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DEXTEROUS MANIPULATION

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Diffusion Policy

real-stanford

A visuomotor policy-learning framework that generates action sequences through diffusion.

What you can explore

Compare documented training, evaluation and dataset workflows as a baseline for manipulation learning.

Before you use it

Tasks and robot action spaces vary. Adapting the framework to a new dexterous hand requires suitable demonstrations and a validated control interface.

Original contributors

Cheng Chi and Diffusion Policy collaborators

License / access: Code: MIT · check external data, models and hardware terms separately

Original code & documentation

Editorial reference · checked 2026-09-22

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