This paper presents a trajectory generation mechanism based on machine learning for a network of unmanned aerial vehicles (UAVs). For delay compensation, we apply an online regression technique to learn a pattern of network-induced effects on UAV maneuvers. Due to online learning, the control system not only adapts to changes to the environment, but also maintains a fixed amount of training data. The proposed algorithm is evaluated on a collaborative trajectory tracking task for two UAVs. Improved tracking is achieved in comparison to a conventional linear compensation algorithm.


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    Titel :

    Trajectory generation for networked UAVs using online learning for delay compensation


    Beteiligte:
    Yoo, Jaehyun (Autor:in) / Lee, Seungjae (Autor:in) / Kim, H. Jin (Autor:in) / Johansson, Karl H. (Autor:in)


    Erscheinungsdatum :

    01.08.2017


    Format / Umfang :

    740051 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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