SaDVIO

This library provide a modular C++ framework dedicated on research about Visual Odometry (VO) and Visual Inertial Odometry (VIO). It also contains implementations of research works done at ISAE such as: factor graph sparsification, traversability estimation with 3D mesh and non overlapping field of view VO. This version is compatible with the middleware ROS2.

Installation

Here are the dependencies:

• OpenCV for image processing
• CERES a non linear solver from google
• Eigen a linera algebra library
• yaml-cpp to parse config files

You can either run this code with ROS2, the famous robotic middleware, or without ROS2. For now it has been tested with Galactic and Humble. A few changes are needed for Jazzy but only in the ros folder.

ROS2 install

Once these are all installed, use the following commands to build:

cd ~/your_ws/src
git clone https://github.com/ISAE-PNX/SaDVIO.git
cd ..
colcon build --symlink-install --packages-select isae_slam_ros

Then launch the program with:

ros2 launch isae_slam_ros isae_slam.xml

You can then play a rosbag with the topics specified in the config files.

Classic install

Go in the cpp folder and build it

cd ~/your_ws/src
git clone https://github.com/ISAE-PNX/SaDVIO.git
cd SaDVIO/cpp
mkdir build
cd build
cmake ..
make

You can then run this executable, adding the folder of the config files and the folder of your dataset:

./isaeslam "/ur/path/SaDVIO/ros/config" "/ur/path/V1_01_easy/mav0"

Your dataset must be at the EUROC dataset format and you must edit properly the files in the config folder.

Docker install

We have included a docker installation of SaDVIO in the docker folder. Simply run the run.sh script to build and run the image. A sequence of the EUROC dataset is downloaded for a first try. To run it, do the following:

cd SaDVIO/cpp/build/
./isaeslam "/root/SaDVIO/ros/config" "/root/V1_01_easy/mav0/"

Disclaimer

A few functionnalities are currently being tested, their performances are not guaranteed and were not presented in any paper:

• The lines as features and landmarks
• The mono and monovio modes work decently

Please consider citing one of the related work if you use our system in your research:

@inproceedings{sparsifDebeunne,
  author={Debeunne, César and Vallvé, Joan and Torres, Alex and Vivet, Damien},
  booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems }, 
  title={Fast Bi-Monocular Visual Odometry Using Factor Graph Sparsification}, 
  year={2023},
  pages={10716-10722},
}

@inproceedings{debeunne2023non,
  title={Non-Recovering Field-of-View Imaging-Based SLAM for Lava Tubes Exploration},
  author={Debeunne, C{\'e}sar and Vivet, Damien and Torres, Alex},
  booktitle={17th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA)},
  year={2023}
}

@article{debeunne2024sadvio,
  title={SaDVIO: Sparsify and Densify VIO for UGV Traversability Estimation},
  author={Debeunne, C{\'e}sar and Torres, Alex and Vivet, Damien},
  journal={IEEE Robotics and Automation Letters},
  year={2024}
}