Predicting human performance during teleoperation

Abstract

Humans are an integral part of many tasks performed by mobile robots and human operator ability can vary greatly between users. Understanding operator skill level can allow for user interfaces to adapt giving novice users additional assistance and expert users more freedom. In this paper, a method is proposed for predicting a human teleoperator's performance based on user behavior observed during the first few minutes of teleoperation. Preliminary analysis indicates a trend between operator performance and the proportion of time an operator spends thinking during a particular segment of time.