{"title":"EKF based distributed cooperative localization for a multirobot team","authors":"Chuxi Li, Jieying Lu, W. Su","doi":"10.1109/ICARCV.2016.7838791","DOIUrl":null,"url":null,"abstract":"This paper studies distributed cooperative localization problem for a multirobot team with one leader and two followers. Each robot in the team is equipped local sensors and can exchange data with its neighbors through wireless communication network. A distributed localization algorithm is developed by using extended Kalman filter (EKF) scheme. In every sampling period, each member in the team estimates its local state based on its local measurements and neighbor's state estimation information sent from its neighbors at current sampling time or last sampling time. A simulation result shows that the algorithm is feasible.","PeriodicalId":128828,"journal":{"name":"2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2016.7838791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper studies distributed cooperative localization problem for a multirobot team with one leader and two followers. Each robot in the team is equipped local sensors and can exchange data with its neighbors through wireless communication network. A distributed localization algorithm is developed by using extended Kalman filter (EKF) scheme. In every sampling period, each member in the team estimates its local state based on its local measurements and neighbor's state estimation information sent from its neighbors at current sampling time or last sampling time. A simulation result shows that the algorithm is feasible.