What Do Robot Gestures Tell Us? Emotions and Messages in Simple Robotic Movement

Gesturing is an important activity in social interaction, but how will different types of robot gesture be interpreted by people? Understanding how humans interpret robot gestures will aid design of effective social robots. We examine the generation and interpretation of gestures in a simple social robot capable of head and arm movement using two studies. In the first study, four participants created gestures with corresponding messages and emotions based on 12 different scenarios provided to them. The resulting gestures were then shown in the second study to 12 participants who rated gesture lifelikeness as well as judging which emotions and messages were being conveyed. Knowledge (present or absent) of the motivating scenario (context) for each gesture was manipulated as an experimental factor. Context was found to assist message understanding while providing only modest assistance to emotion recognition. The gestures participants created varied in movement complexity, and lifelikeness was found to be related to the number of arm movements (but not head movements) in a gesture. While better than chance, both emotion (22%) and message understanding (40%) accuracies were relatively low. The results obtained are discussed in terms of implied guidelines for designing gestures for social robots.