under flight condition. This paper investigates the feasibility of use the in situ camera calibration to obtain these requirements. The camera calibration uses a small sub block of images, extracted from the entire block. A digital Vexcel UltraCam XP camera connected to APPLANIX POS AVTM system was used to get two small blocks of images that were use in this study. The blocks have different flight heights and opposite flight directions. The proposed methodology improved significantly the vertical and horizontal accuracies of the 3D point intersection. Using a minimum set of control points, the horizontal and vertical accuracies achieved nearly one image pixel of resolution on the ground (GSD). The experimental results are shown and discussed.

Motion measurement for synthetic aperture radar

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

Doerry, Armin W.

Synthetic Aperture Radar (SAR) measures radar soundings from a set of locations typically along the flight path of a radar platform vehicle. Optimal focusing requires precise knowledge of the sounding source locations in 3-D space with respect to the target scene. Even data driven focusing techniques (i.e. autofocus) requires some degree of initial fidelity in the measurements of the motion of the radar. These requirements may be quite stringent especially for fine resolution, long ranges, and low velocities. The principal instrument for measuring motion is typically an Inertial Measurement Unit (IMU), but these instruments have inherent limi ted precision andmore » accuracy. The question is %22How good does an IMU need to be for a SAR across its performance space?%22 This report analytically relates IMU specifications to parametric requirements for SAR. - 4 - Acknowledgements Th e preparation of this report is the result of a n unfunded research and development activity . Although this report is an independent effort, it draws heavily from limited - release documentation generated under a CRADA with General Atomics - Aeronautical System, Inc. (GA - ASI), and under the Joint DoD/DOE Munitions Program Memorandum of Understanding. Sandia National Laboratories is a multi - program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of En ergy's National Nuclear Security Administration under contract AC04-94AL85000.« less

Tightly Coupled Inertial Navigation System/Global Positioning System (TCMIG)

NASA Technical Reports Server (NTRS)

Watson, Michael D.; Jackson, Kurt (Technical Monitor)

2002-01-01

Many NASA applications planned for execution later this decade are seeking high performance, miniaturized, low power Inertial Management Units (IMU). Much research has gone into Micro-Electro-Mechanical System (MEMS) over the past decade as a solution to these needs. While MEMS devices have proven to provide high accuracy acceleration measurements, they have not yet proven to have the accuracy required by many NASA missions in rotational measurements. Therefore, a new solution has been formulated integrating the best of all IMU technologies to address these mid-term needs in the form of a Tightly Coupled Micro Inertial Navigation System (INS)/Global Positioning System (GPS) (TCMIG). The TCMIG consists of an INS and a GPS tightly coupled by a Kalman filter executing on an embedded Field Programmable Gate Array (FPGA) processor. The INS consists of a highly integrated Interferometric Fiber Optic Gyroscope (IFOG) and a MEMS accelerometer. The IFOG utilizes a tightly wound fiber coil to reduce volume and the high level of integration and advanced optical components to reduce power. The MEMS accelerometer utilizes a newly developed deep etch process to increase the proof mass and yield a highly accurate accelerometer. The GPS receiver consists of a low power miniaturized version of the Blackjack receiver. Such an IMU configuration is ideal to meet the mid-term needs of the NASA Science Enterprises and the new launch vehicles being developed for the Space Launch Initiative (SLI).

Head Pose Estimation Using Multilinear Subspace Analysis for Robot Human Awareness

NASA Technical Reports Server (NTRS)

Ivanov, Tonislav; Matthies, Larry; Vasilescu, M. Alex O.

2009-01-01

Mobile robots, operating in unconstrained indoor and outdoor environments, would benefit in many ways from perception of the human awareness around them. Knowledge of people's head pose and gaze directions would enable the robot to deduce which people are aware of the its presence, and to predict future motions of the people for better path planning. To make such inferences, requires estimating head pose on facial images that are combination of multiple varying factors, such as identity, appearance, head pose, and illumination. By applying multilinear algebra, the algebra of higher-order tensors, we can separate these factors and estimate head pose regardless of subject's identity or image conditions. Furthermore, we can automatically handle uncertainty in the size of the face and its location. We demonstrate a pipeline of on-the-move detection of pedestrians with a robot stereo vision system, segmentation of the head, and head pose estimation in cluttered urban street scenes.

Inertial measurement unit pre-processors and post-flight STS-1 comparisons

NASA Technical Reports Server (NTRS)

Findlay, J. T.; Mcconnell, J. G.

1981-01-01

The flight results show that the relative tri-redundant Inertial Measurement Unit IMU performance throughout the entire entry flight was within the expected accuracy. Comparisons are presented which show differences in the accumulated sensed velocity changes as measured by the tri-redundant IMUs (in Mean Equator and Equinox of 1950.0), differences in the equivalent inertial Euler angles as measured with respect to the M50 system, and finally, preliminary instrument calibrations determined relative to the ensemble average measurement set. Also, differences in the derived body axes rates and accelerations are presented. Because of the excellent performance of the IMUs during the STS-1 entry, the selection as to which particular IMU would best serve as the dynamic data source for entry reconstruction is arbitrary.

Indoor localization using pedestrian dead reckoning updated with RFID-based fiducials.

PubMed

House, Samuel; Connell, Sean; Milligan, Ian; Austin, Daniel; Hayes, Tamara L; Chiang, Patrick

2011-01-01

We describe a low-cost wearable system that tracks the location of individuals indoors using commonly available inertial navigation sensors fused with radio frequency identification (RFID) tags placed around the smart environment. While conventional pedestrian dead reckoning (PDR) calculated with an inertial measurement unit (IMU) is susceptible to sensor drift inaccuracies, the proposed wearable prototype fuses the drift-sensitive IMU with a RFID tag reader. Passive RFID tags placed throughout the smart-building then act as fiducial markers that update the physical locations of each user, thereby correcting positional errors and sensor inaccuracy. Experimental measurements taken for a 55 m × 20 m 2D floor space indicate an over 1200% improvement in average error rate of the proposed RFID-fused system over dead reckoning alone.

VRACK: measuring pedal kinematics during stationary bike cycling.

PubMed

Farjadian, Amir B; Kong, Qingchao; Gade, Venkata K; Deutsch, Judith E; Mavroidis, Constantinos

2013-06-01

Ankle impairment and lower limb asymmetries in strength and coordination are common symptoms for individuals with selected musculoskeletal and neurological impairments. The virtual reality augmented cycling kit (VRACK) was designed as a compact mechatronics system for lower limb and mobility rehabilitation. The system measures interaction forces and cardiac activity during cycling in a virtual environment. The kinematics measurement was added to the system. Due to the constrained problem definition, the combination of inertial measurement unit (IMU) and Kalman filtering was recruited to compute the optimal pedal angular displacement during dynamic cycling exercise. Using a novel benchmarking method the accuracy of IMU-based kinematics measurement was evaluated. Relatively accurate angular measurements were achieved. The enhanced VRACK system can serve as a rehabilitation device to monitor biomechanical and physiological variables during cycling on a stationary bike.

Context-Aided Sensor Fusion for Enhanced Urban Navigation

PubMed Central

Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María

2012-01-01

The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments. PMID:23223080

Context-aided sensor fusion for enhanced urban navigation.

PubMed

Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María

2012-12-06

 The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.

Head pose estimation in computer vision: a survey.

PubMed

Murphy-Chutorian, Erik; Trivedi, Mohan Manubhai

2009-04-01

The capacity to estimate the head pose of another person is a common human ability that presents a unique challenge for computer vision systems. Compared to face detection and recognition, which have been the primary foci of face-related vision research, identity-invariant head pose estimation has fewer rigorously evaluated systems or generic solutions. In this paper, we discuss the inherent difficulties in head pose estimation and present an organized survey describing the evolution of the field. Our discussion focuses on the advantages and disadvantages of each approach and spans 90 of the most innovative and characteristic papers that have been published on this topic. We compare these systems by focusing on their ability to estimate coarse and fine head pose, highlighting approaches that are well suited for unconstrained environments.

Optimal estimation of spatially variable recharge and transmissivity fields under steady-state groundwater flow. Part 2. Case study

NASA Astrophysics Data System (ADS)

Graham, Wendy D.; Neff, Christina R.

1994-05-01

The first-order analytical solution of the inverse problem for estimating spatially variable recharge and transmissivity under steady-state groundwater flow, developed in Part 1 is applied to the Upper Floridan Aquifer in NE Florida. Parameters characterizing the statistical structure of the log-transmissivity and head fields are estimated from 152 measurements of transmissivity and 146 measurements of hydraulic head available in the study region. Optimal estimates of the recharge, transmissivity and head fields are produced throughout the study region by conditioning on the nearest 10 available transmissivity measurements and the nearest 10 available head measurements. Head observations are shown to provide valuable information for estimating both the transmissivity and the recharge fields. Accurate numerical groundwater model predictions of the aquifer flow system are obtained using the optimal transmissivity and recharge fields as input parameters, and the optimal head field to define boundary conditions. For this case study, both the transmissivity field and the uncertainty of the transmissivity field prediction are poorly estimated, when the effects of random recharge are neglected.

Using Airborne Lidar Data from IcePod to Measure Annual and Seasonal Ice Changes Over Greenland

NASA Astrophysics Data System (ADS)

Frearson, N.; Bertinato, C.; Das, I.

2014-12-01

The IcePod is a multi-sensor airborne science platform that supports a wide suite of instruments, including a Riegl VQ-580 infrared scanning laser, GPS-inertial positioning system, shallow and deep-ice radars, visible-wave and infrared cameras, and upward-looking pyrometer. These instruments allow us to image the ice from top to bottom, including the surface of melt-water plumes that originate at the ice-ocean boundary. In collaboration with the New York Air National Guard 109th Airlift Wing, the IcePod is flown on LC-130 aircraft, which presents the unique opportunity to routinely image the Greenland ice sheet several times within a season. This is particularly important for mass balance studies, as we can measure elevation changes during the melt season. During the 2014 summer, laser data was collected via IcePod over the Greenland ice sheet, including Russell Glacier, Jakobshavn Glacier, Eqip Glacier, and Summit Camp. The Icepod will also be routinely operated in Antarctica. We present the initial testing, calibration, and error estimates from the first set of laser data that were collected on IcePod. At a survey altitude of 1000 m, the laser swath covers ~ 1000 m. A Northrop-Grumman LN-200 tactical grade IMU is rigidly attached to the laser scanner to provide attitude data at a rate of 200 Hz. Several methods were used to determine the lever arm between the IMU center of navigation and GPS antenna phase center, terrestrial scanning laser, total station survey, and optimal estimation. Additionally, initial bore sight calibration flights yielded misalignment angles within an accuracy of ±4 cm. We also performed routine passes over the airport ramp in Kangerlussuaq, Greenland, comparing the airborne GPS and Lidar data to a reference GPS-based ground survey across the ramp, spot GPS points on the ramp and a nearby GPS base station. Positioning errors can severely impact the accuracy of a laser altimeter when flying over remote regions such as across the ice sheets. Setting up GPS base stations along the flight track can prove to be logistically challenging. We have processed the GPS-inertial data using both DGPS and PPP and present the comparison of those results here. Finally, we discuss our processing, calibration and error estimation methods and compare our results to previously flown IceBridge lines.

The Role of Aircraft Motion in Airborne Gravity Data Quality

NASA Astrophysics Data System (ADS)

Childers, V. A.; Damiani, T.; Weil, C.; Preaux, S. A.

2015-12-01

Many factors contribute to the quality of airborne gravity data measured with LaCoste and Romberg-type sensors, such as the Micro-g LaCoste Turnkey Airborne Gravity System used by the National Geodetic Survey's GRAV-D (Gravity for the Redefinition of the American Vertical Datum) Project. For example, it is well documented that turbulence is a big factor in the overall noise level of the measurement. Turbulence is best controlled by avoidance; thus flights in the GRAV-D Project are only undertaken when the predicted wind speeds at flight level are ≤ 40 kts. Tail winds are known to be particularly problematic. The GRAV-D survey operates on a number of aircraft in a variety of wind conditions and geographic locations, and an obvious conclusion from our work to date is that the aircraft itself plays an enormous role in the quality of the airborne gravity measurement. We have identified a number of features of the various aircraft which can be determined to play a role: the autopilot, the size and speed of the aircraft, inherent motion characteristics of the airframe, tip tanks and other modifications to the airframe to reduce motion, to name the most important. This study evaluates the motion of a number of the GRAV-D aircraft and looks at the correlation between this motion and the noise characteristics of the gravity data. The GRAV-D Project spans 7 years and 42 surveys, so we have a significant body of data for this evaluation. Throughout the project, the sensor suite has included an inertial measurement unit (IMU), first the Applanix POSAv, and then later the Honeywell MicroIRS IMU as a part of a NovAtel SPAN GPS/IMU system. We compare the noise characteristics of the data with measures of aircraft motion (via pitch, roll, and yaw captured by the IMU) using a variety of statistical tools. It is expected that this comparison will support the conclusion that certain aircraft tend to work well with this type of gravity sensor while others tend to be problematic in general.

Head Pose Estimation on Eyeglasses Using Line Detection and Classification Approach

NASA Astrophysics Data System (ADS)

Setthawong, Pisal; Vannija, Vajirasak

This paper proposes a unique approach for head pose estimation of subjects with eyeglasses by using a combination of line detection and classification approaches. Head pose estimation is considered as an important non-verbal form of communication and could also be used in the area of Human-Computer Interface. A major improvement of the proposed approach is that it allows estimation of head poses at a high yaw/pitch angle when compared with existing geometric approaches, does not require expensive data preparation and training, and is generally fast when compared with other approaches.

Compact fiber optic gyroscopes for platform stabilization

NASA Astrophysics Data System (ADS)

Dickson, William C.; Yee, Ting K.; Coward, James F.; McClaren, Andrew; Pechner, David A.

2013-09-01

SA Photonics has developed a family of compact Fiber Optic Gyroscopes (FOGs) for platform stabilization applications. The use of short fiber coils enables the high update rates required for stabilization applications but presents challenges to maintain high performance. We are able to match the performance of much larger FOGs by utilizing several innovative technologies. These technologies include source noise reduction to minimize Angular Random Walk (ARW), advanced digital signal processing that minimizes bias drift at high update rates, and advanced passive thermal packaging that minimizes temperature induced bias drift while not significantly affecting size, weight, or power. In addition, SA Photonics has developed unique distributed FOG packaging technologies allowing the FOG electronics and photonics to be packaged remotely from the sensor head or independent axis heads to minimize size, weight, and power at the sensing location(s). The use of these technologies has resulted in high performance, including ARW less than 0.001 deg/rt-hr and bias drift less than 0.004 deg/hr at an update rate of 10 kHz, and total packaged volume less than 30 cu. in. for a 6 degree of freedom FOG-based IMU. Specific applications include optical beam stabilization for LIDAR and LADAR, beam stabilization for long-range free-space optical communication, Optical Inertial Reference Units for HEL stabilization, and Ka band antenna pedestal pointing and stabilization. The high performance of our FOGs also enables their use in traditional navigation and positioning applications. This paper will review the technologies enabling our high-performance compact FOGs, and will provide performance test results.

Carrying Position Independent User Heading Estimation for Indoor Pedestrian Navigation with Smartphones

PubMed Central

Deng, Zhi-An; Wang, Guofeng; Hu, Ying; Cui, Yang

2016-01-01

This paper proposes a novel heading estimation approach for indoor pedestrian navigation using the built-in inertial sensors on a smartphone. Unlike previous approaches constraining the carrying position of a smartphone on the user’s body, our approach gives the user a larger freedom by implementing automatic recognition of the device carrying position and subsequent selection of an optimal strategy for heading estimation. We firstly predetermine the motion state by a decision tree using an accelerometer and a barometer. Then, to enable accurate and computational lightweight carrying position recognition, we combine a position classifier with a novel position transition detection algorithm, which may also be used to avoid the confusion between position transition and user turn during pedestrian walking. For a device placed in the trouser pockets or held in a swinging hand, the heading estimation is achieved by deploying a principal component analysis (PCA)-based approach. For a device held in the hand or against the ear during a phone call, user heading is directly estimated by adding the yaw angle of the device to the related heading offset. Experimental results show that our approach can automatically detect carrying positions with high accuracy, and outperforms previous heading estimation approaches in terms of accuracy and applicability. PMID:27187391

An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors

PubMed Central

Vassallo, Michael

2018-01-01

This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from our method are validated using a Qualisys Motion Capture System. The data are collected from 10 young and 10 older subjects. Each performed a trial in a straight corridor comprising 15 strides of normal walking, a turn around and another 15 strides. We analyse the data for total distance, total time, total velocity, stride, step, cadence, step ratio, stance, and swing. The accuracy of detecting the stride number using the proposed method is 100% for young and 92.67% for older subjects. The accuracy of estimating travelled distance using the proposed method for young subjects is 97.73% and 98.82% for right and left legs; and for the older, is 88.71% and 89.88% for right and left legs. The average travelled distance is 37.77 (95% CI ± 3.57) meters for young subjects and is 22.50 (95% CI ± 2.34) meters for older subjects. The average travelled time for young subjects is 51.85 (95% CI ± 3.08) seconds and for older subjects is 84.02 (95% CI ± 9.98) seconds. The results show that wearable sensors can be used for identifying gait asymmetry without the requirement and expense of an elaborate laboratory setup. This can serve as a tool in diagnosing gait abnormalities in individuals and opens the possibilities for home based self-gait asymmetry assessment. PMID:29495299

The Influence of Head Motion on Intrinsic Functional Connectivity MRI

PubMed Central

Van Dijk, Koene R.A.; Sabuncu, Mert R.; Buckner, Randy L.

2011-01-01

Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (> 0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to estimated head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks – two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions – a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals. PMID:21810475

Improved Feature Matching for Mobile Devices with IMU.

PubMed

Masiero, Andrea; Vettore, Antonio

2016-08-05

Thanks to the recent diffusion of low-cost high-resolution digital cameras and to the development of mostly automated procedures for image-based 3D reconstruction, the popularity of photogrammetry for environment surveys is constantly increasing in the last years. Automatic feature matching is an important step in order to successfully complete the photogrammetric 3D reconstruction: this step is the fundamental basis for the subsequent estimation of the geometry of the scene. This paper reconsiders the feature matching problem when dealing with smart mobile devices (e.g., when using the standard camera embedded in a smartphone as imaging sensor). More specifically, this paper aims at exploiting the information on camera movements provided by the inertial navigation system (INS) in order to make the feature matching step more robust and, possibly, computationally more efficient. First, a revised version of the affine scale-invariant feature transform (ASIFT) is considered: this version reduces the computational complexity of the original ASIFT, while still ensuring an increase of correct feature matches with respect to the SIFT. Furthermore, a new two-step procedure for the estimation of the essential matrix E (and the camera pose) is proposed in order to increase its estimation robustness and computational efficiency.

Head injuries (TBI) to adults and children in motor vehicle crashes.

PubMed

Viano, David C; Parenteau, Chantal S; Xu, Likang; Faul, Mark

2017-08-18

This is a descriptive study. It determined the annual, national incidence of head injuries (traumatic brain injury, TBI) to adults and children in motor vehicle crashes. It evaluated NASS-CDS for exposure and incidence of various head injuries in towaway crashes. It evaluated 3 health databases for emergency department (ED) visits, hospitalizations, and deaths due to TBI in motor vehicle occupants. Four databases were evaluated using 1997-2010 data on adult (15+ years old) and child (0-14 years old) occupants in motor vehicle crashes: (1) NASS-CDS estimated the annual incidence of various head injuries and outcomes in towaway crashes, (2) National Hospital Ambulatory Medical Care Survey (NHAMCS)-estimated ED visits for TBI, (3) National Hospital Discharge Survey (NHDS) estimated hospitalizations for TBI, and (4) National Vital Statistics System (NVSS) estimated TBI deaths. The 4 databases provide annual national totals for TBI related injury and death in motor vehicle crashes based on differing definitions with TBI coded by the Abbreviated Injury Scale (AIS) in NASS-CDS and by International Classification of Diseases (ICD) in the health data. Adults: NASS-CDS had 16,980 ± 2,411 (risk = 0.43 ± 0.06%) with severe head injury (AIS 4+) out of 3,930,543 exposed adults in towaway crashes annually. There were 49,881 ± 9,729 (risk = 1.27 ± 0.25%) hospitalized with AIS 2+ head injury, without death. There were 6,753 ± 882 (risk = 0.17 ± 0.02%) fatalities with a head injury cause. The public health data had 89,331 ± 6,870 ED visits, 33,598 ± 1,052 hospitalizations, and 6,682 ± 22 deaths with TBI. NASS-CDS estimated 48% more hospitalized with AIS 2+ head injury without death than NHDS occupants hospitalized with TBI. NASS-CDS estimated 29% more deaths with AIS 3+ head injury than NVSS occupant TBI deaths but only 1% more deaths with a head injury cause. Children: NASS-CDS had 1,453 ± 318 (risk = 0.32 ± 0.07%) with severe head injury (AIS 4+) out of 454,973 exposed children annually. There were 2,581 ± 683 (risk = 0.57 ± 0.15%) hospitalized with AIS 2+ head injury, without death. There were 466 ± 132 (risk = 0.10 ± 0.03%) fatalities with a head injury cause. The public health data had 19,251 ± 2,803 ED visits, 3,363 ± 255 hospitalizations, and 488 ± 6 deaths with TBI. NASS-CDS estimated 24% fewer hospitalized children with AIS 2+ head injury without death than NHDS hospitalization with TBI. NASS-CDS estimated 31% more deaths with AIS 3+ head injury than NVSS child deaths but 5% fewer deaths with a head injury cause. The annual national incidence of motor vehicle-related head injury (TBI) was estimated using 1997-2010 NASS-CDS from the Department of Transportation and NHAMCS (ED visits), NHDS (hospitalizations), and NVSS (deaths) from the Department of Health and Human Services. The transportation and health databases use different definitions and coding, which complicates direct comparisons. Future work is needed where ICD to AIS translators are used if comparisons of serious head injuries in NASS and health data sets are to be made.

The estimation of 3D SAR distributions in the human head from mobile phone compliance testing data for epidemiological studies

NASA Astrophysics Data System (ADS)

Wake, Kanako; Varsier, Nadège; Watanabe, Soichi; Taki, Masao; Wiart, Joe; Mann, Simon; Deltour, Isabelle; Cardis, Elisabeth

2009-10-01

A worldwide epidemiological study called 'INTERPHONE' has been conducted to estimate the hypothetical relationship between brain tumors and mobile phone use. In this study, we proposed a method to estimate 3D distribution of the specific absorption rate (SAR) in the human head due to mobile phone use to provide the exposure gradient for epidemiological studies. 3D SAR distributions due to exposure to an electromagnetic field from mobile phones are estimated from mobile phone compliance testing data for actual devices. The data for compliance testing are measured only on the surface in the region near the device and in a small 3D region around the maximum on the surface in a homogeneous phantom with a specific shape. The method includes an interpolation/extrapolation and a head shape conversion. With the interpolation/extrapolation, SAR distributions in the whole head are estimated from the limited measured data. 3D SAR distributions in the numerical head models, where the tumor location is identified in the epidemiological studies, are obtained from measured SAR data with the head shape conversion by projection. Validation of the proposed method was performed experimentally and numerically. It was confirmed that the proposed method provided good estimation of 3D SAR distribution in the head, especially in the brain, which is the tissue of major interest in epidemiological studies. We conclude that it is possible to estimate 3D SAR distributions in a realistic head model from the data obtained by compliance testing measurements to provide a measure for the exposure gradient in specific locations of the brain for the purpose of exposure assessment in epidemiological studies. The proposed method has been used in several studies in the INTERPHONE.

The estimation of 3D SAR distributions in the human head from mobile phone compliance testing data for epidemiological studies.

PubMed

Wake, Kanako; Varsier, Nadège; Watanabe, Soichi; Taki, Masao; Wiart, Joe; Mann, Simon; Deltour, Isabelle; Cardis, Elisabeth

2009-10-07

A worldwide epidemiological study called 'INTERPHONE' has been conducted to estimate the hypothetical relationship between brain tumors and mobile phone use. In this study, we proposed a method to estimate 3D distribution of the specific absorption rate (SAR) in the human head due to mobile phone use to provide the exposure gradient for epidemiological studies. 3D SAR distributions due to exposure to an electromagnetic field from mobile phones are estimated from mobile phone compliance testing data for actual devices. The data for compliance testing are measured only on the surface in the region near the device and in a small 3D region around the maximum on the surface in a homogeneous phantom with a specific shape. The method includes an interpolation/extrapolation and a head shape conversion. With the interpolation/extrapolation, SAR distributions in the whole head are estimated from the limited measured data. 3D SAR distributions in the numerical head models, where the tumor location is identified in the epidemiological studies, are obtained from measured SAR data with the head shape conversion by projection. Validation of the proposed method was performed experimentally and numerically. It was confirmed that the proposed method provided good estimation of 3D SAR distribution in the head, especially in the brain, which is the tissue of major interest in epidemiological studies. We conclude that it is possible to estimate 3D SAR distributions in a realistic head model from the data obtained by compliance testing measurements to provide a measure for the exposure gradient in specific locations of the brain for the purpose of exposure assessment in epidemiological studies. The proposed method has been used in several studies in the INTERPHONE.

Comparison of estimation accuracy of body density between different hydrostatics weighing methods without head submersion.

PubMed

Demura, Shinichi; Sato, Susumu; Nakada, Masakatsu; Minami, Masaki; Kitabayashi, Tamotsu

2003-07-01

This study compared the accuracy of body density (Db) estimation methods using hydrostatic weighing without complete head submersion (HW(withoutHS)) of Donnelly et al. (1988) and Donnelly and Sintek (1984) as referenced to Goldman and Buskirk's approach (1961). Donnelly et al.'s method estimates Db from a regression equation using HW(withoutHS), moreover, Donnelly and Sintek's method estimates it from HW(withoutHS) and head anthropometric variables. Fifteen Japanese males (173.8+/-4.5 cm, 63.6+/-5.4 kg, 21.2+/-2.8 years) and fifteen females (161.4+/-5.4 cm, 53.8+/-4.8 kg, 21.0+/-1.4 years) participated in this study. All the subjects were measured for head length, width and HWs under the two conditions of with and without head submersion. In order to examine the consistency of estimation values of Db, the correlation coefficients between the estimation values and the reference (Goldman and Buskirk, 1961) were calculated. The standard errors of estimation (SEE) were calculated by regression analysis using a reference value as a dependent variable and estimation values as independent variables. In addition, the systematic errors of two estimation methods were investigated by the Bland-Altman technique (Bland and Altman, 1986). In the estimation, Donnelly and Sintek's equation showed a high relationship with the reference (r=0.960, p<0.01), but had more differences from the reference compared with Donnelly et al.'s equation. Further studies are needed to develop new prediction equations for Japanese considering sex and individual differences in head anthropometry.

Hydraulic head applications of flow logs in the study of heterogeneous aquifers

USGS Publications Warehouse

Paillet, Frederick L.

2001-01-01

Permeability profiles derived from high-resolution flow logs in heterogeneous aquifers provide a limited sample of the most permeable beds or fractures determining the hydraulic properties of those aquifers. This paper demonstrates that flow logs can also be used to infer the large-scale properties of aquifers surrounding boreholes. The analysis is based on the interpretation of the hydraulic head values estimated from the flow log analysis. Pairs of quasi-steady flow profiles obtained under ambient conditions and while either pumping or injecting are used to estimate the hydraulic head in each water-producing zone. Although the analysis yields localized estimates of transmissivity for a few water-producing zones, the hydraulic head estimates apply to the farfield aquifers to which these zones are connected. The hydraulic head data are combined with information from other sources to identify the large-scale structure of heterogeneous aquifers. More complicated cross-borehole flow experiments are used to characterize the pattern of connection between large-scale aquifer units inferred from the hydraulic head estimates. The interpretation of hydraulic heads in situ under steady and transient conditions is illustrated by several case studies, including an example with heterogeneous permeable beds in an unconsolidated aquifer, and four examples with heterogeneous distributions of bedding planes and/or fractures in bedrock aquifers.

Non-linear Parameter Estimates from Non-stationary MEG Data

PubMed Central

Martínez-Vargas, Juan D.; López, Jose D.; Baker, Adam; Castellanos-Dominguez, German; Woolrich, Mark W.; Barnes, Gareth

2016-01-01

We demonstrate a method to estimate key electrophysiological parameters from resting state data. In this paper, we focus on the estimation of head-position parameters. The recovery of these parameters is especially challenging as they are non-linearly related to the measured field. In order to do this we use an empirical Bayesian scheme to estimate the cortical current distribution due to a range of laterally shifted head-models. We compare different methods of approaching this problem from the division of M/EEG data into stationary sections and performing separate source inversions, to explaining all of the M/EEG data with a single inversion. We demonstrate this through estimation of head position in both simulated and empirical resting state MEG data collected using a head-cast. PMID:27597815

Testing the assumption of normality in body sway area calculations during unipedal stance tests with an inertial sensor.

PubMed

Kyoung Jae Kim; Lucarevic, Jennifer; Bennett, Christopher; Gaunaurd, Ignacio; Gailey, Robert; Agrawal, Vibhor

2016-08-01

The quantification of postural sway during the unipedal stance test is one of the essentials of posturography. A shift of center of pressure (CoP) is an indirect measure of postural sway and also a measure of a person's ability to maintain balance. A widely used method in laboratory settings to calculate the sway of body center of mass (CoM) is through an ellipse that encloses 95% of CoP trajectory. The 95% ellipse can be computed under the assumption that the spatial distribution of the CoP points recorded from force platforms is normal. However, to date, this assumption of normality has not been demonstrated for sway measurements recorded from a sacral inertial measurement unit (IMU). This work provides evidence for non-normality of sway trajectories calculated at a sacral IMU with injured subjects as well as healthy subjects.

Geometric correction of synchronous scanned Operational Modular Imaging Spectrometer II hyperspectral remote sensing images using spatial positioning data of an inertial navigation system

NASA Astrophysics Data System (ADS)

Zhou, Xiaohu; Neubauer, Franz; Zhao, Dong; Xu, Shichao

2015-01-01

The high-precision geometric correction of airborne hyperspectral remote sensing image processing was a hard nut to crack, and conventional methods of remote sensing image processing by selecting ground control points to correct the images are not suitable in the correction process of airborne hyperspectral image. The optical scanning system of an inertial measurement unit combined with differential global positioning system (IMU/DGPS) is introduced to correct the synchronous scanned Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing images. Posture parameters, which were synchronized with the OMIS II, were first obtained from the IMU/DGPS. Second, coordinate conversion and flight attitude parameters' calculations were conducted. Third, according to the imaging principle of OMIS II, mathematical correction was applied and the corrected image pixels were resampled. Then, better image processing results were achieved.

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition

PubMed Central

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-01-01

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible. PMID:29695041

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

PubMed

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-04-24

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.

Sampling and Control Circuit Board for an Inertial Measurement Unit

NASA Technical Reports Server (NTRS)

Chelmins, David; Powis, Rick

2012-01-01

Spacesuit navigation is one component of NASA s efforts to return humans to the Moon. Studies performed at the NASA Glenn Research Center (GRC) considered various navigation technologies and filtering approaches to enable navigation on the lunar surface. As part of this effort, microelectromechanical systems (MEMS) inertial measurement units (IMUs) were studied to determine if they could supplement a radiometric infrastructure. MEMS IMUs were included in the Lunar Extra-Vehicular Activity Crewmember Location Determination System (LECLDS) testbed during NASA s annual Desert Research and Technology Studies (D-RATS) event in 2009 and 2010. The testbed included one IMU in 2009 and three IMUs in 2010, along with a custom circuit board interfacing between the navigation processor and each IMU. The board was revised for the 2010 test, and this paper documents the design details of this latest revision of the interface circuit board and firmware.

Self-calibration method of the inner lever-arm parameters for a tri-axis RINS

NASA Astrophysics Data System (ADS)

Song, Tianxiao; Li, Kui; Sui, Jie; Liu, Zengjun; Liu, Juncheng

2017-11-01

A rotational inertial navigation system (RINS) could improve navigation performance by modulating the inertial sensor errors with rotatable gimbals. When an inertial measurement unit (IMU) rotates, the deviations between the accelerometer-sensitive points and the IMU center will lead to an inner lever-arm effect. In this paper, a self-calibration method of the inner lever-arm parameters for a tri-axis RINS is proposed. A novel rotation scheme with variable angular rate rotation is designed to motivate the velocity errors caused by the inner lever-arm effect. By extending all inner lever-arm parameters as filter states, a Kalman filter with velocity errors as measurement is established to achieve the calibration. The accuracy and feasibility of the proposed method are illustrated by both simulations and experiments. The final results indicate that the inner lever-arm effect is significantly restrained after compensation by the calibration results.

