Do you feel safe with your robot? Factors Influencing Perceived Safety in Human-Robot Interaction based on Subjective and Objective Measures

TL;DR

This study explores how factors like comfort, control, and trust influence perceived safety in human-robot interaction, using subjective questionnaires and objective physiological and video data to improve understanding and prediction of safety perceptions.

Contribution

It introduces a multidisciplinary approach combining subjective and objective measures to analyze perceived safety and demonstrates that physiological data can better predict safety perceptions.

Findings

Perceived safety correlates with comfort, control, and trust.

Physiological signals outperform video data in predicting perceived safety.

Individual characteristics like personality and gender influence safety perception.

Abstract

Safety in human-robot interaction can be divided into physical safety and perceived safety, where the latter is still under-addressed in the literature. Investigating perceived safety in human-robot interaction requires a multidisciplinary perspective. Indeed, perceived safety is often considered as being associated with several common factors studied in other disciplines, i.e., comfort, predictability, sense of control, and trust. In this paper, we investigated the relationship between these factors and perceived safety in human-robot interaction using subjective and objective measures. We conducted a two-by-five mixed-subjects design experiment. The five within-subjects conditions correspond to (1) baseline, and the manipulations of robot behaviors to stimulate: (2) discomfort, (3) decreased perceived safety, (4) decreased sense of control and (5) distrust. Twenty-seven young adult participants took part in the experiments. Participants were asked to answer questionnaires that measure the manipulated factors after within-subjects conditions. Besides questionnaire data, we collected objective measures such as videos and physiological data. The questionnaire results show a correlation between comfort, sense of control, trust, and perceived safety. We also discuss the effect of individual human characteristics (such as personality and gender) that they could be predictors of perceived safety. We used the physiological signal data and facial affect from videos for estimating perceived safety where participants' subjective ratings were utilized as labels. The data from objective measures revealed that the prediction rate was higher from physiological signal data. This paper can play an important role in the goal of better understanding perceived safety in human-robot interaction.