SLAM算法建图对比研究
Comparative Study on SLAM Algorithm for Mapping
李少伟 1钟勇 1杨华山 1邱煌乐 1李方舟1
作者信息
- 1. 福建省汽车与电子电驱动重点实验室(福建理工大学),福建 福州 350118
- 折叠
摘要
本论文旨在探讨在无人驾驶与机器人行业发展火热的背景下,实现准确的定位与导航,对汽车与机器人所处环境进行高精度建模的重要性.激光SLAM作为目前最稳定、最主流的定位导航方法,在此领域得到广泛应用.本研究使用Gmapping算法、Hector算法、Cartographr算法,在一辆搭载 2D激光雷达的智能小车上,对室内环境进行建模,并对三种算法所建地图进行对比分析.实验结果表明在室内环境下,Cartographr算法所建地图的精度最高,建图效果优于Gmapping算法和 Hector算法.
Abstract
This paper aims to explore the importance of achieving accurate positioning and navigation,as well as high-precision modeling of the environment in which cars and robots operate,in the context of the booming development of the autonomous driving and robotics industry.Laser SLAM,as the most stable and mainstream positioning and navigation method,has been widely used in this field.This study uses the Gmapping algorithm,Hector algorithm and Cartographr algorithm to model the indoor environment on an intelligent car equipped with a 2 D laser radar,and compares and analyzes the maps built by the three algorithms.The experimental results show that the cartography algorithm has the highest accuracy in the indoor environment,and the mapping effect is better than that of the Gmapping algorithm and Hector algorithm.
关键词
激光SLAM/Cartographr算法/Gmapping算法/建图Key words
Laser SLAM/Cartographr algorithm/Gmapping algorithm/Mapping引用本文复制引用
出版年
2024
NETL
NSTL
万方数据