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Titlebook: RoboCup 2000: Robot Soccer World Cup IV; Peter Stone,Tucker Balch,Gerhard Kraetzschmar Conference proceedings 2001 Springer-Verlag Berlin

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发表于 2025-3-21 16:30:23 | 显示全部楼层 |阅读模式
书目名称RoboCup 2000: Robot Soccer World Cup IV
编辑Peter Stone,Tucker Balch,Gerhard Kraetzschmar
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: RoboCup 2000: Robot Soccer World Cup IV;  Peter Stone,Tucker Balch,Gerhard Kraetzschmar Conference proceedings 2001 Springer-Verlag Berlin
出版日期Conference proceedings 2001
关键词RoboCup; algorithmic learning; artificial intelligence; computer vision; cooperation; coordination; humano
版次1
doihttps://doi.org/10.1007/3-540-45324-5
isbn_softcover978-3-540-42185-6
isbn_ebook978-3-540-45324-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2001
The information of publication is updating

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FC Portugal Team Description: RoboCup 2000 Simulation League Championonly three months later, in Amsterdam, FC Portugal became the first European Champion of RoboCup scoring a total of 86 goals without conceding a single goal. Three months later, in Melbourne, FC Portugal became RoboCup Simulation League World Champion scoring 94 goals, again without conceding any go
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The UNSW RoboCup 2000 Sony Legged League Team their soccer matches, emerging the outright winners for this league against eleven other international teams. The main advantage that the UNSW team had was speed. The robots not only moved quickly, due to a novel locomotion method, but they also were able to localise and decide on an appropriate ac
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Communication and Coordination among heterogeneous Mid-Size Players: ART99ation and F-180 leagues. In this paper we describe the methods and the results achieved in coordinating the players of the ART team participating in the F-2000 league. The team is formed by several heterogeneous robots having different mechanics, different sensors, different control software, and, i
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A Localization Method for a Soccer Robot Using a Vision-Based Omni-Directional Sensored to fully autonomous soccer robots participating in the middle-size league of RoboCup competitions. It uses natural landmarks of the soccer field, such as field lines and goals, as well as a priori knowledge of the field geometry, to determine the robot position and orientation with respect to a c
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Behavior Classification with Self-Organizing MapsboCup players. By training the Self-Organizing Map with player data we have the possibility to identify various clusters representing typical agent behavior patterns. Thus we can draw certain conclusions about their tactical behavior, using purely motion data, i.e. logfile information. In addition,
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Flexible Synchronisation Within RoboCup Environment: a Comparative Analysistion with the environment. A systematic comparative analysis of alternative approaches to the synchronisation problem remains an open challenge, despite numerous successful implementations of RoboCup teams in the past. The underlying reasons appear to be a multiplicity of software platforms, impleme
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