Loam_livox: A robust LiDAR Odometry and Mapping (LOAM) package for Livox-LiDAR
Abstract
LiDAR odometry and mapping (LOAM) has been playing an important role in autonomous vehicles, due to its ability to simultaneously localize the robot’s pose and build high-precision, high-resolution maps of the surrounding environment. This enables autonomous navigation and safe path planning of autonomous vehicles. In this paper, we present a robust, real-time LOAM algorithm for LiDARs with small FoV and irregular samplings. By taking effort on both front-end and back-end, we address several fundamental challenges arising from such LiDARs, and achieve better performance in both precision and efficiency compared to existing baselines. To share our findings and to make contributions to the community, we open source our codes on Github: https://github.com/hku-mars/loam_livox
1. Introduction
Loam-Livox is a robust, low drift, and real time odometry and mapping package for Livox LiDARs, significant low cost and high performance LiDARs that are designed for massive industrials uses. Our package address many key issues: feature extraction and selection in a very limited FOV, robust outliers rejection, moving objects filtering, and motion distortion compensation. In addition, we also integrate other features like parallelable pipeline, point cloud management using cells and maps, loop closure, utilities for maps saving and reload, etc. To know more about the details, please refer to our related paper:)
Our related paper: our related papers are now available on arxiv:
- Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV
- A fast, complete, point cloud based loop closure for LiDAR odometry and mapping
Our related video: our related videos are now available on YouTube (click below images to open):
Our mapping results reconstructed with Livox-mid40 LiDAR:
Jiarong Lin
Ph.D. candidate in Robotics🤖
My research interests include Simultaneous localization and mapping (SLAM), Multi-sensor (i.e., LiDAR-Inertial-Visual) Fusion, and 3D reconstruction. My popular works include: R3LIVE, FAST-LIO, loam-livox, R2LIVE, and ImMesh🆕.