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Communication among some older adults is affected by cognitive and mobility impairments. This increases isolation, particularly for those residing in care homes, and leads to accelerated cognitive decline. Previous research has leveraged assistive robots to promote recreational routines and communication among older adults, with the robot leading the interaction. However, older adults could have more agency in the interaction, as robots could extend elders' intentions and needs. Therefore, we explored an approach whereby the robot's agency is shifted to the older adults who lead the interaction by commanding a robot's actions using interactive physical blocks (tangible blocks). We conducted sessions with 22 care home dwellers where they could exchange messages and objects using the robot. Based on older adults' observed behaviors during the sessions and perspectives gathered from interviews with geriatric professionals, we reflect on the opportunities and challenges for increased user agency and the asymmetries that emerged from differing abilities and personality traits. Our qualitative results highlight the potential of robotic approaches to extend the agency and communication of older adults, anchored on human values, such as the exchange of affection, collaboration, and competition. [ABSTRACT FROM AUTHOR]

The concept of engagement is widely adopted in the human–robot interaction (HRI) field, as a core social phenomenon in the interaction. Despite the wide usage of the term, the meaning of this concept is still characterized by great vagueness. A common approach is to evaluate it through self-reports and observational grids. While the former solution suffers from a time-discrepancy problem, since the perceived engagement is evaluated at the end of the interaction, the latter solution may be affected by the subjectivity of the observers. From the perspective of developing socially intelligent robots that autonomously adapt their behaviors during the interaction, replicating the ability to properly detect engagement represents a challenge in the social robotics community. This systematic review investigates the conceptualization of engagement, starting with the works that attempted to automatically detect it in interactions involving robots and real users (i.e., online surveys are excluded). The goal is to describe the most worthwhile research efforts and to outline the commonly adopted definitions (which define the authors' perspective on the topic) and their connection with the methodology used for the assessment (if any). The research was conducted within two databases (Web of Science and Scopus) between November 2009 and January 2023. A total of 590 articles were found in the initial search. Thanks to an accurate definition of the exclusion criteria, the most relevant papers on automatic engagement detection and assessment in HRI were identified. Finally, 28 papers were fully evaluated and included in this review. The analysis illustrates that the engagement detection task is mostly addressed as a binary or multi-class classification problem, considering user behavioral cues and context-based features extracted from recorded data. One outcome of this review is the identification of current research barriers and future challenges on the topic, which could be clustered in the following fields: engagement components, annotation procedures, engagement features, prediction techniques, and experimental sessions. [ABSTRACT FROM AUTHOR]

For a period of 3 weeks in June 2021, we embedded a social robot (Softbank Pepper) in a Special Educational Needs (SEN) school for autistic children. The robot's behaviours and integration into the school were co-designed with the children and teachers, with a focus on improving the well-being of the pupils. Using a mix-method approach, we studied the robot's adoption over the course of the study, and the impact of the robot's presence on the children well-being and the school ecosystem. We found that the robot successfully integrated within the school; it fostered and maintained a steady level of interactions (330 interactions, 16 h of continuous use over 3 weeks) with a small yet meaningful group of children with a positive impact on their well-being; and it led to a nuanced conversation with the students and school staff about the role and impact of such a social technology in a SEN school. [ABSTRACT FROM AUTHOR]

As robots become more common, people interact with them individually, with strangers, and with friends. For example, when coming across a robot in a mall, a family might ask it for instructions. An individual person might hesitate to interact with the robot until they see another person interacting, and then explore the robot together. Although human–robot interaction (HRI) research has recently uncovered the importance of examining differences in group behavior toward robots versus individuals' behavior, thus far, most HRI research has not distinguished behavior based on group type (e.g., stranger, companion). In this online lab-based study, we explore how individuals, strangers, and companions collaborate with robot teammates. We test competing hypotheses: (1) More cohesive companion groups will form a human subgroup and exclude the robots more than strangers or individuals, vs. (2) More cohesive companion groups will provide social support to interact better with the novel robotic technology than strangers or individuals. In this cooperative context in which participants were required to interact with the robot, results supported H1: the subgroup hypothesis. Based on these findings, people deploying robots should note that if people are required to interact with the robots, the interactions may not go as smoothly for companion groups compared to stranger groups or individuals. [ABSTRACT FROM AUTHOR]

