Human-robot Interaction Research Research Articles

Gaze-based intention estimation: principles, methodologies, and applications in HRI

Intention prediction has become a relevant field of research in Human-Machine and Human-Robot Interaction. Indeed, any artificial system (co)-operating with and along humans, designed to assist and coordinate its actions with a human partner, would benefit from first inferring the human’s current intention. To spare the user the cognitive burden of explicitly uttering their goals, this inference relies mostly on behavioral cues deemed indicative of the current action. It has been long known that eye movements are highly anticipatory of the single steps unfolding during a task, hence they can serve as a very early and reliable behavioural cue for intention recognition. This conceptual review aims to draw a line between insights in the psychological literature on visuomotor control and relevant applications of gaze-based intention recognition in technical domains, with a focus on teleoperated and assistive robotic systems. Starting from the cognitive principles underlying the relationship between intentions, eye movements, and action, the use of eye tracking and gaze-based models for intent recognition in Human-Robot Interaction is considered, with prevalent methodologies and their diverse applications. Finally, special consideration is given to relevant human factors issues and current limitations to be factored in when designing such systems.

Social robot accessories for tailoring and appropriation of social robots

AbstractThe design of robots for everyday use should take into account the specific nature of the individual end-user and the possibility of interactions with multiple users in diverse scenarios, promoting versatility and increasing the chances of their successful adoption in everyday environments. Most robots are designed, however, to perform tasks and interact in typical social scenarios with an abstract human user. We observed a recent surge in the use of accessories with social robots, which aligns with a broader trend of consumers’ preference for personalizing the technologies they interact with. Drawing from the concepts of adaptability and customizability in collaborative systems, we explore the potential use of accessory-like items for social robots to enable low-tech customization and user appropriation, thus enhancing their value and suitability in various social situations. We draw from Human-Computer Interaction and Computer-Supported Co-operative Work literature to show how end-user customizability and appropriation are essential, but less frequently considered, in the study and design of social robots. We conceptualize Social Robot Accessories (SRAs) as a way for end-users to customize robots, and present three studies - (1) a literature survey on accessory-like item use with social robots, (2) a survey of commercially available robot accessories, and (3) a Twitter-based analysis of accessory use for AIBO and LOVOT robots by their users. We use findings from these studies to envision a design space of SRAs for use by Human-Robot Interaction (HRI) researchers.

Previous Experience Matters: An in-Person Investigation of Expectations in Human–Robot Interaction

The human–robot interaction (HRI) field goes beyond the mere technical aspects of developing robots, often investigating how humans perceive robots. Human perceptions and behavior are determined, in part, by expectations. Given the impact of expectations on behavior, it is important to understand what expectations individuals bring into HRI settings and how those expectations may affect their interactions with the robot over time. For many people, social robots are not a common part of their experiences, thus any expectations they have of social robots are likely shaped by other sources. As a result, individual expectations coming into HRI settings may be highly variable. Although there has been some recent interest in expectations within the field, there is an overall lack of empirical investigation into its impacts on HRI, especially in-person robot interactions. To this end, a within-subject in-person study (N=31\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N=31$$\\end{document}) was performed where participants were instructed to engage in open conversation with the social robot Pepper during two 2.5 min sessions. The robot was equipped with a custom dialogue system based on the GPT-3 large language model, allowing autonomous responses to verbal input. Participants’ affective changes towards the robot were assessed using three questionnaires, NARS, RAS, commonly used in HRI studies, and Closeness, based on the IOS scale. In addition to the three standard questionnaires, a custom question was administered to capture participants’ views on robot capabilities. All measures were collected three times, before the interaction with the robot, after the first interaction with the robot, and after the second interaction with the robot. Results revealed that participants to large degrees stayed with the expectations they had coming into the study, and in contrast to our hypothesis, none of the measured scales moved towards a common mean. Moreover, previous experience with robots was revealed to be a major factor of how participants experienced the robot in the study. These results could be interpreted as implying that expectations of robots are to large degrees decided before interactions with the robot, and that these expectations do not necessarily change as a result of the interaction. Results reveal a strong connection to how expectations are studied in social psychology and human-human interaction, underpinning its relevance for HRI research.

