Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditiona...Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.展开更多
Total knee arthroplasty is highly successful,in part due to range of motion(RoM)recovery.This is typically estimated goniometrically/visually by physical therapists(PTs)in the clinic,which is imprecise.Accordingly,a v...Total knee arthroplasty is highly successful,in part due to range of motion(RoM)recovery.This is typically estimated goniometrically/visually by physical therapists(PTs)in the clinic,which is imprecise.Accordingly,a validated inertial measurement unit(IMU)method for capturing knee RoM was deployed assessing postoperative RoM both in and outside of the clinical setting.The study's objectives were to evaluate the feasibility of continuously capturing knee RoM pre-/post-op via IMUs,dividing data into PT/non-PT portions of each day,and comparing PT/non-PT metrics.We hypothesized IMU-based clinical knee RoM would differ from IMU-based knee RoM captured outside clinical settings.10 patients(3 M,69±13 years)completed informed consent documents following ethics board approval.A validated IMU method captured long duration(8–12 h/day,~50 days)knee RoM pre-/post-op.Post-op metrics were subdivided(PT versus non-PT).Clinical RoM and patient reported outcome measures were also captured.Compliance and clinical disruption were evaluated.ANOVA compared post-op PT and non-PT means and change scores.Maximum flexion during PT was less than outside PT.PT stance/swing RoM and activity level were greater than outside PT.No temporal variable differences were found PT versus non-PT.IMU RoM measurements capture richer information than clinical measures.Maximum PT flexion was likely less than non-PT due to the exercises completed(i.e.high passive RoM vs.low RoM gait).PT gait flexion likely exceed non-PT because of‘white coat effects’wherein patients are closely monitored clinically.This implies data captured clinically represents optimum performance whereas data captured non-clinically represents realistic performance.展开更多
Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditiona...Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.展开更多
As low cost and highly portable sensors, inertial measurements units (IMU) have become increas-ingly used in gait analysis, embodying an efficient alternative to motion capture systems. Mean-while, being able to compu...As low cost and highly portable sensors, inertial measurements units (IMU) have become increas-ingly used in gait analysis, embodying an efficient alternative to motion capture systems. Mean-while, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gy-rometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson’s disease (PD). Estimated stride lengths were compared to GAITRite? walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the in-stantaneous stride length and opens the way to promising applications.展开更多
Accurate navigation is important for long-range rocket projectile＇s precise striking. To obtain stable and high-per- formance navigation result, a ultra-tight global positioning system/inertial navigation system （GP...Accurate navigation is important for long-range rocket projectile＇s precise striking. To obtain stable and high-per- formance navigation result, a ultra-tight global positioning system/inertial navigation system （GPS/INS） integration based nav- igation approach is proposed. The accurate short-time output of INS is used by GPS receiver to assist in acquisition of signal, and output information of INS and GPS is fused based on federated filter. Meanwhile, the improved cubature Kalman filter with strong tracking ability is chosen to serve as the local filter, and then the federated filter is enhanced based on vector sharing theory. Finally, simulation results show that the navigation accuracy with the proposed method is higher than that with traditional methods. It provides reference for long-range rocket projectile navigation.展开更多
In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accele...In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.展开更多
High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based...High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID system.In particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization precision.To tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS conditions.Then,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization precision.The experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.展开更多
When using motion compensation approaches based on the measurement of motion sensors, the residual uncompensated motion errors due to measurement instrument inaccuracies contribute to phase errors and hence degrade Sy...When using motion compensation approaches based on the measurement of motion sensors, the residual uncompensated motion errors due to measurement instrument inaccuracies contribute to phase errors and hence degrade Synthetic Aperture Radar (SAR) images. This paper presents a model to compute the phase error caused by Inertial Measurement Unit (IMU) measurement inaccuracies. By analyzing SAR motion compensation method and the effect of lever arm, this model derives the con-tribution of each term of IMU inaccuracies towards the residual uncompensated motion errors and provides a method to calculate each order of the residual phase error. According to the model, com-puted results of the airborne X-band SAR system with POS AV510 accord closely with the actual image quality.展开更多
