# AlbertSlam/Lee-SLAM-source

SLAM 开发学习资源与经验分享

Repository: https://github.com/AlbertSlam/Lee-SLAM-source
Canonical: https://ross.abutalabs.com/products/lee-slam-source
License Family: other
Last push: 2024-03-31T07:24:09+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": 3448, "days_push": 885, "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 1164, forks 950 (observed 2026-08-28T04:03:49.813991+00:00)

## What it is
A curated awesome-list of SLAM (Simultaneous Localization and Mapping) learning resources, including tutorials, books, video courses, blogs, and open-source SLAM solutions. It is aimed at helping learners progress from beginner fundamentals to advanced SLAM development.

## Use cases
- find resources to learn SLAM from scratch
- get a structured learning path for visual SLAM
- find SLAM books and video lectures
- discover open-source SLAM implementations and solutions
- learn the math foundations behind SLAM like Lie groups and quaternions
- find tutorials on building a SLAM system step by step

## When to choose
- you are starting to learn SLAM and need curated beginner-to-advanced material
- you want a single index of SLAM courses, books, and blogs
- you are a robotics student looking for visual SLAM study guides

## When to avoid
- you need a ready-to-run SLAM library or algorithm implementation
- you need up-to-date research papers on the latest SLAM methods
- you need LiDAR-specific or production-grade SLAM tooling

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools, documentation
- domain: robotics, tutorials, awesome-lists, computer-vision
- platform: cross-platform
- tags: slam, awesome-list, robotics, visual-slam, learning-path, tutorials, state-estimation

## Member repositories
- AlbertSlam/Lee-SLAM-source (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:49.813991+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 2026-08-30T06:29:29.275738+00:00, confidence not recorded.
  - readme: https://github.com/AlbertSlam/Lee-SLAM-source (fetched 2026-08-28T04:03:49.813991+00:00, sha 8d3d0364b470)
- Data as of 2026-08-30T08:39:29.467469+00:00.