Exploring dynamic movement representations in context using generative AI: Effects of media types on the evaluation of service robot morphology

Abstract

With the increase of service robots, understanding how people perceive their human-likeness and capabilities in use contexts is crucial. Advancements in generative AI offer the potential to create realistic, dynamic video representations of robots in motion. This study introduces an AI-assisted workflow for creating video representations of robots for evaluation studies. As a comparative study, it explores the effect of AI-generated videos on people's perceptions of robot designs in three service contexts. Nine video clips depicting robots in motion were created and presented in an online survey. Videos increased human-likeness perceptions for supermarket robots but had the same effect on restaurant and delivery robots as images. Perceptions of capabilities showed negligible differences between media types. No significant differences in the effectiveness of communication were found.