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Journal articles on the topic 'Human Robot Interaction (HRI)'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

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 (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 hu

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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 (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

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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 (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 conce

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Zhao, Mengyao. "Emotion Recognition in Psychology of Human-robot Interaction." Psychomachina 1 (November 21, 2023): 1–11. http://dx.doi.org/10.59388/pm00331.

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The field of Human-Robot Interaction (HRI) has garnered significant attention in recent years, with researchers and practitioners seeking to understand the psychological aspects underlying the interactions between humans and robots. One crucial area of focus within HRI is the psychology of emotion recognition, which plays a fundamental role in shaping the dynamics of human-robot interaction. This paper provides an overview of the background of psychology in the context of human-robot interaction, emphasizing the significance of understanding human emotions in this domain. The concept of emotio

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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 (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 pl

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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 (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 socia

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Lee, Heejin. "A Human-Robot Interaction Entertainment Pet Robot." Journal of Korean Institute of Intelligent Systems 24, no. 2 (2014): 179–85. http://dx.doi.org/10.5391/jkiis.2014.24.2.179.

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Bonarini, Andrea. "Communication in Human-Robot Interaction." Current Robotics Reports 1, no. 4 (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

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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-comput

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Kim, Sehoon. "Working With Robots: Human Resource Development Considerations in Human–Robot Interaction." Human Resource Development Review 21, no. 1 (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 co

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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 (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 inte

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Collins, Galen R. "Improving human–robot interactions in hospitality settings." International Hospitality Review 34, no. 1 (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

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Sirithunge, Chapa, Kalhan S. Boralessa, W. H. Eranga, Buddhika P. Jayasekara, D. P. Chandima, and Manjula U. Hemapala. "Exploring Embodied Resources in Gaze in Human-Robot Collaborative Environments." IOP Conference Series: Materials Science and Engineering 1292, no. 1 (2023): 012013. http://dx.doi.org/10.1088/1757-899x/1292/1/012013.

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Abstract Among various types of embodied resources in humans, gaze, started with mutual gaze, plays a major role in embodied cognition. In addition to establishing relationships during interactions, gaze further portrays information about the level of engagement in a dyadic interaction. Hence the gaze and gaze-related behaviors such as averted gaze can be used as cues to make decisions regarding an interaction. This holds true for a human and a robot during human-robot interaction (HRI) as well. Hence proactive robots could evaluate human gaze as a parameter to achieve situation-awareness. In

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Ruchik, Kashyapkumar Thaker. "Human-Robot Interaction: Designing robots that can naturally interact and collaborate with humans." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 6, no. 4 (2020): 1–6. https://doi.org/10.5281/zenodo.14001622.

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Robot learning from demonstration (LfD) is a key research paradigm that addresses the challenge of scaling robot learning, enabling robots to acquire new knowledge without prior expertise in mechanical engineering or computer programming. This approach allows non-experts to teach robots tasks, promoting real-world applications where robots, like newborns, can learn from humans through interaction. The literature highlights the significant role of LfD in human-robot collaborative tasks, emphasizing the importance of designing communication frameworks for effective human-robot collaboration (HRC

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Lee, Sukhan, Soojin Lee, and Hyunwoo Park. "Integration of Tracking, Re-Identification, and Gesture Recognition for Facilitating Human–Robot Interaction." Sensors 24, no. 15 (2024): 4850. http://dx.doi.org/10.3390/s24154850.

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For successful human–robot collaboration, it is crucial to establish and sustain quality interaction between humans and robots, making it essential to facilitate human–robot interaction (HRI) effectively. The evolution of robot intelligence now enables robots to take a proactive role in initiating and sustaining HRI, thereby allowing humans to concentrate more on their primary tasks. In this paper, we introduce a system known as the Robot-Facilitated Interaction System (RFIS), where mobile robots are employed to perform identification, tracking, re-identification, and gesture recognition in an

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Hayashi, Akiyoshi, Liz Katherine Rincon-Ardila, and Gentiane Venture. "Improving HRI with Force Sensing." Machines 10, no. 1 (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 thin

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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 (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

