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05

Cross-Embodiment Data Standards

“Data from different robots and sources doesn't fit one schema.”
What we do
One taxonomy and format across datasets, robots and sites, so every new source plugs into training without a rewrite.
What you receive
A documented ontology, written guidelines and mapping scripts you own.

Interactive sample · hover a raw label to see where it goes

Before · labels as they arrivedIllustrative

15 labels, three names for the same cup, no structure.

After · one hierarchy

  • object
    • container
      • cup3
    • appliance
      • kettle1
  • action
    • grasp
      • power2
      • precision1
    • pour1
  • agent
    • hand
      • left2
      • right1
  • outcome
    • success1
    • failure
      • drop2
      • slip1

10 leaf classes with definitions, edge-case notes and a version number.

All samples are built on public data: robot episodes from the open ALOHA dataset (LeRobot, MIT licence) and public-domain kitchen footage from the USDA, processed by us. Samples marked “Illustrative” use example data. Sources

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