激光雷达同步定位与建图研究综述

doi:10.3969/j.issn.0255-8297.2026.04.001

Abstract

Abstract: The development of light detection and ranging(LiDAR) simultaneous localization and mapping(SLAM) technology over the past decade was systematically reviewed.First, a general mathematical definition of the SLAM problem was provided to establish a unified analytical framework. Subsequently, the related research was categorized into two main categories according to the number of platforms: single-platform LiDAR SLAM and multi-platform collaborative LiDAR SLAM. In the single-platform section, the multi-sensor fusion methods centered on LiDAR were emphatically summarized; in the multi-platform section, the currently mature collaborative SLAM systems and their key characteristics were outlined. Meanwhile, the challenges and development opportunities faced by LiDAR SLAM in complex scenes, degraded environments, multi-modal data sources, and multiplatform collaboration were discussed. Finally, combined with current research hotspots,the future technical evolution trends of LiDAR SLAM were prospected. The main application forms of deep learning in LiDAR SLAM were analyzed, and the potential value of emerging map representations(such as neural radiance fields and three-dimensional Gaussian splatting) in mapping quality and representation capability was outlined.

Key words: simultaneous localization and mapping(SLAM), light detection and ranging(LiDAR), multisource data fusion, multi-platform collaboration, visual localization and navigation

CLC Number:

TP391.4

DUAN Xuzhe, ZHONG Ruofei, LI Jian, FU Jing, ZHAO Pengcheng, LI Jiayuan, AI Mingyao, HU Qingwu. Review of LiDAR Simultaneous Localization and Mapping[J]. Journal of Applied Sciences, 2026, 44(4): 515-536.

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URL: https://www.jas.shu.edu.cn/EN/10.3969/j.issn.0255-8297.2026.04.001

https://www.jas.shu.edu.cn/EN/Y2026/V44/I4/515

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Review of LiDAR Simultaneous Localization and Mapping

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