real-stanford/diffusion_policy
A research project implementing diffusion-based policies for learning visuomotor control in robotic manipulation tasks.
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This Columbia University project presents Diffusion Policy, a method for learning robotic visuomotor policies through action diffusion models. It provides state-based and vision-based implementations for robot control, with Colab notebooks and full experiment logs including checkpoints and training configurations. The approach applies generative diffusion models to robot action prediction, enabling imitation learning for manipulation tasks.
Frequently asked
- What is real-stanford/diffusion_policy?
- A research project implementing diffusion-based policies for learning visuomotor control in robotic manipulation tasks.
- Is diffusion_policy open source?
- Yes — real-stanford/diffusion_policy is open source, released under the MIT license.
- What language is diffusion_policy written in?
- real-stanford/diffusion_policy is primarily written in Python.
- How popular is diffusion_policy?
- real-stanford/diffusion_policy has 4.3k stars on GitHub.
- Where can I find diffusion_policy?
- real-stanford/diffusion_policy is on GitHub at https://github.com/real-stanford/diffusion_policy.