A Psychological Need-Fulfillment Perspective for Designing Social Robots that Support Well-Being

AbstractThis conceptual paper presents a novel framework for the design and study of social robots that support well-being. Building upon the self-determination theory and the associated Motivation, Engagement, and Thriving in User Experience (METUX) model, this paper argues that users’ psychological basic needs for autonomy, competence, and relatedness should be put at the center of social robot design. These basic needs are essential to people’s psychological well-being, engagement, and self-motivation. However, current literature offers limited insights into how human–robot interactions are related to users’ experiences of the satisfaction of their basic psychological needs and thus, to their well-being and flourishing. We propose that a need-fulfillment perspective could be an inspiring lens for the design of social robots, including socially assistive robots. We conceptualize various ways in which a psychological need-fulfillment perspective may be incorporated into future human–robot interaction research and design, ranging from the interface level to the specific tasks performed by a robot or the user’s behavior supported by the robot. The paper discusses the implications of the framework for designing social robots that promote well-being, as well as the implications for future research.

Privacy and utility perceptions of social robots in healthcare

Many Human-Robot Interaction (HRI) researchers are exploring the use of healthcare robots. Due to the sensitive nature of care, privacy concerns play a significant role in determining robot utility and adoption. While HRI research has explored some dimensions of privacy for robots in general, to our knowledge, no prior work has empirically studied how human-like robot design affects people's privacy and utility perceptions of robots across different healthcare contexts and tasks. We conducted a 3 × 3 × 3 study (n = 239) to understand these relationships, varying robot Human Likeness (HL) (low, medium, and high) and scenario/task type (hospital waiting room/robot check-in support, hospital patient room/robot mobility support, home care/robot neurorehabilitation support) via a mixed between-within subjects design. To our knowledge, this is one of the first studies that operationalizes complex constructs of privacy, healthcare, and HL across multiple realistic healthcare contexts, with a high degree of cognitive fidelity. Our results suggest the tasks and contexts in which privacy is considered in healthcare contexts with robots is more impactful than other factors like robot HL appearance. In particular, some settings include more complex tradeoffs between privacy and utility for robots than others. For example, HRI researchers and practitioners who want to build healthcare robots intended for the home may encounter the greatest challenges for balancing privacy risks. Finally, for the community, we demonstrate that design fiction animations can be a useful way to facilitate cognitive fidelity for supporting studies in HRI and serving as a bridge between narrative methods and the use of real-world robots.

Working with roubles and failures in conversation between humans and robots: workshop report.

This paper summarizes the structure and findings from the first Workshop on Troubles and Failures in Conversations between Humans and Robots. The workshop was organized to bring together a small, interdisciplinary group of researchers working on miscommunication from two complementary perspectives. One group of technology-oriented researchers was made up of roboticists, Human-Robot Interaction (HRI) researchers and dialogue system experts. The second group involved experts from conversation analysis, cognitive science, and linguistics. Uniting both groups of researchers is the belief that communication failures between humans and machines need to be taken seriously and that a systematic analysis of such failures may open fruitful avenues in research beyond current practices to improve such systems, including both speech-centric and multimodal interfaces. This workshop represents a starting point for this endeavour. The aim of the workshop was threefold: Firstly, to establish an interdisciplinary network of researchers that share a common interest in investigating communicative failures with a particular view towards robotic speech interfaces; secondly, to gain a partial overview of the "failure landscape" as experienced by roboticists and HRI researchers; and thirdly, to determine the potential for creating a robotic benchmark scenario for testing future speech interfaces with respect to the identified failures. The present article summarizes both the "failure landscape" surveyed during the workshop as well as the outcomes of the attempt to define a benchmark scenario.

Do Robots Have Sex? A Prolegomenon

Research in Human–Robot Interaction (HRI) suggests that people attribute gender to (some) robots. In this paper we outline a program of research on the gendering of robots and on the ethical issues raised by such gendering. Understanding which robots are gendered, when, and why, will require careful research in HRI, drawing on anthropology and social psychology, informed by state-of-the-art research in gender studies and critical theory. Design features of robots that might influence the attribution of gender include: appearance; tone of voice; speech repertoire; range and style of movement; behaviour; and, intended function. Robots may be gendered differently depending on: the age, class, sex, ethnicity, and sexuality of the person doing the attributing; local cultural histories; social cues from the designers, the physical and institutional environment, and other users; and the role of the robot. An adequate account of the gender of robots will also need to pay attention to the limits of a sex/gender distinction, which has historically been maintained by reference to a “sex” located in a biological body, when it comes to theorising the gender of robots. We argue that, on some accounts of what it is to be sexed, robots might “have” sex: they might be male and female in just the same way as (most) human beings are. Addressing the ethical issues raised by the gendering of robots will require further progress in “robot media ethics”, as well as an account of the responsibilities of both designers and users in a broader social context.

