Abstract
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.
This project is supported by the National Natural Science Foundation of China (61503239, 51575336), and the Creative Activity Plan for Science and Technology Commission of Shanghai (15550722400).
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Sun, B., Zhu, X., Zhang, W., Zhu, D., Chu, Z. (2018). Three Dimensional AUV Complete Coverage Path Planning with Glasius Bio-inspired Neural Network. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10985. Springer, Cham. https://doi.org/10.1007/978-3-319-97589-4_11
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DOI: https://doi.org/10.1007/978-3-319-97589-4_11
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