Model Predictive Visual Trajectory-Tracking Control of Wheeled Mobile Robots

Abstract

In this paper, the visual-based trajectory-tracking control of differential wheeled mobile robots with fixed cameras is investigated by using a model predictive control (MPC)-based method. Firstly, the kinematic model and visual trajectory-tracking error model are established for a mobile robot system with a fixed camera, where the reference trajectory is generated by a reference robot with the same model of real one. The visual trajectory tracking controller is designed, in which the nonlinear model predictive control (NMPC) method is used to ensure that the mobile robot stays in the field-of-view of the global camera. The simulation results are presented, which show that the MPC controller with larger prediction horizon has better performance in the sense of faster convergence rate and higher tracking accuracy, and the cost function also affects the convergence rate and overshoot of the model predictive control system.