In human-robot interaction (HRI), studies show humans can mistakenly assume that robots and humans have the same field of view, possessing an inaccurate mental model of a robot. This misperception is problematic during collaborative HRI tasks where robots might be asked to complete impossible tasks about out-of-view objects. In this initial work, we aim to align humans' mental models of robots by exploring the design of field-of-view indicators in augmented reality (AR). Specifically, we rendered nine such indicators from the head to the task space, and plan to register them onto the real robot and conduct human-subjects studies.
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Wang et al. (2024) studied this question.
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