Guoyu Zuo

Two-agent collaborative shooting method using BP neural network

A two-agent collaborative shooting method based on BP neural network was proposed to improve the shooting success rate. In this method, the two players, an assistant player and a shooter, perform a shooting behavior collaboratively using the position relationships among the assistant player, the shooter and the goal. The three shooting parameters, the assistants passing speed and passing angle and the shooters spinning rate, are predicted using a BP neural network model, and the relative distances and angles between the assistant passer and the shooter at the beginning of shooting and those between the shooter and the mid-point of goal are used as the input of this BP model. The experiments of simulation match were conducted on the Robot Soccer v1.5a platform. Experimental results show that the collaborative shooting method using BP network has a higher shooting efficiency.

Penalty kick strategy using two-player collaboration method

In order to improve the match success rate, we proposed a penalty kick strategy based on two-player collaborative shooting method which is used in two different defense patterns. In this strategy, a self-rotation shooting method is applied when the opponent goalkeeper run out to destroy the ball and a reflecting shooting method is used when the goalkeeper stays at the goal line. The SimuroSot 5vs5 Simulation experiments were conducted on the Robot Soccer v1.5a platform. Experimental results show that the proposed method can get a good match success rate.