# StevenCui/VIO-Doc

主流VIO论文推导及代码解析

Repository: https://github.com/StevenCui/VIO-Doc
Canonical: https://ross.abutalabs.com/products/vio-doc
License Family: other
Topics: ice-ba, factor-graph, slam, vio
Last push: 2019-07-11T03:35:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2862, "days_push": 2610, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1046, forks 299 (observed 2026-08-28T04:03:21.611249+00:00)

## What it is
A Chinese-language documentation collection deriving the math and analyzing the code of mainstream visual-inertial odometry (VIO) systems, covering VINS, MSCKF, ICE-BA, and ROVIO. It serves as a study resource for understanding SLAM state estimation via factor graphs and filtering methods.

## Use cases
- learn how VINS factor graph optimization works
- understand MSCKF filter derivations
- study ICE-BA incremental smoothing algorithm
- compare ROVIO and VINS approaches
- prepare for SLAM research or interviews
- accompany reading VIO source code

## When to choose
- studying visual-inertial odometry theory and derivations
- needing Chinese-language explanations of VIO papers
- working through VINS/MSCKF/ROVIO codebases

## When to avoid
- needing a runnable VIO library or production software
- requiring English-language documentation
- seeking maintained code with a license

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, simulation
- domain: robotics, autonomous-vehicles, tutorials
- platform: -
- tags: vio, slam, visual-inertial-odometry, factor-graph, msckf, vins, rovio, ice-ba, state-estimation, paper-derivations, chinese, algorithms

## Member repositories
- StevenCui/VIO-Doc (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:21.611249+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 2026-08-30T07:01:55.958145+00:00, confidence not recorded.
  - readme: https://github.com/StevenCui/VIO-Doc (fetched 2026-08-28T04:03:21.611249+00:00, sha 8a706878a675)
- Data as of 2026-08-30T08:39:29.467469+00:00.