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
The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Vel...The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Velocity Log) is widely used to improve the underwater navigation performance. However, the DVL’s range of measuring varied depending on the characteristics of sensor. So, if the sea gets too deep suddenly, it cannot measure the velocity. To complement such a weak point, the VKF was additionally designed, which was made of DVL, RPM (Revolve Per Minutes) of motor, and ES (Echo Sounder). The proposed approach relies on a VKF, augmented by an altitude from ES based switching architecture to yield robust performance, even when DVL exceeds the measurement range and the measured value is unable to be valid. The proposed approach relies on two parts: 1) indirect feedback navigation Kalman filter design, 2) VKF design. To evaluate the proposed method, we compare the VKF aided navigation system with PINS (Pure Inertial Navigation System) and conventional INS-DVL navigation system through simulation results. Simulations illustrate the effectiveness of the underwater navigation system assisted by the additional DVL-RPM based VKF in underwater environment.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
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
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.
文摘The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Velocity Log) is widely used to improve the underwater navigation performance. However, the DVL’s range of measuring varied depending on the characteristics of sensor. So, if the sea gets too deep suddenly, it cannot measure the velocity. To complement such a weak point, the VKF was additionally designed, which was made of DVL, RPM (Revolve Per Minutes) of motor, and ES (Echo Sounder). The proposed approach relies on a VKF, augmented by an altitude from ES based switching architecture to yield robust performance, even when DVL exceeds the measurement range and the measured value is unable to be valid. The proposed approach relies on two parts: 1) indirect feedback navigation Kalman filter design, 2) VKF design. To evaluate the proposed method, we compare the VKF aided navigation system with PINS (Pure Inertial Navigation System) and conventional INS-DVL navigation system through simulation results. Simulations illustrate the effectiveness of the underwater navigation system assisted by the additional DVL-RPM based VKF in underwater environment.
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.
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.
