Continuous Wrist Control on the Hannes Prosthesis:
a Vision-based Shared Autonomy Framework

Federico Vasile, Elisa Maiettini, Giulia Pasquale, Nicolò Boccardo, Lorenzo Natale

TL;DR: Synthetic dataset generation of object-centric scenes for grasping

(check out also our dinoDet for instance segmentation, the simulation environment for wrist control on the Hannes prosthetic hand and the iHannes dataset used for evaluation)

Getting started

The project uses Unity 2021.3.28.f1. Find the version here and click on the Unity Hub button to download.

Installation

• Install Git LFS.
• Open a Command Prompt and run git lfs install to initialize it.
  Then, clone the repository: git clone https://github.com/hsp-iit/hemisphere-dataset-generation
• Go on the Unity Hub, click on Open and locate the downloaded repository.

Generate the dataset

For a quick start, open the Unity project and press the Play button.

The dataset generation pipeline supports domain randomization and several scenes (e.g., table-top, outdoor).

Walk through the PerceptionCamera GameObject to set the parameters for the dataset generation, such as the labels required (e.g., segmentation, depth, normals) and the SimulationEnvironment GameObject for the scene parameters (e.g., number of objects, randomization components).

Citation

If you find our work useful, please consider citing our paper as follows:

@inproceedings{vasile2025continuous,
  title={Continuous Wrist Control on the Hannes Prosthesis: a Vision-based Shared Autonomy Framework},
  author={Vasile, Federico and Maiettini, Elisa and Pasquale, Giulia and Boccardo, Nicol{\`o} and Natale, Lorenzo},
  booktitle={2025 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={},
  year={2025},
}

Mantainer

This repository is mantained by:

	@FedericoVasile1