Weidong Chen

Shanghai Jiao Tong University, Shanghai, Shanghai Shi, China

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Publications (136)67.77 Total impact

  • Hesheng Wang · Yinping Lai · Weidong Chen · Qixin Cao ·

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    Xi Chen · Weidong Chen ·
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    ABSTRACT: In through wall radar sensing, the wall parameters estimation (WPE) problem has been a topic that attracts a lot of attention since the wall parameters, i.e., the permittivity and the thickness, are of crucial importance to locate the targets and to produce a well-focused image, but they are usually unknown in practice. To solve this problem, in this paper, the support vector regression (SVR), a powerful tool for regression analysis, is introduced, and its performance on WPE, provided it is used it in the regular way, is investigated. Unfortunately, it is shown that the regular use of SVR cannot afford satisfactory estimation results since the sample data used in SVR, namely the received echoes from the walls, are seriously interfered with the echoes from the targets which are located near the walls. In view of this limitation, a novel SVR-based WPE approach that consists of three stages is proposed by this paper. In the first stage, three regression functions are trained by SVR, one of which will output the estimate of the permittivity in the second stage, and the others are designed to output two instrumental variables for estimating the thickness. In the third stage, the estimate of thickness will be achieved by minimizing a predefined cost function wherein the estimated permittivity and the outputted instrumental variables are involved. The better robustness and higher estimation accuracy of the proposed approach compared to the regular use of SVR are validated by the numerical experimental results using finite-difference time-domain simulations.
    Journal on Advances in Signal Processing 11/2015; 2015(1). DOI:10.1186/s13634-015-0244-8 · 0.78 Impact Factor
  • Xinwu Liang · Hesheng Wang · Weidong Chen · Dejun Guo · Tao Liu ·
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    ABSTRACT: In this paper, the uncalibrated image-based trajectory tracking control problem of wheeled mobile robots will be studied. The motion of the wheeled mobile robot can be observed using an uncalibrated fixed camera on the ceiling. Different from traditional vision-based control strategies of wheeled mobile robots in the fixed camera configuration, the camera image plane is not required to be parallel to the motion plane of the wheeled mobile robots and the camera can be placed at a general position. To guarantee that the wheeled mobile robot can efficiently track its desired trajectory, which is specified by the desired image trajectory of a feature point at the forward axis of the wheeled mobile robot, we will propose a new adaptive image-based trajectory tracking control approach without the exact knowledge of the camera intrinsic and extrinsic parameters and the position parameter of the feature point. To eliminate the nonlinear dependence on the unknown parameters from the closed-loop system, a depth-independent image Jacobian matrix framework for the wheeled mobile robots will be developed such that unknown parameters in the closed-loop system can be linearly parameterized. In this way, adaptive laws can be designed to estimate the unknown parameters online, and the depth information of the feature point can be allowed to be time varying in this case. The Lyapunov stability analysis will also be performed to show asymptotical convergence of image position and velocity tracking errors of the wheeled mobile robot. The simulation results based on a two-wheeled mobile robot will be given in this paper to illustrate the performance of the proposed approach as well. The experimental results based on a real wheeled mobile robot will also be provided to validate the proposed approach.
    IEEE Transactions on Control Systems Technology 11/2015; 23(6):1-1. DOI:10.1109/TCST.2015.2411627 · 2.47 Impact Factor
  • Xinwu Liang · Hesheng Wang · Yun-Hui Liu · Weidong Chen · Jie Zhao ·
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    ABSTRACT: A unified design method is proposed in this paper to handle adaptive visual tracking control problem of robots. In the proposed scheme, the robot dynamic parameters, camera intrinsic and extrinsic parameters and position parameters of feature points are assumed to be uncertain. A unified kinematics model is presented to simultaneously cope with kinematics modeling problem of robots with the eye-in-hand or fixed camera configuration. Based on the unified kinematics, a unified design method is proposed to solve the visual tracking control problem of robots with the eye-in-hand or fixed camera configuration. By using the depth-independent interaction matrix framework, adaptive laws are derived to handle the unknown parameters. Lyapunov stability analysis is provided to show asymptotical convergence of image position and velocity tracking errors. To show the effectiveness of the proposed unified design method, experimental results for both camera configurations are also given.
