LVI SAM Save

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

Project README

LVI-SAM

This repository contains code for a lidar-visual-inertial odometry and mapping system, which combines the advantages of LIO-SAM and Vins-Mono at a system level.

drawing


Dependency

  • ROS (Tested with kinetic and melodic)
  • gtsam (Georgia Tech Smoothing and Mapping library)
    sudo add-apt-repository ppa:borglab/gtsam-release-4.0
    sudo apt install libgtsam-dev libgtsam-unstable-dev
    
  • Ceres (C++ library for modeling and solving large, complicated optimization problems)
    sudo apt-get install -y libgoogle-glog-dev
    sudo apt-get install -y libatlas-base-dev
    wget -O ~/Downloads/ceres.zip https://github.com/ceres-solver/ceres-solver/archive/1.14.0.zip
    cd ~/Downloads/ && unzip ceres.zip -d ~/Downloads/
    cd ~/Downloads/ceres-solver-1.14.0
    mkdir ceres-bin && cd ceres-bin
    cmake ..
    sudo make install -j4
    

Getting start with Docker

When you use Docker, you could solve the dependency at once.
For more information, you can check docker_start.md.


Compile

You can use the following commands to download and compile the package.

cd ~/catkin_ws/src
git clone https://github.com/TixiaoShan/LVI-SAM.git
cd ..
catkin_make

Datasets

drawing

The datasets used in the paper can be downloaded from Google Drive. The data-gathering sensor suite includes: Velodyne VLP-16 lidar, FLIR BFS-U3-04S2M-CS camera, MicroStrain 3DM-GX5-25 IMU, and Reach RS+ GPS.

https://drive.google.com/drive/folders/1q2NZnsgNmezFemoxhHnrDnp1JV_bqrgV?usp=sharing

Note that the images in the provided bag files are in compressed format. So a decompression command is added at the last line of launch/module_sam.launch. If your own bag records the raw image data, please comment this line out.

drawing drawing


Run the package

  1. Configure parameters:
Configure sensor parameters in the .yaml files in the ```config``` folder.
  1. Run the launch file:
roslaunch lvi_sam run.launch
  1. Play existing bag files:
rosbag play handheld.bag 


TODO

  • Update graph optimization using all three factors in imuPreintegration.cpp, simplify mapOptimization.cpp, increase system stability

Paper

Thank you for citing our paper if you use any of this code or datasets.

@inproceedings{lvisam2021shan,
  title={LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping},
  author={Shan, Tixiao and Englot, Brendan and Ratti, Carlo and Rus Daniela},
  booktitle={IEEE International Conference on Robotics and Automation (ICRA)},
  pages={5692-5698},
  year={2021},
  organization={IEEE}
}

Acknowledgement

  • The visual-inertial odometry module is adapted from Vins-Mono.
  • The lidar-inertial odometry module is adapted from LIO-SAM.
Open Source Agenda is not affiliated with "LVI SAM" Project. README Source: TixiaoShan/LVI-SAM
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