Head movement compensation in real-time magnetoencephalographic recordings.

PubMed

Little, Graham; Boe, Shaun; Bardouille, Timothy

2014-01-01

Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimation This work explains the technical details and validates each of these steps.

Human leader and robot follower team: correcting leader's position from follower's heading

NASA Astrophysics Data System (ADS)

Borenstein, Johann; Thomas, David; Sights, Brandon; Ojeda, Lauro; Bankole, Peter; Fellars, Donald

2010-04-01

In multi-agent scenarios, there can be a disparity in the quality of position estimation amongst the various agents. Here, we consider the case of two agents - a leader and a follower - following the same path, in which the follower has a significantly better estimate of position and heading. This may be applicable to many situations, such as a robotic "mule" following a soldier. Another example is that of a convoy, in which only one vehicle (not necessarily the leading one) is instrumented with precision navigation instruments while all other vehicles use lower-precision instruments. We present an algorithm, called Follower-derived Heading Correction (FDHC), which substantially improves estimates of the leader's heading and, subsequently, position. Specifically, FHDC produces a very accurate estimate of heading errors caused by slow-changing errors (e.g., those caused by drift in gyros) of the leader's navigation system and corrects those errors.

A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional ground-water flow model using nonlinear regression

USGS Publications Warehouse

Hill, Mary Catherine

1992-01-01

This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.

Transient Hypermutagenesis Accelerates the Evolution of Legume Endosymbionts following Horizontal Gene Transfer

PubMed Central

Remigi, Philippe; Capela, Delphine; Clerissi, Camille; Tasse, Léna; Torchet, Rachel; Bouchez, Olivier; Batut, Jacques; Cruveiller, Stéphane; Rocha, Eduardo P. C.; Masson-Boivin, Catherine

2014-01-01

Horizontal gene transfer (HGT) is an important mode of adaptation and diversification of prokaryotes and eukaryotes and a major event underlying the emergence of bacterial pathogens and mutualists. Yet it remains unclear how complex phenotypic traits such as the ability to fix nitrogen with legumes have successfully spread over large phylogenetic distances. Here we show, using experimental evolution coupled with whole genome sequencing, that co-transfer of imuABC error-prone DNA polymerase genes with key symbiotic genes accelerates the evolution of a soil bacterium into a legume symbiont. Following introduction of the symbiotic plasmid of Cupriavidus taiwanensis, the Mimosa symbiont, into pathogenic Ralstonia solanacearum we challenged transconjugants to become Mimosa symbionts through serial plant-bacteria co-cultures. We demonstrate that a mutagenesis imuABC cassette encoded on the C. taiwanensis symbiotic plasmid triggered a transient hypermutability stage in R. solanacearum transconjugants that occurred before the cells entered the plant. The generated burst in genetic diversity accelerated symbiotic adaptation of the recipient genome under plant selection pressure, presumably by improving the exploration of the fitness landscape. Finally, we show that plasmid imuABC cassettes are over-represented in rhizobial lineages harboring symbiotic plasmids. Our findings shed light on a mechanism that may have facilitated the dissemination of symbiotic competency among α- and β-proteobacteria in natura and provide evidence for the positive role of environment-induced mutagenesis in the acquisition of a complex lifestyle trait. We speculate that co-transfer of complex phenotypic traits with mutagenesis determinants might frequently enhance the ecological success of HGT. PMID:25181317

Functional characterization of two SOS-regulated genes involved in mitomycin C resistance in Caulobacter crescentus.

PubMed

Lopes-Kulishev, Carina O; Alves, Ingrid R; Valencia, Estela Y; Pidhirnyj, María I; Fernández-Silva, Frank S; Rodrigues, Ticiane R; Guzzo, Cristiane R; Galhardo, Rodrigo S

2015-09-01

The SOS response is a universal bacterial regulon involved in the cellular response to DNA damage and other forms of stress. In Caulobacter crescentus, previous work has identified a plethora of genes that are part of the SOS regulon, but the biological roles of several of them remain to be determined. In this study, we report that two genes, hereafter named mmcA and mmcB, are involved in the defense against DNA damage caused by mitomycin C (MMC), but not against lesions induced by other common DNA damaging agents, such as UVC light, methyl methanesulfonate (MMS) and hydrogen peroxide. mmcA is a conserved gene that encodes a member of the glyoxalases/dioxygenases protein family, and acts independently of known DNA repair pathways. On the other hand, epistasis analysis showed that mmcB acts in the same pathway as imuC (dnaE2), and is required specifically for MMC-induced mutagenesis, but not for that induced by UV light, suggesting a role for MmcB in translesion synthesis-dependent repair of MMC damage. We show that the lack of MMC-induced mutability in the mmcB strain is not caused by lack of proper SOS induction of the imuABC operon, involved in translesion synthesis (TLS) in C. crescentus. Based on this data and on structural analysis of a close homolog, we propose that MmcB is an endonuclease which creates substrates for ImuABC-mediated TLS patches. Copyright © 2015 Elsevier B.V. All rights reserved.

Estimation of body density based on hydrostatic weighing without head submersion in young Japanese adults.

PubMed

Demura, S; Sato, S; Kitabayashi, T

2006-06-01

This study examined a method of predicting body density based on hydrostatic weighing without head submersion (HWwithoutHS). Donnelly and Sintek (1984) developed a method to predict body density based on hydrostatic weight without head submersion. This method predicts the difference (D) between HWwithoutHS and hydrostatic weight with head submersion (HWwithHS) from anthropometric variables (head length and head width), and then calculates body density using D as a correction factor. We developed several prediction equations to estimate D based on head anthropometry and differences between the sexes, and compared their prediction accuracy with Donnelly and Sintek's equation. Thirty-two males and 32 females aged 17-26 years participated in the study. Multiple linear regression analysis was performed to obtain the prediction equations, and the systematic errors of their predictions were assessed by Bland-Altman plots. The best prediction equations obtained were: Males: D(g) = -164.12X1 - 125.81X2 - 111.03X3 + 100.66X4 + 6488.63, where X1 = head length (cm), X2 = head circumference (cm), X3 = head breadth (cm), X4 = head thickness (cm) (R = 0.858, R2 = 0.737, adjusted R2 = 0.687, standard error of the estimate = 224.1); Females: D(g) = -156.03X1 - 14.03X2 - 38.45X3 - 8.87X4 + 7852.45, where X1 = head circumference (cm), X2 = body mass (g), X3 = head length (cm), X4 = height (cm) (R = 0.913, R2 = 0.833, adjusted R2 = 0.808, standard error of the estimate = 137.7). The effective predictors in these prediction equations differed from those of Donnelly and Sintek's equation, and head circumference and head length were included in both equations. The prediction accuracy was improved by statistically selecting effective predictors. Since we did not assess cross-validity, the equations cannot be used to generalize to other populations, and further investigation is required.

Multiple IMU system hardware interface design, volume 2

NASA Technical Reports Server (NTRS)

Landey, M.; Brown, D.

1975-01-01

The design of each system component is described. Emphasis is placed on functional requirements unique in this system, including data bus communication, data bus transmitters and receivers, and ternary-to-binary torquing decision logic. Mechanization drawings are presented.

A Design Study of Onboard Navigation and Guidance During Aerocapture at Mars. M.S. Thesis

NASA Technical Reports Server (NTRS)

Fuhry, Douglas Paul

1988-01-01

The navigation and guidance of a high lift-to-drag ratio sample return vehicle during aerocapture at Mars are investigated. Emphasis is placed on integrated systems design, with guidance algorithm synthesis and analysis based on vehicle state and atmospheric density uncertainty estimates provided by the navigation system. The latter utilizes a Kalman filter for state vector estimation, with useful update information obtained through radar altimeter measurements and density altitude measurements based on IMU-measured drag acceleration. A three-phase guidance algorithm, featuring constant bank numeric predictor/corrector atmospheric capture and exit phases and an extended constant altitude cruise phase, is developed to provide controlled capture and depletion of orbital energy, orbital plane control, and exit apoapsis control. Integrated navigation and guidance systems performance are analyzed using a four degree-of-freedom computer simulation. The simulation environment includes an atmospheric density model with spatially correlated perturbations to provide realistic variations over the vehicle trajectory. Navigation filter initial conditions for the analysis are based on planetary approach optical navigation results. Results from a selection of test cases are presented to give insight into systems performance.

Hybrid Orientation Based Human Limbs Motion Tracking Method

PubMed Central

Glonek, Grzegorz; Wojciechowski, Adam

2017-01-01

One of the key technologies that lays behind the human–machine interaction and human motion diagnosis is the limbs motion tracking. To make the limbs tracking efficient, it must be able to estimate a precise and unambiguous position of each tracked human joint and resulting body part pose. In recent years, body pose estimation became very popular and broadly available for home users because of easy access to cheap tracking devices. Their robustness can be improved by different tracking modes data fusion. The paper defines the novel approach—orientation based data fusion—instead of dominating in literature position based approach, for two classes of tracking devices: depth sensors (i.e., Microsoft Kinect) and inertial measurement units (IMU). The detailed analysis of their working characteristics allowed to elaborate a new method that let fuse more precisely limbs orientation data from both devices and compensates their imprecisions. The paper presents the series of performed experiments that verified the method’s accuracy. This novel approach allowed to outperform the precision of position-based joints tracking, the methods dominating in the literature, of up to 18%. PMID:29232832

A New Blondin System for Surveying and Photogrammetry

PubMed Central

Cuesta, Federico; Lopez-Rodriguez, Francisco M.; Esteban, Antonio

2013-01-01

The main objective of the system presented in this paper is to provide surveyors and engineers with a new photogrammetry device that can be easily integrated with surveying total stations and a global navigation satellite system (GNSS) infrastructure at a construction site, taking advantage of their accuracy and overcoming limitations of aerial vehicles with respect to weight, autonomy and skilled operator requirements in aerial photogrammetry. The system moves between two mounting points, in a blondin ropeway configuration, at the construction site, taking pictures and recording the data of the position and the orientation along the cable path. A cascaded extended Kalman filter is used to integrate measurements from the on-board inertial measurement unit (IMU), a GPS and a GNSS. Experimental results taken in a construction site show the system performance, including the validation of the position estimation, with a robotic surveying total station, or the creation of a digital surface model (DSM), using the emergent structure from motion (SfM) techniques and open software. The georeferencing of the DSM is performed based on estimated camera position or using ground control points (GCPs).

Underwater image mosaicking and visual odometry

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz; Tangirala, Sekhar; Sorber, Scott

2017-05-01

This paper summarizes the results of studies in underwater odometery using a video camera for estimating the velocity of an unmanned underwater vehicle (UUV). Underwater vehicles are usually equipped with sonar and Inertial Measurement Unit (IMU) - an integrated sensor package that combines multiple accelerometers and gyros to produce a three dimensional measurement of both specific force and angular rate with respect to an inertial reference frame for navigation. In this study, we investigate the use of odometry information obtainable from a video camera mounted on a UUV to extract vehicle velocity relative to the ocean floor. A key challenge with this process is the seemingly bland (i.e. featureless) nature of video data obtained underwater which could make conventional approaches to image-based motion estimation difficult. To address this problem, we perform image enhancement, followed by frame to frame image transformation, registration and mosaicking/stitching. With this approach the velocity components associated with the moving sensor (vehicle) are readily obtained from (i) the components of the transform matrix at each frame; (ii) information about the height of the vehicle above the seabed; and (iii) the sensor resolution. Preliminary results are presented.

Indoor Map Aided Wi-Fi Integrated Lbs on Smartphone Platforms

NASA Astrophysics Data System (ADS)

Yu, C.; El-Sheimy, N.

2017-09-01

In this research, an indoor map aided INS/Wi-Fi integrated location based services (LBS) applications is proposed and implemented on smartphone platforms. Indoor map information together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value from Wi-Fi are collected to obtain an accurate, continuous, and low-cost position solution. The main challenge of this research is to make effective use of various measurements that complement each other without increasing the computational burden of the system. The integrated system in this paper includes three modules: INS, Wi-Fi (if signal available) and indoor maps. A cascade structure Particle/Kalman filter framework is applied to combine the different modules. Firstly, INS position and Wi-Fi fingerprint position integrated through Kalman filter for estimating positioning information. Then, indoor map information is applied to correct the error of INS/Wi-Fi estimated position through particle filter. Indoor tests show that the proposed method can effectively reduce the accumulation positioning errors of stand-alone INS systems, and provide stable, continuous and reliable indoor location service.

Covariance analysis for evaluating head trackers

NASA Astrophysics Data System (ADS)

Kang, Donghoon

2017-10-01

Existing methods for evaluating the performance of head trackers usually rely on publicly available face databases, which contain facial images and the ground truths of their corresponding head orientations. However, most of the existing publicly available face databases are constructed by assuming that a frontal head orientation can be determined by compelling the person under examination to look straight ahead at the camera on the first video frame. Since nobody can accurately direct one's head toward the camera, this assumption may be unrealistic. Rather than obtaining estimation errors, we present a method for computing the covariance of estimation error rotations to evaluate the reliability of head trackers. As an uncertainty measure of estimators, the Schatten 2-norm of a square root of error covariance (or the algebraic average of relative error angles) can be used. The merit of the proposed method is that it does not disturb the person under examination by asking him to direct his head toward certain directions. Experimental results using real data validate the usefulness of our method.

Head and neck cancer in South Asia: Macroeconomic consequences and the role of the head and neck surgeon.

PubMed

Alkire, Blake C; Bergmark, Regan W; Chambers, Kyle; Lin, Derrick T; Deschler, Daniel G; Cheney, Mack L; Meara, John G

2016-08-01

Head and neck cancer constitutes a substantial portion of the burden of disease in South Asia, and there is an undersupply of surgical capacity in this region. The purpose of this study was to estimate the economic welfare losses due to head and neck cancer in India, Pakistan, and Bangladesh in 2010. We used publicly available estimates of head and neck cancer morbidity and mortality along with a concept termed the value of a statistical life to estimate economic welfare losses in the aforementioned countries in 2010. Economic losses because of head and neck cancer in India, Pakistan, and Bangladesh totaled $16.9 billion (2010 US dollars [USD]), equivalent to 0.26% of the region's economic output. Bangladesh, the poorest country, experienced the greatest proportional losses. The economic consequences of head and neck cancer in South Asia are significant, and building surgical capacity is essential to begin to address this burden. © 2016 Wiley Periodicals, Inc. Head Neck 38:1242-1247, 2016. © 2016 Wiley Periodicals, Inc.

Learning toward practical head pose estimation

NASA Astrophysics Data System (ADS)

Sang, Gaoli; He, Feixiang; Zhu, Rong; Xuan, Shibin

2017-08-01

Head pose is useful information for many face-related tasks, such as face recognition, behavior analysis, human-computer interfaces, etc. Existing head pose estimation methods usually assume that the face images have been well aligned or that sufficient and precise training data are available. In practical applications, however, these assumptions are very likely to be invalid. This paper first investigates the impact of the failure of these assumptions, i.e., misalignment of face images, uncertainty and undersampling of training data, on head pose estimation accuracy of state-of-the-art methods. A learning-based approach is then designed to enhance the robustness of head pose estimation to these factors. To cope with misalignment, instead of using hand-crafted features, it seeks suitable features by learning from a set of training data with a deep convolutional neural network (DCNN), such that the training data can be best classified into the correct head pose categories. To handle uncertainty and undersampling, it employs multivariate labeling distributions (MLDs) with dense sampling intervals to represent the head pose attributes of face images. The correlation between the features and the dense MLD representations of face images is approximated by a maximum entropy model, whose parameters are optimized on the given training data. To estimate the head pose of a face image, its MLD representation is first computed according to the model based on the features extracted from the image by the trained DCNN, and its head pose is then assumed to be the one corresponding to the peak in its MLD. Evaluation experiments on the Pointing'04, FacePix, Multi-PIE, and CASIA-PEAL databases prove the effectiveness and efficiency of the proposed method.

Heading Estimation for Pedestrian Dead Reckoning Based on Robust Adaptive Kalman Filtering.

PubMed

Wu, Dongjin; Xia, Linyuan; Geng, Jijun

2018-06-19

Pedestrian dead reckoning (PDR) using smart phone-embedded micro-electro-mechanical system (MEMS) sensors plays a key role in ubiquitous localization indoors and outdoors. However, as a relative localization method, it suffers from the problem of error accumulation which prevents it from long term independent running. Heading estimation error is one of the main location error sources, and therefore, in order to improve the location tracking performance of the PDR method in complex environments, an approach based on robust adaptive Kalman filtering (RAKF) for estimating accurate headings is proposed. In our approach, outputs from gyroscope, accelerometer, and magnetometer sensors are fused using the solution of Kalman filtering (KF) that the heading measurements derived from accelerations and magnetic field data are used to correct the states integrated from angular rates. In order to identify and control measurement outliers, a maximum likelihood-type estimator (M-estimator)-based model is used. Moreover, an adaptive factor is applied to resist the negative effects of state model disturbances. Extensive experiments under static and dynamic conditions were conducted in indoor environments. The experimental results demonstrate the proposed approach provides more accurate heading estimates and supports more robust and dynamic adaptive location tracking, compared with methods based on conventional KF.

Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions.

PubMed

Drouard, Vincent; Horaud, Radu; Deleforge, Antoine; Ba, Sileye; Evangelidis, Georgios

2017-03-01

Head-pose estimation has many applications, such as social event analysis, human-robot and human-computer interaction, driving assistance, and so forth. Head-pose estimation is challenging, because it must cope with changing illumination conditions, variabilities in face orientation and in appearance, partial occlusions of facial landmarks, as well as bounding-box-to-face alignment errors. We propose to use a mixture of linear regressions with partially-latent output. This regression method learns to map high-dimensional feature vectors (extracted from bounding boxes of faces) onto the joint space of head-pose angles and bounding-box shifts, such that they are robustly predicted in the presence of unobservable phenomena. We describe in detail the mapping method that combines the merits of unsupervised manifold learning techniques and of mixtures of regressions. We validate our method with three publicly available data sets and we thoroughly benchmark four variants of the proposed algorithm with several state-of-the-art head-pose estimation methods.

Quadrotor helicopter for surface hydrological measurements

NASA Astrophysics Data System (ADS)

Pagano, C.; Tauro, F.; Porfiri, M.; Grimaldi, S.

2013-12-01

Surface hydrological measurements are typically performed through user-assisted and intrusive field methodologies which can be inadequate to monitor remote and extended areas. In this poster, we present the design and development of a quadrotor helicopter equipped with digital acquisition system and image calibration units for surface flow measurements. This custom-built aerial vehicle is engineered to be lightweight, low-cost, highly customizable, and stable to guarantee optimal image quality. Quadricopter stability guarantees minimal vibrations during image acquisition and, therefore, improved accuracy in flow velocity estimation through large scale particle image velocimetry algorithms or particle tracking procedures. Stability during the vehicle pitching and rolling is achieved by adopting large arm span and high-wing configurations. Further, the vehicle framework is composed of lightweight aluminum and durable carbon fiber for optimal resilience. The open source Ardupilot microcontroller is used for remote control of the quadricopter. The microcontroller includes an inertial measurement unit (IMU) equipped with accelerometers and gyroscopes for stable flight through feedback control. The vehicle is powered by a 3 cell (11.1V) 3000 mAh Lithium-polymer battery. Electronic equipment and wiring are hosted into the hollow arms and on several carbon fiber platforms in the waterproof fuselage. Four 35A high-torque motors are supported at the far end of each arm with 10 × 4.7 inch propellers. Energy dissipation during landing is accomplished by four pivoting legs that, through the use of shock absorbers, prevent the impact energy from affecting the frame thus causing significant damage. The data capturing system consists of a GoPro Hero3 camera and in-house built camera gimbal and shock absorber damping device. The camera gimbal, hosted below the vehicle fuselage, is engineered to maintain the orthogonality of the camera axis with respect to the water surface by compensating for changes in pitch and roll during flight. The constant orthogonality of the camera leads to minimal image distortions and, therefore, reduced post-processing for picture dewarping. The gimbal is based on a system of two closed-loop DC motors. The motors are controlled through an open source Martinez V3 brushless controller board and an MPU6050 IMU. The IMU is placed on the back of the camera to read the change in orientation during the flight. To prevent the physical acquisition of ground reference points for image rectification, low power red lasers facing the water surface are placed on each of the quadricopter arms at known distances. The pixel distance between the laser lights in images are then automatically converted to metric units. Experimental results from outdoor testing on water bodies are reported to demonstrate the feasibility of surface water monitoring through this mobile imaging platform.

Inertial sensor self-calibration in a visually-aided navigation approach for a micro-AUV.

PubMed

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P

2015-01-16

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time.

Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV

PubMed Central

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P.

2015-01-01

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time. PMID:25602263

Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture.

PubMed

Hernandez, Andres; Murcia, Harold; Copot, Cosmin; De Keyser, Robin

2015-07-10

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology.

Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture

PubMed Central

Hernandez, Andres; Murcia, Harold; Copot, Cosmin; De Keyser, Robin

2015-01-01

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology. PMID:26184205

Sonographic large fetal head circumference and risk of cesarean delivery.

PubMed

Lipschuetz, Michal; Cohen, Sarah M; Israel, Ariel; Baron, Joel; Porat, Shay; Valsky, Dan V; Yagel, Oren; Amsalem, Hagai; Kabiri, Doron; Gilboa, Yinon; Sivan, Eyal; Unger, Ron; Schiff, Eyal; Hershkovitz, Reli; Yagel, Simcha

2018-03-01

Persistently high rates of cesarean deliveries are cause for concern for physicians, patients, and health systems. Prelabor assessment might be refined by identifying factors that help predict an individual patient's risk of cesarean delivery. Such factors may contribute to patient safety and satisfaction as well as health system planning and resource allocation. In an earlier study, neonatal head circumference was shown to be more strongly associated with delivery mode and other outcome measures than neonatal birthweight. In the present study we aimed to evaluate the association of sonographically measured fetal head circumference measured within 1 week of delivery with delivery mode. This was a multicenter electronic medical record-based study of birth outcomes of primiparous women with term (37-42 weeks) singleton fetuses presenting for ultrasound with fetal biometry within 1 week of delivery. Fetal head circumference and estimated fetal weight were correlated with maternal background, obstetric, and neonatal outcome parameters. Elective cesarean deliveries were excluded. Multinomial regression analysis provided adjusted odds ratios for instrumental delivery and unplanned cesarean delivery when the fetal head circumference was ≥35 cm or estimated fetal weight ≥3900 g, while controlling for possible confounders. In all, 11,500 cases were collected; 906 elective cesarean deliveries were excluded. A fetal head circumference ≥35 cm increased the risk for unplanned cesarean delivery: 174 fetuses with fetal head circumference ≥35 cm (32%) were delivered by cesarean, vs 1712 (17%) when fetal head circumference <35 cm (odds ratio, 2.49; 95% confidence interval, 2.04-3.03). A fetal head circumference ≥35 cm increased the risk of instrumental delivery (odds ratio, 1.48; 95% confidence interval, 1.16-1.88), while estimated fetal weight ≥3900 g tended to reduce it (nonsignificant). Multinomial regression analysis showed that fetal head circumference ≥35 cm increased the risk of unplanned cesarean delivery by an adjusted odds ratio of 1.75 (95% confidence interval, 1.4-2.18) controlling for gestational age, fetal gender, and epidural anesthesia. The rate of prolonged second stage of labor was significantly increased when either the fetal head circumference was ≥35 cm or the estimated fetal weight ≥3900 g, from 22.7% in the total cohort to 31.0%. A fetal head circumference ≥35 cm was associated with a higher rate of 5-minute Apgar score ≤7: 9 (1.7%) vs 63 (0.6%) of infants with fetal head circumference <35 cm (P = .01). The rate among fetuses with an estimated fetal weight ≥3900 g was not significantly increased. The rate of admission to the neonatal intensive care unit did not differ among the groups. Sonographic fetal head circumference ≥35 cm, measured within 1 week of delivery, is an independent risk factor for unplanned cesarean delivery but not instrumental delivery. Both fetal head circumference ≥35 cm and estimated fetal weight ≥3900 g significantly increased the risk of a prolonged second stage of labor. Fetal head circumference measurement in the last days before delivery may be an important adjunct to estimated fetal weight in labor management. Copyright © 2018 Elsevier Inc. All rights reserved.

Shoulder assessment according to the international classification of functioning by means of inertial sensor technologies: A systematic review.

PubMed

De Baets, Liesbet; van der Straaten, Rob; Matheve, Thomas; Timmermans, Annick

2017-09-01

This review investigates current protocols using Inertial Measurement Units (IMUs) in shoulder research, and outlines future paths regarding IMU use for shoulder research. Different databases were searched for relevant articles. Criteria for study selection were (1) research in healthy persons or persons with shoulder problems, (2) IMUs applied as assessment tool for the shoulder (in healthy subjects and shoulder patients) or upper limb (in shoulder patients), (3) peer-reviewed, full-text papers in English or Dutch. Studies with less than five participants and without ethical approval were excluded. Data extraction included (1) study design, (2) participant characteristics, (3) type/brand of IMU, (4) tasks included in the assessment protocol, and (5) outcomes. Risk of bias was assessed using the Downs and Black checklist. Scapulothoracic/glenohumeral and humerothoracic kinematics were reported in respectively 10 and 27 of the 37 included papers. Only one paper in healthy persons assessed, next to scapulothoracic/glenohumeral kinematics, other upper limb joints. IMUs' validity and reliability to capture shoulder function was limited. Considering applied protocols, 39% of the protocols was located on the International-Classification-of-Functioning (ICF) function level, while 38% and 23% were on the 'capacity' and 'actual performance'-sublevel, of the ICF-activity level. Most available IMU-research regarding the shoulder is clinically less relevant, given the widely reported humerothoracic kinematics which do not add to clinical-decision-making, and the absence of protocols assessing the complete upper limb chain. Apart from knowledge on methodological pitfalls and opportunities regarding the use of IMUs, this review provides future research paths. Copyright © 2017 Elsevier B.V. All rights reserved.

Validation of a High Sampling Rate Inertial Measurement Unit for Acceleration During Running.

PubMed

Provot, Thomas; Chiementin, Xavier; Oudin, Emeric; Bolaers, Fabrice; Murer, Sébastien

2017-08-25

The musculo-skeletal response of athletes to various activities during training exercises has become a critical issue in order to optimize their performance and minimize injuries. However, dynamic and kinematic measures of an athlete's activity are generally limited by constraints in data collection and technology. Thus, the choice of reliable and accurate sensors is crucial for gathering data in indoor and outdoor conditions. The aim of this study is to validate the use of the accelerometer of a high sampling rate ( 1344 Hz ) Inertial Measurement Unit (IMU) in the frame of running activities. To this end, two validation protocols are imposed: a classical one on a shaker, followed by another one during running, the IMU being attached to a test subject. For each protocol, the response of the IMU Accelerometer (IMUA) is compared to a calibrated industrial accelerometer, considered as the gold standard for dynamic and kinematic data collection. The repeatability, impact of signal frequency and amplitude (on shaker) as well as the influence of speed (while running) are investigated. Results reveal that the IMUA exhibits good repeatability. Coefficient of Variation CV is 1 % 8.58 ± 0.06 m / s 2 on the shaker and 3 % 26.65 ± 0.69 m / s 2 while running. However, the shaker test shows that the IMUA is affected by the signal frequency (error exceeds 10 % beyond 80 Hz ), an observation confirmed by the running test. Nevertheless, the IMUA provides a reliable measure in the range 0-100 Hz, i.e., the most relevant part in the energy spectrum over the range 0-150 Hz during running. In our view, these findings emphasize the validity of IMUs for the measurement of acceleration during running.

Enhancement Strategies for Frame-To Uas Stereo Visual Odometry

NASA Astrophysics Data System (ADS)

Kersten, J.; Rodehorst, V.

2016-06-01

Autonomous navigation of indoor unmanned aircraft systems (UAS) requires accurate pose estimations usually obtained from indirect measurements. Navigation based on inertial measurement units (IMU) is known to be affected by high drift rates. The incorporation of cameras provides complementary information due to the different underlying measurement principle. The scale ambiguity problem for monocular cameras is avoided when a light-weight stereo camera setup is used. However, also frame-to-frame stereo visual odometry (VO) approaches are known to accumulate pose estimation errors over time. Several valuable real-time capable techniques for outlier detection and drift reduction in frame-to-frame VO, for example robust relative orientation estimation using random sample consensus (RANSAC) and bundle adjustment, are available. This study addresses the problem of choosing appropriate VO components. We propose a frame-to-frame stereo VO method based on carefully selected components and parameters. This method is evaluated regarding the impact and value of different outlier detection and drift-reduction strategies, for example keyframe selection and sparse bundle adjustment (SBA), using reference benchmark data as well as own real stereo data. The experimental results demonstrate that our VO method is able to estimate quite accurate trajectories. Feature bucketing and keyframe selection are simple but effective strategies which further improve the VO results. Furthermore, introducing the stereo baseline constraint in pose graph optimization (PGO) leads to significant improvements.

Multiple IMU system development, volume 1

NASA Technical Reports Server (NTRS)

Landey, M.; Mckern, R.

1974-01-01

A redundant gimballed inertial system is described. System requirements and mechanization methods are defined and hardware and software development is described. Failure detection and isolation algorithms are presented and technology achievements described. Application of the system as a test tool for shuttle avionics concepts is outlined.

Application of Mobile Laser Scanning for Lean and Rapid Highway Maintenance and Construction

DOT National Transportation Integrated Search

2015-08-28

Mobile Terrestrial Laser Scanning (MTLS) is an emerging technology that combines the use of a laser scanner(s), the Global Navigation Satellite System (GNSS), and an Inertial Measurement Unit (IMU) on a vehicle to collect geo-spatial data. The overal...

OLAM: A wearable, non-contact sensor for continuous heart-rate and activity monitoring.

PubMed

Albright, Ryan K; Goska, Benjamin J; Hagen, Tory M; Chi, Mike Y; Cauwenberghs, G; Chiang, Patrick Y

2011-01-01

A wearable, multi-modal sensor is presented that can non-invasively monitor a patient's activity level and heart function concurrently for more than a week. The 4 in(2) sensor incorporates both a non-contact heartrate sensor and a 5-axis inertial measurement unit (IMU), allowing simultaneous heart, respiration, and movement monitoring without requiring physical contact with the skin [1]. Hence, this Oregon State University Life and Activity Monitor (OLAM) provides the unique opportunity to combine motion data with heart-rate information, enabling assessment of actual physical activity beyond conventional movement sensors. OLAM also provides a unique platform for non-contact sensing, enabling the filtering of movement artifacts generated by the non-contact capacitive interface, using the IMU data as a movement noise channel. Intended to be used in clinical trials for weeks at a time with no physician intervention, the OLAM allows continuous non-invasive monitoring of patients, providing the opportunity for long-term observation into a patient's physical activity and subtle longitudinal changes.

Integrated communications and optical navigation system

NASA Astrophysics Data System (ADS)

Mueller, J.; Pajer, G.; Paluszek, M.

2013-12-01

The Integrated Communications and Optical Navigation System (ICONS) is a flexible navigation system for spacecraft that does not require global positioning system (GPS) measurements. The navigation solution is computed using an Unscented Kalman Filter (UKF) that can accept any combination of range, range-rate, planet chord width, landmark, and angle measurements using any celestial object. Both absolute and relative orbit determination is supported. The UKF employs a full nonlinear dynamical model of the orbit including gravity models and disturbance models. The ICONS package also includes attitude determination algorithms using the UKF algorithm with the Inertial Measurement Unit (IMU). The IMU is used as the dynamical base for the attitude determination algorithms. This makes the sensor a more capable plug-in replacement for a star tracker, thus reducing the integration and test cost of adding this sensor to a spacecraft. Recent additions include an integrated optical communications system which adds communications, and integrated range and range rate measurement and timing. The paper includes test results from trajectories based on the NASA New Horizons spacecraft.

Apollo 13 Guidance, Navigation, and Control Challenges

NASA Technical Reports Server (NTRS)

Goodman, John L.

