The Experts below are selected from a list of 3678 Experts worldwide ranked by ideXlab platform
Yantao Shen - One of the best experts on this subject based on the ideXlab platform.
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Rapid robot/workcell calibration using line-Based approach
2008 IEEE International Conference on Automation Science and Engineering, 2008Co-Authors: Yantao Shen, Ning Xi, Ruiguo Yang, Xiongzi Li, George Zhang, Thomas A. FuhlbriggeAbstract: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.
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Uncalibrated visual servoing of planar robots
Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002Co-Authors: Yantao Shen, Guoliang Xiang, Kejie LiAbstract: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.
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Adaptive motion control of manipulators with uncalibrated visual feedback
IEEE RSJ International Conference on Intelligent Robots and Systems, 2002Co-Authors: Yantao Shen, Ning XiAbstract: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.
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Asymptotic motion control of robot manipulators using uncalibrated visual feedback
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001Co-Authors: Yantao Shen, Jianwei Zhang, Kejie Li, A. KnollAbstract: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.
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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, 2001Co-Authors: Yantao Shen, Kejie LiAbstract: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.
Kejie Li - One of the best experts on this subject based on the ideXlab platform.
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Uncalibrated visual servoing of planar robots
Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002Co-Authors: Yantao Shen, Guoliang Xiang, Kejie LiAbstract: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.
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Asymptotic motion control of robot manipulators using uncalibrated visual feedback
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001Co-Authors: Yantao Shen, Jianwei Zhang, Kejie Li, A. KnollAbstract: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.
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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, 2001Co-Authors: Yantao Shen, Kejie LiAbstract: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 - One of the best experts on this subject based on the ideXlab platform.
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Asymptotic motion control of robot manipulators using uncalibrated visual feedback
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001Co-Authors: Yantao Shen, Jianwei Zhang, Kejie Li, A. KnollAbstract: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.
Ning Xi - One of the best experts on this subject based on the ideXlab platform.
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Rapid robot/workcell calibration using line-Based approach
2008 IEEE International Conference on Automation Science and Engineering, 2008Co-Authors: Yantao Shen, Ning Xi, Ruiguo Yang, Xiongzi Li, George Zhang, Thomas A. FuhlbriggeAbstract: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.
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Adaptive motion control of manipulators with uncalibrated visual feedback
IEEE RSJ International Conference on Intelligent Robots and Systems, 2002Co-Authors: Yantao Shen, Ning XiAbstract: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.
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Multisensor Based intelligent planning and control for robotic manipulators on a mobile platform
Proceedings 5th IEEE International Workshop on Robot and Human Communication. RO-MAN'96 TSUKUBA, 1996Co-Authors: B.k. Ghosh, Ning Xi, Di Xiao, Tzyh Jong TarnAbstract:This paper deals with the problem of tracking and grasping a moving part on a rotating turntable with the aid of a robotic manipulator is considered. The position and orientation of the part with respect to the turntable is assumed to be a priori unknown. Likewise the position and orientation of the robot with respect to the turntable is also assumed to be a priori unknown. The procedure of the algorithm described in this paper involves "sensor fusion" with encoders placed on the turntable and encoders on the robot. Having obtained a good estimate of the position and orientation of the part with respect to the Base Frame of the robot, the manipulator is controlled to track and grasp the moving part. The operation of grasping has been demonstrated experimentally. The paper emphasizes various cases of the estimation scheme as a result of choosing various geometric cues on the end effector.
Jianwei Zhang - One of the best experts on this subject based on the ideXlab platform.
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A new method for detecting pipeline deformation by an inspection robot with a moving 2D laser rang finder
2011 IEEE International Conference on Robotics and Biomimetics, 2011Co-Authors: Zhangjun Song, Jianwei ZhangAbstract:Buried pipelines would be deformed as a result of the loading of surface facilities and vehicles. If the deformation has gone beyond the critical level, it may cause serious consequences, such as the damage of the pipeline. Pipeline deformation is also applied to estimate the stress in the pipeline, and thus to keep the pipeline stress below the critical level. A new method for detecting pipeline deformation by an inspection robot with a laser range finder (LRF) is presented in this paper. The robot posture changes instantaneous when the robot is running in the pipeline, which makes the deformation detection difficult. To calculate the deformation rate of the pipeline, the moving Frame of the robot, the Base Frame on the pipeline, and Frame of the LRF are established and their transformation matrix are deduced with the posture angles of the robot detected real-time. After the range data collected by the LRF are transformed to the Base Frame, a least squares method is used to fit the ellipse function. With the fitted ellipse function, the ellipse can be drawn and the deformation rate can be calculated easily. Experiments by the inspection robot in real pipelines are carried out and the results show that the proposed method is useful and valid.
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Asymptotic motion control of robot manipulators using uncalibrated visual feedback
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001Co-Authors: Yantao Shen, Jianwei Zhang, Kejie Li, A. KnollAbstract: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.
