1. Prerequisites and Installation

1.1 Ubuntu and ROS

Tested on Ubuntu 18.04 (with ROS Melodic and OpenCV3) and on Ubuntu 20.04(with ROS Noetic and OpenCV4).

1.2 OpenCV

This package requires OpenCV 3/4 and some features of C++11.

1.3 Eigen, Ceres, and PCL

This package requires Eigen 3.3.7, Ceres 1.14,Sophus and PCL 1.10 or 1.11. You need to download they in your thirdparty folder, and then:

sudo apt-get update
sudo apt-get install -y cmake libgoogle-glog-dev libgflags-dev libatlas-base-dev libsuitesparse-dev 
cd thirdparty/eigen
mkdir -p build && cd build
cmake ..
sudo make install
cd ../../ceres-solver
mkdir -p build && cd build
cmake ..
make -j$(nproc) 
sudo make install
sudo apt-get install -y libflann-dev libvtk6-dev libboost-all-dev ros-noetic-pcl-ros (for ubuntu20.04) libfmt-dev
cd ../../pcl
mkdir -p build && cd build
cmake ..
make -j$(nproc)
sudo make install
cd ../../Sophus
mkdir -p build && cd build
cmake ..
make -j$(nproc) 
sudo make install

1.4 Gnss_comm

This package also requires gnss_comm for ROS message definitions and some utility functions.

1.5 Configure gcc (For Ubuntu 20.04)

sudo apt-get install g++-8
sudo apt-get install gcc-8
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 20
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-8 20

1.6 Build Ground-Fusion

After install all 3rd parties：

mkdir -p ~/Groundfusion_ws/src
cd ~/Groundfusion_ws/src
git clone https://github.com/HKUST-Aerial-Robotics/gnss_comm
git clone https://github.com/SJTU-ViSYS/Ground-Fusion
cd ../..
catkin_make -j12

2. Run examples

2.1 Ground-challenge dataset

Download at Ground-challenge and give a star.

# [launch] open a terminal and type:
source devel/setup.bash
roslaunch vins groundfusion.launch

# [run localization] open another terminal:
source devel/setup.bash
rosrun vins vins_node src/Ground-Fusion/config/realsense/groundchallenge.yaml

# [dense map]open third terminal:
source devel/setup.bash
rosrun dense_map dense_map_node src/Ground-Fusion/config/realsense/groundchallenge.yaml

2.2 M2DGR-P dataset

Download at M2DGR-P and give a star.

# [launch] open a terminal and type:
source devel/setup.bash
roslaunch vins groundfusion.launch

# [run localization] open another terminal:
source devel/setup.bash
rosrun vins vins_node src/Ground-Fusion/config/realsense/m2dgrp.yaml

# [dense map]open third terminal:
source devel/setup.bash
rosrun dense_map dense_map_node src/Ground-Fusion/config/realsense/m2dgrp.yaml

3. Acknowledgement

Thanks support from National Key R&D Program (2022YFB3903802), NSFC(62073214), and Midea Group. This project is based on GVINS, and has borrowed some codes from open-source projects VIW-Fusion and VINS-RGBD, thanks for your great contribution!

4. License

The source code of Ground-Fusion is released under GPLv3 license. Do not use this project for any commercial purpose unless permitted by authors. Yin Jie is still working on improving the system. For any technical issues, please contact him at 1195391308@qq.com.

If you use this work in an academic work, please cite:

@article{yin2021m2dgr,
  title={M2dgr: A multi-sensor and multi-scenario slam dataset for ground robots},
  author={Yin, Jie and Li, Ang and Li, Tao and Yu, Wenxian and Zou, Danping},
  journal={IEEE Robotics and Automation Letters},
  volume={7},
  number={2},
  pages={2266--2273},
  year={2021},
  publisher={IEEE}
}
@article{yin2024ground,
  title={Ground-Fusion: A Low-cost Ground SLAM System Robust to Corner Cases},
  author={Yin, Jie and Li, Ang and Xi, Wei and Yu, Wenxian and Zou, Danping},
  journal={arXiv preprint arXiv:2402.14308},
  year={2024}
}