Run on ubuntu 20.04 + noetic
-
gtsam : 4.1rc
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Eigen : 3.3.7
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gflags : 2.2.2
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Ceres : 1.14.0
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Boost : 1.71.0
sudo apt-get install -y ros-noetic-navigation ros-noetic-robot-localization ros-noetic-robot-state-publisher
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.
- ROS (Tested with kinetic and melodic)
- gtsam (Georgia Tech Smoothing and Mapping library)
wget -O ~/Downloads/gtsam.zip https://github.com/borglab/gtsam/archive/4.0.2.zip cd ~/Downloads/ && unzip gtsam.zip -d ~/Downloads/ cd ~/Downloads/gtsam-4.0.2/ mkdir build && cd build cmake -DGTSAM_BUILD_WITH_MARCH_NATIVE=OFF .. sudo make install -j4
- 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
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
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.
- Configure parameters:
Configure sensor parameters in the .yaml files in the ```config``` folder.
- Run the launch file:
roslaunch lvi_sam run.launch
- Play existing bag files:
rosbag play handheld.bag
ffmpeg \
-i simplescreenrecorder-2021-04-29_23.21.12_MOTION.mp4 \
-r 30 \
-vf "scale=512:-1,split[s0][s1];[s0]palettegen[p];[s1][p]paletteuse" \
-ss 00:00:00 -to 00:01:00 \
LVI_SAM.gif
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}
}