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https://github.com/url-kaist/patchwork-plusplus

Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22
https://github.com/url-kaist/patchwork-plusplus

3d-lidar detection ground ground-detection ground-removal ground-segmentation lidar point-cloud segmentation

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Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22

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README 

        
# Patchwork++



## :bookmark_tabs: About Patchwork++ (IROS'22)



* A fast, robust, and self-adaptive **ground segmentation algorithm** on 3D point cloud.



animated



* An extension of [Patchwork][patchworklink] (RA-L'21 with IROS'21).

* Please refer our [paper][patchworkppIEEElink] for detailed explanantions and experimental results!



   * Validated on [SemanticKITTI][SemanticKITTIlink] dataset. The benchmark code is available on [here][benchmarklink].



* :bulb: Contents: [YouTube][YouTubeLink], [arXiv][arXivlink], [IEEE *Xplore*][patchworkppIEEElink]



[YouTubeLInk]: https://www.youtube.com/watch?v=fogCM159GRk

[arXivlink]: https://arxiv.org/abs/2207.11919

[patchworklink]: https://github.com/LimHyungTae/patchwork

[SemanticKITTIlink]: http://www.semantic-kitti.org/

[benchmarklink]: https://github.com/url-kaist/Ground-Segmentation-Benchmark



## :open_file_folder: What's in this repo



* C++ source code of Patchwork++ ([patchworkpp][sourcecodelink])

* Python binding of Patchwork++ using pybind11 ([python_wrapper][wraplink])

* Examples codes, which visualizes a ground segmentation result by Patchwork++ ([examples][examplelink]) :thumbsup:



> If you are familiar with ROS, you can also visit [here][roslink] and try executing ROS-based Patchwork++!



[roslink]: https://github.com/url-kaist/patchwork-plusplus-ros



[sourcecodelink]: https://github.com/url-kaist/patchwork-plusplus/tree/master/patchworkpp

[pybind11link]: https://github.com/pybind/pybind11

[wraplink]: https://github.com/url-kaist/patchwork-plusplus/tree/master/python_wrapper

[examplelink]: https://github.com/url-kaist/patchwork-plusplus/tree/master/examples



## :package: Prerequisite packages

> You may need to install Eigen, numpy, and Open3D. Open3D is used for point cloud visualization.



```bash

# Install prerequisite packages including Open3D

$ git clone https://github.com/url-kaist/patchwork-plusplus

$ cd patchwork-plusplus

$ bash scripts/install_open3d.bash

```



 Manual Installation line-by-line 



```bash

# To install Eigen and numpy

$ sudo apt-get install libeigen3-dev

$ pip install numpy



# To install Open3D Python packages

$ pip install open3d



# To install Open3D C++ packages

$ git clone https://github.com/isl-org/Open3D

$ cd Open3D

$ util/install_deps_ubuntu.sh # Only needed for Ubuntu

$ mkdir build && cd build

$ cmake ..

$ make # If it fails, try several times or try 'sudo make'

$ sudo make install

```



## :gear: How to build

> Please follow below codes to build Patchwork++.



### Python

```bash

# in patchwork-plusplus directory

$ pip install . 

```



### C++

```bash

# in patchwork-plusplus directory

$ mkdir build && cd build

$ cmake ..

$ make

```



## :runner: To run the demo codes

> There are some example codes for your convenience!

> Please try using Patchwork++ to segment ground points in a 3D point cloud :smiley:



### Python

```bash

# Run patchwork++ and visualize ground points(green) and nonground points(red)

$ python examples/python/demo_visualize.py



# Run patchwork++ with sequential point cloud inputs 

$ python examples/python/demo_sequential.py

```



### C++

```bash

# Run patchwork++ and visualize ground points(green) and nonground points(red)

$ ./build/examples/cpp/demo_visualize



# Run patchwork++ with sequential point cloud inputs 

$ ./build/examples/cpp/demo_sequential



# Run patchwork++ with your point cloud file, example here

$ ./build/examples/cpp/demo_visualize ./data/000000.bin # specify file path

```



### Demo Result

If you execute Patchwork++ with given demo codes well, you can get the following result!



It is a ground segmentation result of data/000000.bin file using Open3D visualization. (Ground : Green, Nonground : Red)



![Open3D Visualization of "data/000000.bin"](pictures/demo_000000.png)



## :pencil: Citation

If you use our codes, please cite our paper ([arXiv][arXivLink], [IEEE *Xplore*][patchworkppIEEElink])

```

@inproceedings{lee2022patchworkpp,

    title={{Patchwork++: Fast and robust ground segmentation solving partial under-segmentation using 3D point cloud}},

    author={Lee, Seungjae and Lim, Hyungtae and Myung, Hyun},

    booktitle={Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst.},

    year={2022},

    pages={13276-13283}

}

```



In addition, you can also check the paper of our baseline, Patchwork. ([arXiv][patchworkarXivlink], [IEEE *Xplore*][patchworkIEEElink])

```

@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}

}

```

[patchworkppIEEElink]: https://ieeexplore.ieee.org/document/9981561

[patchworkarXivlink]: https://arxiv.org/abs/2108.05560

[patchworkIEEElink]: https://ieeexplore.ieee.org/document/9466396



## :triangular_flag_on_post: Tested Environment



- Ubuntu 18.04 and 20.04

- CMake 3.25.1 (>=3.20, min. Required to install Open3D)

- Open3D 0.15.2

- pybind11 v2.2.3

- Eigen 3.3.7



## :mailbox: Contact Information

If you have any questions, please do not hesitate to contact us

* [Seungjae Lee][sjlink] :envelope: `sj98lee at kaist.ac.kr`

* [Hyungtae Lim][htlink] :envelope: `shapelim at kaist.ac.kr`



[sjlink]: https://github.com/seungjae24

[htlink]: https://github.com/LimHyungTae