| Name | perceptual-kiss-slam JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | None |
| Summary | KISS-SLAM: A Simple, Robust, and Accurate 3D LiDAR SLAM System With Enhanced Generalization Capabilities |
| upload_time | 2025-10-06 15:42:50 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
lidar
slam
mapping
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div align="center">
<h1>KISS-SLAM</h1>
<a href="https://github.com/PRBonn/kiss-slam/releases"><img src="https://img.shields.io/github/v/release/PRBonn/kiss-slam?label=version" /></a>
<a href="https://github.com/PRBonn/kiss-slam/blob/main/LICENSE"><img src="https://img.shields.io/github/license/PRBonn/kiss-slam" /></a>
<a href="https://github.com/PRBonn/kiss-slam/blob/main/"><img src="https://img.shields.io/badge/Linux-FCC624?logo=linux&logoColor=black" /></a>
<a href="https://github.com/PRBonn/kiss-slam/blob/main/"><img src="https://img.shields.io/badge/mac%20os-000000?&logo=apple&logoColor=white" /></a>
<br />
<br />
<a href="https://github.com/PRBonn/kiss-slam/blob/main/README.md#Install">Install</a>
<span> • </span>
<a href="https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/kiss2025iros.pdf">Paper</a>
<span> • </span>
<a href=https://github.com/PRBonn/kiss-slam/issues>Contact Us</a>
<br />
<br />
[KISS-SLAM](https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/kiss2025iros.pdf) is a simple, robust, and accurate 3D LiDAR SLAM system that **just works**.
</div>
<hr />
## Install
```
pip install kiss-slam
```
## Running the system
Next, follow the instructions on how to run the system by typing:
```
kiss_slam_pipeline --help
```
This should print the following help message:
### Config
You can generate a default `config.yaml` by typing:
```
kiss_slam_dump_config
```
which will generate a `kiss_slam.yaml` file. Now, you can modify the parameters and pass the file to the `--config` option when running the `kiss_slam_pipeline`.
Suggestion for indoor applications:
1. Reduce the `odometry.preprocessing.max_range` to 50.0, this will automatically reduce the `voxel_size` to 0.5.
2. Reduce the `local_mapper.splitting_distance` to a suitable distance based on the scale of the indoor environment.
### Install Python API (developer mode)
For development purposes:
```
sudo apt install git python3-pip libeigen3-dev libsuitesparse-dev
python3 -m pip install --upgrade pip
git clone https://github.com/PRBonn/kiss-slam.git
cd kiss-slam
make editable
```
### Paper Results
As we decided to continue developing **KISS-SLAM** beyond the scope of the IROS paper, we created a ``git tag`` so that researchers can consistently reproduce the results presented in the publication. To checkout at this tag, you can run the following:
```sh
git checkout IROS25
```
Our development aims to surpass the performance of **KISS-SLAM** beyond the original results presented in the paper.
## Citation
If you use this library for any academic work, please cite our original paper:
```bib
@article{kiss2025arxiv,
author = {T. Guadagnino and B. Mersch and S. Gupta and I. Vizzo and G. Grisetti and C. Stachniss},
title = {{KISS-SLAM: A Simple, Robust, and Accurate 3D LiDAR SLAM System With Enhanced Generalization Capabilities}},
journal = {arXiv preprint},
year = 2025,
volume = {arXiv:2503.12660},
url = {https://arxiv.org/pdf/2503.12660},
}
```
## Acknowledgements
This project builds on top of [KISS-ICP](https://github.com/PRBonn/kiss-icp), [MapClosures](https://github.com/PRBonn/MapClosures), and [g2o](https://github.com/RainerKuemmerle/g2o).
## Contributing
We envision KISS-SLAM as a community-driven project. We love to see how the project is growing, thanks to the contributions from the community. We would love to see your face in the list below; open a Pull Request!
