# BaiShuanghao/Awesome-Robotics-Manipulation

A comprehensive list of papers about Robot Manipulation, including papers, codes, and related websites.

Repository: https://github.com/BaiShuanghao/Awesome-Robotics-Manipulation
Canonical: https://ross.abutalabs.com/products/awesome-robotics-manipulation
Homepage: https://arxiv.org/abs/2510.10903
License: MIT
License Family: permissive
Topics: robot-manipulation, diffusion-policy, grasping, imitation-learning, vision-language-action-model, input-modeling, policy-learning, latent-learning
Last push: 2026-08-25T11:39:57+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 48
- inputs: {"age_days": 679, "days_push": 8, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1098, forks 62 (observed 2026-08-28T04:03:34.891536+00:00)

## What it is
A curated awesome-list of research papers, code, benchmarks, and datasets on robot manipulation, accompanying a comprehensive T-RO survey. It covers learning-based policy learning, grasping, imitation learning, and vision-language-action models alongside non-learning control methods.

## Use cases
- find papers on robot manipulation
- survey imitation learning methods for robotic grasping
- find benchmarks and datasets for manipulation research
- learn about vision-language-action models
- get started researching robot learning
- find code implementations of diffusion policy

## When to choose
- starting literature review on robot manipulation
- looking for datasets, simulators, or benchmarks for manipulation
- tracking recent learning-based manipulation research

## When to avoid
- you need runnable software rather than a paper list
- you need non-robotics machine learning resources

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: robotics, artificial-intelligence, machine-learning, awesome-lists
- platform: cross-platform
- tags: awesome-list, robot-manipulation, grasping, imitation-learning, vision-language-action, survey, papers, diffusion-policy

## Member repositories
- BaiShuanghao/Awesome-Robotics-Manipulation (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:34.891536+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 2026-08-30T06:46:12.250896+00:00, confidence not recorded.
  - readme: https://github.com/BaiShuanghao/Awesome-Robotics-Manipulation (fetched 2026-08-28T04:03:34.891536+00:00, sha 983e000e2623)
  - homepage: https://arxiv.org/abs/2510.10903 (fetched 2026-08-29T12:49:46.611368+00:00, sha f788e20eb199)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T12:49:46.614016+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T12:49:46.618085+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T12:49:46.620111+00:00, sha a1f16f915a9a)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T12:49:46.615922+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.