{"title":"Review on LiDAR-based SLAM Techniques","authors":"Leyao Huang","doi":"10.1109/CONF-SPML54095.2021.00040","DOIUrl":null,"url":null,"abstract":"LiDAR-based Simultaneous Localization and Mapping (LiDAR-SLAM) uses the LiDAR sensor to localize itself by observing environmental features and incrementally build the map of the surrounding environment. In this way, the purpose of simultaneous localization and mapping in the unknown environment can be achieved. Localization and mapping with high robustness, high accuracy, and high practicability is a complex and hot issue in recent years. This paper will briefly introduce the information background, classification and development history of LiDAR-SLAM. We will also summarize the common frameworks of LiDAR-SLAM and the function of core modules in the existing LiDAR-SLAM. Additionally, the state-of-the-art multi-sensor fusion-based LiDAR-SLAM techniques are investigated, and the future development trend of LiDAR-SLAM is discussed.","PeriodicalId":415094,"journal":{"name":"2021 International Conference on Signal Processing and Machine Learning (CONF-SPML)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Signal Processing and Machine Learning (CONF-SPML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONF-SPML54095.2021.00040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

Abstract

LiDAR-based Simultaneous Localization and Mapping (LiDAR-SLAM) uses the LiDAR sensor to localize itself by observing environmental features and incrementally build the map of the surrounding environment. In this way, the purpose of simultaneous localization and mapping in the unknown environment can be achieved. Localization and mapping with high robustness, high accuracy, and high practicability is a complex and hot issue in recent years. This paper will briefly introduce the information background, classification and development history of LiDAR-SLAM. We will also summarize the common frameworks of LiDAR-SLAM and the function of core modules in the existing LiDAR-SLAM. Additionally, the state-of-the-art multi-sensor fusion-based LiDAR-SLAM techniques are investigated, and the future development trend of LiDAR-SLAM is discussed.
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基于激光雷达的SLAM技术综述
基于激光雷达的同步定位和测绘(LiDAR- slam)利用激光雷达传感器通过观察环境特征来定位自身,并逐步构建周围环境的地图。这样就可以达到在未知环境中同时定位和映射的目的。高鲁棒性、高精度、高实用性的定位与制图是近年来一个复杂而又热门的问题。本文将简要介绍激光雷达slam的信息背景、分类和发展历史。我们还将总结LiDAR-SLAM的常见框架以及现有LiDAR-SLAM中核心模块的功能。此外,对基于多传感器融合的激光雷达slam技术进行了研究,并对激光雷达slam的未来发展趋势进行了讨论。
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