저널 : JICRS(Journal of Institute of Control, Robotics and Systems), Vol.25, No.1, pp.736-741, 2019. 1.
· 논문제목 : “A Spatio-Temporal Context Query Processing Framework for Service Robots”
· 저자 : 이석준, 김인철
· 요약 : In this paper, we propose a context query language, ST-RCQL(Spatio-Temporal Robotic Context Query Language), and an efficient query processing system, ST-RCQP, for service robots operating in indoor environments. In order to accomplish their tasks successfully, indoor service robots should not only recognize the current context changing dynamically, but also remember past contexts. To meet these requirements, the proposed context query language ST-RCQL is designed to retrieve efficiently 3D spatial relations between indoor objects which continuously change as time goes by. Based on Allen’s interval algebra, ST-RCQL includes convenient temporl operators to find and compare different spatial contexts on different times. ST-RCQL has high expressive power to represent spatio-temporal context queries, and also has the precise grammar structure. The proposed ST-RCQP is a query processing system, which finds answers for ST-RCQL context queries efficiently. In order to infer high-level spatial relationships between objects from real-time sensory data, ST-RCQP contains a backward spatial inference engine. Moreover, it has the facility to improve the query processing speed by maintaining both the temporal index and the spatial index for a large amount of context knowledge base. Through various qualitative and quantitative experiments, we demonstrate the high efficiency and performance of both the proposed query language SP-RCQL and the query processing system ST-RCQP.