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Arora, Anshu Saxena, Mayumi Fleming, Amit Arora, Vas Taras, and Jiajun Xu. "Finding “H” in HRI." International Journal of Intelligent Information Technologies 17, no. 1 (January 2021): 19–38. http://dx.doi.org/10.4018/ijiit.2021010102.
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The study examines the relationship between the big five personality traits (extroversion, agreeableness, conscientiousness, neuroticism, and openness) and robot likeability and successful HRI implementation in varying human-robot interaction (HRI) situations. Further, this research investigates the influence of human-like attributes in robots (a.k.a. robotic anthropomorphism) on the likeability of robots. The research found that robotic anthropomorphism positively influences the relationship between human personality variables (e.g., extraversion and agreeableness) and robot likeability in human interaction with social robots. Further, anthropomorphism positively influences extraversion and robot likeability during industrial robotic interactions with humans. Extraversion, agreeableness, and neuroticism were found to play a significant role. This research bridges the gap by providing an in-depth understanding of the big five human personality traits, robotic anthropomorphism, and robot likeability in social-collaborative robotics.
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Vallverdú, Jordi, Toyoaki Nishida, Yoshisama Ohmoto, Stuart Moran, and Sarah Lázare. "Fake Empathy and Human-Robot Interaction (HRI)." International Journal of Technology and Human Interaction 14, no. 1 (January 2018): 44–59. http://dx.doi.org/10.4018/ijthi.2018010103.
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Empathy is a basic emotion trigger for human beings, especially while regulating social relationships and behaviour. The main challenge of this paper is study whether people's empathic reactions towards robots change depending on previous information given to human about the robot before the interaction. The use of false data about robot skills creates different levels of what we call ‘fake empathy'. This study performs an experiment in WOZ environment in which different subjects (n=17) interacting with the same robot while they believe that the robot is a different robot, up to three versions. Each robot scenario provides a different ‘humanoid' description, and out hypothesis is that the more human-like looks the robot, the more empathically can be the human responses. Results were obtained from questionnaires and multi- angle video recordings. Positive results reinforce the strength of our hypothesis, although we recommend a new and bigger and then more robust experiment.
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Dautenhahn, Kerstin. "Socially intelligent robots: dimensions of human–robot interaction." Philosophical Transactions of the Royal Society B: Biological Sciences 362, no. 1480 (February 13, 2007): 679–704. http://dx.doi.org/10.1098/rstb.2006.2004.
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Social intelligence in robots has a quite recent history in artificial intelligence and robotics. However, it has become increasingly apparent that social and interactive skills are necessary requirements in many application areas and contexts where robots need to interact and collaborate with other robots or humans. Research on human–robot interaction (HRI) poses many challenges regarding the nature of interactivity and ‘social behaviour’ in robot and humans. The first part of this paper addresses dimensions of HRI, discussing requirements on social skills for robots and introducing the conceptual space of HRI studies. In order to illustrate these concepts, two examples of HRI research are presented. First, research is surveyed which investigates the development of a cognitive robot companion. The aim of this work is to develop social rules for robot behaviour (a ‘robotiquette’) that is comfortable and acceptable to humans. Second, robots are discussed as possible educational or therapeutic toys for children with autism. The concept of interactive emergence in human–child interactions is highlighted. Different types of play among children are discussed in the light of their potential investigation in human–robot experiments. The paper concludes by examining different paradigms regarding ‘social relationships’ of robots and people interacting with them.
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Lee, Heejin. "A Human-Robot Interaction Entertainment Pet Robot." Journal of Korean Institute of Intelligent Systems 24, no. 2 (April 25, 2014): 179–85. http://dx.doi.org/10.5391/jkiis.2014.24.2.179.
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Collins, Emily C. "Drawing parallels in human–other interactions: a trans-disciplinary approach to developing human–robot interaction methodologies." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1771 (March 11, 2019): 20180433. http://dx.doi.org/10.1098/rstb.2018.0433.
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This opinion paper discusses how human–robot interaction (HRI) methodologies can be robustly developed by drawing on insights from fields outside of HRI that explore human–other interactions. The paper presents a framework that draws parallels between HRIs, and human–human, human–animal and human–object interaction literature, by considering the morphology and use of a robot to aid the development of robust HRI methodologies. The paper then briefly presents some novel empirical work as proof of concept to exemplify how the framework can help researchers define the mechanism of effect taking place within specific HRIs. The empirical work draws on known mechanisms of effect in animal-assisted therapy, and behavioural observations of touch patterns and their relation to individual differences in caring and attachment styles, and details how this trans-disciplinary approach to HRI methodology development was used to explore how an interaction with an animal-like robot was impacting a user. In doing so, this opinion piece outlines how useful objective, psychological measures of social cognition can be for deepening our understanding of HRI, and developing richer HRI methodologies, which take us away from questions that simply ask ‘Is this a good robot?’, and closer towards questions that ask ‘What mechanism of effect is occurring here, through which effective HRI is being performed?’ This paper further proposes that in using trans-disciplinary methodologies, experimental HRI can also be used to study human social cognition in and of itself. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
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Bonarini, Andrea. "Communication in Human-Robot Interaction." Current Robotics Reports 1, no. 4 (August 27, 2020): 279–85. http://dx.doi.org/10.1007/s43154-020-00026-1.
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Abstract Purpose of Review To present the multi-faceted aspects of communication between robot and humans (HRI), putting in evidence that it is not limited to language-based interaction, but it includes all aspects that are relevant in communication among physical beings, exploiting all the available sensor channels. Recent Findings For specific purposes, machine learning algorithms could be exploited when data sets and appropriate algorithms are available. Summary Together with linguistic aspects, physical aspects play an important role in HRI and make the difference with respect to the more limited human-computer interaction (HCI). A review of the recent literature about the exploitation of different interaction channels is presented. The interpretation of signals and the production of appropriate communication actions require to consider psychological, sociological, and practical aspects, which may affect the performance. Communication is just one of the functionalities of an interactive robot and, as all the others, will need to be benchmarked to support the possibility for social robots to reach a real market.
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Su, Wei Hua, Jing Gong Sun, Fu Niu, and Xin Yue Xu. "The Human-Robot Interaction: An Investigation of Rescue Robot." Advanced Materials Research 711 (June 2013): 523–28. http://dx.doi.org/10.4028/www.scientific.net/amr.711.523.
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The thesis research aimed to further the study of human-robot interaction (HRI) issues, especially regarding the development of rescue robot. The paper firstly discussed the status of the rescue robot and described the framework of human-robot interaction of search-rescue robot and rescue-evacuation robot. Subsequently, the general HRI issues will be discussed to explain how they affect the use of robots. Finally, we present suggested this multidisciplinary field of research, namely human-robot interaction, requires contributions from a variety of research fields such as robotics, human-computer interaction, and artificial intelligence.
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Collins, Galen R. "Improving human–robot interactions in hospitality settings." International Hospitality Review 34, no. 1 (April 18, 2020): 61–79. http://dx.doi.org/10.1108/ihr-09-2019-0019.
