The advisor robot: tracing people's mental model from a robot's physical attributes
Humanoid robots offer many physical design choices such as voice frequency and head dimensions. We used hierarchical statistical mediation analysis to trace differences in people's mental model of robots from these choices. In an experiment, a humanoid robot gave participants online advice about their health. We used mediation analysis to identify the causal path from the robot's voice and head dimensions to the participants' mental model, and to their willingness to follow the robot's advice. The male robot voice predicted impressions of a knowledgeable robot, whose advice participants said they would follow. Increasing the voice's fundamental frequency reduced this effect. The robot's short chin length (but not its forehead dimensions) predicted impressions of a sociable robot, which also predicted intentions to take the robot's advice. We discuss the use of this approach for designing robots for different roles, when people's mental model of the robot matters.
HRI '06