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

机译:基于改进的生物启发式神经网络的AUV 3D实时路径规划

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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.
机译:提出了一种基于生物启发神经网络的改进算法,用于三维(3D)环境下的自动水下航行器(AUV)实时路径规划。该算法对神经网络模型的分流方程进行了改进,特别是在动态环境中,它有助于进行路径规划。该方法具有较高的效率和良好的实时性能。

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