Egocentric & RGB-D

Synchronized first-person video, depth, pose, and optional IMU for manipulation and navigation.

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Representative use cases

Robot manipulation

Capture and acceptance criteria are tailored to the intended model behavior and deployment environment.

Navigation and policy learning

Capture and acceptance criteria are tailored to the intended model behavior and deployment environment.

Embodied evaluation

Capture and acceptance criteria are tailored to the intended model behavior and deployment environment.

Schema and capture coverage

Built for measurable coverage.

Every engagement begins with a versioned brief: intended use, environments, exclusions, participant consent, sensor configuration, quotas, and acceptance criteria.

media.uriProtected object reference · 4K RGB · 30–60 fps · depth calibrated

capture.contextLocale · coarse geography · environment · device

annotation[]Events · objects · actions · quality flags

rightsConsent version · allowed use · retention state

qaProbe version · reviewer agreement · disposition

deliveryManifest · checksums · limitations report

QA report preview · illustrative

Acceptance evidence travels with the data.

Coverage is reported against the approved quota matrix. Automated checks and blinded human samples expose rejection reasons, duplicates, media compliance, and annotation agreement.

Media probe pass98.4% illustrative

Human sample10% stratified

Agreement0.91 illustrative

Unresolved exceptions0 at delivery gate

From pilot to delivery.

Approve representative pilot samples before production. Inspect aggregate coverage, rejection reasons, agreement, duplicates, and media compliance as the collection progresses.

PILOT 01Environment coverage

PILOT 02Annotation overlay

PILOT 03QA evidence

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