Xiang Cao1,2,3, Haichun Yu1,3, Hongbing Sun1,3
Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 25-34, 2019, DOI:10.31209/2018.100000038
Abstract For cooperative hunting by a multi-AUV (multiple autonomous underwater
vehicles) team, not only basic problems such as path planning and collision
avoidance should be considered but also task assignments in a dynamic way. In
this paper, an integrated algorithm is proposed by combining the self-organizing
map (SOM) neural network and the Glasius Bio-Inspired Neural Network
(GBNN) approach to improve the efficiency of multi-AUV cooperative hunting.
With this integrated algorithm, the SOM neural network is adopted for dynamic
allocation, while the GBNN is employed for path planning. It deals with various
situations for single/multiple target(s) hunting in underwater environments with
obstacles.… More >
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