  • Xinwu Liang · Hesheng Wang · Yun-Hui Liu · Weidong Chen · Guoqiang Hu · Jie Zhao ·
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    ABSTRACT: In this paper, the task-space cooperative tracking control problem of networked robotic manipulators without task-space velocity measurements is addressed. To overcome the problem without task-space velocity measurements, a novel task-space position observer is designed to update the estimated task-space position and to simultaneously provide the estimated task-space velocity, based on which an adaptive cooperative tracking controller without task-space velocity measurements is presented by introducing new estimated task-space reference velocity and acceleration. Furthermore, adaptive laws are provided to cope with uncertain kinematics and dynamics and rigorous stability analysis is given to show asymptotical convergence of the task-space tracking and synchronization errors in the presence of communication delays under strongly connected directed graphs. Simulation results are given to demonstrate the performance of the proposed approach.
    09/2015; DOI:10.1109/TCYB.2015.2477606
  • Jingchuan Wang · Ming Yang · Weidong Chen ·
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    ABSTRACT: According to the long length characteristics of transfer cask compared to the environment space between Tokmak Building (TB) and HCB (Hot Cell Building), this paper proposes an autonomous localization and alignment method for the internal components transportation and replacement. A localization method based on the localizability estimation is used to realize the cask's localization and navigation accurately. Once the cask arrives at the front of the TB window, the position and attitude measurement system is used to detect the relative alignment error between the seal door of pallet and the window of TB real-time. The alignment between seal door and TB window could be realized based on this offset. The simulation experiment based on the real model is designed according to the real TB situation. The experiment results show that the proposed localization and alignment method can be used for transfer cask.
  • Hesheng Wang · Weidong Chen · Lifei Xu · Tao He ·
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    ABSTRACT: The vibration should be suppressed if it happens during the motion of a flexible robot or under the influence of external disturbance caused by its structural features and material properties, because the vibration may affect the positioning accuracy and image quality. In Tokamak environment, we need to get the real-time vibration information on vibration suppression of robotic arm, however, some sensors are not allowed in the extreme Tokamak environment. This paper proposed a vision-based method for online vibration estimation of a flexible manipulator, which is achieved by utilizing the environment image information from the end-effector camera to estimate its vibration. Short-time Fourier Transformation with adaptive window length method is used to estimate vibration parameters of non-stationary vibration signals. Experiments with one-link flexible manipulator equipped with camera are carried out to validate the feasibility of this method in this paper.
  • Li Ding · Weidong Chen · Wenyi Zhang · H. Vincent Poor ·
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    ABSTRACT: Multiple-input multiple-output (MIMO) radar imaging suffers from performance degradation under carrier offsets across transmitters and receivers. This paper analyzes the impact of carrier offsets on imaging a sparse target, from the perspective of the MIMO point spread function (PSF). Conditions are established for successful support recovery using orthogonal matching pursuit (OMP), and the performance loss is characterized in terms of l2 distance. A sparse imaging algorithm taking into account the perturbation due to carrier offsets is also proposed, which improves upon the OMP algorithm. Numerical experiments corroborate this analysis.
    IEEE Transactions on Aerospace and Electronic Systems 07/2015; 51(3):2236-2247. DOI:10.1109/TAES.2015.140428 · 1.76 Impact Factor
  • Hesheng Wang · Weidong Chen · Yinping Lai · Tao He ·
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    ABSTRACT: Tokamak flexible in-vessel inspection robot is mainly designed to carry a camera for close observation of the first wall of the vacuum vessel, which is essential for the maintenance of the future tokamak reactor without breaking the working condition of the vacuum vessel. A tokamak flexible in-vessel inspection robot is designed. In order to improve efficiency of the remote maintenance, it is necessary to design a corresponding trajectory planning algorithm to complete the automatic full coverage scanning of the complex tokamak cavity. Two different trajectory planning methods, RS (rough scanning) and FS (fine scanning), according to different demands of the task, are used to ensure the full coverage of the first wall scanning. To quickly locate the damage position, the first trajectory planning method is targeted for quick and wide-ranging scan of the tokamak D-shaped section, and the second one is for careful observation. Furthermore, both of the two different trajectory planning methods can ensure the full coverage of the first wall scanning with an optimal end posture. The method is tested on a simulated platform of EAST (Experimental Advanced Superconducting Tokamak) with the flexible in-vessel inspection robot, and the results show the effectiveness of the proposed algorithm.