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PurposeService robotics, a branch of robotics that entails the development of robots able to assist humans in their environment, is of growing interest in the hospitality industry. Designing effective autonomous service robots, however, requires an understanding of Human–Robot Interaction (HRI), a relatively young discipline dedicated to understanding, designing, and evaluating robotic systems for use by or with humans. HRI has not yet received sufficient attention in hospitality robotic design, much like Human–Computer Interaction (HCI) in property management system design in the 1980s. This article proposes a set of introductory HRI guidelines with implementation standards for autonomous hospitality service robots.Design/methodology/approachA set of key user-centered HRI guidelines for hospitality service robots were extracted from 52 research articles. These are organized into service performance categories to provide more context for their application in hospitality settings.FindingsBased on an extensive literature review, this article presents some HRI guidelines that may drive higher levels of acceptance of service robots in customer-facing situations. Deriving meaningful HRI guidelines requires an understanding of how customers evaluate service interactions with humans in hospitality settings and to what degree those will differ with service robots.Originality/valueRobots are challenging assumptions on how hospitality businesses operate. They are being increasingly deployed by hotels and restaurants to boost productivity and maintain service levels. Effective HRI guidelines incorporate user requirements and expectations in the design specifications. Compilation of such information for designers of hospitality service robots will offer a clearer roadmap for them to follow.
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Kim, Sehoon. "Working With Robots: Human Resource Development Considerations in Human–Robot Interaction." Human Resource Development Review 21, no. 1 (February 9, 2022): 48–74. http://dx.doi.org/10.1177/15344843211068810.
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Advancements in robotic technology have accelerated the adoption of collaborative robots in the workplace. The role of humans is not reduced, but robotic technology requires different high-level responsibilities in human–robot interaction (HRI). Based on a human-centered perspective, this literature review is to explore current knowledge on HRI through the lens of HRD and propose the roles of HRD in this realm. The review identifies HRD considerations that help implement effective HRI in three human-centered domains: human capabilities, collaboration configuration, and attributes related to contact. The eight HRD considerations include employees’ attitudes toward robots, their readiness for robot technology, communication with robots, human–robot team building, leading multiple robots, systemwide collaboration, safety interventions, and ethical issues. Theoretical implications, practical implications, and limitations are discussed. This paper contributes to HRD by introducing potential areas of multidisciplinary collaborations to help organizations implement robotic systems.
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Warta, Samantha F., Katelynn A. Kapalo, Andrew Best, and Stephen M. Fiore. "Similarity, Complementarity, and Agency in HRI." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 1230–34. http://dx.doi.org/10.1177/1541931213601287.
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Robotic teammates are becoming prevalent in increasingly complex and dynamic operational and social settings. For this reason, the perception of robots operating in such environments has transitioned from the perception of robots as tools, extending human capabilities, to the perception of robots as teammates, collaborating with humans and displaying complex social cognitive processes. The goal of this paper is to introduce a discussion on an integrated set of robotic design elements, as well as provide support for the idea that human-robot interaction requires a clearer understanding of social cognitive constructs to optimize human-robot collaboration. We develop a set of research questions addressing these constructs with the goal of improving the engineering of artificial cognitive systems reliant on natural human-robot interaction.
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Rauchbauer, Birgit, Bruno Nazarian, Morgane Bourhis, Magalie Ochs, Laurent Prévot, and Thierry Chaminade. "Brain activity during reciprocal social interaction investigated using conversational robots as control condition." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1771 (March 11, 2019): 20180033. http://dx.doi.org/10.1098/rstb.2018.0033.
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We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (human–human interaction, HHI) to an interaction with a conversational robot (human–robot interaction, HRI). The social interaction consists of 1 min blocks of live bidirectional discussion between the scanned participant and the human or robot agent. A final sample of 21 participants is included in the corpus comprising physiological (blood oxygen level-dependent, respiration and peripheral blood flow) and behavioural (recorded speech from all interlocutors, eye tracking from the scanned participant, face recording of the human and robot agents) data. Here, we present the first analysis of this corpus, contrasting neural activity between HHI and HRI. We hypothesized that independently of differences in behaviour between interactions with the human and robot agent, neural markers of mentalizing (temporoparietal junction (TPJ) and medial prefrontal cortex) and social motivation (hypothalamus and amygdala) would only be active in HHI. Results confirmed significantly increased response associated with HHI in the TPJ, hypothalamus and amygdala, but not in the medial prefrontal cortex. Future analysis of this corpus will include fine-grained characterization of verbal and non-verbal behaviours recorded during the interaction to investigate their neural correlates. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction'.
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Hayashi, Akiyoshi, Liz Katherine Rincon-Ardila, and Gentiane Venture. "Improving HRI with Force Sensing." Machines 10, no. 1 (December 24, 2021): 15. http://dx.doi.org/10.3390/machines10010015.
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In the future, in a society where robots and humans live together, HRI is an important field of research. While most human–robot-interaction (HRI) studies focus on appearance and dialogue, touch-communication has not been the focus of many studies despite the importance of its role in human–human communication. This paper investigates how and where humans touch an inorganic non-zoomorphic robot arm. Based on these results, we install touch sensors on the robot arm and conduct experiments to collect data of users’ impressions towards the robot when touching it. Our results suggest two main things. First, the touch gestures were collected with two sensors, and the collected data can be analyzed using machine learning to classify the gestures. Second, communication between humans and robots using touch can improve the user’s impression of the robots.
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Aspragathos, Nikos, Vassilis Moulianitis, and Panagiotis Koustoumpardis. "Special Issue on Human–Robot Interaction (HRI)." Robotica 38, no. 10 (October 2020): 1715–16. http://dx.doi.org/10.1017/s0263574720000946.
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Human–robot interaction (HRI) is one of the most rapidly growing research fields in robotics and promising for the future of robotics technology. Despite the fact that numerous significant research results in HRI have been presented during the last years, there are still challenges in several critical topics of HRI, which could be summarized as: (i) collision and safety, (ii) virtual guides, (iii) cooperative manipulation, (iv) teleoperation and haptic interfaces, and (v) learning by observation or demonstration. In physical HRI research, the complementarity of the human and the robot capabilities is carefully considered for the advancement of their cooperation in a safe manner. New advanced control systems should be developed so the robot will acquire the ability to adapt easily to the human intentions and to the given task. The possible applications requiring co-manipulation are cooperative transportation of bulky and heavy objects, manufacturing processes such as assembly and surgery.
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Kang, In Sung, and Ken Nah. "Proposal of Emotional HRI Design for human interaction with autonomous driving robot that prevents crime." Korea Institute of Design Research Society 7, no. 2 (June 30, 2022): 246–55. http://dx.doi.org/10.46248/kidrs.2022.2.246.
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As technologies such as autonomous driving, AI, and robots develop as the era of the 4th industrial revolution arrives, robot development is accelerating as it has been proven that the introduction of robots in service industries and fields improves productivity. HRI design is an important element that enables smooth communication between humans and robots to create friendly emotions, and is a meaningful research topic for humans and robots to coexist in the future society. To this end, in this paper, we propose the design of human-robot interaction (HRI) with objectivity through user analysis. For this study, the user perception was accurately investigated by comparing two robots that have a common category in the autonomous driving patrol robot field and have different interaction ranges such as appearance, color, and display, which are visual elements. As a result of the survey, the three keywords derived for the recognition of autonomous driving crime prevention robots were cute, soft, and friendly. We set the emotional expression HRI design direction focusing on three keywords, and proposed 16 kinds of emotional expression expression designs according to use cases. In addition, various interactions will be designed for smoother communication through follow-up research, and a usability test will be conducted.
