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Base Frame

The Experts below are selected from a list of 3678 Experts worldwide ranked by ideXlab platform

Yantao Shen – 1st expert on this subject based on the ideXlab platform

  • Rapid robot/workcell calibration using line-Based approach
    2008 IEEE International Conference on Automation Science and Engineering, 2008
    Co-Authors: Yantao Shen, Ning Xi, Ruiguo Yang, Xiongzi Li, George Zhang, Thomas A. Fuhlbrigge

    Abstract:

    This paper presents a new line-Based calibration method for automatically computing the transformation relationship between industrial robots and workcell. The calibration method mainly depends on the position-sensitive detector (PSD) servo control of the robots. The developed servo controller allows precisely positioning the laser beam (line) from a single laser pointer attached at the end-effector of robot onto the center of the PSD in a well-designed lateral-effect PSDs fixture. The selected PSD in the fixture has high performance with the resolution of 0.5 mum. Once the precision localizations/positioning in the centers of multiple PSDs are achieved, the group of points in the robot Base Frame and workcell Frame can be generated by using the intersection of laser beams (lines) and by using the predefined fixture-workcell information, respectively. A quaternion algorithm and the least square method are then employed to determine the transformation relationship between robot Base Frame and workcell Frame. The experiments have been implemented on an ABB industrial robot IRB1600, the results verify the effectiveness of both the PSD servoing and the line-Based calibration method as well as demonstrate the performance of the whole system.

  • Uncalibrated visual servoing of planar robots
    Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002
    Co-Authors: Yantao Shen, Guoliang Xiang, Kejie Li

    Abstract:

    The calibration accuracy of the intrinsic and extrinsic parameters of the vision system greatly affects the performance of visual servoing. We address the problem of controlling a planar manipulator using a fixed single camera without calibrating its intrinsic parameters and the transformation matrix between the robot Base Frame and the camera Frame, and without measuring manipulator’s depth. Based on an important observation that the unknown parameters can be separated from the unknown composite image Jacobian matrix, we propose an adaptive algorithm to estimate the unknown and mixed parameters on-line. It is proved with a full consideration of dynamics of the system by Lyapunov approach that the feature points of planar manipulator approach asymptotically to the desired ones on image plane and the estimated parameters are bounded under the control of the proposed visual servo controller. The performance has been confirmed by simulations and experiments.

  • Adaptive motion control of manipulators with uncalibrated visual feedback
    IEEE RSJ International Conference on Intelligent Robots and Systems, 2002
    Co-Authors: Yantao Shen, Ning Xi

    Abstract:

    For the visual servoing tasks, it is required to calibrate accurately the homogeneous transformation matrix between the robot Base Frame and vision Frame besides the intrinsic parameters of the vision system. In this paper, Based on an important observation, that is, the unknown transformation matrix between the robot Base Frame and vision Frame can be separated from the visual Jacobian matrix, and by virtue of decomposition of rotation matrix, we design a novel adaptive position-Based visual servo controller for manipulators when the transformation matrix is not calibrated. It is proved with a full dynamics of the system by the Lyapunov approach that the motion of the manipulator approaches asymptotically to the desired trajectory. Simulations and experimental results both demonstrate the performance of this new controller.

Kejie Li – 2nd expert on this subject based on the ideXlab platform

  • Uncalibrated visual servoing of planar robots
    Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002
    Co-Authors: Yantao Shen, Guoliang Xiang, Kejie Li

    Abstract:

    The calibration accuracy of the intrinsic and extrinsic parameters of the vision system greatly affects the performance of visual servoing. We address the problem of controlling a planar manipulator using a fixed single camera without calibrating its intrinsic parameters and the transformation matrix between the robot Base Frame and the camera Frame, and without measuring manipulator’s depth. Based on an important observation that the unknown parameters can be separated from the unknown composite image Jacobian matrix, we propose an adaptive algorithm to estimate the unknown and mixed parameters on-line. It is proved with a full consideration of dynamics of the system by Lyapunov approach that the feature points of planar manipulator approach asymptotically to the desired ones on image plane and the estimated parameters are bounded under the control of the proposed visual servo controller. The performance has been confirmed by simulations and experiments.

  • Asymptotic motion control of robot manipulators using uncalibrated visual feedback
    Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001
    Co-Authors: Yantao Shen, Jianwei Zhang, Kejie Li, A. Knoll

    Abstract:

    To implement a visual feedback controller, it is necessary to calibrate the homogeneous transformation matrix between the robot Base Frame and the vision Frame besides the intrinsic parameters of the vision system. The calibration accuracy greatly affects the control performance. In this paper, we address the problem of controlling a robot manipulator using visual feedback without calibrating the transformation matrix. We propose an adaptive algorithm to estimate the unknown matrix online. It is proved by the Lyapunov method that the robot motion approaches asymptotically to the desired one and the estimated matrix is bounded under the control of the proposed visual feedback controller. The performance was confirmed by simulations and experiments.

  • Adaptive visual feedback control of manipulators in uncalibrated environment
    Proceedings 2001 IEEE RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millenni, 2001
    Co-Authors: Yantao Shen, Kejie Li

    Abstract:

    To implement a position-Based visual feedback controller for a manipulator, it is necessary to calibrate the homogeneous transformation matrix between its Base Frame and the vision Frame besides the intrinsic parameters of the vision system. In this paper, Based on an important observation that the unknown transformation matrix can be separated from the visual Jacobian matrix, we design an adaptive controller for manipulators when the matrix is not calibrated. It is proved, with a full dynamics of the system, by the Lyapunov approach that the motion of the manipulator approaches asymptotically to the desired trajectory. Simulations and experimental results both demonstrate the performance of this new controller.

A. Knoll – 3rd expert on this subject based on the ideXlab platform

  • Asymptotic motion control of robot manipulators using uncalibrated visual feedback
    Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001
    Co-Authors: Yantao Shen, Jianwei Zhang, Kejie Li, A. Knoll

    Abstract:

    To implement a visual feedback controller, it is necessary to calibrate the homogeneous transformation matrix between the robot Base Frame and the vision Frame besides the intrinsic parameters of the vision system. The calibration accuracy greatly affects the control performance. In this paper, we address the problem of controlling a robot manipulator using visual feedback without calibrating the transformation matrix. We propose an adaptive algorithm to estimate the unknown matrix online. It is proved by the Lyapunov method that the robot motion approaches asymptotically to the desired one and the estimated matrix is bounded under the control of the proposed visual feedback controller. The performance was confirmed by simulations and experiments.