An Efficient TP Model Transformation Algorithm for Robust Visual Servoing in the Presence of Uncertain Data

Abstract

This paper presents a robust visual servoing controller based on an efficient TP model transformation method, while taking into account an uncertain image Jacobian matrix where, the camera intrinsic parameters, image features, and depth estimations are affected by unknown random uncertainties with known bounds. The convex vertex decomposition of image Jacobian matrix through uniform design greatly reduce the number of LMIs in the quasi-min-max model predictive control (MPC) scheme, in order to obtain the optimal control inputs of the constrained visual servoing system, while meeting the real-time requirements. Simulation and Experimental results demonstrate the effectiveness of the proposed method.