C4.5: programs for machine learning
C4.5: programs for machine learning
BabyTigers 2001: Osaka Legged Robot Team
RoboCup 2001: Robot Soccer World Cup V
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Since the vision sensors bring a huge amount of data, visual attention is one of the most important issues for a mobile robot to accomplish a given task in complicated environments. This paper proposes a method of sensor space segmentation for visual attention control that enables efficient observation by taking the time for observation into account. The efficiency is considered from a viewpoint of not geometrical reconstruction but unique action selection based on information criterion regardless of localization uncertainty. The method is applied to four legged robot that tries to shoot a ball into the goal. To build a decision tree, a training data set is given by the designer, and a kind of off-line learning is performed on the given data set. The visual attention control in the method and the future work are discussed.