EgoStation GoPro Pick-and-Place Dataset
GoPro first-person pick-and-place trajectories
A non-gated CC-BY-NC-4.0 LeRobot-style dataset with GoPro first-person manipulation, hand-world coordinates, and 6DoF trajectory tags.
Pick-and-place benchmark fixtures
Open access but non-commercial license terms apply.
Inspect schema and run a bounded sample audit before committing to the full release.
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has rich observation and semantic context, but limited geometry/sim-real alignment.
fit 68 · confidence 55
Contains observation, intent, and action/state, but feedback/correction signal is weak.
fit 72 · confidence 55
Verified facts and provenance
Claims, metadata verification, and sample verification are shown separately.
Unknown — no machine-readable schema facts have been captured.
Unknown — metadata conclusions do not prove sample coverage, alignment, or file integrity.
Declared loop signal coverage
Signals inferred from official metadata; Data pipeline verification is still pending.
Observation / ego video
video
Action / hand pose / robot state
hand pose · trajectory · actions · timeseries
Gaze / attention
No decision-grade evidence captured yet.
Language intent / task phase
Useful because it has a concrete manipulation task and LeRobot-style packaging.
Feedback / correction / failure
No decision-grade evidence captured yet.
Sim-real pairing
No decision-grade evidence captured yet.
License / format / access
Open · CC-BY-NC · LeRobot · Parquet
Model and task fit · OpenBot inference
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has rich observation and semantic context, but limited geometry/sim-real alignment.
fit 68 · confidence 55
Contains observation, intent, and action/state, but feedback/correction signal is weak.
fit 72 · confidence 55
Failure, correction, intervention, and recovery annotations have not been verified.
fit 50 · confidence 15
Good tasks
Blockers and unresolved evidence
- Gaze / attentionunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
- Feedback / correction / failureunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
- Sim-real pairingunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
Raw dataset signals
OpenBot fit
- Pick-and-place benchmark fixtures
- 6DoF action schema testing
- OpenBot Data LeRobot ingestion demos
Related models and papers
Model references linked to similar loop signals.
OpenVLA
Open-source vision-language-action model for generalist robotic manipulation, trained on diverse real-world robot demonstrations.
RT-1
Robotics Transformer policy trained on large-scale real-world robot demonstrations for language-conditioned manipulation.
pi0 / OpenPI
Generalist robot policy family and open-source robotics model package from Physical Intelligence.
SmolVLA
Compact open vision-language-action policy designed for practical robot fine-tuning and deployment through the LeRobot ecosystem.
Octo
Open-source generalist robot policy pretrained on Open X-Embodiment trajectories and designed for fine-tuning to new robots and tasks.
ACT
Action Chunking with Transformers predicts short action sequences for efficient imitation learning in manipulation tasks.
Integration notes
- Open access but non-commercial license terms apply.
- Useful because it has a concrete manipulation task and LeRobot-style packaging.