This paper describes the results of the analysis of specific 'corner detection' algorithms within a machine vision approach for the problem of aerial refueling for unmanned aerial vehicles. Specifically, the performances of the SUSAN and the Harris corner detection algorithms have been compared. A critical goal of this study was to evaluate the interface of these feature extraction schemes with the successive detection and labeling, and pose estimation schemes in the overall scheme. Closed-loop simulations were performed using a Simulink-based simulation environment to reproduce docking maneuvers using the US Air Force refueling boom.


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    Title :

    Addressing corner detection issues for machine vision based UAV aerial refueling


    Additional title:

    Aspekte der Erkennung von Eckpunkten bei der Betankung unbemannter Flugzeuge auf Basis des maschinellen Sehens



    Published in:

    Publication date :

    2007


    Size :

    13 Seiten, 14 Bilder, 2 Tabellen, 20 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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