Decision-Making and Tactical Behavior with Potential Fields

Using potential fields is a technique seldom used in RoboCup scenarios. The existing approaches mainly concentrate on world state representations of single actions such as a kick. In this paper we will show how to apply potential fields to assist fast and precise decisions in an easy and intuitive way. We go beyond the existing approaches by using potential fields to determine all possible player actions, basic and advanced tactics, and also general player behaviors. To ensure fast computing, we mainly use basic mathematical computations for potential field-related calculations. This gives us the advantage of both determining and understanding player actions. Therefore, the integration of future features such as a complex online coach and progressive localization methods will be easier. We implemented the approach in our team Bremen University Goal Seekers (BUGS) and tested it in numerous games against other simulation league teams. The results show that the CPU-time for decision-making has been decreased significantly. This is a crucial improvement for calculations in time-critical environments.