2009-01-01

Combustion and rupture of a liquid oxygen tank during the Apollo 13 mission provides lessons and insights for future spacecraft designers and operations personnel who may never, during their careers, have participated in saving a vehicle and crew during a spacecraft emergency. Guidance, Navigation, and Control (GNC) challenges were the reestablishment of attitude control after the oxygen tank incident, re-establishment of a free return trajectory, resolution of a ground tracking conflict between the LM and the Saturn V S-IVB stage, Inertial Measurement Unit (IMU) alignments, maneuvering to burn attitudes, attitude control during burns, and performing manual GNC tasks with most vehicle systems powered down. Debris illuminated by the Sun and gaseous venting from the Service Module (SM) complicated crew attempts to identify stars and prevented execution of nominal IMU alignment procedures. Sightings on the Sun, Moon, and Earth were used instead. Near continuous communications with Mission Control enabled the crew to quickly perform time critical procedures. Overcoming these challenges required the modification of existing contingency procedures.

An IMU-to-Body Alignment Method Applied to Human Gait Analysis.

PubMed

Vargas-Valencia, Laura Susana; Elias, Arlindo; Rocon, Eduardo; Bastos-Filho, Teodiano; Frizera, Anselmo

2016-12-10

This paper presents a novel calibration procedure as a simple, yet powerful, method to place and align inertial sensors with body segments. The calibration can be easily replicated without the need of any additional tools. The proposed method is validated in three different applications: a computer mathematical simulation; a simplified joint composed of two semi-spheres interconnected by a universal goniometer; and a real gait test with five able-bodied subjects. Simulation results demonstrate that, after the calibration method is applied, the joint angles are correctly measured independently of previous sensor placement on the joint, thus validating the proposed procedure. In the cases of a simplified joint and a real gait test with human volunteers, the method also performs correctly, although secondary plane errors appear when compared with the simulation results. We believe that such errors are caused by limitations of the current inertial measurement unit (IMU) technology and fusion algorithms. In conclusion, the presented calibration procedure is an interesting option to solve the alignment problem when using IMUs for gait analysis.

Indoor Pedestrian Navigation Using Foot-Mounted IMU and Portable Ultrasound Range Sensors

PubMed Central

Girard, Gabriel; Côté, Stéphane; Zlatanova, Sisi; Barette, Yannick; St-Pierre, Johanne; van Oosterom, Peter

2011-01-01

Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians. PMID:22164034

Concept of AHRS Algorithm Designed for Platform Independent Imu Attitude Alignment

NASA Astrophysics Data System (ADS)

Tomaszewski, Dariusz; Rapiński, Jacek; Pelc-Mieczkowska, Renata

2017-12-01

Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.

Towards a neuromorphic vestibular system.

PubMed

Corradi, Federico; Zambrano, Davide; Raglianti, Marco; Passetti, Giovanni; Laschi, Cecilia; Indiveri, Giacomo

2014-10-01

The vestibular system plays a crucial role in the sense of balance and spatial orientation in mammals. It is a sensory system that detects both rotational and translational motion of the head, via its semicircular canals and otoliths respectively. In this work, we propose a real-time hardware model of an artificial vestibular system, implemented using a custom neuromorphic Very Large Scale Integration (VLSI) multi-neuron chip interfaced to a commercial Inertial Measurement Unit (IMU). The artificial vestibular system is realized with spiking neurons that reproduce the responses of biological hair cells present in the real semicircular canals and otholitic organs. We demonstrate the real-time performance of the hybrid analog-digital system and characterize its response properties, presenting measurements of a successful encoding of angular velocities as well as linear accelerations. As an application, we realized a novel implementation of a recurrent integrator network capable of keeping track of the current angular position. The experimental results provided validate the hardware implementation via comparisons with a detailed computational neuroscience model. In addition to being an ideal tool for developing bio-inspired robotic technologies, this work provides a basis for developing a complete low-power neuromorphic vestibular system which integrates the hardware model of the neural signal processing pathway described with custom bio-mimetic gyroscopic sensors, exploiting neuromorphic principles in both mechanical and electronic aspects.

An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis

PubMed Central

Barrois, R.; Gregory, Th.; Oudre, L.; Moreau, Th.; Truong, Ch.; Aram Pulini, A.; Vienne, A.; Labourdette, Ch.; Vayatis, N.; Buffat, S.; Yelnik, A.; de Waele, C.; Laporte, S.; Vidal, P. P.; Ricard, D.

2016-01-01

For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor’s office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient’s home. PMID:27776168

A Role for MST Neurons in Heading Estimation

NASA Technical Reports Server (NTRS)

Stone, L. S.; Perrone, J. A.

1994-01-01

A template model of human visual self-motion perception, which uses neurophysiologically realistic "heading detectors", is consistent with numerous human psychophysical results including the failure of humans to estimate their heading (direction of forward translation) accurately under certain visual conditions. We tested the model detectors with stimuli used by others in single-unit studies. The detectors showed emergent properties similar to those of MST neurons: (1) Sensitivity to non-preferred flow; Each detector is tuned to a specific combination of flow components and its response is systematically reduced by the addition of nonpreferred flow, and (2) Position invariance; The detectors maintain their apparent preference for particular flow components over large regions of their receptive fields. It has been argued that this latter property is incompatible with MST playing a role in heading perception. The model however demonstrates how neurons with the above response properties could still support accurate heading estimation within extrastriate cortical maps.

Modeling heading and path perception from optic flow in the case of independently moving objects

PubMed Central

Raudies, Florian; Neumann, Heiko

2013-01-01

Humans are usually accurate when estimating heading or path from optic flow, even in the presence of independently moving objects (IMOs) in an otherwise rigid scene. To invoke significant biases in perceived heading, IMOs have to be large and obscure the focus of expansion (FOE) in the image plane, which is the point of approach. For the estimation of path during curvilinear self-motion no significant biases were found in the presence of IMOs. What makes humans robust in their estimation of heading or path using optic flow? We derive analytical models of optic flow for linear and curvilinear self-motion using geometric scene models. Heading biases of a linear least squares method, which builds upon these analytical models, are large, larger than those reported for humans. This motivated us to study segmentation cues that are available from optic flow. We derive models of accretion/deletion, expansion/contraction, acceleration/deceleration, local spatial curvature, and local temporal curvature, to be used as cues to segment an IMO from the background. Integrating these segmentation cues into our method of estimating heading or path now explains human psychophysical data and extends, as well as unifies, previous investigations. Our analysis suggests that various cues available from optic flow help to segment IMOs and, thus, make humans' heading and path perception robust in the presence of such IMOs. PMID:23554589

Estimating the variance and integral scale of the transmissivity field using head residual increments

USGS Publications Warehouse

Zheng, Li; Silliman, Stephen E.

2000-01-01

A modification of previously published solutions regarding the spatial variation of hydraulic heads is discussed whereby the semivariogram of increments of head residuals (termed head residual increments HRIs) are related to the variance and integral scale of the transmissivity field. A first‐order solution is developed for the case of a transmissivity field which is isotropic and whose second‐order behavior can be characterized by an exponential covariance structure. The estimates of the variance σY2 and the integral scale λ of the log transmissivity field are then obtained via fitting a theoretical semivariogram for the HRI to its sample semivariogram. This approach is applied to head data sampled from a series of two‐dimensional, simulated aquifers with isotropic, exponential covariance structures and varying degrees of heterogeneity (σY2 = 0.25, 0.5, 1.0, 2.0, and 5.0). The results show that this method provided reliable estimates for both λ and σY2 in aquifers with the value of σY2 up to 2.0, but the errors in those estimates were higher for σY2 equal to 5.0. It is also demonstrated through numerical experiments and theoretical arguments that the head residual increments will provide a sample semivariogram with a lower variance than will the use of the head residuals without calculation of increments.

Effect of parental head circumference on that of the newborn child.

PubMed Central

Osborne, J; Havalad, S; Hudson, B; Hughes, A

1980-01-01

The head circumferences of 74 term, normal babies were measured, together with the head circumferences of their parents. Maternal head circumference had a significant effect on that of the newborn infant but paternal head circumference had not. An equation is given for estimating the expected head circumference of a newborn infant, provided the birthweight and maternal head circumference are known. PMID:7436491

An evaluation of 3D head pose estimation using the Microsoft Kinect v2.

PubMed

Darby, John; Sánchez, María B; Butler, Penelope B; Loram, Ian D

2016-07-01

The Kinect v2 sensor supports real-time non-invasive 3D head pose estimation. Because the sensor is small, widely available and relatively cheap it has great potential as a tool for groups interested in measuring head posture. In this paper we compare the Kinect's head pose estimates with a marker-based record of ground truth in order to establish its accuracy. During movement of the head and neck alone (with static torso), we find average errors in absolute yaw, pitch and roll angles of 2.0±1.2°, 7.3±3.2° and 2.6±0.7°, and in rotations relative to the rest pose of 1.4±0.5°, 2.1±0.4° and 2.0±0.8°. Larger head rotations where it becomes difficult to see facial features can cause estimation to fail (10.2±6.1% of all poses in our static torso range of motion tests) but we found no significant changes in performance with the participant standing further away from Kinect - additionally enabling full-body pose estimation - or without performing face shape calibration, something which is not always possible for younger or disabled participants. Where facial features remain visible, the sensor has applications in the non-invasive assessment of postural control, e.g. during a programme of physical therapy. In particular, a multi-Kinect setup covering the full range of head (and body) movement would appear to be a promising way forward. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimal estimation of spatially variable recharge and transmissivity fields under steady-state groundwater flow. Part 1. Theory

NASA Astrophysics Data System (ADS)

Graham, Wendy D.; Tankersley, Claude D.

1994-05-01

Stochastic methods are used to analyze two-dimensional steady groundwater flow subject to spatially variable recharge and transmissivity. Approximate partial differential equations are developed for the covariances and cross-covariances between the random head, transmissivity and recharge fields. Closed-form solutions of these equations are obtained using Fourier transform techniques. The resulting covariances and cross-covariances can be incorporated into a Bayesian conditioning procedure which provides optimal estimates of the recharge, transmissivity and head fields given available measurements of any or all of these random fields. Results show that head measurements contain valuable information for estimating the random recharge field. However, when recharge is treated as a spatially variable random field, the value of head measurements for estimating the transmissivity field can be reduced considerably. In a companion paper, the method is applied to a case study of the Upper Floridan Aquifer in NE Florida.

GOES-R active vibration damping controller design, implementation, and on-orbit performance

NASA Astrophysics Data System (ADS)

Clapp, Brian R.; Weigl, Harald J.; Goodzeit, Neil E.; Carter, Delano R.; Rood, Timothy J.

2018-01-01

GOES-R series spacecraft feature a number of flexible appendages with modal frequencies below 3.0 Hz which, if excited by spacecraft disturbances, can be sources of undesirable jitter perturbing spacecraft pointing. To meet GOES-R pointing stability requirements, the spacecraft flight software implements an Active Vibration Damping (AVD) rate control law which acts in parallel with the nadir point attitude control law. The AVD controller commands spacecraft reaction wheel actuators based upon Inertial Measurement Unit (IMU) inputs to provide additional damping for spacecraft structural modes below 3.0 Hz which vary with solar wing angle. A GOES-R spacecraft dynamics and attitude control system identified model is constructed from pseudo-random reaction wheel torque commands and IMU angular rate response measurements occurring over a single orbit during spacecraft post-deployment activities. The identified Fourier model is computed on the ground, uplinked to the spacecraft flight computer, and the AVD controller filter coefficients are periodically computed on-board from the Fourier model. Consequently, the AVD controller formulation is based not upon pre-launch simulation model estimates but upon on-orbit nadir point attitude control and time-varying spacecraft dynamics. GOES-R high-fidelity time domain simulation results herein demonstrate the accuracy of the AVD identified Fourier model relative to the pre-launch spacecraft dynamics and control truth model. The AVD controller on-board the GOES-16 spacecraft achieves more than a ten-fold increase in structural mode damping for the fundamental solar wing mode while maintaining controller stability margins and ensuring that the nadir point attitude control bandwidth does not fall below 0.02 Hz. On-orbit GOES-16 spacecraft appendage modal frequencies and damping ratios are quantified based upon the AVD system identification, and the increase in modal damping provided by the AVD controller for each structural mode is presented. The GOES-16 spacecraft AVD controller frequency domain stability margins and nadir point attitude control bandwidth are presented along with on-orbit time domain disturbance response performance.

GOES-R Active Vibration Damping Controller Design, Implementation, and On-Orbit Performance

NASA Technical Reports Server (NTRS)

Clapp, Brian R.; Weigl, Harald J.; Goodzeit, Neil E.; Carter, Delano R.; Rood, Timothy J.

2017-01-01

GOES-R series spacecraft feature a number of flexible appendages with modal frequencies below 3.0 Hz which, if excited by spacecraft disturbances, can be sources of undesirable jitter perturbing spacecraft pointing. In order to meet GOES-R pointing stability requirements, the spacecraft flight software implements an Active Vibration Damping (AVD) rate control law which acts in parallel with the nadir point attitude control law. The AVD controller commands spacecraft reaction wheel actuators based upon Inertial Measurement Unit (IMU) inputs to provide additional damping for spacecraft structural modes below 3.0 Hz which vary with solar wing angle. A GOES-R spacecraft dynamics and attitude control system identified model is constructed from pseudo-random reaction wheel torque commands and IMU angular rate response measurements occurring over a single orbit during spacecraft post-deployment activities. The identified Fourier model is computed on the ground, uplinked to the spacecraft flight computer, and the AVD controller filter coefficients are periodically computed on-board from the Fourier model. Consequently, the AVD controller formulation is based not upon pre-launch simulation model estimates but upon on-orbit nadir point attitude control and time-varying spacecraft dynamics. GOES-R high-fidelity time domain simulation results herein demonstrate the accuracy of the AVD identified Fourier model relative to the pre-launch spacecraft dynamics and control truth model. The AVD controller on-board the GOES-16 spacecraft achieves more than a ten-fold increase in structural mode damping of the fundamental solar wing mode while maintaining controller stability margins and ensuring that the nadir point attitude control bandwidth does not fall below 0.02 Hz. On-orbit GOES-16 spacecraft appendage modal frequencies and damping ratios are quantified based upon the AVD system identification, and the increase in modal damping provided by the AVD controller for each structural mode is presented. The GOES-16 spacecraft AVD controller frequency domain stability margins and nadir point attitude control bandwidth are presented along with on-orbit time domain disturbance response performance.

Small satellite attitude determination based on GPS/IMU data fusion

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

Golovan, Andrey; Cepe, Ali

In this paper, we present the mathematical models and algorithms that describe the problem of attitude determination for a small satellite using measurements from three angular rate sensors (ARS) and aiding measurements from multiple GPS receivers/antennas rigidly attached to the platform of the satellite.

Integrated Multiple Device CMOS-MEMS IMU Systems and RF MEMS Applications

DTIC Science & Technology

2002-12-17

microstructures [7]~[9]. The success of the surface-micromachined electrostatic micromotor in the late 80’s [10] stimulated the industry and government...processed electrostatic synchronous micromotors ,” Sensors Actuators, vol. 20, pp. 48-56, 1989. [11] “ADXL05-monolithic accelerometer with signal

Body mass and stature estimation based on the first metatarsal in humans.

PubMed

De Groote, Isabelle; Humphrey, Louise T

2011-04-01

Archaeological assemblages often lack the complete long bones needed to estimate stature and body mass. The most accurate estimates of body mass and stature are produced using femoral head diameter and femur length. Foot bones including the first metatarsal preserve relatively well in a range of archaeological contexts. In this article we present regression equations using the first metatarsal to estimate femoral head diameter, femoral length, and body mass in a diverse human sample. The skeletal sample comprised 87 individuals (Andamanese, Australasians, Africans, Native Americans, and British). Results show that all first metatarsal measurements correlate moderately to highly (r = 0.62-0.91) with femoral head diameter and length. The proximal articular dorsoplantar diameter is the best single measurement to predict both femoral dimensions. Percent standard errors of the estimate are below 5%. Equations using two metatarsal measurements show a small increase in accuracy. Direct estimations of body mass (calculated from measured femoral head diameter using previously published equations) have an error of just over 7%. No direct stature estimation equations were derived due to the varied linear body proportions represented in the sample. The equations were tested on a sample of 35 individuals from Christ Church Spitalfields. Percentage differences in estimated and measured femoral head diameter and length were less than 1%. This study demonstrates that it is feasible to use the first metatarsal in the estimation of body mass and stature. The equations presented here are particularly useful for assemblages where the long bones are either missing or fragmented, and enable estimation of these fundamental population parameters in poorly preserved assemblages. Copyright © 2011 Wiley-Liss, Inc.

Estimating 3D topographic map of optic nerve head from a single fundus image

NASA Astrophysics Data System (ADS)

Wang, Peipei; Sun, Jiuai

2018-04-01

Optic nerve head also called optic disc is the distal portion of optic nerve locating and clinically visible on the retinal surface. It is a 3 dimensional elliptical shaped structure with a central depression called the optic cup. This shape of the ONH and the size of the depression can be varied due to different retinopathy or angiopathy, therefore the estimation of topography of optic nerve head is significant for assisting diagnosis of those retinal related complications. This work describes a computer vision based method, i.e. shape from shading (SFS) to recover and visualize 3D topographic map of optic nerve head from a normal fundus image. The work is expected helpful for assessing those complications associated the deformation of optic nerve head such as glaucoma and diabetes. The illumination is modelled as uniform over the area around optic nerve head and its direction estimated from the available image. The Tsai discrete method has been employed to recover the 3D topographic map of the optic nerve head. The initial experimental result demonstrates our approach works on most of fundus images and provides a cheap, but good alternation for rendering and visualizing the topographic information of the optic nerve head for potential clinical use.

A head motion estimation algorithm for motion artifact correction in dental CT imaging

NASA Astrophysics Data System (ADS)

Hernandez, Daniel; Elsayed Eldib, Mohamed; Hegazy, Mohamed A. A.; Hye Cho, Myung; Cho, Min Hyoung; Lee, Soo Yeol

2018-03-01

A small head motion of the patient can compromise the image quality in a dental CT, in which a slow cone-beam scan is adopted. We introduce a retrospective head motion estimation method by which we can estimate the motion waveform from the projection images without employing any external motion monitoring devices. We compute the cross-correlation between every two successive projection images, which results in a sinusoid-like displacement curve over the projection view when there is no patient motion. However, the displacement curve deviates from the sinusoid-like form when patient motion occurs. We develop a method to estimate the motion waveform with a single parameter derived from the displacement curve with aid of image entropy minimization. To verify the motion estimation method, we use a lab-built micro-CT that can emulate major head motions during dental CT scans, such as tilting and nodding, in a controlled way. We find that the estimated motion waveform conforms well to the actual motion waveform. To further verify the motion estimation method, we correct the motion artifacts with the estimated motion waveform. After motion artifact correction, the corrected images look almost identical to the reference images, with structural similarity index values greater than 0.81 in the phantom and rat imaging studies.

A Kindergarten Teacher Bringing Science to a Community

ERIC Educational Resources Information Center

Theis, Becky; Galindo, Ed; Shockey, Tod

2014-01-01

The National Aeronautical and Space Administration (NASA) sponsored professional development of educators in the NASA Summer of Innovation (SOI) program. The Idaho, Montana, and Utah (IMU-SOI) program worked with educators and students from thirteen Native American communities. The summer sessions were focused on problem based learning and…

Car Accident Reconstruction and Head Injury Correlation

NASA Astrophysics Data System (ADS)

Chawla, A.; Grover, V.; Mukherjee, S.; Hassan, A. M.

2013-04-01

Estimation of brain damage remains an elusive issue and controlled tests leading to brain damage cannot be carried out on volunteers. This study reconstructs real-world car accidents to estimate the kinematics of the head impact. This data is to be used to estimate the head injury measures through computer simulations and then correlate reported skull as well as brain damage to impact measures; whence validating the head FE model (Willinger, IJCrash 8:605-617, 2003). In this study, two crash cases were reconstructed. Injury correlation was successful in one of these cases in that the injuries to the brain of one of the car drivers could be correlated in terms of type, location and severity when compared with the tolerance limits of relevant injury parameters (Willinger, IJCrash 8:605-617, 2003).

Engineering description of the ascent/descent bet product

NASA Technical Reports Server (NTRS)

Seacord, A. W., II

1986-01-01

The Ascent/Descent output product is produced in the OPIP routine from three files which constitute its input. One of these, OPIP.IN, contains mission specific parameters. Meteorological data, such as atmospheric wind velocities, temperatures, and density, are obtained from the second file, the Corrected Meteorological Data File (METDATA). The third file is the TRJATTDATA file which contains the time-tagged state vectors that combine trajectory information from the Best Estimate of Trajectory (BET) filter, LBRET5, and Best Estimate of Attitude (BEA) derived from IMU telemetry. Each term in the two output data files (BETDATA and the Navigation Block, or NAVBLK) are defined. The description of the BETDATA file includes an outline of the algorithm used to calculate each term. To facilitate describing the algorithms, a nomenclature is defined. The description of the nomenclature includes a definition of the coordinate systems used. The NAVBLK file contains navigation input parameters. Each term in NAVBLK is defined and its source is listed. The production of NAVBLK requires only two computational algorithms. These two algorithms, which compute the terms DELTA and RSUBO, are described. Finally, the distribution of data in the NAVBLK records is listed.

3D indoor modeling using a hand-held embedded system with multiple laser range scanners

NASA Astrophysics Data System (ADS)

Hu, Shaoxing; Wang, Duhu; Xu, Shike

2016-10-01

Accurate three-dimensional perception is a key technology for many engineering applications, including mobile mapping, obstacle detection and virtual reality. In this article, we present a hand-held embedded system designed for constructing 3D representation of structured indoor environments. Different from traditional vehicle-borne mobile mapping methods, the system presented here is capable of efficiently acquiring 3D data while an operator carrying the device traverses through the site. It consists of a simultaneous localization and mapping(SLAM) module, a 3D attitude estimate module and a point cloud processing module. The SLAM is based on a scan matching approach using a modern LIDAR system, and the 3D attitude estimate is generated by a navigation filter using inertial sensors. The hardware comprises three 2D time-flight laser range finders and an inertial measurement unit(IMU). All the sensors are rigidly mounted on a body frame. The algorithms are developed on the frame of robot operating system(ROS). The 3D model is constructed using the point cloud library(PCL). Multiple datasets have shown robust performance of the presented system in indoor scenarios.

A Stationary North-Finding Scheme for an Azimuth Rotational IMU Utilizing a Linear State Equality Constraint

PubMed Central

Yu, Huapeng; Zhu, Hai; Gao, Dayuan; Yu, Meng; Wu, Wenqi

2015-01-01

The Kalman filter (KF) has always been used to improve north-finding performance under practical conditions. By analyzing the characteristics of the azimuth rotational inertial measurement unit (ARIMU) on a stationary base, a linear state equality constraint for the conventional KF used in the fine north-finding filtering phase is derived. Then, a constrained KF using the state equality constraint is proposed and studied in depth. Estimation behaviors of the concerned navigation errors when implementing the conventional KF scheme and the constrained KF scheme during stationary north-finding are investigated analytically by the stochastic observability approach, which can provide explicit formulations of the navigation errors with influencing variables. Finally, multiple practical experimental tests at a fixed position are done on a postulate system to compare the stationary north-finding performance of the two filtering schemes. In conclusion, this study has successfully extended the utilization of the stochastic observability approach for analytic descriptions of estimation behaviors of the concerned navigation errors, and the constrained KF scheme has demonstrated its superiority over the conventional KF scheme for ARIMU stationary north-finding both theoretically and practically. PMID:25688588

Fracture mechanics approach to estimate rail wear limits

DOT National Transportation Integrated Search

2009-10-01

This paper describes a systematic methodology to estimate allowable limits for rail head wear in terms of vertical head-height loss, gage-face side wear, and/or the combination of the two. This methodology is based on the principles of engineering fr...

Erosion estimation of guide vane end clearance in hydraulic turbines with sediment water flow

NASA Astrophysics Data System (ADS)

Han, Wei; Kang, Jingbo; Wang, Jie; Peng, Guoyi; Li, Lianyuan; Su, Min

2018-04-01

The end surface of guide vane or head cover is one of the most serious parts of sediment erosion for high-head hydraulic turbines. In order to investigate the relationship between erosion depth of wall surface and the characteristic parameter of erosion, an estimative method including a simplified flow model and a modificatory erosion calculative function is proposed in this paper. The flow between the end surfaces of guide vane and head cover is simplified as a clearance flow around a circular cylinder with a backward facing step. Erosion characteristic parameter of csws3 is calculated with the mixture model for multiphase flow and the renormalization group (RNG) k-𝜀 turbulence model under the actual working conditions, based on which, erosion depths of guide vane and head cover end surfaces are estimated with a modification of erosion coefficient K. The estimation results agree well with the actual situation. It is shown that the estimative method is reasonable for erosion prediction of guide vane and can provide a significant reference to determine the optimal maintenance cycle for hydraulic turbine in the future.

Self-motion magnitude estimation during linear oscillation - Changes with head orientation and following fatigue

NASA Technical Reports Server (NTRS)

Parker, D. E.; Wood, D. L.; Gulledge, W. L.; Goodrich, R. L.

1979-01-01

Two types of experiments concerning the estimated magnitude of self-motion during exposure to linear oscillation on a parallel swing are described in this paper. Experiment I examined changes in magnitude estimation as a function of variation of the subject's head orientation, and Experiments II a, II b, and II c assessed changes in magnitude estimation performance following exposure to sustained, 'intense' linear oscillation (fatigue-inducting stimulation). The subjects' performance was summarized employing Stevens' power law R = k x S to the nth, where R is perceived self-motion magnitude, k is a constant, S is amplitude of linear oscillation, and n is an exponent). The results of Experiment I indicated that the exponents, n, for the magnitude estimation functions varied with head orientation and were greatest when the head was oriented 135 deg off the vertical. In Experiments II a-c, the magnitude estimation function exponents were increased following fatigue. Both types of experiments suggest ways in which the vestibular system's contribution to a spatial orientation perceptual system may vary. This variability may be a contributing factor to the development of pilot/astronaut disorientation and may also be implicated in the occurrence of motion sickness.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.

2015-08-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian

2016-05-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Application of Multifunctional Doppler LIDAR for Noncontact Track Speed, Distance, and Curvature Assessment

NASA Astrophysics Data System (ADS)

Munoz, Joshua

The primary focus of this research is evaluation of feasibility, applicability, and accuracy of Doppler Light Detection And Ranging (LIDAR) sensors as non-contact means for measuring track speed, distance traveled, and curvature. Speed histories, currently measured with a rotary, wheelmounted encoder, serve a number of useful purposes, one significant use involving derailment investigations. Distance calculation provides a spatial reference system for operators to locate track sections of interest. Railroad curves, using an IMU to measure curvature, are monitored to maintain track infrastructure within regulations. Speed measured with high accuracy leads to highfidelity distance and curvature data through utilization of processor clock rate and left-and rightrail speed differentials during curve navigation, respectively. Wheel-mounted encoders, or tachometers, provide a relatively low-resolution speed profile, exhibit increased noise with increasing speed, and are subject to the inertial behavior of the rail car which affects output data. The IMU used to measure curvature is dependent on acceleration and yaw rate sensitivity and experiences difficulty in low-speed conditions. Preliminary system tests onboard a "Hy-Rail" utility vehicle capable of traveling on rail show speed capture is possible using the rails as the reference moving target and furthermore, obtaining speed profiles from both rails allows for the calculation of speed differentials in curves to estimate degrees curvature. Ground truth distance calibration and curve measurement were also carried out. Distance calibration involved placement of spatial landmarks detected by a sensor to synchronize distance measurements as a pre-processing procedure. Curvature ground truth measurements provided a reference system to confirm measurement results and observe alignment variation throughout a curve. Primary testing occurred onboard a track geometry rail car, measuring rail speed over substantial mileage in various weather conditions, providing highaccuracy data to further calculate distance and curvature along the test routes. Tests results indicate the LIDAR system measures speed at higher accuracy than the encoder, absent of noise influenced by increasing speed. Distance calculation is also high in accuracy, results showing high correlation with encoder and ground truth data. Finally, curvature calculation using speed data is shown to have good correlation with IMU measurements and a resolution capable of revealing localized track alignments. Further investigations involve a curve measurement algorithm and speed calibration method independent from external reference systems, namely encoder and ground truth data. The speed calibration results show a high correlation with speed data from the track geometry vehicle. It is recommended that the study be extended to provide assessment of the LIDAR's sensitivity to car body motion in order to better isolate the embedded behavior in the speed and curvature profiles. Furthermore, in the interest of progressing the system toward a commercially viable unit, methods for self-calibration and pre-processing to allow for fully independent operation is highly encouraged.

Detailed Test Plan Redundant Sensor Strapdown IMU Evaluation Program

NASA Technical Reports Server (NTRS)

Hartwell, T.; Miyatake, Y.; Wedekind, D. E.

1971-01-01

The test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The subjects discussed are: (1) test philosophy and limitations, (2) test sequence, (3) equipment specifications, (4) general operating procedures, (5) calibration procedures, (6) alignment test phase, and (7) navigation test phase. The data and analysis requirements are analyzed.

Quantifying infant physical interactions using sensorized toys in a natural play environment.

PubMed

Goyal, Vatsala; Torres, Wilson; Rai, Roshan; Shofer, Frances; Bogen, Daniel; Bryant, Phillip; Prosser, Laura; Johnson, Michelle J

2017-07-01

Infants with developmental delays must be detected early in their development to minimize the progression of motor and neurological impairments. Our objective is to quantify how sensorized toys in a natural play environment can promote infant-toy physical interactions. We created a hanging elephant toy, equipped with an inertial measurement unit (IMU), a pressure transducer, and multiple feedback sensors, to be a hand-grasping toy. We used a 3 DoF robotic model with inputs from the IMU to calculate multiple kinematic metrics and an equation to calculate haptic metrics from the pressure transducer. Six typical infants were tested in the gym set-up. Three infants interacted with the toy for more than half the trial time. The youngest infant exhibited the largest toy displacement with ΔD = 27.6 cm, while the oldest infant squeezed the toy with the largest mean pressure of 4.5 kPa. More data on on both typical and atypical infants needs to be collected. After testing atypical infants in the SmarToyGym set-up, we will be able to identify interaction metrics that differentiate atypical and typical infants.

An IMU-to-Body Alignment Method Applied to Human Gait Analysis

PubMed Central

Vargas-Valencia, Laura Susana; Elias, Arlindo; Rocon, Eduardo; Bastos-Filho, Teodiano; Frizera, Anselmo

2016-01-01

This paper presents a novel calibration procedure as a simple, yet powerful, method to place and align inertial sensors with body segments. The calibration can be easily replicated without the need of any additional tools. The proposed method is validated in three different applications: a computer mathematical simulation; a simplified joint composed of two semi-spheres interconnected by a universal goniometer; and a real gait test with five able-bodied subjects. Simulation results demonstrate that, after the calibration method is applied, the joint angles are correctly measured independently of previous sensor placement on the joint, thus validating the proposed procedure. In the cases of a simplified joint and a real gait test with human volunteers, the method also performs correctly, although secondary plane errors appear when compared with the simulation results. We believe that such errors are caused by limitations of the current inertial measurement unit (IMU) technology and fusion algorithms. In conclusion, the presented calibration procedure is an interesting option to solve the alignment problem when using IMUs for gait analysis. PMID:27973406

A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint

PubMed Central

Zou, Jiaheng

2018-01-01

With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location with as little given information as possible. This paper presents a foot-mounted inertial measurement unit (IMU) positioning algorithm under the loop closure constraint based on magnetic information. It can provide relatively reliable position information without maps and geomagnetic information and provides a relatively accurate coordinate for the collection of a fingerprint database. In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. The average error of the trajectory under loop closure constraint is controlled below 2.15 m. PMID:29494542

A Foot-Mounted Inertial Measurement Unit (IMU) Positioning Algorithm Based on Magnetic Constraint.

PubMed

Wang, Yan; Li, Xin; Zou, Jiaheng

2018-03-01

With the development of related applications, indoor positioning techniques have been more and more widely developed. Based on Wi-Fi, Bluetooth low energy (BLE) and geomagnetism, indoor positioning techniques often rely on the physical location of fingerprint information. The focus and difficulty of establishing the fingerprint database are in obtaining a relatively accurate physical location with as little given information as possible. This paper presents a foot-mounted inertial measurement unit (IMU) positioning algorithm under the loop closure constraint based on magnetic information. It can provide relatively reliable position information without maps and geomagnetic information and provides a relatively accurate coordinate for the collection of a fingerprint database. In the experiment, the features extracted by the multi-level Fourier transform method proposed in this paper are validated and the validity of loop closure matching is tested with a RANSAC-based method. Moreover, the loop closure detection results show that the cumulative error of the trajectory processed by the graph optimization algorithm is significantly suppressed, presenting a good accuracy. The average error of the trajectory under loop closure constraint is controlled below 2.15 m.