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Malik, Dr Pankaj. "The integration of Natural Language Processing (NLP) in Human-Robot Interaction (HRI) represents a significant advancement towards achieving more natural and effective communication between humans and robots. This research explores the application of state-of-the-art NLP techniques to enhance HRI, focusing on improving robots' abilities to understand and generate human language. Key components of our approach include advanced speech recognition, natural language understanding (NLU), dialogue management, and natural language generation (NLG). We designed and implemented an HRI system that leverages models such as BERT for language understanding and GPT-3 for generating contextually appropriate responses. Our methodology involves integrating these NLP models with a robotics platform, ensuring real-time interaction capabilities while maintaining a high level of accuracy and context awareness. The system was evaluated through a series of user studies, measuring performance metrics such as accuracy, latency, and user satisfaction. Results indicate that our NLP-enhanced HRI system significantly improves the quality of interactions, demonstrating superior understanding and responsiveness compared to traditional systems. This paper discusses the implementation challenges, including computational constraints and ambiguity resolution, and provides insights into user feedback and system performance. Future work will focus on enhancing context management, exploring multimodal interaction, and addressing ethical considerations in deploying advanced HRI systems. Our findings underscore the potential of NLP to transform human-robot communication, paving the way for more intuitive and effective robotic assistants in various domains. Keywords: Human-Robot Interaction (HRI), Natural Language Processing (NLP), Conversational AI, Speech Recognition, Natural Language Understanding (NLU), Natural Language Generation (NLG), Multimodal Interaction, Dialogue Systems, Context Awareness, Emotion Recognition, Machine Learning in HRI, Personalized Interaction, User Experience (UX) in HRI, Human-Centered Design, Collaborative Robots (Cobots)." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem35803.

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The integration of Natural Language Processing (NLP) in Human-Robot Interaction (HRI) represents a significant advancement towards achieving more natural and effective communication between humans and robots. This research explores the application of state-of-the-art NLP techniques to enhance HRI, focusing on improving robots' abilities to understand and generate human language. Key components of our approach include advanced speech recognition, natural language understanding (NLU), dialogue management, and natural language generation (NLG). We designed and implemented an HRI system that lever

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Aspragathos, Nikos, Vassilis Moulianitis, and Panagiotis Koustoumpardis. "Special Issue on Human–Robot Interaction (HRI)." Robotica 38, no. 10 (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 capabili

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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 (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

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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 (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 examine

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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 (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 reveal

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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

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Subramanian, Karthik, Liya Thomas, Melis Sahin, and Ferat Sahin. "Supporting Human–Robot Interaction in Manufacturing with Augmented Reality and Effective Human–Computer Interaction: A Review and Framework." Machines 12, no. 10 (2024): 706. http://dx.doi.org/10.3390/machines12100706.

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The integration of Augmented Reality (AR) into Human–Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI with a focus on manufacturing, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved Situational Awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detai

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Alexander Obaigbena, Oluwaseun Augustine Lottu, Ejike David Ugwuanyi, et al. "AI and human-robot interaction: A review of recent advances and challenges." GSC Advanced Research and Reviews 18, no. 2 (2024): 321–30. http://dx.doi.org/10.30574/gscarr.2024.18.2.0070.

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The integration of artificial intelligence (AI) into human-robot interaction (HRI) has witnessed significant advancements in recent years, revolutionizing the way humans and robots collaborate and coexist. This review provides a comprehensive overview of the latest breakthroughs in AI-driven HRI and identifies the challenges that lie ahead. Recent years have seen a surge in AI-driven capabilities that enhance human-robot interaction. Machine learning algorithms enable robots to adapt to user preferences and behaviors, creating personalized and intuitive interactions. Natural language processin

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Alexander, Obaigbena, Augustine Lottu Oluwaseun, David Ugwuanyi Ejike, Sonimitiem Jacks Boma, Oluwademilade Sodiya Enoch, and Donald Daraojimba Obinna. "AI and human-robot interaction: A review of recent advances and challenges." GSC Advanced Research and Reviews 18, no. 2 (2024): 321–30. https://doi.org/10.5281/zenodo.11216497.

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The integration of artificial intelligence (AI) into human-robot interaction (HRI) has witnessed significant advancements in recent years, revolutionizing the way humans and robots collaborate and coexist. This review provides a comprehensive overview of the latest breakthroughs in AI-driven HRI and identifies the challenges that lie ahead. Recent years have seen a surge in AI-driven capabilities that enhance human-robot interaction. Machine learning algorithms enable robots to adapt to user preferences and behaviors, creating personalized and intuitive interactions. Natural language processin

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Arpitha J, Yogitha R, Soniya G R, Sumanth Gowda, and Rudresh. "A Review on Human Robot Interaction in Healthcare." International Journal of Soft Computing and Engineering 14, no. 4 (2024): 7–11. http://dx.doi.org/10.35940/ijsce.i9948.14040924.

