The Impact of Robot’s Body Language on Customer Experience: An Analysis in a Cafe Setting

Tan Viet Tuyen Nguyen, Mateusz Adamski, Yuchen Wang, Shintaro Okazaki, Oya Celiktutan

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

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Abstract

Nonverbal communication plays a crucial role in human-robot interaction (HRI) and have been widely used for robots in service environments. While few studies have addressed the understanding customer’s acceptance of robots under many different interaction conditions, the impact of robots’ nonverbal interaction modalities (i.e., a combination of body language, voice, and touch) on customers’ experience has not been investigated truly. To this end, in this paper, we introduce an HRI framework that aims to assist customers in their food and beverage choices in a real-world cafe setting. With this framework, the contribution of this paper are two folds. We introduce a time-synchronised multisensory HRI dataset comprising the interactions between a social robot and customers in a real-world environment. We conduct a user study to evaluate the configuration of multimodal HRI framework, particularly nonverbal gestures, and its contribution to customers’ interaction experience in this specific marketing setting.
Original languageEnglish
Title of host publicationCompanion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction (HRI’23 Companion)
PublisherACM
Publication statusAccepted/In press - 2023

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