OpenBot
Platform
Manipulation datasetOpen
OBRS 34•Bronze

DexMimicGen

DexMimicGen is an automated data-generation system that synthesizes large-scale trajectory datasets for bimanual dexterous manipulation from a handful of human teleoperation demonstrations.

Source notes

DexMimicGen is an automated data-generation system that synthesizes large-scale trajectory datasets for bimanual dexterous manipulation from a handful of human teleoperation demonstrations. It generated over 21,000 demonstrations from 60 source human demos across 9 simulation tasks in robosuite/MuJoCo, spanning three embodiments (bimanual Panda arms with parallel-jaw grippers, bimanual Panda arms with dexterous hands, and a Fourier GR-1 humanoid with Inspire dexterous hands), and includes a Real2Sim2Real pipeline validated on a real GR-1 robot.

Scale
64.3 GB size
Formats
hdf5
License
CC-BY-NC-4.0
Published
2024-10-31
Official sourceAll recordsDataset index A–ZRun local preflightRequest scoped audit

Decision summary

Best for

scripted

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

63/100

Provisional

4/6 dimensions scored · 48% confidence

Access and governance35conf. 85
Schema and signal coverageNot scoredconf. 15
Policy training readiness70conf. 55
World-model readiness82conf. 50
Failure and recovery readinessNot scoredconf. 15
Download and processing readiness65conf. 65
Read the evidence behind all 6 dimensions

Access and governance

The declared license restricts commercial use.

limitedfit 35 · 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 70 · confidence 55

World-model readiness

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

usefulfit 82 · 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.

Next checks

  • Read the dataset manifest and feature schema.
  • Run a bounded sample audit before assigning Strong readiness.

Dataset facts

Source
NVIDIA Research (with UT Austin and UC San Diego)
Evidence
secondary claim
Formats
hdf5
episodes
21K
tasks
9
size
64.3 GB
Read paper

Loop signals

5/7 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

depth · video

present
Action / hand pose / robot state

ee_pose · DexMimicGen is an automated data-generation system that synthesizes large-scale trajectory datasets for bimanual dexterous manipulation from a handful of human teleoperation demonstrations. It generated over 21,000 demonstrations from 60 source human demos across 9 simulation tasks in robosuite/MuJoCo, spanning three embodiments (bimanual Panda arms with parallel-jaw grippers, bimanual Panda arms with dexterous hands, and a Fourier GR-1 humanoid with Inspire dexterous hands), and includes a Real2Sim2Real pipeline validated on a real GR-1 robot.

present
Language intent / task phase

DexMimicGen is an automated data-generation system that synthesizes large-scale trajectory datasets for bimanual dexterous manipulation from a handful of human teleoperation demonstrations. It generated over 21,000 demonstrations from 60 source human demos across 9 simulation tasks in robosuite/MuJoCo, spanning three embodiments (bimanual Panda arms with parallel-jaw grippers, bimanual Panda arms with dexterous hands, and a Fourier GR-1 humanoid with Inspire dexterous hands), and includes a Real2Sim2Real pipeline validated on a real GR-1 robot.

partial
Sim-real pairing

depth · simulation · DexMimicGen is an automated data-generation system that synthesizes large-scale trajectory datasets for bimanual dexterous manipulation from a handful of human teleoperation demonstrations. It generated over 21,000 demonstrations from 60 source human demos across 9 simulation tasks in robosuite/MuJoCo, spanning three embodiments (bimanual Panda arms with parallel-jaw grippers, bimanual Panda arms with dexterous hands, and a Fourier GR-1 humanoid with Inspire dexterous hands), and includes a Real2Sim2Real pipeline validated on a real GR-1 robot.

present
License / format / access

Open · CC-BY-NC-4.0 · hdf5

partial
Evidence details and provenance

Official signal claims

DepthEe_poseProprioceptionVideo

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.