Visual Servoing Based Regulation for Robots with Unknown Parameters

This paper addresses robust visual servoing based regulation of multi-feature points for a 3D manipulator with unknown intrinsic and extrinsic parameters of the vision system. This class of control systems are highly nonlinear control systems characterized as time-varying and strong couple in states and unknown parameters. It is first pointed out that the image Jacobian matrix is not only nonsingular, but its minimum singular value has a positive limit also. This provides the foundation of kinematics and dynamics control of manipulators with visual feedback. Secondly, Euler angle expressed rotation transformation is employed to estimate a subspace of the parameter space of the vision system. Based on the two results above, arbitrarily chosen parameters in this subspace, tracking controllers are proposed so that the image errors can be made as small as desired so long as the control gain is allowed large. The controller does not use visual velocity so as to achieve high and robust performance with low sampling rate of the vision system. The obtained results are proved by Lyapunov direct method. The experiments are included to demonstrate the effectiveness of the controller proposed