StevenCui/VIO-Doc resource
主流VIO论文推导及代码解析 observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2862
- days_rel: n/a
- days_push: 2610
- n_releases_24m: 0
Adoption not part of the score
1046 stars · 299 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
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
learning-resource · maturity maintenance
documentation simulation robotics autonomous-vehicles tutorials vio slam visual-inertial-odometry factor-graph msckf vins rovio ice-ba state-estimation paper-derivations chinese algorithms
1 source
- readme: https://github.com/StevenCui/VIO-Doc · fetched 2026-08-28 · 8a706878a675
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| StevenCui/VIO-Doc | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="StevenCui/VIO-Doc")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem