Adaptive Visual Servoing with Imperfect Camera and Robot Parameters

This paper presents a new adaptive controller for dynamic image-based visual servoing of a robot manipulator when the camera intrinsic and extrinsic parameters and robot physical are not calibrated. To cope with nonlinear dependence of the image Jacobian on the unknown parameters, this controller employs depth-independent image Jacobian which does not depend on the scale factors determined by the depths of feature points. By removing the scale factors, the camera and robot parameters appear linearly in the close-loop dynamics so that a new algorithm is developed to estimate these parameters on-line. Lyapunov theory is employed to prove asymptotic convergence of the image errors based on the robot dynamics. Simulations have been conducted to demonstrate the performance of the proposed controller.