Research on 2D-SLAM of Indoor Mobile Robot based on Laser Radar

D. Shen, Yuhang Xu, Yakun Huang
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引用次数: 7

Abstract

Nowadays simultaneous localization and mapping (SLAM) of indoor mobile robots in unknown environment is very popular in robot research. Laser radar is widely used in SLAM research. In this paper, three 2D-SLAM algorithms based on laser radar in the robot operating system (ROS) were compared and evaluated, namely Gmapping, Hector-SLAM and Cartographer. It firstly built a mobile robot experimental platform based on ROS in the real environment. In order to reflect the ability of building maps by three SLAM algorithms, experiments were carried out in simple corridor and laboratory with many obstacles respectively. Meanwhile, ten points in the real environment were selected to measure the distance on maps and the real distance obtained by laser range finder for comparison and error analysis. Finally, according to the experimental results, strengths and weaknesses of each SLAM algorithm were discussed. It is concluded that Gmapping has the highest mapping accuracy in simple small scene environment while Hector-slam is more suitable for a long corridor environment, and Cartographer has more advantages in complex environment.
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基于激光雷达的室内移动机器人二维slam研究
目前,室内移动机器人在未知环境下的同步定位与绘图是机器人研究的热点。激光雷达在SLAM研究中有着广泛的应用。本文对机器人操作系统(ROS)中基于激光雷达的三种2D-SLAM算法gapping、Hector-SLAM和Cartographer进行了比较和评价。首先在真实环境中搭建了基于ROS的移动机器人实验平台。为了体现三种SLAM算法构建地图的能力,分别在简单的走廊和障碍物较多的实验室进行了实验。同时,选取真实环境中的10个点测量地图上的距离与激光测距仪获得的实际距离进行对比和误差分析。最后,根据实验结果,讨论了各种SLAM算法的优缺点。结果表明,gmap在简单的小场景环境中具有最高的制图精度,而Hector-slam更适合于长走廊环境,而Cartographer在复杂环境中更具优势。
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