https://github.com/engcang/fast-lio-sam-sc-qn
A SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on ScanContext, Quatro, and Nano-GICP
https://github.com/engcang/fast-lio-sam-sc-qn
lidar lidar-inertial-odometry lidar-slam loop-closure slam
Last synced: 12 months ago
JSON representation
A SLAM implementation combining FAST-LIO2 with pose graph optimization and loop closing based on ScanContext, Quatro, and Nano-GICP
- Host: GitHub
- URL: https://github.com/engcang/fast-lio-sam-sc-qn
- Owner: engcang
- License: other
- Created: 2024-02-01T04:58:56.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2024-10-27T21:28:23.000Z (over 1 year ago)
- Last Synced: 2025-06-04T19:30:47.343Z (about 1 year ago)
- Topics: lidar, lidar-inertial-odometry, lidar-slam, loop-closure, slam
- Language: C++
- Homepage:
- Size: 50.8 KB
- Stars: 117
- Watchers: 3
- Forks: 10
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# FAST-LIO-SAM-SC-QN
+ This repository is a SLAM implementation combining [FAST-LIO2](https://github.com/hku-mars/FAST_LIO) with pose graph optimization and loop closing based on [ScanContext](https://github.com/gisbi-kim/scancontext_tro), [Quatro](https://quatro-plusplus.github.io/), and [Nano-GICP module](https://github.com/engcang/nano_gicp)
+ [ScanContext](https://github.com/gisbi-kim/scancontext_tro) - a global descriptor for LiDAR point cloud, here it is used as loop candidate pair detection
+ [Quatro](https://quatro-plusplus.github.io/) - fast, accurate and robust global registration which provides great initial guess of transform
+ [Quatro module](https://github.com/engcang/quatro) - `Quatro` as a module, can be easily used in other packages
+ [Nano-GICP module](https://github.com/engcang/nano_gicp) - fast ICP combining [FastGICP](https://github.com/SMRT-AIST/fast_gicp) + [NanoFLANN](https://github.com/jlblancoc/nanoflann)
+ Note: similar repositories already exist
+ [FAST_LIO_LC](https://github.com/yanliang-wang/FAST_LIO_LC): FAST-LIO2 + SC-A-LOAM based SLAM
+ [FAST_LIO_SLAM](https://github.com/gisbi-kim/FAST_LIO_SLAM): FAST-LIO2 + ScanContext based SLAM
+ [FAST_LIO_SAM](https://github.com/kahowang/FAST_LIO_SAM): FAST-LIO2 + LIO-SAM (not modularized)
+ [FAST_LIO_SAM](https://github.com/engcang/FAST-LIO-SAM): FAST-LIO2 + LIO-SAM (modularized)
+ [FAST_LIO_SAM_QN](https://github.com/engcang/FAST-LIO-SAM-QN): FAST-LIO2 + LIO-SAM + Quatro + Nano-GICP (modularized)
+ 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](https://engcang.github.io/2023/07/15/gtsam_tutorial.html)
## Video clip - https://youtu.be/MQ8XxRY472Y
## Main difference between [FAST_LIO_SAM_QN](https://github.com/engcang/FAST-LIO-SAM-QN) and FAST_LIO_SAM_SC_QN
+ 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
## Dependencies
+ `C++` >= 17, `OpenMP` >= 4.5, `CMake` >= 3.10.0, `Eigen` >= 3.2, `Boost` >= 1.54
+ `ROS`
+ [`GTSAM`](https://github.com/borglab/gtsam) >= 4.1.1
```shell
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++`](https://github.com/MIT-SPARK/TEASER-plusplus)
```shell
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`)
```shell
sudo apt install libtbb-dev
```
## How to build
+ Get the code and then build the main code.
```shell
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 -DQUATRO_DEBUG=OFF
catkin build -DCMAKE_BUILD_TYPE=Release
. devel/setup.bash
```
## How to run
+ Then run (change config files in third_party/`FAST_LIO`)
```shell
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
```
* In particular, we provide a preset launch option for specific datasets:
```shell
roslaunch fast_lio_sam_sc_qn run.launch lidar:=kitti
roslaunch fast_lio_sam_sc_qn run.launch lidar:=mulran
roslaunch fast_lio_sam_sc_qn run.launch lidar:=newer-college20
```
## Structure
+ odomPcdCallback
+ 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
+ loopTimerFunc
+ process a saved keyframe
+ detect loop -> if loop, add to pose graph
+ visTimerFunc
+ visualize all **(Note: global map is only visualized once uncheck/check the mapped_pcd in rviz to save comp.)**
## Memo
+ `Quatro` module fixed for empty matches
+ `Quatro` module is updated with `optimizedMatching` which limits the number of correspondences and increased the speed
## License
This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/)