Automatic Building Robot Technology Ontology Based on Basic-Level Knowledge
Trung Lam Ngo*, Haeyeon Lee**, and Makoto Mizukawa*
*Graduate School of Engineering, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-ku, Tokyo 135-8548, Japan
**Division of Partner Robot, Toyota Motor Corporation, 4-18 Koraku 1-chome, Bunkyo-ku, Tokyo 112-8701, Japan
When robot comes to our daily life, sharing knowledge is a key factor to realize the symbiosis between human and robot. In previous research, Robot Technology (RT) ontology was proposed as a knowledge base to help robot understands human’s intention in daily activities. However, the method to build that ontology was not discussed. This paper presents our approach to build RT ontology based on basic-level knowledge. We proposed a new structure for RT ontology with Where, What, and How layers based on 4W1H. As for input data, we used educational books and MIT’s ConceptNet. Our method is able to build RT ontology automatically by extracting objects and human activities from these data sources. We also implemented a weighting mechanism for the new ontology. Result shows that our method achieved better accuracy than conventional approach using Internet data.
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