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Robot Knowledge Framework of a Mobile Robot for Object Recognition and Navigation  

Lim, Gi-Hyun (Division of Electrical Computer Engineering, Hanyang University)
Suh, Il-Hong (Collage of Information and Communications, Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.44, no.6, 2007 , pp. 19-29 More about this Journal
Abstract
This paper introduces a robot knowledge framework which is represented with multiple classes, levels and layers to implement robot intelligence at real environment for mobile robot. Our root knowledge framework consists of four classes of knowledge (KClass), axioms, rules, a hierarchy of three knowledge levels (KLevel) and three ontology layers (OLayer). Four KClasses including perception, model, activity and context class. One type of rules are used in a way of unidirectional reasoning. And, the other types of rules are used in a way of bi-directional reasoning. The robot knowledge framework enable a robot to integrate robot knowledge from levels of its own sensor data and primitive behaviors to levels of symbolic data and contextual information regardless of class of knowledge. With the integrated knowledge, a robot can have any queries not only through unidirectional reasoning between two adjacent layers but also through bidirectional reasoning among several layers even with uncertain and partial information. To verify our robot knowledge framework, several experiments are successfully performed for object recognition and navigation.
Keywords
Robot Knowledge; Robot ontology; Bi-directional reasoning; Object Recognition; Navigation;
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