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 neglect tolerance model for performance measurements assume ideal conditions in which the operator switches control between robots sequentially based on acceptable performance level for each robot 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 neglect tolerance 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 alarm demand and robot performances were largely consistent with the proposed extended neglect tolerance model predictions for real and virtual experiments for both autonomy modes. Experiments also showed that extended neglect tolerance model offered better estimation of robot performances as compared to the traditionally adopted neglect tolerance model for situations wherein false alarms are prevalent.