Abstract: UAV hunting is a challenging and realistic task. In order to enable UAVs to hun moving targets successfully and effectively, a multi-UAV hunting algorithm based on dynamic prediction of hunting points and improved whale optimization algorithm is proposed. When the environment is unknown and the target motion trajectory is unknown, this paper first uses polynomial fitting to predict the target motion trajectory, obtains the prediction point by dynamically predicting the number of steps, sets up hunting points around it, and then uses the two-way negotiation method to make reasonable assign each target point. Aiming at the shortcomings of the whale optimization algorithm that it is easy to fall into the local optimum, a method based on adaptive weights and changing the position of the spiral is proposed to improve the development ability and search ability of the algorithm. Finally, several experimental simulations were carried out in different experimental environments, and the experimental results showed the effectiveness of the proposed algorithm.

Key words: dynamic prediction, target hunting, two-way negotiation, whale optimization algorithm