This paper presents a new algorithm for de-noising global positioning system （GPS） and inertial navigation system （INS） data and estimates the INS error using wavelet multi-resolution analysis algorithm （WMRA）-b...This paper presents a new algorithm for de-noising global positioning system （GPS） and inertial navigation system （INS） data and estimates the INS error using wavelet multi-resolution analysis algorithm （WMRA）-based genetic algorithm （GA） with a well-designed structure appropriate for practical and real time implementations because of its very short training time and elevated accuracy. Different techniques have been implemented to de-noise and estimate the INS and GPS errors. Wavelet de-noising is one of the most exploited techniques that have been recently used to increase the precision and reliability of the integrated GPS/INS navigation system. To ameliorate the WMRA algorithm, GA was exploited to optimize the wavelet parameters so as to determine the best wavelet filter, thresholding selection rule （TSR）, and the optimum level of decomposition （LOD）. This results in increasing the robustness of the WMRA algorithm to estimate the INS error. The proposed intelligent technique has overcome the drawbacks of the tedious selection for WMRA algorithm parameters. Finally, the proposed method improved the stability and reliability of the estimated INS error using real field test data.展开更多
The microminiature inertial measurement system, a new style of inertial measurement system, has many advantages compared with traditional systems, such as small size, low mass, low cost, low power consumption, high ...The microminiature inertial measurement system, a new style of inertial measurement system, has many advantages compared with traditional systems, such as small size, low mass, low cost, low power consumption, high bearing capacity, and long life. Undoubtedly, it will have wide applications in military and commercial fields. However, current micro inertial sensors do not have sufficient accuracy, so, its applications are limited to some extent. This paper describes a microminiature inertial measurement system and its design, operating theory and error control techniques. In addition, its performance and applications are evaluated.展开更多
This paper deals with rigid body attitude estimation on the basis of the data obtained from an inertial measurement unit mounted on the body. The aim of this work is to present the numerical algorithm, which can be ea...This paper deals with rigid body attitude estimation on the basis of the data obtained from an inertial measurement unit mounted on the body. The aim of this work is to present the numerical algorithm, which can be easily applied to the wide class of problems concerning rigid body positioning, arising in aerospace and marine engineering, or in increasingly popular robotic systems and unmanned aerial vehicles. Following the considerations of kinematics of rigid bodies, the relations between accelerations of different points of the body are given. A rotation matrix is formed using the quaternion approach to avoid singularities. We present numerical procedures for determination of the absolute accelerations of the center of mass and of an arbitrary point of the body expressed in the inertial reference frame, as well as its attitude. An application of the algorithm to the example of a heavy symmetrical gyroscope is presented, where input data for the numerical procedure are obtained from the solution of differential equations of motion, instead of using sensor measurements.展开更多
An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. ...An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good eslimates of the states. When the system is in the high dynamic mode and the bias has converged to an aceurate estimate, the attitude caleulation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance,展开更多
Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–mach...Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–machine interface which is controlled by human head movements is designed and implemented.The proposed system enables users to steer the desired movement direction and to control the speed of an output device by using head movements.Head movements of the users are detected using a 6 DOF IMUs measuring three-axis accelerometer and three-axis gyroscope.The head movement axes and the Euler angles have been associated with movement direction and speed,respectively.To ensure driving safety,the speed of the system is determined by considering the speed requested by the user and the obstacle distance on the route.In this context,fuzzy logic algorithm is employed for closed-loop speed control according to distance sensors and reference speed data.A car model was used as the output device on the machine interface.However,the wireless communication between human and machine interfaces provides to adapt this system to any remote device or systems.The implemented system was tested by five subjects.Performance of the system was evaluated in terms of task completion times and feedback from the subjects about their experience with the system.Results indicate that the proposed system is easy to use;and the control capability and usage speed increase with user experience.The control speed is improved with the increase in user experience.展开更多
We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim w...We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim was to improve the kinematic performance of spherical robots.We developed mechanical and dynamic models so that we could analyze the motions of the robot on land and in water.The robot was equipped with an Inertial Measurement Unit(IMU)that provided inclination and motion information.We designed three types of walking gait for the robot,with different stabilities and speeds.Furthermore,we proposed an online adjustment mechanism to adjust the gaits so that the robot could climb up slopes in a stable manner.As the system function changed continuously as the robot moved underwater,we implemented an online motion recognition system with a forgetting factor least squares algorithm.We proposed a generalized prediction control algorithm to achieve robust underwater motion control.To ensure real-time performance and reduce power consumption,the robot motion control system was implemented on a Zynq-7000 System-on-Chip(SoC).Our experimental results show that the robot’s motion remains stable at different speeds in a variety of amphibious environments,which meets the requirements for applications in a range of terrains.展开更多
