A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without req...A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.展开更多
A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay ...A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.展开更多
In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of im...In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of image Jacobian, CMAC (cerebellar model articulation controller) neural network is inserted into visual servo control loop to implement the nonlinear mapping. Two control schemes are used. Simulation results on two schemes are provided, which show a better tracking precision and stability can be achieved using scheme 2.展开更多
A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visua...A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visual guiding mode, for the robot works in an open loop visual servo control mode, the manipulating burden of the operator is reduced largely. In the visual servo mode the robot can locate the position of the target assigned by the operator and pick it up by its manipulator. With the help of the operator, the diffieuh problems of finding and handling a target in a complicated environment by the robot can be solved easily.展开更多
针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应...针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应滑模控制方法。通过将表征机器人图像空间与任务空间映射关系的图像雅可比矩阵与系统不确定项集总到同一通道的状态方程,引入ESO对分拣并联机器人视觉伺服系统的集总不确定性进行在线估计,设计一种基于扩张状态观测器的自适应积分滑模控制器,并通过设计自适应律动态调整滑模控制切换增益,以提高视觉伺服系统精度,同时达到抑制滑模控制抖振的效果。采用Lyapunov稳定性理论证明该控制方法的稳定性,最后通过仿真实验验证了所提出视觉伺服自适应滑模控制方法的可行性和有效性。展开更多
文摘A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.
基金supported by China Postdoctoral Science Founda-tion (No. 20080441093)Key Laboratory Foundation of Liaoning Province (No. 2008S088).
文摘A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.
基金This project is supported by National Natural Science Foundation of China (No.59990470).
文摘In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of image Jacobian, CMAC (cerebellar model articulation controller) neural network is inserted into visual servo control loop to implement the nonlinear mapping. Two control schemes are used. Simulation results on two schemes are provided, which show a better tracking precision and stability can be achieved using scheme 2.
基金Supported by the National High Technology Research and Development Program of China （No. 2003AA421030） and the National Science Foundation of China （No. 60375026）.
文摘A dual operational modes mobile robot system based on visual guiding and visual servo control is presented. This system consists of a mobile robot with a two-axis manipulator and a tele-operation station. In the visual guiding mode, for the robot works in an open loop visual servo control mode, the manipulating burden of the operator is reduced largely. In the visual servo mode the robot can locate the position of the target assigned by the operator and pick it up by its manipulator. With the help of the operator, the diffieuh problems of finding and handling a target in a complicated environment by the robot can be solved easily.
基金Supported by National Natural Science Foundation of China（60874002） Key Project of Shanghai Education Committee （09ZZ158） Leading Academic Discipline Project of Shanghai Municipal Government （S30501）
文摘针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应滑模控制方法。通过将表征机器人图像空间与任务空间映射关系的图像雅可比矩阵与系统不确定项集总到同一通道的状态方程,引入ESO对分拣并联机器人视觉伺服系统的集总不确定性进行在线估计,设计一种基于扩张状态观测器的自适应积分滑模控制器,并通过设计自适应律动态调整滑模控制切换增益,以提高视觉伺服系统精度,同时达到抑制滑模控制抖振的效果。采用Lyapunov稳定性理论证明该控制方法的稳定性,最后通过仿真实验验证了所提出视觉伺服自适应滑模控制方法的可行性和有效性。