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Onnasch, Linda, and Clara Laudine Hildebrandt. "Impact of Anthropomorphic Robot Design on Trust and Attention in Industrial Human-Robot Interaction." ACM Transactions on Human-Robot Interaction 11, no. 1 (March 31, 2022): 1–24. http://dx.doi.org/10.1145/3472224.
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The application of anthropomorphic features to robots is generally considered beneficial for human-robot interaction (HRI ). Although previous research has mainly focused on social robots, the phenomenon gains increasing attention in industrial human-Robot interaction as well. In this study, the impact of anthropomorphic design of a collaborative industrial robot on the dynamics of trust and visual attention allocation was examined. Participants interacted with a robot, which was either anthropomorphically or non-anthropomorphically designed. Unexpectedly, attribute-based trust measures revealed no beneficial effect of anthropomorphism but even a negative impact on the perceived reliability of the robot. Trust behavior was not significantly affected by an anthropomorphic robot design during faultless interactions, but showed a relatively steeper decrease after participants experienced a failure of the robot. With regard to attention allocation, the study clearly reveals a distracting effect of anthropomorphic robot design. The results emphasize that anthropomorphism might not be an appropriate feature in industrial HRI as it not only failed to reveal positive effects on trust, but distracted participants from relevant task areas which might be a significant drawback with regard to occupational safety in HRI.
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Morya, Shubham, and Raja P. "A Review on HRI for Child Learning." International Journal of Engineering Research in Computer Science and Engineering 9, no. 6 (June 20, 2022): 45–49. http://dx.doi.org/10.36647/ijercse/09.06.art008.
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Human robot interaction (HRI) becomes an effective method of interacting with kids. Many HRI's system are currently available. In this paper, a review of various robotic tutor system based on design aspects, safety aspects, mechanical and electronic aspects of robots, learning outcome of kids, type of interaction, configuration of various learning modules, real time behavior monitoring and socio centric aspect are presented in this paper. As the robot tutoring has several benefits over human tutoring because these kinds of system have various pre-installed learning modules so that without any human monitoring child learn its concept. The robotic system is now a days become very effective for the learner for real time applications
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Lei, Yu, Zhi Su, and Chao Cheng. "Virtual reality in human-robot interaction: Challenges and benefits." Electronic Research Archive 31, no. 5 (2023): 2374–408. http://dx.doi.org/10.3934/era.2023121.
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<abstract> <p>Virtual reality (VR) technology has been increasingly employed in human-robot interaction (HRI) research to enhance the immersion and realism of the interaction. However, the integration of VR into HRI also introduces new challenges, such as latency, mismatch between virtual and real environments and potential adverse effects on human users. Despite these challenges, the use of VR in HRI has the potential to provide numerous benefits, including improved communication, increased safety and enhanced training and education. Yet, little research has been done by scholars to review the state of the art of VR applications in human-robot interaction. To bridge the gap, this paper provides an overview of the challenges and benefits of using VR in HRI, as well as current research in the field and future directions for development. It has been found that robots are getting more personalized, interactive and engaging than ever; and with the popularization of virtual reality innovations, we might be able to foresee the wide adoption of VR in controlling robots to fulfill various tasks of hospitals, schools and factories. Still, there are several challenges, such as the need for more advanced VR technologies to provide more realistic and immersive experiences, the development of more human-like robot models to improve social interactions and the need for better methods of evaluating the effectiveness of VR in human-robot interaction.</p> </abstract>
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Pollmann, Kathrin, and Daniel Ziegler. "A Pattern Approach to Comprehensible and Pleasant Human–Robot Interaction." Multimodal Technologies and Interaction 5, no. 9 (August 27, 2021): 49. http://dx.doi.org/10.3390/mti5090049.
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HRI designers are faced with the task of creating robots that are easy and pleasant to use for the users. The growing body of research in human–robot interaction (HRI) is still mainly focused on technical aspects of the interaction. It lacks defined guidelines that describe how behavioral expressions for social robots need to be designed to promote high usability and positive user experience. To achieve this goal, we propose to apply the concept of design patterns to HRI. We present a design process that provides step-by-step guidance and methods for HRI designers to generate high quality behavioral patterns for social robots that can be used for different robots and use cases. To document the resulting patterns, we developed a documentation format that provides a clear, standardized structure to note down all relevant aspects of a pattern so that others can understand its design recommendations and apply them to their own robot and use cases. In the present paper, we demonstrate our pattern approach based on an example and describe how we arrived at a pattern language of 40 behavioral patterns that found the basis for future social robot design and related research activities.
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Wullenkord, Ricarda, and Friederike Eyssel. "Imagine how to behave: the influence of imagined contact on human–robot interaction." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1771 (March 11, 2019): 20180038. http://dx.doi.org/10.1098/rstb.2018.0038.
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Imagined contact (IC), that is, mentally simulating an interaction with an outgroup member, reduces negative attitudes towards outgroup members, increases contact intentions, and reduces intergroup anxiety in human–human intergroup context. Our experiment tested the effectiveness of IC with a robot to improve human–robot interaction (HRI). Social psychological literature suggested that IC provides a behavioural script for an interaction. Hence, an imagined scenario similar to a real contact scenario should be more effective in eliciting the aforementioned positive effects. We therefore examined the effect of similarity between IC with a robot and the following actual HRI on interaction perception, and behaviours towards the robot. High similarity was expected to lead to a more positive perception of HRI and more positive interaction behaviour towards the robot (e.g. more social behaviour). Results showed that perceived HRI quality was evaluated more positively and participants displayed more social behaviour towards the robot when the imagined task resembled the HRI that followed, compared to when it did not resemble the subsequent HRI. When controlling for covariates, the effects on number of social behaviours and perceived interaction quality remained significant, however, there was no effect on the total amount of time spent producing social behaviours. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
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Williams, Tom, Daniel Szafir, Tathagata Chakraborti, and Heni Ben Amor. "The 1st International Workshop on Virtual, Augmented, and Mixed Reality for Human-Robot Interaction." AI Magazine 39, no. 4 (December 1, 2018): 64–66. http://dx.doi.org/10.1609/aimag.v39i4.2822.
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The 1st International Workshop on Virtual, Augmented, and Mixed Reality for Human-Robot Interaction (VAM-HRI) was held in 2018 in conjunction with the 13th International Conference on Human-Robot Interaction, and brought together researchers from the fields of Human-Robot Interaction (HRI), Robotics, Artificial Intelligence, and Virtual, Augmented, and Mixed Reality in order to identify challenges in mixed reality interactions between humans and robots. This inaugural workshop featured a keynote talk from Blair MacIntyre (Mozilla, Georgia Tech), a panel discussion, and twenty-nine papers presented as lightning talks and/or posters. In this report, we briefly survey the papers presented at the workshop and outline some potential directions for the community.
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Vazhapilli Sureshbabu, A., N. M. Martins Pacheco, L. I. Duran Noy, and M. Zimmermann. "Design of an Autonomous Trash-Picking Service Robot Focussed on Human-Robot Interaction." Proceedings of the Design Society 2 (May 2022): 2523–32. http://dx.doi.org/10.1017/pds.2022.255.
