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作 者:陈春旭 漆钰晖 朱一帆 裴凌[1] 徐昌庆[1] CHEN Chun xu;QI Yu hui;ZHU Yi fan;PEI Ling;XU Chang qing(Shanghai Jiao Tong University,Shanghai Key I.aboratory of Navigation and I.ocation based Services Shanghai 2002,10,China;School of Information Engineering,Nanchang University,Nanchang 330031,China)
机构地区:[1]上海交通大学上海市北斗导航与位置服务重点实验室,上海200240 [2]南昌大学信息工程学院,南昌330031
出 处:《导航定位与授时》2018年第5期67-72,共6页Navigation Positioning and Timing
基 金:上海市科委重点项目(17DZ1100803);上海市科委项目(17511106300)
摘 要:基于3D激光雷达传感器的同时定位与地图构建(SLAM)技术,是机器人自主定位解决方案的核心。三维点云配准环节是3D激光雷达SLAM实现自身定位与地图构建的关键所在。重点围绕ICP算法在三维激光点云配准中的应用开展研究,首先对ICP算法的配准原理及其求解过程进行详细分析,其次介绍了ICP的影响因素并提出了相应的评价指标,最后测试了ICP算法在不同角度和位移下的配准效果并进行了实验分析。Simultaneous I.ocalization and Mapping (SLAM) technology based on multi layer LiDAR sensor is the core solution of the robot autonomous localization. Registration on 3D laser point clouds is the key to realize self positioning and map building. This paper focuses on the ap plication of ICP (Iteration closest point) algorithm in 3D laser point cloud registration. Firstly, the registration principle and the solution process of the ICP algorithm is introduced. Secondly, the influencing factors and the corresponding evaluation indexes of ICP are proposed. Finally, the effects of the ICP algorithm at different angles and displacements are tested and the experimental analysis is given.
分 类 号:TN249[电子电信—物理电子学]
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