{"title":"CBTMP:异构协作环境下的多智能体寻径优化","authors":"Jianqi Gao;Yanjie Li;Yongjin Mu;Qi Liu;Haoyao Chen;Yunjiang Lou","doi":"10.1109/LRA.2025.3557672","DOIUrl":null,"url":null,"abstract":"This letter introduces the Conflict-Based Three-agent Meeting with Pickup (CBTMP), a near-optimal algorithm tailored for cooperative multi-agent path finding in heterogeneous environments, specifically to boost the operational efficiency of intelligent warehouses. CBTMP is a two-level algorithm. The high-level policy identifies the meeting positions for heterogeneous agents by reformulating the cooperative multi-agent path finding problem as a multi-group, three-agent meeting with pickup problem. Using the meeting positions and predefined task positions, the low-level policy utilizes the proposed conflict-based search with time-step alignment algorithm to plan conflict-free paths for all heterogeneous agents. Extensive evaluations on six two-dimensional grid benchmark maps reveal that CBTMP not only significantly bolsters solution success rates but also attains near-optimal sum-of-costs and makespan values. To confirm its real-world applicability, we also validate CBTMP through experiments with physical Turtlebot3 robots.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 5","pages":"5010-5017"},"PeriodicalIF":4.6000,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CBTMP: Optimizing Multi-Agent Path Finding in Heterogeneous Cooperative Environments\",\"authors\":\"Jianqi Gao;Yanjie Li;Yongjin Mu;Qi Liu;Haoyao Chen;Yunjiang Lou\",\"doi\":\"10.1109/LRA.2025.3557672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter introduces the Conflict-Based Three-agent Meeting with Pickup (CBTMP), a near-optimal algorithm tailored for cooperative multi-agent path finding in heterogeneous environments, specifically to boost the operational efficiency of intelligent warehouses. CBTMP is a two-level algorithm. The high-level policy identifies the meeting positions for heterogeneous agents by reformulating the cooperative multi-agent path finding problem as a multi-group, three-agent meeting with pickup problem. Using the meeting positions and predefined task positions, the low-level policy utilizes the proposed conflict-based search with time-step alignment algorithm to plan conflict-free paths for all heterogeneous agents. Extensive evaluations on six two-dimensional grid benchmark maps reveal that CBTMP not only significantly bolsters solution success rates but also attains near-optimal sum-of-costs and makespan values. To confirm its real-world applicability, we also validate CBTMP through experiments with physical Turtlebot3 robots.\",\"PeriodicalId\":13241,\"journal\":{\"name\":\"IEEE Robotics and Automation Letters\",\"volume\":\"10 5\",\"pages\":\"5010-5017\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Robotics and Automation Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10948333/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Robotics and Automation Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10948333/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
CBTMP: Optimizing Multi-Agent Path Finding in Heterogeneous Cooperative Environments
This letter introduces the Conflict-Based Three-agent Meeting with Pickup (CBTMP), a near-optimal algorithm tailored for cooperative multi-agent path finding in heterogeneous environments, specifically to boost the operational efficiency of intelligent warehouses. CBTMP is a two-level algorithm. The high-level policy identifies the meeting positions for heterogeneous agents by reformulating the cooperative multi-agent path finding problem as a multi-group, three-agent meeting with pickup problem. Using the meeting positions and predefined task positions, the low-level policy utilizes the proposed conflict-based search with time-step alignment algorithm to plan conflict-free paths for all heterogeneous agents. Extensive evaluations on six two-dimensional grid benchmark maps reveal that CBTMP not only significantly bolsters solution success rates but also attains near-optimal sum-of-costs and makespan values. To confirm its real-world applicability, we also validate CBTMP through experiments with physical Turtlebot3 robots.
期刊介绍:
The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.