Dynamic Visual Servoing with an Uncalibrated Eye-in-Hand Camera

Abstract

This Chapter presents a new adaptive controller for dynamic image-based visual servoing of a robot manipulator uncalibrated eye-in-hand visual feedback. To cope with nonlinear dependence of the image Jacobian on the unknown parameters, this controller employs a matrix called depth-independent interaction matrix which does not depend on the scale factors determined by the depths of target points. A new adaptive algorithm has been developed to estimate the unknown intrinsic and extrinsic parameters and the unknown 3-D coordinates of the target points. With a full consideration of dynamic responses of the robot manipulator, we employed the Lyapunov method to prove the convergence of the postion errors to zero and the convergence of the estimated parameters to the real values. Experimental results illustrate the performance of the proposed methods.