# koide3/small_gicp

Efficient and parallel algorithms for point cloud registration [C++, Python]

Repository: https://github.com/koide3/small_gicp
Canonical: https://ross.abutalabs.com/products/small_gicp
Language: C++
License: MIT
License Family: permissive
Topics: cpp, icp, multi-threading, pcl, pointcloud, python, registration, scan-matching, point-cloud-regstration, open3d
Last push: 2026-08-31T06:28:08+00:00

## Health v2 (maintenance only)
Score: 60/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 100, release rhythm 8, longevity 63
- inputs: {"age_days": 894, "days_push": 2, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1023, forks 129 (observed 2026-09-01T02:14:03.530331+00:00)

## What it is
small_gicp is a header-only C++ library with Python bindings for fast, parallelized point cloud registration algorithms including ICP, Point-to-Plane ICP, GICP, and VGICP. It is an optimized rewrite of fast_gicp with minimal dependencies (Eigen, bundled nanoflann and Sophus) and OpenMP/Intel TBB parallelism backends.

## Use cases
- align two 3d point clouds with icp in c++
- fast gicp scan matching for lidar slam
- python point cloud registration with open3d
- drop-in replacement for pcl iterative closest point
- parallel kd-tree construction and point cloud downsampling
- register 3d scans for robotics odometry
- multithreaded point cloud alignment library

## When to choose
- you need CPU-based point cloud registration with high performance and parallelism
- you want minimal dependencies and a header-only C++ integration
- you need Python bindings that work with Open3D without PCL
- you want a customizable registration pipeline via traits and templates

## When to avoid
- you need GPU-accelerated registration - this package has no GPU implementations
- you require coarse/global registration rather than fine local alignment
- your project is not C++ or Python

## Facets
- artifact type: library
- maturity: active
- function: computer-vision, image-processing, math, concurrency
- domain: robotics, computer-vision, autonomous-vehicles
- platform: cpp, python, windows, cross-platform
- tags: point-cloud-registration, icp, gicp, scan-matching, lidar, slam, header-only, openmp, tbb, pcl, open3d, kd-tree, algorithms, linux, macos

## Member repositories
- koide3/small_gicp (main) score 60

## Provenance
- Observed fields: from GitHub, fetched 2026-09-01T02:14:03.530331+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 2026-08-30T07:09:29.280387+00:00, confidence not recorded.
  - readme: https://github.com/koide3/small_gicp (fetched 2026-09-01T02:14:03.530331+00:00, sha b263e9f42cbd)
- Data as of 2026-08-30T08:39:29.467469+00:00.