Do you feel safe with your robot? Factors influencing perceived safety in human-robot interaction based on subjective and objective measures
Datos Bibliográficos
| ID | 21642423 |
|---|---|
| Autores | Neziha Akalın (0000-0001-6168-0706, Örebro University, autor de correspondencia), Neziha Akalin, Annica Kristoffersson (0000-0002-4368-4751, Mälardalen University), Amy Loutfi (0000-0002-3122-693X, Örebro University) |
| Año | 2022 |
| Volumen | 158 |
| Páginas | 102744 |
| Fecha de publicación | 2022-02-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | International Journal of Human-Computer Studies (JOURNAL) |
| Identificadores de la revista | ISSN: 1071-5819 • E-ISSN: 1095-9300 |
| Editorial | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijhcs.2021.102744 |
| OpenAlex | W3207144782 |
| Idioma | EN |
| Citas recibidas | 17 |
| Referencias citadas | 39 |
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. There were two between-subjects conditions: the faulty robot was experienced at the beginning or the end of the interaction. 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. The idea of triggering a deprivation of these factors was motivated by the definition of safety in the literature where safety is often defined by the absence of it. 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. Since these factors are the main factors that influence perceived safety, they should be considered in human-robot interaction design decisions. 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
Cognitive psychology · Distrust · Human–robot interaction · Personality · Robot · Applied Psychology · Communication · Computer Science · Human-Automation Interaction and Safety · Occupational Health and Safety Research · Psychology · Safety Warnings and Signage · Social Psychology · Artificial Intelligence
Between fear and trust
Translation, Adaptation, and Validation in Portuguese of an Acceptance Scale for Human–Robot Interaction in an Industrial Context
Predicting Human Perceptions of Robot Performance during Navigation Tasks
Human–Robot Teaming
Indoor Human–Mobile Robot Encounters
How transparency impacts trust in teleoperated autonomous robots under uncertainty
Different dimensions of anthropomorphic design cues
Trust dynamics in human interaction with an industrial robot
How Women Respond to Computer-Generated Inclusive Advertising
Socially Assistive Robots in Mental Healthcare
Evaluating the Effect of Speed and Acceleration on Human Factors during an Assembly Task in Human–Robot Interaction (HRI)
Exploring the Dynamics of Human-Robot Interaction
A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction
Multi-Attribute Decision-Making Model for Security Perception in Smart Apartments from a User Experience Perspective
Affective and Conversational Predictors of Re-Engagement in Human–Robot Interactions
The role of knowledge and trust in developing risk perceptions of autonomous vehicles
The impact of prior chatbot identity disclosure on customer tolerance of service failures
Measuring School Climate in High Schools
Neuroticism is a fundamental domain of personality with enormous public health implications
What drives people to accept automated vehicles? Findings from a field experiment
Repeated Measures Correlation
A Mass-Produced Sociable Humanoid Robot
The role of trust in automation reliance
Measuring emotion
Psychological Conditions of Personal Engagement and Disengagement at Work.
Measuring heterogeneous perception of urban space with massive data and machine learning
Synthesizing Robot Motions Adapted to Human Presence
Make new friends or keep the old
The Relation Between Valence and Arousal in Subjective Experience Varies With Personality and Culture
Measuring personality in one minute or less
The Influence of Feedback Type in Robot-Assisted Training
On the Safety of Mobile Robots Serving in Public Spaces
A theory of human motivation
Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots
| Obras citantes distintas | 17 |
|---|---|
| Citas por año | 4,25 |
| Intervalo de citas | 2022 - 2026 (5) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 17 |