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AbstractThe design of service robots is typically treated as a mechatronic design problem aimed at implementation of its core technical functionalities. Intuitive operation and usability are ignored. We developed a trash-picking service robot with a strong focus on human-robot interaction (HRI) using the double diamond framework. The HRI-focussed hardware features were successfully implemented and tested. The results were shown to satisfy the ease of operation and usability requirements set as development goals for the robot.
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Lohse, Manja, Marc Hanheide, Karola Pitsch, Katharina J. Rohlfing, and Gerhard Sagerer. "Improving HRI design by applying Systemic Interaction Analysis (SInA)." Interaction Studies 10, no. 3 (December 10, 2009): 298–323. http://dx.doi.org/10.1075/is.10.3.03loh.
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Social robots are designed to interact with humans. That is why they need interaction models that take social behaviors into account. These usually influence many of a robot’s abilities simultaneously. Hence, when designing robots that users will want to interact with, all components need to be tested in the system context, with real users and real tasks in real interactions. This requires methods that link the analysis of the robot’s internal computations within and between components (system level) with the interplay between robot and user (interaction level). This article presents Systemic Interaction Analysis (SInA) as an integrated method to (a) derive prototypical courses of interaction based on system and interaction level, (b) identify deviations from these, (c) infer the causes of deviations by analyzing the system’s operational sequences, and (d) improve the robot iteratively by adjusting models and implementations. Keywords: analysis tools, user studies, autonomous robots
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Alenljung, Beatrice, Jessica Lindblom, Rebecca Andreasson, and Tom Ziemke. "User Experience in Social Human-Robot Interaction." International Journal of Ambient Computing and Intelligence 8, no. 2 (April 2017): 12–31. http://dx.doi.org/10.4018/ijaci.2017040102.
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Socially interactive robots are expected to have an increasing importance in human society. For social robots to provide long-term added value to people's lives, it is of major importance to stress the need for positive user experience (UX) of such robots. The human-centered view emphasizes various aspects that emerge in the interaction between humans and robots. However, a positive UX does not appear by itself but has to be designed for and evaluated systematically. In this paper, the focus is on the role and relevance of UX in human-robot interaction (HRI) and four trends concerning the role and relevance of UX related to socially interactive robots are identified, and three challenges related to its evaluation are also presented. It is argued that current research efforts and directions are not sufficient in HRI research, and that future research needs to further address interdisciplinary research in order to achieve long-term success of socially interactive robots.
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Medicherla, Harsha, and Ali Sekmen. "Human–robot interaction via voice-controllable intelligent user interface." Robotica 25, no. 5 (September 2007): 521–27. http://dx.doi.org/10.1017/s0263574707003414.
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SUMMARYAn understanding of how humans and robots can successfully interact to accomplish specific tasks is crucial in creating more sophisticated robots that may eventually become an integral part of human societies. A social robot needs to be able to learn the preferences and capabilities of the people with whom it interacts so that it can adapt its behaviors for more efficient and friendly interaction. Advances in human– computer interaction technologies have been widely used in improving human–robot interaction (HRI). It is now possible to interact with robots via natural communication means such as speech. In this paper, an innovative approach for HRI via voice-controllable intelligent user interfaces is described. The design and implementation of such interfaces are described. The traditional approaches for human–robot user interface design are explained and the advantages of the proposed approach are presented. The designed intelligent user interface, which learns user preferences and capabilities in time, can be controlled with voice. The system was successfully implemented and tested on a Pioneer 3-AT mobile robot. 20 participants, who were assessed on spatial reasoning ability, directed the robot in spatial navigation tasks to evaluate the effectiveness of the voice control in HRI. Time to complete the task, number of steps, and errors were collected. Results indicated that spatial reasoning ability and voice-control were reliable predictors of efficiency of robot teleoperation. 75% of the subjects with high spatial reasoning ability preferred using voice-control over manual control. The effect of spatial reasoning ability in teleoperation with voice-control was lower compared to that of manual control.
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Ferland, François, Aurélien Reveleau, Francis Leconte, Dominic Létourneau, and François Michaud. "Coordination mechanism for integrated design of Human-Robot Interaction scenarios." Paladyn, Journal of Behavioral Robotics 8, no. 1 (December 20, 2017): 100–111. http://dx.doi.org/10.1515/pjbr-2017-0006.
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Abstract The ultimate long-term goal in Human-Robot Interaction (HRI) is to design robots that can act as a natural extension to humans. This requires the design of robot control architectures to provide structure for the integration of the necessary components into HRI. This paper describes how HBBA, a Hybrid Behavior-Based Architecture, can be used as a unifying framework for integrated design of HRI scenarios. More specifically, we focus here on HBBA’s generic coordination mechanism of behavior-producing modules, which allows to address a wide range or cognitive capabilities ranging from assisted teleoperation to selective attention and episodic memory. Using IRL-1, a humanoid robot equipped with compliant actuators for motion and manipulation, proximity sensors, cameras and a microphone array, three interaction scenarios are implemented: multi-modal teleoperation with physical guidance interaction, fetching-and delivering and tour-guiding.
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Wei, Yuan, and Jing Zhao. "Designing robot behavior in human robot interaction based on emotion expression." Industrial Robot: An International Journal 43, no. 4 (June 20, 2016): 380–89. http://dx.doi.org/10.1108/ir-08-2015-0164.
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Purpose This paper aims to deal with the problem of designing robot behaviors (mainly to robotic arms) to express emotions. The authors study the effects of robot behaviors from our humanoid robot NAO on the subject’s emotion expression in human–robot interaction (HRI). Design/methodology/approach A method to design robot behavior through the movement primitives is proposed. Then, a novel dimensional affective model is built. Finally, the concept of action semantics is adopted to combine the robot behaviors with emotion expression. Findings For the evaluation of this combination, the authors assess positive (excited and happy) and negative (frightened and sad) emotional patterns on 20 subjects which are divided into two groups (whether they were familiar with robots). The results show that the recognition of the different emotion patterns does not have differences between the two groups and the subjects could recognize the robot behaviors with emotions. Practical implications Using affective models to guide robots’ behavior or express their intentions is highly beneficial in human–robot interaction. The authors think about several applications of the emotional motion: improve efficiency in HRI, direct people during disasters, better understanding with human partners or help people perform their tasks better. Originality/value This paper presents a method to design robot behaviors with emotion expression. Meanwhile, a similar methodology can be used in other parts (leg, torso, head and so on) of humanoid robots or non-humanoid robots, such as industrial robots.
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Mostafaoui, Ghiles, R. C. Schmidt, Syed Khursheed Hasnain, Robin Salesse, and Ludovic Marin. "Human unintentional and intentional interpersonal coordination in interaction with a humanoid robot." PLOS ONE 17, no. 1 (January 19, 2022): e0261174. http://dx.doi.org/10.1371/journal.pone.0261174.
