一种利用多普勒效应改进的基于CNN的路径规划算法

R. Yeniceri, M. Yalçin
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引用次数: 3

摘要

文献中发现了许多使用细胞神经/非线性网络(CNN)的路径规划和导航论文。这些作品中有很大一部分来源于CNN的波处理特性。本文提出了已知元胞非线性网络模型的一个特殊条件,使得该网络非常适合获得嵌套的重复行波。在这种特殊条件下,多普勒效应作为一个必然结果出现。多普勒效应对使用cnn的路径规划应用程序的主要贡献是提供了一个机会来调整跟踪器的速度或完全改变路线,取决于目标的运动。从而对基于cnn的波计算技术对波源运动的应用有了新的认识。
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A new CNN based path planning algorithm improved by the Doppler effect
Many path planning and navigation papers using Cellular Neural/Nonlinear Networks (CNN) are found in literature. High proportion of these works originated by wave processing feature of CNN. This paper proposes a special condition of a known Cellular Nonlinear Network model which makes the network very proper to obtain nested and repetitive travelling waves. The Doppler effect appears as a corollary using this special condition. The main contribution of the Doppler effect to the path planning applications that uses CNNs is giving an opportunity to adjust the tracker's speed or change the route completely, dependent to the target's motion. By this way, this paper gains a new qualification to the CNN-based wave computing techniques putting the wave source's motion into use.
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