Design of path planning based Cellular Neural Network

Yan Cao, Xiaolan Zhou, Shuai Li, Feng Zhang, Xinwei Wu, A. Li, Lei Sun
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引用次数: 6

Abstract

In this paper , a Novel Cellular Neural Network (CNN) entitled the shortest path CNN (SP-CNN) is proposed. It has a good performance in path planning for mobile robots because of its network structure and neural dynamics. The proposed method not only can generate the best solution in static environments in real time but also generate the optional solution in dynamic environments or in unknown environments according to its currently acquired navigation map. Extensive simulations about the above mentioned aspects demonstrate the effectiveness of the proposed approach.
基于细胞神经网络的路径规划设计
本文提出了一种新颖的细胞神经网络(CNN),称为最短路径CNN (SP-CNN)。由于其网络结构和神经动力学特性,在移动机器人的路径规划中具有良好的性能。该方法既能实时生成静态环境下的最优解,又能根据当前获取的导航地图生成动态环境或未知环境下的可选解。对上述各方面的大量仿真验证了所提方法的有效性。
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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