{"title":"A local multi-robot cooperative formation control","authors":"L. Yang, Y. Che, J. Guo, Xiwen Huang","doi":"10.1109/YAC.2018.8406397","DOIUrl":null,"url":null,"abstract":"An advanced algorithm for local sensing multi-robot cooperative formation control in uncertain environments is presented in this paper. In this proposed algorithm, the global-level multi-robot cooperative formation control problem is decomposed into a tracking problem of some subsystems each of which only includes one follower and one lead robot. A multi-step predictive strategy is adopted, in which each follower predicts the motion of the leading robot and estimates the relevant information based on the history motion information. The follower keeps formation by observing its leader on the local coordinate system of the following robot. The simulation results are given to demonstrate the feasibility and effectiveness of the approach.","PeriodicalId":226586,"journal":{"name":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YAC.2018.8406397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
An advanced algorithm for local sensing multi-robot cooperative formation control in uncertain environments is presented in this paper. In this proposed algorithm, the global-level multi-robot cooperative formation control problem is decomposed into a tracking problem of some subsystems each of which only includes one follower and one lead robot. A multi-step predictive strategy is adopted, in which each follower predicts the motion of the leading robot and estimates the relevant information based on the history motion information. The follower keeps formation by observing its leader on the local coordinate system of the following robot. The simulation results are given to demonstrate the feasibility and effectiveness of the approach.