kiss-slam

A LiDAR SLAM system that just works

https://github.com/prbonn/kiss-slam

Science Score: 36.0%

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CITATION.cff file
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codemeta.json file
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Academic publication links
Links to: arxiv.org
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Scientific vocabulary similarity
Low similarity (14.5%) to scientific vocabulary

Keywords

lidar lidar-slam mapping perception robotics slam

Last synced: 6 months ago · JSON representation

Repository

A LiDAR SLAM system that just works

Basic Info

Host: GitHub
Owner: PRBonn
License: mit
Language: Python
Default Branch: main
Homepage: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/kiss2025iros.pdf
Size: 78.1 KB

Statistics

Stars: 430
Watchers: 10
Forks: 38
Open Issues: 2
Releases: 3

Topics

lidar lidar-slam mapping perception robotics slam

Created 11 months ago · Last pushed 7 months ago

Metadata Files

Readme License Citation Codeowners

KISS-SLAM

Install • Paper • Contact Us

[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**. ![motivation](https://github.com/user-attachments/assets/66c3e50f-009a-4a36-9856-283a895c300f)

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:

help

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, MapClosures, and 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!

Contact Us

For questions or feedback: - GitHub Issues: https://github.com/PRBonn/kiss-slam/issues

Owner

Name: Photogrammetry & Robotics Bonn
Login: PRBonn
Kind: organization
Email: cyrill.stachniss@igg.uni-bonn.de
Location: Bonn

Website: www.ipb.uni-bonn.de
Repositories: 41
Profile: https://github.com/PRBonn

Photogrammetry & Robotics Lab at the University of Bonn

Citation (CITATION.cff)

GitHub Events

Total

Fork event: 29
Create event: 12
Issues event: 45
Release event: 3
Watch event: 369
Delete event: 9
Issue comment event: 88
Member event: 2
Public event: 1
Push event: 23
Pull request review comment event: 8
Pull request event: 24
Pull request review event: 19

Last Year

Fork event: 29
Create event: 12
Issues event: 45
Release event: 3
Watch event: 369
Delete event: 9
Issue comment event: 88
Member event: 2
Public event: 1
Push event: 23
Pull request review comment event: 8
Pull request event: 24
Pull request review event: 19

Packages

Total packages: 1
Total downloads:
- pypi 356 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 2
Total maintainers: 1

pypi.org: kiss-slam

KISS-SLAM: A Simple, Robust, and Accurate 3D LiDAR SLAM System With Enhanced Generalization Capabilities

Homepage: https://github.com/PRBonn/kiss-slam
Documentation: https://kiss-slam.readthedocs.io/
License: MIT License
Latest release: 0.0.2
published 9 months ago

Versions: 2
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 356 Last month

Rankings

Dependent packages count: 9.5%

Average: 31.4%

Dependent repos count: 53.3%

Maintainers (1)

saurabh.gupta1002

Last synced: 6 months ago

Dependencies

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.github/workflows/pre-commit.yml actions

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.github/workflows/python.yml actions

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pyproject.toml pypi

PyYAML *
kiss-icp >=1.2.3
map_closures >=2.0.1
numpy *
open3d >=0.19.0
pydantic >=2
pydantic-settings *
tqdm *

ecosyste.ms

Data

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Experiments

Open Source Science