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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    Title :

    Image Segmentation-Based Unmanned Aerial Vehicle Safe Navigation


    Contributors:

    Published in:

    Publication date :

    2017-05-19


    Size :

    20 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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