    Fusion Engineering and Design 06/2015; DOI:10.1016/j.fusengdes.2015.05.028 · 1.15 Impact Factor
  • Xinwu Liang · Hesheng Wang · Y.-H. Liu · Weidong Chen ·
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    ABSTRACT: The adaptive image-based trajectory tracking control problem of rigid-link electrically driven (RLED) robotic manipulators is addressed in this paper. A fixed camera configuration is considered and the camera intrinsic and extrinsic parameters are assumed to be unknown. Furthermore, the manipulator dynamic and motor dynamic parameters are assumed to be uncertain and the depths of feature points can be allowed to be time varying. The depth-independent interaction matrix framework is used such that unknown parameters in the closed-loop dynamics can be parameterized linearly and adaptive laws can be derived to estimate them online. By simultaneously taking into consideration the mechanical and electrical subsystem dynamics of RLED robotic manipulators, the backstepping technique is used to design control voltage inputs to guarantee the tracking of desired image trajectories in the presence of parameter uncertainties and time-varying depth information. Asymptotical convergence of image tracking errors to zeros is proved by using Lyapunov stability theory. Simulation results based on a 3-DOFs anthropomorphic robotic manipulator are given to demonstrate the performance of the proposed adaptive visual tracking scheme.
  • Jianfei Zhang · Jingchuan Wang · Weidong Chen ·
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    ABSTRACT: Driver assistance is one of the major tasks on smart wheelchair development. However, human following is also necessary in real application. In this paper, a control system of driver assistance and human following for smart wheelchair is presented. Driver assistance can keep the wheelchair from stairs falling and obstacle collision when the user is driving the wheelchair in complex environments with unknown obstacles. Human following can guarantee the wheelchair to follow the user with a suitable distance when the user wants to walk along by himself. The target occlusion problem caused by obstacle avoidance during human following can also be effectively solved by the use of odometry data. Both the driver assistance and human following are based on shared control strategy. And since the sensor used is ultrasound, instead of LRF, the proposed system is low-cost and can be easily implemented in real applications. The system is developed and tested on JiaoLong smart wheelchair. Experiment results show that the proposed system can improve user's driving ability in driver assistance task and it can control the wheelchair to keep a suitable distance with the target human. And it can effectively handle the target occlusion problem when it has to avoid obstacle in human following task.
  • Li Ding · Weidong Chen ·
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    ABSTRACT: Sparse recovery algorithms with application to multiple-input-multiple-output (MIMO) radar imaging could lose their advantage under a phase mismatch among transmitter-receiver pairs. In this letter, we identify that the impact of a random phase mismatch on the imaging problem can come to a scale-down factor on the amplitude of the MIMO point spread function. We thereby establish the conditions of successful support recovery and the performance measure for the orthogonal matching pursuit (OMP) algorithm for the involved problem, both of which are functions of the scale-down factor. Meanwhile, sparse imaging via expectation-maximization (SIEM) is proposed to alleviate OMP performance loss in the face of a phase mismatch. Numerical results corroborate the analysis and illustrate the effectiveness of the SIEM algorithm.
