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.).
Source notes
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
- 7.32 GB size
- Formats
- hdf5 · rlds
- License
- MIT
- Published
- 2021-08-06
Decision summary
scripted
Metadata requires review against the official source before publication.
Read the dataset manifest and feature schema.
Release history
Source-backed release timing for this canonical dataset record.
- Release evidence
Dataset series published
Release timing is recorded from official dataset metadata.
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
70/100
Provisional
3/6 dimensions scored · 42% confidence
Read the evidence behind all 6 dimensions
Access and governance
Access and license are declared by the source.
Schema and signal coverage
No machine-readable schema has been verified yet.
Policy training readiness
Observation and action/state signals are declared; alignment quality still depends on sample verification.
World-model readiness
World-model observation, geometry, or temporal semantics are not verified.
Failure and recovery readiness
No verified failure/recovery annotation evidence is available yet.
Download and processing readiness
Scale is declared; transfer and processing estimates are not measured.
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
- Stanford Vision and Learning Lab / ARISE Initiative
- Evidence
- secondary claim
- Formats
- hdf5 · rlds
- tasks
- 8
- size
- 7.32 GB
Loop signals
5/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 5 more signal categories
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.
presentee_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.
partialhas-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.
partialsimulation · 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.
presentOpen · MIT · hdf5 · rlds
presentEvidence details and provenance
Official signal claims
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.