Three Dimensional AUV Complete Coverage Path Planning with Glasius Bio-inspired Neural Network

In this paper, with the combination of AUV working characteristics in three-dimensional underwater space, an AUV complete coverage path planning algorithm based on GBNN model (Glasius Bio-inspired Neural Network) is proposed. The three dimensional space is divided into different depth plane, and in turn completely traverse multiple two-dimensional flat water surface, to solve the AUV three-dimensional complete coverage path planning problem. Through simulation experiment and discussion, it can be verified that, whether it is a static environment or the dynamic environment for the whole three-dimensional space, AUV can cover all the specified work waters without omissions and collision.

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