Towards a conceptualisation and critique of everyday life in HRI.

This paper focuses on the topic of "everyday life" as it is addressed in Human-Robot Interaction (HRI) research. It starts from the argument that while human daily life with social robots has been increasingly discussed and studied in HRI, the concept of everyday life lacks clarity or systematic analysis, and it plays only a secondary role in supporting the study of the key HRI topics. In order to help conceptualise everyday life as a research theme in HRI in its own right, we provide an overview of the Social Science and Humanities (SSH) perspectives on everyday life and lived experiences, particularly in sociology, and identify the key elements that may serve to further develop and empirically study such a concept in HRI. We propose new angles of analysis that may help better explore unique aspects of human engagement with social robots. We look at the everyday not just as a reality as we know it (i.e., the realm of the "ordinary") but also as the future that we need to envision and strive to materialise (i.e., the transformation that will take place through the "extraordinary" that comes with social robots). Finally, we argue that HRI research would benefit not only from engaging with a systematic conceptualisation but also critique of the contemporary everyday life with social robots. This is how HRI studies could play an important role in challenging the current ways of understanding of what makes different aspects of the human world "natural" and ultimately help bringing a social change towards what we consider a "good life."

AAAI 2023 Spring Symposium on HRI in Academia and Industry: Bridging the Gap

AbstractOn March 27–29, 2023, the AAAI symposium on “HRI in Academia and Industry: Bridging the Gap” was held in a hybrid format, with both in‐person and remote participants, gathering Human‐Robot Interaction (HRI) researchers and practitioners from academia, industry, and national research laboratories to find common ground, understand the different constraints at play, and determine how to work together. The use of robots that operate in spaces in which humans are physically co‐present is growing at a dramatic rate. We are seeing more and more robots in our warehouses, on our streets, and even in our homes. All of these robots will interact with humans in some way, whether intentionally or unintentionally. To be successful, their interactions with humans will have to be carefully designed. For more than a decade, the field of HRI has been growing at the intersection of robotics, Artificial Intelligence (AI) , human‐computer interaction (HCI), psychology, and other fields; however, until quite recently, it has been a largely academic area, with university researchers proposing, implementing, and reporting on experiments at a limited scale. With the current increase of commercially‐available robots, HRI is starting to make its way into the robotics industry in a meaningful way. This symposium brought together HRI researchers and practitioners from academia, industry, and national research laboratories to find common ground, understand the different constraints at play, and determine how to effectively work together.

Ethics and Robot Democratization: Reflecting on Integrative Ethics Practices

This paper aims to address the need for new integrative approaches to aid the further development of robot ethics as a research field. It presents observations gathered in a collaborative robotics project that pursued an integrative ethics approach. The paper first contextualizes the increasing attention to ethical approaches in robotics development, design and implementation. Several existing considerations and attempts to further integrate ethics into the field of robotics are reviewed, while also providing context with respect to new trends that generate new possibilities for integrating ethical approaches into robotics and human-robot interaction research. Subsequently, the paper elaborates on the specificities of the collaborative robotics project that pursued an integrative approach. The collaborative robot is presented as a specific type of technological artifact, and insight is given into the project’s aim to “democratize” this technology. Furthermore, practices required to integrate ethics are reviewed based on the author’s observations and experiences in the project. Finally, to contribute to the further development of integrative approaches in robot ethics, these observations are developed into three constitutive components that should aid the further development of integrative robot ethics approaches, namely: increased attention for the way interdisciplinarity is defined in the field of robot ethics, the role and nature of ethical critique, and finally the chances integrative approaches offer for the development of more thorough anticipatory concepts.