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In order to establish natural social synchrony between two humans, two requirements need to be fulfilled. First, the coupling must be bi-directional. The two humans react to each other’s actions. Second, natural social bodily synchronization has to be intentional or unintentional. Assuming that these essential aspects of human-human interactions are present, the present paper investigates whether similar bodily synchrony emerges between an interacting human and an artificial agent such as a robot. More precisely, we investigate whether the same human unintentional rhythmic entrainment and synchronization is present in Human Robot Interaction (HRI). We also evaluate which model (e.g., an adaptive vs non adaptive robot) better reproduces such unintentional entrainment. And finally, we compare interagent coordination stability of the HRI under 1) unidirectional (robot with fixed frequency) versus bidirectional (robot with adaptive frequency) rhythmic entrainment and 2) human intentional versus unintentional coupling. Fifteen young adults made vertical arm movements in front of the NAO robot under five different conditions of intentional/unintentional and unidirectional/bidirectional interactions. Consistent with prior research investigating human-human interpersonal coordination, when humans interact with our robot, (i) unintentional entrainment was present, (ii) bi-directional coupling produced more stable in-phase un-intentional and intentional coordination, (iii) and intentional coordination was more stable than unintentional coordination. To conclude, this study provides a foundation for modeling future social robots involving unintentional and bidirectional synchronization—aspects which seem to enhance humans’ willingness to interact with robots.
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Shi, Lei, Cosmin Copot, and Steve Vanlanduit. "GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction." Robotics 10, no. 2 (April 30, 2021): 68. http://dx.doi.org/10.3390/robotics10020068.
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In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario.
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Cross, Emily S., Ruud Hortensius, and Agnieszka Wykowska. "From social brains to social robots: applying neurocognitive insights to human–robot interaction." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1771 (March 11, 2019): 20180024. http://dx.doi.org/10.1098/rstb.2018.0024.
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Amidst the fourth industrial revolution, social robots are resolutely moving from fiction to reality. With sophisticated artificial agents becoming ever more ubiquitous in daily life, researchers across different fields are grappling with the questions concerning how humans perceive and interact with these agents and the extent to which the human brain incorporates intelligent machines into our social milieu. This theme issue surveys and discusses the latest findings, current challenges and future directions in neuroscience- and psychology-inspired human–robot interaction (HRI). Critical questions are explored from a transdisciplinary perspective centred around four core topics in HRI: technical solutions for HRI, development and learning for HRI, robots as a tool to study social cognition, and moral and ethical implications of HRI. Integrating findings from diverse but complementary research fields, including social and cognitive neurosciences, psychology, artificial intelligence and robotics, the contributions showcase ways in which research from disciplines spanning biological sciences, social sciences and technology deepen our understanding of the potential and limits of robotic agents in human social life. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
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Isbister, Katherine, Peter Cottrell, Alessia Cecchet, Ella Dagan, Nikki Theofanopoulou, Ferran Altarriba Bertran, Aaron J. Horowitz, Nick Mead, Joel B. Schwartz, and Petr Slovak. "Design (Not) Lost in Translation: A Case Study of an Intimate-Space Socially Assistive “Robot” for Emotion Regulation." ACM Transactions on Computer-Human Interaction 29, no. 4 (August 31, 2022): 1–36. http://dx.doi.org/10.1145/3491083.
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We present a Research-through-Design case study of the design and development of an intimate-space tangible device perhaps best understood as a socially assistive robot, aimed at scaffolding children’s efforts at emotional regulation. This case study covers the initial research device development, as well as knowledge transfer to a product development company toward translating the research into a workable commercial product that could also serve as a robust “research product” for field trials. Key contributions to the literature include: (1) sharing of lessons learned from the knowledge transfer process that can be useful to others interested in developing robust products (whether commercial or research) that preserve design values, while allowing for large scale deployment and research; (2) articulation of a design space in HCI/HRI (Human Robot Interaction) of intimate space socially assistive robots , with the current artifact as a central exemplar, contextualized alongside other related HRI artifacts.
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Durdu, Akif, Aydan M. Erkmen, and Alper Yilmaz. "Reshaping human intention in Human-Robot Interactions by robot moves." Interaction Studies 20, no. 3 (November 18, 2019): 530–60. http://dx.doi.org/10.1075/is.18068.dur.
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Abstract This paper outlines the methodology and experiments associated with the reshaping of human intentions based on robot movements within Human-Robot Interactions (HRIs). Although studies on estimating human intentions are well studied in the literature, reshaping intentions through robot-initiated interactions is a new significant branching in the field of HRI. In this paper, we analyze how estimated human intentions can intentionally change through cooperation with mobile robots in real Human-Robot environments. This paper proposes an intention-reshaping system that includes either the Observable Operator Models (OOMs) or Hidden Markov Models (HMMs) to estimate human intention and decide which moves a robot should perform to reshape previously estimated human intentions into desired ones. At the low level, the system needs to track the locations of all mobile agents using cameras. We test our system on videos taken in a real HRI environment that has been developed as our experimental setup. The results show that OOMs are faster than HMMs and both models give correct decisions for testing sequences.
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Liu, Huashuo, Fei Wang, and Dan Zhang. "Inspiring Real-Time Evaluation and Optimization of Human–Robot Interaction with Psychological Findings from Human–Human Interaction." Applied Sciences 13, no. 2 (January 4, 2023): 676. http://dx.doi.org/10.3390/app13020676.
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The increasingly central role of robotic agents in daily life requires effective human–robot interaction (HRI). For roboticists to optimize interaction design, it is crucial to understand the potential effects of robotic agents on human performance. Yet a systematic specification of contributing factors is lacking, and objective measures of HRI performance are still limited. In these regards, the findings of research on human–human interaction can provide valuable insights. In this review, we break down the complex effects of robotic agents on interacting humans into some basic building blocks based on human–human interaction findings, i.e., the potential effects of physical presence, motor actions, and task co-representation in HRI. For each effect, we advise on future directions regarding its implication. Furthermore, we propose that the neural correlates of these effects could support real-time evaluation and optimization of HRI with electroencephalograph (EEG)-based brain–computer interface (BCI).
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Tian, Leimin, and Sharon Oviatt. "A Taxonomy of Social Errors in Human-Robot Interaction." ACM Transactions on Human-Robot Interaction 10, no. 2 (May 2021): 1–32. http://dx.doi.org/10.1145/3439720.
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Robotic applications have entered various aspects of our lives, such as health care and educational services. In such Human-robot Interaction (HRI), trust and mutual adaption are established and maintained through a positive social relationship between a user and a robot. This social relationship relies on the perceived competence of a robot on the social-emotional dimension. However, because of technical limitations and user heterogeneity, current HRI is far from error-free, especially when a system leaves controlled lab environments and is applied to in-the-wild conditions. Errors in HRI may either degrade a user’s perception of a robot’s capability in achieving a task (defined as performance errors in this work) or degrade a user’s perception of a robot’s socio-affective competence (defined as social errors in this work). The impact of these errors and effective strategies to handle such an impact remains an open question. We focus on social errors in HRI in this work. In particular, we identify the major attributes of perceived socio-affective competence by reviewing human social interaction studies and HRI error studies. This motivates us to propose a taxonomy of social errors in HRI. We then discuss the impact of social errors situated in three representative HRI scenarios. This article provides foundations for a systematic analysis of the social-emotional dimension of HRI. The proposed taxonomy of social errors encourages the development of user-centered HRI systems, designed to offer positive and adaptive interaction experiences and improved interaction outcomes.
