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激光即时定位与建图算法综述
引用本文:刘志成,王华龙,马兴录. 激光即时定位与建图算法综述[J]. 计算机测量与控制, 2024, 32(3): 1-8
作者姓名:刘志成  王华龙  马兴录
作者单位:青岛科技大学,,青岛科技大学
摘    要:激光即时定位与建图(SLAM)算法是一种在机器人导航和自主驾驶领域被广泛应用的技术;该技术可以利用激光雷达扫描环境并提取特征点,实现机器人的自主定位和地图构建;针对机器人激光SLAM技术进行研究,分析了各个激光SLAM算法的基本原理,并且对主流SLAM算法进行了现状总结;根据激光SLAM算法的特点以及原理不同,将激光SLAM算法分为:基于滤波器的算法、基于图优化的算法、基于配准的算法、基于学习的算法等;基于上述分类,详细介绍了每个算法的优缺点,并且分述了近两年的主要研究成果;针对移动机器人激光SLAM算法研究现状,对激光SLAM算法的未来发展进行了展望。

关 键 词:即时定位与建图  特征提取  匹配  优化  未来发展
收稿时间:2023-04-17
修稿时间:2023-05-16

Summary of the Laser SLAM Algorithms
马兴录. Summary of the Laser SLAM Algorithms[J]. Computer Measurement & Control, 2024, 32(3): 1-8
Authors:马兴录
Abstract:Laser SLAM (Simultaneous Localization and Mapping) is a widely used technology in the field of robot navigation and autonomous driving; The technique can use lidar to scan the environment and extract feature points, Realize the autonomous positioning and map construction of the robot; Research on the robotic laser SLAM technology, Analyzed the underlying principles of the various laser SLAM algorithms, And the mainstream SLAM algorithm is summarized; According to the characteristics and principles of the laser SLAM algorithm, The laser SLAM algorithm is divided into: filter based algorithm, graph optimization based algorithm, registration based algorithm, learning based algorithm and other algorithms; Based on the above classification, Details of the advantages and disadvantages of each algorithm, And described the main research results of the past two years; For the research status of laser SLAM algorithm in mobile robot, We discuss the future development of the laser SLAM algorithm.
Keywords:Laser SLAM   feature extraction   matching   optimization   future development
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