# PRBonn/kiss-icp

A LiDAR odometry pipeline that just works

Repository: https://github.com/PRBonn/kiss-icp
Canonical: https://ross.abutalabs.com/products/kiss-icp
Homepage: https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2023ral.pdf
Language: C++
License: MIT
License Family: permissive
Topics: 3d-mapping, icp, lidar-slam, slam, robotics, ros, ros2
Last push: 2026-06-09T14:20:13+00:00

## Health v2 (maintenance only)
Score: 83/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 86, release rhythm 69, longevity 100
- inputs: {"age_days": 1450, "days_push": 85, "days_rel": 129, "gap_med": 45, "n_releases_24m": 6}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2303, forks 457 (observed 2026-08-28T04:06:35.602334+00:00)

## What it is
KISS-ICP is a LiDAR odometry pipeline built around a simple ICP-based approach that works out of the box on most datasets without parameter tuning. It is written in C++ with Python bindings, a CLI pipeline runner, and ROS 2 support.

## Use cases
- estimate vehicle trajectory from lidar point clouds
- run lidar odometry without tuning parameters
- process rosbag lidar data offline
- integrate lidar odometry into a ROS 2 robot stack
- benchmark odometry on SLAM datasets
- build 3D maps from moving lidar scans

## When to choose
- you need a simple, dependency-light lidar odometry baseline that works without tuning
- you want a pip-installable CLI to process point cloud data quickly
- you use ROS 2 and need an odometry node
- you need cross-platform (Linux/macOS/Windows) support

## When to avoid
- you need full SLAM with loop closure and global mapping
- you rely on ROS 1, which is no longer officially supported
- you need visual-inertial or multi-sensor fusion odometry
- you need highly tuned odometry for extreme conditions like degenerate geometry

## Facets
- artifact type: library
- maturity: active
- function: robotics, computer-vision, simulation
- domain: robotics, autonomous-vehicles
- platform: windows, python, cpp
- tags: lidar-odometry, icp, slam, point-clouds, ros2, 3d-mapping, algorithms, linux, macos, ros

## Member repositories
- PRBonn/kiss-icp (main) score 83

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:35.602334+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:39:53.928636+00:00, confidence not recorded.
  - readme: https://github.com/PRBonn/kiss-icp (fetched 2026-08-28T04:06:35.602334+00:00, sha 2d336a5e55ff)
- Data as of 2026-08-30T08:39:29.467469+00:00.