The utility of affect expression in natural language interactions in joint human-robot tasks

Abstract

Recognizing and responding to human affect is important in collaborative tasks in joint human-robot teams. In this paper we present an integrated affect and cognition architecture for HRI and report results from an experiment with this architecture that shows that expressing affect and responding to human affect with affect expressions can significantly improve team performance in a joint human-robot task.