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Manipulation datasetOpen

robomimic

robomimic is a framework and dataset suite for robot learning from demonstration, released with the CoRL 2021 study 'What Matters in Learning from Offline Human Demonstrations for Robot Manipulation' (Mandlekar et al.). It provides teleoperated human and machine-generated demonstrations on five simulated robosuite/MuJoCo tasks (Lift, Can, Square, Transport, Tool Hang) using the Franka Panda robot (Transport is dual-arm), plus three real-world Franka Panda tasks. Data is distributed as HDF5 with low-dim, image, and raw variants, and includes RGB camera views, proprioception, end-effector pose, and object state.

Scale
8 tasks
Formats
hdf5 · rlds
License
MIT
Published
2021-08-06

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.

Catalog assessment

Selection evidence

70/100

Provisional · confidence 42 · 3/6 evaluated

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 70 · confidence 55
View 3 more dimensions

World-model readiness

World-model observation, geometry, or temporal semantics are not verified.

unknownnot scored · confidence 15

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.

Record specifics

Dataset facts

Source
Stanford Vision and Learning Lab / ARISE Initiative
Evidence
secondary claim
Formats
hdf5 · rlds
tasks
8
bytes
7322820280
Read paper

Metadata coverage

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

video · robomimic is a framework and dataset suite for robot learning from demonstration, released with the CoRL 2021 study 'What Matters in Learning from Offline Human Demonstrations for Robot Manipulation' (Mandlekar et al.). It provides teleoperated human and machine-generated demonstrations on five simulated robosuite/MuJoCo tasks (Lift, Can, Square, Transport, Tool Hang) using the Franka Panda robot (Transport is dual-arm), plus three real-world Franka Panda tasks. Data is distributed as HDF5 with low-dim, image, and raw variants, and includes RGB camera views, proprioception, end-effector pose, and object state.

present
Action / hand pose / robot state

ee_pose · robomimic is a framework and dataset suite for robot learning from demonstration, released with the CoRL 2021 study 'What Matters in Learning from Offline Human Demonstrations for Robot Manipulation' (Mandlekar et al.). It provides teleoperated human and machine-generated demonstrations on five simulated robosuite/MuJoCo tasks (Lift, Can, Square, Transport, Tool Hang) using the Franka Panda robot (Transport is dual-arm), plus three real-world Franka Panda tasks. Data is distributed as HDF5 with low-dim, image, and raw variants, and includes RGB camera views, proprioception, end-effector pose, and object state.

partial
Language intent / task phase

has-success-labels · robomimic is a framework and dataset suite for robot learning from demonstration, released with the CoRL 2021 study 'What Matters in Learning from Offline Human Demonstrations for Robot Manipulation' (Mandlekar et al.). It provides teleoperated human and machine-generated demonstrations on five simulated robosuite/MuJoCo tasks (Lift, Can, Square, Transport, Tool Hang) using the Franka Panda robot (Transport is dual-arm), plus three real-world Franka Panda tasks. Data is distributed as HDF5 with low-dim, image, and raw variants, and includes RGB camera views, proprioception, end-effector pose, and object state.

partial
Sim-real pairing

simulation · robomimic is a framework and dataset suite for robot learning from demonstration, released with the CoRL 2021 study 'What Matters in Learning from Offline Human Demonstrations for Robot Manipulation' (Mandlekar et al.). It provides teleoperated human and machine-generated demonstrations on five simulated robosuite/MuJoCo tasks (Lift, Can, Square, Transport, Tool Hang) using the Franka Panda robot (Transport is dual-arm), plus three real-world Franka Panda tasks. Data is distributed as HDF5 with low-dim, image, and raw variants, and includes RGB camera views, proprioception, end-effector pose, and object state.

present
License / format / access

Open · MIT · hdf5 · rlds

present
Evidence details and provenance

Official signal claims

Ee_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.

Catalog links

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