Journal
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
Volume 20, Issue 3, Pages 330-341Publisher
ZHEJIANG UNIV
DOI: 10.1631/FITEE.1800562
Keywords
Autonomous underwater vehicles; Self-organizing neural networks; Azimuths; Ocean current
Categories
Funding
- National Natural Science Foundation of China [U1706224, 91748117, 51575336]
- Creative Activity Plan for Science and Technology Commission of Shanghai, China [18JC1413000, 18DZ1206305, 16550720200]
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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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