Design and implementation of educational platform in RoboCup simulation games

RoboCup is an international game and academic activity which focuses on improving the education and research of distributed AI, intelligent robotics, machine learning and other related fields. To stimulate the student's interests of AI research and introduce the RoboCup games to more students, we transplant the RoboCup to an educational platform for students to study and research. This paper shows the structure and design of the whole platform, the specific implementation of basic modules on the educational platform. The platform is divided into three parts: low-level module, libraries, and program scheme. Students should work in the programming scheme part, build the basic skill and top-level strategy layer. This paper describes the main theory of the basic skills such as dribble, kick, and shoot, including the distributed planning in realizing these skills. The top-level strategy part analyzes the realization of several basic strategies and machine learning's impact on the game. We also provide the method and framework for implementing the basic skills and top-level strategy, called the qsinghuAeolus program. Finally, we show the educational value of the platform in RoboCup simulation games.