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Manipulation datasetOpenReadiness 69 · confidence 34

LingBot Masked Depth Modeling Data Dataset

Metric RGB-D pretraining for spatial perception

3.0Msamples

A roughly three-million-sample mixture of real indoor, robot-manipulation, and simulated RGB-D data used by LingBot-Depth.

Best for

Depth completion

Not for / blocker

Perception dataset rather than an action-policy training corpus; RobbyVla is the manipulation-related subset.

Download decision

Inspect schema and run a bounded sample audit before committing to the full release.

Policy learningUseful

Has observation and action/state proxy, but weak task-phase context.

fit 70 · confidence 55

World modelUseful

Has visual observations plus geometry, calibration, depth, or reconstruction cues.

fit 82 · confidence 55

WAMUnknown

WAM-required observation, intent, and action alignment is not fully verified.

fit 50 · confidence 15

Verified facts and provenance

Claims, metadata verification, and sample verification are shown separately.

curated official source
Official claim · signals
ImagesDepthCamera calibrationPoint cloudSIM Real
Metadata verified · schema / annotations

Unknown — no machine-readable schema facts have been captured.

Sample / pipeline verification

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.

4/7 categories present or partial

Observation / ego video

images · depth · camera calibration · RGB-D

present

Action / hand pose / robot state

Perception dataset rather than an action-policy training corpus; RobbyVla is the manipulation-related subset. · A roughly three-million-sample mixture of real indoor, robot-manipulation, and simulated RGB-D data used by LingBot-Depth.

partial

Gaze / attention

No decision-grade evidence captured yet.

unknown

Language intent / task phase

No decision-grade evidence captured yet.

unknown

Feedback / correction / failure

No decision-grade evidence captured yet.

unknown

Sim-real pairing

depth · camera calibration · sim-real · Depth completion

present

License / format / access

Open · RGB-D · Camera intrinsics

partial

Model and task fit · OpenBot inference

Policy learningUseful

Has observation and action/state proxy, but weak task-phase context.

fit 70 · confidence 55

World modelUseful

Has visual observations plus geometry, calibration, depth, or reconstruction cues.

fit 82 · confidence 55

WAMUnknown

WAM-required observation, intent, and action alignment is not fully verified.

fit 50 · confidence 15

Failure miningUnknown

Failure, correction, intervention, and recovery annotations have not been verified.

fit 50 · confidence 15

Good tasks

pick-place / manipulation3D / sim-real alignment

Blockers and unresolved evidence

  • Gaze / attentionunknown
    Not enough evidence to classify this signal. Verify metadata or a bounded sample.
  • Language intent / task phaseunknown
    Not enough evidence to classify this signal. Verify metadata or a bounded sample.
  • Feedback / correction / failureunknown
    Not enough evidence to classify this signal. Verify metadata or a bounded sample.

Raw dataset signals

ImagesDepthCamera calibrationPoint cloudSIM Real

OpenBot fit

  • Depth completion
  • 3D reconstruction
  • Spatial representation pretraining

Integration notes

  • Perception dataset rather than an action-policy training corpus; RobbyVla is the manipulation-related subset.

Related by signals