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Recognizing Patterns of Dynamic Behaviors Based on Multiple Relations in Soccer Robotics Domain

机译:足球机器人领域基于多重关系的动态行为识别模式

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This work is focused on the recognition of team patterns represented by different formations played by a soccer team during a match. In the soccer domain, the recognition of formation patterns is difficult due to the dynamic and real time conditions of the environment as well as the multiple interactions among team mates. In this work, some of these multiple interactions are modeled as relations represented by a topological graph which is able to manage the dynamic changes of structures. Thus, the topological graph serves to recognize apparent changes of formations from real changes of them. The proposed model has been tested with different teams in different matches of the Robocup Simulation League. The results have shown that the model can recognize the different main formations used by a team during a match even the multiple changes of the players due to the dynamic nature of a match.
机译:这项工作的重点是识别由足球队在比赛中扮演的不同阵型所代表的球队模式。在足球领域,由于环境的动态和实时条件以及队友之间的多次交互,很难识别队形的形式。在这项工作中,这些多重相互作用中的一些相互作用被建模为由能够管理结构动态变化的拓扑图表示的关系。因此,拓扑图用于从岩层的真实变化中识别岩层的明显变化。该模型已经在Robocup Simulation League的不同比赛中与不同的团队进行了测试。结果表明,该模型可以识别团队在比赛中使用的不同主要队形,甚至由于比赛的动态性质,也可以识别玩家的多次变化。

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