A ROBUST PREDICTOR FOR IMAGE-BASED VISUAL SERVOING
The main control problem of visual servoing is to cope with the delay introduced by image acquisition and image processing. This delay is the main reason for limited tracking velocity and acceleration. Predictive algorithms are one solution to handle the delay. A predictor is constructed using BP neural network. It is able to estimate the moving target state even if the motion model of the target is unknown. The composite Jacobian is estimated on-line based on changes in image features and joint angles, eliminating the need for a precise analytical model. Target tracking is achieved by adaptive PD control algorithm with uncertain gravity compensation. Robot control is not dependent on the robot and camera configurations. The visual servoing control scheme provides a good steady-state tracking behaviour and keeps good robustness and adaptability at the same time.
Visual tracking BP neural network State estimation composite Jacobian Image-based visual servoing
FEI LI HUA-LONG XIE XIN-HE XU
Institute of Artificial Intelligence and Robotics, Northeastern University, Shenyang 110004, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
3715-3720
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）