{"title":"Formation control based on artificial intelligence for multi-agent coordination","authors":"Seong-woo Hong, S. Shin, D. Ahn","doi":"10.1109/ISIE.2001.931828","DOIUrl":null,"url":null,"abstract":"In this paper, the authors propose a method of cooperative control based on an artificially intelligent system in a distributed autonomous robotic system. In general, a multi-agent behavior algorithm is simple and effective for small number of robots. However, as the number of robots increases, this becomes difficult to realize because a multi-robot behavior algorithm requires multiple constraints and goals in mobile robot navigation problems. As the solution to the above problem, the authors propose an architecture of a fuzzy-neuro system for obstacle avoidance. The controller adopts a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. Simulation results shows that the proposed strategy is effective for multi-robot to avoid obstacles while maintaining a formation.","PeriodicalId":124749,"journal":{"name":"ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.2001.931828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
In this paper, the authors propose a method of cooperative control based on an artificially intelligent system in a distributed autonomous robotic system. In general, a multi-agent behavior algorithm is simple and effective for small number of robots. However, as the number of robots increases, this becomes difficult to realize because a multi-robot behavior algorithm requires multiple constraints and goals in mobile robot navigation problems. As the solution to the above problem, the authors propose an architecture of a fuzzy-neuro system for obstacle avoidance. The controller adopts a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. Simulation results shows that the proposed strategy is effective for multi-robot to avoid obstacles while maintaining a formation.