Journal of Guangdong University of Technology ›› 2022, Vol. 39 ›› Issue (05): 93-101.doi: 10.12052/gdutxb.220074

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Tracking and Obstacle Avoidance of Multi-mobile Robots Under Model Predictive Control

Peng Ji-guang, Xiao Han-zhen   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2022-04-02 Published:2022-07-18

Abstract: Aiming to control the formation tracking and obstacle avoidance system of multi-mobile robots under the changing topology, an obstacle avoidance method based on distance and speed between robots and an artificial potential field method to avoid obstacles are proposed to establish a consistent control formation control protocol. Firstly, the communication topology between robots is established to facilitate the information exchange between robots. At the level of formation control, a formation control law with collision avoidance is designed. Then, at the level of formation tracking, the formation error motion problem is transformed into a minimum optimization problem according to the cost function by using model predictive control method. In order to efficiently solve the optimization problem online, a generalized projection neural network optimization method is used, in which the optimal solution is used as the control input. Finally, the simulation of multi-mobile robot formation verifies the effectiveness of the proposed strategy.

Key words: artificial potential field method, model predictive control (MPC), multi-robot formation control, general projection neural network (GPNN).

CLC Number: 

  • TG156
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