Thermal assessment of sunlight impinging on OSIRIS-REx OCAMS PolyCam, OTES, and IMU-sunshade MLI blankets in flight

NASA Astrophysics Data System (ADS)

Choi, Michael K.

2017-09-01

The NASA Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer (OSIRIS-REx) spacecraft was successfully launched into orbit on September 8, 2016. It is traveling to a near-Earth asteroid (101955) Bennu, study it in detail, and bring back a pristine sample to Earth for scientific analyses. At the Outbound Cruise nominal spacecraft attitude, with Sun on +X, sunlight impinges on the OSIRIS-REx camera suite (OCAMS) PolyCam sunshade multilayer insulation (MLI) with microporous black polytetrafluoroethylene (PTFE), a portion of the PolyCam optics support tube (MLI with germanium black Kapton (GBK)), a portion of the OSIRIS-REx Thermal Emission Spectrometer (OTES) sunshade (MLI with GBK), the Inertia Measurement Unit (IMU) sunshade (MLI with GBK), and the OSIRIS-REx Laser Altimeter (OLA) sunshade (MLI with GBK). Sunlight is reflected or scattered by the above MLIs to the other components on the forward (+Z) deck. It illuminates the forward deck. A detailed thermal assessment on the solar impingement has been performed for the Proximity Ops at the asteroid, Touch-and-Go sample acquisition, and Return Cruise mission phases.

A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments

PubMed Central

López, Elena; García, Sergio; Barea, Rafael; Bergasa, Luis M.; Molinos, Eduardo J.; Arroyo, Roberto; Romera, Eduardo; Pardo, Samuel

2017-01-01

One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory configuration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To do this, a minimum onboard sensory configuration is supposed, consisting of a monocular camera, an Inertial Measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (LSD-SLAM and ORB-SLAM are tested and compared in this work) by solving scale ambiguity and providing additional information to the EKF. When payload and computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2.5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with two different commercial platforms, and validate the system by applying it to their position control. PMID:28397758

Mars Aerobraking Spacecraft State Estimation by Processing Inertial Measurement Unit Data

NASA Technical Reports Server (NTRS)

Jah, Moriba K.; Lisano, Michael E.,, II; Born, George H.; Axelrad, Penina

2006-01-01

Aerobraking is an efficient technique for orbit adjustment of planetary spacecraft, such as Magellan (Venus), Mars Global Surveyor, and Mars Odyssey. Determination of the vehicle state during the aerobraking phase has conventionally been performed using only radiometric tracking data prior to and following the atmospheric drag pass. This approach is sufficiently accurate and timely to meet current mission operational requirements; however, it is expensive in terms of ground support and leads to delayed results because ofthe need for post-drag pass data. This research presents a new approach to estimation of the vehicle state during the atmospheric pass that sequentially incorporates observations from an Inertial Measurement Unit (IMU) and models of the vehicle and environment. The approach, called Inertial Measurements for Aerobraking Navigation (IMAN), is shown to perform at a level comparable to the conventional methods in terms of navigation accuracy and superior to them in terms of availability of the results immediately after completion ofthe pass. Furthermore, the research shows that IMAN can be used to reliably predict subsequent periapsis times and locations over all aerobraking regimes. IMAN also yields accurate peak dynamic pressure and heating rates, critical for a successful corridor control strategy, comparable to navigation team reconstructed values. This research also provides the first instance of the utilization of the Unscented Kalman Filter for the purpose of estimating an actual spacecraft trajectory arc about another planet.

Mars aerobraking spacecraft state estimation by processing inertial measurement unit data

NASA Astrophysics Data System (ADS)

Jah, Moriba Kemessia

Aerobraking is an efficient technique for orbit adjustment of planetary spacecraft such as Magellan (Venus), Mars Global Surveyor, and Mars Odyssey. Determination of the vehicle state during the Aerobraking phase has conventionally been performed using only radiometric tracking data prior to and following the atmospheric drag pass. This approach is sufficiently accurate and timely to meet current mission operational requirements; however, it is expensive in terms of ground support and leads to delayed results because of the need for post drag pass data. This dissertation presents a new approach to estimation of the vehicle state during the atmospheric pass that sequentially incorporates observations from an Inertial Measurement Unit (IMU) and models of the vehicle and environment. The approach, called Inertial Measurements for Aerobraking Navigation (IMAN), is shown to perform at a level comparable to the conventional methods in terms of navigation accuracy and superior to them in terms of availability of the results immediately after completion of the pass. Furthermore, the research shows that IMAN can be used to reliably predict subsequent periapsis times and locations over all aerobraking regimes. IMAN also yields accurate peak dynamic pressure and heating rates, critical for a successful corridor control strategy, comparable to navigation team reconstructed values. This research also provides the first instance of the utilization of the Unscented Kalman Filter for the purpose of estimating an actual spacecraft trajectory arc about another planet.

Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation.

PubMed

Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin

2014-03-01

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.

Influence of visual path information on human heading perception during rotation.

PubMed

Li, Li; Chen, Jing; Peng, Xiaozhe

2009-03-31

How does visual path information influence people's perception of their instantaneous direction of self-motion (heading)? We have previously shown that humans can perceive heading without direct access to visual path information. Here we vary two key parameters for estimating heading from optic flow, the field of view (FOV) and the depth range of environmental points, to investigate the conditions under which visual path information influences human heading perception. The display simulated an observer traveling on a circular path. Observers used a joystick to rotate their line of sight until deemed aligned with true heading. Four FOV sizes (110 x 94 degrees, 48 x 41 degrees, 16 x 14 degrees, 8 x 7 degrees) and depth ranges (6-50 m, 6-25 m, 6-12.5 m, 6-9 m) were tested. Consistent with our computational modeling results, heading bias increased with the reduction of FOV or depth range when the display provided a sequence of velocity fields but no direct path information. When the display provided path information, heading bias was not influenced as much by the reduction of FOV or depth range. We conclude that human heading and path perception involve separate visual processes. Path helps heading perception when the display does not contain enough optic-flow information for heading estimation during rotation.

Head injuries presenting to emergency departments in the United States from 1990 to 1999 for ice hockey, soccer, and football.

PubMed

Delaney, J Scott

2004-03-01

To examine the number and rates of head injuries occurring in the community as a whole for the team sports of ice hockey, soccer, and football by analyzing data from patients presenting to US emergency departments (EDs) from 1990 to 1999. Retrospective analysis. Data compiled for the US Consumer Product Safety Commission using the National Electronic Injury Surveillance System were used to generate estimates for the total number of head injuries, concussions, internal head injuries, and skull fractures occurring on a national level from the years 1990 to 1999. These data were combined with yearly participation figures to generate rates of injuries presenting to the ED for each sport. There were an estimated 17,008 head injuries from ice hockey, 86,697 from soccer, and 204,802 from football that presented to US EDs from 1990 to 1999. The total number of concussions presenting to EDs in the United States over the same period was estimated to be 4820 from ice hockey, 21,715 from soccer, and 68,861 from football. While the rates of head injuries, concussions, and combined concussions/internal head injuries/skull fractures presenting to EDs per 10,000 players were not always statistically similar for all 3 sports in each year data were available, they were usually comparable. While the total numbers of head injuries, concussions, and combined concussions/skull fractures/internal head injuries presenting to EDs in the United States are different for ice hockey, soccer, and football for the years studied, the yearly rates for these injuries are comparable among all 3 sports.

Rigorous Performance Evaluation of Smartphone GNSS/IMU Sensors for ITS Applications

PubMed Central

Gikas, Vassilis; Perakis, Harris

2016-01-01

With the rapid growth in smartphone technologies and improvement in their navigation sensors, an increasing amount of location information is now available, opening the road to the provision of new Intelligent Transportation System (ITS) services. Current smartphone devices embody miniaturized Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU) and other sensors capable of providing user position, velocity and attitude. However, it is hard to characterize their actual positioning and navigation performance capabilities due to the disparate sensor and software technologies adopted among manufacturers and the high influence of environmental conditions, and therefore, a unified certification process is missing. This paper presents the analysis results obtained from the assessment of two modern smartphones regarding their positioning accuracy (i.e., precision and trueness) capabilities (i.e., potential and limitations) based on a practical but rigorous methodological approach. Our investigation relies on the results of several vehicle tracking (i.e., cruising and maneuvering) tests realized through comparing smartphone obtained trajectories and kinematic parameters to those derived using a high-end GNSS/IMU system and advanced filtering techniques. Performance testing is undertaken for the HTC One S (Android) and iPhone 5s (iOS). Our findings indicate that the deviation of the smartphone locations from ground truth (trueness) deteriorates by a factor of two in obscured environments compared to those derived in open sky conditions. Moreover, it appears that iPhone 5s produces relatively smaller and less dispersed error values compared to those computed for HTC One S. Also, the navigation solution of the HTC One S appears to adapt faster to changes in environmental conditions, suggesting a somewhat different data filtering approach for the iPhone 5s. Testing the accuracy of the accelerometer and gyroscope sensors for a number of maneuvering (speeding, turning, etc.,) events reveals high consistency between smartphones, whereas the small deviations from ground truth verify their high potential even for critical ITS safety applications. PMID:27527187

Rigorous Performance Evaluation of Smartphone GNSS/IMU Sensors for ITS Applications.

PubMed

Gikas, Vassilis; Perakis, Harris

2016-08-05

With the rapid growth in smartphone technologies and improvement in their navigation sensors, an increasing amount of location information is now available, opening the road to the provision of new Intelligent Transportation System (ITS) services. Current smartphone devices embody miniaturized Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU) and other sensors capable of providing user position, velocity and attitude. However, it is hard to characterize their actual positioning and navigation performance capabilities due to the disparate sensor and software technologies adopted among manufacturers and the high influence of environmental conditions, and therefore, a unified certification process is missing. This paper presents the analysis results obtained from the assessment of two modern smartphones regarding their positioning accuracy (i.e., precision and trueness) capabilities (i.e., potential and limitations) based on a practical but rigorous methodological approach. Our investigation relies on the results of several vehicle tracking (i.e., cruising and maneuvering) tests realized through comparing smartphone obtained trajectories and kinematic parameters to those derived using a high-end GNSS/IMU system and advanced filtering techniques. Performance testing is undertaken for the HTC One S (Android) and iPhone 5s (iOS). Our findings indicate that the deviation of the smartphone locations from ground truth (trueness) deteriorates by a factor of two in obscured environments compared to those derived in open sky conditions. Moreover, it appears that iPhone 5s produces relatively smaller and less dispersed error values compared to those computed for HTC One S. Also, the navigation solution of the HTC One S appears to adapt faster to changes in environmental conditions, suggesting a somewhat different data filtering approach for the iPhone 5s. Testing the accuracy of the accelerometer and gyroscope sensors for a number of maneuvering (speeding, turning, etc.,) events reveals high consistency between smartphones, whereas the small deviations from ground truth verify their high potential even for critical ITS safety applications.

The educational environment and self-perceived clinical competence of senior medical students in a Malaysian medical school.

PubMed

Lai, N; Nalliah, S; Jutti, R C; Hla, Y; Lim, V K E

2009-08-01

The educational environment is widely considered to be a major factor affecting students' motivation and learning outcomes. Although students' perceptions of their educational environment are often reported, we are unaware of any published reports that relate this information to students' clinical competence, either self-perceived or objectively measured. We aimed to correlate students' perceptions of their learning environment and their self-perceived competence in clinical, practical and personal skills, using validated scales. Subjects included a cohort of 71 final-year medical students who were posted to a peripheral campus affiliated with a district hospital. Two questionnaires were administered concurrently: a modified DREEM (50 items) to assess the learning environment and an abbreviated IMU Student Competency Survey (29 items) to examine self-perceived competence across a wide range of skills and work-readiness. We correlated the major domains in both surveys using Spearman's Correlation. Fifty-nine students (83%) completed the questionnaires. Comparing correlations of the five major domains of the modified DREEM questionnaire ("Perception of learning", "Perception of teachers", "Academic self-perception", "Perception of atmosphere" and "Social self-perception") with all subscales in the abbreviated IMU Student Competency Survey (clinical, practical, personal skills and overall work-readiness), we found that academic self-perception domain had the strongest correlations (r:0.405 to 0.579, p:0.002 to < 0.001) and perception of teachers bears the weakest correlations (r:0.171 to 0.284, p:0.254 to 0.031). Self-perceived competence in practical skills in the IMU Student Competency Survey correlated the weakest with all domains of the modified DREEM (r:0.206 to 0.405, p:0.124 to 0.002). The overall weak-to-moderate correlations between perceptions of learning environment and self-perceived clinical competence suggest that other factors might interact with the learning environment to determine students' confidence and achievements.

Reconstruction of head impacts in FIS World Cup alpine skiing.

PubMed

Steenstrup, Sophie Elspeth; Mok, Kam-Ming; McIntosh, Andrew S; Bahr, Roald; Krosshaug, Tron

2018-06-01

Prior to the 2013/2014 season, the International Ski Federation (FIS) increased the helmet testing speed from 5.4 to 6.8 m/s for alpine downhill, super-G and giant slalom. Whether this increased testing speed reflects head impact velocities in real head injury situations on snow is unclear. We therefore investigated the injury mechanisms and gross head impact biomechanics in seven real head injury situations among World Cup (WC) alpine skiers. We analysed nine head impacts from seven head injury videos from the FIS Injury Surveillance System, throughout nine WC seasons (2006-2015) in detail. We used commercial video-based motion analysis software to estimate head impact kinematics in two dimensions, including directly preimpact and postimpact, from broadcast video. The sagittal plane angular movement of the head was also measured using angle measurement software. In seven of nine head impacts, the estimated normal to slope preimpact velocity was higher than the current FIS helmet rule of 6.8 m/s (mean 8.1 (±SD 0.6) m/s, range 1.9±0.8 to 12.1±0.4 m/s). The nine head impacts had a mean normal to slope velocity change of 9.3±1.0 m/s, range 5.2±1.1 to 13.5±1.3 m/s. There was a large change in sagittal plane angular velocity (mean 43.3±2.9 rad/s (range 21.2±1.5 to 64.2±3.0 rad/s)) during impact. The estimated normal to slope preimpact velocity was higher than the current FIS helmet rule of 6.8 m/s in seven of nine head impacts. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Development of Head Injury Assessment Reference Values Based on NASA Injury Modeling

NASA Technical Reports Server (NTRS)

Somers, Jeffrey T.; Melvin, John W.; Tabiei, Ala; Lawrence, Charles; Ploutz-Snyder, Robert; Granderson, Bradley; Feiveson, Alan; Gernhardt, Michael; Patalak, John

2011-01-01

NASA is developing a new capsule-based, crewed vehicle that will land in the ocean, and the space agency desires to reduce the risk of injury from impact during these landings. Because landing impact occurs for each flight and the crew might need to perform egress tasks, current injury assessment reference values (IARV) were deemed insufficient. Because NASCAR occupant restraint systems are more effective than the systems used to determine the current IARVs and are similar to NASA s proposed restraint system, an analysis of NASCAR impacts was performed to develop new IARVs that may be more relevant to NASA s context of vehicle landing operations. Head IARVs associated with race car impacts were investigated by completing a detailed analysis of all of the 2002-2008 NASCAR impact data. Specific inclusion and exclusion criteria were used to select 4071 impacts from the 4015 recorder files provided (each file could contain multiple impact events). Of the 4071 accepted impacts, 274 were selected for numerical simulation using a custom NASCAR restraint system and Humanetics Hybrid-III 50th percentile numerical dummy model in LS-DYNA. Injury had occurred in 32 of the 274 selected impacts, and 27 of those injuries involved the head. A majority of the head injuries were mild concussions with or without brief loss of consciousness. The 242 non-injury impacts were randomly selected and representative of the range of crash dynamics present in the total set of 4071 impacts. Head dynamics data (head translational acceleration, translational change in velocity, rotational acceleration, rotational velocity, HIC-15, HIC-36, and the Head 3ms clip) were filtered according to SAE J211 specifications and then transformed to a log scale. The probability of head injury was estimated using a separate logistic regression analysis for each log-transformed predictor candidate. Using the log transformation constrains the estimated probability of injury to become negligible as IARVs approach zero. For the parameters head translational acceleration, head translational velocity change, head rotational acceleration, HIC-15, and HIC-36, conservative values (in the lower 95% confidence interval) that gave rise to a 5% risk of any injury occurring were estimated as 40.0 G, 7.9 m/s, 2200 rad/s2, 98.4, and 77.4 respectively. Because NASA is interested in the consequence of any particular injury on the ability of the crew to perform egress tasks, the head injuries that occurred in the NASCAR dataset were classified according to a NASA-developed scale (Classes I - III) for operationally relevant injuries, which classifies injuries on the basis of their operational significance. Additional analysis of the data was performed to determine the probability of each injury class occurring, and this was estimated using an ordered probit model. For head translational acceleration, head translational velocity change, head rotational acceleration, head rotational velocity, HIC-36, and head 3ms clip, conservative values of IARVs that produced a 5% risk of Class II injury were estimated as 50.7 G, 9.5 m/s, 2863 rad/s2, 11.0 rad/s, 30.3, and 46.4 G respectively. The results indicate that head IARVs developed from the NASCAR dataset may be useful to protect crews during landing impact.

Simultaneous head tissue conductivity and EEG source location estimation.

PubMed

Akalin Acar, Zeynep; Acar, Can E; Makeig, Scott

2016-01-01

Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality. Copyright © 2015 Elsevier Inc. All rights reserved.

Simultaneous head tissue conductivity and EEG source location estimation

PubMed Central

Acar, Can E.; Makeig, Scott

2015-01-01

Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3 cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15 cm2-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm2-scale accurate 3-D functional cortical imaging modality. PMID:26302675

Development of a 3D workspace shoulder assessment tool incorporating electromyography and an inertial measurement unit-a preliminary study.

PubMed

Aslani, Navid; Noroozi, Siamak; Davenport, Philip; Hartley, Richard; Dupac, Mihai; Sewell, Philip

2018-06-01

Traditional shoulder range of movement (ROM) measurement tools suffer from inaccuracy or from long experimental setup times. Recently, it has been demonstrated that relatively low-cost wearable inertial measurement unit (IMU) sensors can overcome many of the limitations of traditional motion tracking systems. The aim of this study is to develop and evaluate a single IMU combined with an electromyography (EMG) sensor to monitor the 3D reachable workspace with simultaneous measurement of deltoid muscle activity across the shoulder ROM. Six volunteer subjects with healthy shoulders and one participant with a 'frozen' shoulder were recruited to the study. Arm movement in 3D space was plotted in spherical coordinates while the relative EMG intensity of any arm position is presented graphically. The results showed that there was an average ROM surface area of 27291 ± 538 deg 2 among all six healthy individuals and a ROM surface area of 13571 ± 308 deg 2 for the subject with frozen shoulder. All three sections of the deltoid show greater EMG activity at higher elevation angles. Using such tools enables individuals, surgeons and physiotherapists to measure the maximum envelope of motion in conjunction with muscle activity in order to provide an objective assessment of shoulder performance in the voluntary 3D workspace. Graphical abstract The aim of this study is to develop and evaluate a single IMU combined with an electromyography (EMG) sensor to monitor the 3D reachable workspace with simultaneous measurement of deltoid muscle activity across the shoulder ROM. The assessment tool consists of an IMU sensor, an EMG sensor, a microcontroller and a Bluetooth module. The assessment tool was attached to subjects arm. Individuals were instructed to move their arms with the elbow fully extended. They were then asked to provide the maximal voluntary elevation envelope of the arm in 3D space in multiple attempts starting from a small movement envelope going to the biggest possible in four consecutive circuits. The results showed that there was an average ROM surface area of 27291 ± 538 deg2 among all six healthy individuals and a ROM surface area of 13571 ± 308 deg2 for the subject with frozen shoulder. All three sections of the deltoid show greater EMG activity at higher elevation angles. Using such tools enables individuals, surgeons and physiotherapists to measure the maximum envelope of motion in conjunction with muscle activity in order to provide an objective assessment of shoulder performance in the voluntary 3D workspace.

Rapid Transfer Alignment of MEMS SINS Based on Adaptive Incremental Kalman Filter.

PubMed

Chu, Hairong; Sun, Tingting; Zhang, Baiqiang; Zhang, Hongwei; Chen, Yang

2017-01-14

In airborne MEMS SINS transfer alignment, the error of MEMS IMU is highly environment-dependent and the parameters of the system model are also uncertain, which may lead to large error and bad convergence of the Kalman filter. In order to solve this problem, an improved adaptive incremental Kalman filter (AIKF) algorithm is proposed. First, the model of SINS transfer alignment is defined based on the "Velocity and Attitude" matching method. Then the detailed algorithm progress of AIKF and its recurrence formulas are presented. The performance and calculation amount of AKF and AIKF are also compared. Finally, a simulation test is designed to verify the accuracy and the rapidity of the AIKF algorithm by comparing it with KF and AKF. The results show that the AIKF algorithm has better estimation accuracy and shorter convergence time, especially for the bias of the gyroscope and the accelerometer, which can meet the accuracy and rapidity requirement of transfer alignment.

Attitude Determination Algorithm based on Relative Quaternion Geometry of Velocity Incremental Vectors for Cost Efficient AHRS Design

NASA Astrophysics Data System (ADS)

Lee, Byungjin; Lee, Young Jae; Sung, Sangkyung

2018-05-01

A novel attitude determination method is investigated that is computationally efficient and implementable in low cost sensor and embedded platform. Recent result on attitude reference system design is adapted to further develop a three-dimensional attitude determination algorithm through the relative velocity incremental measurements. For this, velocity incremental vectors, computed respectively from INS and GPS with different update rate, are compared to generate filter measurement for attitude estimation. In the quaternion-based Kalman filter configuration, an Euler-like attitude perturbation angle is uniquely introduced for reducing filter states and simplifying propagation processes. Furthermore, assuming a small angle approximation between attitude update periods, it is shown that the reduced order filter greatly simplifies the propagation processes. For performance verification, both simulation and experimental studies are completed. A low cost MEMS IMU and GPS receiver are employed for system integration, and comparison with the true trajectory or a high-grade navigation system demonstrates the performance of the proposed algorithm.

Rapid Transfer Alignment of MEMS SINS Based on Adaptive Incremental Kalman Filter

PubMed Central

Chu, Hairong; Sun, Tingting; Zhang, Baiqiang; Zhang, Hongwei; Chen, Yang

2017-01-01

In airborne MEMS SINS transfer alignment, the error of MEMS IMU is highly environment-dependent and the parameters of the system model are also uncertain, which may lead to large error and bad convergence of the Kalman filter. In order to solve this problem, an improved adaptive incremental Kalman filter (AIKF) algorithm is proposed. First, the model of SINS transfer alignment is defined based on the “Velocity and Attitude” matching method. Then the detailed algorithm progress of AIKF and its recurrence formulas are presented. The performance and calculation amount of AKF and AIKF are also compared. Finally, a simulation test is designed to verify the accuracy and the rapidity of the AIKF algorithm by comparing it with KF and AKF. The results show that the AIKF algorithm has better estimation accuracy and shorter convergence time, especially for the bias of the gyroscope and the accelerometer, which can meet the accuracy and rapidity requirement of transfer alignment. PMID:28098829

PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features

PubMed Central

Zhao, Ji; Guo, Yue; He, Wenhao; Yuan, Kui

2018-01-01

To address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point–line visual–inertial odometry (PL-VIO), a tightly-coupled monocular visual–inertial odometry system exploiting both point and line features. Compared with point features, lines provide significantly more geometrical structure information on the environment. To obtain both computation simplicity and representational compactness of a 3D spatial line, Plücker coordinates and orthonormal representation for the line are employed. To tightly and efficiently fuse the information from inertial measurement units (IMUs) and visual sensors, we optimize the states by minimizing a cost function which combines the pre-integrated IMU error term together with the point and line re-projection error terms in a sliding window optimization framework. The experiments evaluated on public datasets demonstrate that the PL-VIO method that combines point and line features outperforms several state-of-the-art VIO systems which use point features only. PMID:29642648

Evaluation of lamprey larvicides in the Big Garlic River and Saux Head Lake

USGS Publications Warehouse

Manion, Patrick J.

1969-01-01

Bayluscide (5,2'-dichloro-4'-nitrosalicylanilide) and TFM (3-trifluoromethyl-4-nitrophenol) were evaluated as selective larvicides for control of the sea lamprey, Petromyzon marinus, in the Big Garlic River and Saux Head Lake in Marquette County, Michigan. Population estimates and movement of ammocetes were determined from the recapture of marked ammocetes released before chemical treatment. In 1966 the estimated population of 3136 ammocetes off the stream mouth in Saux Head Lake was reduced 89% by treatment with granular Bayluscide; this percentage was supported by a population estimate of 120 ammocetes in 1967, an indicated reduction of 96% from 1966. Post-marking movement of ammocetes was greater upstream than downstream.

Asymmetry hidden in birds’ tracks reveals wind, heading, and orientation ability over the ocean

PubMed Central

Goto, Yusuke; Yoda, Ken; Sato, Katsufumi

2017-01-01

Numerous flying and swimming animals constantly need to control their heading (that is, their direction of orientation) in a flow to reach their distant destination. However, animal orientation in a flow has yet to be satisfactorily explained because it is difficult to directly measure animal heading and flow. We constructed a new animal movement model based on the asymmetric distribution of the GPS (Global Positioning System) track vector along its mean vector, which might be caused by wind flow. This statistical model enabled us to simultaneously estimate animal heading (navigational decision-making) and ocean wind information over the range traversed by free-ranging birds. We applied this method to the tracking data of homing seabirds. The wind flow estimated by the model was consistent with the spatiotemporally coarse wind information provided by an atmospheric simulation model. The estimated heading information revealed that homing seabirds could head in a direction different from that leading to the colony to offset wind effects and to enable them to eventually move in the direction they intended to take, even though they are over the open sea where visual cues are unavailable. Our results highlight the utility of combining large data sets of animal movements with the “inverse problem approach,” enabling unobservable causal factors to be estimated from the observed output data. This approach potentially initiates a new era of analyzing animal decision-making in the field. PMID:28959724

Emulating the Visual Receptive Field Properties of MST Neurons with a Template Model of Heading Estimation

NASA Technical Reports Server (NTRS)

Perrone, John A.; Stone, Leland S.

1997-01-01

We have previously proposed a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. The model detectors were designed to extract self-translation (heading), self-rotation, as well as the scene layout (relative distances) ahead of a moving observer, and are arranged in cortical-like heading maps to perform this function. Heading estimation from optic flow has been postulated by some to be implemented within the medial superior temporal (MST) area. Others have questioned whether MST neurons can fulfill this role because some of their receptive-field properties appear inconsistent with a role in heading estimation. To resolve this issue, we systematically compared MST single-unit responses with the outputs of model detectors under matched stimulus conditions. We found that the basic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support heading estimation and that the template model provides an explicit set of testable hypotheses which can guide future exploration of MST and adjacent areas within the primate superior temporal sulcus.

76 FR 73010 - Technical Report Evaluating the 1999-2003 Head Impact Upgrade of FMVSS No. 201, Upper-Interior...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-28

...-Interior Components: Effectiveness of Energy-Absorbing Materials Without Head-Protection Air Bags. DATES... Reporting System--Multiple Cause of Death files for 1999-2007. FMVSS No. 201 without head-protection air bags reduces AIS 4-to-6 head injuries due to contact with upper-interior components by an estimated 24...

Hydraulic head estimation at unobserved locations: Approximating the distribution of the absolute error based on geologic interpretations

NASA Astrophysics Data System (ADS)

Langousis, Andreas; Kaleris, Vassilios; Xeygeni, Vagia; Magkou, Foteini

2017-04-01

Assessing the availability of groundwater reserves at a regional level, requires accurate and robust hydraulic head estimation at multiple locations of an aquifer. To that extent, one needs groundwater observation networks that can provide sufficient information to estimate the hydraulic head at unobserved locations. The density of such networks is largely influenced by the spatial distribution of the hydraulic conductivity in the aquifer, and it is usually determined through trial-and-error, by solving the groundwater flow based on a properly selected set of alternative but physically plausible geologic structures. In this work, we use: 1) dimensional analysis, and b) a pulse-based stochastic model for simulation of synthetic aquifer structures, to calculate the distribution of the absolute error in hydraulic head estimation as a function of the standardized distance from the nearest measuring locations. The resulting distributions are proved to encompass all possible small-scale structural dependencies, exhibiting characteristics (bounds, multi-modal features etc.) that can be explained using simple geometric arguments. The obtained results are promising, pointing towards the direction of establishing design criteria based on large-scale geologic maps.

A game-theoretic approach for calibration of low-cost magnetometers under noise uncertainty

NASA Astrophysics Data System (ADS)

Siddharth, S.; Ali, A. S.; El-Sheimy, N.; Goodall, C. L.; Syed, Z. F.

2012-02-01

Pedestrian heading estimation is a fundamental challenge in Global Navigation Satellite System (GNSS)-denied environments. Additionally, the heading observability considerably degrades in low-speed mode of operation (e.g. walking), making this problem even more challenging. The goal of this work is to improve the heading solution when hand-held personal/portable devices, such as cell phones, are used for positioning and to improve the heading estimation in GNSS-denied signal environments. Most smart phones are now equipped with self-contained, low cost, small size and power-efficient sensors, such as magnetometers, gyroscopes and accelerometers. A magnetometer needs calibration before it can be properly employed for navigation purposes. Magnetometers play an important role in absolute heading estimation and are embedded in many smart phones. Before the users navigate with the phone, a calibration is invoked to ensure an improved signal quality. This signal is used later in the heading estimation. In most of the magnetometer-calibration approaches, the motion modes are seldom described to achieve a robust calibration. Also, suitable calibration approaches fail to discuss the stopping criteria for calibration. In this paper, the following three topics are discussed in detail that are important to achieve proper magnetometer-calibration results and in turn the most robust heading solution for the user while taking care of the device misalignment with respect to the user: (a) game-theoretic concepts to attain better filter parameter tuning and robustness in noise uncertainty, (b) best maneuvers with focus on 3D and 2D motion modes and related challenges and (c) investigation of the calibration termination criteria leveraging the calibration robustness and efficiency.

Autonomous Flight Safety System

NASA Technical Reports Server (NTRS)

Simpson, James

2010-01-01

The Autonomous Flight Safety System (AFSS) is an independent self-contained subsystem mounted onboard a launch vehicle. AFSS has been developed by and is owned by the US Government. Autonomously makes flight termination/destruct decisions using configurable software-based rules implemented on redundant flight processors using data from redundant GPS/IMU navigation sensors. AFSS implements rules determined by the appropriate Range Safety officials.

Rapid Annealing of Iron Implanted Hg(1-x)Cd(x)Te

DTIC Science & Technology

1990-03-01

Alnrroveii rFoi’ PubikI Release; distributin tilIntl ted DTICELECTEJUN 12 IMU’ BEest Available Cop, D i ..:6 (J,•, 4iL& , AD Rapid Annealing of Ion...Recently, we have received from Or.J. Dinan of the Night Vision and Electro-optic Army Labs at Fort Belvoir a few electrically uncharacterized Hg

Dynamo: A Model Transition Framework for Dynamic Stability Control and Body Mass Manipulation

DTIC Science & Technology

2011-11-01

driving at high speed, and you turn the steering wheel hard to the right and slam on the brakes, then you will end up in the oversteer regime. At the...sensors (GPS, IMU, LIDAR ) for vehicle control. Figure 17: Dynamo high-speed small UGV hardware platform We will perform experiments to measure the MTC

75 FR 59745 - In the Matter of: Certain Components for Installation of Marine Autopilots With GPS or IMU...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-28

.... Strandvelen 18, Lysaker, Norway. Navico UK, Ltd., Premier Way, Abbey Park, Romsey Hampshire, United Kingdom..., Southampton Road. Portsmouth Hampshire, PO6 4QB, United Kingdom. Raymarine Inc., 21 Manchester Street... violations of section 337 based upon the importation into the United States, the sale for importation, and...

