Sarah Brown, Mauricio Zuluaga, Yinan Zhang, R. Vaughan
{"title":"Rational aggressive behaviour reduces interference in a mobile robot team","authors":"Sarah Brown, Mauricio Zuluaga, Yinan Zhang, R. Vaughan","doi":"10.1109/ICAR.2005.1507491","DOIUrl":null,"url":null,"abstract":"Spatial interference can reduce the effectiveness of teams of mobile robots. We examine a team of robots with no centralized control performing a transportation task, in which robots frequently interfere with each other. The robots must work in the same space, so territorial methods are not appropriate. Previously we have shown that a stereotyped competition, inspired by aggressive displays in various animal species, can reduce interference and improve overall system performance. However, none of the methods previously devised for selecting a robot's 'aggression level' performed better than selecting aggression at random. This paper describes a new, principled approach to selecting an aggression level, based on robot's investment in a task. Simulation experiments with teams of six robots in an office-type environment show that, under certain conditions, this method can significantly improve system performance compared to a random competition and a noncompetitive control experiment. Finally, we discuss the benefits and limitations of such a scheme with respect to the specific environment","PeriodicalId":428475,"journal":{"name":"ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005.","volume":"487 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAR.2005.1507491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Spatial interference can reduce the effectiveness of teams of mobile robots. We examine a team of robots with no centralized control performing a transportation task, in which robots frequently interfere with each other. The robots must work in the same space, so territorial methods are not appropriate. Previously we have shown that a stereotyped competition, inspired by aggressive displays in various animal species, can reduce interference and improve overall system performance. However, none of the methods previously devised for selecting a robot's 'aggression level' performed better than selecting aggression at random. This paper describes a new, principled approach to selecting an aggression level, based on robot's investment in a task. Simulation experiments with teams of six robots in an office-type environment show that, under certain conditions, this method can significantly improve system performance compared to a random competition and a noncompetitive control experiment. Finally, we discuss the benefits and limitations of such a scheme with respect to the specific environment