Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 최용석 | - |
dc.date.accessioned | 2021-09-08T07:27:25Z | - |
dc.date.available | 2021-09-08T07:27:25Z | - |
dc.date.issued | 2020-03 | - |
dc.identifier.citation | SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing, Page. 2029-2038 | en_US |
dc.identifier.isbn | 978-1-4503-6866-7 | - |
dc.identifier.uri | https://dl.acm.org/doi/10.1145/3341105.3373977 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/164983 | - |
dc.description.abstract | Recently, increasing interest in service robots with artificial intelligence has triggered several studies on developing service robots as human assistants. To perform automated tasks, service robots are not only required to recognize various attributes of the service environment, but they must also determine, which tasks and behaviors to perform, according to their internal system specifications and those of the individual situation. To perform tasks in such a generalized manner efficiently, the service robot must abstractly understand the recognition data obtained from the external environment and plan its tasks by combining the data and existing knowledge. Thus, an abstract and integrated knowledge management of low-level external recognition data and symbolic-level knowledge is indispensable. This study proposes a knowledge model for an integrated robot framework, which is used to provide human-robot interactive services. Our knowledge model is based on an ontology that contains general knowledge which provides clear definitions of common concepts and domain knowledge which provides specific concepts required to understand the information about agents(users and robots), and the environments about human-robot interactive services. An exemplary experiment is given in the context of a social robot service, which shows the usability of our knowledge model. | en_US |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF), a grant funded by the Korean government (Ministry of Science and ICT) (2018R1A5A7059549), the ITRC (Information Technology Research Center) support program (IITP-2017-0-01642) supervised by the IITP (Institute for Information and communications Technology Promotion, Korea), and the Technology Innovation Program (10077553) funded by the Ministry of Trade, Industry, and Energy (MOTIE, Korea). | en_US |
dc.language.iso | en | en_US |
dc.publisher | ACM | en_US |
dc.subject | knowledge framework | en_US |
dc.subject | ontology-based knowledge processing | en_US |
dc.subject | social robot service | en_US |
dc.subject | human-robot interaction | en_US |
dc.title | Ontology-Based Knowledge model for Human-Robot Interactive Services | en_US |
dc.type | Article | en_US |
dc.relation.page | 2029-2038 | - |
dc.contributor.googleauthor | Chang, Doo Soo | - |
dc.contributor.googleauthor | Cho, Gun Hee | - |
dc.contributor.googleauthor | Choi, Yong Suk | - |
dc.relation.code | 20200164 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF COMPUTER SCIENCE | - |
dc.identifier.pid | cys | - |
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