We propose an efficient semantic map to realize flexible human-robot interaction (HRI) in domestic environments. Our proposed map is created from an output of Simultaneous Localization and Mapping and already-known environmental information such as furniture and room. In this study, we evaluated the effectiveness of our proposed method on two benchmark tests for HRI in RoboCup@Home held in Bangkok in 2022. In the RoboCup@Home, we employ 3D human recognition to apply our proposed map to HRI, such as "find and offer an empty seat." Our proposed method had the best score of all teams on both tests. The results of our experiments are available at https://youtube.com/playlist?list=PLfbN50Mwh2DG3OPDeCHo4TNuyrU4qYCrJ.

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