{"title":"Deployment Strategy for Mobile Robots with Energy and Timing Constraints","authors":"Yongguo Mei, Yung-Hsiang Lu, Y.C. Hu, C.S.G. Lee","doi":"10.1109/ROBOT.2005.1570540","DOIUrl":null,"url":null,"abstract":"Mobile robots usually carry limited energy and have to accomplish their tasks before deadlines. Examples of these tasks include search and rescue, landmine detection, and carpet cleaning. Many researchers have been studying control, sensing, and coordination for these tasks. However, one major problem has not been fully addressed: the initial deployment of mobile robots. The deployment problem considers the number of robots needed and their initial locations. In this paper, we present a solution for the deployment problem when robots have limited energy and time to collectively accomplish coverage tasks. Simulation results show that our method uses 26% fewer robots comparing with two heuristics for covering the same size of area.","PeriodicalId":350878,"journal":{"name":"Proceedings of the 2005 IEEE International Conference on Robotics and Automation","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2005 IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOT.2005.1570540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 46
Abstract
Mobile robots usually carry limited energy and have to accomplish their tasks before deadlines. Examples of these tasks include search and rescue, landmine detection, and carpet cleaning. Many researchers have been studying control, sensing, and coordination for these tasks. However, one major problem has not been fully addressed: the initial deployment of mobile robots. The deployment problem considers the number of robots needed and their initial locations. In this paper, we present a solution for the deployment problem when robots have limited energy and time to collectively accomplish coverage tasks. Simulation results show that our method uses 26% fewer robots comparing with two heuristics for covering the same size of area.
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