# yanyan-li/SLAM-BOOK

这是一本关于SLAM的书稿，希望能清楚的介绍SLAM系统中的使用的几何方法和深度学习方法。书稿最后应该会达到200页左右，书稿每章对应的代码也会被整理出来。

Repository: https://github.com/yanyan-li/SLAM-BOOK
Canonical: https://ross.abutalabs.com/products/slam-book
Language: Python
License Family: other
Topics: slam
Last push: 2024-07-20T14:57:03+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2310, "days_push": 774, "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 1088, forks 165 (observed 2026-08-28T04:03:32.461610+00:00)

## What it is
An open book draft (in Chinese) explaining geometric and deep learning methods used in SLAM systems, with accompanying code per chapter. It covers topics like multi-view geometry and learning-based pose estimation, targeting roughly 200 pages when complete.

## Use cases
- learn SLAM from scratch
- understand geometric vs deep learning approaches to SLAM
- study multi-view geometry for visual odometry
- find code examples accompanying a SLAM textbook
- learn how deep learning is integrated into SLAM systems

## When to choose
- you want a structured, textbook-style introduction to SLAM covering both classical geometry and deep learning
- you read Chinese and want free educational material with per-chapter code
- you are a student or researcher entering visual SLAM

## When to avoid
- you need a production-ready SLAM library or framework
- you need English-language material
- you need a complete, finished book - only the first few chapters are available
- you need permissively licensed code - it is CC BY-NC-SA (non-commercial)

## Facets
- artifact type: learning-resource
- maturity: experimental
- function: machine-learning, computer-vision, simulation
- domain: robotics, computer-vision, tutorials, deep-learning
- platform: python, cross-platform
- tags: slam, book, visual-slam, multi-view-geometry, deep-learning, robotics, educational

## Member repositories
- yanyan-li/SLAM-BOOK (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:32.461610+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 2026-08-30T06:49:23.976899+00:00, confidence not recorded.
  - readme: https://github.com/yanyan-li/SLAM-BOOK (fetched 2026-08-28T04:03:32.461610+00:00, sha 83f7cb189111)
- Data as of 2026-08-30T08:39:29.467469+00:00.