Robust Online Model Predictive Control for a Constrained Image-Based Visual Servoing

This paper presents an online image-based visual servoing (IBVS) controller for a 6-degrees-of-freedom (DOF) robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing system's input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real-time experimental results on a 6-DOF robot manipulator with eye-in-hand configuration are presented and discussed.