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A SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on ScanContext, Quatro, and Nano-GICP
License: Other
fast-lio-sam-sc-qn's Introduction
- This repository is a SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on ScanContext, Quatro, and Nano-GICP module
- ScanContext - a global descriptor for LiDAR point cloud, here it is used as loop candidate pair detection
- 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
- Note2: main code (PGO) is modularized and hence can be combined with any other LIO / LO
- This repo is to learn GTSAM myself!
- and as GTSAM tutorial for beginners - GTSAM 튜토리얼 한글 포스팅
- FAST_LIO_SAM_QN sets loop candidate pair as (current keyframe, the closest and old enough keyframe)
- FAST_LIO_SAM_SC_QN gets loop candidate pair from ScanContext
C++ >= 17, OpenMP >= 4.5, CMake >= 3.10.0, Eigen >= 3.2, Boost >= 1.54ROSGTSAM >= 4.1.1
wget -O gtsam.zip https://github.com/borglab/gtsam/archive/refs/tags/4.1.1.zip
unzip gtsam.zip
cd gtsam-4.1.1/
mkdir build && cd build
cmake -DGTSAM_BUILD_WITH_MARCH_NATIVE=OFF -DGTSAM_USE_SYSTEM_EIGEN=ON ..
sudo make install -j16
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-SAM-SC-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_sam_sc_qn run.launch lidar:=ouster
roslaunch fast_lio_sam_sc_qn run.launch lidar:=velodyne
roslaunch fast_lio_sam_sc_qn run.launch lidar:=livox
- odom_pcd_cb
- pub realtime pose in corrected frame
- keyframe detection -> if keyframe, add to pose graph + save to keyframe queue + generate ScanContext
- pose graph optimization with iSAM2
- loop_timer_func
- process a saved keyframe
- detect loop -> if loop, add to pose graph
- vis_timer_func
- visualize all (Note: global map is only visualized once uncheck/check the mapped_pcd in rviz to save comp.)
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