S4OM: A Real-Time Lidar Odometry and Mapping System Based on Super4PCS Scan-Matching

Yi He, Bo Zhou, Xiaomao Li, K. Qian, Xudong Ma
{"title":"S4OM: A Real-Time Lidar Odometry and Mapping System Based on Super4PCS Scan-Matching","authors":"Yi He, Bo Zhou, Xiaomao Li, K. Qian, Xudong Ma","doi":"10.1109/ROBIO.2018.8665138","DOIUrl":null,"url":null,"abstract":"For long-distance accurate localization and mapping of mobile robots in outdoor environment, a new real-time lidar odometry and mapping system(S40M) is proposed in this paper, it divides the complex problem of simultaneous localization and mapping into localization problem and mapping problem, and then uses two algorithms to deal with them. The localization algorithm outputs the location information at a high frequency, it achieves coarse-to-fine matching by combination the Super4PCS algorithm with ICP algorithm. The mapping algorithm corrects the location information and builds map at a low frequency, it uses NDT matching method to match the current keyframe with the local map. The S4OM system formed by the above two algorithms can achieve good balance of instantaneity and accuracy without GPS or other inertial navigation aids, and has good robustness and environmental adaptability, in the case of large displacements and low-overlap of point clouds it can still achieve good results. The method in this paper has been tested with a large number of datasets and has been submitted for evaluation on KITTI odometry benchmark. The results indicate the effectiveness and feasibility of the method.","PeriodicalId":417415,"journal":{"name":"2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"586 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2018.8665138","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

For long-distance accurate localization and mapping of mobile robots in outdoor environment, a new real-time lidar odometry and mapping system(S40M) is proposed in this paper, it divides the complex problem of simultaneous localization and mapping into localization problem and mapping problem, and then uses two algorithms to deal with them. The localization algorithm outputs the location information at a high frequency, it achieves coarse-to-fine matching by combination the Super4PCS algorithm with ICP algorithm. The mapping algorithm corrects the location information and builds map at a low frequency, it uses NDT matching method to match the current keyframe with the local map. The S4OM system formed by the above two algorithms can achieve good balance of instantaneity and accuracy without GPS or other inertial navigation aids, and has good robustness and environmental adaptability, in the case of large displacements and low-overlap of point clouds it can still achieve good results. The method in this paper has been tested with a large number of datasets and has been submitted for evaluation on KITTI odometry benchmark. The results indicate the effectiveness and feasibility of the 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
S4OM:基于Super4PCS扫描匹配的实时激光雷达测程与制图系统
针对户外环境下移动机器人的远程精确定位与测绘,本文提出了一种新的实时激光雷达测程与测绘系统(S40M),该系统将同时定位与测绘的复杂问题划分为定位问题和测绘问题,并采用两种算法进行处理。定位算法以高频率输出位置信息,将Super4PCS算法与ICP算法相结合,实现粗精匹配。该算法对位置信息进行校正,在低频率下构建地图,采用无损检测匹配方法将当前关键帧与局部地图进行匹配。由上述两种算法组成的S4OM系统在不使用GPS或其他惯导辅助的情况下,能够很好地实现实时性和精度的平衡,具有良好的鲁棒性和环境适应性,在点云位移大、重叠度低的情况下仍能取得良好的效果。本文方法已在大量数据集上进行了测试,并提交KITTI odometry benchmark进行评估。结果表明了该方法的有效性和可行性。
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
Design, Development and Experimental Evaluation of a Thrust Vectoring Vortex Climbing Robot A Novel Transfer Metric Learning Approach Based on Multi-Group An Efficient L-Shape Fitting Method for Vehicle Pose Detection with 2D LiDAR S4OM: A Real-Time Lidar Odometry and Mapping System Based on Super4PCS Scan-Matching Research on High Precision Micro-assembly Technology for Automated MEMS Thermopile Chip Die Bonding Process
×
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