期刊
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
卷 11, 期 1, 页码 73-84出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCDS.2018.2810235
关键词
Autonomous underwater vehicles (AUVs); complete coverage; Glasius bio-inspired neural network (GBNN); path planning
资金
- National Natural Science Foundation of China [61503239, U170620065]
- Creative Activity Plan for Science and Technology Commission of Shanghai [15550722400]
- National Key Research and Development Plan [2017YFC0306302]
For the complete coverage path planning of autonomous underwater vehicles (AUVs), a new strategy with Glasius bio-inspired neural network (GBNN) algorithm with discrete and centralized programming is proposed. The basic modeling for multi-AUVs complete coverage problem based on grid map and neural network is discussed first. Then, the design for single AUV complete coverage is introduced based on GBNN algorithm which is a new developed tool with small amount of calculation and high efficiency. In order to solve the difficulty of single AUV full coverage task of large water range, the multi-AUV full coverage discrete and centralized programming is proposed based on GBNN algorithm. The simulation experiment is conducted to confirm that through the proposed algorithm, multi-AUVs can plan reasonable and collision-free coverage path and reach full coverage on the same task area with division of labor and cooperation.
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