https://github.com/limhyungtae/patchwork
SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)
https://github.com/limhyungtae/patchwork
3dpointcloud autonomous-driving autonomous-vehicles ground-estimation ground-estimator ground-segmentation lidar ros
Last synced: 3 months ago
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SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)
- Host: GitHub
- URL: https://github.com/limhyungtae/patchwork
- Owner: LimHyungTae
- License: mit
- Created: 2021-06-17T04:16:52.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-05-05T01:50:51.000Z (5 months ago)
- Last Synced: 2025-05-05T02:35:56.241Z (5 months ago)
- Topics: 3dpointcloud, autonomous-driving, autonomous-vehicles, ground-estimation, ground-estimator, ground-segmentation, lidar, ros
- Language: C++
- Homepage:
- Size: 76.5 MB
- Stars: 521
- Watchers: 13
- Forks: 77
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
---
**IMPORTANT**: (Aug. 18th, 2024) I employ TBB, so its FPS is increased from **50 Hz** to **100 Hz**!
If you want to use the paper version of Patchwork for SOTA comparison purpose, Please use this [ground seg. benchmark code](https://github.com/url-kaist/Ground-Segmentation-Benchmark).
Patchwork | Concept of our method (CZM & GLE)
:-------------------------:|:-------------------------:
 | 
It's an overall updated version of **R-GPF of ERASOR** [**[Code](https://github.com/LimHyungTae/ERASOR)**] [**[Paper](https://arxiv.org/abs/2103.04316)**].
---
## :open_file_folder: Contents
0. [Test Env.](#Test-Env.)
0. [Requirements](#requirements)
0. [How to Run Patchwork](#How-to-Run-Patchwork)
0. [Citation](#citation)
### Test Env.
The code is tested successfully at
* Linux 24.04 LTS
* ROS2 Jazzy
ROS Noetic version can be found [here](https://github.com/LimHyungTae/patchwork/releases/tag/v0.2)
## :package: Prerequisite Installation
```bash
mkdir -p ~/colcon/src
cd ~/colcon/src
git clone https://github.com/LimHyungTae/patchwork.git
cd ..
colcon build --packages-up-to patchwork --cmake-args -DCMAKE_BUILD_TYPE=Release
```
## :gear: How to Run Patchwork
#### :chart_with_upwards_trend: Offline KITTI dataset
1. Download [SemanticKITTI](http://www.semantic-kitti.org/dataset.html#download) Odometry dataset (We also need labels since we also open the evaluation code! :)
2. The `dataset_path` should consist of `velodyne` folder and `labels` folder as follows:
```
data_path (e.g. 00, 01, ..., or 10)
_____velodyne
|___000000.bin
|___000001.bin
|___000002.bin
|...
_____labels
|___000000.label
|___000001.label
|___000002.label
|...
_____...
```
3. Run launch file
```
ros2 launch patchwork evaluate.launch.yaml evaluate_semantickitti:=true dataset_path:="
e.g.,
ros2 launch patchwork evaluate.launch.yaml evaluate_semantickitti:=true dataset_path:="/home/hyungtae_lim/semkitti/dataset/sequences/04"
```
#### :runner: Online Ground Segmentation
```
ros2 launch patchwork run_patchwork.launch.yaml scan_topic:= sensor_type:=
e.g.,
ros2 launch patchwork run_patchwork.launch.yaml scan_topic:="/acl_jackal2/lidar_points" sensor_type:="velodyne16"
```
For better understanding of the parameters of Patchwork, please read [our wiki, 4. IMPORTANT: Setting Parameters of Patchwork in Your Own Env.](https://github.com/LimHyungTae/patchwork/wiki/4.-IMPORTANT:-Setting-Parameters-of-Patchwork-in-Your-Own-Env.).
---------
## Citation
If you use our code or method in your work, please consider citing the following:
@article{lim2021patchwork,
title={Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor},
author={Lim, Hyungtae and Minho, Oh and Myung, Hyun},
journal={IEEE Robotics and Automation Letters},
year={2021}
}
---
## Updates
#### NEWS (22.12.24)
- Merry christmas eve XD! `include/label_generator` is added to make the `.label` file, following the SemanticKITTI format.
- The `.label` files can be directly used in [3DUIS benchmark](https://github.com/PRBonn/3DUIS)
- Thank [Lucas Nunes](https://scholar.google.com/citations?user=PCxhsf4AAAAJ&hl=en&oi=ao) and [Xieyuanli Chen](https://scholar.google.com/citations?user=DvrngV4AAAAJ&hl=en&oi=sra) for providing code snippets to save a `.label` file.
#### NEWS (22.07.25)
- Pybinding + more advanced version is now available on [Patchwork++](https://github.com/url-kaist/patchwork-plusplus) as a preprocessing step for deep learning users (i.e., python users can also use our robust ground segmentation)!
#### NEWS (22.07.13)
- For increasing convenience of use, the examples and codes are extensively revised by reflecting [issue #12](https://github.com/LimHyungTae/patchwork/issues/12).
#### NEWS (22.05.22)
- The meaning of `elevation_thresholds` is changed to increase the usability. The meaning is explained in [wiki](https://github.com/LimHyungTae/patchwork/wiki/4.-IMPORTANT:-Setting-Parameters-of-Patchwork-in-Your-Own-Env.).
- A novel height estimator, called *All-Terrain Automatic heighT estimator (ATAT)* is added within the patchwork code, which auto-calibrates the sensor height using the ground points in the vicinity of the vehicle/mobile robot.
- Please refer to the function `consensus_set_based_height_estimation()`.
-blue){kind=icon}
