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Introduction

本仓库是 LVI-SAM 的粗略中文注释。

Done

TODO

Acknowledgements


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.

<p align='center'> <img src="./doc/demo.gif" alt="drawing" width="800"/> </p>

Dependency


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

<p align='center'> <img src="./doc/sensor.jpeg" alt="drawing" width="600"/> </p>

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.

<p align='center'> <img src="./doc/jackal-earth.png" alt="drawing" width="286.5"/> <img src="./doc/handheld-earth.png" alt="drawing" width="328"/> </p>

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 

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={to-be-added},
  year={2021},
  organization={IEEE}
}

Acknowledgement