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  • 1.
    Akalin, Neziha
    et al.
    Örebro University, School of Science and Technology.
    Kristoffersson, Annica
    School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Do you feel safe with your robot? Factors influencing perceived safety in human-robot interaction based on subjective and objective measures2022In: International journal of human-computer studies, ISSN 1071-5819, E-ISSN 1095-9300, Vol. 158, article id 102744Article in journal (Refereed)
    Abstract [en]

    Safety in human-robot interaction can be divided into physical safety and perceived safety, where the later 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.

  • 2.
    Robertsson, Linn
    et al.
    Örebro University, Department of Technology.
    Iliev, Boyko
    Örebro University, Department of Technology.
    Palm, Rainer
    Örebro University, Department of Technology.
    Wide, Peter
    Örebro University, Department of Technology.
    Perception modeling for human-like artificial sensor systems2007In: International journal of human-computer studies, ISSN 1071-5819, E-ISSN 1095-9300, Vol. 65, no 5, p. 446-459Article in journal (Refereed)
    Abstract [en]

    In this article we present an approach to the design of human-like artificial systems. It uses a perception model to describe how sensory information is processed for a particular task and to correlate human and artificial perception. Since human-like sensors share their principle of operation with natural systems, their response can be interpreted in an intuitive way. Therefore, such sensors allow for easier and more natural human–machine interaction.

    The approach is demonstrated in two applications. The first is an “electronic tongue”, which performs quality assessment of food and water. In the second application we describe the development of an artificial hand for dexterous manipulation. We show that human-like functionality can be achieved even if the structure of the system is not completely biologically inspired.

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