Soccer Robots Local Passing And Tactics Cooperation

Soccer robot is a frontier project in artificial intelligence and robotics research, which is a bridge connecting fundamental research and practical application. On the basis of Apollo3 D team’s RoboCup3 D robot soccer simulation environment, this paper presents the improvement and optimization of the humanoid robot action and multi.agent pass tactics against collaborative.Initially, this paper introduces the Nao robot model and structure. Subsequently, the following chapters describe the robot motion planning of various actions. Aiming at the kicking design of humanoid robots, this paper presented a gradual accumulation learning method which based on the Covariance Matrix Adaptation Evolution Strategy(CMAES).Through three layers of learning optimization implemented the passing action from flexible to stable and accurate. This method makes long.distance, stable and quick passing motions come true.Simultaneously, this paper proposes a passing method based on reinforcement learning to realize multi.agent cooperation strategy under the platform of Keepaway. The platform of Keepaway3 vs 2 was a local tactical strategy in 2D simulation competition proposed by Peter Stone. In this section, it builds a Keepaway model in RoboCup3 D simulation game, then takes advantage of Sarsa(?) algorithm based linear function approximation in this training model to implement the strategy of soccer robot in team collaboration mechanism, include PASS and GETOPEN strategy.Finally, the team coordination mechanism is achieved in RoboCup multi.agent system. After that, establishing a dynamic role assignment system and various formation,thus achieving the overall collaborative alliance, and rely on teamwork to achieve an effective offensive strategy.Some competitions have proved that the proposed methods above greatly improve individual and overall performances of Apollo3 D, especially in the robot dynamic obstacle avoidance and coordination, the effects of which are remarkable.