---
title: 'Open X-Embodiment: Robotic Learning Datasets and RT-X Models'
license: CC-BY-4.0
license_url: https://creativecommons.org/licenses/by/4.0/
license_note: 'paper is CC BY 4.0 (verified on arXiv abs page 2026-11-11; icon by-4.0.png, http://creativecommons.org/licenses/by/4.0/); note is our own summary'
source: https://iinventedlight.com/library/notes/2310-08864-open-x-embodiment.md
source_license: 'CC BY 4.0'
attribution: 'Summary by iinventedlight (AI-assisted). Source: Open X-Embodiment Collaboration, Open X-Embodiment: Robotic Learning Datasets and RT-X Models (CC BY 4.0). Authors are listed on the arXiv abs page.'
author: 'iinventedlight (AI-assisted)'
date: 2026-11-11
status: published
approved_by: "Cole Withington, 2026-11-11 20:58 PT, Grok Bot chat widget t1717s7407: \"Publish all 100 including the LLMs Encode Clinical Knowledge note\""
checked_on: 2026-11-11
as_of: 2026-11-11
confidence: medium
untested: 'Not reproduced. Abs page and HTML key sections read 2026-11-11. Named project URL checked for HTTP 200; code and models not run.'
category: arxiv
topic_area: 'ai-research: AI-for-science'
tags: arxiv, robotics, datasets, foundation-models
arxiv_id: 2310.08864
alias: 2310.08864-open-x-embodiment
sources:
  - id: S1
    title: 'Open X-Embodiment: Robotic Learning Datasets and RT-X Models'
    publisher: arXiv
    authors: 'Open X-Embodiment Collaboration (authors listed on the arXiv abs page)'
    url: https://arxiv.org/abs/2310.08864
    version_read: 'v9 (14 May 2025)'
    accessed: 2026-11-11
    license: 'CC BY 4.0'
---
# Open X-Embodiment: Robotic Learning Datasets and RT-X Models

## Summary
This paper provides datasets in standardized formats and models so the field can train generalist X-robot policies, adapted to new robots, tasks, and environments. The authors assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). Later they also describe the repository as pooling 60 existing robot datasets and containing 1M+ real robot trajectories spanning 22 robot embodiments. A high-capacity model trained on this data, which they call RT-X (with RT-1-X and RT-2-X variants), shows positive transfer across robots. More details can be found on the project website, robotics-transformer-x.github.io. [S1]

## Claims
- id: C1
  claim: 'The dataset comes from 22 robots collected across 21 institutions.'
  source: S1
  evidence: "22 different robots collected through a collaboration between 21 institutions"
- id: C2
  claim: 'The authors report 527 skills (160266 tasks) in the assembled dataset.'
  source: S1
  evidence: "demonstrating 527 skills (160266 tasks)"
- id: C3
  claim: 'The project website is given as robotics-transformer-x.github.io.'
  source: S1
  evidence: "The project website is robotics-transformer-x.github.io"

## Verification
- Code available: Paper: the project website https://robotics-transformer-x.github.io/, which returned HTTP 200 on 2026-11-11. Models and data were not downloaded or run.
- Reproduced: not reproduced (2026-11-11). Code not run.
- Related work: Live notes [ao-evals-multimodal-agents](https://iinventedlight.com/library/notes/ao-evals-multimodal-agents/).
- Limits: Training mixtures used in the reported experiments use fewer embodiments than the full repository, and the discussion section lists open problems in cross-robot transfer and evaluation.
- License: CC BY 4.0 on the abs page (2026-11-11; icon by-4.0.png; http://creativecommons.org/licenses/by/4.0/). Submitted 13 Oct 2023 (v1); last revised 14 May 2025 (v9). Sources: [S1] https://arxiv.org/abs/2310.08864, v9 (14 May 2025). checked_on: 2026-11-11.

## When to apply
Use when asking what the Open X-Embodiment dataset contains and how the RT-X models were trained across many robot platforms.

## Facts
- id: F1
  claim: 'The assembled dataset comes from 22 robots and 21 institutions, with 527 skills (160266 tasks).'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F2
  claim: 'The authors also describe the repository as pooling 60 existing datasets and more than 1M real robot trajectories across 22 embodiments.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F3
  claim: 'RT-X is the name they give the high-capacity model trained on this data; the project site is robotics-transformer-x.github.io.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0

## Sources
- [S1] arXiv 2310.08864, https://arxiv.org/abs/2310.08864. License: CC BY 4.0. v9 (14 May 2025). Accessed 2026-11-11.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted). Paper is CC BY 4.0.

---

Agents: [/agents.md](/agents.md) | [/.well-known/agent-library.json](/.well-known/agent-library.json).