Technological development of motion and posture analyses is rapidly progressing,especially in rehabilitation settings and sport biomechanics.Consequently,clear discrimination among different measurement systems is req...Technological development of motion and posture analyses is rapidly progressing,especially in rehabilitation settings and sport biomechanics.Consequently,clear discrimination among different measurement systems is required to diversify their use as needed.This review aims to resume the currently used motion and posture analysis systems,clarify and suggest the appropriate approaches suitable for specific cases or contexts.The currently gold standard systems of motion analysis,widely used in clinical settings,present several limitations related to marker placement or long procedure time.Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies,especially outside laboratories.Similarly,new posture analysis techniques are emerging,often driven by the need for fast and non-invasive methods to obtain high-precision results.These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies.The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient.Herein,these devices and their uses are described,providing researchers,clinicians,orthopedics,physical therapists,and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis,therapy,and prevention.展开更多
This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observati...This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observations from an onboard monocular camera.A homography based approach is used to calculate the motion of the vehicle in 6 degrees of freedom by image feature match.This visual measurement is fused with the inertial outputs by an indirect extended Kalman filter（EKF） for attitude and velocity estimation.Then,another EKF is employed to estimate the position of the vehicle and the locations of the features in the map.Both simulations and experiments are carried out to test the performance of the proposed system.The result of the comparison with the referential global positioning system/inertial navigation system（GPS/INS） navigation indicates that the proposed SLAM can provide reliable and stable state estimation for small UAVs in GPS-denied environments.展开更多
Inertial measurement unit (IMU) is a standard motion sensor in modern airborne SAR systems. But how to remove its systematic error is a difficult problem, which impacts the improvement of resolution in azimuth. The te...Inertial measurement unit (IMU) is a standard motion sensor in modern airborne SAR systems. But how to remove its systematic error is a difficult problem, which impacts the improvement of resolution in azimuth. The technique of motion compensation presented in this paper, uses the GPS as a reference system to estimate and correct the systematic error of the IMU on the concept of linear unbiased minimum variance (LUMV). This new and effective method achieves very accurate position measurement (both high and low frequency) of the APC in not only short but also long terms, so that it can satisfy the requirement of high resolution airborne SAR. In the last section of the paper, some experimental simulations from raw data are given.展开更多
This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several e...This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several experiments were carried out using a motion capture system（VICON） and inertial sensors to identify the human posture during the sit-to-stand motion.The EJAD uses only two inertial measurement units（IMUs） fused through an adaptive neuro-fuzzy inference systems（ANFIS） algorithm to imitate the real motion of the caregiver.The EJAD consists of two main parts,a robot arm and an active walker.The robot arm is a 2-degree-of-freedom（2-DOF） planar manipulator.In addition,a back support with a passive joint is used to support the patient s back.The IMUs on the leg and trunk of the patient are used to compensate for and adapt to the EJAD system motion depending on the obtained patient posture.The ANFIS algorithm is used to train the fuzzy system that converts the IMUs signals to the right posture of the patient.A control scheme is proposed to control the system motion based on practical measurements taken from the experiments.A computer simulation showed a relatively good performance of the EJAD in assisting the patient.展开更多
An indoor positioning method for robots is presented to improve the precision of displacement measurement using only low-cost inertial measurement units(IMUs).Firstly,a high-fidelity displacement estimation for linear...An indoor positioning method for robots is presented to improve the precision of displacement measurement using only low-cost inertial measurement units(IMUs).Firstly,a high-fidelity displacement estimation for linear motion is proposed.A new robot motion model is designed as well as an axis alignment that only uses a single axis of the accelerometer.The integral error of velocity is eliminated by a new subsection calculation method.Two complementary IMUs are combined by assigning them different weights to obtain high accuracy displacement results.Secondly,an orientation estimation based on a fusion filter for the steering motion is proposed.Experiments show that the proposed method significantly improves the accuracy of linear motion measurement and is effective for the indoor positioning of a robot.展开更多
文摘Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.
基金This was work supported by the National Center for Advancing Translational Sciences of the National Institutes of Health[UL1TR001086].