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Story, Matthew, Cyril Jaksic, Sarah R. Fletcher, Philip Webb, Gilbert Tang, and Jonathan Carberry. "Evaluating the use of human aware navigation in industrial robot arms." Paladyn, Journal of Behavioral Robotics 12, no. 1 (January 1, 2021): 379–91. http://dx.doi.org/10.1515/pjbr-2021-0024.
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Abstract Although the principles followed by modern standards for interaction between humans and robots follow the First Law of Robotics popularized in science fiction in the 1960s, the current standards regulating the interaction between humans and robots emphasize the importance of physical safety. However, they are less developed in another key dimension: psychological safety. As sales of industrial robots have been increasing over recent years, so has the frequency of human–robot interaction (HRI). The present article looks at the current safety guidelines for HRI in an industrial setting and assesses their suitability. This article then presents a means to improve current standards utilizing lessons learned from studies into human aware navigation (HAN), which has seen increasing use in mobile robotics. This article highlights limitations in current research, where the relationships established in mobile robotics have not been carried over to industrial robot arms. To understand this, it is necessary to focus less on how a robot arm avoids humans and more on how humans react when a robot is within the same space. Currently, the safety guidelines are behind the technological advance, however, with further studies aimed at understanding HRI and applying it to newly developed path finding and obstacle avoidance methods, science fiction can become science fact.
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MUñOZ, John Edison, and Kerstin Dautenhahn. "Robo Ludens." ACM Transactions on Human-Robot Interaction 10, no. 4 (December 31, 2021): 1–28. http://dx.doi.org/10.1145/3451343.
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The use of games as vehicles to study human-robot interaction (HRI) has been established as a suitable solution to create more realistic and naturalistic opportunities to investigate human behavior. In particular, multiplayer games that involve at least two human players and one or more robots have raised the attention of the research community. This article proposes a scoping review to qualitatively examine the literature on the use of multiplayer games in HRI scenarios employing embodied robots aiming to find experimental patterns and common game design elements. We find that researchers have been using multiplayer games in a wide variety of applications in HRI, including training, entertainment and education, allowing robots to take different roles. Moreover, robots have included different capabilities and sensing technologies, and elements such as external screens or motion controllers were used to foster gameplay. Based on our findings, we propose a design taxonomy called Robo Ludens, which identifies HRI elements and game design fundamentals and classifies important components used in multiplayer HRI scenarios. The Robo Ludens taxonomy covers considerations from a robot-oriented perspective as well as game design aspects to provide a comprehensive list of elements that can foster gameplay and bring enjoyable experiences in HRI scenarios.
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Hüttenrauch, Helge, Elin A. Topp, and Kerstin Severinson-Eklundh. "The Art of Gate-Crashing." Interaction Studies 10, no. 3 (December 10, 2009): 274–97. http://dx.doi.org/10.1075/is.10.3.02hut.
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Special purpose service robots have already entered the market and their users’ homes. Also the idea of the general purpose service robot or personal robot companion is increasingly discussed and investigated. To probe human–robot interaction with a mobile robot in arbitrary domestic settings, we conducted a study in eight different homes. Based on previous results from laboratory studies we identified particular interaction situations which should be studied thoroughly in real home settings. Based upon the collected sensory data from the robot we found that the different environments influenced the spatial management observable during our subjects’ interaction with the robot. We also validated empirically that the concept of spatial prompting can aid spatial management and communication, and assume this concept to be helpful for Human–Robot Interaction (HRI) design. In this article we report on our exploratory field study and our findings regarding, in particular, the spatial management observed during show episodes and movement through narrow passages. Keywords: COGNIRON, Domestic Service Robotics, Robot Field Trial, Human Augmented Mapping (HAM), Human–Robot Interaction (HRI), Spatial Management, Spatial Prompting
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Banisetty, Santosh Balajee, Scott Forer, Logan Yliniemi, Monica Nicolescu, and David Feil-Seifer. "Socially Aware Navigation: A Non-linear Multi-objective Optimization Approach." ACM Transactions on Interactive Intelligent Systems 11, no. 2 (July 19, 2021): 1–26. http://dx.doi.org/10.1145/3453445.
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Mobile robots are increasingly populating homes, hospitals, shopping malls, factory floors, and other human environments. Human society has social norms that people mutually accept; obeying these norms is an essential signal that someone is participating socially with respect to the rest of the population. For robots to be socially compatible with humans, it is crucial for robots to obey these social norms. In prior work, we demonstrated a Socially-Aware Navigation (SAN) planner, based on Pareto Concavity Elimination Transformation (PaCcET), in a hallway scenario, optimizing two objectives so the robot does not invade the personal space of people. This article extends our PaCcET-based SAN planner to multiple scenarios with more than two objectives. We modified the Robot Operating System’s (ROS) navigation stack to include PaCcET in the local planning task. We show that our approach can accommodate multiple Human-Robot Interaction (HRI) scenarios. Using the proposed approach, we achieved successful HRI in multiple scenarios such as hallway interactions, an art gallery, waiting in a queue, and interacting with a group. We implemented our method on a simulated PR2 robot in a 2D simulator (Stage) and a pioneer-3DX mobile robot in the real-world to validate all the scenarios. A comprehensive set of experiments shows that our approach can handle multiple interaction scenarios on both holonomic and non-holonomic robots; hence, it can be a viable option for a Unified Socially-Aware Navigation (USAN).
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Morze, Magdalena. "Human Robot Interaction - key areas in teamwork." Journal of Advanced Research in Leadership 1, no. 2 (November 14, 2022): 9–17. http://dx.doi.org/10.33422/jarl.v1i2.158.
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Industry 4.0 is based on the implementation of smart technologies. Work teams consisting of humans and intelligent machines, such as robots, are becoming more common. Their cooperation is based on joint performance of tasks in order to achieve set goals. The aim of the article is to present the challenges associated with the functioning of new types of work teams in organizations: based on cooperation between people and intelligent machines (robots or artificial intelligence algorithms). The article discusses the impact of factors such as trust, mental models, human personality, and machine reliability on the functioning of human-robot teams. It is shown how these areas can affect the performance of HRI - Human Robot Interaction Teams. The literature analysis indicates that before valuable human-robot interaction can occur, humans must first build trust in the machines. And the reliability of robots, and the human sense of control over them, increases trust. In addition, human personality and the attributes presented by a robot are also important for cooperation. For example, robots perceived as extroverted and socially intelligent have a high level of acceptance from humans.
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Gunes, Hatice, Oya Celiktutan, and Evangelos Sariyanidi. "Live human–robot interactive public demonstrations with automatic emotion and personality prediction." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1771 (March 11, 2019): 20180026. http://dx.doi.org/10.1098/rstb.2018.0026.
