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Hesheng Wang - One of the best experts on this subject based on the ideXlab platform.

  • a unified design method for adaptive visual tracking control of robots with eye in hand Fixed Camera configuration
    Automatica, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu, Jie Zhao
    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.

  • Adaptive Image-Based Trajectory Tracking Control of Wheeled Mobile Robots With an Uncalibrated Fixed Camera
    IEEE Transactions on Control Systems Technology, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Dejun Guo, Tao Liu
    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.

  • adaptive visual tracking control of uncertain rigid link electrically driven robotic manipulators with an uncalibrated Fixed Camera
    Robotics and Biomimetics, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen
    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.

  • uncalibrated image based visual servoing of rigid link electrically driven robotic manipulators
    Asian Journal of Control, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu
    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.

  • Uncalibrated visual servoing of robots using a depth-independent interaction matrix
    IEEE Transactions on Robotics, 2006
    Co-Authors: Hesheng Wang, Chengyou Wang
    Abstract:

    This paper presents a new adaptive controller for image-based dynamic control of a robot manipulator using a Fixed Camera whose intrinsic and extrinsic parameters are not known. To map the visual signals onto the joints of the robot manipulator, this paper proposes a depth-independent interaction matrix, which differs from the traditional interaction matrix in that it does not depend on the depths of the feature points. Using the depth-independent interaction matrix makes the unknown Camera parameters appear linearly in the closed-loop dynamics so that a new algorithm is developed to estimate their values on-line. This adaptive algorithm combines the Slotine-Li method with on-line minimization of the errors between the real and estimated projections of the feature points on the image plane. Based on the nonlinear robot dynamics, we prove asymptotic convergence of the image errors to zero by the Lyapunov theory. Experiments have been conducted to verify the performance of the proposed controller. The results demonstrated good convergence of the image errors

Xinwu Liang - One of the best experts on this subject based on the ideXlab platform.

  • a unified design method for adaptive visual tracking control of robots with eye in hand Fixed Camera configuration
    Automatica, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu, Jie Zhao
    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.

  • Adaptive Image-Based Trajectory Tracking Control of Wheeled Mobile Robots With an Uncalibrated Fixed Camera
    IEEE Transactions on Control Systems Technology, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Dejun Guo, Tao Liu
    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.

  • adaptive visual tracking control of uncertain rigid link electrically driven robotic manipulators with an uncalibrated Fixed Camera
    Robotics and Biomimetics, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen
    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.

  • uncalibrated image based visual servoing of rigid link electrically driven robotic manipulators
    Asian Journal of Control, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu
    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.

Weidong Chen - One of the best experts on this subject based on the ideXlab platform.

  • a unified design method for adaptive visual tracking control of robots with eye in hand Fixed Camera configuration
    Automatica, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu, Jie Zhao
    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.

  • Adaptive Image-Based Trajectory Tracking Control of Wheeled Mobile Robots With an Uncalibrated Fixed Camera
    IEEE Transactions on Control Systems Technology, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Dejun Guo, Tao Liu
    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.

  • adaptive visual tracking control of uncertain rigid link electrically driven robotic manipulators with an uncalibrated Fixed Camera
    Robotics and Biomimetics, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen
    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.

  • uncalibrated image based visual servoing of rigid link electrically driven robotic manipulators
    Asian Journal of Control, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu
    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.

Yunhui Liu - One of the best experts on this subject based on the ideXlab platform.

  • a unified design method for adaptive visual tracking control of robots with eye in hand Fixed Camera configuration
    Automatica, 2015
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu, Jie Zhao
    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.

  • uncalibrated image based visual servoing of rigid link electrically driven robotic manipulators
    Asian Journal of Control, 2014
    Co-Authors: Xinwu Liang, Hesheng Wang, Weidong Chen, Yunhui Liu
    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.

A Behal - One of the best experts on this subject based on the ideXlab platform.

  • adaptive homography based visual servo tracking for a Fixed Camera configuration with a Camera in hand extension
    IEEE Transactions on Control Systems and Technology, 2005
    Co-Authors: Jian Chen, D M Dawson, Warren E Dixon, A Behal
    Abstract:

    In this brief, a homography-based adaptive visual servo controller is developed to enable a robot end-effector to track a desired Euclidean trajectory as determined by a sequence of images for both the Camera-in-hand and Fixed-Camera configurations. To achieve the objectives, a Lyapunov-based adaptive control strategy is employed to actively compensate for the lack of unknown depth measurements and the lack of an object model. The error systems are constructed as a hybrid of pixel information and reconstructed Euclidean variables obtained by comparing the images and decomposing a homographic relationship. Simulation results are provided to demonstrate the performance of the developed controller for the Fixed Camera configuration.