Motion planning algorithms for tactical actions in robot soccer

Robot soccer became a challenging area in computational intelligence and machine learning, including disciplines like real-time image processing, path planning, control and obstacle avoidance. In this uncertain and highly dynamic environment precise and fast actions are required. Defining dominance areas and implement primitives like kick, pass and dribble are crucial with the aspect of computational time reduction. The hard computing analytical solutions presented in this paper allow accurate and rapid actions that are essential for a successful robot soccer strategy.