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Communication with humans is a multi-faceted phenomenon where the emotions, personality and non-verbal behaviours, as well as the verbal behaviours, play a significant role, and human–robot interaction (HRI) technologies should respect this complexity to achieve efficient and seamless communication. In this paper, we describe the design and execution of five public demonstrations made with two HRI systems that aimed at automatically sensing and analysing human participants’ non-verbal behaviour and predicting their facial action units, facial expressions and personality in real time while they interacted with a small humanoid robot. We describe an overview of the challenges faced together with the lessons learned from those demonstrations in order to better inform the science and engineering fields to design and build better robots with more purposeful interaction capabilities. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
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Kwon, Ohbyung, Jeonghun Kim, Yoonsun Jin, and Namyeon Lee. "Impact of human-robot interaction on user satisfaction with humanoid-based healthcare." International Journal of Engineering & Technology 7, no. 2.12 (April 3, 2018): 68. http://dx.doi.org/10.14419/ijet.v7i2.12.11038.
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Background/Objectives: The advent of self-service technology (SST) (e.g.,kiosks and Automatic Response System), has made it possible for service providersto make use of non-face-to-face channels to meet users’needs and decrease users’costs and time. On the other hand, however, more complex technology and/or services inhibit users’ satisfaction and,consequently,the intention to adopt SST, because such SST can instill fear in users. Nevertheless, at present, patients and other people who are interested in their own health and well-being are paying great attention to healthcare robots (as a form of SST)and,consequently, it has become crucial to investigate how these healthcare robots can positively influence users’ satisfaction with them. Hence, this study aims to empirically investigate the factors that affect users’ satisfaction with healthcare robots, especially in regard to human-robot interaction (HRI).Methods/Statistical analysis: We focused on the theory of heterophily and applied a series of factors identified in previous robot-adoption studies.Uniquely, this study focuses on users’ heterophily with healthcare robots, examining heterophily through three fundamental elements, empathy, professionalism, and personality, which we considered to be suitable fordetermining user satisfaction with HRI-based communication.To prove the validity of our hypotheses, we conducted an empirical testthat involved participants receiving a short health assessment from a robot.Findings: The findings of our empirical test supported our hypothesis that the lower the difference in empathy between a user and robot, the higher the level of user satisfaction with the humanoid-style healthcare service. Further, our results also suggest that heterogeneity between a user and healthcare robot is positively associated with user satisfaction.Improvements/Applications: First, to increase user satisfaction,robots must be provided with the ability to somehow recognizea user’s personality and adjust their own accordingly before beginning the robot-based healthcare service. Secondly, users’ behavior patterns should be analyzed by the healthcare robot. Overall, our study empirically shows the importance of ensuring thatprofessionalism is present in healthcare-domain-related HRI.
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Nomura, Tatsuya. "Robots and Gender." Gender and the Genome 1, no. 1 (March 2017): 18–26. http://dx.doi.org/10.1089/gg.2016.29002.nom.
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This article provides an overview of the current research on gender in human-robot interaction (HRI) including a discussion of the effects of gender characteristics in robotics design (robot gender), gender differences on interaction with robots (human gender), and some interaction effects between the two. The article also reviews research that examined the impact of the interaction between humans and robots with regard to robot appearance and behaviors, and situational factors, such as tasks and roles. Although the current state of research findings is complicated, it appears that even simple gendering of robots by manipulation of voice and name can affect humans’ feelings and behaviors toward robots. These effects vary and are dependent on other factors, including human gender. Future research should focus on gender stereotypes, cultural influences, and robotic applications in various fields. At the same time, we should consider if gendering of robots, for given roles, is really necessary to encourage interactions between humans and robots.
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Murphy, Robin R., and Jennifer L. Burke. "Up from the Rubble: Lessons Learned about HRI from Search and Rescue." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 3 (September 2005): 437–41. http://dx.doi.org/10.1177/154193120504900347.
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The Center for Robot-Assisted Search and Rescue has collected data at three responses (World Trade Center, Hurricane Charley, and the La Conchita mudslide) and nine high fidelity field exercises. Our results can be distilled into four lessons. First, building situation awareness, not autonomous navigation, is the major bottleneck in robot autonomy. Most of the robotics literature assumes a single operator single robot (SOSR), while our work shows that two operators working together are nine times more likely to find a victim. Second, human-robot interaction should not be thought of how to control the robot but rather how a team of experts can exploit the robot as an active information source. The third lesson is that team members use shared visual information to build shared mental models and facilitate team coordination. This suggests that high bandwidth, reliable communications will be necessary for effective teamwork. Fourth, victims and rescuers in close proximity to the robots respond to the robot socially. We conclude with observations about the general challenges in human-robot interaction.
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Rosli, Muhammad Azeem, Aimi Shazwani Ghazali, and Muhammad Ikmal Hakim Shamsul Bahrin. "Enhancing social responses: effects of controlling language by a social robot in a decision-making game for human-robot interaction (HRI)." Applied Research and Smart Technology (ARSTech) 3, no. 2 (December 27, 2022): 81–92. http://dx.doi.org/10.23917/arstech.v3i2.1187.
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The rise of technology has induced the development of robots that engage with humans through social interaction. The robot is believed capable of assisting humans in their life. However, the current technology is still far from a fully autonomous robot as there are many limitations. Additionally, it is unclear whether the current social robot effectively influences social reactance in Human-Robot Interaction (HRI). The objective of the study is to investigate the influence of social cues used by the social robot on human social responses for HRI applications. Also, the study validates the reactance scale used in the questionnaire by correlating the measure with Galvanic Skin Response (GSR) readings. The study proposes Wizard of Oz (WoZ) approach to observe HRI through decision-making games. A social robot is programmed to persuade participants' in making choices. The participants' decisions made during the experiment and their GSR reading are recorded, and then they are asked to answer questionnaires. Statistical analyses are done on the collected data using the regression and MANOVA statistical tests. As results, there is a significant correlation between GSR reading and enjoyment. Regarding social cues, the participants feel more relaxed when the social robot exhibits social cues in High Controlling Language (HCL) conditions rather than Low Controlling Language (LCL) conditions. Furthermore, the Attitude trait of the social robots greatly influences human perceived social intelligence towards the robot.
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Khan, Sara, and Claudio Germak. "Reframing HRI Design Opportunities for Social Robots: Lessons Learnt from a Service Robotics Case Study Approach Using UX for HRI." Future Internet 10, no. 10 (October 10, 2018): 101. http://dx.doi.org/10.3390/fi10100101.
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Over the last few decades, semi-autonomous machine’s technology started to promote awareness towards the importance of human–robot interaction (HRI) for improving daily activities. More affordable social robots are being commercially released and in order to implement viable applications of HRI, a combination human-computer interaction and user experience methodologies could play a pivotal role in assessing new scenarios and evaluating new investigations. However, literature shows that it is still challenging to reach an optimal user experience with robotic companions. The aim of the study was to determine the chance to enhance the user experience with a semi-autonomous social robot, using user experience and human–computer interaction methodologies. In this study, a social robotic companion has been developed and prototyped in order to be adopted in a specific public environment such as a company workspace. The challenges emerged from this peculiar environment triggered the need for a more productive and comfortable office for the employees, and, at the same time, the usability, acceptance and likeability of the robotic companion have been evaluated. The results emphasize that, since HRI is highly interdisciplinary, the benefits of combining approaches from other fields could positively benefit from a meaningful social interaction with the users.
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Roy, Raphaëlle N., Nicolas Drougard, Thibault Gateau, Frédéric Dehais, and Caroline P. C. Chanel. "How Can Physiological Computing Benefit Human-Robot Interaction?" Robotics 9, no. 4 (November 25, 2020): 100. http://dx.doi.org/10.3390/robotics9040100.
