Abstract
There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles (AUVs) is proposed for a three-dimensional underwater workspace in the ocean current. Each AUV in the model will be competed, and the shortest path under an ocean current and different azimuths will be selected for task assignment and path planning while guaranteeing the least total consumption. First, the initial position and orientation of each AUV are determined. The velocity and azimuths of the constant ocean current are determined. Then the AUV task assignment problem in the constant ocean current environment is considered. The AUV that has the shortest path is selected for task assignment and path planning. Finally, to prove the effectiveness of the proposed method, simulation results are given.
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We would like to thank Dr. Bing SUN for discussion.
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Project supported by the National Natural Science Foundation of China (Nos. U1706224, 91748117, and 51575336) and the Creative Activity Plan for Science and Technology Commission of Shanghai, China (Nos. 18JC1413000, 18DZ1206305, and 16550720200)
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Zhu, Dq., Qu, Y. & Yang, S.X. Multi-AUV SOM task allocation algorithm considering initial orientation and ocean current environment. Frontiers Inf Technol Electronic Eng 20, 330–341 (2019). https://doi.org/10.1631/FITEE.1800562
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DOI: https://doi.org/10.1631/FITEE.1800562