Research on 2D-SLAM of Indoor Mobile Robot based on Laser Radar
Dong Shen, Yuhang Xu, Yakun Huang
- 发表年份
- 2019
- 引用次数
- 12
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002