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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/83720

    Title: Vision-Based Tracking and Position Estimation of Moving Targets for Unmanned Helicopter Systems
    Authors: Lin, Chien-Hong;Hsiao, Fu-Yuen;Hsiao, Fei-Bin
    Contributors: 淡江大學航空太空工程學系
    Keywords: Target tracking and position estimation;image processing;Kalman filtering;unmanned helicopter
    Date: 2013-01
    Issue Date: 2013-03-20 16:56:37 (UTC+8)
    Publisher: Hoboken: Wiley-Blackwell Publishing, Inc.
    Abstract: The primary goal of this study is to track a ground-moving target using a machine-vision system installed on an unmanned helicopter, and to estimate its position if the target becomes unobservable. The machine-vision system is accomplished using real-time color images obtained from a charge-coupled device (CCD) camera mounted on a computer-controlled gimbaled system that can pitch and yaw. To avoid real-time image-tracking failure resulting from a moving target becoming concealed, the Kalman filtering technique is applied to predict the target's follow-on position, so that the camera can continuously track the target. The entire system is initially tested on the ground and then mounted on a helicopter for in-flight testing. The following three cases are shown in the flight tests: (1) an uncovered static target; (2) a moving visible target; and (3) a target that moves in a straight line at a constant speed and becomes temporarily concealed. The vision-based tracking system with the developed algorithm is successfully applied in all three cases.
    Relation: Asian Journal of Control 15(5), pp.1270–1283
    DOI: 10.1002/asjc.654
    Appears in Collections:[Graduate Institute & Department of Aerospace Engineering] Journal Article

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