OpenBot
Platform
Egocentric datasetOpen
OBRS 29•Bronze

POV Egocentric Video Robotics FHD Samples

A small MIT-licensed first-person robotics video sample set for human demonstrations, VLA experiments, manipulation, and household activities.

Scale
<1K rows
Formats
video · text metadata
License
MIT
Published
2026
Official sourceAll recordsDataset index A–ZRun local preflightRequest scoped audit

Decision summary

Best for

Small open fixture for first-person video ingestion

Main blocker

Small sample dataset, not a large training corpus.

Next check

Read the dataset manifest and feature schema.

Release history

Source-backed release timing for this canonical dataset record.

Important releases

No source-backed day-level release date is published for this dataset. Its year is not being converted into an inferred event.

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

69/100

Provisional

3/6 dimensions scored · 41% confidence

Access and governance75conf. 85
Schema and signal coverageNot scoredconf. 15
Policy training readinessNot scoredconf. 15
World-model readiness68conf. 50
Failure and recovery readinessNot scoredconf. 15
Download and processing readiness65conf. 65
Read the evidence behind all 6 dimensions

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/action alignment has not been established.

unknownnot scored · confidence 15

World-model readiness

Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.

usefulfit 68 · confidence 50

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.
  • 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.

Dataset facts

Source
Hugging Face · TrainThemAI/POV-Egocentric-Video-Robotics-FHD-Samples
Evidence
official claim
Formats
video · text metadata
rows
<1K
languages
EN/ES
quality
FHD

Loop signals

4/7 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 · Small open fixture for first-person video ingestion · A small MIT-licensed first-person robotics video sample set for human demonstrations, VLA experiments, manipulation, and household activities. · Hugging Face · TrainThemAI/POV-Egocentric-Video-Robotics-FHD-Samples

present
Action / hand pose / robot state

Household manipulation demos · A small MIT-licensed first-person robotics video sample set for human demonstrations, VLA experiments, manipulation, and household activities.

partial
Language intent / task phase

task phase · robotics labels

present
Sim-real pairing

No decision-grade evidence captured yet.

unknown
License / format / access

Open · MIT · video · text metadata

present
Evidence details and provenance

Official signal claims

VideoTask phaseDemonstrationsRobotics Labels

Schema and annotations

No machine-readable schema facts are captured.

Sample verification

Pending. Metadata does not prove sample coverage, alignment, or file integrity.

curated source metadata

Integration notes

  • Small sample dataset, not a large training corpus.
  • Useful because it is MIT licensed and directly accessible.