RoboMIND Dataset
Multi-embodiment demonstrations with explicit failures
A unified multi-embodiment manipulation dataset with successful demonstrations, real-world failures, and failure causes.
Failure mining
One of the strongest current matches for OpenBot loop-signal analysis.
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, action/state, and feedback-like supervision.
fit 88 · 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 · Video
Action / hand pose / robot state
actions · robot state · A unified multi-embodiment manipulation dataset with successful demonstrations, real-world failures, and failure causes.
Gaze / attention
No decision-grade evidence captured yet.
Language intent / task phase
language · task phase
Feedback / correction / failure
failure · Failure mining · Correction-aware policy learning · Multi-embodiment demonstrations with explicit failures
Sim-real pairing
No decision-grade evidence captured yet.
License / format / access
Open · HDF5 · Video
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, action/state, and feedback-like supervision.
fit 88 · confidence 55
Has failure/evaluation-style labels with action or manipulation context.
fit 82 · confidence 55
Good tasks
Blockers and unresolved evidence
- Gaze / attentionunknownNot 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
- Failure mining
- VLA training
- Correction-aware policy learning
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-VLA 2.0
A whole-body VLA release focused on broader cross-embodiment transfer, mobile manipulation, and predictive dynamics supervision.
X-VLA
A 0.9B soft-prompted VLA that adapts a shared backbone across heterogeneous embodiments and action spaces.
Integration notes
- One of the strongest current matches for OpenBot loop-signal analysis.