In this paper, we perform the actual verification of the anomaly detection (AD) model of each drone that indicates the anomaly in swarm drone flight using the actual flight data. For this purpose, we use a model-based AD method that uses data accumulated through actual flight tests. The AD model uses a deep neural network-based generation model to create a training model with normal data and perform tests with abnormal data. As a result, the diagnostic results of mainly three cases are derived and analyzed for validity. The proposed AD method can be integrated with a machine learning based framework that can immediately detect abnormal behavior of swarm drone flights, which can be utilized to improve the reliability of swarm drone flight operations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Deep Learning based Anomaly Detection for a Vehicle in Swarm Drone System


    Beteiligte:
    Ahn, Hyojung (Autor:in)


    Erscheinungsdatum :

    01.09.2020


    Format / Umfang :

    631989 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    One-hand control swarm drone system based on deep learning

    CHOI JI HOON | Europäisches Patentamt | 2024

    Freier Zugriff

    Anomaly detection via drone

    HILLER NATHAN D / NEWMAN DAVID I / TORRES ROBERT B | Europäisches Patentamt | 2024

    Freier Zugriff

    Autonomous Decision-Making of Drone Swarm Based on Deep Reinforcement Learning

    Zhang, Na / Chen, Shuhan / Xiong, Shixun et al. | Springer Verlag | 2025


    ANOMALY DETECTION VIA UNMANNED AERIAL DRONE

    HILLER NATHAN D / NEWMAN DANIEL I / TORREZ RAYMUNDO B | Europäisches Patentamt | 2024

    Freier Zugriff