Analysis of Soccer Robot Behaviors Using Time Petri Nets

Abstract

Using Petri nets (PNs) to model complex systems allows for analysis and increased comprehension of the system itself. PNs can be used to show the logic behind a system or to create a visual representation of the steps a system will take. Although this alone can be useful, there are some areas in which normal PNs fail, in these cases introducing time into the nets can open the modeling possibilities. Time can be used to literally represent the duration of an event or can be used to implement probability into a system. In this paper, Time Petri nets (TPNs) are used to model soccer playing robots whose movements are based on the proposed algorithm, which serves to guide the robots to the safest path to the goal. After modeling and testing, it was shown that the proposed algorithm, Optimal Path for Ball Movement, outperformed both random prioritization and the Rapidly-exploring Random Tree algorithm by about 43% and 37%, respectively.