Shaping Naive Users' Models of Robots' Situation Awareness

Abstract

This paper addresses a so far neglected area of human-robot interaction by approaching situation awareness from the point of view of naive users. In particular, we present an investigation into which naive models of robots' capabilities users carry into the interaction, how these models influence the interaction, and which means can be taken to guide users into more realistic models and behaviours if necessary. Quantitative and qualitative investigations reveal not only considerable uncertainty about robots' situation awareness, but also significant differences in dealing with this uncertainty. Three different types of users can be distinguished on the basis of the strategies they take. Finally, we describe experiments with two means of shaping the users' models into more realistic accounts of robots' capabilities. The results suggest that verbal robot output is a powerful means for guiding users subtly, unobtrusively and online into an understanding of robots' capabilities that is more realistic and adequate than users' naive models of robots' situation awareness.