Metadata-Version: 2.1
Name: kiss_icp
Version: 0.2.7
Summary: Simple yet effective 3D LiDAR-Odometry registration pipeline
Home-page: https://github.com/PRBonn/kiss-icp
Author: Ignacio Vizzo
Author-email: ignaciovizzo@gmail.com
License: MIT
Keywords: SLAM,LiDAR,Odometry,Localization
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
Provides-Extra: visualizer
Provides-Extra: all
License-File: LICENSE

<div align="center">
    <h1>KISS-ICP</h1>
    <a href="https://github.com/PRBonn/kiss-icp/releases"><img src="https://img.shields.io/github/v/release/PRBonn/kiss-icp?label=version" /></a>
    <a href="https://github.com/PRBonn/kiss-icp/blob/main/LICENSE"><img src="https://img.shields.io/github/license/PRBonn/kiss-icp" /></a>
    <a href="https://github.com/PRBonn/kiss-icp/blob/main/"><img src="https://img.shields.io/badge/Linux-FCC624?logo=linux&logoColor=black" /></a>
    <a href="https://github.com/PRBonn/kiss-icp/blob/main/"><img src="https://img.shields.io/badge/Windows-0078D6?st&logo=windows&logoColor=white" /></a>
    <a href="https://github.com/PRBonn/kiss-icp/blob/main/"><img src="https://img.shields.io/badge/mac%20os-000000?&logo=apple&logoColor=white" /></a>
    <br />
    <br />
    <a href=https://user-images.githubusercontent.com/21349875/219626075-d67e9165-31a2-4a1b-8c26-9f04e7d195ec.mp4>Demo</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href="https://github.com/PRBonn/kiss-icp/edit/main/README.md#install">Install</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href="https://github.com/PRBonn/kiss-icp/blob/main/ros">ROS 1</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href="https://github.com/PRBonn/kiss-icp/blob/main/ros">ROS 2</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href=https://user-images.githubusercontent.com/21349875/214578180-b1d2431c-8fff-440e-aa6e-99a1d85989b5.mp4
>ROS Demo</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href=https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2023ral.pdf>Paper</a>
    <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
    <a href=https://github.com/PRBonn/kiss-icp/issues>Contact Us</a>
  <br />
  <br />

[KISS-ICP](https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2023ral.pdf) is a LiDAR Odometry pipeline that **just works** on most of the cases withouth tunning any parameter.

  <p align="center">
    <a href="https://user-images.githubusercontent.com/21349875/219626075-d67e9165-31a2-4a1b-8c26-9f04e7d195ec.mp4"><img alt="KISS-ICP Demo" src="https://user-images.githubusercontent.com/21349875/211829074-474bec08-0129-4e34-85e7-62265e44a7de.png"></a>
  </p>
</div>

<hr />

## Install

```sh
pip install kiss-icp
```

If you also want to install all the *(optional)* dependencies, like Open3D for running the visualizer:

```sh
pip install "kiss-icp[all]"
```

## Running the system

Next, follow the instructions on how to run the system by typing:

```sh
kiss_icp_pipeline --help
```

This should print the following help message:
![out](https://user-images.githubusercontent.com/21349875/193282970-25a400aa-ebcd-487a-b839-faa04eeca5b9.png)

### Install Python API (developer mode)

If you plan to modify the code then you need to setup the dev dependencies, luckilly, the only real
requirements are a modern C++ compiler and the `pip` package manager, nothing else!, in Ubuntu-based
sytems this can be done with:

```sh
sudo apt install g++ python3-pip
```

After that you can clone the code and install the python api:

```sh
git clone https://github.com/PRBonn/kiss-icp.git
cd kiss-icp
pip install --verbose .
```

### Install Python API (expert mode)

If you want to have more controll over the build, you should then install `cmake`, ,`ninja`, `tbb`,
`Eigen`, and `pybind11` as extra dependencies in your system, the ubuntu-way of doing this is:

```sh
sudo apt install build-essential libeigen3-dev libtbb-dev pybind11-dev ninja-build
```

## Citation

If you use this library for any academic work, please cite our original [paper](https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2023ral.pdf).

```bibtex
@article{vizzo2023ral,
  author    = {Vizzo, Ignacio and Guadagnino, Tiziano and Mersch, Benedikt and Wiesmann, Louis and Behley, Jens and Stachniss, Cyrill},
  title     = {{KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If Done the Right Way}},
  journal   = {IEEE Robotics and Automation Letters (RA-L)},
  pages     = {1029--1036},
  doi       = {10.1109/LRA.2023.3236571},
  volume    = {8},
  number    = {2},
  year      = {2023},
  codeurl   = {https://github.com/PRBonn/kiss-icp},
}
```

## Contributing

We envision KISS-ICP as a comunity-driven project, we love to see how the project is growing thanks to the contributions from the comunity. We would love to see your face in the list below, just open a Pull Request!

<a href="https://github.com/PRBonn/kiss-icp/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=PRBonn/kiss-icp" />
</a>
[![Star History Chart](https://api.star-history.com/svg?repos=PRBonn/kiss-icp&type=Date)](https://star-history.com/#PRBonn/kiss-icp&Date)
