This work proposes a vision-based guidance scheme for an unmanned aerial vehicle navigating through urban environments while seeking a predefined goal point. Optical flow of image corner feature points is considered to segment obstacles from the image. An obstacle-avoidance guidance law is proposed to avoid the segmented obstacles. Additionally, detecting open space between segmented obstacles, a passage-following guidance law also presented for intelligent decision making. Analytic comparison with an existing methodology is carried out to highlight superior obstacle-avoidance properties of the proposed strategy. Simulations are carried out in a three-dimensional environment for single and multiple obstacles. Results comply with the analytic findings and present a much improved avoidance performance as compared to existing optical flow-based methods.


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    Titel :

    Image Segmentation-Based Unmanned Aerial Vehicle Safe Navigation


    Beteiligte:
    Agrawal, Pooja (Autor:in) / Ratnoo, Ashwini (Autor:in) / Ghose, Debasish (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.07.2017




    Medientyp :

    Aufsatz (Konferenz) , Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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