Validation of Robot Interactive Behaviors Through Users Emotional Perception and Their Effects on Trust

Cucciniello, Ilenia; Sangiovanni, Sara; Maggi, Gianpaolo; Rossi, Silvia

doi:10.1109/ro-man50785.2021.9515352

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…The level of familiarity with robots and robot-related experience can be gained by the exposure of robots. A person who has experience and familiarity with robots would have positive perceptions towards acceptance of robots [25], have a positive attitude and less anxiety towards robots [11], and trust in robots [22]. On the other hand, lack of familiarity might lead to negative feelings toward technology and robots [25].…”

Section: Experience and Familiaritymentioning

confidence: 99%

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

Akalın

Kiselev

Kristoffersson

et al. 2023

Int J of Soc Robotics

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Safety is a fundamental prerequisite that must be addressed before any interaction of robots with humans. Safety has been generally understood and studied as the physical safety of robots in human–robot interaction, whereas how humans perceive these robots has received less attention. Physical safety is a necessary condition for safe human–robot interaction. However, it is not a sufficient condition. A robot that is safe by hardware and software design can still be perceived as unsafe. This article focuses on perceived safety in human–robot interaction. We identified six factors that are closely related to perceived safety based on the literature and the insights obtained from our user studies. The identified factors are the context of robot use, comfort, experience and familiarity with robots, trust, the sense of control over the interaction, and transparent and predictable robot actions. We then made a literature review to identify the robot-related factors that influence perceived safety. Based the literature, we propose a taxonomy which includes human-related and robot-related factors. These factors can help researchers to quantify perceived safety of humans during their interactions with robots. The quantification of perceived safety can yield computational models that would allow mitigating psychological harm.

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Section: Experience and Familiaritymentioning

confidence: 99%

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

Akalın

Kiselev

Kristoffersson

et al. 2023

Int J of Soc Robotics

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What Should Autonomous Robots Verbalize and What Should They Not?

Yoshihara,

Yuguchi,

Kawano

et al. 2025

Lecture Notes in Computer Science

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Mind Perception in HRI: Exploring Users’ Attribution of Mental and Emotional States to Robots with Different Behavioural Styles

Cucciniello

Sangiovanni

Maggi

et al. 2023

Int J of Soc Robotics

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Theory of Mind is crucial to understand and predict others’ behaviour, underpinning the ability to engage in complex social interactions. Many studies have evaluated a robot’s ability to attribute thoughts, beliefs, and emotions to humans during social interactions, but few studies have investigated human attribution to robots with such capabilities. This study contributes to this direction by evaluating how the cognitive and emotional capabilities attributed to the robot by humans may be influenced by some behavioural characteristics of robots during the interaction. For this reason, we used the Dimensions of Mind Perception questionnaire to measure participants’ perceptions of different robot behaviour styles, namely Friendly, Neutral, and Authoritarian, which we designed and validated in our previous works. The results obtained confirmed our hypotheses because people judged the robot’s mental capabilities differently depending on the interaction style. Particularly, the Friendly is considered more capable of experiencing positive emotions such as Pleasure, Desire, Consciousness, and Joy; conversely, the Authoritarian is considered more capable of experiencing negative emotions such as Fear, Pain, and Rage than the Friendly. Moreover, they confirmed that interaction styles differently impacted the perception of the participants on the Agency dimension, Communication, and Thought.

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Validation of Robot Interactive Behaviors Through Users Emotional Perception and Their Effects on Trust

Cited by 5 publications

References 22 publications

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

What Should Autonomous Robots Verbalize and What Should They Not?

Mind Perception in HRI: Exploring Users’ Attribution of Mental and Emotional States to Robots with Different Behavioural Styles

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