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Mobile Robots datasetOpenReadiness 73/100Provisional

RT-1 Robot Action Dataset

The RT-1 robot action dataset (fractal20220817data in Open X-Embodiment) contains 87,212 human-teleoperated demonstration episodes of tabletop manipulation with 17 objects, collected on Google's Everyday Robots mobile…

Source notes

The RT-1 robot action dataset (fractal20220817_data in Open X-Embodiment) contains 87,212 human-teleoperated demonstration episodes of tabletop manipulation with 17 objects, collected on Google's Everyday Robots mobile manipulators. Each step pairs an RGB image and natural-language instruction with a discretized arm+base action, plus success/feasible/undesirable labels, stored in RLDS/TFDS format.

Scale
350.6 hours
Formats
rlds
License
CC-BY-4.0
Published
2022-12-13
Official sourceAll recordsDataset index A–ZRun local preflightRequest scoped audit

Decision summary

Best for

teleoperation

Main blocker

Metadata requires review against the official source before publication.

Next check

Read the dataset manifest and feature schema.

Release history

Source-backed release timing for this canonical dataset record.

Important releases

  1. Dataset series published

    Release timing is recorded from official dataset metadata.

    Release evidence

Selection readiness

6 evidence dimensions for deciding whether this dataset is ready to inspect, compare, or adopt. This is not a model benchmark.

Catalog evidence · not task performance

How scores work

73/100

Provisional

4/6 dimensions scored · 48% confidence

Access and governance75conf. 85
Schema and signal coverageNot scoredconf. 15
Policy training readiness85conf. 55
World-model readiness68conf. 50
Failure and recovery readinessNot scoredconf. 15
Download and processing readiness65conf. 65
Read the evidence behind all 6 dimensions

Access and governance

Access and license are declared by the source.

usefulfit 75 · confidence 85

Schema and signal coverage

No machine-readable schema has been verified yet.

unknownnot scored · confidence 15

Policy training readiness

Observation and action/state signals are declared; alignment quality still depends on sample verification.

usefulfit 85 · confidence 55

World-model readiness

Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.

usefulfit 68 · confidence 50

Failure and recovery readiness

No verified failure/recovery annotation evidence is available yet.

unknownnot scored · confidence 15

Download and processing readiness

Scale is declared; transfer and processing estimates are not measured.

usefulfit 65 · confidence 65
Review unresolved evidence and next checks

Signal gaps

  • Gaze / attention. Not enough evidence is available to classify this signal.
  • Feedback / correction / failure. Not enough evidence is available to classify this signal.
  • Sim-real pairing. Not enough evidence is available to classify this signal.

Next checks

  • Read the dataset manifest and feature schema.
  • Run a bounded sample audit before assigning Strong readiness.
Engineering checks (OBRS) behind this record
Engineering checksBronze

Needs Audit

5/12checks passed

OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.

Standardization & Loaders15 / 25 pt
Physical & Action Quality2 / 25 pt
Semantic & Annotation20 / 20 pt
Real-World Validation0 / 15 pt
License & Compliance10 / 15 pt
Missing evidence and readiness gaps
  • A passing real-hardware test report is required.
  • A passing ingestion/pipeline test report is required.
  • A passing privacy and provenance review is required.

Dataset facts

Source
Google (Robotics at Google / Everyday Robots)
Evidence
secondary claim
Formats
rlds
episodes
87.2K
hours
350.6
tasks
599
Read paper

Loop signals

4/7 present or partial

Gaze / attention

No decision-grade evidence captured yet.

unknown
Feedback / correction / failure

No decision-grade evidence captured yet.

unknown
View 5 more signal categories
Observation / ego video

video · The RT-1 robot action dataset (fractal20220817_data in Open X-Embodiment) contains 87,212 human-teleoperated demonstration episodes of tabletop manipulation with 17 objects, collected on Google's Everyday Robots mobile manipulators. Each step pairs an RGB image and natural-language instruction with a discretized arm+base action, plus success/feasible/undesirable labels, stored in RLDS/TFDS format.

present
Action / hand pose / robot state

ee_pose · The RT-1 robot action dataset (fractal20220817_data in Open X-Embodiment) contains 87,212 human-teleoperated demonstration episodes of tabletop manipulation with 17 objects, collected on Google's Everyday Robots mobile manipulators. Each step pairs an RGB image and natural-language instruction with a discretized arm+base action, plus success/feasible/undesirable labels, stored in RLDS/TFDS format.

partial
Language intent / task phase

language · has-success-labels · The RT-1 robot action dataset (fractal20220817_data in Open X-Embodiment) contains 87,212 human-teleoperated demonstration episodes of tabletop manipulation with 17 objects, collected on Google's Everyday Robots mobile manipulators. Each step pairs an RGB image and natural-language instruction with a discretized arm+base action, plus success/feasible/undesirable labels, stored in RLDS/TFDS format.

present
Sim-real pairing

No decision-grade evidence captured yet.

unknown
License / format / access

Open · CC-BY-4.0 · rlds

present
Evidence details and provenance

Official signal claims

Ee_poseLanguageProprioceptionVideo

Schema and annotations

No machine-readable schema facts are captured.

Sample verification

Pending. Metadata does not prove sample coverage, alignment, or file integrity.

curated official source

Integration notes

  • Metadata requires review against the official source before publication.