EMG-Based Shared Control Framework for Human-Robot Co-Manipulation Tasks
Francesca Patriarca, Paolo Di Lillo, Filippo Arrichiello
2024
Abstract
The paper presents a shared control architecture designed for human-robot co-manipulation tasks, that allows the human to switch among robot’s operational modes through surface electromyography (sEMG) signals from the user’s arm. A support vector machine (SVM) classifier is employed to process the raw EMG data to identify two classes of contractions that are fed into a finite state machine algorithm to trigger the activation of different sets of admittance control parameters corresponding to the envisaged operational modes. The proposed architecture has been experimentally validated using a Kinova Jaco2 manipulator, equipped with Force/Torque sensor at the end-effector, and with a user wearing Delsys Trigno Avanti EMG sensors on the dominant upper limb.
DownloadPaper Citation
in Harvard Style
Patriarca F., Di Lillo P. and Arrichiello F. (2024). EMG-Based Shared Control Framework for Human-Robot Co-Manipulation Tasks. In Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-717-7, SciTePress, pages 46-53. DOI: 10.5220/0012943600003822
in Bibtex Style
@conference{icinco24,
author={Francesca Patriarca and Paolo Di Lillo and Filippo Arrichiello},
title={EMG-Based Shared Control Framework for Human-Robot Co-Manipulation Tasks},
booktitle={Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2024},
pages={46-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012943600003822},
isbn={978-989-758-717-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - EMG-Based Shared Control Framework for Human-Robot Co-Manipulation Tasks
SN - 978-989-758-717-7
AU - Patriarca F.
AU - Di Lillo P.
AU - Arrichiello F.
PY - 2024
SP - 46
EP - 53
DO - 10.5220/0012943600003822
PB - SciTePress