基于RoboCup仿真2D的数字孪生框架应用

Application of digital twin framework based on RoboCup simulation 2D

RoboCup意为机器人世界杯足球赛,它是目前人工智能领域重要的国际学术赛事活动之一,迄今已举办22届。其中仿真2D是RoboCup中主要的分支,其项目状态空间极为庞大,优化、研发工作难以具有针对性。为了解决该问题,构建由物理层、信息层和数字孪生层组成的基于仿真2D下的数字孪生模型框架,并依托该框架,以球员画像为重点,对日志文件解析、信息层处理及球员画像建立等关键技术和问题进行研究,探索球队攻守态的判定优化因素。同时研究表明,该框架可以有效地为球队优化指导提供捷径。

RoboCup(Robot World Cup)is one of the most important international academic events in the field of artificial intelligence,and 22 sessions have been held.Simulation 2D is the main branch of RoboCup.As its state space is too large,it is difficult to optimize and develop.To solve this problem,we have constructed a simulation 2D digital twin model framework,consisting of physical layer,information layer and digital twin layer.Based on this framework,we investigated the key technologies and problems of log file parsing,information layer processing and player portrait building.Focusing on the portraits of the players,we explored the factors determining the team's offensive and defensive state.The result shows that this framework can effectively provide a shortcut for team optimization guidance.