VISION-BASED MOBILE ROBOT LEADER-FOLLOWER CONTROL USING MODEL PREDICTIVE CONTROL

Leader-follower control of mobile robots has been an attractive topic in the robotics community. In this paper, a vision-based leader- follower tracking control system is presented using two autonomous mobile robots and model predictive control (MPC). In particular, the follower robot employs a vision sensor and a laser scanner to acquire the distance and orientation information between the leader robot and the follower. Then, the extended Kalman filter algorithm is employed to remove the measurement noise. A vision-based model predictive control (MPC) method for nonholonomic mobile robots is proposed to implement a reliable leader-follower tracking control. The simulation results under different control horizons are provided to validate the proposed control strategy.