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Dynamic Bayesian Network Modeling and Reasoning Based on Ontology for Occluded Object Recognition of Service Robot  

Song, Youn-Suk (연세대학교 컴퓨터과학과)
Cho, Sung-Bae (연세대학교 컴퓨터과학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.13, no.2, 2007 , pp. 100-109 More about this Journal
Abstract
Object recognition of service robots is very important for most of services such as delivery, and errand. Conventional methods are based on the geometric models in static industrial environments, but they have limitations in indoor environments where the condition is changable and the movement of service robots occur because the interesting object can be occluded or small in the image according to their location. For solving these uncertain situations, in this paper, we propose the method that exploits observed objects as context information for predicting interesting one. For this, we propose the method for modeling domain knowledge in probabilistic frame by adopting Bayesian networks and ontology together, and creating knowledge model dynamically to extend reasoning models. We verify the performance of our method through the experiments and show the merit of inductive reasoning in the probabilistic model
Keywords
Object Recognition; Service Robot; Bayesian network; Ontology;
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Times Cited By KSCI : 1  (Citation Analysis)
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