As autonomous robots become integrated into society, they must socially navigate around humans. We propose that effective social robot navigation relies on three key principles: social norms, perceived safety, and legibility. Our framework, Overlapping Social Navigation Principles, suggests that the strength of each principle is influenced by the presence of other principles. To test our framework, we implemented SRN behaviors on an autonomous robot in a passing scenario and conducted an online study where participants ranked videos of different SRN behavior combinations. Our findings show that incorporating all three principles enhances SRN, with social norms having the greatest impact.

Anxiety toward robots is a pre-conditioned emotion that might inhibit the formation of positive attitudes about interactions with robots. In the context of consumer robotics, this study operationalizes anxiety toward robots as consumers’ anxious feelings and fears about robots in frontline retail encounters. The study evaluates item quality of the anxiety toward robots construct and showcases the benefits of using Classical Test Theory (CTT) and Item Response Theory (IRT) for developing and assessing a scale measurement. The findings of this study suggest that the five items comprising the anxiety toward robots scale demonstrate high measurement quality, indicating their accurate representation of the intended construct. By integrating CTT and IRT analytic techniques, the study successfully builds a reliable scale for measuring anxiety toward robots in a and contributes to the use of an alternative statistical method for facilitating the construction of valid research instruments in consumer robotics.