15 Years of (Who)man Robot Interaction: Reviewing the H in Human-Robot Interaction

Recent work identified a concerning trend of disproportional gender representation in research participants in Human–Computer Interaction (HCI). Motivated by the fact that Human–Robot Interaction (HRI) shares many participant practices with HCI, we explored whether this trend is mirrored in our field. By producing a dataset covering participant gender representation in all 684 full papers published at the HRI conference from 2006–2021, we identify current trends in HRI research participation. We find an over-representation of men in research participants to date, as well as inconsistent and/or incomplete gender reporting, which typically engages in a binary treatment of gender at odds with published best practice guidelines. We further examine if and how participant gender has been considered in user studies to date, in-line with current discourse surrounding the importance and/or potential risks of gender based analyses. Finally, we complement this with a survey of HRI researchers to examine correlations between who is doing with the who is taking part, to further reflect on factors which seemingly influence gender bias in research participation across different sub-fields of HRI. Through our analysis, we identify areas for improvement, but also reason for optimism, and derive some practical suggestions for HRI researchers going forward.

Concerning Trends in Likert Scale Usage in Human-robot Interaction: Towards Improving Best Practices

As robots become more prevalent, the importance of the field of human-robot interaction (HRI) grows accordingly. As such, we should endeavor to employ the best statistical practices in HRI research. Likert scales are commonly used metrics in HRI to measure perceptions and attitudes. Due to misinformation or honest mistakes, many HRI researchers do not adopt best practices when analyzing Likert data. We conduct a review of psychometric literature to determine the current standard for Likert scale design and analysis. Next, we conduct a survey of five years of the International Conference on Human-Robot Interaction (HRIc) (2016 through 2020) and report on incorrect statistical practices and design of Likert scales [ 1 , 2 , 3 , 5 , 7 ]. During these years, only 4 of the 144 papers applied proper statistical testing to correctly designed Likert scales. We additionally conduct a survey of best practices across several venues and provide a comparative analysis to determine how Likert practices differ across the field of Human-robot Interaction. We find that a venue’s impact score negatively correlates with number of Likert-related errors and acceptance rate, and total number of papers accepted per venue positively correlates with the number of errors. We also find statistically significant differences between venues for the frequency of misnomer and design errors. Our analysis suggests there are areas for meaningful improvement in the design and testing of Likert scales. Based on our findings, we provide guidelines and a tutorial for researchers for developing and analyzing Likert scales and associated data. We also detail a list of recommendations to improve the accuracy of conclusions drawn from Likert data.

A Study on Social Exclusion in Human-Robot Interaction

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 with a robot) and the Nao robot were asked to cooperate in solving the bomb defusal task, during which the robot favored one participant with whom it had a longer interaction before the task. The robot was controlled using the Wizard-of-Oz methodology throughout the experiment. Our results show that the discriminated participants reported a higher feeling of exclusion. Though some other hypotheses were not confirmed, we present several qualitative observations from our experiment. For example, it was noticed that the participants who behaved more openly and were more extraverted acted more comfortably when interacting with the robot.

From EU Robotics and AI Governance to HRI Research: Implementing the Ethics Narrative

AbstractIn recent years, the European Union has made considerable efforts to develop dedicated strategies and policies for the governance of robotics and AI. An important component of the EU’s approach is its emphasis on the need to mitigate the potential societal impacts of the expected rise in the interactive capacities of autonomous systems. In the quest to define and implement new policies addressing this issue, ethical notions have taken an increasingly central position. This paper presents a concise overview of the integration of this ethics narrative in the EU’s policy plans. It demonstrates how the ethics narrative aids the definition of policy issues and the establishment of new policy ideas. Crucially, in this context, robotics and AI are explicitly understood as emerging technologies. This implies many ambiguities about their actual future impact, which in turn results in uncertainty regarding effective implementation of policies that draw on the ethics narrative. In an effort to develop clearer pathways towards the further development of ethical notions in AI and robotics governance, this paper understands human-robot interaction (HRI) research as a field that can play an important role in the implementation of ethics. Four different complementary pathways towards ethics integration in (HRI) research are proposed, namely: providing insights for the improvement of ethical assessment, further research into the moral competence of artificial agents, engage in value-based design and implementation of robots, and participation in discussions on building ethical sociotechnical systems around robots.

