Simultaneous localization and map building for a team of cooperating robots: a set membership approach

M. D. Marco, A. Garulli, Antonio Giannitrapani, A. Vicino
{"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}
引用次数: 98

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.
协作机器人团队的同步定位和地图构建:集合成员方法
研究了协作机器人在未知环境中移动时的同时定位和地图构建问题。机器人必须估计可识别的静态地标的位置,然后利用距离和角度测量,相对于其他机器人和地标进行定位。提出了一种新的集论方法来解决这一问题。提出的定位算法为环境中所有机器人和地标提供位置估计和保证的不确定性区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信