Abstract
Making full use of the cooperation of multi-robots can improve the success rate of apursuit task. Therefore, this paper proposes a multi-robot cooperative pursuit strategy based on the zero-sum game and surrounding points adjustment. First, a mathematical description of the multi-robot pursuit problem is constructed, and the zero-sum game model is established considering the cooperation of the pursuit robots and the confrontation between the pursuit robots and the escape robot. By solving the game model, the optimal movement strategies of the pursuit robots and the escape robot are obtained. Then, the position adjustment method of the pursuit robots is studied based on the Hungarian algorithm, and the pursuit robots are controlled to surround the escape robot. Based on this, a multi-robot cooperative pursuit strategy is proposed that divides the pursuit process into two stages: pursuit robot position adjustment and game pursuit. Finally, the correctness and effectiveness of the multi-robot cooperative pursuit strategy are verified with simulation experiments. The multi-robot cooperative pursuit strategy allows the pursuit robots to capture the escape robot successfully without conflicts among the pursuit robots. It can be seen from the documented simulation experiments that the success rate of the pursuit task using the strategy proposed in this paper is 100%.
Highlights
A multi-robot system consists of more than two robots, which can improve the efficiency of task completion with cooperation [1]
Su [16] proposed a multi-robot cooperative pursuit strategy based on the Q-learning algorithm, where the pursuit robots are moved to a certain distance from the escape robot
The zero-sum game model of the multi-robot pursuit problem is established based on the three basic elements of the game player, strategy sets, and payoff function
Summary
A multi-robot system consists of more than two robots, which can improve the efficiency of task completion with cooperation [1]. Su [16] proposed a multi-robot cooperative pursuit strategy based on the Q-learning algorithm, where the pursuit robots are moved to a certain distance from the escape robot This strategy does not analyze whether the positions of the pursuit robots meet the initial position constraints, which results in the pursuit task having a high probability of failure. In research previously conducted on multi-robot pursuit, the movement of the escape robot needs to be considered For this problem, Selvakumar [21] regarded the team of pursuit robots as a players in a game and the escape robot as the another player. The problem of multi-robot cooperative pursuit: a multi-robot cooperative pursuit strategy including two stages and considering both pursuit robot position adjustment and the pursuit robots’ pursuit of the eacape robots based on a zero-sum game is proposed to improve the success rate of the pursuit task; 2.
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