Automated Planning for Peer-to-peer Teaming and its Evaluation in Remote Human-Robot Interaction

Human factor studies on remote human-robot interaction are often restricted to various forms of supervision, in which the robot is essentially being used as a smart mobile ma-nipulation platform with sensing capabilities. In this study, we investigate the incorporation of a general planning capa-bility into the robot to facilitate peer-to-peer human-robot teaming, in which the human and robot are viewed as team-mates that are physically separated. One intriguing ques-tion is to what extent humans may feel uncomfortable at such robot autonomy and lose situation awareness, which can potentially reduce teaming performance. Our results suggest that peer-to-peer teaming is preferred by humans and leads to better performance. Furthermore, our results show that peer-to-peer teaming reduces cognitive loads from objective measures (even though subjects did not report this in their subjective evaluations), and it does not reduce situ-ation awareness for short-term tasks