Skip to content

LIO_SAM#

What is LIO_SAM?#

  • A framework that achieves highly accurate, real-time mobile robot trajectory estimation and map-building. It formulates lidar-inertial odometry atop a factor graph, allowing a multitude of relative and absolute measurements, including loop closures, to be incorporated from different sources as factors into the system

Repository Information#

https://github.com/TixiaoShan/LIO-SAM

Required Sensors#

  • LIDAR [Livox, Velodyne, Ouster]
  • IMU [9-AXIS]
  • GPS [OPTIONAL]

drawing

ROS Compatibility#

Dependencies#

  • ROS
  • PCL

  • GTSAM (Georgia Tech Smoothing and Mapping library)

    bash sudo add-apt-repository ppa:borglab/gtsam-release-4.0 sudo apt install libgtsam-dev libgtsam-unstable-dev

bash sudo apt-get install -y ros-melodic-navigation sudo apt-get install -y ros-melodic-robot-localization sudo apt-get install -y ros-melodic-robot-state-publisher

Build & Run#

1) Build#

bash mkdir -p ~/catkin_lio_sam/src cd ~/catkin_lio_sam/src git clone https://github.com/TixiaoShan/LIO-SAM.git cd .. catkin_make source devel/setup.bash

2) Set parameters#

  • Set topics and sensor settings on lio_sam/config/params.yaml

3) Run#

```bash # Run the Launch File roslaunch lio_sam run.launch

# Play bag file in the other terminal
  rosbag play xxx.bag --clock

```

Example Result#

drawing

Paper#

Thank you for citing LIO-SAM (IROS-2020) if you use any of this code.

bash @inproceedings{liosam2020shan, title={LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping}, author={Shan, Tixiao and Englot, Brendan and Meyers, Drew and Wang, Wei and Ratti, Carlo and Rus Daniela}, booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={5135-5142}, year={2020}, organization={IEEE} }

Part of the code is adapted from LeGO-LOAM.

bash @inproceedings{legoloam2018shan, title={LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain}, author={Shan, Tixiao and Englot, Brendan}, booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={4758-4765}, year={2018}, organization={IEEE} }

Acknowledgements#

  • LIO-SAM is based on LOAM (J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time).