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Robots are increasingly being used in healthcare delivery and their effectiveness can be determined through understanding their personalities. Nonetheless, healthcare human robot interaction (H-HRI) has not had a systematic or comprehensive grasp of personality. In the past Healthcare has presented benefits for humanoid robots. However, there is no systematic and comprehensive understanding of personality in health care human robot interaction (H-HRI). This paper examines some common scenarios in medicine and provides an exhaustive way to measure trust. Such a proposed paradigm highlights the

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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 (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 beha

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Antonio, Imelda B., Jerwin Sadia, Roe Jr A. Bata-anon, Erwin B. Quendangan, and Jeffrey T. Leonen. "EXPLORING THE DYNAMICS OF HUMAN- ROBOT INTERACTION(HRI): A MULTIDISCIPLINARY INVESTIGATION." Ignatian International Journal for Multidisciplinary Research 2, no. 6 (2024): 2081–91. https://doi.org/10.5281/zenodo.12560284.

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This study explores the dynamics of human-robot interaction (HRI) by integrating insights from cognitive science, robotics engineering, sociology, psychology, and ethics. The research aims to understand the factors influencing human perception and acceptance of robots, as well as the implications for individuals, communities, and broader societal structures. The study employs a descriptive research methodology, gathering data through questionnaires and direct perception from 30 respondents. The results highlight the importance of multidisciplinary approaches in enhancing HRI, including design,

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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 (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 prese

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Yogitha, R. "A Review on Human Robot Interaction in Healthcare." International Journal of Soft Computing and Engineering (IJSCE) 14, no. 4 (2024): 7–11. https://doi.org/10.35940/ijsce.I9948.14040924.

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<strong>Abstract: </strong>Robots are increasingly being used in healthcare delivery and their effectiveness can be determined through understanding their personalities. Nonetheless, healthcare human robot interaction (H-HRI) has not had a systematic or comprehensive grasp of personality. In the past Healthcare has presented benefits for humanoid robots. However, there is no systematic and comprehensive understanding of personality in health care human robot interaction (H-HRI). This paper examines some common scenarios in medicine and provides an exhaustive way to measure trust. Such a propos

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Gao, Wa, Yuan Tian, Shiyi Shen, et al. "Exploring the Effects of Multi-Factors on User Emotions in Scenarios of Interaction Errors in Human–Robot Interaction." Applied Sciences 14, no. 18 (2024): 8164. http://dx.doi.org/10.3390/app14188164.

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Interaction errors are hard to avoid in the process of human–robot interaction (HRI). User emotions toward interaction errors could further affect the user’s attitudes to robots and experiences of HRI and so on. In this regard, the present study explores the effects of different factors on user emotions when interaction errors occur in HRI. There is sparse research directly studying this perspective. In so doing, three factors, including robot feedback, passive and active contexts, and previous user emotions, were considered. Two stages of online surveys with 465 participants were implemented

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Adawy, Mohammad, Hasan Abualese, Nidhal Kamel Taha El-Omari, and Abdulwadood Alawadhi. "Human-Robot Interaction (HRI) using Machine Learning (ML): a Survey and Taxonomy." International Journal of Advances in Soft Computing and its Applications 16, no. 3 (2024): 166–82. http://dx.doi.org/10.15849/ijasca.241130.11.

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Human-robot interaction (HRI) which has become the fundamental need of the hour is born out of the necessity for studying the relation between humans and robots. This cutting-edge discipline is a multidisciplinary field that draws from computer science, robotics along with human-computer interaction and psychology. It focuses mainly on designing and programming machines, best known as automated machines or robots, which are used by humans to perform specific tasks in a timely manner and with higher quality. The key problem in HRI is to realize, shape, tune, and modelling the humanrobot interac

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Mousa, Ali, and Asia Mahdi Nasser. "ENHANCING HUMAN-ROBOT INTERACTION THROUGH GROUP EMOTION RECOGNITION." Iraqi Journal for Computers and Informatics 49, no. 2 (2023): 111–19. http://dx.doi.org/10.25195/ijci.v49i2.444.

