# xioTechnologies/Fusion

Repository: https://github.com/xioTechnologies/Fusion
Canonical: https://ross.abutalabs.com/products/xiotechnologies-fusion
Language: C
License: MIT
License Family: permissive
Last push: 2026-08-21T07:17:26+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 1617, "days_push": 12, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1719, forks 367 (observed 2026-08-28T04:05:26.538346+00:00)

## What it is
Fusion is a C library for sensor fusion on Inertial Measurement Units (IMUs), implementing an AHRS algorithm that combines gyroscope, accelerometer, and magnetometer data into orientation estimates. It is optimised for embedded systems and also available as the Python package imufusion.

## Use cases
- fuse imu sensor data into orientation estimates
- compute attitude and heading from gyroscope accelerometer and magnetometer
- track device orientation on embedded microcontrollers
- estimate orientation using only gyroscope and accelerometer
- combine gps heading with imu data
- analyze imu sensor data in python

## When to choose
- you need efficient AHRS orientation estimation on embedded systems
- you want a lightweight C sensor fusion library with a Python wrapper
- you need flexible sensor combinations including gyro-only or gyro plus external heading

## When to avoid
- you need full SLAM or visual-inertial odometry
- you require Kalman-filter-based fusion with covariance outputs
- your project is not in C or Python

## Facets
- artifact type: library
- maturity: stable
- function: simulation, math, sdk
- domain: embedded-systems, robotics, hardware
- platform: c, python, embedded, cross-platform
- tags: imu, sensor-fusion, ahrs, attitude-estimation, madgwick, gyroscope, accelerometer, magnetometer, algorithms

## Member repositories
- xioTechnologies/Fusion (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:26.538346+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 2026-08-30T03:34:08.947119+00:00, confidence not recorded.
  - readme: https://github.com/xioTechnologies/Fusion (fetched 2026-08-28T04:05:26.538346+00:00, sha 6f8756b10de3)
- Data as of 2026-08-30T08:39:29.467469+00:00.