GVINS: Tightly Coupled GNSS-Visual-Inertial Fusion for Smooth and Consistent State Estimation. paper link
Authors: Shaozu CAO, Xiuyuan LU and Shaojie SHEN
GVINS is a non-linear optimization based system that tightly fuses GNSS raw measurements with visual and inertial information for real-time and drift-free state estimation. By incorporating GNSS pseudorange and Doppler shift measurements, GVINS is capable to provide smooth and consistent 6-DoF global localization in complex environment. The system framework and VIO part are adapted from VINS-Mono. Our system contains the following features:
- global 6-DoF estimation in ECEF frame;
- multi-constellation support (GPS, GLONASS, Galileo, BeiDou);
- online local-ENU frame alignment;
- global pose recovery in GNSS-unfriendly or even GNSS-denied area.
1.1 C++11 Compiler
This package requires some features of C++11.
This package is developed under ROS Kinetic environment.
Our code uses Eigen 3.3.3 for matrix manipulation.
We use ceres 1.12.0 to solve the non-linear optimization problem.
2. Build GVINS
Clone the repository to your catkin workspace (for example
cd ~/catkin_ws/src/ git clone https://github.com/HKUST-Aerial-Robotics/GVINS.git
Then build the package with:
cd ~/catkin_ws/ catkin_make source ~/catkin_ws/devel/setup.bash
If you encounter any problem during the building of GVINS, we recommend you to try docker first.
To simplify the building process, we add docker in our code. Docker is like a sandbox so it can isolate our code from your local environment. To run with docker, first make sure ros and docker are installed on your machine. Then add your account to
docker group by
sudo usermod -aG docker $USER. Logout and re-login to avoid the Permission denied error, then type:
cd ~/catkin_ws/src/GVINS/docker make build
The docker image
gvins:latest should be successfully built after a while. Then you can run GVINS with:
./run.sh visensor_f9p.launch). Open another terminal and play your rosbag file, then you should be able to see the result. If you modify the code, simply re-run
./run.sh LAUNCH_FILE to update.
4. Run GVINS with our dataset
Download our GVINS-Dataset and launch GVINS via:
roslaunch gvins visensor_f9p.launch
Open another terminal and launch the rviz by:
rviz -d ~/catkin_ws/src/GVINS/config/gvins_rviz_config.rviz
Then play the bag:
rosbag play sports_field.bag
The source code is released under GPLv3 license.