基于改进仿生神经网络的水下航行器三维实时路径规划

2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW) Pub Date : 2016-05-27 DOI:10.1109/ICCE-TW.2016.7520935

J. Ni, Liuying Wu, Shihao Wang, Kang Wang

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引用次数: 7

摘要

提出了一种基于仿生神经网络的自主水下航行器(AUV)三维环境实时路径规划改进算法。该算法对神经网络模型的分流方程进行了改进，有利于动态环境下的路径规划。该方法效率高，实时性好。

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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3D real-time path planning for AUV based on improved bio-inspired neural network

An improved algorithm based on bio-inspired neural network is proposed for Autonomous Underwater Vehicle (AUV) real-time path planning in three-dimensional (3D) environment in this paper. The algorithm has made an improvement in the shunting equation of the neural network model which is conductive to path planning especially in dynamic environments. The proposed approach has high efficiency and good real-time performance.

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来源期刊

2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

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