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Colored Petri Net Representation of Logical and Decisive Passing Algorithm for Humanoid Soccer Robots

机译:人性化足球机器人的逻辑和决定性传递算法的彩色Petri网表示

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The Robot World Cup Initiative instigates the challenge of programming robots which will one day be capable of competing against a human soccer team. The current state of the RoboCup Standard Platform League requires utilization of the humanoid NAO robots created by Aldebaran. While teams have made incredible progress in programming a NAO's ability to play the game, there is still a long way before a robot's thinking is anywhere close to the complexity of a human's brain when playing a soccer match. A team's strategy is crucial in winning a soccer match, but RoboCup teams have yet to program the robots in a manner where teamwork is utilized. With the intricacies that must be accounted for in programming a robot to play an entire soccer game, the Colored Petri net (CPN) model can be useful in providing a basis for analyzing and testing algorithms for gameplay prior to implementation. To explore the possibility of teamwork in RoboCup gameplay, this paper proposes and tests the Passing with Logical Strategy (PaLS) algorithm, which guides the robots' kicking decision and avoids opponents from gaining control of the ball via intentional and decisive passing between teammates. When compared to a path finding algorithm proposed by Bajrami, Dërmaku, and Demaku, the PaLS algorithm performs 34% more efficiently, proving that by utilizing a team-based algorithm, the ball can reach the goal faster.
机译:机器人世界杯计划激发了编程机器人的挑战,该机器人将有一天能够与一支人类足球队竞争。 RoboCup标准平台联盟的当前状态要求使用Aldebaran创建的类人动物NAO机器人。尽管团队在编写NAO的比赛能力方面取得了令人难以置信的进步,但距离足球比赛中机器人的思维还远不及人类大脑的复杂性,还有很长的路要走。团队的策略对于赢得足球比赛至关重要,但是RoboCup团队尚未以利用团队合作的方式对机器人进行编程。由于在编程机器人以进行整个足球比赛时必须考虑到的复杂性,有色Petri网(CPN)模型可为在实施之前分析和测试游戏玩法的算法提供基础。为了探索RoboCup游戏中团队合作的可能性,本文提出并测试了“通过逻辑策略传球”(PaLS)算法,该算法可指导机器人的踢球决策,并避免对手通过队友之间的有意和果断传球来控制球。与Bajrami,Dërmaku和Demaku提出的寻路算法相比,PaLS算法的执行效率提高了34%,这证明通过使用基于团队的算法,控球可以更快地达到目标。

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