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Feature recognition and tracking of aircraft tanker and refueling drogue for UAV aerial refueling

机译:用于无人机空中加油的飞机油轮和加油锥的特征识别和跟踪

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This paper describes the results of the analysis of specific ‘feature detection and recognition’ algorithms within a Machine Vision approach for the problem of aerial refueling for unmanned aerial vehicles. In order to precisely obtain the center of the features of the aircraft tanker and refueling drogue in the images of vision-based navigation during automated aerial refueling docking, a feature extraction method based on the HSV color space information of images is proposed. The HSV color space is introduced and the features of the aircraft tanker and refueling drogue are made based on the principle of choosing features. By using of least square ellipse fitting, after making color converted, color phase filter, binary and edge detection on images. The feature locations of the aircraft tanker and refueling drogue are precisely obtained and tracked. The experiment shows that the method proposed can not only extract the features accurately but can also calculate their locations in real-time, which provides a more reliable feature extraction and tracking method for vision-based navigation for automated aerial refueling.
机译:本文介绍了机器视觉方法中针对“无人机”空中加油问题的特定“特征检测和识别”算法的分析结果。为了在空中加油对接过程中基于视觉的导航图像中准确获得飞机油轮和加油锥的特征中心,提出了一种基于图像的HSV色彩空间信息的特征提取方法。介绍了HSV色彩空间,并根据特征选择原则确定了飞机油轮和加油口的特征。通过使用最小二乘椭圆拟合,在对图像进行颜色转换,颜色相位滤波,二进制和边缘检测之后。飞机油轮和加油锥的特征位置可以精确获取和跟踪。实验表明,所提出的方法不仅可以准确地提取特征,还可以实时计算其位置,从而为基于视觉的空中加油导航提供了更加可靠的特征提取和跟踪方法。

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