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.
International Journal of Robotics and Automation
Digital Object Identifier (DOI)
Guo, Tongying; Wang, Haichen; Liu, Yong; and Wang, Ying, "VISION-BASED MOBILE ROBOT LEADER–FOLLOWER CONTROL USING MODEL PREDICTIVE CONTROL" (2019). Faculty Publications. 4572.