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