• This repository is a map-based localization implementation combining FAST-LIO2 as an odometry with Quatro and Nano-GICP module as a map matching method
  • Quatro - fast, accurate and robust global registration which provides great initial guess of transform
  • Quatro module - Quatro as a module, can be easily used in other packages
  • Nano-GICP module - fast ICP combining FastGICP + NanoFLANN
• Note: similar repositories already exist
  • FAST_LIO_LOCALIZATION: FAST-LIO2 + Open3D's ICP
• Note2: main code is modularized and hence can be combined with any other LIO / LO
• Note3: this repo is to apply Quatro in localization. Quatro can be worked in scan-to-scan matching or submap-to-submap matching but not scan-to-submap, i.e., the numbers of pointclouds to be matched should be similar.
• Note4: saved map file is needed. The map should be in .bag format. This .bag files can be built with FAST-LIO-SAM-QN and FAST-LIO-SAM

• C++ >= 17, OpenMP >= 4.5, CMake >= 3.10.0, Eigen >= 3.2, Boost >= 1.54
• ROS
• Teaser++

  git clone https://github.com/MIT-SPARK/TEASER-plusplus.git
  cd TEASER-plusplus && mkdir build && cd build
  cmake .. -DENABLE_DIAGNOSTIC_PRINT=OFF
  sudo make install -j16
  sudo ldconfig

• tbb (is used for faster Quatro)

  sudo apt install libtbb-dev

• Get the code and then build the main code.

  cd ~/your_workspace/src
  git clone https://github.com/engcang/FAST-LIO-Localization-QN --recursive
  
  cd ~/your_workspace
  # nano_gicp, quatro first
  catkin build nano_gicp -DCMAKE_BUILD_TYPE=Release
  # Note the option!
  catkin build quatro -DCMAKE_BUILD_TYPE=Release -DQUATRO_TBB=ON
  catkin build -DCMAKE_BUILD_TYPE=Release
  . devel/setup.bash

• Then run (change config files in third_party/FAST_LIO)

  roslaunch fast_lio_localization_qn run.launch lidar:=ouster
  roslaunch fast_lio_localization_qn run.launch lidar:=velodyne
  roslaunch fast_lio_localization_qn run.launch lidar:=livox

• In particular, we provide a preset launch option for specific datasets:

  roslaunch fast_lio_localization_qn run.launch lidar:=kitti
  roslaunch fast_lio_localization_qn run.launch lidar:=mulran
  roslaunch fast_lio_localization_qn run.launch lidar:=newer-college20

• odomPcdCallback
  • pub realtime pose in corrected frame
  • keyframe detection -> if keyframe, add to pose graph + save to keyframe queue
• matchingTimerFunc
  • process a saved keyframe
    • detect map match -> if matched, correct TF
  • visualize all

• Quatro module fixed for empty matches
• Quatro module is updated with optimizedMatching which limits the number of correspondences and increased the speed

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License