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--- |
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license: apache-2.0 |
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datasets: |
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- lerobot/pusht |
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pipeline_tag: robotics |
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tags: |
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- robotics |
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--- |
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# PushT Diffusion Policy - Robot Control Model |
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This model is an implementation of Diffusion Policy for the PushT environment, which simulates robotic pushing tasks. |
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## Model |
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This model uses a conditional diffusion architecture to predict robotic actions based on visual observations. |
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## Performance |
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The model achieves a success rate of 100.0% in the PushT environment with different initial configurations. |
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## Demonstration Videos |
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The repository includes demonstration videos in the `videos/` folder. |
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## Usage |
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```python |
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from lerobot.common.policies.diffusion.modeling_diffusion import DiffusionPolicy |
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policy = DiffusionPolicy.from_pretrained("RafaelJaime/pusht-diffusion") |
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``` |
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# Citation |
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```bibtex |
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@article{chi2024diffusionpolicy, |
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author = {Cheng Chi and Zhenjia Xu and Siyuan Feng and Eric Cousineau and Yilun Du and Benjamin Burchfiel and Russ Tedrake and Shuran Song}, |
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title = {Diffusion Policy: Visuomotor Policy Learning via Action Diffusion}, |
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journal = {The International Journal of Robotics Research}, |
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year = {2024} |
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} |
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``` |
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Published on 2025-04-28 |
