KISS-SLAM

Install • Paper • Contact Us

KISS-SLAM is a simple, robust, and accurate 3D LiDAR SLAM system that just works.

motivation

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:

Reduce the odometry.preprocessing.max_range to 50.0, this will automatically reduce the voxel_size to 0.5.
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:

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:

@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

Metadata

Release files for perceptual-kiss-slam 0.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for perceptual-kiss-slam 0.0.3
File	Size	Uploaded
perceptual_kiss_slam-0.0.3.tar.gz	18.5 kB	Oct 6, 2025	Details

Built distributions (wheels)

Table of built distributions (wheels) for perceptual-kiss-slam 0.0.3
File	Interpreter	ABI	Platform	Reset
perceptual_kiss_slam-0.0.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 775.4 kB Oct 6, 2025	CPython 3.13	CPython 3.13	Linux glibc 2.17+ x86-64	Details
perceptual_kiss_slam-0.0.3-cp313-cp313-macosx_11_0_arm64.whl 621.9 kB Oct 6, 2025	CPython 3.13	CPython 3.13	macOS 11.0+ ARM64	Details
perceptual_kiss_slam-0.0.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 775.9 kB Oct 6, 2025	CPython 3.12	CPython 3.12	Linux glibc 2.17+ x86-64	Details
perceptual_kiss_slam-0.0.3-cp312-cp312-macosx_11_0_arm64.whl 621.9 kB Oct 6, 2025	CPython 3.12	CPython 3.12	macOS 11.0+ ARM64	Details
perceptual_kiss_slam-0.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 777.6 kB Oct 6, 2025	CPython 3.11	CPython 3.11	Linux glibc 2.17+ x86-64	Details
perceptual_kiss_slam-0.0.3-cp311-cp311-macosx_11_0_arm64.whl 621.3 kB Oct 6, 2025	CPython 3.11	CPython 3.11	macOS 11.0+ ARM64	Details
perceptual_kiss_slam-0.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 777.6 kB Oct 6, 2025	CPython 3.10	CPython 3.10	Linux glibc 2.17+ x86-64	Details
perceptual_kiss_slam-0.0.3-cp310-cp310-macosx_11_0_arm64.whl 620.1 kB Oct 6, 2025	CPython 3.10	CPython 3.10	macOS 11.0+ ARM64	Details
perceptual_kiss_slam-0.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 776.4 kB Oct 6, 2025	CPython 3.9	CPython 3.9	Linux glibc 2.17+ x86-64	Details
perceptual_kiss_slam-0.0.3-cp39-cp39-macosx_11_0_arm64.whl 620.3 kB Oct 6, 2025	CPython 3.9	CPython 3.9	macOS 11.0+ ARM64	Details
perceptual_kiss_slam-0.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl 776.4 kB Oct 6, 2025	CPython 3.8	CPython 3.8	Linux glibc 2.17+ x86-64	Details
perceptual_kiss_slam-0.0.3-cp38-cp38-macosx_11_0_arm64.whl 620.1 kB Oct 6, 2025	CPython 3.8	CPython 3.8	macOS 11.0+ ARM64	Details

Total release size: 8.4 MB

Release files / perceptual_kiss_slam-0.0.3.tar.gz

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SHA-256 checksum How to use checksums	`79a707eff069e21ae7284d8821885c96fb795ce6519581d5bfe18ff1c42b83ae`
BLAKE2b-256 checksum How to use checksums	`2fe7f38ec21f69e02749ec26d04069df7d0d8326fca9c0294330e9096a0a327e`
Upload date	Oct 6, 2025
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Uploaded via	`twine/6.1.0 CPython/3.13.7`

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Publishing repository: github.com/perceptual-ai/kiss-slam
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Download URL	perceptual_kiss_slam-0.0.3-cp38-cp38-macosx_11_0_arm64.whl
Size	620.1 kB
Tags	CPython 3.8 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`4eea002b6f91c764124574c83d278d3baf84bfe671b019991f7ba3168c317cc0`
BLAKE2b-256 checksum How to use checksums	`499e83313898b16fd980141aa91d7ca25b466dc93b75a3f28f62f5ac093ac4f8`
Upload date	Oct 6, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.7`

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Publishing repository: github.com/perceptual-ai/kiss-slam
Publishing commit: github.com/perceptual-ai/kiss-slam/tree/d162b373d483249a1bb8b571e94ed6c4bb6cf0a4

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Subject: perceptual_kiss_slam-0.0.3-cp38-cp38-macosx_11_0_arm64.whl
SHA-256 checksum: 4eea002b6f91c764124574c83d278d3baf84bfe671b019991f7ba3168c317cc0 Verifying attestations

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This release

0.0.3 This release

Oct 6, 2025 13 release files

perceptual-kiss-slam 0.0.3

KISS-SLAM

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Release files for perceptual-kiss-slam 0.0.3

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