Elizabeth Phillips
ABSTRACT
Anthropomorphic robots, or robots with human-like appearance features such as eyes, hands, or faces, have drawn considerable attention in recent years. To date, what makes a robot appear human-like has been driven by designers» and researchers» intuitions, because a systematic understanding of the range, variety, and relationships among constituent features of anthropomorphic robots is lacking. To fill this gap, we introduce the ABOT (Anthropomorphic roBOT) Database---a collection of 200 images of real-world robots with one or more human-like appearance features (http://www.abotdatabase.info). Harnessing this database, Study 1 uncovered four distinct appearance dimensions (i.e., bundles of features) that characterize a wide spectrum of anthropomorphic robots and Study 2 identified the dimensions and specific features that were most predictive of robots» perceived human-likeness. With data from both studies, we then created an online estimation tool to help researchers predict how human-like a new robot will be perceived given the presence of various appearance features. The present research sheds new light on what makes a robot look human, and makes publicly accessible a powerful new tool for future research on robots» human-likeness.
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Index Terms
- What is Human-like?: Decomposing Robots' Human-like Appearance Using the Anthropomorphic roBOT (ABOT) Database
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