OpenBot
Platform
Manipulation datasetUnknownReadiness 77/100Provisional

FineART

FineART: Fine-Grained Annotated Robotic Trajectory Dataset

Source notes

FineART: Fine-Grained Annotated Robotic Trajectory Dataset

FineART is co-released by Scale AI and Hugging Face LeRobot. The data was collected and annotated by the Physical AI unit at Scale AI. FineART is a bimanual manipulation dataset where every episode comes with dense, human-written subtask annotations. It has 40,543 teleoperated episodes (1,718 hours), 533,913 subtask labels, and 151 tasks, all collected on a Trossen Stationary AI (ALOHA-style) bimanual robot. Most robot… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/FineART.

Scale
Not declared
Formats
Not declared
License
cc-by-4.0
Published
2026-10-12
Embodiments
Not declared
Modalities
Not declared
Official sourceAudit a local copy

Decision summary

Best for

VLA training

Main blocker

No verified blocker is published; unresolved facts remain unknown.

Next check

Read the dataset manifest and feature schema.

Release history

Source-backed release timing for this canonical dataset record.

Important releases

  1. Dataset published

    Release timing is recorded from the official source creation date.

    Release evidence

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 work

77/100

Provisional

2/6 dimensions scored · 28% confidence

Access and governanceNot scoredconf. 20
Schema and signal coverageNot scoredconf. 15
Policy training readiness85conf. 55
World-model readiness68conf. 50
Failure and recovery readinessNot scoredconf. 15
Download and processing readinessNot scoredconf. 10
Read the evidence behind all 6 dimensions

Access and governance

Access and license are declared by the source.

unknownnot scored · confidence 20

Schema and signal coverage

No machine-readable schema has been verified yet.

unknownnot scored · confidence 15

Policy training readiness

Observation and action/state signals are declared; alignment quality still depends on sample verification.

usefulfit 85 · confidence 55

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

Dataset scale and sampling path are unknown.

unknownnot scored · confidence 10
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.
Engineering checks (OBRS) behind this record
Engineering checksBronze

Needs Audit

3/12checks passed

OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.

Standardization & Loaders2 / 25 pt
Physical & Action Quality12 / 25 pt
Semantic & Annotation12 / 20 pt
Real-World Validation0 / 15 pt
License & Compliance10 / 15 pt
Missing evidence and readiness gaps
  • 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
Evidence
official claim
Formats
Not declared
Read paper

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 · modality:video

present
Action / hand pose / robot state

actions · vision-language-action · bimanual-manipulation · FineART: Fine-Grained Annotated Robotic Trajectory Dataset FineART is co-released by Scale AI and Hugging Face LeRobot. The data was collected and annotated by the Physical AI unit at Scale AI. FineART is a bimanual manipulation dataset where every episode comes with dense, human-written subtask annotations. It has 40,543 teleoperated episodes (1,718 hours), 533,913 subtask labels, and 151 tasks, all collected on a Trossen Stationary AI (ALOHA-style) bimanual robot. Most robot… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/FineART.

present
Language intent / task phase

language · task phase · vision-language-action · task_categories:robotics

present
Sim-real pairing

No decision-grade evidence captured yet.

unknown
License / format / access

Unknown · cc-by-4.0

present
Evidence details and provenance

Official signal claims

VideoActionsLanguageTask phaseModality:videoVision Language Action

Schema and annotations

No machine-readable schema facts are captured.

Sample verification

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

README/card declaration

Integration notes

No integration notes are published.