文摘Total knee arthroplasty is highly successful,in part due to range of motion(RoM)recovery.This is typically estimated goniometrically/visually by physical therapists(PTs)in the clinic,which is imprecise.Accordingly,a validated inertial measurement unit(IMU)method for capturing knee RoM was deployed assessing postoperative RoM both in and outside of the clinical setting.The study's objectives were to evaluate the feasibility of continuously capturing knee RoM pre-/post-op via IMUs,dividing data into PT/non-PT portions of each day,and comparing PT/non-PT metrics.We hypothesized IMU-based clinical knee RoM would differ from IMU-based knee RoM captured outside clinical settings.10 patients(3 M,69±13 years)completed informed consent documents following ethics board approval.A validated IMU method captured long duration(8–12 h/day,~50 days)knee RoM pre-/post-op.Post-op metrics were subdivided(PT versus non-PT).Clinical RoM and patient reported outcome measures were also captured.Compliance and clinical disruption were evaluated.ANOVA compared post-op PT and non-PT means and change scores.Maximum flexion during PT was less than outside PT.PT stance/swing RoM and activity level were greater than outside PT.No temporal variable differences were found PT versus non-PT.IMU RoM measurements capture richer information than clinical measures.Maximum PT flexion was likely less than non-PT due to the exercises completed(i.e.high passive RoM vs.low RoM gait).PT gait flexion likely exceed non-PT because of‘white coat effects’wherein patients are closely monitored clinically.This implies data captured clinically represents optimum performance whereas data captured non-clinically represents realistic performance.
基金This work was supported by the International Partnership Program of Chinese Academy of Sciences(173321KYSB20180020,173321KYSB20200002)the National Natural Science Foundation of China(61903357,62022088)+3 种基金Liaoning Provincial Natural Science Foundation of China(2020-MS-032,2019-YQ-09,2020JH2/10500002,2021JH6/10500114)LiaoNing Revitalization Talents Program(XLYC1902110)China Postdoctoral Science Foundation(2020M672600)the Swedish Foundation for Strategic Research(APR20-0023).
文摘Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.
基金supported by an INRIA internal financial support:ADT SENSBIO and a Montpellier Hospital internal financial support(AOI PARKDEMAR CHU Montpellier).
文摘As low cost and highly portable sensors, inertial measurements units (IMU) have become increas-ingly used in gait analysis, embodying an efficient alternative to motion capture systems. Mean-while, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gy-rometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson’s disease (PD). Estimated stride lengths were compared to GAITRite? walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the in-stantaneous stride length and opens the way to promising applications.
基金Project Funded by Chongqing Changjiang Electrical Appliances Industries Group Co.,Ltd
文摘Accurate navigation is important for long-range rocket projectile＇s precise striking. To obtain stable and high-per- formance navigation result, a ultra-tight global positioning system/inertial navigation system （GPS/INS） integration based nav- igation approach is proposed. The accurate short-time output of INS is used by GPS receiver to assist in acquisition of signal, and output information of INS and GPS is fused based on federated filter. Meanwhile, the improved cubature Kalman filter with strong tracking ability is chosen to serve as the local filter, and then the federated filter is enhanced based on vector sharing theory. Finally, simulation results show that the navigation accuracy with the proposed method is higher than that with traditional methods. It provides reference for long-range rocket projectile navigation.
基金Project(61301181) supported by the National Natural Science Foundation of China
文摘In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.
基金supported in part by the National Natural Science Foundation of China under Grant No.61771474in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.KYCX212243+2 种基金in part by the Young Talents of Xuzhou Science and Technology Plan Project under Grant No.KC19051in part by the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2021D02in part by the Open Fund of Information Photonics and Optical Communications (IPOC) (BUPT)。
文摘High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID system.In particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization precision.To tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS conditions.Then,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization precision.The experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.
基金Supported by the National Basic Research Program (973)of China (No. 2009CB724003)the National High-Tech Research and Development Program (863) of China (No. 2007AA120302)
文摘When using motion compensation approaches based on the measurement of motion sensors, the residual uncompensated motion errors due to measurement instrument inaccuracies contribute to phase errors and hence degrade Synthetic Aperture Radar (SAR) images. This paper presents a model to compute the phase error caused by Inertial Measurement Unit (IMU) measurement inaccuracies. By analyzing SAR motion compensation method and the effect of lever arm, this model derives the con-tribution of each term of IMU inaccuracies towards the residual uncompensated motion errors and provides a method to calculate each order of the residual phase error. According to the model, com-puted results of the airborne X-band SAR system with POS AV510 accord closely with the actual image quality.
