Colored Petri Net Representation of Logical and Decisive Passing Algorithm for Humanoid Soccer Robots

The Robot World Cup Initiative instigates the challenge of programming robots which will one day be capable of competing against a human soccer team. The current state of the RoboCup Standard Platform League requires utilization of the humanoid NAO robots created by Aldebaran. While teams have made incredible progress in programming a NAO's ability to play the game, there is still a long way before a robot's thinking is anywhere close to the complexity of a human's brain when playing a soccer match. A team's strategy is crucial in winning a soccer match, but RoboCup teams have yet to program the robots in a manner where teamwork is utilized. With the intricacies that must be accounted for in programming a robot to play an entire soccer game, the Colored Petri net (CPN) model can be useful in providing a basis for analyzing and testing algorithms for gameplay prior to implementation. To explore the possibility of teamwork in RoboCup gameplay, this paper proposes and tests the Passing with Logical Strategy (PaLS) algorithm, which guides the robots' kicking decision and avoids opponents from gaining control of the ball via intentional and decisive passing between teammates. When compared to a path finding algorithm proposed by Bajrami, Dërmaku, and Demaku, the PaLS algorithm performs 34% more efficiently, proving that by utilizing a team-based algorithm, the ball can reach the goal faster.