Robotics Notebooks — Chinese-language robotics tech stack map and learning index

TL;DR

A Chinese-language (“机器人技术栈地图”) curated learning index for robotics, maintained by Chong Liu. The site organizes robotics knowledge along four axes — 路线 (roadmaps), 图谱 (concept graphs), 模块 (modules), and 论文 (papers) — and ranks entries by in-site cross-link degree so readers start from the most-connected pages. It’s a navigational resource, not a paper.

Key claims

The site is organized as an entry-point map with four navigation axes: roadmaps, concept graphs, modules, and papers, letting a reader choose the shortest path to their current goal rather than absorbing the whole graph up front [landing page].
Entries are ordered by total undirected in-site link degree — the most cross-linked pages surface first, treating connectivity as a proxy for centrality in the robotics stack [landing page ranking blurb].

Method

The site is a static learning-index that uses cross-link density as a navigation heuristic. Content is Chinese-language; the visible landing page enumerates the four navigation axes and promises a “top list” (完整榜单) of most-connected pages. The internal roadmap/module/paper inventory itself was not loaded at fetch time (the landing page shows “加载中…” placeholders where dynamic content mounts), so the depth and scope of the collection can’t be assessed from the landing page alone.

Results

Not applicable — this is a resource directory, not an experimental artifact. No benchmarks reported.

Why it’s interesting

Fits into the small but growing set of curated robotics learning / dataset directories the wiki has been tracking — cf. TrueLabel — Physical AI Dataset Directory: Robotics, Humanoid & Egocentric Data for physical-AI datasets and datasets.bot — Curated catalog of robotics and embodied-AI training datasets for a robotics/embodied-AI dataset catalog. Where those two catalog data, Robotics_Notebooks catalogs concepts and papers along a tech-stack map, so it complements them rather than duplicates them. Cross-link-degree as a navigation heuristic is also worth noting — a lightweight version of the same principle Bud’s concept clusters use.