Reimagining RViz: Multidimensional Augmented Reality Robot Signal Design

From RViz to augmented reality (AR), a wide variety of robot signal visualizations exist for conveying robot capabilities. Many of the visualizations designed for AR, however, have not isolated multiple salient Virtual Design Elements (VDEs) for a given signal and comparatively evaluated combinations of those VDEs. To address this, we identify multiple VDEs for AR signaling of the following core robot capabilities: navigation, light detection and ranging (LiDAR), camera, face detection, audio localization, and natural language processing. We evaluated each signal's VDE combinations with an Amazon Mechanical Turk study (n=150) where participants watched 4 videos for each signal (consisting of 2 independent VDE choices) and rated the clarity and visual appeal of each signal. The results define a set of the most clear and visually appealing signal visualization designs and inform about interaction effects among VDEs. The resulting VDEs offer design insights and a baseline for continued research into AR robot capability signalling.