Abstract
RoboCup, a project originally named the Robot World Cup Initiative, challenges people around the world to program robots that are capable of competing in a soccer tournament. The goal is that one day, a group of robots will be able to match the playing ability of a human soccer team, and even be able to win against humans in soccer. The RoboCup Standard Platform League utilizes teams of humanoid NAO robots. These robots must be successfully programmed with image recognition, positioning, ball kicking, and a playing strategy in order to successfully get through a match. In human soccer, a team strategy is crucial to winning a match, but not all RoboCup teams have programmed their team strategies to call on the robots to work together in order to score a goal. The improved Passing with Logical Strategy (iPaLS) is an algorithm that proposes passing of the ball between players to more quickly score a goal. This algorithm is an extension of the Passing with Logical Strategy (PaLS) algorithm, which proposed a more rudimentary method of passing between players. iPaLS builds upon PaLS by further exploring the kicking decisions that must be made by the NAO robot and considers ways to hinder the opposing team’s ability to gain possession of the ball and ways to regain possession of the ball if possession is lost. Colored Petri net modeling and simulation is used in order to test the various scenarios of a system that implements iPaLS and helps to prove the advantages of this algorithm over a strategy of having each NAO robot kick the ball towards the goal without regard for their teammates.
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Pham, K.T., Cantone, C., Kim, Sy. (2019). Improved Logical Passing Strategy and Gameplay Algorithm for Humanoid Soccer Robots Using Colored Petri Nets. In: Bouabana-Tebibel, T., Bouzar-Benlabiod, L., Rubin, S. (eds) Theory and Application of Reuse, Integration, and Data Science. IEEE IRI 2017 2017. Advances in Intelligent Systems and Computing, vol 838. Springer, Cham. https://doi.org/10.1007/978-3-319-98056-0_1
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