Technology Acceptance, Sociocultural Influence and Gender Perception of Robots: A Human Robot Interaction Study with Naive Users in Rural India

Estimating distances between people and robots plays a crucial role in understanding social Human–Robot Interaction (HRI) from an egocentric view. It is a key step if robots should engage in social interactions, and to collaborate with people as part of human–robot teams. For distance estimation between a person and a robot, different sensors can be employed, and the number of challenges to be addressed by the distance estimation methods rise with the simplicity of the technology of a sensor. In the case of estimating distances using individual images from a single camera in a egocentric position, it is often required that individuals in the scene are facing the camera, do not occlude each other, and are fairly visible so specific facial or body features can be identified. In this paper, we propose a novel method for estimating distances between a robot and people using single images from a single egocentric camera. The method is based on previously proven 2D pose estimation, which allows partial occlusions, cluttered background, and relatively low resolution. The method estimates distance with respect to the camera based on the Euclidean distance between ear and torso of people in the image plane. Ear and torso characteristic points has been selected based on their relatively high visibility regardless of a person orientation and a certain degree of uniformity with regard to the age and gender. Experimental validation demonstrates effectiveness of the proposed method.

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Social-cue perception and mentalizing ability following traumatic brain injury: A human-robot interaction study

Brain Injury ◽

10.1080/02699052.2018.1531305 ◽

2018 ◽

Vol 33 (1) ◽

pp. 23-31 ◽

Cited By ~ 2

Author(s):

Bilge Mutlu ◽

Melissa Duff ◽

Lyn Turkstra

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Human Robot Interaction ◽

Interaction Study ◽

Robot Interaction ◽

Social Cue

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Factors Influencing Consumers’ Intention to Adopt Fashion Robot Advisors: Psychological Network Analysis

Clothing and Textiles Research Journal ◽

10.1177/0887302x20941261 ◽

2020 ◽

pp. 0887302X2094126

Author(s):

So Young Song ◽

Youn-Kyung Kim

Keyword(s):

Network Analysis ◽

Technology Acceptance ◽

Social Intelligence ◽

Online Survey ◽

Human Robot Interaction ◽

Robot Interaction ◽

Adoption Of Technology ◽

Intention To Adopt ◽

Psychological Attributes ◽

Technology Acceptance Models

Drawing upon the theory of human–robot interaction (HRI), this study examined the relations among perceived characteristics of fashion robot advisors (FRAs), consumers’ negative preconceptions toward robots, and positive dispositions toward technology to identify network differences in adoption and nonadoption groups. For interviews, pretests, and main data collection, we presented video clips of FRAs as stimuli. Based on the data ( n = 464) collected via an online survey, we conducted psychological network analysis to explore defining factors that differentiate adoption and nonadoption groups. The results indicate that perceived characteristics of social intelligence, humanlikeness, and knowledgeableness combined with a positive disposition of technological self-efficacy lead to adoption of FRAs. This study contributes to the literature on the theory of HRI and technology acceptance models, particularly in fashion retail sectors. Furthermore, this study provides a new graphical approach to networks that conceptualizes shoppers’ adoption of technology as a complex interplay of psychological attributes.

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Human–Robot Interaction and Sexbots: A Systematic Literature Review

Sensors ◽

10.3390/s21010216 ◽

2020 ◽

Vol 21 (1) ◽

pp. 216

Author(s):

Carina Soledad González-González ◽

Rosa María Gil-Iranzo ◽

Patricia Paderewski-Rodríguez

Keyword(s):

Literature Review ◽

Systematic Literature Review ◽

Social Robots ◽

Human Robot Interaction ◽

New Paradigm ◽

Robot Interaction ◽

Male Bias ◽

Ethical Approaches ◽

Research Questions ◽

And Gender

At present, sexual robots have become a new paradigm of social robots. In this paper, we developed a systematic literature review about sexual robots (sexbots). To do this, we used the Scopus and WoS databases to answer different research questions regarding the design, interaction, and gender and ethical approaches from 1980 until 2020. In our review, we found a male bias in this discipline, and in recent years, articles have shown that user opinion has become more relevant. Some insights and recommendations on gender and ethics in designing sexual robots were also made.

