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Complex Systems and Complexity Science  2023, Vol. 20 Issue (3): 97-102    DOI: 10.13306/j.1672-3813.2023.03.013
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Ring-around Formation Control of Multi-robot Systems Based on Reinforcement Learning
HAN Yilin, WANG Lili, YANG Hongyong, FAN Zhilin
School of Information and Electrical Engineering, Ludong University, Yantai 264025, China
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Abstract  For the robot formation tracking problem of unknown target, a robot motion control model is established, and a target tracking and ring-around control strategy based on Reinforcement Learning(RL) is proposed to solve the problem. Driven by RL, the robot explore the location of the target point and initiate tracking. The robot tracking strategy is optimized in real time using the ring-around formation motion model to achieve dynamic tracking and ring-around control of the fleeing target point. A multi-robot motion control environment is established, and the experiments indicate that the combined RL can accelerate the multi-robot formation adjustment time and prove the efficiency of the multi-robot ring-around formation control strategy.
Key wordsmotion control      reinforcement learning      target tracking      ring-around formation control     
Received: 12 March 2021      Published: 08 October 2023
ZTFLH:  TP273+.5  
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HAN Yilin
WANG Lili
YANG Hongyong
FAN Zhilin
Cite this article:   
HAN Yilin,WANG Lili,YANG Hongyong, et al. Ring-around Formation Control of Multi-robot Systems Based on Reinforcement Learning[J]. Complex Systems and Complexity Science, 2023, 20(3): 97-102.
URL:  
https://fzkx.qdu.edu.cn/EN/10.13306/j.1672-3813.2023.03.013     OR     https://fzkx.qdu.edu.cn/EN/Y2023/V20/I3/97