CLARU
Rutav2025

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos

A dataset of 8 hours of human play videos and 30 objects across 8 kitchen environments for training humanoid robots to solve manipulation tasks through in-context learning. Built on the RoboCasa simulation framework with evaluation spanning three difficulty levels.

Downloads193
Hours8

Why This Matters for Physical AI

This dataset enables humanoid robots to learn manipulation skills from diverse, scalable human play videos, advancing in-context learning approaches for general-purpose robotic manipulation in everyday environments.

Technical Profile

Modalities
rgb
Robot Embodiments
humanoid
Environment
simulationkitchen
Task Types
manipulationpick_and_placegrasping
Total Hours
8
Annotation Types
language_instructions
Part of the RoboCasa family

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