LiDAR and Image Point Cloud Comparison

DTIC Science & Technology

2014-09-01

UAV unmanned aerial vehicle USGS United States Geological Survey UTM Universal Transverse Mercator WGS 84 World Geodetic System 1984 WSI...19  1.  Physics of LiDAR Systems ................................................................20  III.  DATA AND SOFTWARE...ground control point GPS Global Positioning System IMU inertial measurements unit LiDAR light detection and ranging MI mutual information MVS

2007 Precision Strike Annual Programs Review

DTIC Science & Technology

2007-04-25

Adapting our methods • Remaining a flexible combined-arms force • Enabling a generation of combat- experienced decision-makers by distributing...Sustain Propulsion Network RadioMEMS IMU Flexible Engagement Options Requirements Capabilities Precision Attack Missile (PAM) 67” (with Canister...Aimpoint 6 PAM Seeker Modes PAM’s Multiple Targeting Modes Increase Flexibility , Improve Lethality PAM’s Multiple Targeting Modes Increase Flexibility

Confined aquifer head measurements and storage properties in the San Luis Valley, Colorado, from spaceborne InSAR observations

NASA Astrophysics Data System (ADS)

Chen, Jingyi; Knight, Rosemary; Zebker, Howard A.; Schreüder, Willem A.

2016-05-01

Interferometric Synthetic Aperture Radar (InSAR), a remote sensing technique for measuring centimeter-level surface deformation, is used to estimate hydraulic head in the confined aquifer of the San Luis Valley (SLV), Colorado. Reconstructing head measurements from InSAR in agricultural regions can be difficult, as InSAR phase data are often decorrelated due to vegetation growth. Analysis of 17 L-band ALOS PALSAR scenes, acquired between January 2007 and March 2011, demonstrates that comprehensive InSAR deformation measurements can be recovered over the vegetated groundwater basin with an improved processing strategy. Local skeletal storage coefficients and time delays between the head change and deformation are estimated through a joint InSAR-well data analysis. InSAR subsidence estimates are transformed to head changes with finer temporal and spatial resolution than is possible using existing well records alone. Both InSAR and well data suggest that little long-term water-storage loss occurred in the SLV over the study period and that inelastic compaction was negligible. The seasonal head variations derived from InSAR are consistent with the existing well data at most locations where confined aquifer pumping activity dominates. Our results demonstrate the advantages of InSAR measurements for basin-wide characterization of aquifer storage properties and groundwater levels over agricultural regions.

Trends in head and neck cancers in Peru between 1987 and 2008: Experience from a large public cancer hospital in Lima

PubMed Central

Walter, Leora; Vidaurre, Tatiana; Gilman, Robert H.; Poquioma, Ebert; Olaechea, Carlos; Gravitt, Patti E.; Marks, Morgan A.

2017-01-01

Background Few studies have evaluated the trends in head and neck cancer in developing countries. The purpose of this study was to estimate trends in incidence of human papillomavirus–related (HPV-R) and HPV-unrelated (HPV-U) head and neck cancer in Lima, Peru, from 1987 to 2008. Methods Registry data from a single public cancer hospital were used to estimate age and sex-specific incidence rates. Annualized percent change was estimated using Poisson regression. Results The rate of total head and neck cancers, HPV-U, and HPV-R was 11.9, 10.9, and 0.8, respectively, per 100,000 person-years. Significant increases in HPV-U head and neck cancer were observed in men aged 30 to 44 (2.5%/year) and women 15 to 29 (4.2%/year), 30 to 44 (3.4%/ year), and 60 to 74 (2.0%/year). Significant increases in HPV-R head and neck cancer were observed only among men aged 45 to 59 (9.6%/year). Conclusion Although increased exposure to tobacco, occupational carcinogens, and changing sexual behaviors could be influencing these trends, additional analyses to assess generalizability of these findings to other regions of Peru are needed. PMID:23616366

Ceramic Heads Decrease Metal Release Caused by Head-taper Fretting and Corrosion.

PubMed

Kocagoz, Sevi B; Underwood, Richard J; MacDonald, Daniel W; Gilbert, Jeremy L; Kurtz, Steven M

2016-04-01

Metal release resulting from taper fretting and corrosion is a clinical concern, because wear and corrosion products may stimulate adverse local tissue reactions. Unimodular hip arthroplasties have a conical taper between the femoral head (head bore taper) and the femoral stem (stem cone taper). The use of ceramic heads has been suggested as a way of reducing the generation of wear and corrosion products from the head bore/stem cone taper junction. A previous semiquantitative study found that ceramic heads had less visual evidence of fretting-corrosion damage compared with CoCr heads; but, to our knowledge, no studies have quantified the volumetric material loss from the head bore and stem cone tapers of a matched cohort of ceramic and metal heads. We asked: (1) Do ceramic heads result in less volume of material loss at the head-stem junction compared with CoCr heads; (2) do stem cone tapers have less volumetric material loss compared with CoCr head bore tapers; (3) do visual fretting-corrosion scores correlate with volumetric material loss; and (4) are device, patient, or intraoperative factors associated with volumetric material loss? A quantitative method was developed to estimate volumetric material loss from the head and stem taper in previously matched cohorts of 50 ceramic and 50 CoCr head-stem pairs retrieved during revision surgery for causes not related to adverse reactions to metal particles. The cohorts were matched according to (1) implantation time, (2) stem flexural rigidity, and (3) lateral offset. Fretting corrosion was assessed visually using a previously published four-point, semiquantitative scoring system. The volumetric loss was measured using a precision roundness machine. Using 24 equally spaced axial traces, the volumetric loss was estimated using a linear least squares fit to interpolate the as-manufactured surfaces. The results of this analysis were considered in the context of device (taper angle clearance, head size, head offset, lateral offset, stem material, and stem surface finish) and patient factors that were obtained from the patients' operative records (implantation time, age at insertion, activity level, and BMI). The cumulative volumetric material losses estimated for the ceramic cohort had a median of 0.0 mm(3) per year (range, 0.0-0.4 mm(3)). The cumulative volumetric material losses estimated for the CoCr cohort had a median of 0.1 mm(3) per year (range, 0.0-8.8 mm(3)). An order of magnitude reduction in volumetric material loss was found when a ceramic head was used instead of a CoCr head (p < 0.0001). In the CoCr cohort, the femoral head bore tapers had a median material loss of 0.02 mm(3) (range, 0.0-8.7 mm(3)) and the stem cone tapers had a median material loss of 0.0 mm(3) (range, 0.0-0.32 mm(3)/year). There was greater material loss from femoral head bore tapers compared with stem cone tapers in the CoCr cohort (p < 0.001). There was a positive correlation between visual scoring and volumetric material loss (Spearman's ρ = 0.67, p < 0.01). Although visual scoring was effective for preliminary screening to separate tapers with no or mild damage from tapers with moderate to severe damage, it was not capable of discriminating in the large range of material loss observed at the taper surfaces with moderate to severe fretting-corrosion damage, indicated with a score of 3 or 4. We observed no correlations between volumetric material loss and device and patient factors. The majority of estimated material loss from the head bore-stem cone junctions resulting from taper fretting and corrosion was from the CoCr head bore tapers as opposed to the stem cone tapers. Additionally, the total material loss from the ceramic cohort showed a reduction in the amount of metal released by an order of magnitude compared with the CoCr cohort. We found that ceramic femoral heads may be an effective means by which to reduce metal release caused by taper fretting and corrosion at the head bore-stem cone modular interface in THAs.

High quality InSAR data linked to seasonal change in hydraulic head for an agricultural area in the San Luis Valley, Colorado

NASA Astrophysics Data System (ADS)

Reeves, Jessica A.; Knight, Rosemary; Zebker, Howard A.; Schreüder, Willem A.; Shanker Agram, Piyush; Lauknes, Tom R.

2011-12-01

In the San Luis Valley (SLV), Colorado legislation passed in 2004 requires that hydraulic head levels in the confined aquifer system stay within the range experienced in the years 1978-2000. While some measurements of hydraulic head exist, greater spatial and temporal sampling would be very valuable in understanding the behavior of the system. Interferometric synthetic aperture radar (InSAR) data provide fine spatial resolution measurements of Earth surface deformation, which can be related to hydraulic head change in the confined aquifer system. However, change in cm-scale crop structure with time leads to signal decorrelation, resulting in low quality data. Here we apply small baseline subset (SBAS) analysis to InSAR data collected from 1992 to 2001. We are able to show high levels of correlation, denoting high quality data, in areas between the center pivot irrigation circles, where the lack of water results in little surface vegetation. At three well locations we see a seasonal variation in the InSAR data that mimics the hydraulic head data. We use measured values of the elastic skeletal storage coefficient to estimate hydraulic head from the InSAR data. In general the magnitude of estimated and measured head agree to within the calculated error. However, the errors are unacceptably large due to both errors in the InSAR data and uncertainty in the measured value of the elastic skeletal storage coefficient. We conclude that InSAR is capturing the seasonal head variation, but that further research is required to obtain accurate hydraulic head estimates from the InSAR deformation measurements.

Turning semicircular canal function on its head: dinosaurs and a novel vestibular analysis.

PubMed

Georgi, Justin A; Sipla, Justin S; Forster, Catherine A

2013-01-01

Previous investigations have correlated vestibular function to locomotion in vertebrates by scaling semicircular duct radius of curvature to body mass. However, this method fails to discriminate bipedal from quadrupedal non-avian dinosaurs. Because they exhibit a broad range of relative head sizes, we use dinosaurs to test the hypothesis that semicircular ducts scale more closely with head size. Comparing the area enclosed by each semicircular canal to estimated body mass and to two different measures of head size, skull length and estimated head mass, reveals significant patterns that corroborate a connection between physical parameters of the head and semicircular canal morphology. Head mass more strongly correlates with anterior semicircular canal size than does body mass and statistically separates bipedal from quadrupedal taxa, with bipeds exhibiting relatively larger canals. This morphologic dichotomy likely reflects adaptations of the vestibular system to stability demands associated with terrestrial locomotion on two, versus four, feet. This new method has implications for reinterpreting previous studies and informing future studies on the connection between locomotion type and vestibular function.

Turning Semicircular Canal Function on Its Head: Dinosaurs and a Novel Vestibular Analysis

PubMed Central

Georgi, Justin A.; Sipla, Justin S.; Forster, Catherine A.

2013-01-01

Previous investigations have correlated vestibular function to locomotion in vertebrates by scaling semicircular duct radius of curvature to body mass. However, this method fails to discriminate bipedal from quadrupedal non-avian dinosaurs. Because they exhibit a broad range of relative head sizes, we use dinosaurs to test the hypothesis that semicircular ducts scale more closely with head size. Comparing the area enclosed by each semicircular canal to estimated body mass and to two different measures of head size, skull length and estimated head mass, reveals significant patterns that corroborate a connection between physical parameters of the head and semicircular canal morphology. Head mass more strongly correlates with anterior semicircular canal size than does body mass and statistically separates bipedal from quadrupedal taxa, with bipeds exhibiting relatively larger canals. This morphologic dichotomy likely reflects adaptations of the vestibular system to stability demands associated with terrestrial locomotion on two, versus four, feet. This new method has implications for reinterpreting previous studies and informing future studies on the connection between locomotion type and vestibular function. PMID:23516495

Costs in Serving Handicapped Children in Head Start: An Analysis of Methods and Cost Estimates. Final Report.

ERIC Educational Resources Information Center

Syracuse Univ., NY. Div. of Special Education and Rehabilitation.

An evaluation of the costs of serving handicapped children in Head Start was based on information collected in conjunction with on-site visits to regular Head Start programs, experimental programs, and specially selected model preschool programs, and from questionnaires completed by 1,353 grantees and delegate agencies of regular Head Start…

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

PubMed Central

Savalia, Neil K.; Agres, Phillip F.; Chan, Micaela Y.; Feczko, Eric J.; Kennedy, Kristen M.

2016-01-01

Abstract Motion‐contaminated T1‐weighted (T1w) magnetic resonance imaging (MRI) results in misestimates of brain structure. Because conventional T1w scans are not collected with direct measures of head motion, a practical alternative is needed to identify potential motion‐induced bias in measures of brain anatomy. Head movements during functional MRI (fMRI) scanning of 266 healthy adults (20–89 years) were analyzed to reveal stable features of in‐scanner head motion. The magnitude of head motion increased with age and exhibited within‐participant stability across different fMRI scans. fMRI head motion was then related to measurements of both quality control (QC) and brain anatomy derived from a T1w structural image from the same scan session. A procedure was adopted to “flag” individuals exhibiting excessive head movement during fMRI or poor T1w quality rating. The flagging procedure reliably reduced the influence of head motion on estimates of gray matter thickness across the cortical surface. Moreover, T1w images from flagged participants exhibited reduced estimates of gray matter thickness and volume in comparison to age‐ and gender‐matched samples, resulting in inflated effect sizes in the relationships between regional anatomical measures and age. Gray matter thickness differences were noted in numerous regions previously reported to undergo prominent atrophy with age. Recommendations are provided for mitigating this potential confound, and highlight how the procedure may lead to more accurate measurement and comparison of anatomical features. Hum Brain Mapp 38:472–492, 2017. © 2016 Wiley Periodicals, Inc. PMID:27634551

Sex estimation by femur in modern Thai population.

PubMed

Monum, T; Prasitwattanseree, S; Das, S; Siriphimolwat, P; Mahakkanukrauh, P

2017-01-01

Sex estimation is an important step of postmortem investigation and the femur is a useful bone for sex estimation by using metric analysis method. Even though there have been a reported sex estimation method by using femur in Thais, the temporal change related to time and anthropological data need to be renewed. Thus the aim of this study is to re-evaluate sex estimation by femur in Thais. 97 adult male and 103 female femora were random chosen from Forensic osteology research center and 6 measurements were applied tend to. To compare with previous Thai data, mid shaft diameter to increase but femoral head and epicondylar breadth to stabilize and when tested previous discriminant function by vertical head diameter and epicondalar breadth, the accuracy of prediction was lower than previous report. From the new data, epicondalar breadth is the best variable for distinguishing male and female at 88.7 percent of accuracy, following by transverse and vertical head diameter at 86.7 percent and femoral neck diameter at 81.7 percent of accuracy. Multivariate discriminant analysis indicated transverse head diameter and epicondylar breadth performed highest rate of accuracy at 89.7 percent. The percent of accuracy of femur was close to previous reported sex estimation by talus and calcaneus in Thai population. Thus, for especially in case of lower limb remain, which absence of pelvis.

Inertial Pocket Navigation System: Unaided 3D Positioning

PubMed Central

Munoz Diaz, Estefania

2015-01-01

Inertial navigation systems use dead-reckoning to estimate the pedestrian's position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelerometer readings, the step-and-heading approach lacks the vertical displacement estimation. We propose the first step-and-heading approach based on unaided inertial data solving 3D positioning. We present a step detector for steps up and down and a novel vertical displacement estimator. Our navigation system uses the sensor introduced in the front pocket of the trousers, a likely location of a smartphone. The proposed algorithms are based on the opening angle of the leg or pitch angle. We analyzed our step detector and compared it with the state-of-the-art, as well as our already proposed step length estimator. Lastly, we assessed our vertical displacement estimator in a real-world scenario. We found that our algorithms outperform the literature step and heading algorithms and solve 3D positioning using unaided inertial data. Additionally, we found that with the pitch angle, five activities are distinguishable: standing, sitting, walking, walking up stairs and walking down stairs. This information complements the pedestrian location and is of interest for applications, such as elderly care. PMID:25897501

Intelligent Melting Probes - How to Make the Most out of our Data

NASA Astrophysics Data System (ADS)

Kowalski, J.; Clemens, J.; Chen, S.; Schüller, K.

2016-12-01

Direct exploration of glaciers, ice sheets, or subglacial environments poses a big challenge. Different technological solutions have been proposed and deployed in the last decades, examples being hot-water drills or different melting probe designs. Most of the recent engineering concepts integrate a variety of different on-board sensors, e.g. temperature sensors, pressure sensors, or an inertial measurement unit. Not only do individual sensors provide valuable insight into the current state of the probe, yet often they also contain a wealth of additional information when analyzed collectively. This quite naturally raises the question: How can we make most out of our data? We find that it is necessary to implement intelligent data integration and sensor fusion strategies to retrieve a maximum amount of information from the observations. In this contribution, we are inspired by the engineering design of the IceMole, a minimally invasive, steerable melting probe. We will talk about two sensor integration strategies relevant to IceMole melting scenarios. At first, we will present a multi-sensor fusion approach to accurately retrieve subsurface position and attitude information. It uses an extended Kalman filter to integrate data from an on-board IMU, a differential magnetometer system, the screw feed, as well as the travel time of acoustic signals originating from emitters at the ice surface. Furthermore, an evidential mapping algorithm estimates a map of the environment from data of ultrasound phased arrays in the probe's head. Various results from tests in a swimming pool and in glacier ice will be shown during the presentation. A second block considers the fluid-dynamical state in the melting channel, as well as the ambient cryo-environment. It is devoted to retrieving information from on-board temperature and pressure sensors. Here, we will report on preliminary results from re-analysing past field test data. Knowledge from integrated sensor data likewise provides valuable input for the parameter identification and verification of data based models. Due to the concept of not focusing on the physical laws, this approach can still be used, if modifications are done. It is highly transferable and hasn't been exploited rigorously so far. This could be a potential future direction.

Triana Safehold: A New Gyroless, Sun-Pointing Attitude Controller

NASA Technical Reports Server (NTRS)

Chen, J.; Morgenstern, Wendy; Garrick, Joseph

2001-01-01

Triana is a single-string spacecraft to be placed in a halo orbit about the sun-earth Ll Lagrangian point. The Attitude Control Subsystem (ACS) hardware includes four reaction wheels, ten thrusters, six coarse sun sensors, a star tracker, and a three-axis Inertial Measuring Unit (IMU). The ACS Safehold design features a gyroless sun-pointing control scheme using only sun sensors and wheels. With this minimum hardware approach, Safehold increases mission reliability in the event of a gyroscope anomaly. In place of the gyroscope rate measurements, Triana Safehold uses wheel tachometers to help provide a scaled estimation of the spacecraft body rate about the sun vector. Since Triana nominally performs momentum management every three months, its accumulated system momentum can reach a significant fraction of the wheel capacity. It is therefore a requirement for Safehold to maintain a sun-pointing attitude even when the spacecraft system momentum is reasonably large. The tachometer sun-line rate estimation enables the controller to bring the spacecraft close to its desired sun-pointing attitude even with reasonably high system momentum and wheel drags. This paper presents the design rationale behind this gyroless controller, stability analysis, and some time-domain simulation results showing performances with various initial conditions. Finally, suggestions for future improvements are briefly discussed.

Precise visual navigation using multi-stereo vision and landmark matching

NASA Astrophysics Data System (ADS)

Zhu, Zhiwei; Oskiper, Taragay; Samarasekera, Supun; Kumar, Rakesh

2007-04-01

Traditional vision-based navigation system often drifts over time during navigation. In this paper, we propose a set of techniques which greatly reduce the long term drift and also improve its robustness to many failure conditions. In our approach, two pairs of stereo cameras are integrated to form a forward/backward multi-stereo camera system. As a result, the Field-Of-View of the system is extended significantly to capture more natural landmarks from the scene. This helps to increase the pose estimation accuracy as well as reduce the failure situations. Secondly, a global landmark matching technique is used to recognize the previously visited locations during navigation. Using the matched landmarks, a pose correction technique is used to eliminate the accumulated navigation drift. Finally, in order to further improve the robustness of the system, measurements from low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) sensors are integrated with the visual odometry in an extended Kalman Filtering framework. Our system is significantly more accurate and robust than previously published techniques (1~5% localization error) over long-distance navigation both indoors and outdoors. Real world experiments on a human worn system show that the location can be estimated within 1 meter over 500 meters (around 0.1% localization error averagely) without the use of GPS information.

Effects of variations of stage and flux at different frequencies on the estimates using river stage tomography

NASA Astrophysics Data System (ADS)

Wang, Y. L.; Yeh, T. C. J.; Wen, J. C.

2017-12-01

This study is to investigate the ability of river stage tomography to estimate the spatial distribution of hydraulic transmissivity (T), storage coefficient (S), and diffusivity (D) in groundwater basins using information of groundwater level variations induced by periodic variations of stream stage, and infiltrated flux from the stream boundary. In order to accomplish this objective, the sensitivity and correlation of groundwater heads with respect to the hydraulic properties is first conducted to investigate the spatial characteristics of groundwater level in response to the stream variations at different frequencies. Results of the analysis show that the spatial distributions of the sensitivity of heads at an observation well in response to periodic river stage variations are highly correlated despite different frequencies. On the other hand, the spatial patterns of the sensitivity of the observed head to river flux boundaries at different frequencies are different. Specifically, the observed head is highly correlated with T at the region between the stream and observation well when the high-frequency periodic flux is considered. On the other hand, it is highly correlated with T at the region between monitoring well and the boundary opposite to the stream when the low-frequency periodic flux is prescribed to the stream. We also find that the spatial distributions of the sensitivity of observed head to S variation are highly correlated with all frequencies in spite of heads or fluxes stream boundary. Subsequently, the differences of the spatial correlations of the observed heads to the hydraulic properties under the head and flux boundary conditions are further investigated by an inverse model (i.e., successive stochastic linear estimator). This investigation uses noise-free groundwater and stream data of a synthetic aquifer, where aquifer heterogeneity is known exactly. The ability of river stage tomography is then tested with these synthetic data sets to estimate T, S, and D distribution. The results reveal that boundary flux variations with different frequencies contain different information about the aquifer characteristics while the head boundary does not.

Shrinkage and growth compensation in common sunflowers: refining estimates of damage

USGS Publications Warehouse

Sedgwick, James A.; Oldemeye, John L.; Swenson, Elizabeth L.

1986-01-01

Shrinkage and growth compensation of artificially damaged common sunflowers (Helianthus annuus) were studied in central North Dakota during 1981-1982 in an effort to increase accuracy of estimates of blackbird damage to sunflowers. In both years, as plants matured damaged areas on seedheads shrank at a greater rate than the sunflower heads themselves. This differential shrinkage resulted in an underestimation of the area damaged. Sunflower head and damaged-area shrinkage varied widely by time and degree of damage and by size of the seedhead damaged. Because variation in shrinkage by time of damage was so large, predicting when blackbird damage occurs may be the most important factor in estimating seed loss. Yield'occupied seed area was greater (P < 0.05) for damaged than undamaged heads and tended to increase as degree of damage inflicted increased, indicating growth compensation was occurring in response to lost seeds. Yields of undamaged seeds in seedheads damaged during early seed development were higher than those of heads damaged later. This suggested that there was a period of maximal response to damage when plants were best able to redirect growth to seeds remaining in the head. Sunflowers appear to be able to compensate for damage of ≤ 15% of the total hear area. Estimates of damage can be improved by applying empirical results of differential shrinkage and growth compensations.

Maternal hypothyroxinemia during pregnancy and growth of the fetal and infant head.

PubMed

van Mil, Nina H; Steegers-Theunissen, Régine P M; Bongers-Schokking, Jacoba J; El Marroun, Hanan; Ghassabian, Akhgar; Hofman, Albert; Jaddoe, Vincent W V; Visser, Theo J; Verhulst, Frank C; de Rijke, Yolanda B; Steegers, Eric A P; Tiemeier, Henning

2012-12-01

Severe maternal thyroid dysfunction during pregnancy affects fetal brain growth and corticogenesis. This study focused on the effect of maternal hypothyroxinemia during early pregnancy on growth of the fetal and infant head. In a population-based birth cohort, we assessed thyroid status in early pregnancy (median 13.4, 90% range 10.8-17.2), in 4894 women, and measured the prenatal and postnatal head size of their children at 5 time points. Hypothyroxinemia was defined as normal thyroid-stimulating hormone levels and free thyroxine-4 concentrations below the 10th percentile. Statistical analysis was performed using linear generalized estimating equation. Maternal hypothyroxinemia was associated with larger fetal and infant head size (overall estimate β: 1.38, 95% confidence interval 0.56; 2.19, P = .001). In conclusion, in the general population, even small variations in maternal thyroid function during pregnancy may affect the developing head of the young child.

Psychophysical estimation of the effects of aging on direction-of-heading judgments

NASA Astrophysics Data System (ADS)

Raghuram, Aparna; Lakshminarayanan, Vasudevan

2011-11-01

We conducted psychophysical experiments on direction-of-heading judgments using old and young subjects. Subjects estimated heading directions on a translation perpendicular to the vertical plane (frontoparallel); we found that heading judgments were affected by age. Increasing the random dot density in the stimulus from 24 to 400 dots did not improve threshold significantly. Older subjects started performing worse at the highest dots condition of 400. The speed of the radial motion was important, as heading judgments with slower radial motion were difficult to judge than faster radial motion, as the focus of expansion was easier to locate owing to the larger displacement of dots. Gender differences indicated that older women had a higher threshold than older men. This was only significant for the faster simulated radial speed. A general trend of women having a higher threshold than men was noticed.

A Role for MST Neurons in Heading Estimation

NASA Technical Reports Server (NTRS)

Stone, Leland Scott; Perrone, J. A.; Wade, Charles E. (Technical Monitor)

1994-01-01

A template model of human visual self-motion perception (Perrone, JOSA, 1992; Perrone & Stone, Vis. Res., in press), which uses neurophysiologically realistic "heading detectors", is consistent with numerous human psychophysical results (Warren & Hannon, Nature, 1988; Stone & Perrone, Neuro. Abstr., 1991) including the failure of humans to estimate their heading (direction of forward translation) accurately under certain visual conditions (Royden et al., Nature, 1992). We tested the model detectors with stimuli used by others in- single-unit studies. The detectors showed emergent properties similar to those of MST neurons: 1) Sensitivity to non-preferred flow. Each detector is tuned to a specific combination of flow components and its response is systematically reduced by the addition of nonpreferred flow (Orban et al., PNAS, 1992), and 2) Position invariance. The detectors maintain their apparent preference for particular flow components over large regions of their receptive fields (e.g. Duffy & Wurtz, J. Neurophys., 1991; Graziano et al., J. Neurosci., 1994). It has been argued that this latter property is incompatible with MST playing a role in heading perception. The model however demonstrates how neurons with the above response properties could still support accurate heading estimation within extrastriate cortical maps.

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.

Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control.

PubMed

Gunn, Cameron Allan; Dickson, Jennifer L; Pretty, Christopher G; Alsweiler, Jane M; Lynn, Adrienne; Shaw, Geoffrey M; Chase, J Geoffrey

2014-07-01

Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal. A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (SI) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort. Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in SI of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient SI deviation 13.7%. In virtual trials, 87-93% of recommended insulin rates were equal or slightly reduced (Δ<0.16mU/h) under the head circumference method, while glycaemic control outcomes showed little change. The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Near Real Time Structural Health Monitoring with Multiple Sensors in a Cloud Environment

NASA Astrophysics Data System (ADS)

Bock, Y.; Todd, M.; Kuester, F.; Goldberg, D.; Lo, E.; Maher, R.

2017-12-01

A repeated near real time 3-D digital surrogate representation of critical engineered structures can be used to provide actionable data on subtle time-varying displacements in support of disaster resiliency. We describe a damage monitoring system of optimally-integrated complementary sensors, including Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical Systems (MEMS) accelerometers coupled with the GNSS (seismogeodesy), light multi-rotor Unmanned Aerial Vehicles (UAVs) equipped with high-resolution digital cameras and GNSS/IMU, and ground-based Light Detection and Ranging (LIDAR). The seismogeodetic system provides point measurements of static and dynamic displacements and seismic velocities of the structure. The GNSS ties the UAV and LIDAR imagery to an absolute reference frame with respect to survey stations in the vicinity of the structure to isolate the building response to ground motions. The GNSS/IMU can also estimate the trajectory of the UAV with respect to the absolute reference frame. With these constraints, multiple UAVs and LIDAR images can provide 4-D displacements of thousands of points on the structure. The UAV systematically circumnavigates the target structure, collecting high-resolution image data, while the ground LIDAR scans the structure from different perspectives to create a detailed baseline 3-D reference model. UAV- and LIDAR-based imaging can subsequently be repeated after extreme events, or after long time intervals, to assess before and after conditions. The unique challenge is that disaster environments are often highly dynamic, resulting in rapidly evolving, spatio-temporal data assets with the need for near real time access to the available data and the tools to translate these data into decisions. The seismogeodetic analysis has already been demonstrated in the NASA AIST Managed Cloud Environment (AMCE) designed to manage large NASA Earth Observation data projects on Amazon Web Services (AWS). The Cloud provides distinct advantages in terms of extensive storage and computing resources required for processing UAV and LIDAR imagery. Furthermore, it avoids single points of failure and allows for remote operations during emergencies, when near real time access to structures may be limited.

Modeling Navigation System Performance of a Satellite-Observing Star Tracker Tightly Integrated with an Inertial Measurement Unit

DTIC Science & Technology

2015-03-26

tracker, an Inertial Measurement Unit (IMU), and a barometric altimeter using an Extended Kalman Filter (EKF). Models of each of these components are...Positioning 15 2.5 Detector Device Improvement . . . . . . . . . . . . . . . 15 2.6 Kalman Filter . . . . . . . . . . . . . . . . . . . . . . . . 17 2.6.1...Extended Kalman Filter . . . . . . . . . . . . . 17 2.7 System Properties . . . . . . . . . . . . . . . . . . . . . 21 2.8 Sun Exitance

External Aiding Methods for IMU-Based Navigation

DTIC Science & Technology

2016-11-26

Carlo simulation and particle filtering . This approach allows for the utilization of highly complex systems in a black box configuration with minimal...alternative method, which has the advantage of being less computationally demanding, is to use a Kalman filtering -based approach. The particular...Kalman filtering -based approach used here is known as linear covariance analysis. In linear covariance analysis, the nonlinear systems describing the

Apollo Onboard Navigation Techniques

NASA Technical Reports Server (NTRS)

Interbartolo, Michael

2009-01-01

This viewgraph presentation reviews basic navigation concepts, describes coordinate systems and identifies attitude determination techniques including Primary Guidance, Navigation and Control System (PGNCS) IMU management and Command and Service Module Stabilization and Control System/Lunar Module (LM) Abort Guidance System (AGS) attitude management. The presentation also identifies state vector determination techniques, including PGNCS coasting flight navigation, PGNCS powered flight navigation and LM AGS navigation.

MIT Orbital Transfer Vehicle (MOTV): CASTOR Satellite: Design Document

DTIC Science & Technology

2010-11-18

65 Table 2.2-3: MEMS IMU RATE Sensor ...................................................................................... 66 Table 2.2...either high power mode, providing about 4 mN of thrust, or in off mode, in which the cathode will remain heated . The propulsion system will also...subsections: ICD Block Diagram, Heat Transfer Method, Thermal Path, Heat Loads and Fluxes, and Modeling. The ICD Block Diagram identifies the connections

Autonomous Legged Hill and Stairwell Ascent

DTIC Science & Technology

2011-11-01

environments with little burden to a human operator. Keywords: autonomous robot , hill climbing , stair climbing , sequential composition, hexapod, self...X-RHex robot on a set of stairs with laser scanner, IMU, wireless repeater, and handle payloads. making them useful for both climbing hills and...reconciliation into that more powerful (but restrictive) framework. 1) The Stair Climbing Behavior: RHex robots have been climbing single-flight stairs

Extraction and Analysis of Respiratory Motion Using Wearable Inertial Sensor System during Trunk Motion

PubMed Central

Gaidhani, Apoorva; Moon, Kee S.; Ozturk, Yusuf; Lee, Sung Q.; Youm, Woosub

2017-01-01

Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as standing, bending, trunk stretching or during yoga exercises. A single IMU (inertial measurement unit) can be used in measuring respiratory motion; however, breathing motion data may be influenced by a body trunk movement that occurs while recording respiratory activity. This research employs a pair of wireless, wearable IMU sensors custom-made by the Department of Electrical Engineering at San Diego State University. After appropriate sensor placement for data collection, this research applies principles of robotics, using the Denavit-Hartenberg convention, to extract relative angular motion between the two sensors. One of the obtained relative joint angles in the “Sagittal” plane predominantly yields respiratory activity. An improvised version of the proposed method and wearable, wireless sensors can be suitable to extract respiratory information while performing sports or exercises, as they do not restrict body motion or the choice of location to gather data. PMID:29258214

A Highly Miniaturized, Wireless Inertial Measurement Unit for Characterizing the Dynamics of Pitched Baseballs and Softballs

PubMed Central

McGinnis, Ryan S.; Perkins, Noel C.

2012-01-01

Baseball and softball pitch types are distinguished by the path and speed of the ball which, in turn, are determined by the angular velocity of the ball and the velocity of the ball center at the instant of release from the pitcher's hand. While radar guns and video-based motion capture (mocap) resolve ball speed, they provide little information about how the angular velocity of the ball and the velocity of the ball center develop and change during the throwing motion. Moreover, mocap requires measurements in a controlled lab environment and by a skilled technician. This study addresses these shortcomings by introducing a highly miniaturized, wireless inertial measurement unit (IMU) that is embedded in both baseballs and softballs. The resulting “ball-embedded” sensor resolves ball dynamics right on the field of play. Experimental results from ten pitches, five thrown by one softball pitcher and five by one baseball pitcher, demonstrate that this sensor technology can deduce the magnitude and direction of the ball's velocity at release to within 4.6% of measurements made using standard mocap. Moreover, the IMU directly measures the angular velocity of the ball, which further enables the analysis of different pitch types.

