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. © 2002 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Mitsunaga, N., & Asada, M. (2002). Visual attention control by sensor space segmentation for a small quadruped robot based on information criterion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2377 LNAI, pp. 154–163). Springer Verlag. https://doi.org/10.1007/3-540-45603-1_16
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