HannesImitation: Grasping with the Hannes Prosthetic Hand via Imitation Learning

HannesImitation is an imitation learning-based approach that trains a single grasping policy across diverse objects and environments. The learned policy is deployed on the Hannes prosthetic hand, enabling control of wrist orientation and hand closure. The main contributions are

• HannesImitationPolicy: The novel application of Diffusion Policy to control a prosthetic hand equipped with and anthropomorphic wrist.
• HannesImitationDataset: A novel dataset for imitation learning with the Hannes prosthetic hand for grasping on unstructured scenarios.

🛠️ Installation

To set up the environment and dependencies, please follow the installation instructions provided in the Diffusion Policy repository: https://github.com/real-stanford/diffusion_policy.

The HannesImitation project builds on top of that setup.

📂 Dataset

The HannesImitationDataset is available at: https:...

📚 Learn more

📄 Preprint available on arXiv: https://arxiv.org/abs/your-arxiv-id.

🤝 Citation

If you found this useful, you could cite the article as follows:

@inproceedings{...,
  title={HannesImitation: Grasping with the Hannes Prosthetic Hand via Imitation Learning},
  author={...},
  booktitle={...},
  pages={...},
  year={...},
  organization={...}
}

📬 Contacts

If you have any questions, please feel free to contact Carlo Alessi.