基金supported in part by Graduate School of Studies through the Graduate Research Fellowship (GRF) sponsored by University Putra Malaysia
文摘This paper presents a new algorithm for de-noising global positioning system （GPS） and inertial navigation system （INS） data and estimates the INS error using wavelet multi-resolution analysis algorithm （WMRA）-based genetic algorithm （GA） with a well-designed structure appropriate for practical and real time implementations because of its very short training time and elevated accuracy. Different techniques have been implemented to de-noise and estimate the INS and GPS errors. Wavelet de-noising is one of the most exploited techniques that have been recently used to increase the precision and reliability of the integrated GPS/INS navigation system. To ameliorate the WMRA algorithm, GA was exploited to optimize the wavelet parameters so as to determine the best wavelet filter, thresholding selection rule （TSR）, and the optimum level of decomposition （LOD）. This results in increasing the robustness of the WMRA algorithm to estimate the INS error. The proposed intelligent technique has overcome the drawbacks of the tedious selection for WMRA algorithm parameters. Finally, the proposed method improved the stability and reliability of the estimated INS error using real field test data.
基金the Major Research Project of the Ninth-Five Plan (1996 2 0 0 0 ) of China (No.8.7.1.9)
文摘The microminiature inertial measurement system, a new style of inertial measurement system, has many advantages compared with traditional systems, such as small size, low mass, low cost, low power consumption, high bearing capacity, and long life. Undoubtedly, it will have wide applications in military and commercial fields. However, current micro inertial sensors do not have sufficient accuracy, so, its applications are limited to some extent. This paper describes a microminiature inertial measurement system and its design, operating theory and error control techniques. In addition, its performance and applications are evaluated.
基金supported by the Serbian Ministry of Education, Science and Technological Development (Grant 174016)
文摘This paper deals with rigid body attitude estimation on the basis of the data obtained from an inertial measurement unit mounted on the body. The aim of this work is to present the numerical algorithm, which can be easily applied to the wide class of problems concerning rigid body positioning, arising in aerospace and marine engineering, or in increasingly popular robotic systems and unmanned aerial vehicles. Following the considerations of kinematics of rigid bodies, the relations between accelerations of different points of the body are given. A rotation matrix is formed using the quaternion approach to avoid singularities. We present numerical procedures for determination of the absolute accelerations of the center of mass and of an arbitrary point of the body expressed in the inertial reference frame, as well as its attitude. An application of the algorithm to the example of a heavy symmetrical gyroscope is presented, where input data for the numerical procedure are obtained from the solution of differential equations of motion, instead of using sensor measurements.
文摘An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good eslimates of the states. When the system is in the high dynamic mode and the bias has converged to an aceurate estimate, the attitude caleulation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance,
基金the Scientific and Technological Research Council of Turkey(TUBITAK).
文摘Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–machine interface which is controlled by human head movements is designed and implemented.The proposed system enables users to steer the desired movement direction and to control the speed of an output device by using head movements.Head movements of the users are detected using a 6 DOF IMUs measuring three-axis accelerometer and three-axis gyroscope.The head movement axes and the Euler angles have been associated with movement direction and speed,respectively.To ensure driving safety,the speed of the system is determined by considering the speed requested by the user and the obstacle distance on the route.In this context,fuzzy logic algorithm is employed for closed-loop speed control according to distance sensors and reference speed data.A car model was used as the output device on the machine interface.However,the wireless communication between human and machine interfaces provides to adapt this system to any remote device or systems.The implemented system was tested by five subjects.Performance of the system was evaluated in terms of task completion times and feedback from the subjects about their experience with the system.Results indicate that the proposed system is easy to use;and the control capability and usage speed increase with user experience.The control speed is improved with the increase in user experience.
基金National Natural Science Foundation of China(61773064,61503028).
文摘We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim was to improve the kinematic performance of spherical robots.We developed mechanical and dynamic models so that we could analyze the motions of the robot on land and in water.The robot was equipped with an Inertial Measurement Unit(IMU)that provided inclination and motion information.We designed three types of walking gait for the robot,with different stabilities and speeds.Furthermore,we proposed an online adjustment mechanism to adjust the gaits so that the robot could climb up slopes in a stable manner.As the system function changed continuously as the robot moved underwater,we implemented an online motion recognition system with a forgetting factor least squares algorithm.We proposed a generalized prediction control algorithm to achieve robust underwater motion control.To ensure real-time performance and reduce power consumption,the robot motion control system was implemented on a Zynq-7000 System-on-Chip(SoC).Our experimental results show that the robot’s motion remains stable at different speeds in a variety of amphibious environments,which meets the requirements for applications in a range of terrains.
