974 research outputs found

    RoboCup: the evolution of a robotic scientific challenge

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    The RoboCup is a scientific challenge used to foster research in the robotics areas, which main objective consists in developing a robotic football team able to play against a human team in the year 2050. This paper describes the rules of such a competition, the actual state of the art of robotic football players in the middle size league, and describes the main characteristics to take into account in order to build such type of robots. These aspects are described and analysed in terms of further developments.Fundação para a Ciência e a Tecnologia (FCT) - projecto “Development of Robotic Football Team for participation in the RoboCup (Middle Size League)”, POSI/ROBO/43892/2002

    Problems and solutions in middle size robot soccer: a review

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    A review of current scientific and technological problems encountered in building and programming middle size soccer robots is made in this paper. Solutions and solution trends to the problems, as presented by different teams, are also examined. Perceptual systems of individual robots, in particular with respect to object location, communications between robot players, decision making with regard to game strategy and behaviour generation, and, finally, actuation, are the topics dealt with. This makes for a wide perspective on the actual state of the art of middle size soccer robots

    Behavior Acquisition in RoboCup Middle Size League Domain

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    Neural network in computer vision for RoboCup middle size league

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    Robot World Cup Initiative (RoboCup) is a worldwide competition proposed to advance research in robotics and artificial intelligence. It has a league called RoboCup soccer devoted for soccer robots. Robotic soccer is a challenge because robots are mobile, fully autonomous, multi-agents, and they play on a dynamic environment. Moreover, robots must recognize the game entities, which is a crucial task during a game. A camera is usually used as an input system to recognize ball, opponents, soccer field, and so on. These elements may be recognized applying some tools of computational intelligence, for example an artificial neural network. This paper describes the application of an artificial neural network on middle size robotic football league, where a multilayer perceptron neural network is trained with the backpropagation algorithm, to classify elements on the image. The results show that an artificial neural network successfully classified the entities. They were recognized even when similar color entities were present on the image.info:eu-repo/semantics/publishedVersio
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