{"title":"Market-based approach to Multi-robot Task Allocation","authors":"A. Hussein, A. Khamis","doi":"10.1109/ICBR.2013.6729278","DOIUrl":null,"url":null,"abstract":"This paper presents a market-based approach used for solving the Multi-robot Task Allocation (MRTA) problem that arises in the context of Multi-robot Systems (MRS). The proposed approach is used to find the best allocation of a number of heterogeneous robots to a number of heterogeneous tasks. The approach was extensively tested over a number of test scenarios in order to test its capability of handling complex constrained MRS applications that included extended number of tasks and robots. Finally a comparative study is implemented between the proposed market-based approach and two optimization-based approaches, the results show that the optimization-based approaches outperformed the market-based approach in terms of best allocation and computational time, however, in terms of capabilities matching the difference between both algorithms is very minimal.","PeriodicalId":269516,"journal":{"name":"2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBR.2013.6729278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
This paper presents a market-based approach used for solving the Multi-robot Task Allocation (MRTA) problem that arises in the context of Multi-robot Systems (MRS). The proposed approach is used to find the best allocation of a number of heterogeneous robots to a number of heterogeneous tasks. The approach was extensively tested over a number of test scenarios in order to test its capability of handling complex constrained MRS applications that included extended number of tasks and robots. Finally a comparative study is implemented between the proposed market-based approach and two optimization-based approaches, the results show that the optimization-based approaches outperformed the market-based approach in terms of best allocation and computational time, however, in terms of capabilities matching the difference between both algorithms is very minimal.