高技术通讯2026，Vol.36Issue(3)：298-306,9.DOI:10.3772/j.issn.1002-0470.2026.03.008
完全信息下的四足机器人多对一追捕问题研究
Research on multi-to-one pursuit problem of quadruped robots under complete information
摘要
Abstract
The pursuit-evasion problem has wide applications in areas such as confrontation,cooperation,and search.This paper studies the multi-to-one pursuit-evasion game problem under complete information conditions.In this scenario,the positional information of all participants is publicly available.Based on this,a continuous random game framework is constructed,and using the fixed-point theorem,the existence of Nash equilibrium strategies for the pursuit-evasion game is proven within this framework.To achieve this,a method based on deep reinforcement learning is proposed,combining the concept of virtual self-game,to solve for the optimal strategies of both pursuer and evader.Then,comparisons are made with other traditional pursuit algorithms through simulations,demonstra-ting that the pursuit success rate of the proposed algorithm can reach 90%.Finally,experiments are conducted using a physical capture platform to validate the effectiveness and practicality of the proposed approach.关键词
追逃问题/连续随机博弈/深度强化学习/虚拟自博弈/纳什均衡Key words
pursuit-evasion problem/continuous random game/deep reinforcement learning/virtual self-game/Nash equilibrium引用本文复制引用
丁镱明,冯宇,李永强..完全信息下的四足机器人多对一追捕问题研究[J].高技术通讯,2026,36(3):298-306,9.基金项目
国家自然科学基金面上项目(61973276)资助. （61973276）