Decoding static and dynamic arm and hand gestures from the JPL BioSleeve

NASA Astrophysics Data System (ADS)

Wolf, M. T.; Assad, C.; Stoica, A.; You, Kisung; Jethani, H.; Vernacchia, M. T.; Fromm, J.; Iwashita, Y.

This paper presents methods for inferring arm and hand gestures from forearm surface electromyography (EMG) sensors and an inertial measurement unit (IMU). These sensors, together with their electronics, are packaged in an easily donned device, termed the BioSleeve, worn on the forearm. The gestures decoded from BioSleeve signals can provide natural user interface commands to computers and robots, without encumbering the users hands and without problems that hinder camera-based systems. Potential aerospace applications for this technology include gesture-based crew-autonomy interfaces, high degree of freedom robot teleoperation, and astronauts' control of power-assisted gloves during extra-vehicular activity (EVA). We have developed techniques to interpret both static (stationary) and dynamic (time-varying) gestures from the BioSleeve signals, enabling a diverse and adaptable command library. For static gestures, we achieved over 96% accuracy on 17 gestures and nearly 100% accuracy on 11 gestures, based solely on EMG signals. Nine dynamic gestures were decoded with an accuracy of 99%. This combination of wearableEMGand IMU hardware and accurate algorithms for decoding both static and dynamic gestures thus shows promise for natural user interface applications.

IMU-Based Joint Angle Measurement for Gait Analysis

PubMed Central

Seel, Thomas; Raisch, Jorg; Schauer, Thomas

2014-01-01

This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations in which the sensors are mounted with respect to the body segments. After a review of available methods that may cope with this challenge, we present a set of new methods for: (1) joint axis and position identification; and (2) flexion/extension joint angle measurement. In particular, we propose methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field. We provide results from gait trials of a transfemoral amputee in which we compare the inertial measurement unit (IMU)-based methods to an optical 3D motion capture system. Unlike most authors, we place the optical markers on anatomical landmarks instead of attaching them to the IMUs. Root mean square errors of the knee flexion/extension angles are found to be less than 1° on the prosthesis and about 3° on the human leg. For the plantar/dorsiflexion of the ankle, both deviations are about 1°. PMID:24743160

Reconstruction of Twist Torque in Main Parachute Risers

NASA Technical Reports Server (NTRS)

Day, Joshua D.

2015-01-01

The reconstruction of twist torque in the Main Parachute Risers of the Capsule Parachute Assembly System (CPAS) has been successfully used to validate CPAS Model Memo conservative twist torque equations. Reconstruction of basic, one degree of freedom drop tests was used to create a functional process for the evaluation of more complex, rigid body simulation. The roll, pitch, and yaw of the body, the fly-out angles of the parachutes, and the relative location of the parachutes to the body are inputs to the torque simulation. The data collected by the Inertial Measurement Unit (IMU) was used to calculate the true torque. The simulation then used photogrammetric and IMU data as inputs into the Model Memo equations. The results were then compared to the true torque results to validate the Model Memo equations. The Model Memo parameters were based off of steel risers and the parameters will need to be re-evaluated for different materials. Photogrammetric data was found to be more accurate than the inertial data in accounting for the relative rotation between payload and cluster. The Model Memo equations were generally a good match and when not matching were generally conservative.

Between-year breeding dispersal by White-headed Woodpeckers: A caution about using color bands to estimate survival

Treesearch

Teresa J Lorenz

2016-01-01

Between-year breeding dispersal has not been previously documented in White-headed Woodpeckers (Picoides albolarvatus). Therefore, resightings of color-banded adults on previous years’ breeding territories have been considered a means of estimating annual adult survival. From 2013 to 2015, I observed 2 cases of between-year breeding dispersal by...

Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

PubMed Central

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

2015-01-01

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

Coordinates of Human Visual and Inertial Heading Perception.

PubMed

Crane, Benjamin Thomas

2015-01-01

Heading estimation involves both inertial and visual cues. Inertial motion is sensed by the labyrinth, somatic sensation by the body, and optic flow by the retina. Because the eye and head are mobile these stimuli are sensed relative to different reference frames and it remains unclear if a perception occurs in a common reference frame. Recent neurophysiologic evidence has suggested the reference frames remain separate even at higher levels of processing but has not addressed the resulting perception. Seven human subjects experienced a 2s, 16 cm/s translation and/or a visual stimulus corresponding with this translation. For each condition 72 stimuli (360° in 5° increments) were delivered in random order. After each stimulus the subject identified the perceived heading using a mechanical dial. Some trial blocks included interleaved conditions in which the influence of ±28° of gaze and/or head position were examined. The observations were fit using a two degree-of-freedom population vector decoder (PVD) model which considered the relative sensitivity to lateral motion and coordinate system offset. For visual stimuli gaze shifts caused shifts in perceived head estimates in the direction opposite the gaze shift in all subjects. These perceptual shifts averaged 13 ± 2° for eye only gaze shifts and 17 ± 2° for eye-head gaze shifts. This finding indicates visual headings are biased towards retina coordinates. Similar gaze and head direction shifts prior to inertial headings had no significant influence on heading direction. Thus inertial headings are perceived in body-centered coordinates. Combined visual and inertial stimuli yielded intermediate results.

Coordinates of Human Visual and Inertial Heading Perception

PubMed Central

Crane, Benjamin Thomas

2015-01-01

Heading estimation involves both inertial and visual cues. Inertial motion is sensed by the labyrinth, somatic sensation by the body, and optic flow by the retina. Because the eye and head are mobile these stimuli are sensed relative to different reference frames and it remains unclear if a perception occurs in a common reference frame. Recent neurophysiologic evidence has suggested the reference frames remain separate even at higher levels of processing but has not addressed the resulting perception. Seven human subjects experienced a 2s, 16 cm/s translation and/or a visual stimulus corresponding with this translation. For each condition 72 stimuli (360° in 5° increments) were delivered in random order. After each stimulus the subject identified the perceived heading using a mechanical dial. Some trial blocks included interleaved conditions in which the influence of ±28° of gaze and/or head position were examined. The observations were fit using a two degree-of-freedom population vector decoder (PVD) model which considered the relative sensitivity to lateral motion and coordinate system offset. For visual stimuli gaze shifts caused shifts in perceived head estimates in the direction opposite the gaze shift in all subjects. These perceptual shifts averaged 13 ± 2° for eye only gaze shifts and 17 ± 2° for eye-head gaze shifts. This finding indicates visual headings are biased towards retina coordinates. Similar gaze and head direction shifts prior to inertial headings had no significant influence on heading direction. Thus inertial headings are perceived in body-centered coordinates. Combined visual and inertial stimuli yielded intermediate results. PMID:26267865

Fully Self-Contained Vision-Aided Navigation and Landing of a Micro Air Vehicle Independent from External Sensor Inputs

NASA Technical Reports Server (NTRS)

Brockers, Roland; Susca, Sara; Zhu, David; Matthies, Larry

2012-01-01

Direct-lift micro air vehicles have important applications in reconnaissance. In order to conduct persistent surveillance in urban environments, it is essential that these systems can perform autonomous landing maneuvers on elevated surfaces that provide high vantage points without the help of any external sensor and with a fully contained on-board software solution. In this paper, we present a micro air vehicle that uses vision feedback from a single down looking camera to navigate autonomously and detect an elevated landing platform as a surrogate for a roof top. Our method requires no special preparation (labels or markers) of the landing location. Rather, leveraging the planar character of urban structure, the landing platform detection system uses a planar homography decomposition to detect landing targets and produce approach waypoints for autonomous landing. The vehicle control algorithm uses a Kalman filter based approach for pose estimation to fuse visual SLAM (PTAM) position estimates with IMU data to correct for high latency SLAM inputs and to increase the position estimate update rate in order to improve control stability. Scale recovery is achieved using inputs from a sonar altimeter. In experimental runs, we demonstrate a real-time implementation running on-board a micro aerial vehicle that is fully self-contained and independent from any external sensor information. With this method, the vehicle is able to search autonomously for a landing location and perform precision landing maneuvers on the detected targets.

Estimating Impacts of Treatment Random Assignment on Classroom Quality in the Head Start Impact Study: The Problem of Missing Data

ERIC Educational Resources Information Center

Friedman-Krauss, Allison H.; Connors, Maia C.; Morris, Pamela A.

2013-01-01

As a result of the 1998 reauthorization of Head Start, the Department of Health and Human Services conducted a national evaluation of the Head Start program. The goal of Head Start is to improve the school readiness skills of low-income children in the United States. There is a substantial body of experimental and correlational research that has…

Effectiveness of Interaural Delays Alone as Cues During Dynamic Sound Localization

NASA Technical Reports Server (NTRS)

Wenzel, Elizabeth M.; Null, Cynthia H. (Technical Monitor)

1996-01-01

The contribution of interaural time differences (ITDs) to the localization of virtual sound sources with and without head motion was examined. Listeners estimated the apparent azimuth, elevation and distance of virtual sources presented over headphones. Stimuli (3 sec., white noise) were synthesized from minimum-phase representations of nonindividualized head-related transfer functions (HRTFs); binaural magnitude spectra were derived from the minimum phase estimates and ITDs were represented as a pure delay. During dynamic conditions, listeners were encouraged to move their heads; head position was tracked and stimuli were synthesized in real time using a Convolvotron to simulate a stationary external sound source. Two synthesis conditions were tested: (1) both interaural level differences (ILDs) and ITDs correctly correlated with source location and head motion, (2) ITDs correct, no ILDs (flat magnitude spectrum). Head movements reduced azimuth confusions primarily when interaural cues were correctly correlated, although a smaller effect was also seen for ITDs alone. Externalization was generally poor for ITD-only conditions and was enhanced by head motion only for normal HRTFs. Overall the data suggest that, while ITDs alone can provide a significant cue for azimuth, the errors most commonly associated with virtual sources are reduced by location-dependent magnitude cues.

MODFLOW 2000 Head Uncertainty, a First-Order Second Moment Method

USGS Publications Warehouse

Glasgow, H.S.; Fortney, M.D.; Lee, J.; Graettinger, A.J.; Reeves, H.W.

2003-01-01

A computationally efficient method to estimate the variance and covariance in piezometric head results computed through MODFLOW 2000 using a first-order second moment (FOSM) approach is presented. This methodology employs a first-order Taylor series expansion to combine model sensitivity with uncertainty in geologic data. MODFLOW 2000 is used to calculate both the ground water head and the sensitivity of head to changes in input data. From a limited number of samples, geologic data are extrapolated and their associated uncertainties are computed through a conditional probability calculation. Combining the spatially related sensitivity and input uncertainty produces the variance-covariance matrix, the diagonal of which is used to yield the standard deviation in MODFLOW 2000 head. The variance in piezometric head can be used for calibrating the model, estimating confidence intervals, directing exploration, and evaluating the reliability of a design. A case study illustrates the approach, where aquifer transmissivity is the spatially related uncertain geologic input data. The FOSM methodology is shown to be applicable for calculating output uncertainty for (1) spatially related input and output data, and (2) multiple input parameters (transmissivity and recharge).

Translation and Rotation Trade Off in Human Visual Heading Estimation

NASA Technical Reports Server (NTRS)

Stone, Leland S.; Perrone, John A.; Null, Cynthia H. (Technical Monitor)

1996-01-01

We have previously shown that, during simulated curvilinear motion, humans can make reasonably accurate and precise heading judgments from optic flow without either oculomotor or static-depth cues about rotation. We now systematically investigate the effect of varying the parameters of self-motion. We visually simulated 400 ms of self-motion along curved paths (constant rotation and translation rates, fixed retinocentric heading) towards two planes of random dots at 10.3 m and 22.3 m at mid-trial. Retinocentric heading judgments of 4 observers (2 naive) were measured for 12 different combinations of translation (T between 4 and 16 m/s) and rotation (R either 8 or 16 deg/s). In the range tested, heading bias and uncertainty decrease quasilinearly with T/R, but the bias also appears to depend on R. If depth is held constant, the ratio T/R can account for much of the variation in the accuracy and precision of human visual heading estimation, although further experiments are needed to resolve whether absolute rotation rate, total flow rate, or some other factor can account for the observed -2 deg shift between the bias curves.

Automatic Calibration Method for Driver’s Head Orientation in Natural Driving Environment

PubMed Central

Fu, Xianping; Guan, Xiao; Peli, Eli; Liu, Hongbo; Luo, Gang

2013-01-01

Gaze tracking is crucial for studying driver’s attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head movements. Traditional calibrations that require subjects to follow calibrators are very cumbersome to be implemented in daily driving situations. A new automatic calibration method, based on a single camera for determining the head orientation and which utilizes the side mirrors, the rear-view mirror, the instrument board, and different zones in the windshield as calibration points, is presented in this paper. Supported by a self-learning algorithm, the system tracks the head and categorizes the head pose in 12 gaze zones based on facial features. The particle filter is used to estimate the head pose to obtain an accurate gaze zone by updating the calibration parameters. Experimental results show that, after several hours of driving, the automatic calibration method without driver’s corporation can achieve the same accuracy as a manual calibration method. The mean error of estimated eye gazes was less than 5°in day and night driving. PMID:24639620

Beneficial effects of zinc supplementation on head circumference of Nepalese infants and toddlers: a randomized controlled trial.

PubMed

Surkan, P J; Shankar, M; Katz, J; Siegel, E H; Leclerq, S C; Khatry, S K; Stoltzfus, R J; Tielsch, J M

2012-07-01

To assess the effects of micronutrient supplementation on head circumference of rural Nepali infants and children. We used a randomized controlled trial to assess the effects of micronutrient supplementation on head circumference in 569 rural Nepali infants and children aged 4-17 months. Children were randomized to: (1) zinc, (2) iron-folic acid, (3) zinc plus iron-folic acid or (4) a placebo group. Data on head circumference were collected during five visits at ∼3 month intervals over the course of a year. We calculated change in head circumference in treatment groups receiving zinc and iron comparing the first and fifth visits as well as used generalized estimating equations (GEE) to take advantage of data from all points in time. Models were adjusted for covariates unbalanced in the randomization and for baseline head circumference. Estimating differences in head circumference between baseline and visit 5, children in the zinc treatment group showed smaller decreases in head circumference z-score compared with placebo (adjusted β=0.13, 95% confidence interval (CI): 0.03 to 0.23). Using GEE, zinc treatment was associated with 0.11 (95% CI: 0.05 to 0.17) decrease in the rate of decline in head circumference z-score across visits as compared with placebo. Iron-folic acid supplementation was not associated with head circumference z-scores when comparing visits 1 with 5 or including data across all visits in adjusted models. Our results suggest that zinc supplementation confers a beneficial effect on the rate of head growth in Nepali infants.

A Unified Model of Heading and Path Perception in Primate MSTd

PubMed Central

Layton, Oliver W.; Browning, N. Andrew

2014-01-01

Self-motion, steering, and obstacle avoidance during navigation in the real world require humans to travel along curved paths. Many perceptual models have been proposed that focus on heading, which specifies the direction of travel along straight paths, but not on path curvature, which humans accurately perceive and is critical to everyday locomotion. In primates, including humans, dorsal medial superior temporal area (MSTd) has been implicated in heading perception. However, the majority of MSTd neurons respond optimally to spiral patterns, rather than to the radial expansion patterns associated with heading. No existing theory of curved path perception explains the neural mechanisms by which humans accurately assess path and no functional role for spiral-tuned cells has yet been proposed. Here we present a computational model that demonstrates how the continuum of observed cells (radial to circular) in MSTd can simultaneously code curvature and heading across the neural population. Curvature is encoded through the spirality of the most active cell, and heading is encoded through the visuotopic location of the center of the most active cell's receptive field. Model curvature and heading errors fit those made by humans. Our model challenges the view that the function of MSTd is heading estimation, based on our analysis we claim that it is primarily concerned with trajectory estimation and the simultaneous representation of both curvature and heading. In our model, temporal dynamics afford time-history in the neural representation of optic flow, which may modulate its structure. This has far-reaching implications for the interpretation of studies that assume that optic flow is, and should be, represented as an instantaneous vector field. Our results suggest that spiral motion patterns that emerge in spatio-temporal optic flow are essential for guiding self-motion along complex trajectories, and that cells in MSTd are specifically tuned to extract complex trajectory estimation from flow. PMID:24586130

Water flux characterization through hydraulic head and temperature data assimilation: Numerical modeling and sandbox experiments

NASA Astrophysics Data System (ADS)

Ju, Lei; Zhang, Jiangjiang; Chen, Cheng; Wu, Laosheng; Zeng, Lingzao

2018-03-01

Spatial distribution of groundwater recharge/discharge fluxes has an important impact on mass and energy exchanges in shallow streambeds. During the last two decades, extensive studies have been devoted to the quantification of one-dimensional (1-D) vertical exchange fluxes. Nevertheless, few studies were conducted to characterize two-dimensional (2-D) heterogeneous flux fields that commonly exist in real-world cases. In this study, we used an iterative ensemble smoother (IES) to quantify the spatial distribution of 2-D exchange fluxes by assimilating hydraulic head and temperature measurements. Four assimilation scenarios corresponding to different potential field applications were tested. In the first three scenarios, the heterogeneous hydraulic conductivity fields were first inferred from hydraulic head and/or temperature measurements, and then the flux fields were derived through Darcy's law using the estimated conductivity fields. In the fourth scenario, the flux fields were estimated directly from the temperature measurements, which is more efficient and especially suitable for the situation that a complete knowledge of flow boundary conditions is unavailable. We concluded that, the best estimation could be achieved through jointly assimilating hydraulic head and temperature measurements, and temperature data were superior to the head data when they were used independently. Overall, the IES method provided more robust and accurate vertical flux estimations than those given by the widely used analytical solution-based methods. Furthermore, IES gave reasonable uncertainty estimations, which were unavailable in traditional methods. Since temperature can be accurately monitored with high spatial and temporal resolutions, the coupling of heat tracing techniques and IES provides promising potential in quantifying complex exchange fluxes under field conditions.

Viscosity-adjusted estimation of pressure head and pump flow with quasi-pulsatile modulation of rotary blood pump for a total artificial heart.

PubMed

Yurimoto, Terumi; Hara, Shintaro; Isoyama, Takashi; Saito, Itsuro; Ono, Toshiya; Abe, Yusuke

2016-09-01

Estimation of pressure and flow has been an important subject for developing implantable artificial hearts. To realize real-time viscosity-adjusted estimation of pressure head and pump flow for a total artificial heart, we propose the table estimation method with quasi-pulsatile modulation of rotary blood pump in which systolic high flow and diastolic low flow phased are generated. The table estimation method utilizes three kinds of tables: viscosity, pressure and flow tables. Viscosity is estimated from the characteristic that differential value in motor speed between systolic and diastolic phases varies depending on viscosity. Potential of this estimation method was investigated using mock circulation system. Glycerin solution diluted with salty water was used to adjust viscosity of fluid. In verification of this method using continuous flow data, fairly good estimation could be possible when differential pulse width modulation (PWM) value of the motor between systolic and diastolic phases was high. In estimation under quasi-pulsatile condition, inertia correction was provided and fairly good estimation was possible when the differential PWM value was high, which was not different from the verification results using continuous flow data. In the experiment of real-time estimation applying moving average method to the estimated viscosity, fair estimation could be possible when the differential PWM value was high, showing that real-time viscosity-adjusted estimation of pressure head and pump flow would be possible with this novel estimation method when the differential PWM value would be set high.

Initial Implementation and Testing of a Tightly-Coupled IMU/Pseudolite System

DTIC Science & Technology

2015-03-26

accelerometer and 26 gyro[30]. f bins = f bias + abias + w f INS (3.2) ωbibins = ωbias + ω b ib + w ω INS (3.3) abias = ȧbias + w a bias (3.4) where f...bins: forces on the force measurements in the INS f bias: bias in the forces abias : accelleration bias wfINS: white guassian noise acting upon the

Wind Assessment for Aerial Payload Delivery Systems Using GPS and IMU Sensors

DTIC Science & Technology

2016-09-01

post- processing of the resultant test data were the research methods used in development of this thesis . Ultimately, this thesis presents two models ...processing of the resultant test data were the research methods used in development of this thesis . Ultimately, this thesis presents two models for winds...7  E .  THESIS OBJECTIVE AND ORGANIZATION ................................. 7  II.  BLIZZARD SYSTEM COMPONENTS

Nearshore Sea Clutter Measurements from a Fixed Platform

DTIC Science & Technology

2012-04-01

Water (MLL W) datum. 7. GPS Two differential GPS units, Magellan ProMark 3.0, were utilized to determine precise differences in position between the...8 Figure 8. (a) Trihedral configuration on the small boat and position of the GPS and IMU sensors. (b) Profile view of...SIO Miniature Directional Wave Buoys The Scripps Institution of Oceanography designs and manufactures GPS -based miniature directional wave buoys

Closing the Gap Between Research and Field Applications for Multi-UAV Cooperative Missions

DTIC Science & Technology

2013-09-01

IMU Inertial Measurement Units INCOSE International Council on Systems Engineering ISR Intelligence Surveillance and Reconnaissance ISTAR...light-weight and low-cost inertial measurement units ( IMUs ) are widely adopted for navigation of small- scale UAVs. Low-costs IMUs are characterized...by high measurement noises and large measurement biases. Hence pure initial navigation using low-cost IMUs drifts rapidly. In practice, inertial

Characterization of a Robotic Manipulator for Dynamic Wind Tunnel Applications

DTIC Science & Technology

2015-03-26

further enhancements would need to be performed individually for each joint. This research effort focused on the improvement of the MTA wrist roll ...Measurement Unit ( IMU ), was used to validate the Euler angle output calculated by the MTA Computer using forward kinematics. Additionally, fast-response...61 3.7 Modeling the Wrist Roll Motor and Controller . . . . . . . . . . . . . . . . . . . . . 64 3.8 Proportional Control for Improved Performance

Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system.

PubMed

Wittmann, Frieder; Held, Jeremia P; Lambercy, Olivier; Starkey, Michelle L; Curt, Armin; Höver, Raphael; Gassert, Roger; Luft, Andreas R; Gonzenbach, Roman R

2016-08-11

The effect of rehabilitative training after stroke is dose-dependent. Out-patient rehabilitation training is often limited by transport logistics, financial resources and a lack of motivation/compliance. We studied the feasibility of an unsupervised arm therapy for self-directed rehabilitation therapy in patients' homes. An open-label, single group study involving eleven patients with hemiparesis due to stroke (27 ± 31.5 months post-stroke) was conducted. The patients trained with an inertial measurement unit (IMU)-based virtual reality system (ArmeoSenso) in their homes for six weeks. The self-selected dose of training with ArmeoSenso was the principal outcome measure whereas the Fugl-Meyer Assessment of the upper extremity (FMA-UE), the Wolf Motor Function Test (WMFT) and IMU-derived kinematic metrics were used to assess arm function, training intensity and trunk movement. Repeated measures one-way ANOVAs were used to assess differences in training duration and clinical scores over time. All subjects were able to use the system independently in their homes and no safety issues were reported. Patients trained on 26.5 ± 11.5 days out of 42 days for a duration of 137 ± 120 min per week. The weekly training duration did not change over the course of six weeks (p = 0.146). The arm function of these patients improved significantly by 4.1 points (p = 0.003) in the FMA-UE. Changes in the WMFT were not significant (p = 0.552). ArmeoSenso based metrics showed an improvement in arm function, a high number of reaching movements (387 per session), and minimal compensatory movements of the trunk while training. Self-directed home therapy with an IMU-based home therapy system is safe and can provide a high dose of rehabilitative therapy. The assessments integrated into the system allow daily therapy monitoring, difficulty adaptation and detection of maladaptive motor patterns such as trunk movements during reaching. Unique identifier: NCT02098135 .

Wavelet based automated postural event detection and activity classification with single IMU (TEMPO)

PubMed Central

Lockhart, Thurmon E.; Soangra, Rahul; Zhang, Jian; Wu, Xuefang

2013-01-01

Mobility characteristics associated with activity of daily living such as sitting down, lying down, rising up, and walking are considered to be important in maintaining functional independence and healthy life style especially for the growing elderly population. Characteristics of postural transitions such as sit-to-stand are widely used by clinicians as a physical indicator of health, and walking is used as an important mobility assessment tool. Many tools have been developed to assist in the assessment of functional levels and to detect a person’s activities during daily life. These include questionnaires, observation, diaries, kinetic and kinematic systems, and validated functional tests. These measures are costly and time consuming, rely on subjective patient recall and may not accurately reflect functional ability in the patient’s home. In order to provide a low-cost, objective assessment of functional ability, inertial measurement unit (IMU) using MEMS technology has been employed to ascertain ADLs. These measures facilitate long-term monitoring of activity of daily living using wearable sensors. IMU system are desirable in monitoring human postures since they respond to both frequency and the intensity of movements and measure both dc (gravitational acceleration vector) and ac (acceleration due to body movement) components at a low cost. This has enabled the development of a small, lightweight, portable system that can be worn by a free-living subject without motion impediment - TEMPO. Using the TEMPO system, we acquired indirect measures of biomechanical variables that can be used as an assessment of individual mobility characteristics with accuracy and recognition rates that are comparable to the modern motion capture systems. In this study, five subjects performed various ADLs and mobility measures such as posture transitions and gait characteristics were obtained. We developed postural event detection and classification algorithm using denoised signals from single wireless inertial measurement unit (TEMPO) placed at sternum. The algorithm was further validated and verified with motion capture system in laboratory environment. Wavelet denoising highlighted postural events and transition durations that further provided clinical information on postural control and motor coordination. The presented method can be applied in real life ambulatory monitoring approaches for assessing condition of elderly. PMID:23686204

Comparisons of Simultaneously Acquired Airborne Sfm Photogrammetry and Lidar

NASA Astrophysics Data System (ADS)

Larsen, C. F.

2014-12-01

Digital elevation models (DEMs) created using images from a consumer DSLR camera are compared against simultaneously acquired LiDAR on a number of airborne mapping projects across Alaska, California and Utah. The aircraft used is a Cessna 180, and is equipped with the University of Alaska Geophysical Institute (UAF-GI) scanning airborne LiDAR system. This LiDAR is the same as described in Johnson et al, 2013, and is the principal instrument used for NASA's Operation IceBridge flights in Alaska. The system has been in extensive use since 2009, and is particularly well characterized with dozens of calibration flights and a careful program of boresight angle determination and monitoring. The UAF-GI LiDAR has a precision of +/- 8 cm and accuracy of +/- 15 cm. The photogrammetry DEM simultaneously acquired with the LiDAR relies on precise shutter timing using an event marker input to the IMU associated with the LiDAR system. The photo positions are derived from the fully coupled GPS/IMU processing, which samples at 100 Hz and is able to directly calculate the antenna to image plane offset displacements from the full orientation data. This use of the GPS/IMU solution means that both the LiDAR and Cessna 180 photogrammetry DEM share trajectory input data, however no orientation data nor ground control is used for the photorammetry processing. The photogrammetry DEMs are overlaid on the LiDAR point cloud and analyzed for horizontal shifts or warps relative to the LiDAR. No warping or horizontal shifts have been detectable for a number of photogrammetry DEMs. Vertical offsets range from +/- 30 cm, with a typical standard deviation about that mean of 10 cm or better. LiDAR and photogrammetry function inherently differently over trees and brush, and direct comparisons between the two methods show much larger differences over vegetated areas. Finally, the differences in flight patterns associated with the two methods will be discussed, highlighting the photogrammetry requirements for a well planned grid pattern and the effects of significant end lap and side lap in the imagery coverage.

Competitive Dynamics in MSTd: A Mechanism for Robust Heading Perception Based on Optic Flow

PubMed Central

Layton, Oliver W.; Fajen, Brett R.

2016-01-01

Human heading perception based on optic flow is not only accurate, it is also remarkably robust and stable. These qualities are especially apparent when observers move through environments containing other moving objects, which introduce optic flow that is inconsistent with observer self-motion and therefore uninformative about heading direction. Moving objects may also occupy large portions of the visual field and occlude regions of the background optic flow that are most informative about heading perception. The fact that heading perception is biased by no more than a few degrees under such conditions attests to the robustness of the visual system and warrants further investigation. The aim of the present study was to investigate whether recurrent, competitive dynamics among MSTd neurons that serve to reduce uncertainty about heading over time offer a plausible mechanism for capturing the robustness of human heading perception. Simulations of existing heading models that do not contain competitive dynamics yield heading estimates that are far more erratic and unstable than human judgments. We present a dynamical model of primate visual areas V1, MT, and MSTd based on that of Layton, Mingolla, and Browning that is similar to the other models, except that the model includes recurrent interactions among model MSTd neurons. Competitive dynamics stabilize the model’s heading estimate over time, even when a moving object crosses the future path. Soft winner-take-all dynamics enhance units that code a heading direction consistent with the time history and suppress responses to transient changes to the optic flow field. Our findings support recurrent competitive temporal dynamics as a crucial mechanism underlying the robustness and stability of perception of heading. PMID:27341686

Dynamic modulation of ocular orientation during visually guided saccades and smooth-pursuit eye movements

NASA Technical Reports Server (NTRS)

Hess, Bernhard J M.; Angelaki, Dora E.

2003-01-01

Rotational disturbances of the head about an off-vertical yaw axis induce a complex vestibuloocular reflex pattern that reflects the brain's estimate of head angular velocity as well as its estimate of instantaneous head orientation (at a reduced scale) in space coordinates. We show that semicircular canal and otolith inputs modulate torsional and, to a certain extent, also vertical ocular orientation of visually guided saccades and smooth-pursuit eye movements in a similar manner as during off-vertical axis rotations in complete darkness. It is suggested that this graviceptive control of eye orientation facilitates rapid visual spatial orientation during motion.

Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field.

PubMed

Ilyas, Muhammad; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok

2016-09-09

Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called "virtual sensor"), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth's magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms.

A nudging data assimilation algorithm for the identification of groundwater pumping

NASA Astrophysics Data System (ADS)

Cheng, Wei-Chen; Kendall, Donald R.; Putti, Mario; Yeh, William W.-G.

2009-08-01

This study develops a nudging data assimilation algorithm for estimating unknown pumping from private wells in an aquifer system using measured data of hydraulic head. The proposed algorithm treats the unknown pumping as an additional sink term in the governing equation of groundwater flow and provides a consistent physical interpretation for pumping rate identification. The algorithm identifies the unknown pumping and, at the same time, reduces the forecast error in hydraulic heads. We apply the proposed algorithm to the Las Posas Groundwater Basin in southern California. We consider the following three pumping scenarios: constant pumping rates, spatially varying pumping rates, and temporally varying pumping rates. We also study the impact of head measurement errors on the proposed algorithm. In the case study we seek to estimate the six unknown pumping rates from private wells using head measurements from four observation wells. The results show an excellent rate of convergence for pumping estimation. The case study demonstrates the applicability, accuracy, and efficiency of the proposed data assimilation algorithm for the identification of unknown pumping in an aquifer system.

A nudging data assimilation algorithm for the identification of groundwater pumping

NASA Astrophysics Data System (ADS)

Cheng, W.; Kendall, D. R.; Putti, M.; Yeh, W. W.

2008-12-01

This study develops a nudging data assimilation algorithm for estimating unknown pumping from private wells in an aquifer system using measurement data of hydraulic head. The proposed algorithm treats the unknown pumping as an additional sink term in the governing equation of groundwater flow and provides a consistently physical interpretation for pumping rate identification. The algorithm identifies unknown pumping and, at the same time, reduces the forecast error in hydraulic heads. We apply the proposed algorithm to the Las Posas Groundwater Basin in southern California. We consider the following three pumping scenarios: constant pumping rate, spatially varying pumping rates, and temporally varying pumping rates. We also study the impact of head measurement errors on the proposed algorithm. In the case study, we seek to estimate the six unknown pumping rates from private wells using head measurements from four observation wells. The results show excellent rate of convergence for pumping estimation. The case study demonstrates the applicability, accuracy, and efficiency of the proposed data assimilation algorithm for the identification of unknown pumping in an aquifer system.

