Unmanned aerial vehicle(UAV) has become more and more widely used in military and non-military applications, but endurance has become a major limiting factor in the development of UAV. In order to increase the UAV’s endurance, this paper uses a vision guidance method to achieve automatic aerial refueling technology. This paper proposes an automatic refueling technology based on a deep-learning algorithm for detection. The Faster Rcnn algorithm can simultaneously recognize the fuel receiver and the Drogue at long-distance and returns the center coordinate value of the receiver. If the pixel area of the identified Drogue is greater than a certain threshold, the central coordinate value of the Drogue is returned. The experiment results show that the average accuracy of the algorithm reaches 67.75%, and the real-time performance is about 5HZ.


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    Titel :

    Research on Drogue Detection Algorithm for Aerial Refueling (IEEE/CSAA GNCC)*


    Beteiligte:
    Chen, A.Guanyu (Autor:in) / Wang, B. Xinhua (Autor:in) / Yang, C. Tiankai (Autor:in) / Wei, D.Zhiqiang (Autor:in)


    Erscheinungsdatum :

    2018-08-01


    Format / Umfang :

    576727 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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