计算机工程与应用2024，Vol.60Issue(1)：1-14,14.DOI:10.3778/j.issn.1002-8331.2308-0455
激光雷达SLAM算法综述
Review of SLAM Based on Lidar
摘要
Abstract
Simultaneous localization and mapping(SLAM)is a crucial technology for autonomous mobile robots and au-tonomous driving systems,with a laser scanner(also known as lidar)playing a vital role as a supporting sensor for SLAM algorithms.This article provides a comprehensive review of lidar-based SLAM algorithms.Firstly,it introduces the overall framework of lidar-based SLAM,providing detailed explanations of the functions of the front-end odometry,back-end optimization,loop closure detection,and map building modules,along with a summary of the algorithms used.Secondly,it presents descriptions and summaries of representative open-source algorithms in a sequential order of 2D to 3D and single-sensor to multi-sensor fusion.Additionally,it discusses commonly used open-source datasets,precision evaluation metrics,and evaluation tools.Lastly,it offers an outlook on the development trends of lidar-based SLAM technology from four dimensions:deep learning,multi-sensor fusion,multi-robot collaboration,and robustness research.关键词
即时定位与地图构建/激光雷达/惯性/多传感器融合Key words
simultaneous localization and mapping/lidar/inertial/multi-sensor fusion分类
信息技术与安全科学引用本文复制引用
刘铭哲,徐光辉,唐堂,钱晓健,耿明..激光雷达SLAM算法综述[J].计算机工程与应用,2024,60(1):1-14,14.基金项目
国家自然科学基金(62071486). （62071486）