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How Ethical Issues Raised by Human–Robot Interaction can Impact the Intention to use the Robot?

International Journal of Social Robotics ◽

10.1007/s12369-021-00857-8 ◽

2022 ◽

Author(s):

Reza Etemad-Sajadi ◽

Antonin Soussan ◽

Théo Schöpfer

Keyword(s):

Structural Equation ◽

User Study ◽

Ethical Issues ◽

Human Robot Interaction ◽

Equation Modeling ◽

Intention To Use ◽

Robot Interaction ◽

Final Sample ◽

Perception Of Robots ◽

The Impact

AbstractThe goal of this research is to focus on the ethical issues linked to the interaction between humans and robots in a service delivery context. Through this user study, we want to see how ethics influence user’s intention to use a robot in a frontline service context. We want to observe the importance of each ethical attribute on user’s intention to use the robot in the future. To achieve this goal, we incorporated a video that showed Pepper, the robot, in action. Then respondents had to answer questions about their perception of robots based on the video. Based on a final sample of 341 respondents, we used structural equation modeling (SEM) to test our hypotheses. The results show that the most important ethical issue is the Replacement and its implications for labor. When we look at the impact of the ethical issues on the intention to use, we discovered that the variables impacting the most are Social cues, Trust and Safety.

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Students’ Perceptions and Acceptance of lego Robots in Syria

The Journal of Interrupted Studies ◽

10.1163/25430149-00101005 ◽

2018 ◽

Vol 1 (1) ◽

pp. 26-33

Author(s):

Ghaith Mqawass

Keyword(s):

Online Courses ◽

Recent Trend ◽

Age Groups ◽

Human Robot Interaction ◽

Gender Effects ◽

Robot Interaction ◽

Degree Of Acceptance ◽

And Gender ◽

Educational Robots ◽

Two Age Groups

An important recent trend in education has been the integration of different technologies such as digital games, online courses, and educational robots. The development of educational robots such as lego Mindstorms nxt allows students to learn to build their own robots. This paper describes the human-robot interaction (hri) focusing especially on the model lego Mindstorms nxt. A questionnaire among 250 Syrian school and university students was conducted to investigate the different perceptions about lego robots in 2016. The informants were grouped based on their age; participants in the first group were aged between 11 and 18 years while participants in the second between 19 and 24. The current study also focuses on the factors leading to the acceptance of lego robots. Another questionnaire was conducted to highlight what factors determine the degree of acceptance of lego robots by the studied groups. Significant age and gender effects were found. The results show a noticeable difference between the two age groups, with the younger group tending to accept lego robots more. Furthermore, it was found that male respondents show more positive reactions towards lego robots than females.

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“I See What You Did There”

ACM Transactions on Human-Robot Interaction ◽

10.1145/3461534 ◽

2021 ◽

Vol 10 (3) ◽

pp. 1-28

Author(s):

Bob R. Schadenberg ◽

Dennis Reidsma ◽

Dirk K. J. Heylen ◽

Vanessa Evers

Keyword(s):

Social Interactions ◽

Conceptual Understanding ◽

Visual Cues ◽

Mental States ◽

Human Robot Interaction ◽

Interaction Study ◽

Robot Interaction ◽

The Relationship

Unpredictability in robot behaviour can cause difficulties in interacting with robots. However, for social interactions with robots, a degree of unpredictability in robot behaviour may be desirable for facilitating engagement and increasing the attribution of mental states to the robot. To generate a better conceptual understanding of predictability, we looked at two facets of predictability, namely, the ability to predict robot actions and the association of predictability as an attribute of the robot. We carried out a video human-robot interaction study where we manipulated whether participants could either see the cause of a robot’s responsive action or could not see this, because there was no cause, or because we obstructed the visual cues. Our results indicate that when the cause of the robot’s responsive actions was not visible, participants rated the robot as more unpredictable and less competent, compared to when it was visible. The relationship between seeing the cause of the responsive actions and the attribution of competence was partially mediated by the attribution of unpredictability to the robot. We argue that the effects of unpredictability may be mitigated when the robot identifies when a person may not be aware of what the robot wants to respond to and uses additional actions to make its response predictable.

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