hyye / Lio Mapping
Licence: gpl-3.0
Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)
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LIO-mapping
A Tightly Coupled 3D Lidar and Inertial Odometry and Mapping Approach
Authors: Haoyang Ye, Yuying Chen, and Ming Liu from RAM-LAB.
[Paper], [Project], [Bib]. ICRA 2019.
Table of Contents
Demo Results
Video: [More indoor and outdoor tests].
Prerequisites
See Dockerfile as a reference:
- ROS with Ubuntu 18.04 or Ubuntu 16.04.
- Ceres-solver.
- PCL, the default version accompanying by ROS.
- OpenCV, the default version accompanying by ROS.
Build
-
git clone [email protected]:hyye/lio-mapping.gitinto thesrcfolder of your catkin workspace. -
catkin build -DCMAKE_BUILD_TYPE=Release lioorcatkin_make -DCMAKE_BUILD_TYPE=Release.
Examples
Some sample data.
-
source devel/setup.zsh, orsetup.bashif your preferbash. -
roslaunch lio test_indoor.launch &. -
roslaunch lio map_4D_indoor.launch &. -
rosbag play fast1.bag.
Docker
Try it out using docker:
- Run
docker/build_docker.sh. - Run
docker/run_docker.sh. - Run
rosbag play fast1.bag, in your host machine or in the running container.
Note: Visualization (rviz) can run in the running container with nvidia-docker. The Dockerfile is compatible with nvidia-docker 2.0; 1.Dockerfile with nvidia-docker 1.0.
Credits
The feature extraction, lidar-only odometry and baseline implemented were heavily derived or taken from the original LOAM and its modified version (the point_processor in our project), and one of the initialization methods and the optimization pipeline from VINS-mono. The copyright headers are retained for the relevant files.
Licence
The source code is released under GPL-3.0.
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