Local Multiresolution Path Planning in Soccer Games Based on Projected Intentions

Following obstacle free paths towards the ball and avoiding opponents while dribbling are key skills to win soccer games. These tasks are challenging as the robot’s environment in soccer games is highly dynamic. Thus, exact plans will likely become invalid in the future and continuous replanning is necessary. The robots of the RoboCup Standard Platform League are equipped with limited computational resources, but have to perform many parallel tasks with real-time requirements. Consequently, path planning algorithms have to be fast. In this paper, we compare two approaches to reduce the planning time by using a local-multiresolution representation or a log-polar representation of the environment. Both approaches combine a detailed representation of the vicinity of the robot with a reasonably short planning time. We extend the multiresolution approach to the time dimension and we predict the opponents movement by projecting the planning robot’s intentions.