[IEEE RA-L] This repository is the official code for Narrowing your FOV with SOLiD: Spatially Organized and Lightweight Global Descriptor for FOV-constrained LiDAR Place Recognition.
- [August, 2024] Now, the SOLiD-PyICP-SLAM code is released!!
- [August, 2024] The SOLiD is added in awesome-lidar-place-recognition!!
- [August, 2024] Now, the SOLiD code is released!!
- [July, 2024] SOLiD is accepted in RA-L!!
- SOLiD can be integrated with various LiDAR odometry including solid-state LiDAR.
- (TBD) Integrated with A-LOAM: SOLiD-A-LOAM
- (TBD) Integrated with LOAM-LIVOX: SOLiD-LOAM-LIVOX
- Integrated with a basic ICP odometry: SOLiD-PyICP-SLAM
- This implementation is fully python-based so slow but educational purpose.
- The traditional method uses a bird eye view and overlooks vertical information.
- Also, because it focuses on performance, it is difficult to apply in real-time on an onboard computer.
- SOLiD is a lightweight and fast LiDAR global descriptor for FOV constraints situations that are limited through fusion with other sensors or blocked by robot/sensor operators including mechanical components or solid-state LiDAR (e.g. Livox).
- Python version
- If you use the other LiDAR sensor, you modify the parameters in parser of test.py and lidar file structure in utils/point_module.py.
$ git clone https://github.com/sparolab/solid.git
$ cd python
$ python3 test.py
- Cpp version
- If you use the other LiDAR sensor, you modify the parameters in include/solid_module.h.
$ git clone https://github.com/sparolab/solid.git
$ cd cpp
$ mkdir build
$ cd build
$ cmake ..
$ make
$ ./test_solid
- If you want to clip the points, you can use python/bin/point_clipper.py
$ git clone https://github.com/sparolab/solid.git
$ cd python/bin/
$ python3 point_clipper.py
- If you have a question, you utilize a alphaXiv and comment here.
@article{kim2024narrowing,
title={Narrowing your FOV with SOLiD: Spatially Organized and Lightweight Global Descriptor for FOV-constrained LiDAR Place Recognition},
author={Kim, Hogyun and Choi, Jiwon and Sim, Taehu and Kim, Giseop and Cho, Younggun},
journal={IEEE Robotics and Automation Letters},
year={2024},
publisher={IEEE}
}
- Hogyun Kim ([email protected])