Open X-Embodiment Dataset
Cross-embodiment robot learning in a unified format
A large multi-institution collection spanning 22 robot embodiments and hundreds of skills for cross-robot policy learning.
Cross-embodiment VLA pretraining
Licenses differ across constituent datasets and must be checked individually.
Inspect schema and run a bounded sample audit before committing to the full release.
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has rich observation and semantic context, but limited geometry/sim-real alignment.
fit 68 · confidence 55
Contains observation, intent, and action/state, but feedback/correction signal is weak.
fit 72 · confidence 55
Verified facts and provenance
Claims, metadata verification, and sample verification are shown separately.
Unknown — no machine-readable schema facts have been captured.
Unknown — metadata conclusions do not prove sample coverage, alignment, or file integrity.
Declared loop signal coverage
Signals inferred from official metadata; Data pipeline verification is still pending.
Observation / ego video
video
Action / hand pose / robot state
actions · robot state
Gaze / attention
No decision-grade evidence captured yet.
Language intent / task phase
language · task phase
Feedback / correction / failure
No decision-grade evidence captured yet.
Sim-real pairing
No decision-grade evidence captured yet.
License / format / access
Open · Dataset-specific; code Apache-2.0 · RLDS · TensorFlow Datasets
Model and task fit · OpenBot inference
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has rich observation and semantic context, but limited geometry/sim-real alignment.
fit 68 · confidence 55
Contains observation, intent, and action/state, but feedback/correction signal is weak.
fit 72 · confidence 55
Failure, correction, intervention, and recovery annotations have not been verified.
fit 50 · confidence 15
Good tasks
Blockers and unresolved evidence
- Gaze / attentionunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
- Feedback / correction / failureunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
- Sim-real pairingunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
Raw dataset signals
OpenBot fit
- Cross-embodiment VLA pretraining
- Policy transfer
- Dataset mixture analysis
Related models and papers
Model references linked to similar loop signals.
LingBot-VLA
A 4B pragmatic VLA foundation model pretrained on roughly 20,000 hours of real-world data from nine dual-arm robot configurations.
LingBot-VA
An autoregressive video-action world-model policy that interleaves future video-latent prediction with robot action generation.
pi0.5
A VLA model designed for open-world generalization by combining heterogeneous robot data, semantic subtask prediction, and high-level knowledge transfer.
Gemini Robotics 1.5
An agentic robotics model combining advanced multimodal reasoning with vision-language-action control for multi-step physical tasks.
Galaxea G0
A dual-system VLM plus VLA model for planning and fine-grained control on long-horizon mobile-manipulation tasks.
StarVLA
A modular, MIT-licensed VLA development stack with multiple VLM backbones, model scales, and dataset integrations.
Integration notes
- Licenses differ across constituent datasets and must be checked individually.