A Literature Survey of How to Convey Transparency in Co-Located Human–Robot Interaction

In human–robot interaction, transparency is essential to ensure that humans understand and trust robots. Understanding is vital from an ethical perspective and benefits interaction, e.g., through appropriate trust. While there is research on explanations and their content, the methods used to convey the explanations are underexplored. It remains unclear which approaches are used to foster understanding. To this end, we contribute a systematic literature review exploring how robot transparency is fostered in papers published in the ACM Digital Library and IEEE Xplore. We found that researchers predominantly rely on monomodal visual or verbal explanations to foster understanding. Commonly, these explanations are external, as opposed to being integrated in the robot design. This paper provides an overview of how transparency is communicated in human–robot interaction research and derives a classification with concrete recommendations for communicating transparency. Our results establish a solid base for consistent, transparent human–robot interaction designs.

Robot leadership-Investigating human perceptions and reactions towards social robots showing leadership behaviors.

Human-robot interaction research has shown that social robots can interact with humans in complex social situations and display leadership-related behaviors. Therefore, social robots could be able to take on leadership roles. The aim of our study was to investigate human followers' perceptions and reactions towards robot leadership behavior, and differences based on the robot's displayed leadership style. We implemented a robot to show either a transformational or a transactional leadership style in its speech and its movements. We presented the robot to university and executive MBA students (N = 29) and subsequently conducted semi-structured interviews and group discussions. The results of explorative coding indicated that participants differed in their perceptions and reactions based on the robot's leadership style and based on their assumptions about robots in general. We observed that participants quickly imagined either a utopia or worried about a dystopia, depending on the robot's leadership style and their assumptions, and that a subsequent reflection led to more nuanced views. We discuss the implications and recommendations for human-robot interaction and leadership research.

Designing Robots for Aging: Wisdom as a Critical Lens

Although the concept of wisdom is ancient, empirical research on it has only recently received attention in gerontology. This coincides with a critical turn away from a deficit model of aging, viewing aging as a series of losses, toward a more supportive and developmental model. This article draws on this recent work to consider how wisdom can be a critical lens for human-robot interaction (HRI) researchers and other technology design researchers to pay more attention to the coping strategies that older adults accumulated throughout their lives. We engaged in a 6-month collaborative design process with community-dwelling older adults. The contributions of this article are twofold. First, we found that wisdom as a design concept helps researchers to critically examine how they define knowledge. Wisdom as an accumulation of experiential knowledge of older adults helps researchers rethink the definition of knowledge—valuing computational and technological knowledge—in the field of HRI. Second, wisdom leads researchers to the past experiences of older adults. Although past experiences are as important as current experiences, they are not actively considered in robot design studies for older adults. We hope wisdom as a critical lens could allow researchers to integrate the invisible aspects of older adults’ aging experiences into the existing practices of designing robots for aging users.

The role of prior exposure in the likelihood of adopting the Intentional Stance toward a humanoid robot

Abstract One of the key questions in human–robot interaction research is whether humans perceive robots as intentional agents, or rather only as mindless machines. Research has shown that, in some contexts, people do perceive robots as intentional agents. However, the role of prior exposure to robots as a factor potentially playing a role in the attribution of intentionality is still poorly understood. To this end, we asked two samples of high school students, which differed with respect to the type of education they were pursuing (scientific/technical vs. artistic) to complete the InStance Test, measuring individual tendency to attribute intentionality toward robots. Results showed that, overall, participants were more prone to attribute intentionality to robots after being exposed to a theoretical lecture about robots’ functionality and use. Moreover, participants’ scientific/technical education resulted in a higher likelihood of attribution of intentionality to robots, relative to those with artistic education. Therefore, we suggest that the type of education, as well as individually acquired knowledge, modulates the likelihood of attributing intentionality toward robots.

Virtual reality in human-robot interaction: Challenges and benefits

<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>

Autonomous social robots are real in the mind's eye of many.

Clark and Fischer's dismissal of extant human-robot interaction research approaches limits opportunities to understand major variables shaping people's engagement with social robots. Instead, this endeavour categorically requires multidisciplinary approaches. We refute the assumption that people cannot (correctly or incorrectly) represent robots as autonomous social agents. This contradicts available empirical evidence, and will become increasingly tenuous as robot automation improves.