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Judging a Socially Assistive Robot by Its Cover: The Effect of Body Structure, Outline, and Color on Users’ Perception

Ela Liberman-Pincu, Yisrael Parmet, Tal Oron-Gilad

2022ACM Transactions on Human-Robot Interaction37 citationsDOIOpen Access PDF

Abstract

Socially assistive robots (SARs) aim to provide assistance through social interaction. Previous studies contributed to understanding users’ perceptions and preferences regarding existing commercially available SARs. Yet very few studies regarding SARs’ appearance used designated SAR designs, and even fewer evaluated isolated visual qualities (VQs). In this work, we aim to assess the effect of isolated VQs systematically. To achieve this, we first conducted market survey and deconstructed the VQs attributed to SARs. Then, a reconstruction of body structure, outline, and color scheme was done, resulting in the creation of 30 new SAR models that differ in their VQs, allowing us to isolate one character at a time. We used these new designs to evaluate users’ preferences and perceptions in two empirical studies. Our empirical findings link VQs with perceptions of SAR characteristics. These can lead to forming guidelines for the industrial design processes of new SARs to match user expectations.

Topics & Concepts

PerceptionRobotEmpirical researchComputer scienceHuman–computer interactionCover (algebra)Artificial intelligencePsychologyEngineeringNeuroscienceEpistemologyMechanical engineeringPhilosophyFace Recognition and PerceptionColor perception and designVisual Attention and Saliency Detection