    IEEE Geoscience and Remote Sensing Letters 03/2015; 12(4). DOI:10.1109/LGRS.2014.2363110 · 2.10 Impact Factor
  • Yanlong Zhang · Weidong Chen ·
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    ABSTRACT: Nonparametric time-of-arrival (TOA) estimators for impulse radio ultra-wideband (IR-UWB) signals are proposed. Non-parametric detection is obviously useful in situations where detailed information about the statistics of the noise is unavailable or not accurate. Such TOA estimators are obtained based on conditional statistical tests with only a symmetry distribution assumption on the noise probability density function. The nonparametric estimators are attractive choices for low-resolution IR-UWB digital receivers which can be implemented by fast comparators or high sampling rate low resolution analog-to-digital converters (ADCs), in place of high sampling rate high resolution ADCs which may not be available in practice. Simulation results demonstrate that nonparametric TOA estimators provide more effective and robust performance than typical energy detection (ED) based estimators.
    Journal of Systems Engineering and Electronics 02/2015; 26(1):26-31. DOI:10.1109/JSEE.2015.00004 · 0.38 Impact Factor
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    Dejun Guo · Hesheng Wang · Weidong Chen · Xinwu Liang ·
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    ABSTRACT: This paper focuses on the problem of the adaptive image-based leader-follower formation control of mobile robot with on-board omnidirectional camera. A calibrated omnidirectional camera is fixed on the follower in any position, and a feature point representing the leader can be chosen in any position. An adaptive image-based controller without depending on the velocity of the leader is proposed based on a filter technology. In other words, only by relying on the projection of the feature on the image plane, can the follower track the leader and achieve the formation control. Moreover, an observer is introduced to estimate the unknown camera extrinsic parameters and the unknown parameters of plane, where the feature point moves, relative to omnidirectional camera frame. At last, the lyapunov method is applied to prove the uniform semiglobal practical asymptotic stability (USPAS) for the closed-loop system. Simulation results are presented to validate the algorithm.
    Journal of Applied Mathematics 01/2015; 2015(2):1-12. DOI:10.1155/2015/194251 · 0.72 Impact Factor
  • Jingchuan Wang · Li Liu · Zhe Liu · Weidong Chen ·

    International Journal of Advanced Robotic Systems 01/2015; DOI:10.5772/61240 · 0.53 Impact Factor
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    ABSTRACT: Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.
    12/2014; 2014:280207. DOI:10.1155/2014/280207
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    Shougang Chai · Weidong Chen · Chang Chen ·
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    ABSTRACT: For high resolution imaging of a non-cooperative moving target, this paper proposes a sparse fusion imaging method. The imaging system contains two radar stations, which are separated by a certain bistatic angle and configured in a transmitter/receiver-receiver (T/R-R) manner. Consequently, two synthetic apertures are obtained at the same time from different aspect angles. By coherently fusing the echoes of the two radars, a virtual aperture spanned by these two sub-apertures can be constructed, which is larger than either of the sub-apertures; thus, the cross-range resolution of the image is enhanced. Moreover, the fusion of the echoes is realized by exploiting the sparse scattering property of the target. Then, based on the maximum a posteriori (MAP) criterion, the T/R-R fusion imaging problem is converted into a sparse signal recovery problem with unknown parameters. Finally, it is solved in an iterative manner, which contains two steps, i.e., sparse imaging and parameter estimation. Simulation results show that the proposed sparse fusion imaging method can improve the cross-range resolution significantly compared to inverse synthetic aperture radar (ISAR) within the same coherent processing interval (CPI).
    Sensors 06/2014; 14(6):10664-10679. DOI:10.3390/s140610664 · 2.25 Impact Factor
  • Yong Wang · Weidong Chen · Jingchuan Wang ·
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    ABSTRACT: Purpose ‐ The purpose of this paper is to propose a localizability-based particle filtering localization algorithm for mobile robots to maintain localization accuracy in the high-occluded and dynamic environments with moving people. Design/methodology/approach ‐ First, the localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Second, based on the classical two-sensor track fusion algorithm, the odometer-based proposal distribution function (PDF) is corrected, taking account of the localizability. Then, the corrected PDF is introduced into the classical PF with "roulette" re-sampling. Finally, the robot pose is estimated according to all the particles. Findings ‐ The experimental results show that, first, it is necessary to consider the influence of the prior-map during the localization in the high-occluded and dynamic environments. Second, the proposed algorithm can maintain an accurate and robust robot pose in the high-occluded and dynamic environments. Third, its real timing is acceptable. Research limitations/implications ‐ When the odometer error and occlusion caused by the dynamic obstacles are both serious, the proposed algorithm also has a probability evolving into the kidnap problem. But fortunately, such serious situations are not common in practice. Practical implications ‐ To check the ability of real application, we have implemented the proposed algorithm in the campus cafeteria and metro station using an intelligent wheelchair. To better help the elderly and disabled people during their daily lives, the proposed algorithm will be tested in a social welfare home in the future. Original/value ‐ The localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Based on the localizability, the odometer-based PDF is corrected properly.
