Monte carlo localization in highly symmetric environments

ICINCO-RA Pub Date : 2018-08-21 DOI:10.5220/0001215802490254
S. Sehestedt, Frank E. Schneider
{"title":"Monte carlo localization in highly symmetric environments","authors":"S. Sehestedt, Frank E. Schneider","doi":"10.5220/0001215802490254","DOIUrl":null,"url":null,"abstract":"The localization problem is a central issue in mobile robotics. Monte Carlo Localization (MCL) is a popular method to solve the localization problem for mobile robots. However, usual MCL has some shortcomings in terms of computational complexity, robustness and the handling of highly symmetric environments. These three issues are adressed in this work. We present three Monte Carlo localization algorithms as a solution to these problems. The focus lies on two of these, which are especially suitable for highly symmetric environments, for which we introduce two-stage sampling as the resampling scheme.","PeriodicalId":302311,"journal":{"name":"ICINCO-RA","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICINCO-RA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0001215802490254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

The localization problem is a central issue in mobile robotics. Monte Carlo Localization (MCL) is a popular method to solve the localization problem for mobile robots. However, usual MCL has some shortcomings in terms of computational complexity, robustness and the handling of highly symmetric environments. These three issues are adressed in this work. We present three Monte Carlo localization algorithms as a solution to these problems. The focus lies on two of these, which are especially suitable for highly symmetric environments, for which we introduce two-stage sampling as the resampling scheme.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
高度对称环境中的蒙特卡罗定位
定位问题是移动机器人的一个核心问题。蒙特卡罗定位(MCL)是解决移动机器人定位问题的一种常用方法。然而,通常的MCL在计算复杂性、鲁棒性和对高度对称环境的处理方面存在一些不足。这三个问题在本工作中得到了解决。我们提出了三种蒙特卡罗定位算法来解决这些问题。重点在于其中的两个,它们特别适合于高度对称的环境,为此我们引入了两阶段采样作为重采样方案。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Calibration Aspects of Multiple Line-scan Vision System Application for Planar Objects Inspection Automatic Generation of Executable Code for a Robot Cell using UPNP and XIRP Kamanbaré - a tree-climbing biomimetic robotic platform for environmental research Monte carlo localization in highly symmetric environments The tele-echography medical robot Otelo2 - teleoperated with a multi level architecture using trinomial protocol
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1