Towards Brain-Computer Interfaces for Drone Swarm Control

Ji Hoon Jeong, Dae Hyeok Lee, Hyung Ju Ahn, Seong Whan Lee

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    27 Citations (Scopus)

    Abstract

    Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention. Recent advances have been developed for the BCI-based drone control system as the demand for drone control increases. Especially, drone swarm control based on brain signals could provide various industries such as military service or industry disaster. This paper presents a prototype of a brain-swarm interface system for a variety of scenarios using a visual imagery paradigm. We designed the experimental environment that could acquire brain signals under a drone swarm control simulator environment. Through the system, we collected the electroencephalogram (EEG) signals with respect to four different scenarios. Seven subjects participated in our experiment and evaluated classification performances using the basic machine learning algorithm. The grand average classification accuracy is higher than the chance level accuracy. Hence, we could confirm the feasibility of the drone swarm control system based on EEG signals for performing high-level tasks.

    Original languageEnglish
    Title of host publication8th International Winter Conference on Brain-Computer Interface, BCI 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781728147079
    DOIs
    Publication statusPublished - 2020 Feb
    Event8th International Winter Conference on Brain-Computer Interface, BCI 2020 - Gangwon, Korea, Republic of
    Duration: 2020 Feb 262020 Feb 28

    Publication series

    Name8th International Winter Conference on Brain-Computer Interface, BCI 2020

    Conference

    Conference8th International Winter Conference on Brain-Computer Interface, BCI 2020
    Country/TerritoryKorea, Republic of
    CityGangwon
    Period20/2/2620/2/28

    Bibliographical note

    Funding Information:
    Research was funded by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning).

    Publisher Copyright:
    © 2020 IEEE.

    Keywords

    • brain-computer interface
    • drone swarm control
    • electroencephalogram
    • visual imagery

    ASJC Scopus subject areas

    • Behavioral Neuroscience
    • Cognitive Neuroscience
    • Artificial Intelligence
    • Human-Computer Interaction

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