    Industrial Robot 05/2014; 41(3). DOI:10.1108/IR-06-2013-371 · 0.64 Impact Factor
  • Xinwu Liang · Hesheng Wang · Weidong Chen · Yun‐Hui Liu ·
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    ABSTRACT: In this paper, the uncalibrated fixed-camera visual servoing problem of robot manipulators will be addressed by considering its full motor dynamics. A new adaptive image-space visual servoing strategy without both the joint and visual acceleration measurements is presented, which can handle uncertainties in the camera intrinsic and extrinsic parameters, the robot kinematic and dynamic parameters, and the motor dynamic parameters. The proposed scheme is developed based on the depth-independent interaction matrix in order to deal with the nonlinear dependence of image Jacobian matrix on the unknown parameters, which allows the camera and robot kinematic parameters in the closed-loop dynamics to be linearly parameterized. In this way, adaptive laws for the online estimation of the unknown camera, kinematic, rigid dynamic, and motor dynamic parameters can be developed very efficiently. Furthermore, a joint velocity observer will also be presented to solve the problem without both the joint and visual acceleration measurements. To show asymptotic convergence of image errors, stability analysis based on both the rigid-link robot dynamics and full motor dynamics will be performed by using Lyapunov theory. Simulation results will be given to validate the performance of the proposed scheme.
    Asian Journal of Control 05/2014; 16(3). DOI:10.1002/asjc.796 · 1.56 Impact Factor
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    Tianyun Wang · Xinfei Lu · Xiaofei Yu · Zhendong Xi · Weidong Chen ·
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    ABSTRACT: In recent years, various applications regarding sparse continuous signal recovery such as source localization, radar imaging, communication channel estimation, etc., have been addressed from the perspective of compressive sensing (CS) theory. However, there are two major defects that need to be tackled when considering any practical utilization. The first issue is off-grid problem caused by the basis mismatch between arbitrary located unknowns and the pre-specified dictionary, which would make conventional CS reconstruction methods degrade considerably. The second important issue is the urgent demand for low-complexity algorithms, especially when faced with the requirement of real-time implementation. In this paper, to deal with these two problems, we have presented three fast and accurate sparse reconstruction algorithms, termed as HR-DCD, Hlog-DCD and Hlp-DCD, which are based on homotopy, dichotomous coordinate descent (DCD) iterations and non-convex regularizations, by combining with the grid refinement technique. Experimental results are provided to demonstrate the effectiveness of the proposed algorithms and related analysis.
    Sensors 04/2014; 14(4):5929-51. DOI:10.3390/s140405929 · 2.25 Impact Factor

Publication Stats

338 Citations
67.77 Total Impact Points


  • 2006-2015
    • Shanghai Jiao Tong University
      • • Department of Automation
      • • School of Electronic, Information and Electrical Engineering
      Shanghai, Shanghai Shi, China
    • University of Science and Technology of China
      • Department of Electronic Engineering and Information Science
      Luchow, Anhui Sheng, China
  • 2010-2013
    • University of Electronic Science and Technology of China
      Hua-yang, Sichuan, China
  • 2011
    • Hefei University of Technology
      Luchow, Anhui Sheng, China
  • 2007-2009
    • Shanghai University
      • Department of Automation
      Shanghai, Shanghai Shi, China