SuperVINS: A Real-Time Visual-Inertial SLAM Framework for Challenging Imaging Conditions

http://luohongkun.com/SuperVINS/

[PDF] [Code] [Pages]

The code is not yet fully open. The currently uploaded version in this repository is still in a basic stage and is being organized.

News

• 2024.10.6:add base code
• 2024.8.7:add demo.
• 2024.7.31:Publish a preprint(Journal in submission).Preprint: https://arxiv.org/abs/2407.21348

Demo

GIF

Video

If you want to watch the full demo video, please click the link

1 Brief Introduction

This project is improved based on VINS-Fusion. VINS-Fusion is a well-known SLAM framework. The original version of VINS-Fusion front-end uses traditional geometric feature points and then performs optical flow tracking. This project uses the feature point method, introduces SuperPoint feature points and feature descriptors, and uses the LightGlue network for feature matching. In the loopback part, the original VINS-Fusion extracts the brief descriptor and uses DBoW2 for loopback detection. This project uses DBoW3 and SuperPoint deep learning descriptors for loopback detection. Created a SLAM system based on deep learning.

2 Build Project

2.1 Ubuntu and ROS

Ubuntu 64-bit 20.04. ROS Noetic. ROS Installation

2.2 OpenCV

OpenCV4.2.0. OpenCV4.2.0

if you use Ubuntu 20.04, you can install it by:sudo apt-get install libopencv-dev

2.3 Ceres Solver

Follow Ceres Installation. Ceres 2.1.0.

2.4 ONNX RUNTIME

onnxruntime-linux-x64-gpu-1.16.3

2.5 install libraries to the specified path

If you want to install the third-party library in the specified path, you can follow the steps below

mkdir build
cd build
cmake -D CMAKE_INSTALL_PREFIX="/some/where/local"  ..
make -j4
make install

3 Create a ROS1 workspace

mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src/
catkin_init_workspace
cd ~/catkin_ws
catkin_make
echo "source ~/catkin_ws/devel/setup.bash" >> ~/.bash
source ~/.bashrc

4 How does it work?

4.1 Clone project

  cd ~/catkin_ws/src
  git clone https://github.com/luohongk/SuperVINS.git

4.2 Data download

You can download the specified data set yourself, or you can use download_data.sh to download the data set. The download method is as follows.

cd ~/catkin_ws/src/SuperVINS
chmod +x download_data.sh
./download_data.sh

4.3 Path change

Absolute paths are used in some places in the project. You need to simply change the path configuration according to your own computer path. The change method is as follows

• file:vins_estimator\CMakeLists.txt , supervins_loop_fusion\CMakeLists.txt , camera_models\CMakeLists.txt

change
set(ONNXRUNTIME_ROOTDIR "/home/lhk/Thirdparty/onnxruntime")
find_package(Ceres REQUIRED PATHS "/home/lhk/Thirdparty/Ceres")
to
set(ONNXRUNTIME_ROOTDIR "your onnxruntime path")
find_package(Ceres REQUIRED PATHS "you Ceres path")

• file:supervins_loop_fusion\src\pose_graph_node.cpp line 554

change
string vocabulary_file = "/home/lhk/catkin_ws/src/VINS_SPLG_BOW/loop_fusion/src/ThirdParty/Voc/superpoint.yml.gz";
to
string vocabulary_file = "your superpoint.yml.gz path";

• file:config\euroc\euroc_mono_imu_config.yaml line:61,65,66

change
pose_graph_save_path: "/home/lhk/catkin_ws/src/SuperVINS/output"
extractor_weight_path: "/home/lhk/catkin_ws/src/SuperVINS/vins_estimator/weights_dpl/superpoint.onnx"
matcher_weight_path: "/home/lhk/catkin_ws/src/SuperVINS/vins_estimator/weights_dpl/superpoint_lightglue_fused_cpu.onnx" 
to
pose_graph_save_path: "you output path"
extractor_weight_path: "your superpoint.onnx path"
matcher_weight_path: "your superpoint_lightglue_fused_cpu.onnx path" 

4.4 Compile project

cd ~/catkin_ws
catkin_make

4.5 Run the project

roslaunch supervins supervins_rviz.launch
rosrun supervins supervins_node ~/catkin_ws/src/SuperVINS/config/euroc/euroc_mono_imu_config.yaml
rosrun supervins_loop_fusion supervins_loop_fusion_node ~/catkin_ws/src/SuperVINS/config/euroc/euroc_mono_imu_config.yaml
rosbag play ~/data/EuRoC/MH_01_easy.bag

If Python is installed on your computer, you can directly use the python script to run it with one click

cd ~/catkin_ws/src/SuperVINS
python run.py