LeRobot Shirt-Folding Dataset
The shirt-folding dataset from LeRobot's open-source 'Unfolding Robotics: Open-Source Shirt Folding from Data to Deployment' project, which trained a bimanual robot to fold t-shirts at a 90% success rate.
Source notes
The shirt-folding dataset from LeRobot's open-source 'Unfolding Robotics: Open-Source Shirt Folding from Data to Deployment' project, which trained a bimanual robot to fold t-shirts at a 90% success rate. Collected via real-world leader-follower teleoperation across 8 bimanual setups optimizing for diversity (25+ t-shirts, 8 backgrounds, varied camera/robot heights), structured as Level 1 (fold a laid-out shirt) and Level 2 (spread a crumpled shirt, fold, set aside). The full dataset has 5,688 episodes (~131h); a curated high-quality subset (lerobot/high_quality_folding) has 1,200 episodes (~30h). Each episode has 3 camera streams (base 480x640, two wrists 720x1280) and 16-dim joint+gripper states/actions, stored in LeRobotDataset v3.0 (video-encoded).
- Scale
- 131 hours
- Formats
- lerobot
- License
- Apache-2.0
- Published
- 2026-06-22
- Embodiments
- parallel_jaw
- Modalities
- proprioception, rgb
Decision summary
teleoperation
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
How scores work70/100
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.
- Language intent / task phase. 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
Needs Audit
OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.
- 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
- LeRobot (Hugging Face)
- Evidence
- secondary claim
- Formats
- lerobot
- episodes
- 5,688
- hours
- 131
- tasks
- 2
Loop signals
3/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 5 more signal categories
video · The shirt-folding dataset from LeRobot's open-source 'Unfolding Robotics: Open-Source Shirt Folding from Data to Deployment' project, which trained a bimanual robot to fold t-shirts at a 90% success rate. Collected via real-world leader-follower teleoperation across 8 bimanual setups optimizing for diversity (25+ t-shirts, 8 backgrounds, varied camera/robot heights), structured as Level 1 (fold a laid-out shirt) and Level 2 (spread a crumpled shirt, fold, set aside). The full dataset has 5,688 episodes (~131h); a curated high-quality subset (lerobot/high_quality_folding) has 1,200 episodes (~30h). Each episode has 3 camera streams (base 480x640, two wrists 720x1280) and 16-dim joint+gripper states/actions, stored in LeRobotDataset v3.0 (video-encoded).
presentThe shirt-folding dataset from LeRobot's open-source 'Unfolding Robotics: Open-Source Shirt Folding from Data to Deployment' project, which trained a bimanual robot to fold t-shirts at a 90% success rate. Collected via real-world leader-follower teleoperation across 8 bimanual setups optimizing for diversity (25+ t-shirts, 8 backgrounds, varied camera/robot heights), structured as Level 1 (fold a laid-out shirt) and Level 2 (spread a crumpled shirt, fold, set aside). The full dataset has 5,688 episodes (~131h); a curated high-quality subset (lerobot/high_quality_folding) has 1,200 episodes (~30h). Each episode has 3 camera streams (base 480x640, two wrists 720x1280) and 16-dim joint+gripper states/actions, stored in LeRobotDataset v3.0 (video-encoded).
presentNo decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownOpen · Apache-2.0 · 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.