# hku-mars/FAST-LIVO2

FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry

Repository: https://github.com/hku-mars/FAST-LIVO2
Canonical: https://ross.abutalabs.com/products/fast-livo2
Language: C++
License: GPL-2.0
License Family: copyleft
Topics: 3d-reconstruction, colored-point-cloud, gaussian-splatting, lidar-camera-fusion, lidar-inertial-odometry, lidar-slam, mesh-reconstruction, nerf, sensor-fusion, slam
Last push: 2026-03-08T15:40:36+00:00

## Health v2 (maintenance only)
Score: 56/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 71, release rhythm 35, longevity 61
- inputs: {"age_days": 863, "days_push": 178, "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 4557, forks 844 (observed 2026-08-28T04:08:53.367120+00:00)

## What it is
FAST-LIVO2 is a fast, tightly-coupled LiDAR-inertial-visual odometry and mapping system written in C++ on ROS. It provides real-time, accurate localization and colored 3D reconstruction, suitable for onboard robotic use in degraded environments.

## Use cases
- real-time lidar-inertial-visual odometry for drones and robots
- colored 3D point cloud mapping from lidar and camera
- localization in degraded environments like tunnels or darkness
- building datasets for NeRF or gaussian splatting reconstruction
- onboard SLAM for resource-constrained platforms
- mesh reconstruction from fused sensor data

## When to choose
- you need accurate real-time odometry fusing lidar, IMU, and camera
- you want colored point clouds or 3D reconstruction output from a SLAM system
- you run ROS on Ubuntu with a supported Livox or similar lidar setup
- you need onboard localization on resource-constrained hardware

## When to avoid
- you need a pure visual SLAM without lidar
- you are not using ROS or Linux
- you need a plug-and-play solution without sensor calibration and synchronization
- your project requires a permissive license (GPL-2.0)

## Facets
- artifact type: library
- maturity: active
- function: robotics, computer-vision, graphics, simulation, sdk
- domain: robotics, autonomous-vehicles, computer-vision, simulation
- platform: cpp
- tags: slam, lidar, odometry, sensor-fusion, 3d-reconstruction, point-cloud, nerf, gaussian-splatting, localization, mapping, algorithms, linux, ros

## Member repositories
- hku-mars/FAST-LIVO2 (main) score 56

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:53.367120+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 2026-08-29T18:20:01.935800+00:00, confidence not recorded.
  - readme: https://github.com/hku-mars/FAST-LIVO2 (fetched 2026-08-28T04:08:53.367120+00:00, sha 30e4cb594dc5)
- Data as of 2026-08-30T08:39:29.467469+00:00.