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Use case · Embodied AI

Egocentric data for embodied AI.

The grounded, first-person perception stream agents need to learn to see, move, and act in the physical world.

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The need

Embodied agents perceive and act from a first-person viewpoint. Training their perception and planning requires long-horizon, multimodal egocentric experience — video, ego-motion, and gaze — captured as a person actually moves through and interacts with real environments.

What we provide

  • Long-horizon, everyday-activity footage
  • Navigation and object-interaction sequences
  • Synced gaze, IMU, depth, and ego-motion
  • Wide environment and scenario diversity

How it's collected

  • Daily-living and goal-directed task scenarios
  • Consented contributors across varied settings
  • Multimodal head-mounted capture

How it's delivered

  • Temporally segmented and annotated sequences
  • Model-ready formats
  • Auditable consent and licensing

Need Embodied AI data?

Tell us the tasks and environments — we'll scope the capture.