Adaptive control techniques for dynamic visual repositioning of hand-eye robotic systems

Using active monocular vision for 3-D visual control tasks is difficult since the translational and the rotational degrees of freedom are strongly coupled. The paper addresses several issues in 3-D visual control and presents adaptive control schemes for the problem of robotic visual servoing (eye-in-hand configuration) around a static rigid target. The objective is to move the image projections of several feature points of the static rigid target to some desired image positions. The inverse perspective transformation is assumed partially unknown. The adaptive controllers compensate for the servoing errors, the partially unknown camera parameters, and the computational delays which are introduced by the time-consuming vision algorithms. The authors present a stability analysis along with a study of the conditions that the feature points must satisfy in order for the problem to be solvable. Finally, several experimental results are presented to verify the validity and the efficacy of the proposed algorithms.