Material Driven HRI Design: Aesthetics as Explainability

TL;DR

This paper explores how material choices in robot design influence user perceptions and expectations, proposing a framework that uses aesthetics as a form of explainability to improve human-robot interaction.

Contribution

It introduces a novel framework linking materials and aesthetics to interaction signals, enhancing robot design for better user understanding and expectations.

Findings

Materials can signal interaction cues and roles.

A content analysis of 6 robots illustrates the framework.

Design choices impact user expectations and robot legibility.

Abstract

Aesthetics - often treated as secondary to function-guides how people interpret robots' roles. A great deal of robot designs - both real and fictitious - use sleek industrial aesthetics. These feature hard glossy plastics, hiding as much of the underlying mechanical and electrical components as possible, resembling something akin to a nude humanoid figure. This leaves robots as something of a blank slate to which end-users apply coverings to, often based on media of fiction and non-fiction alike. We argue that designers can take cues from fashion to design interaction and set appropriate expectations. Rather than viewing appearance as decoration, we propose that color, texture, and material choices function as interaction signals. These signals can invite or discourage touch, clarify a robot's role, and help align user expectations with a robot's actual capabilities. When done thoughtfully, such cues can create familiarity and legibility; when done poorly, they can lead to wrong expectations. This preliminary paper proposes a framework describing how materials can create explainability by signaling expectations for interaction, task, and environment. We use this framework to do a content analysis of 6 robots.