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Abstract - This article explores within the field of Human-Robot Interaction (HRI), focusing on the complicated relationship between emotions, decision-making, and robot behaviors. Emotions are essential to effective communication and interaction, requiring the development of emotion recognition systems in robots. The article explores both individual and group emotion recognition, including microexpressions and macroexpressions. Group emotion dynamics, encompassing phenomena like emotional contagion, convergence, and social influence, are separated to understand how emotions combine within col

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Motorina, L. E. "HRI as a Phenomenon of Social Interaction." Social Psychology and Society 14, no. 1 (2023): 38–54. http://dx.doi.org/10.17759/sps.2023140103.

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<p style="text-align: justify;"><strong>Objective</strong><strong>.</strong> Development of general theoretical and methodological concepts for the analysis of the interaction "human-robot" as a holistic human-technological gestalt; introduction into scientific circulation of the concept of human-technological reality; the formulation of the author's definition of personal space as a methodological basis for the study of human-technological relations.<br><strong>Background.</strong> The creation of high-tech computer cognitive agents and humanoid

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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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Medicherla, Harsha, and Ali Sekmen. "Human–robot interaction via voice-controllable intelligent user interface." Robotica 25, no. 5 (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 mean

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Lu, Sin-Ru, Jia-Hsun Lo, Yi-Tian Hong, and Han-Pang Huang. "Implementation of Engagement Detection for Human–Robot Interaction in Complex Environments." Sensors 24, no. 11 (2024): 3311. http://dx.doi.org/10.3390/s24113311.

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This study develops a comprehensive robotic system, termed the robot cognitive system, for complex environments, integrating three models: the engagement model, the intention model, and the human–robot interaction (HRI) model. The system aims to enhance the naturalness and comfort of HRI by enabling robots to detect human behaviors, intentions, and emotions accurately. A novel dual-arm-hand mobile robot, Mobi, was designed to demonstrate the system’s efficacy. The engagement model utilizes eye gaze, head pose, and action recognition to determine the suitable moment for interaction initiation,

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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 (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

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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 (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 sync

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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 (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 as

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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 (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

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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 (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 a

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Han, In Ho, Dong Hwan Kim, Kyoung Hyup Nam, et al. "Human-Robot Interaction and Social Robot: The Emerging Field of Healthcare Robotics and Current and Future Perspectives for Spinal Care." Neurospine 21, no. 3 (2024): 868–77. http://dx.doi.org/10.14245/ns.2448432.216.

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Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI,

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Gregory, Jason M., and Satyandra K. Gupta. "Opportunities for Generative Artificial Intelligence to Accelerate Deployment of Human-Supervised Autonomous Robots." Proceedings of the AAAI Symposium Series 2, no. 1 (2024): 177–81. http://dx.doi.org/10.1609/aaaiss.v2i1.27667.

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Autonomous robots have the potential to supplement human capabilities while reducing cognitive and physical burden. However, deploying such systems in natural settings is currently a time-consuming process that revolves around a human’s ability to research, design, test, and evaluate the robot – thereby introducing unnecessary bottlenecks and significant delays to technology adoption. The current work in the field of human-robot interaction (HRI) has historically focused on robot use even though humans play a critical role during autonomous system design and deployment. We argue that the scope

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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 (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

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Hüttenrauch, Helge, Elin A. Topp, and Kerstin Severinson-Eklundh. "The Art of Gate-Crashing." Interaction Studies 10, no. 3 (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 influenc

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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 (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 quest

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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 (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

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Spisak, Sharon Ewa, and Bipin Indurkhya. "A Study on Social Exclusion in Human-Robot Interaction." Electronics 12, no. 7 (2023): 1585. http://dx.doi.org/10.3390/electronics12071585.

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Recent research in human-robot interaction (HRI) points to possible unfair outcomes caused by artificial systems based on machine learning. The aim of this study was to investigate if people are susceptible to social exclusion shown by a robot and, if they are, how they signal the feeling of being rejected from the group. We review the research on social exclusion in the context of human–human interaction and explore its relevance for HRI. Then we present the results of our experiment to simulate social exclusion in the context of HRI: the participants (for whom it was their first encounter wi

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