What is SC-LIO-SAM?

• SC-LIO-SAM is a real-time lidar-inertial SLAM package.
  • LiDAR-inertial SLAM: Scan Context + LIO-SAM
• This repository is an example use-case of Scan Context, which is a fast and robust LiDAR place recognition method.
• For more details for each algorithm please refer to
  Scan Context https://github.com/irapkaist/scancontext
  LIO-SAM https://github.com/TixiaoShan/LIO-SAM
  
• You can also use the LiDAR-only versions of this project: SC-LeGO-LOAM and SC-A-LOAM.

Scan Context: A fast and robust place recognition

• Light-weight: a single header and cpp file named "Scancontext.h" and "Scancontext.cpp"
  • Our module has KDtree and we used nanoflann. nanoflann is an also single-header-program and that file is in our directory.
• Easy to use: A user just remembers and uses only two API functions; makeAndSaveScancontextAndKeys and detectLoopClosureID.
• Fast: A single loop detection requires under 30 ms (for 20 x 60 size, 3 candidates)

How to use?

• We provide a tutorial that runs SC-LIO-SAM on MulRan dataset, you can reproduce the above results by following these steps.

1. You can download the dataset at the MulRan dataset website
2. Place the directory SC-LIO-SAM under user catkin work space
   For example,

   cd ~/catkin_ws/src
   git clone https://github.com/gisbi-kim/SC-LIO-SAM.git
   cd ..
   catkin_make
   source devel/setup.bash
   roslaunch lio_sam run.launch # or roslaunch lio_sam run_mulran.launch
   

3. By following this guideline, you can easily publish the MulRan dataset's LiDAR and IMU topics via ROS.

Application

Framework

SC generation

Test