Signaling Human Intentions to Service Robots: Understanding the Use of Social Cues during In-Person Conversations

要旨

As social service robots become commonplace, it is essential for them to effectively interpret human signals, such as verbal, gesture, and eye gaze, when people need to focus on their primary tasks to minimize interruptions and distractions. Toward such a socially acceptable Human-Robot Interaction, we conducted a study (N=24) in an AR-simulated context of a coffee chat. Participants elicited social cues to signal intentions to an anthropomorphic, zoomorphic, grounded technical, or aerial technical robot waiter when they were speakers or listeners. Our findings reveal common patterns of social cues over intentions, the effects of robot morphology on social cue position and conversational role on social cue complexity, and users' rationale in choosing social cues. We offer insights into understanding social cues concerning perceptions of robots, cognitive load, and social context. Additionally, we discuss design considerations on approaching, social cue recognition, and response strategies for future service robots.

受賞
Honorable Mention
著者
Hanfang Lyu
Hong Kong University of Science and Technology, Hong Kong, Hong Kong
Xiaoyu Wang
The Hong Kong University of Science and Technology, Hong Kong, Hong Kong
Nandi Zhang
University of Calgary, Calgary, Alberta, Canada
Shuai Ma
The Hong Kong University of Science and Technology, Hong Kong, China
Qian Zhu
The Hong Kong University of Science and Technology, Hong Kong, China
Yuhan Luo
City University of Hong Kong, Hong Kong, China
Fugee Tsung
The Hong Kong University of Science and Technology, Hong Kong, International, China
Xiaojuan Ma
Hong Kong University of Science and Technology, Hong Kong, Hong Kong
DOI

10.1145/3706598.3714235

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714235

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Interacting with Robots

G318+G319
7 件の発表
2025-04-30 20:10:00
2025-04-30 21:40:00
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