# TixiaoShan/LVI-SAM

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

Repository: https://github.com/TixiaoShan/LVI-SAM
Canonical: https://ross.abutalabs.com/products/lvi-sam
Homepage: https://youtu.be/8CTl07D6Ibc
Language: C++
License: BSD-3-Clause
License Family: permissive
Topics: lidar-odometry, visual-odometry
Last push: 2022-12-17T15:34:36+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2009, "days_push": 1355, "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 1875, forks 512 (observed 2026-08-28T04:05:47.703324+00:00)

## What it is
LVI-SAM is a tightly-coupled Lidar-Visual-Inertial Odometry and mapping system implemented in C++ on ROS, combining LIO-SAM and VINS-Mono at the system level. It fuses lidar, camera, and IMU data via factor-graph smoothing and mapping (GTSAM and Ceres) for real-time state estimation.

## Use cases
- estimate robot trajectory from lidar, camera, and IMU data
- build 3D maps while localizing a mobile robot or handheld sensor rig
- run odometry on rosbag datasets from a Velodyne VLP-16 and camera/IMU suite
- fuse visual-inertial and lidar-inertial odometry for robust SLAM
- benchmark SLAM algorithms on public handheld and ground-robot datasets

## When to choose
- you need robust odometry and mapping fusing lidar, camera, and IMU in a ROS pipeline
- your platform has all three sensor types and you want a proven, well-cited system
- you want a factor-graph SLAM baseline built on GTSAM and Ceres

## When to avoid
- you only have a camera and IMU without lidar (use VINS-Mono instead)
- you need a maintained project with recent updates and support for newer ROS versions
- you need a pure lidar-inertial solution (use LIO-SAM instead)

## Facets
- artifact type: application
- maturity: maintenance
- function: simulation, computer-vision, graphics
- domain: robotics, autonomous-vehicles, computer-vision
- platform: cpp
- tags: slam, lidar-odometry, visual-odometry, sensor-fusion, ros, gtsam, ceres-solver, state-estimation, linux

## Member repositories
- TixiaoShan/LVI-SAM (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:47.703324+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 2026-08-30T03:14:45.859783+00:00, confidence not recorded.
  - readme: https://github.com/TixiaoShan/LVI-SAM (fetched 2026-08-28T04:05:47.703324+00:00, sha 30ec90f4b2c1)
  - homepage: https://youtu.be/8CTl07D6Ibc (fetched 2026-08-29T10:53:35.548985+00:00, sha f6713b240296)
- Data as of 2026-08-30T08:39:29.467469+00:00.