An Approach to Elicit Human-Understandable Robot Expressions to Support Human-Robot Interaction

要旨

Understanding the intentions of robots is essential for natural and seamless human-robot collaboration. Ensuring that robots have means for non-verbal communication is a basis for intuitive and implicit interaction. For this, we describe an approach to elicit and design human-understandable robot expressions. We outline the approach in the context of non-humanoid robots. We paired human mimicking and enactment with research from gesture elicitation in two phases: first, to elicit expressions, and second, to ensure they are understandable. We present an example application through two studies (N=16 \& N=260) of our approach to elicit expressions for a simple 6-DoF robotic arm. We show that the approach enabled us to design robot expressions that signal curiosity and interest in getting attention. Our main contribution is an approach to generate and validate understandable expressions for robots, enabling more natural human-robot interaction.

著者
Jan Leusmann
LMU Munich, Munich, Germany
Steeven Villa
LMU Munich, Munich, Germany
Thomas Liang
University of Illinois Urbana-Champaign, Champaign, Illinois, United States
Chao Wang
Honda Research Institute Europe, Offenbach/Main, Germany
Albrecht Schmidt
LMU Munich, Munich, Germany
Sven Mayer
LMU Munich, Munich, Germany
DOI

10.1145/3706598.3713085

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713085

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: Human-Agent Interaction

Annex Hall F204
7 件の発表
2025-04-29 20:10:00
2025-04-29 21:40:00
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