A Comparison of LiDAR Odometry and Mapping Techniques

被引:3
|
作者
Murcia, Harold F. [1 ]
Rubio, Cristian F. [1 ]
机构
[1] Univ Ibague, Fac Ingn, Res Grp D TEC, Carrera 22 Calle 67, Ibague 730002, Colombia
来源
2021 IEEE 5TH COLOMBIAN CONFERENCE ON AUTOMATIC CONTROL (CCAC): TECHNOLOGICAL ADVANCES FOR A SUSTAINABLE REGIONAL DEVELOPMENT | 2021年
关键词
Simultaneous localization and mapping; LiDAR; ROS; KITTI database; real-time pose estimation;
D O I
10.1109/CCAC51819.2021.9633299
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Light detection and ranging LiDAR systems on-board mobile platforms are in rapid advancement for real-time mapping applications. Modern 3D laser scanners have a high data rate which, coupled with the complexity of their processing methods, makes simultaneous online localization and mapping (SLAM) a computational challenge. Different 3D LiDAR SLAM algorithms have emerged in recent years, most notably LiDAR Odometry and Mapping and its derivatives. This paper performs the implementation of A-LOAM, ISCLOAM, and LeGO-LOAM algorithms and a respective comparison with the total sequences of the KITTI database which includes different environments and routes from a Velodyne HDL-64E sensor. The results evaluate the performance of the methods on computational cost, absolute error, and relative error. Our code implementation is available online. https://github.com/HaroldMurcia/LOaM- comparison.
引用
收藏
页码:192 / 197
页数:6
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