Cost of Meeting House and Senate Proposed Head Start Teacher Qualification Requirements

ERIC Educational Resources Information Center

Center for Law and Social Policy, Inc. (CLASP), 2005

2005-01-01

This analysis provides a preliminary estimate of the necessary level of funding needed to raise the degree qualifications to meet the requirements in the Head Start reauthorization legislation currently proposed in the House and Senate. While each bill is designed to improve the quality of Head Start programs by requiring an increase in the number…

Estimating Contact Exposure in Football Using the Head Impact Exposure Estimate

PubMed Central

Littleton, Ashley C.; Cox, Leah M.; DeFreese, J.D.; Varangis, Eleanna; Lynall, Robert C.; Schmidt, Julianne D.; Marshall, Stephen W.; Guskiewicz, Kevin M.

2015-01-01

Abstract Over the past decade, there has been significant debate regarding the effect of cumulative subconcussive head impacts on short and long-term neurological impairment. This debate remains unresolved, because valid epidemiological estimates of athletes' total contact exposure are lacking. We present a measure to estimate the total hours of contact exposure in football over the majority of an athlete's lifespan. Through a structured oral interview, former football players provided information related to primary position played and participation in games and practice contacts during the pre-season, regular season, and post-season of each year of their high school, college, and professional football careers. Spring football for college was also included. We calculated contact exposure estimates for 64 former football players (n=32 college football only, n=32 professional and college football). The head impact exposure estimate (HIEE) discriminated between individuals who stopped after college football, and individuals who played professional football (p<0.001). The HIEE measure was independent of concussion history (p=0.82). Estimating total hours of contact exposure may allow for the detection of differences between individuals with variation in subconcussive impacts, regardless of concussion history. This measure is valuable for the surveillance of subconcussive impacts and their associated potential negative effects. PMID:25603189

Estimating Contact Exposure in Football Using the Head Impact Exposure Estimate.

PubMed

Kerr, Zachary Y; Littleton, Ashley C; Cox, Leah M; DeFreese, J D; Varangis, Eleanna; Lynall, Robert C; Schmidt, Julianne D; Marshall, Stephen W; Guskiewicz, Kevin M

2015-07-15

Over the past decade, there has been significant debate regarding the effect of cumulative subconcussive head impacts on short and long-term neurological impairment. This debate remains unresolved, because valid epidemiological estimates of athletes' total contact exposure are lacking. We present a measure to estimate the total hours of contact exposure in football over the majority of an athlete's lifespan. Through a structured oral interview, former football players provided information related to primary position played and participation in games and practice contacts during the pre-season, regular season, and post-season of each year of their high school, college, and professional football careers. Spring football for college was also included. We calculated contact exposure estimates for 64 former football players (n = 32 college football only, n = 32 professional and college football). The head impact exposure estimate (HIEE) discriminated between individuals who stopped after college football, and individuals who played professional football (p < 0.001). The HIEE measure was independent of concussion history (p = 0.82). Estimating total hours of contact exposure may allow for the detection of differences between individuals with variation in subconcussive impacts, regardless of concussion history. This measure is valuable for the surveillance of subconcussive impacts and their associated potential negative effects.

Head and neck cancer in South Asia: macroeconomic consequences and the role of surgery.

PubMed

Alkire, Blake C; Bergmark, Regan W; Chambers, Kyle; Cheney, Mack L; Meara, John G

2015-04-27

Head and neck cancer, for which the diagnosis and treatment are often surgical, comprises a substantial proportion of the burden of disease in South Asia. Further, estimates of surgical volume suggest this region faces a critical shortage of surgical capacity. We aimed to estimate the total economic welfare losses due to the morbidity and mortality of head and neck cancer in India, Pakistan, and Bangladesh for 1 year (2010). We used publicly available estimates from the Institute for Health Metrics and Evaluation regarding the morbidity and mortality of head and neck cancer in India, Pakistan, and Bangladesh, along with an economic concept termed the value of a statistical life, to estimate total economic welfare losses due to head and neck cancer in the aforementioned countries in the year 2010. The counterfactual scenario is absence of disease. Sensitivity analyses were done with regard to how the value of a statistical life changes with income. In 2010, the most conservative estimate of economic welfare losses due to head and neck cancer in the three studied countries is US$16·9 billion (2010 USD, PPP), equivalent to 0·26% of their combined gross domestic product (GDP). The welfare losses experienced by the population younger than 70 years of age accounted for US$15·2 billion (90% of the total losses). When adjusted for the size of their respective economies, Bangladesh, the poorest of the three countries, incurred the greatest loss (US$930 million), equivalent to 0·29% of its GDP. India and Pakistan experienced welfare losses of US$14·1 billion and US$1·9 billion, respectively. These figures are equivalent to 0·26% of the GDP for both countries. Oropharyngeal and hypopharyngeal cancer made up the largest share of the total burden at 39% (US$6·6 billion), followed closely by oral cavity cancer at 34% (US$5·7 billion). The burden of non-communicable diseases, to which cancer contributes greatly, is growing at a rapid pace in South Asia. Head and neck cancer is a leading cause of cancer-related mortality in this region, and this study suggests that the associated economic welfare losses, estimated to be US$16·9 billion in 2010 alone, are substantial. A number of strategies are available to address this burden. Surgery, as part of a multidisciplinary approach that includes radiation therapy and chemotherapy, plays a central part in the diagnosis and treatment of head and neck cancer, and building surgical capacity, which offers large economies of scope and scale, can not only address the burden of head and neck cancer, but also create a platform for beginning to confront the rising tide of non-communicable diseases. None. Copyright © 2015 Elsevier Ltd. All rights reserved.

Stabilization and mobility of the head, neck and trunk in horses during overground locomotion: comparisons with humans and other primates.

PubMed

Dunbar, Donald C; Macpherson, Jane M; Simmons, Roger W; Zarcades, Athina

2008-12-01

Segmental kinematics were investigated in horses during overground locomotion and compared with published reports on humans and other primates to determine the impact of a large neck on rotational mobility (> 20 deg.) and stability (< or = 20 deg.) of the head and trunk. Three adult horses (Equus caballus) performing walks, trots and canters were videotaped in lateral view. Data analysis included locomotor velocity, segmental positions, pitch and linear displacements and velocities, and head displacement frequencies. Equine, human and monkey skulls and cervical spines were measured to estimate eye and vestibular arc length during head pitch displacements. Horses stabilized all three segments in all planes during all three gaits, unlike monkeys and humans who make large head pitch and yaw rotations during walks, and monkeys that make large trunk pitch rotations during gallops. Equine head angular displacements and velocities, with some exceptions during walks, were smaller than in humans and other primates. Nevertheless, owing to greater off-axis distances, orbital and vestibular arc lengths remained larger in horses, with the exception of head-neck axial pitch during trots, in which equine arc lengths were smaller than in running humans. Unlike monkeys and humans, equine head peak-frequency ranges fell within the estimated range in which inertia has a compensatory stabilizing effect. This inertial effect was typically over-ridden, however, by muscular or ligamentous intervention. Thus, equine head pitch was not consistently compensatory, as reported in humans. The equine neck isolated the head from the trunk enabling both segments to provide a spatial reference frame.

a New Survey on Self-Tuning Integrated Low-Cost Gps/ins Vehicle Navigation System in Harsh Environment

NASA Astrophysics Data System (ADS)

Navidi, N.; Landry, R., Jr.

2015-08-01

Nowadays, Global Positioning System (GPS) receivers are aided by some complementary radio navigation systems and Inertial Navigation Systems (INS) to obtain more accuracy and robustness in land vehicular navigation. Extended Kalman Filter (EKF) is an acceptable conventional method to estimate the position, the velocity, and the attitude of the navigation system when INS measurements are fused with GPS data. However, the usage of the low-cost Inertial Measurement Units (IMUs) based on the Micro-Electro-Mechanical Systems (MEMS), for the land navigation systems, reduces the precision and stability of the navigation system due to their inherent errors. The main goal of this paper is to provide a new model for fusing low-cost IMU and GPS measurements. The proposed model is based on EKF aided by Fuzzy Inference Systems (FIS) as a promising method to solve the mentioned problems. This model considers the parameters of the measurement noise to adjust the measurement and noise process covariance. The simulation results show the efficiency of the proposed method to reduce the navigation system errors compared with EKF.

Load-embedded inertial measurement unit reveals lifting performance.

PubMed

Tammana, Aditya; McKay, Cody; Cain, Stephen M; Davidson, Steven P; Vitali, Rachel V; Ojeda, Lauro; Stirling, Leia; Perkins, Noel C

2018-07-01

Manual lifting of loads arises in many occupations as well as in activities of daily living. Prior studies explore lifting biomechanics and conditions implicated in lifting-induced injuries through laboratory-based experimental methods. This study introduces a new measurement method using load-embedded inertial measurement units (IMUs) to evaluate lifting tasks in varied environments outside of the laboratory. An example vertical load lifting task is considered that is included in an outdoor obstacle course. The IMU data, in the form of the load acceleration and angular velocity, is used to estimate load vertical velocity and three lifting performance metrics: the lifting time (speed), power, and motion smoothness. Large qualitative differences in these parameters distinguish exemplar high and low performance trials. These differences are further supported by subsequent statistical analyses of twenty three trials (including a total of 115 total lift/lower cycles) from fourteen healthy participants. Results reveal that lifting time is strongly correlated with lifting power (as expected) but also correlated with motion smoothness. Thus, participants who lift rapidly do so with significantly greater power using motions that minimize motion jerk. Copyright © 2018 Elsevier Ltd. All rights reserved.

A dual-processor multi-frequency implementation of the FINDS algorithm

NASA Technical Reports Server (NTRS)

Godiwala, Pankaj M.; Caglayan, Alper K.

1987-01-01

This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance.

Accurate Visual Heading Estimation at High Rotation Rate Without Oculomotor or Static-Depth Cues

NASA Technical Reports Server (NTRS)

Stone, Leland S.; Perrone, John A.; Null, Cynthia H. (Technical Monitor)

1995-01-01

It has been claimed that either oculomotor or static depth cues provide the signals about self-rotation necessary approx.-1 deg/s. We tested this hypothesis by simulating self-motion along a curved path with the eyes fixed in the head (plus or minus 16 deg/s of rotation). Curvilinear motion offers two advantages: 1) heading remains constant in retinotopic coordinates, and 2) there is no visual-oculomotor conflict (both actual and simulated eye position remain stationary). We simulated 400 ms of rotation combined with 16 m/s of translation at fixed angles with respect to gaze towards two vertical planes of random dots initially 12 and 24 m away, with a field of view of 45 degrees. Four subjects were asked to fixate a central cross and to respond whether they were translating to the left or right of straight-ahead gaze. From the psychometric curves, heading bias (mean) and precision (semi-interquartile) were derived. The mean bias over 2-5 runs was 3.0, 4.0, -2.0, -0.4 deg for the first author and three naive subjects, respectively (positive indicating towards the rotation direction). The mean precision was 2.0, 1.9, 3.1, 1.6 deg. respectively. The ability of observers to make relatively accurate and precise heading judgments, despite the large rotational flow component, refutes the view that extra-flow-field information is necessary for human visual heading estimation at high rotation rates. Our results support models that process combined translational/rotational flow to estimate heading, but should not be construed to suggest that other cues do not play an important role when they are available to the observer.

Two-Stage Parameter Estimation in Confined Costal Aquifers

NASA Astrophysics Data System (ADS)

Hsu, N.

2003-12-01

Using field observations of tidal level and piezometric head at an observation well, this research develops a two-stage parameter estimation approach for estimating the hydraulic conductivity (T) and storage coefficient (S) of a confined aquifer in a costal area. While the y-axis coincides with the coastline, the x-axis extends from zero to infinity and, therefore, the domain of the aquifer is assumed to be a half plane. Other assumptions include homogeneity, isotropy and constant thickness of the aquifer, and zero initial head distribution. In the first stage, fluctuations of the tidal level and piezometric head at the observation well are collected simultaneously without the influence of pumping. Fourier spectra analysis is used to find the autocorrelation and crosscorrelation of the two sets of observations as well as the phase vs. frequency function. The tidal efficiency and time delay can then be computed. The analytical solution of Ferris (1951) is then used to compute the ratio of T/S. In the second stage, the system is stressed with pumping and observations of the tidal level and piezometric head at the observation well are collected simultaneously. The effect of tide to the observation well without pumping can be computed by the analytical solution of Ferris (1951) based upon the identified ratio of T/S and is deducted from the piezometric head observations to obtain the updated piezometric head. Theis equation coupled with the method of image is then applied to the updated piezometric head to obtain the T and S values. The developed approach is applied to a hypothetical aquifer. The results obtained show convergence of the approach. The robustness of the developed approach is also demonstrated by using noise-corrupted observations.

Head-Impact-Measurement Devices: A Systematic Review.

PubMed

O'Connor, Kathryn L; Rowson, Steven; Duma, Stefan M; Broglio, Steven P

2017-03-01

With an estimated 3.8 million sport- and recreation-related concussions occurring annually, targeted prevention and diagnostic methods are needed. Biomechanical analysis of head impacts may provide quantitative information that can inform both prevention and diagnostic strategies. To assess available head-impact devices and their clinical utility. We performed a systematic search of the electronic database PubMed for peer-reviewed publications, using the following phrases: accelerometer and concussion, head impact telemetry, head impacts and concussion and sensor, head impacts and sensor, impact sensor and concussion, linear acceleration and concussion, rotational acceleration and concussion, and xpatch concussion. In addition to the literature review, a Google search for head impact monitor and concussion monitor yielded 15 more devices. Included studies were performed in vivo, used commercially available devices, and focused on sport-related concussion. One author reviewed the title and abstract of each study for inclusion and exclusion criteria and then reviewed each full-text article to confirm inclusion criteria. Controversial articles were reviewed by all authors to reach consensus. In total, 61 peer-reviewed articles involving 4 head-impact devices were included. Participants in boxing, football, ice hockey, soccer, or snow sports ranged in age from 6 to 24 years; 18% (n = 11) of the studies included female athletes. The Head Impact Telemetry System was the most widely used device (n = 53). Fourteen additional commercially available devices were presented. Measurements collected by impact monitors provided real-time data to estimate player exposure but did not have the requisite sensitivity to concussion. Proper interpretation of previously reported head-impact kinematics across age, sport, and position may inform future research and enable staff clinicians working on the sidelines to monitor athletes. However, head-impact-monitoring systems have limited clinical utility due to error rates, designs, and low specificity in predicting concussive injury.

Estimating Aircraft Heading Based on Laserscanner Derived Point Clouds

NASA Astrophysics Data System (ADS)

Koppanyi, Z.; Toth, C., K.

2015-03-01

Using LiDAR sensors for tracking and monitoring an operating aircraft is a new application. In this paper, we present data processing methods to estimate the heading of a taxiing aircraft using laser point clouds. During the data acquisition, a Velodyne HDL-32E laser scanner tracked a moving Cessna 172 airplane. The point clouds captured at different times were used for heading estimation. After addressing the problem and specifying the equation of motion to reconstruct the aircraft point cloud from the consecutive scans, three methods are investigated here. The first requires a reference model to estimate the relative angle from the captured data by fitting different cross-sections (horizontal profiles). In the second approach, iterative closest point (ICP) method is used between the consecutive point clouds to determine the horizontal translation of the captured aircraft body. Regarding the ICP, three different versions were compared, namely, the ordinary 3D, 3-DoF 3D and 2-DoF 3D ICP. It was found that 2-DoF 3D ICP provides the best performance. Finally, the last algorithm searches for the unknown heading and velocity parameters by minimizing the volume of the reconstructed plane. The three methods were compared using three test datatypes which are distinguished by object-sensor distance, heading and velocity. We found that the ICP algorithm fails at long distances and when the aircraft motion direction perpendicular to the scan plane, but the first and the third methods give robust and accurate results at 40m object distance and at ~12 knots for a small Cessna airplane.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter.

PubMed

Alatise, Mary B; Hancke, Gerhard P

2017-09-21

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders.

PubMed

Huang, Haoqian; Chen, Xiyuan; Zhang, Bo; Wang, Jian

2017-01-01

The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter

PubMed Central

Hancke, Gerhard P.

2017-01-01

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs). PMID:28934102

General Revenue Financing of Medicare: Who Will Bear the Burden?

PubMed Central

Johnson, Janet L.; Long, Stephen H.

1982-01-01

Two recent national advisory committees on Social Security recommended major shifts in Medicare financing to preserve the financial viability of the Social Security trust funds. This paper estimates the income redistribution consequences of the two proposals, in contrast to current law, using a micro-simulation model of taxes and premiums. These estimates show that while the current Medicare financing package is mildly progressive, the new proposals would substantially increase income redistribution under the program. Two insights provided by separate estimates, for families headed by the elderly (persons age 65 or over) versus those headed by the non-elderly, are: 1) the surprisingly large Medicare tax burdens on families headed by the elderly under the current financing package of payroll taxes, general revenues, and enrollee premiums; and 2) the substantial increases in these burdens under proposed shifts toward increased general revenue financing. PMID:10309601

National Profiles of Classroom Quality and Family Involvement: A Multilevel Examination of Proximal Influences on Head Start Children's School Readiness

ERIC Educational Resources Information Center

Bulotsky-Shearer, Rebecca J.; Wen, Xiaoli; Faria, Ann-Marie; Hahs-Vaughn, Debbie L.; Korfmacher, Jon

2012-01-01

Guided by a developmental and ecological model, the study employed latent profile analysis to identify a multilevel typology of family involvement and Head Start classroom quality. Using the nationally representative Head Start Family and Child Experiences Survey (FACES 1997; N = 1870), six multilevel latent profiles were estimated, characterized…

Supine Length, Weight and Head Circumference at Birth in Central Iran

ERIC Educational Resources Information Center

Ayatollahi, S. M. T.; Rafiei, Mohammad

2007-01-01

Supine length, weight and head circumferences of 10,241 neonates (5241 boys, 5000 girls, sex ratio 105) born in Arak (central Iran) in 2004 are reported. The mean plus or minus standard deviation of boys' and girls' (p value for sex difference) supine length (mm), weight (g) and head circumference (mm) were estimated as 501 plus or minus 30 and…

Two-Year versus One-Year Head Start Program Impact: Addressing Selection Bias by Comparing Regression Modeling with Propensity Score Analysis

ERIC Educational Resources Information Center

Leow, Christine; Wen, Xiaoli; Korfmacher, Jon

2015-01-01

This article compares regression modeling and propensity score analysis as different types of statistical techniques used in addressing selection bias when estimating the impact of two-year versus one-year Head Start on children's school readiness. The analyses were based on the national Head Start secondary dataset. After controlling for…

Factors affecting breeding season survival of red-headed woodpeckers in South Carolina

Treesearch

John C. Kilgo; Mark Vukovich

2012-01-01

Red-headed woodpecker (Melanerpes erythrocephalus) populations have declined in the United States and Canada over the past 40 years. However, few demographic studies have been published on the species and none have addressed adult survival. During 2006¨C2007, we estimated survival probabilities of 80 radio-tagged red-headed woodpeckers during the breeding season in...

A Review of Instrumented Equipment to Investigate Head Impacts in Sport

PubMed Central

2016-01-01

Contact, collision, and combat sports have more head impacts as compared to noncontact sports; therefore, such sports are uniquely suited to the investigation of head impact biomechanics. Recent advances in technology have enabled the development of instrumented equipment, which can estimate the head impact kinematics of human subjects in vivo. Literature pertaining to head impact measurement devices was reviewed and usage, in terms of validation and field studies, of such devices was discussed. Over the past decade, instrumented equipment has recorded millions of impacts in the laboratory, on the field, in the ring, and on the ice. Instrumented equipment is not without limitations; however, in vivo head impact data is crucial to investigate head injury mechanisms and further the understanding of concussion. PMID:27594780

A Roll, Fin, and Fin Controller Prediction Computer Program.

DTIC Science & Technology

1980-06-01

IERATI *EQ. 03 WRITE16920301 ROLL 365 365 3R1TE(G. 26311 ROLL 366 no 505 ImU - 1,NNU ROLL 36? 50S WRITE(G.2011 3U(I’U),OAWPU(1PU,SIGLCfINU) ROLL 360...ROLL DAMPING WILL BE ONE**/$ ROLL 642 2016 FORMAT (/jIX,*LONGCRESTEO SVECTRA AND COMPONENTS WILL SE PRINTED. ROLL 44S 2’) ROLL 444 2019 FORMAT (1/19

Magician Simulator: A Realistic Simulator for Heterogenous Teams of Autonomous Robots. MAGIC 2010 Challenge

DTIC Science & Technology

2011-02-07

Sensor UGVs (SUGV) or Disruptor UGVs, depending on their payload. The SUGVs included vision, GPS/IMU, and LIDAR systems for identifying and tracking...employed by all the MAGICian research groups. Objects of interest were tracked using standard LIDAR and Computer Vision template-based feature...tracking approaches. Mapping was solved through Multi-Agent particle-filter based Simultaneous Locali- zation and Mapping ( SLAM ). Our system contains

Magician Simulator. A Realistic Simulator for Heterogenous Teams of Autonomous Robots

DTIC Science & Technology

2011-01-18

IMU, and LIDAR systems for identifying and tracking mobile OOI at long range (>20m), providing early warnings and allowing neutralization from a... LIDAR and Computer Vision template-based feature tracking approaches. Mapping was solved through Multi-Agent particle-filter based Simultaneous...Locali- zation and Mapping ( SLAM ). Our system contains two maps, a physical map and an influence map (location of hostile OOI, explored and unexplored

CTC Sentinel. Volume 7, Issue 7

DTIC Science & Technology

2014-07-01

provide other support activities to organizations operating outside of Europe.3 The largely laissez - faire attitude of Swiss authorities (an approach, it...Counterterrorism Strategy By J.N.C. Hill 18 Contrasting the Leadership of Mullah Fazlullah and Khan Said Sajna in Pakistan By Daud Khattak 20...the IMU’s leadership since 2009.5 The existing literature, however, fails to explore the role played by the IMU in recent high- profile attacks in

A Challenge for Micro and Mini UAV: The Sensor Problem

DTIC Science & Technology

2005-05-01

pressure airspeed sensors on one single circuit board (Figure 8). Figure 8: Autopilot. The Quadcopter The fourth and final MAV is a quad-copter with...UNCLASSIFIED/UNLIMITED Figure 9: Quadcopter MAV. Figure 10: Loopshaping Diagram. The IMU contains 3 MEMS gyros. These form the rotational sensors Gx...flapping wings) and even by insects (vibrating wings). Once in operation, they will be extremely discrete, making it very difficult to distinct

Sensing, Navigation and Reasoning Technologies for the DARPA Urban Challenge

DTIC Science & Technology

2007-12-31

from the Applanix hardware and processed the data to account for state jumps. It then broadcast the world and local frame coordinate for the vehicle...contiguous series of control tactics, as requested by the Control. 22 Team Caltech Sensing and Mapping Subsystem Health Monitor Applanix (GPS and IMU...California Institute of Technology, Big Dog Ventures, Northrop Grumman Corporation, Mohr Davidow Ventures and Applanix Inc. The authors would also

TARDEC Ground Vehicle Robotics: Vehicle Dynamic Characterization and Research

DTIC Science & Technology

2015-09-01

inferred roll angles that are found with the IMU . This is usually done with UNCLASSIFIED UNCLASSIFIED linear potentiometers, which have an electrical...wire electric, Electric traction control. Suspension Styles: Suspension is what keeps the vehicle off the ground and mechanically isolated from the...lot” maneuvers. Because of this, they roll with no slip angles. This means that the steering angles of the front wheels must be calibrated perfectly

Wave Evolution in River Mouths and Tidal Inlets

DTIC Science & Technology

2014-06-01

Monterey Bay by a Datawell Buoy (blue) and three collocated WRD buoys (red). Also shown is the f −4 spectral roll off (black dashed). .............. 48...f −4 spectral roll off (black dashed) and the blocking frequency in regions B-E. .................................................... 53   Figure...Significant Wave Height Hz hertz IMU Inertial measurement unit JONSWAP Joint North Sea Wave Program km kilometer MCR Mouth of the Columbia River MEMS

Lords of the Silk Route: Violent Non-State Actors in Central Asia

DTIC Science & Technology

2002-05-01

communications, internet connectivity, and the like; however, more traditional activities, such as simple cross-border smuggling, remain popular in the...Uzbekistan. It is a government production intended to sustain popular support for an on-going conflict with the Islamic Movement of Uzbekistan (IMU...valuable, cost-effective research to meet the needs of our sponsors. We appreciate your continued interest in INSS and our research products

Biosleeve Human-Machine Interface

NASA Technical Reports Server (NTRS)

Assad, Christopher (Inventor)

2016-01-01

Systems and methods for sensing human muscle action and gestures in order to control machines or robotic devices are disclosed. One exemplary system employs a tight fitting sleeve worn on a user arm and including a plurality of electromyography (EMG) sensors and at least one inertial measurement unit (IMU). Power, signal processing, and communications electronics may be built into the sleeve and control data may be transmitted wirelessly to the controlled machine or robotic device.

General test plan redundant sensor strapdown IMU evaluation program

NASA Technical Reports Server (NTRS)

Hartwell, T.; Irwin, H. A.; Miyatake, Y.; Wedekind, D. E.

1971-01-01

The general test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The inertial unit contains six gyros and three orthogonal accelerometers. The software incorporates failure detection and correction logic and a land vehicle navigation program. The principal objective of the test is a demonstration of the practicability, reliability, and performance of the inertial measuring unit with failure detection and correction in operational environments.

A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients

PubMed Central

Rodríguez-Martín, Daniel; Pérez-López, Carlos; Samà, Albert; Català, Andreu; Moreno Arostegui, Joan Manuel; Cabestany, Joan; Mestre, Berta; Alcaine, Sheila; Prats, Anna; de la Cruz Crespo, María; Bayés, Àngels

2017-01-01

Inertial measurement units (IMUs) are devices used, among other fields, in health applications, since they are light, small and effective. More concretely, IMUs have been demonstrated to be useful in the monitoring of motor symptoms of Parkinson’s disease (PD). In this sense, most of previous works have attempted to assess PD symptoms in controlled environments or short tests. This paper presents the design of an IMU, called 9 × 3, that aims to assess PD symptoms, enabling the possibility to perform a map of patients’ symptoms at their homes during long periods. The device is able to acquire and store raw inertial data for artificial intelligence algorithmic training purposes. Furthermore, the presented IMU enables the real-time execution of the developed and embedded learning models. Results show the great flexibility of the 9 × 3, storing inertial information and algorithm outputs, sending messages to external devices and being able to detect freezing of gait and bradykinetic gait. Results obtained in 12 patients exhibit a sensitivity and specificity over 80%. Additionally, the system enables working 23 days (at waking hours) with a 1200 mAh battery and a sampling rate of 50 Hz, opening up the possibility to be used for other applications like wellbeing and sports. PMID:28398265

Position Tracking During Human Walking Using an Integrated Wearable Sensing System.

PubMed

Zizzo, Giulio; Ren, Lei

2017-12-10

Progress has been made enabling expensive, high-end inertial measurement units (IMUs) to be used as tracking sensors. However, the cost of these IMUs is prohibitive to their widespread use, and hence the potential of low-cost IMUs is investigated in this study. A wearable low-cost sensing system consisting of IMUs and ultrasound sensors was developed. Core to this system is an extended Kalman filter (EKF), which provides both zero-velocity updates (ZUPTs) and Heuristic Drift Reduction (HDR). The IMU data was combined with ultrasound range measurements to improve accuracy. When a map of the environment was available, a particle filter was used to impose constraints on the possible user motions. The system was therefore composed of three subsystems: IMUs, ultrasound sensors, and a particle filter. A Vicon motion capture system was used to provide ground truth information, enabling validation of the sensing system. Using only the IMU, the system showed loop misclosure errors of 1% with a maximum error of 4-5% during walking. The addition of the ultrasound sensors resulted in a 15% reduction in the total accumulated error. Lastly, the particle filter was capable of providing noticeable corrections, which could keep the tracking error below 2% after the first few steps.

Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation

PubMed Central

Broumandan, Ali; Lachapelle, Gérard

2018-01-01

Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated. PMID:29695064

Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation.

PubMed

Broumandan, Ali; Lachapelle, Gérard

2018-04-24

Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated.

Calibration Matters: Advances in Strapdown Airborne Gravimetry

NASA Astrophysics Data System (ADS)

Becker, D.

2015-12-01

Using a commercial navigation-grade strapdown inertial measurement unit (IMU) for airborne gravimetry can be advantageous in terms of cost, handling, and space consumption compared to the classical stable-platform spring gravimeters. Up to now, however, large sensor errors made it impossible to reach the mGal-level using such type IMUs as they are not designed or optimized for this kind of application. Apart from a proper error-modeling in the filtering process, specific calibration methods that are tailored to the application of aerogravity may help to bridge this gap and to improve their performance. Based on simulations, a quantitative analysis is presented on how much IMU sensor errors, as biases, scale factors, cross couplings, and thermal drifts distort the determination of gravity and the deflection of the vertical (DOV). Several lab and in-field calibration methods are briefly discussed, and calibration results are shown for an iMAR RQH unit. In particular, a thermal lab calibration of its QA2000 accelerometers greatly improved the long-term drift behavior. Latest results from four recent airborne gravimetry campaigns confirm the effectiveness of the calibrations applied, with cross-over accuracies reaching 1.0 mGal (0.6 mGal after cross-over adjustment) and DOV accuracies reaching 1.1 arc seconds after cross-over adjustment.

Atrial Fibrillation Detection via Accelerometer and Gyroscope of a Smartphone.

PubMed

Lahdenoja, Olli; Hurnanen, Tero; Iftikhar, Zuhair; Nieminen, Sami; Knuutila, Timo; Saraste, Antti; Kiviniemi, Tuomas; Vasankari, Tuija; Airaksinen, Juhani; Pankaala, Mikko; Koivisto, Tero

2018-01-01

We present a smartphone-only solution for the detection of atrial fibrillation (AFib), which utilizes the built-in accelerometer and gyroscope sensors [inertial measurement unit, (IMU)] in the detection. Depending on the patient's situation, it is possible to use the developed smartphone application either regularly or occasionally for making a measurement of the subject. The smartphone is placed on the chest of the patient who is adviced to lay down and perform a noninvasive recording, while no external sensors are needed. After that, the application determines whether the patient suffers from AFib or not. The presented method has high potential to detect paroxysmal ("silent") AFib from large masses. In this paper, we present the preprocessing, feature extraction, feature analysis, and classification results of the envisioned AFib detection system based on clinical data acquired with a standard mobile phone equipped with Google Android OS. Test data was gathered from 16 AFib patients (validated against ECG), as well as a control group of 23 healthy individuals with no diagnosed heart diseases. We obtained an accuracy of 97.4% in AFib versus healthy classification (a sensitivity of 93.8% and a specificity of 100%). Due to the wide availability of smart devices/sensors with embedded IMU, the proposed methods could potentially also scale to other domains such as embedded body-sensor networks.

SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell

PubMed Central

González-Partida, José-Tomás; Almorox-González, Pablo; Burgos-García, Mateo; Dorta-Naranjo, Blas-Pablo

2008-01-01

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar. PMID:27879884

SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell.

PubMed

González-Partida, José-Tomás; Almorox-González, Pablo; Burgos-Garcia, Mateo; Dorta-Naranjo, Blas-Pablo

2008-05-23

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar.

Engineering analyses for railroad tank car head puncture resistance

DOT National Transportation Integrated Search

2006-11-06

This paper describes engineering analyses to estimate the : forces, deformations, and puncture resistance of railroad tank : cars. Different approaches to examine puncture of the tank car : head are described. One approach is semi-empirical equations...

Correction of static pressure on a research aircraft in accelerated flight using differential pressure measurements

NASA Astrophysics Data System (ADS)

Rodi, A. R.; Leon, D. C.

2012-11-01

A method is described that estimates the error in the static pressure measurement on an aircraft from differential pressure measurements on the hemispherical surface of a Rosemount model 858AJ air velocity probe mounted on a boom ahead of the aircraft. The theoretical predictions for how the pressure should vary over the surface of the hemisphere, involving an unknown sensitivity parameter, leads to a set of equations that can be solved for the unknowns - angle of attack, angle of sideslip, dynamic pressure and the error in static pressure - if the sensitivity factor can be determined. The sensitivity factor was determined on the University of Wyoming King Air research aircraft by comparisons with the error measured with a carefully designed sonde towed on connecting tubing behind the aircraft - a trailing cone - and the result was shown to have a precision of about ±10 Pa over a wide range of conditions, including various altitudes, power settings, and gear and flap extensions. Under accelerated flight conditions, geometric altitude data from a combined Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) system are used to estimate acceleration effects on the error, and the algorithm is shown to predict corrections to a precision of better than ±20 Pa under those conditions. Some limiting factors affecting the precision of static pressure measurement on a research aircraft are discussed.

