AUV Cooperative Hunting Algorithm based on Bio-inspired Neural Network for Path Conflict State

Cooperative hunting is a challenging and critical issue in multi-AUV system research. To conduct the cooperative hunting by multi-AUV in underwater environments, the AUVs not only need to take into account catch the target efficiently, but also need to avoid path conflict. In this paper, a novel algorithm based on bio-inspired neural network is proposed for the cooperative hunting by multi-AUV. Firstly, based on the establishment of bio-inspired neural network model, AUV working environment is represent by it, there is one-to-one correspondence between each neuron in neural network and the position of the grid map of underwater environment. Then the activity values of biological neurons guide the AUV's sailing path and finally the target is surrounded by AUVs. In addition, a method called location forecasting is used to solve the path conflict of AUVs. The simulation results show that the algorithm used in the paper can provide a rapid and high efficient hunting in the underwater environment with obstacles and non-obstacles.