Motion Algorithm for Unmanned Aerial Vehicle Landing on a Car

Ruiyang Zhou, N. Konstantin, Selezneva Mariya, Ryazanova Natalya, Xinke Zhang
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Abstract

The authors studied the task of processing the information from the optical system when the UAV is landing on a moving unmanned vehicle. Generally, color image analysis algorithms are very accurate, but they cannot work in real time or need to enhance the performance of professional computers. A compact high-speed color image recognition algorithm is developed basing on a pre-processing method—a «downsample» function for decimation; HSV model; Otsu's method - an algorithm for calculating the binary threshold of grayscale images, and method for isolating connected components-Two-Pass method. The simulation results demonstrated the operating capability and high enough efficiency of the developed algorithm. It is possible to achieve a significant reduction in the implementation time of the algorithm by using the decimation function and the HSV model.
无人机在汽车上着陆的运动算法
研究了无人机在移动的无人车辆上着陆时,对光学系统信息的处理任务。一般来说,彩色图像分析算法是非常准确的,但它们不能实时工作或需要增强专业计算机的性能。基于“下采样”抽取函数的预处理方法,提出了一种紧凑的高速彩色图像识别算法;HSV模型;Otsu的方法-一种计算灰度图像二值阈值的算法,以及隔离连接组件的方法-双通道法。仿真结果证明了该算法的运行能力和较高的效率。通过使用抽取函数和HSV模型,可以显著减少算法的实现时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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