Imitation or Innovation? Translating Features of Expressive Motion from Humans to Robots

Expressive robot motion can help establish acceptance of this technology in everyday life, but understanding what makes movement expressive is a complex and multifaceted task. This paper presents the results of an online study with 46 participants, it aims to explore how people perceive and interpret the expressive qualities of human movement and how they envision the translation of their description into an imagined non-humanoid, quadrupedal robot. Through a qualitative analysis of responses, we conceptualize three themes: their understanding of intent, their interpretations of movement qualities, and finally, their translation from human to robot movement. Respondents’ descriptions of their initial understanding of the performer’s intent fall into two modes, bio-mechanical and narrative. We illustrate their interpretations of movement qualities through four strategies: movement features as kinematic indicators, intent indicators, attributed context, and perceived internal states. Lastly, we observe their translation from human to robot movement, with a particular focus on respondents’ use of kinaesthetic empathy and anthropomorphism. Our findings aim to support a bottom-up approach, using users’ general knowledge for designing expressive robot motion.