Improving Human-Robot Team Transparency with Eye-tracking based Situation Awareness Assessment

Abstract

Human-robot interactions rely on transparency to foster effective collaboration. Transparency can be assessed through metrics associated with factors such as situation awareness. This manuscript presents an ocular metric to assess situation awareness for human-machine teams. Participants used a decision support system to select a grasp for underwater manipulation. The participants' gaze behavior and visual awareness was analyzed using a wearable eye tracker. An initial analysis that measures saccadic distance provides insight into the requirements of future techniques for objectively assessing situation awareness.