To Understand Indicators of Robots' Vision Capabilities
Keywords: System transparency, robot design, vision capability, field of view, augmented reality (AR), human-robot interaction (HRI)
Abstract: Study [10] indicates that humans can mistakenly assume that robots and humans have the same field of view (FoV), 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. To help align humans’ mental models of robots’ vision capabilities, we explore the design space by proposing nine FoV indicator designs in augmented reality (AR) and present an experiment design to evaluate them subjectively and objectively. Specifically, we designed these indicators from a spectrum from the head to the task space. Regarding the experiment, we propose an assembly task to assess them in terms of accuracy, task efficiency, and subjective experience like confidence and likability. Our future results will inform robot designers to better indicate robots’ FoV to align humans’ mental models of robots’ vision capabilities.
Submission Number: 2
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