A multimodal 3D framework for fire characteristics estimation

NASA Astrophysics Data System (ADS)

Toulouse, T.; Rossi, L.; Akhloufi, M. A.; Pieri, A.; Maldague, X.

2018-02-01

In the last decade we have witnessed an increasing interest in using computer vision and image processing in forest fire research. Image processing techniques have been successfully used in different fire analysis areas such as early detection, monitoring, modeling and fire front characteristics estimation. While the majority of the work deals with the use of 2D visible spectrum images, recent work has introduced the use of 3D vision in this field. This work proposes a new multimodal vision framework permitting the extraction of the three-dimensional geometrical characteristics of fires captured by multiple 3D vision systems. The 3D system is a multispectral stereo system operating in both the visible and near-infrared (NIR) spectral bands. The framework supports the use of multiple stereo pairs positioned so as to capture complementary views of the fire front during its propagation. Multimodal registration is conducted using the captured views in order to build a complete 3D model of the fire front. The registration process is achieved using multisensory fusion based on visual data (2D and NIR images), GPS positions and IMU inertial data. Experiments were conducted outdoors in order to show the performance of the proposed framework. The obtained results are promising and show the potential of using the proposed framework in operational scenarios for wildland fire research and as a decision management system in fighting.

Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field

PubMed Central

Ilyas, Muhammad; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok

2016-01-01

Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called “virtual sensor”), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth’s magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms. PMID:27618056

Ship heading and velocity analysis by wake detection in SAR images

NASA Astrophysics Data System (ADS)

Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

2016-11-01

With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement.

PubMed

Gao, Nuo; Zhu, S A; He, Bin

2005-06-07

We have developed a new algorithm for magnetic resonance electrical impedance tomography (MREIT), which uses only one component of the magnetic flux density to reconstruct the electrical conductivity distribution within the body. The radial basis function (RBF) network and simplex method are used in the present approach to estimate the conductivity distribution by minimizing the errors between the 'measured' and model-predicted magnetic flux densities. Computer simulations were conducted in a realistic-geometry head model to test the feasibility of the proposed approach. Single-variable and three-variable simulations were performed to estimate the brain-skull conductivity ratio and the conductivity values of the brain, skull and scalp layers. When SNR = 15 for magnetic flux density measurements with the target skull-to-brain conductivity ratio being 1/15, the relative error (RE) between the target and estimated conductivity was 0.0737 +/- 0.0746 in the single-variable simulations. In the three-variable simulations, the RE was 0.1676 +/- 0.0317. Effects of electrode position uncertainty were also assessed by computer simulations. The present promising results suggest the feasibility of estimating important conductivity values within the head from noninvasive magnetic flux density measurements.

A simple approach to ignoring irrelevant variables by population decoding based on multisensory neurons

PubMed Central

Kim, HyungGoo R.; Pitkow, Xaq; Angelaki, Dora E.

2016-01-01

Sensory input reflects events that occur in the environment, but multiple events may be confounded in sensory signals. For example, under many natural viewing conditions, retinal image motion reflects some combination of self-motion and movement of objects in the world. To estimate one stimulus event and ignore others, the brain can perform marginalization operations, but the neural bases of these operations are poorly understood. Using computational modeling, we examine how multisensory signals may be processed to estimate the direction of self-motion (i.e., heading) and to marginalize out effects of object motion. Multisensory neurons represent heading based on both visual and vestibular inputs and come in two basic types: “congruent” and “opposite” cells. Congruent cells have matched heading tuning for visual and vestibular cues and have been linked to perceptual benefits of cue integration during heading discrimination. Opposite cells have mismatched visual and vestibular heading preferences and are ill-suited for cue integration. We show that decoding a mixed population of congruent and opposite cells substantially reduces errors in heading estimation caused by object motion. In addition, we present a general formulation of an optimal linear decoding scheme that approximates marginalization and can be implemented biologically by simple reinforcement learning mechanisms. We also show that neural response correlations induced by task-irrelevant variables may greatly exceed intrinsic noise correlations. Overall, our findings suggest a general computational strategy by which neurons with mismatched tuning for two different sensory cues may be decoded to perform marginalization operations that dissociate possible causes of sensory inputs. PMID:27334948

Hydra multiple head star sensor and its in-flight self-calibration of optical heads alignment

NASA Astrophysics Data System (ADS)

Majewski, L.; Blarre, L.; Perrimon, N.; Kocher, Y.; Martinez, P. E.; Dussy, S.

2017-11-01

HYDRA is EADS SODERN new product line of APS-based autonomous star trackers. The baseline is a multiple head sensor made of three separated optical heads and one electronic unit. Actually the concept which was chosen offers more than three single-head star trackers working independently. Since HYDRA merges all fields of view the result is a more accurate, more robust and completely autonomous multiple-head sensor, releasing the AOCS from the need to manage the outputs of independent single-head star trackers. Specific to the multiple head architecture and the underlying data fusion, is the calibration of the relative alignments between the sensor optical heads. The performance of the sensor is related to its estimation of such alignments. HYDRA design is first reminded in this paper along with simplification it can bring at system level (AOCS). Then self-calibration of optical heads alignment is highlighted through descriptions and simulation results, thus demonstrating the performances of a key part of HYDRA multiple-head concept.

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection.

PubMed

Power, Jonathan D; Plitt, Mark; Kundu, Prantik; Bandettini, Peter A; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10-50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion).

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection

PubMed Central

Plitt, Mark; Kundu, Prantik; Bandettini, Peter A.; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). PMID:28880888

Stabilization and mobility of the head, neck and trunk in horses during overground locomotion: comparisons with humans and other primates

PubMed Central

Dunbar, Donald C.; Macpherson, Jane M.; Simmons, Roger W.; Zarcades, Athina

2009-01-01

SUMMARY Segmental kinematics were investigated in horses during overground locomotion and compared with published reports on humans and other primates to determine the impact of a large neck on rotational mobility (>20deg.) and stability (≤20deg.) of the head and trunk. Three adult horses (Equus caballus) performing walks, trots and canters were videotaped in lateral view. Data analysis included locomotor velocity, segmental positions, pitch and linear displacements and velocities, and head displacement frequencies. Equine, human and monkey skulls and cervical spines were measured to estimate eye and vestibular arc length during head pitch displacements. Horses stabilized all three segments in all planes during all three gaits, unlike monkeys and humans who make large head pitch and yaw rotations during walks, and monkeys that make large trunk pitch rotations during gallops. Equine head angular displacements and velocities, with some exceptions during walks, were smaller than in humans and other primates. Nevertheless, owing to greater off-axis distances, orbital and vestibular arc lengths remained larger in horses, with the exception of head–neck axial pitch during trots, in which equine arc lengths were smaller than in running humans. Unlike monkeys and humans, equine head peak-frequency ranges fell within the estimated range in which inertia has a compensatory stabilizing effect. This inertial effect was typically over-ridden, however, by muscular or ligamentous intervention. Thus, equine head pitch was not consistently compensatory, as reported in humans. The equine neck isolated the head from the trunk enabling both segments to provide a spatial reference frame. PMID:19043061

Use of head circumference as a predictor of height of individual.

PubMed

Mansur, D I; Haque, M K; Sharma, K; Mehta, D K; Shakya, R

2014-01-01

Establishing personal identity is one of the main concerns in forensic investigations. In forensic anthropology, estimation of height from head circumference has a significant role in establishing personal identity. The objective of the present study was an attempt to understand the relationship between height and head circumference of an individual and to derive regression formulae to estimate the height from the head circumference. The present study consisted of 440 (258 male and 182 female) students of age group 17 to 25 years studying in Kathmandu University School of Medical Sciences, Dhulikhel, Nepal during the period from November 2012 to October 2013. Height and head circumference of an individual were measured in centimeter. Data were analyzed by using statistical software SPSS-16. The findings of the present study were significant correlation between height and head circumference (r = 0.443, p < 0.01 for male, r = 0.302, p<0.01 for female, and r = 0. 398, p < 0.01 for combined (male and female). The regression equation for height and head circumference was found to be Y = 1.734X + 70.36 (R2 = 0.196) for male, Y = 0.916X + 106.8 (R2 = 0.091) for female, and Y = 1.648 X + 71.69 (R2 = 0.158) for combined (male and female), where Y is the height of Individual and X is the Head Circumference. Head circumference showed highly significant positive correlation with individual's height. Therefore, the present study will help in medico-legal cases in establishing the identity of an individual and this would also be useful for Anatomists and Anthropologists.

Quantitative evaluation of dual-flip-angle T1 mapping on DCE-MRI kinetic parameter estimation in head and neck

PubMed Central

Chow, Steven Kwok Keung; Yeung, David Ka Wai; Ahuja, Anil T; King, Ann D

2012-01-01

Purpose To quantitatively evaluate the kinetic parameter estimation for head and neck (HN) dynamic contrast-enhanced (DCE) MRI with dual-flip-angle (DFA) T1 mapping. Materials and methods Clinical DCE-MRI datasets of 23 patients with HN tumors were included in this study. T1 maps were generated based on multiple-flip-angle (MFA) method and different DFA combinations. Tofts model parameter maps of kep, Ktrans and vp based on MFA and DFAs were calculated and compared. Fitted parameter by MFA and DFAs were quantitatively evaluated in primary tumor, salivary gland and muscle. Results T1 mapping deviations by DFAs produced remarkable kinetic parameter estimation deviations in head and neck tissues. In particular, the DFA of [2º, 7º] overestimated, while [7º, 12º] and [7º, 15º] underestimated Ktrans and vp, significantly (P<0.01). [2º, 15º] achieved the smallest but still statistically significant overestimation for Ktrans and vp in primary tumors, 32.1% and 16.2% respectively. kep fitting results by DFAs were relatively close to the MFA reference compared to Ktrans and vp. Conclusions T1 deviations induced by DFA could result in significant errors in kinetic parameter estimation, particularly Ktrans and vp, through Tofts model fitting. MFA method should be more reliable and robust for accurate quantitative pharmacokinetic analysis in head and neck. PMID:23289084

Gender-related family head schooling and Aedes aegypti larval breeding risk in southern Mexico.

PubMed

Danis-Lozano, Rogelio; Rodríguez, Mario H; Hernández-Avila, Mauricio

2002-01-01

To investigate if family head genre-associated education is related to the risk of domiciliary Aedes aegypti larval breeding in a dengue-endemic village of Southern Mexico. A family head was considered to have a low education level if he/she had not completed elementary school. To estimate larval breeding risk within each household, a three-category Maya index was constructed using a weighted estimation of controllable and disposable domestic water containers. A socio-economic index was constructed based on household construction characteristics. Low-level education of either family head was associated to higher larval breeding risk. Households with low-educated mothers had more larval breeding containers. These associations persisted after adjusting for household socio-economic level. These results indicate that households with female family heads with low education levels accumulate more containers that favor Ae. aegypti breeding, and that education campaigns for dengue control should be addressed to this part of the population. The English version of this paper is available too at: http://www.insp.mx/salud/index.html.

Female headship, feminization of poverty and welfare.

PubMed

Kimenyi, M S; Mbaku, J M

1995-07-01

Female-headed households are at greater risk of slipping into poverty than male-headed households. Indeed, sex and marital status of the head of household are the most important determinants of a family's poverty status in the US. Divorce, separation, death of a husband, and out-of-wedlock births can lead to female headship. Transfer payments, especially the Aid to Families with Dependent Children program, are blamed for contributing to increased marital instability and out-of-wedlock births. The authors examined the role of welfare benefits in influencing female headship. Preliminary results using standard estimation procedures indicate that transfers do not significantly influence female headship. Standard estimation procedures are, however, erroneous because they ignore differences in propensities to establish mother-only households. Therefore, adjusting for differences in propensities to establish female-headed households, the level of welfare benefits is indeed an important factor in explaining the variation in the changes in the birth rates to unmarried women. The use of a weighted measure suggests that welfare benefits, by increasing female headship of women who otherwise have low propensities to be female heads, have played a significant role in the feminization of poverty.

Estimation of effective dose and lifetime attributable risk from multiple head CT scans in ventriculoperitoneal shunted children.

PubMed

Aw-Zoretic, J; Seth, D; Katzman, G; Sammet, S

2014-10-01

The purpose of this review is to determine the averaged effective dose and lifetime attributable risk factor from multiple head computed tomography (CT) dose data on children with ventriculoperitoneal shunts (VPS). A total of 422 paediatric head CT exams were found between October 2008 and January 2011 and retrospectively reviewed. The CT dose data was weighted with the latest IRCP 103 conversion factor to obtain the effective dose per study and the averaged effective dose was calculated. Estimates of the lifetime attributable risk were also calculated from the averaged effective dose using a conversion factor from the latest BEIR VII report. Our study found the highest effective doses in neonates and the lowest effective doses were observed in the 10-18 years age group. We estimated a 0.007% potential increase risk in neonates and 0.001% potential increased risk in teenagers over the base risk. Multiple head CTs in children equates to a slight potential increase risk in lifetime attributable risk over the baseline risk for cancer, slightly higher in neonates relative to teenagers. The potential risks versus clinical benefit must be assessed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Automatic facial animation parameters extraction in MPEG-4 visual communication

NASA Astrophysics Data System (ADS)

Yang, Chenggen; Gong, Wanwei; Yu, Lu

2002-01-01

Facial Animation Parameters (FAPs) are defined in MPEG-4 to animate a facial object. The algorithm proposed in this paper to extract these FAPs is applied to very low bit-rate video communication, in which the scene is composed of a head-and-shoulder object with complex background. This paper addresses the algorithm to automatically extract all FAPs needed to animate a generic facial model, estimate the 3D motion of head by points. The proposed algorithm extracts human facial region by color segmentation and intra-frame and inter-frame edge detection. Facial structure and edge distribution of facial feature such as vertical and horizontal gradient histograms are used to locate the facial feature region. Parabola and circle deformable templates are employed to fit facial feature and extract a part of FAPs. A special data structure is proposed to describe deformable templates to reduce time consumption for computing energy functions. Another part of FAPs, 3D rigid head motion vectors, are estimated by corresponding-points method. A 3D head wire-frame model provides facial semantic information for selection of proper corresponding points, which helps to increase accuracy of 3D rigid object motion estimation.

Comparison of americium-241 and technetium-99m as transmission sources for attenuation correction of thallium-201 SPECT imaging of the heart.

PubMed

Ficaro, E P; Fessler, J A; Rogers, W L; Schwaiger, M

1994-04-01

This study compares the ability of 241Am and 99mTc to estimate 201Tl attenuation maps while minimizing the loss in the precision of the emission data. A triple-head SPECT system with either an 241Am or 99mTc line source opposite a fan-beam collimator was used to estimate attenuation maps of the thorax of an anthropomorphic phantom. Linear attenuation values at 75 keV for 201Tl were obtained by linear extrapolation of the measured values from 241Am and 99mTc. Lung and soft-tissue estimates from both isotopes showed excellent agreement to within 3% of the measured values for 201Tl. Linear extrapolation did not yield satisfactory estimates for bone from either 241Am (+11.7%) or 99mTc (-15.3%). Patient data were used to estimate the dependence of crosstalk on patient size. Contamination from 201Tl in the transmission window was 5-6 times greater for 241Am compared to 99mTc, while the contamination in the 201Tl data in the transmission-emission detector head (head 1) was 4-5 times greater for 99mTc compared to 241Am. No contamination was detected in the 201Tl emission data of heads 2 and 3 from 241Am, whereas the 99mTc produced a small crosstalk component giving a signal-to-crosstalk ratio near 20:1. Measurements with a fillable chest phantom estimated the mean error introduced into the data from the removal of the crosstalk. Based on the measured data, 241Am is a suitable transmission source for simultaneous transmission-emission tomography for 201Tl cardiac studies.

Robust head pose estimation via supervised manifold learning.

PubMed

Wang, Chao; Song, Xubo

2014-05-01

Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations. Copyright © 2014 Elsevier Ltd. All rights reserved.

A miniature shoe-mounted orientation determination system for accurate indoor heading and trajectory tracking.

PubMed

Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Liu, Sheng

2016-06-01

Tracking the position of pedestrian is urgently demanded when the most commonly used GPS (Global Position System) is unavailable. Benefited from the small size, low-power consumption, and relatively high reliability, micro-electro-mechanical system sensors are well suited for GPS-denied indoor pedestrian heading estimation. In this paper, a real-time miniature orientation determination system (MODS) was developed for indoor heading and trajectory tracking based on a novel dual-linear Kalman filter. The proposed filter precludes the impact of geomagnetic distortions on pitch and roll that the heading is subjected to. A robust calibration approach was designed to improve the accuracy of sensors measurements based on a unified sensor model. Online tests were performed on the MODS with an improved turntable. The results demonstrate that the average RMSE (root-mean-square error) of heading estimation is less than 1°. Indoor heading experiments were carried out with the MODS mounted on the shoe of pedestrian. Besides, we integrated the existing MODS into an indoor pedestrian dead reckoning application as an example of its utility in realistic actions. A human attitude-based walking model was developed to calculate the walking distance. Test results indicate that mean percentage error of indoor trajectory tracking achieves 2% of the total walking distance. This paper provides a feasible alternative for accurate indoor heading and trajectory tracking.

Finding the most accurate method to measure head circumference for fetal weight estimation.

PubMed

Schmidt, Ulrike; Temerinac, Dunja; Bildstein, Katharina; Tuschy, Benjamin; Mayer, Jade; Sütterlin, Marc; Siemer, Jörn; Kehl, Sven

2014-07-01

Accurate measurement of fetal head biometry is important for fetal weight estimation (FWE) and is therefore an important prognostic parameter for neonatal morbidity and mortality and a valuable tool for determining the further obstetric management. Measurement of the head circumference (HC) in particular is employed in many commonly used weight equations. The aim of the present study was to find the most accurate method to measure head circumference for fetal weight estimation. This prospective study included 481 term pregnancies. Inclusion criteria were a singleton pregnancy and ultrasound examination with complete fetal biometric parameters within 3 days of delivery, and an absence of structural or chromosomal malformations. Different methods were used for ultrasound measurement of the HC (ellipse-traced, ellipse-calculated, and circle-calculated). As a reference method, HC was also determined using a measuring tape immediately after birth. FWE was carried out with Hadlock formulas, including either HC or biparietal diameter (BPD), and differences were compared using percentage error (PE), absolute percentage error (APE), limits of agreement (LOA), and cumulative distribution. The ellipse-traced method showed the best results for FWE among all of the ultrasound methods assessed. It had the lowest median APE and the narrowest LOA. With regard to the cumulative distribution, it included the largest number of cases at a discrepancy level of ±10%. The accuracy of BPD was similar to that of the ellipse-traced method when it was used instead of HC for weight estimation. Differences between the three techniques for calculating HC were small but significant. For clinical use, the ellipse-traced method should be recommended. However, when BPD is used instead of HC for FWE, the accuracy is similar to that of the ellipse-traced method. The BPD might therefore be a good alternative to head measurements in estimating fetal weight. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Measurement of Ship Air Wake Impact on a Remotely Piloted Vehicle

DTIC Science & Technology

2012-05-09

Figure 12. T-Rex 600 E Super Pro with “ spider leg” flotation system......................................... 16 Figure 13. x-IMU Inertial Measurement... spider legs” mounted underneath the helicopter. The “ spider legs” with free spinning 16 whiffle balls attached at the ends of each leg are...with “ spider leg” flotation system. 2.1.1.1 Remote Controlled Helicopter Training and Safety Program Safe operation of the RC helicopter was of

Handheld Synthetic Array Final Report, Part B

DTIC Science & Technology

2014-12-01

Multiple Model IMU Inertial Measurement Unit 4/154 IEEE Institute of Electrical and Electronics Engineers KF Kalman Filter KL Kullback - Leibler LAMBDA...important metric in information theory is the input–output mutual information (MI) that is used as an indicator of how much coded information can be...tracking using best- fitting Gaussian distributions,” Proc. Int. Conf. Inform . Fusion, pp. 1–8, 2005. [liv] L. Svensson, “On the Bayesian Cramér-Rao

Wide Area Assessment (WAA) for Marine Munitions and Explosives of Concern

DTIC Science & Technology

2011-08-01

from an integrated inertial system ( Applanix POS MV 320). This high performance system measured vessel pitch, roll, and heave, which was used by...measurement unit (IMU) of the Applanix POS MV 320 (Table 5-1). These offsets are used by the HYPACK®/HYSWEEP® acquisition software to combine and...calibration test (the “patch test” [refer to Section 5.5.3]), and whenever necessary as automatically determined by the Applanix software (POSView), an

JPRS Report, West Europe

DTIC Science & Technology

1987-06-09

remembers that the idea of participation, repeated last year at the congress in Courtrai, came from the VU? We stand for a free market economy with...be a RIZIV [National Institute for Health and Disability Insurance] office in every community ? This would in all respects make it impossible for the...a division of their own. This is shown by the new DAGENS NYHETER-IMU [Institute for Market Research] poll on confidence in the party leaders, in

Modular Electronics for Flash Memory Production

DTIC Science & Technology

2011-12-28

DEFENSE TECHNICAL INFORMATION CENTER ImuM ktkUmlimäj DTICfhas determined on oc öf^H AJI that this Technical Document has the Distribution...the second harmonic (8I2/8V2), and a normalization to remove the scale of the measured current. The red dashed lines represent notable vibrational...superimposed as red dashed lines. The agreement between the two spectroscopies is conclusive that we have successfully put our OPE derivative into the gap

How the Degree of Accuracy of an Inertial Measurement Unit (IMU) Influences the Miss Distance of a Gun-Launched Precision Munition

DTIC Science & Technology

2011-09-01

September 2011 Thesis Advisor: Walter E. Owen Second Reader: Donald E. Carlucci THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE...Author: David W. Panhorst Approved by: Dr. Walter E. Owen Dr. Donald E. Carlucci Dr. Clifford A. Whitcomb, Chair, Department...symmetric projectiles. Atglen, PA: Schiffer Publishing, Ltd. 42 New Webster’s dictionary of the English language. (1988). Melrose Park: Delair

Central Asia: Regional Developments and Implications for U.S. Interests

DTIC Science & Technology

2009-11-20

Central Asia. Other officials have stated that a large - scale influx has not yet occurred. Actions of the IMU and IJU in Germany and Elsewhere Officials...Independence: Regional Tensions and Conflicts”) that stated that “as large - scale military operations against terrorism have come to an end in... breeder reactor at Aktau that was the world’s only nuclear desalinization facility. In 1997 and 1999, U.S.-Kazakh accords were signed on

Development of Parameters for the Collection and Analysis of Lidar at Military Munitions Sites

DTIC Science & Technology

2010-01-01

and inertial measurement unit (IMU) equipment is used to locate the sensor in the air . The time of return of the laser signal allows for the...approximately 15 centimeters (cm) on soft ground surfaces and a horizontal accuracy of approximately 60 cm, both compared to surveyed control points...provide more accurate topographic data than other sources, at a reasonable cost compared to alternatives such as ground survey or photogrammetry

EEG source localization: Sensor density and head surface coverage.

PubMed

Song, Jasmine; Davey, Colin; Poulsen, Catherine; Luu, Phan; Turovets, Sergei; Anderson, Erik; Li, Kai; Tucker, Don

2015-12-30

The accuracy of EEG source localization depends on a sufficient sampling of the surface potential field, an accurate conducting volume estimation (head model), and a suitable and well-understood inverse technique. The goal of the present study is to examine the effect of sampling density and coverage on the ability to accurately localize sources, using common linear inverse weight techniques, at different depths. Several inverse methods are examined, using the popular head conductivity. Simulation studies were employed to examine the effect of spatial sampling of the potential field at the head surface, in terms of sensor density and coverage of the inferior and superior head regions. In addition, the effects of sensor density and coverage are investigated in the source localization of epileptiform EEG. Greater sensor density improves source localization accuracy. Moreover, across all sampling density and inverse methods, adding samples on the inferior surface improves the accuracy of source estimates at all depths. More accurate source localization of EEG data can be achieved with high spatial sampling of the head surface electrodes. The most accurate source localization is obtained when the voltage surface is densely sampled over both the superior and inferior surfaces. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law.

PubMed

Olsen, Cody S; Thomas, Andrea M; Singleton, Michael; Gaichas, Anna M; Smith, Tracy J; Smith, Gary A; Peng, Justin; Bauer, Michael J; Qu, Ming; Yeager, Denise; Kerns, Timothy; Burch, Cynthia; Cook, Lawrence J

2016-12-01

Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S. We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative risks (RR) and 95 % confidence intervals (CIs) for head, facial, traumatic brain, and moderate to severe head/facial injuries associated with helmet use within each helmet law setting using generalized log-binomial regression. Reported helmet use was higher in universal law states (88 % vs. 42 %). Median charges, adjusted for inflation and differences in state-incomes, were higher in partial law states (emergency department $1987 vs. $1443; inpatient $31,506 vs. $25,949). Injuries to the head and face, including traumatic brain injuries, were more common in partial law states. Effectiveness estimates of helmet use were higher in partial law states (adjusted-RR (CI) of head injury: 2.1 (1.9-2.2) partial law single vehicle; 1.4 (1.2, 1.6) universal law single vehicle; 1.8 (1.6-2.0) partial law multi-vehicle; 1.2 (1.1-1.4) universal law multi-vehicle). Medical charges and rates of head, facial, and brain injuries among motorcyclists were lower in universal law states. Helmets were effective in reducing injury in both helmet law settings; lower effectiveness estimates were observed in universal law states.

Motorcycle helmet effectiveness in reducing head, face and brain injuries by state and helmet law.

PubMed

Olsen, Cody S; Thomas, Andrea M; Singleton, Michael; Gaichas, Anna M; Smith, Tracy J; Smith, Gary A; Peng, Justin; Bauer, Michael J; Qu, Ming; Yeager, Denise; Kerns, Timothy; Burch, Cynthia; Cook, Lawrence J

Despite evidence that motorcycle helmets reduce morbidity and mortality, helmet laws and rates of helmet use vary by state in the U.S. We pooled data from eleven states: five with universal laws requiring all motorcyclists to wear a helmet, and six with partial laws requiring only a subset of motorcyclists to wear a helmet. Data were combined in the Crash Outcome Data Evaluation System's General Use Model and included motorcycle crash records probabilistically linked to emergency department and inpatient discharges for years 2005-2008. Medical outcomes were compared between partial and universal helmet law settings. We estimated adjusted relative risks (RR) and 95 % confidence intervals (CIs) for head, facial, traumatic brain, and moderate to severe head/facial injuries associated with helmet use within each helmet law setting using generalized log-binomial regression. Reported helmet use was higher in universal law states (88 % vs. 42 %). Median charges, adjusted for inflation and differences in state-incomes, were higher in partial law states (emergency department $1987 vs. $1443; inpatient $31,506 vs. $25,949). Injuries to the head and face, including traumatic brain injuries, were more common in partial law states. Effectiveness estimates of helmet use were higher in partial law states (adjusted-RR (CI) of head injury: 2.1 (1.9-2.2) partial law single vehicle; 1.4 (1.2, 1.6) universal law single vehicle; 1.8 (1.6-2.0) partial law multi-vehicle; 1.2 (1.1-1.4) universal law multi-vehicle). Medical charges and rates of head, facial, and brain injuries among motorcyclists were lower in universal law states. Helmets were effective in reducing injury in both helmet law settings; lower effectiveness estimates were observed in universal law states.

Analysis of a severe head injury in World Cup alpine skiing.

PubMed

Yamazaki, Junya; Gilgien, Matthias; Kleiven, Svein; McIntosh, Andrew S; Nachbauer, Werner; Müller, Erich; Bere, Tone; Bahr, Roald; Krosshaug, Tron

2015-06-01

Traumatic brain injury (TBI) is the leading cause of death in alpine skiing. It has been found that helmet use can reduce the incidence of head injuries between 15% and 60%. However, knowledge on optimal helmet performance criteria in World Cup alpine skiing is currently limited owing to the lack of biomechanical data from real crash situations. This study aimed to estimate impact velocities in a severe TBI case in World Cup alpine skiing. Video sequences from a TBI case in World Cup alpine skiing were analyzed using a model-based image matching technique. Video sequences from four camera views were obtained in full high-definition (1080p) format. A three-dimensional model of the course was built based on accurate measurements of piste landmarks and matched to the background video footage using the animation software Poser 4. A trunk-neck-head model was used for tracking the skier's trajectory. Immediately before head impact, the downward velocity component was estimated to be 8 m·s⁻¹. After impact, the upward velocity was 3 m·s⁻¹, whereas the velocity parallel to the slope surface was reduced from 33 m·s⁻¹ to 22 m·s⁻¹. The frontal plane angular velocity of the head changed from 80 rad·s⁻¹ left tilt immediately before impact to 20 rad·s⁻¹ right tilt immediately after impact. A unique combination of high-definition video footage and accurate measurements of landmarks in the slope made possible a high-quality analysis of head impact velocity in a severe TBI case. The estimates can provide crucial information on how to prevent TBI through helmet performance criteria and design.

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

Prevalence of Head Lice Infestation and Its Associated Factors among Primary School Students in Iran: A Systematic Review and Meta-analysis.

PubMed

Moosazadeh, Mahmood; Afshari, Mahdi; Keianian, Hormoz; Nezammahalleh, Asghar; Enayati, Ahmad Ali

2015-12-01

Head lice infestation is one of the most important health problems, generally involving children aged 5-13 years. This study aims to estimate the prevalence of head lice infestation and its associated factors among primary school children using systematic review and meta-analysis methods. Different national and international databases were searched for selecting the relevant studies using appropriate keywords, Medical Subject Heading terms, and references. Relevant studies with acceptable quality for meta-analysis were selected having excluded duplicate and irrelevant articles, quality assessment, and application of inclusion/exclusion criteria. With calculating standard errors according to binomial distribution and also considering the Cochrane's Q test as well as I-squared index for heterogeneity, pediculosis prevalence rate was estimated using Stata SE V.11 software. Forty studies met the inclusion criteria of this review and entered into the meta-analysis including 200,306 individuals. Using a random effect model, the prevalence (95% confidence interval) of head lice infestation among primary school children was estimated as 1.6% (1.2-2.05), 8.8% (7.6-9.9), and 7.4% (6.6-8.2) for boys, girls, and all the students, respectively. The infestation rate was found to be associated with low educational level of parents, long hair, family size, mother's job (housewife), father's job (worker/unemployed), using a common comb, lack of bathrooms in the house, and a low frequency of bathing. This meta-analysis revealed that the prevalence of head lice infestation among Iranian primary school children is relatively high with more prevalence among girls. We also found that economic, social, cultural, behavioral, and hygienic factors are associated with this infestation.

Head-Impact–Measurement Devices: A Systematic Review

PubMed Central

O'Connor, Kathryn L.; Rowson, Steven; Duma, Stefan M.; Broglio, Steven P.

2017-01-01

Context: With an estimated 3.8 million sport- and recreation-related concussions occurring annually, targeted prevention and diagnostic methods are needed. Biomechanical analysis of head impacts may provide quantitative information that can inform both prevention and diagnostic strategies. Objective: To assess available head-impact devices and their clinical utility. Data Sources: We performed a systematic search of the electronic database PubMed for peer-reviewed publications, using the following phrases: accelerometer and concussion, head impact telemetry, head impacts and concussion and sensor, head impacts and sensor, impact sensor and concussion, linear acceleration and concussion, rotational acceleration and concussion, and xpatch concussion. In addition to the literature review, a Google search for head impact monitor and concussion monitor yielded 15 more devices. Study Selection: Included studies were performed in vivo, used commercially available devices, and focused on sport-related concussion. Data Extraction: One author reviewed the title and abstract of each study for inclusion and exclusion criteria and then reviewed each full-text article to confirm inclusion criteria. Controversial articles were reviewed by all authors to reach consensus. Data Synthesis: In total, 61 peer-reviewed articles involving 4 head-impact devices were included. Participants in boxing, football, ice hockey, soccer, or snow sports ranged in age from 6 to 24 years; 18% (n = 11) of the studies included female athletes. The Head Impact Telemetry System was the most widely used device (n = 53). Fourteen additional commercially available devices were presented. Conclusions: Measurements collected by impact monitors provided real-time data to estimate player exposure but did not have the requisite sensitivity to concussion. Proper interpretation of previously reported head-impact kinematics across age, sport, and position may inform future research and enable staff clinicians working on the sidelines to monitor athletes. However, head-impact–monitoring systems have limited clinical utility due to error rates, designs, and low specificity in predicting concussive injury. PMID:28387553