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移动机器人同步定位与建图技术综述
引用本文:任伟建,高强,康朝海,霍凤财,张志强.移动机器人同步定位与建图技术综述[J].计算机测量与控制,2022,30(2):1-10.
作者姓名:任伟建  高强  康朝海  霍凤财  张志强
作者单位:东北石油大学电气信息工程学院,黑龙江大庆 163318;黑龙江省网络化与智能控制重点实验室,黑龙江大庆163318
基金项目:国家自然科学基金资助项目(61933007,61873058),黑龙江省自然科学基金(F2018004,F2018005)
摘    要:同步定位与建图技术(SLAM)一直是移动机器人领域比较热门的研究方向,它可以给机器人提供强大的环境感知能力;传统的依靠外部位置参考来定位的方法如果无法获得时,移动机器人需要即时定位自身位置来构建增量式地图,因此SLAM技术也就应运而生;对激光SLAM和视觉SLAM的研究现状及最新标志性成果进行了介绍,重点对以相机与激光雷达融合、相机与IMU融合、激光雷达与IMU融合为代表的多传感器融合SLAM技术展开讨论、系统地梳理了几种融合方式的优势与不足,同时介绍了该领域的研究热点语义SLAM,最后讨论了SLAM技术在该领域未来的发展方向以及存在的挑战。

关 键 词:视觉SLAM  激光SLAM  多传感器融合SLAM  语义SLAM
收稿时间:2021/8/17 0:00:00
修稿时间:2021/9/9 0:00:00

Overview of Simultaneous Localization and Mapping Technology of Mobile Robots
REN Weijian,GAO Qiang,KANG Chaohai,HUO Fengcai,ZHANG Zhiqiang.Overview of Simultaneous Localization and Mapping Technology of Mobile Robots[J].Computer Measurement & Control,2022,30(2):1-10.
Authors:REN Weijian  GAO Qiang  KANG Chaohai  HUO Fengcai  ZHANG Zhiqiang
Affiliation:(Department of Electrical Information Engineering,Northeast Petroleum University,Daqing 163318,China;Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control,Daqing 163318,China)
Abstract:Simultaneous Localization and Mapping (SLAM) has always been a popular research direction in the field of mobile robots. It can provide robots with powerful environmental perception capabilities. If the traditional localization method relying on external location reference is not available, the mobile robot needs to locate its own position in time to build incremental maps. Therefore, SLAM technology comes into being. Introduced the current research status and the latest landmark achievements of laser SLAM and visual SLAM,and focus on discussing the multi-sensor fusion SLAM technology represented by camera and lidar fusion, camera and IMU fusion, and lidar and IMU fusion, and systematically sort out the advantages and disadvantages of several fusion methods. At the same time, the research hotspot of semantic SLAM in this field is introduced. Finally, the future development direction of SLAM technology in this field and the existing challenges are discussed.
Keywords:evaluation and analysis  Visual SLAM  Lidar SLAM  multi-sensor fusion SLAM  semantic SLAM
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