Adaptive Image-Based Trajectory Tracking of Robots

This paper presents a new and novel controller for dynamic image-based trajectory tracking of a robot manipulator in uncalibrated environments. The controller is designed to cope with the case when the homogenous transformation matrix between the root and the vision system is unknown. A new adaptive algorithm, different from the Slotine and Li’s method, has been developed to estimate a set of parameters corresponding to the unknown transformation matrix. With a full consideration of dynamic responses of the robot manipulator, we employed the Lyapunov method to prove the convergence of the image errors of the trajectory to zero and the convergence of the estimated parameters to the real values up to a scale. Simulations and experiments have been conducted to demonstrate good convergence of the trajectory errors of the robot and the estimated parameters under the control of the proposed method.