Mobile Robot Autonomous Exploration and Navigation in Large-scale Indoor Environments

Amauri B. Camargo, Yisha Liu, Guojian He, Yan Zhuang
{"title":"Mobile Robot Autonomous Exploration and Navigation in Large-scale Indoor Environments","authors":"Amauri B. Camargo, Yisha Liu, Guojian He, Yan Zhuang","doi":"10.1109/ICICIP47338.2019.9012209","DOIUrl":null,"url":null,"abstract":"This work is intended to study the stages of exploring, localization and mapping of autonomous mobile robots and vehicles. In addition to the use of integrated and standard software, ROS has the possibility of creating small map data files recorded with the data provided by 2D Light Detection And Ranging (LiDAR) sensors. The low data density favours the increased efficiency during data processing. The metric maps register just enough information to create the topological nodes and edges in a relational map. Extensive experiments in both simulated environments and real-world applications show the effectiveness of the proposed method.","PeriodicalId":431872,"journal":{"name":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP47338.2019.9012209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This work is intended to study the stages of exploring, localization and mapping of autonomous mobile robots and vehicles. In addition to the use of integrated and standard software, ROS has the possibility of creating small map data files recorded with the data provided by 2D Light Detection And Ranging (LiDAR) sensors. The low data density favours the increased efficiency during data processing. The metric maps register just enough information to create the topological nodes and edges in a relational map. Extensive experiments in both simulated environments and real-world applications show the effectiveness of the proposed method.
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
大型室内环境下移动机器人自主探索与导航
本工作旨在研究自主移动机器人和车辆的探索、定位和映射阶段。除了使用集成的标准软件外,ROS还可以创建小型地图数据文件,这些文件记录了2D光探测和测距(LiDAR)传感器提供的数据。低数据密度有利于提高数据处理效率。度量映射注册了足够的信息来创建关系映射中的拓扑节点和边。在模拟环境和实际应用中的大量实验表明了该方法的有效性。
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
Mobile Robot Autonomous Exploration and Navigation in Large-scale Indoor Environments Cross Spectral-Spatial Convolutional Network for Hyperspectral Image Classification Sparse Coding with Outliers A Novel Fuzzy Logic Control on the FVVT Lift of Internal Combustion Engine Adaptive Fuzzy Compensation Control of MIMO Stochastic Nonlinear Systems with Input Hysteresis
×
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