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首页> 外文会议>IEEE International Conference on Fuzzy Systems >A Visual Protocol for Autonomous Landing of Unmanned Aerial Vehicles Based on Fuzzy Matching and Evolving Clustering
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A Visual Protocol for Autonomous Landing of Unmanned Aerial Vehicles Based on Fuzzy Matching and Evolving Clustering

机译：基于模糊匹配和不断发展的聚类的无人机自主着陆自主着陆视觉协议

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摘要

This paper proposes a visual approach based on a RGB/HSV tag to precise and autonomous landing of unmanned aerial vehicles (UAV). The proposed tag is correctly identified by an algorithm divided in four stages: hue filtering, clustering, matching and center location. The first stage is based on fuzzy matching and highlights the pixels with similar colors to the searched pattern, while ignores the pixels with different colors. The clustering stage is responsible for grouping the pixels by color and proximity. The matching stage compares the searched and found landing points. Finally, the last stage locates the center of the landing point in relation to the UAV location. The proposed approach is significantly different from the state-of-the art techniques, since it is able not only to correctly identify a designated landing point, but also to distinguish it from different landing points. It requires very low computational effort and is very suitable for real-time video applications. The algorithm was successfully used, in an online manner, for location of landing points in real-time, using very limited hardware.
机译：本文提出了一种基于RGB / HSV标签的视觉方法，以实现无人驾驶飞行器（UAV）的精确和自主着陆。所提出的标签是通过分为四个阶段的算法正确识别：色调过滤，群集，匹配和中心位置。第一阶段基于模糊匹配，并突出显示具有与搜索模式相似的颜色的像素，同时忽略不同颜色的像素。聚类阶段负责通过颜色和接近分组像素。匹配阶段将搜索和找到的着陆点进行比较。最后，最后阶段定位与UAV位置相关的着陆点的中心。所提出的方法与最先进的技术显着不同，因为它不仅能够正确地识别指定的着陆点，而且还能够将其区分开地区分。它需要非常低的计算工作，非常适合实时视频应用。使用非常有限的硬件，以在线方式成功地使用该算法，以实时地用于着陆点的位置。

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