@Article{2018.100000038,
AUTHOR = {Xiang Cao, Haichun Yu, Hongbing Sun},
TITLE = {Dynamic Task Assignment for Multi-AUV Cooperative Hunting},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {25},
YEAR = {2019},
NUMBER = {1},
PAGES = {25--34},
URL = {http://www.techscience.com/iasc/v25n1/39638},
ISSN = {2326-005X},
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. The simulation results show that the proposed algorithm is capable 
of a cooperative hunting task with efficiency and adaptability.},
DOI = {10.31209/2018.100000038}
}