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As systems grow more automatized, the human operator is all too often overlooked. Although human-robot interaction (HRI) can be quite demanding in terms of cognitive resources, the mental states (MS) of the operators are not yet taken into account by existing systems. As humans are no providential agents, this lack can lead to hazardous situations. The growing number of neurophysiology and machine learning tools now allows for efficient operators’ MS monitoring. Sending feedback on MS in a closed-loop solution is therefore at hand. Involving a consistent automated planning technique to handle such a process could be a significant asset. This perspective article was meant to provide the reader with a synthesis of the significant literature with a view to implementing systems that adapt to the operator’s MS to improve human-robot operations’ safety and performance. First of all, the need for this approach is detailed regarding remote operation, an example of HRI. Then, several MS identified as crucial for this type of HRI are defined, along with relevant electrophysiological markers. A focus is made on prime degraded MS linked to time-on-task and task demands, as well as collateral MS linked to system outputs (i.e., feedback and alarms). Lastly, the principle of symbiotic HRI is detailed and one solution is proposed to include the operator state vector into the system using a mixed-initiative decisional framework to drive such an interaction.
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Kaonain, Tamanna E., Mohd Azizi Abdul Rahman, Mohd Hatta Mohammed Ariff, and Kuheli Mondal. "A simulated risk assessment of human-robot interaction in the domestic environment." IAES International Journal of Robotics and Automation (IJRA) 9, no. 4 (December 1, 2020): 300. http://dx.doi.org/10.11591/ijra.v9i4.pp300-310.
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In human-robot interaction, the use of collaborative robots or cobots in many industries is of major importance to researchers in human-robot interaction (HRI). The interaction between human robot carries several challenges, the greatest being the risk of human injury. In addition to reducing the proximity between robots and humans, increased difficulty of human-robot encounters raises the likelihood of accidents only. This paper proposes a virtual collaborative robot in the simulated non-industrial workspace. The safety during human-robot interaction using simulation software was investigated by measuring the risks for planning and control. A reactive robot controller was formulated to minimize the risk during human-robot interaction. A Gazebo software is used in this article, written in Python language, to replicate complex environments that a robot can face. This paper also investigated the robot’s speed. It can be reduced before a collision with a human about to happen, and it minimized the risk of the collision or reduced the damage of the risk. After the successful simulation, this can be applied to the real robot in a practical domestic environment.
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Cantucci, Filippo, and Rino Falcone. "Collaborative Autonomy: Human–Robot Interaction to the Test of Intelligent Help." Electronics 11, no. 19 (September 26, 2022): 3065. http://dx.doi.org/10.3390/electronics11193065.
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A big challenge in human–robot interaction (HRI) is the design of autonomous robots that collaborate effectively with humans, exposing behaviors similar to those exhibited by humans when they interact with each other. Indeed, robots are part of daily life in multiple environments (i.e., cultural heritage sites, hospitals, offices, touristic scenarios and so on). In these contexts, robots have to coexist and interact with a wide spectrum of users not necessarily able or willing to adapt their interaction level to the kind requested by a machine: the users need to deal with artificial systems whose behaviors must be adapted as much as possible to the goals/needs of the users themselves, or more in general, to their mental states (beliefs, goals, plans and so on). In this paper, we introduce a cognitive architecture for adaptive and transparent human–robot interaction. The architecture allows a social robot to dynamically adjust its level of collaborative autonomy by restricting or expanding a delegated task on the basis of several context factors such as the mental states attributed to the human users involved in the interaction. This collaboration has to be based on different cognitive capabilities of the robot, i.e., the ability to build a user’s profile, to have a Theory of Mind of the user in terms of mental states attribution, to build a complex model of the context, intended both as a set of physical constraints and constraints due to the presence of other agents, with their own mental states. Based on the defined cognitive architecture and on the model of task delegation theorized by Castelfranchi and Falcone, the robot’s behavior is explainable by considering the abilities to attribute specific mental states to the user, the context in which it operates and its attitudes in adapting the level of autonomy to the user’s mental states and the context itself. The architecture has been implemented by exploiting the well known agent-oriented programming framework Jason. We provide the results of an HRI pilot study in which we recruited 26 real participants that have interacted with the humanoid robot Nao, widely used in HRI scenarios. The robot played the role of a museum assistant with the main goal to provide the user the most suitable museum exhibition to visit.
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Vallverdú, Jordi, Gabriele Trovato, and Lorenzo Jamone. "Allocentric Emotional Affordances in HRI: The Multimodal Binding." Multimodal Technologies and Interaction 2, no. 4 (November 6, 2018): 78. http://dx.doi.org/10.3390/mti2040078.
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The concept of affordance perception is one of the distinctive traits of human cognition; and its application to robots can dramatically improve the quality of human-robot interaction (HRI). In this paper we explore and discuss the idea of “emotional affordances” by proposing a viable model for implementation into HRI; which considers allocentric and multimodal perception. We consider “2-ways” affordances: perceived object triggering an emotion; and perceived human emotion expression triggering an action. In order to make the implementation generic; the proposed model includes a library that can be customised depending on the specific robot and application scenario. We present the AAA (Affordance-Appraisal-Arousal) model; which incorporates Plutchik’s Wheel of Emotions; and we outline some numerical examples of how it can be used in different scenarios.
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Ashraf, Kamran, and Muhammad Asif. "Robust Action Selection by the Robot in Human-Robot Interaction (HRI) Environment." International Journal of Computer Applications 155, no. 7 (December 15, 2016): 40–43. http://dx.doi.org/10.5120/ijca2016912359.
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Daza, Marcos, Dennis Barrios-Aranibar, José Diaz-Amado, Yudith Cardinale, and João Vilasboas. "An Approach of Social Navigation Based on Proxemics for Crowded Environments of Humans and Robots." Micromachines 12, no. 2 (February 13, 2021): 193. http://dx.doi.org/10.3390/mi12020193.
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Nowadays, mobile robots are playing an important role in different areas of science, industry, academia and even in everyday life. In this sense, their abilities and behaviours become increasingly complex. In particular, in indoor environments, such as hospitals, schools, banks and museums, where the robot coincides with people and other robots, its movement and navigation must be programmed and adapted to robot–robot and human–robot interactions. However, existing approaches are focused either on multi-robot navigation (robot–robot interaction) or social navigation with human presence (human–robot interaction), neglecting the integration of both approaches. Proxemic interaction is recently being used in this domain of research, to improve Human–Robot Interaction (HRI). In this context, we propose an autonomous navigation approach for mobile robots in indoor environments, based on the principles of proxemic theory, integrated with classical navigation algorithms, such as ORCA, Social Momentum, and A*. With this novel approach, the mobile robot adapts its behaviour, by analysing the proximity of people to each other, with respect to it, and with respect to other robots to decide and plan its respective navigation, while showing acceptable social behaviours in presence of humans. We describe our proposed approach and show how proxemics and the classical navigation algorithms are combined to provide an effective navigation, while respecting social human distances. To show the suitability of our approach, we simulate several situations of coexistence of robots and humans, demonstrating an effective social navigation.