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Digital Twin for Drone Control through a Brain-Machine Interface

Authors:
Diana Ramos
Gil Gonçalves
Ricardo Faria

Keywords: drone; Brain-Computer Interface; digital twin; Robot Operating System 2.

Abstract:
Drones enable humans to perform certain high-risk and attention operations and safety-critical tasks remotely, which are boosted by the use of Brain-Computer Interfaces. However, these technologies are correlated with the cognitive state of the operator, who is prone to stress and diversions, which brings instability to drone control. In this paper, we propose a decision making system aiming to decide, upon the operator's emotional state, whether the command should or should not be sent to the drone. By building a predictive operator's digital twin for cognitive emotional detection and by benefiting from a visual facial expression classifier, this system computes the coordinates and sends them to the drone through a Robot Operating System 2 client. Results show that both the digital twin and the facial expression classifier are capable of detecting emotions in a real-time setting and the system provides a reliable and secure way of commanding drones through the mind.

Pages: 22 to 26

Copyright: Copyright (c) IARIA, 2021

Publication date: July 18, 2021

Published in: conference

ISSN: 2308-4065

ISBN: 978-1-61208-882-2

Location: Nice, France

Dates: from July 18, 2021 to July 22, 2021