<a href="https://github.com/PRBonn/kiss-slam/graphs/contributors">
<img src="https://contrib.rocks/image?repo=PRBonn/kiss-slam" />
</a>
## Contact Us
For questions or feedback:
- GitHub Issues: https://github.com/PRBonn/kiss-slam/issues
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"description": "<div align=\"center\">\n <h1>KISS-SLAM</h1>\n <a href=\"https://github.com/PRBonn/kiss-slam/releases\"><img src=\"https://img.shields.io/github/v/release/PRBonn/kiss-slam?label=version\" /></a>\n <a href=\"https://github.com/PRBonn/kiss-slam/blob/main/LICENSE\"><img src=\"https://img.shields.io/github/license/PRBonn/kiss-slam\" /></a>\n <a href=\"https://github.com/PRBonn/kiss-slam/blob/main/\"><img src=\"https://img.shields.io/badge/Linux-FCC624?logo=linux&logoColor=black\" /></a>\n <a href=\"https://github.com/PRBonn/kiss-slam/blob/main/\"><img src=\"https://img.shields.io/badge/mac%20os-000000?&logo=apple&logoColor=white\" /></a>\n <br />\n <br />\n <a href=\"https://github.com/PRBonn/kiss-slam/blob/main/README.md#Install\">Install</a>\n <span> \u2022 </span>\n <a href=\"https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/kiss2025iros.pdf\">Paper</a>\n <span> \u2022 </span>\n <a href=https://github.com/PRBonn/kiss-slam/issues>Contact Us</a>\n <br />\n <br />\n\n[KISS-SLAM](https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/kiss2025iros.pdf) is a simple, robust, and accurate 3D LiDAR SLAM system that **just works**.\n\n\n\n\n\n</div>\n\n<hr />\n\n## Install\n\n```\npip install kiss-slam\n```\n\n## Running the system\nNext, follow the instructions on how to run the system by typing:\n```\nkiss_slam_pipeline --help\n```\n\nThis should print the following help message:\n\n\n\n### Config\nYou can generate a default `config.yaml` by typing:\n\n```\nkiss_slam_dump_config\n```\n\nwhich will generate a `kiss_slam.yaml` file. Now, you can modify the parameters and pass the file to the `--config` option when running the `kiss_slam_pipeline`.\n\nSuggestion for indoor applications:\n1. Reduce the `odometry.preprocessing.max_range` to 50.0, this will automatically reduce the `voxel_size` to 0.5.\n2. Reduce the `local_mapper.splitting_distance` to a suitable distance based on the scale of the indoor environment.\n\n### Install Python API (developer mode)\nFor development purposes:\n\n```\nsudo apt install git python3-pip libeigen3-dev libsuitesparse-dev\npython3 -m pip install --upgrade pip\ngit clone https://github.com/PRBonn/kiss-slam.git\ncd kiss-slam\nmake editable\n```\n\n### Paper Results\nAs we decided to continue developing **KISS-SLAM** beyond the scope of the IROS paper, we created a ``git tag`` so that researchers can consistently reproduce the results presented in the publication. To checkout at this tag, you can run the following:\n```sh\ngit checkout IROS25\n```\nOur development aims to surpass the performance of **KISS-SLAM** beyond the original results presented in the paper.\n\n## Citation\nIf you use this library for any academic work, please cite our original paper:\n```bib\n@article{kiss2025arxiv,\n author = {T. Guadagnino and B. Mersch and S. Gupta and I. Vizzo and G. Grisetti and C. Stachniss},\n title = {{KISS-SLAM: A Simple, Robust, and Accurate 3D LiDAR SLAM System With Enhanced Generalization Capabilities}},\n journal = {arXiv preprint},\n year = 2025,\n volume = {arXiv:2503.12660},\n url = {https://arxiv.org/pdf/2503.12660},\n}\n```\n\n## Acknowledgements\nThis project builds on top of [KISS-ICP](https://github.com/PRBonn/kiss-icp), [MapClosures](https://github.com/PRBonn/MapClosures), and [g2o](https://github.com/RainerKuemmerle/g2o).\n\n## Contributing\n\nWe envision KISS-SLAM as a community-driven project. We love to see how the project is growing, thanks to the contributions from the community. We would love to see your face in the list below; open a Pull Request!\n\n<a href=\"https://github.com/PRBonn/kiss-slam/graphs/contributors\">\n <img src=\"https://contrib.rocks/image?repo=PRBonn/kiss-slam\" />\n</a>\n\n## Contact Us\nFor questions or feedback:\n- GitHub Issues: https://github.com/PRBonn/kiss-slam/issues\n",
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