AIRoA MoMa Dataset
The AIRoA MoMa Dataset is a large-scale, real-world dataset for mobile manipulation collected with the Toyota Human Support Robot (HSR) via leader-follower teleoperation in household environments. It contains 25,469 episodes (~94 hours) sampled at 30 Hz, with synchronized RGB images from head and wrist cameras, joint states, six-axis wrist force-torque signals, and internal robot states. A two-layer annotation schema of sub-goals and primitive actions supports hierarchical learning and error analysis across seven primary household tasks. The data is standardized in the LeRobot v2.1 format and released by AIRoA (AI Robot Association) under the GENIAC project (METI/NEDO).
- Scale
- 94 hours
- Formats
- lerobot
- License
- custom
- Published
- 2025-09-29
Decision summary
teleoperation
Metadata requires review against the official source before publication.
Read the dataset manifest and feature schema.
Catalog assessment
Selection evidence
73/100
Provisional · confidence 48 · 4/6 evaluated
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.
View 3 more dimensions
World-model readiness
Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.
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.
- 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.
Record specifics
Dataset facts
- Source
- AIRoA (AI Robot Association)
- Evidence
- secondary claim
- Formats
- lerobot
- episodes
- 25469
- hours
- 94
- tasks
- 7
Metadata coverage
Loop signals
4/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 4 more signal categories
video · The AIRoA MoMa Dataset is a large-scale, real-world dataset for mobile manipulation collected with the Toyota Human Support Robot (HSR) via leader-follower teleoperation in household environments. It contains 25,469 episodes (~94 hours) sampled at 30 Hz, with synchronized RGB images from head and wrist cameras, joint states, six-axis wrist force-torque signals, and internal robot states. A two-layer annotation schema of sub-goals and primitive actions supports hierarchical learning and error analysis across seven primary household tasks. The data is standardized in the LeRobot v2.1 format and released by AIRoA (AI Robot Association) under the GENIAC project (METI/NEDO).
presentThe AIRoA MoMa Dataset is a large-scale, real-world dataset for mobile manipulation collected with the Toyota Human Support Robot (HSR) via leader-follower teleoperation in household environments. It contains 25,469 episodes (~94 hours) sampled at 30 Hz, with synchronized RGB images from head and wrist cameras, joint states, six-axis wrist force-torque signals, and internal robot states. A two-layer annotation schema of sub-goals and primitive actions supports hierarchical learning and error analysis across seven primary household tasks. The data is standardized in the LeRobot v2.1 format and released by AIRoA (AI Robot Association) under the GENIAC project (METI/NEDO).
presentlanguage · has-success-labels · The AIRoA MoMa Dataset is a large-scale, real-world dataset for mobile manipulation collected with the Toyota Human Support Robot (HSR) via leader-follower teleoperation in household environments. It contains 25,469 episodes (~94 hours) sampled at 30 Hz, with synchronized RGB images from head and wrist cameras, joint states, six-axis wrist force-torque signals, and internal robot states. A two-layer annotation schema of sub-goals and primitive actions supports hierarchical learning and error analysis across seven primary household tasks. The data is standardized in the LeRobot v2.1 format and released by AIRoA (AI Robot Association) under the GENIAC project (METI/NEDO).
presentOpen · custom · lerobot
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.
Catalog links