Tongying Guo, Haichen Wang, Yong Liu, Ming Li, and Ying Wang
Mobile robots, leader–follower control, model predictive control,computer vision
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.
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