基金Supported by University Research Project GrantNo. PIACERI Found–NATURE-OA-2020-2022。
文摘Technological development of motion and posture analyses is rapidly progressing,especially in rehabilitation settings and sport biomechanics.Consequently,clear discrimination among different measurement systems is required to diversify their use as needed.This review aims to resume the currently used motion and posture analysis systems,clarify and suggest the appropriate approaches suitable for specific cases or contexts.The currently gold standard systems of motion analysis,widely used in clinical settings,present several limitations related to marker placement or long procedure time.Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies,especially outside laboratories.Similarly,new posture analysis techniques are emerging,often driven by the need for fast and non-invasive methods to obtain high-precision results.These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies.The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient.Herein,these devices and their uses are described,providing researchers,clinicians,orthopedics,physical therapists,and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis,therapy,and prevention.
基金supported by National High Technology Research Development Program of China (863 Program) (No.2011AA040202)National Science Foundation of China (No.51005008)
文摘This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observations from an onboard monocular camera.A homography based approach is used to calculate the motion of the vehicle in 6 degrees of freedom by image feature match.This visual measurement is fused with the inertial outputs by an indirect extended Kalman filter（EKF） for attitude and velocity estimation.Then,another EKF is employed to estimate the position of the vehicle and the locations of the features in the map.Both simulations and experiments are carried out to test the performance of the proposed system.The result of the comparison with the referential global positioning system/inertial navigation system（GPS/INS） navigation indicates that the proposed SLAM can provide reliable and stable state estimation for small UAVs in GPS-denied environments.
文摘Inertial measurement unit (IMU) is a standard motion sensor in modern airborne SAR systems. But how to remove its systematic error is a difficult problem, which impacts the improvement of resolution in azimuth. The technique of motion compensation presented in this paper, uses the GPS as a reference system to estimate and correct the systematic error of the IMU on the concept of linear unbiased minimum variance (LUMV). This new and effective method achieves very accurate position measurement (both high and low frequency) of the APC in not only short but also long terms, so that it can satisfy the requirement of high resolution airborne SAR. In the last section of the paper, some experimental simulations from raw data are given.
基金supported in part by a scholarship provided by the Mission DepartmentMinistry of Higher Education of the Government of Egypt
文摘This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several experiments were carried out using a motion capture system（VICON） and inertial sensors to identify the human posture during the sit-to-stand motion.The EJAD uses only two inertial measurement units（IMUs） fused through an adaptive neuro-fuzzy inference systems（ANFIS） algorithm to imitate the real motion of the caregiver.The EJAD consists of two main parts,a robot arm and an active walker.The robot arm is a 2-degree-of-freedom（2-DOF） planar manipulator.In addition,a back support with a passive joint is used to support the patient s back.The IMUs on the leg and trunk of the patient are used to compensate for and adapt to the EJAD system motion depending on the obtained patient posture.The ANFIS algorithm is used to train the fuzzy system that converts the IMUs signals to the right posture of the patient.A control scheme is proposed to control the system motion based on practical measurements taken from the experiments.A computer simulation showed a relatively good performance of the EJAD in assisting the patient.
基金National Natural Science Foundation of China(61375103,61533004,61320106012,and 61321002)the 863 Program of China(2014AA041602,2015AA042305 and 2015AA043202)+2 种基金the Key Technologies Research and Development Program(2015BAF13B01 and 2015BAK35B01)the Beijing Municipal Science and Technology Project(D161100003016002)the "111" Project under Grant B08043
文摘An indoor positioning method for robots is presented to improve the precision of displacement measurement using only low-cost inertial measurement units(IMUs).Firstly,a high-fidelity displacement estimation for linear motion is proposed.A new robot motion model is designed as well as an axis alignment that only uses a single axis of the accelerometer.The integral error of velocity is eliminated by a new subsection calculation method.Two complementary IMUs are combined by assigning them different weights to obtain high accuracy displacement results.Secondly,an orientation estimation based on a fusion filter for the steering motion is proposed.Experiments show that the proposed method significantly improves the accuracy of linear motion measurement and is effective for the indoor positioning of a robot.
