Abstract
Performance of robots in human robot teams has always been a topic of interest for many researchers in human robot interaction community. Traditionally adopted Crandall's model for performance measurements assume ideal conditions in which the operator switches control between robots sequentially based on acceptable performance level ignoring any false alarms due to erroneous interactions. In this paper, we present the false alarm demand, a new metric for measuring effects of false alarms on human robot team performance and extend the Crandall's model to situations in which false positives and false negatives are prevalent. Experiments were performed with real and virtual humanoid soccer robots across tele-operated, and point to point modes of autonomy. Measured false alarms demand and robot performances were largely consistent with the proposed extended Crandall's model predictions for both real and virtual experiments for both autonomy modes.