Tsuyoshi Ogawa, K. Sakurama, Shintaro Nakatani, S. Nishida
{"title":"Relative Position Estimation of Detected Robots for Formation Control","authors":"Tsuyoshi Ogawa, K. Sakurama, Shintaro Nakatani, S. Nishida","doi":"10.9746/SICETR.55.181","DOIUrl":null,"url":null,"abstract":"In this paper, we address a relative position estimation problem for a line formation of multiple robots. The existing study assumed that the light of all distance sensors hits other robots, which does not always happen. Therefore, we propose a method for estimating the relative positions of the detected robots which is effective even if the light of distance sensors does not always hit the robots. We consider using information on the motion of the robots obtained by wireless communication. To fuse the information from the distance sensors and wireless sensors, the Extended Kalman Filter is employed. Finally, we verify the effectiveness of this method by a simulation.","PeriodicalId":416828,"journal":{"name":"Transactions of the Society of Instrument and Control Engineers","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions of the Society of Instrument and Control Engineers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9746/SICETR.55.181","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
In this paper, we address a relative position estimation problem for a line formation of multiple robots. The existing study assumed that the light of all distance sensors hits other robots, which does not always happen. Therefore, we propose a method for estimating the relative positions of the detected robots which is effective even if the light of distance sensors does not always hit the robots. We consider using information on the motion of the robots obtained by wireless communication. To fuse the information from the distance sensors and wireless sensors, the Extended Kalman Filter is employed. Finally, we verify the effectiveness of this method by a simulation.