M. D. Marco, A. Garulli, Antonio Giannitrapani, A. Vicino
{"title":"协作机器人团队的同步定位和地图构建:集合成员方法","authors":"M. D. Marco, A. Garulli, Antonio Giannitrapani, A. Vicino","doi":"10.1109/TRA.2003.808849","DOIUrl":null,"url":null,"abstract":"The problem of simultaneous localization and map building for a team of cooperating robots moving in an unknown environment is addressed. The robots have to estimate the position of distinguishable static landmarks, and then localize themselves with respect to other robots and landmarks, exploiting distance and angle measurements. A novel set theoretic approach to this problem is presented. The proposed localization algorithm provides position estimates and guaranteed uncertainty regions for all robots and landmarks in the environment.","PeriodicalId":161449,"journal":{"name":"IEEE Trans. Robotics Autom.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2003-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"98","resultStr":"{\"title\":\"Simultaneous localization and map building for a team of cooperating robots: a set membership approach\",\"authors\":\"M. D. Marco, A. Garulli, Antonio Giannitrapani, A. Vicino\",\"doi\":\"10.1109/TRA.2003.808849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of simultaneous localization and map building for a team of cooperating robots moving in an unknown environment is addressed. The robots have to estimate the position of distinguishable static landmarks, and then localize themselves with respect to other robots and landmarks, exploiting distance and angle measurements. A novel set theoretic approach to this problem is presented. The proposed localization algorithm provides position estimates and guaranteed uncertainty regions for all robots and landmarks in the environment.\",\"PeriodicalId\":161449,\"journal\":{\"name\":\"IEEE Trans. Robotics Autom.\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"98\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Trans. Robotics Autom.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TRA.2003.808849\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Trans. Robotics Autom.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TRA.2003.808849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simultaneous localization and map building for a team of cooperating robots: a set membership approach
The problem of simultaneous localization and map building for a team of cooperating robots moving in an unknown environment is addressed. The robots have to estimate the position of distinguishable static landmarks, and then localize themselves with respect to other robots and landmarks, exploiting distance and angle measurements. A novel set theoretic approach to this problem is presented. The proposed localization algorithm provides position estimates and guaranteed uncertainty regions for all robots and landmarks in the environment.