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WIREs Cogn Sci
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Robot soccer

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Abstract Robot soccer is a test bed for a variety of robotic and Artificial Intelligence (AI) methods. Its relevance to Cognitive Science is that it confronts the designer with a task that requires the integration of almost all aspects of AI to create an agent that is capable of working in a complex, dynamic environment inhabited by other agents, some of which are cooperative and others competitive. We describe the main elements that make up a robot soccer player and how these players associate to create effective teams. We pay special attention to the architecture of the players. WIREs Cogn Sci 2010 1 824–833 This article is categorized under: Computer Science > Robotics Psychology > Theory and Methods

(a) Sony's Aibo ERS‐7 and (b) the Aldebaran Nao.

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Behaviors implemented as a decision tree.

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The trajectory of ‘paws’ can be described by a simple figure whose parameters are easy to tune for different walks.

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The world model of two robots on the ‘blue’ team. Blue ellipses represent blue robots; red ellipses represent red robots; orange represents the robot's estimate of where the ball is; and pink is the other teammate's estimate of where the ball is. The gray arc is the robot's heading.

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Line detection is done by scanning bottom to top with increasing resolution.

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3D YUV Color space. The data represent pixels that have been manually labeled with the correct color. These can be used as training data for learning color regions.

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Architecture of a soccer robot.

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A RoboCup rescue arena.

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The soccer field (from the Standard Platform League Nao Rule Book10).

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Computer Science > Robotics
Psychology > Theory and Methods

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