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Article

A Robotic Context Query-Processing Framework Based on Spatio-Temporal Context Ontology

Department of Computer Science, Kyonggi University, San 94-6, Yiui-dong, Youngtong-gu, Suwon-si 443-760, Korea
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Sensors 2018, 18(10), 3336; https://doi.org/10.3390/s18103336
Received: 31 August 2018 / Revised: 27 September 2018 / Accepted: 1 October 2018 / Published: 5 October 2018
(This article belongs to the Special Issue Context and Activity Modelling and Recognition)
Service robots operating in indoor environments should recognize dynamic changes from sensors, such as RGB-depth (RGB-D) cameras, and recall the past context. Therefore, we propose a context query-processing framework, comprising spatio-temporal robotic context query language (ST-RCQL) and a spatio-temporal robotic context query-processing system (ST-RCQP), for service robots. We designed them based on spatio-temporal context ontology. ST-RCQL can query not only the current context knowledge, but also the past. In addition, ST-RCQL includes a variety of time operators and time constants; thus, queries can be written very efficiently. The ST-RCQP is a query-processing system equipped with a perception handler, working memory, and backward reasoner for real-time query-processing. Moreover, ST-RCQP accelerates query-processing speed by building a spatio-temporal index in the working memory, where percepts are stored. Through various qualitative and quantitative experiments, we demonstrate the high efficiency and performance of the proposed context query-processing framework. View Full-Text
Keywords: intelligent service robot; robotic context query; context ontology intelligent service robot; robotic context query; context ontology
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MDPI and ACS Style

Lee, S.; Kim, I. A Robotic Context Query-Processing Framework Based on Spatio-Temporal Context Ontology. Sensors 2018, 18, 3336. https://doi.org/10.3390/s18103336

AMA Style

Lee S, Kim I. A Robotic Context Query-Processing Framework Based on Spatio-Temporal Context Ontology. Sensors. 2018; 18(10):3336. https://doi.org/10.3390/s18103336

Chicago/Turabian Style

Lee, Seokjun, and Incheol Kim. 2018. "A Robotic Context Query-Processing Framework Based on Spatio-Temporal Context Ontology" Sensors 18, no. 10: 3336. https://doi.org/10.3390/s18103336

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