Robust object tracking of robot manipulator using low-cost vision system

This paper proposes a robust visual servoing scheme for robot manipulator with eye-in-hand camera configuration. To perform the tasks defined in the image plane, the velocity Jacobian matrix is used to transform the camera motion to the objection position change. In addition, a dynamic learning controller is designed to improve the tracking performance of robotic system. The proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system without the dynamic control loop in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.