Uncalibrated Visual Servo control with multi-constraint satisfaction

Abstract

This paper devises a new multicriteria image-based controller for the control of six degrees of freedom (PUMA560) robotic arm, based upon Linear Matrix Inequality (LMI). The aim lies in developing such a method that neither involves camera calibration parameters nor inverse kinematics. The approach adopted in this paper includes transpose Jacobian control; thus, inverse of the Jacobian matrix is no longer required. The proposed controller allows stabilizing the camera despite the unknown value of the target point depth. To make sure that the features remain in the camera field of view, and to restrict the controller's input using some bounds, visibility and kinematic constraints are introduced in the form of LMIs. By invoking the Lyapunov's direct method, closed-loop stability of the system is ensured. Simulation results are shown for three different cases, which exhibit the system stability and convergence even in the presence of large errors, and present the comparative analysis of both i.e., systems with and without visibility and kinematic constraints.