Discovering patterns of touch: A case study for visualization-driven analysis in Human-Robot Interaction

Abstract

An important challenge in Human-Robot Interaction (HRI) is the analysis and interpretation of large volumes of data to inform the design process within a complex, multi-faceted research space. In this study, we explore how data visualization techniques can contribute to HRI methodology, particularly in terms of linking qualitative and quantitative analysis methods. Specifically, we present a case study demonstrating the visualization of touch data to identify potential patterns of interaction with a social robot intended for deployment in preschool classrooms.