Robots are a source of evaluative conflict and thus elicit ambivalence. In fact, psychological research has shown across domains that people simultaneously report strong positive and strong negative evaluations about one and the same attitude object. This is defined as ambivalence. In the current research, we extended existing ambivalence research by measuring ambivalence towards various robot-related stimuli using explicit (i.e., self-report) and implicit measures. Concretely, we used a mouse tracking approach to gain insights into the experience and resolution of evaluative conflict elicited by robots. We conducted an extended replication across four experiments with N = 411 overall. This featured a mixed-methods approach and included a single paper meta-analysis. Thereby, we showed that the amount of reported conflicting thoughts and feelings (i.e., objective ambivalence) and self-reported experienced conflict (i.e., subjective ambivalence) were consistently higher towards robot-related stimuli compared to stimuli evoking univalent responses. Further, implicit measures of ambivalence revealed that response times were higher when evaluating robot-related stimuli compared to univalent stimuli, however results concerning behavioral indicators of ambivalence in mouse trajectories were inconsistent. This might indicate that behavioral indicators of ambivalence apparently depend on the respective robot-related stimulus. We could not obtain evidence of systematic information processing as a cognitive indicator of ambivalence, however, qualitative data suggested that participants might focus on especially strong arguments to compensate their experienced conflict. Furthermore, interindividual differences did not seem to substantially influence ambivalence towards robots. Taken together, the current work successfully applied the implicit and explicit measurement of ambivalent attitudes to the domain of social robotics, while at the same time identifying potential boundaries for its application. [ABSTRACT FROM AUTHOR]

This paper addresses the lack of proper Learning from Demonstration (LfD) architectures for Sign Language-based Human–Robot Interactions to make them more extensible. The paper proposes and implements a Learning from Demonstration structure for teaching new Iranian Sign Language signs to a teacher assistant social robot, RASA. This LfD architecture utilizes one-shot learning techniques and Convolutional Neural Network to learn to recognize and imitate a sign after seeing its demonstration (using a data glove) just once. Despite using a small, low diversity data set (~ 500 signs in 16 categories), the recognition module reached a promising 4-way accuracy of 70% on the test data and showed good potential for increasing the extensibility of sign vocabulary in sign language-based human–robot interactions. The expansibility and promising results of the one-shot Learning from Demonstration technique in this study are the main achievements of conducting such machine learning algorithms in social Human–Robot Interaction. [ABSTRACT FROM AUTHOR]

As dementia-induced impairments of daily functioning escalate, novel cognitive stimulation techniques utilizing technological advances, like social robots, have surfaced. This study examines the interaction level of the EBO social-care robot with day center patients in Cáceres, Extremadura, Spain. The study uses systematic video analysis as a method of interaction assessment. This observational pilot study was performed on patients above 65 with mild to moderate cognitive impairment (Minimental State Examination ≥ 21) receiving cognitive therapy at the AZTIDE social and health center. Two individualized 10–15 min sessions, replicating the Wizard of Oz technique, were conducted per participant, with the human operator's commands being unnoticeably executed by the EBO robot. Of the six participants involved, all maintained complete eye contact with the robot, with 83.3 % of the interactions recording maximum attention. Participants felt comfortable and calm, rating conversational factors such as attentiveness and naturalness as 'good' or 'excellent'. The high interaction level with the EBO robot suggests it as a promising tool for cognitive stimulation in patients with mild to moderate cognitive impairment. The systematic video evaluation also appears effective in assessing user–robot interaction, thus underscoring its potential utility in future social robotics research. [ABSTRACT FROM AUTHOR]

Social learning is an evolutionarily important ability increasingly attributed also to invertebrate species. Interfacing robots with animals represents a promising strategy to investigate social learning. Herein, we studied if the gregarious form of Locusta migratoria, a particularly suited model to examine social learning, can use social information provided by robotic demonstrators to optimize their predator avoidance. Robotic demonstrators with different silhouettes and colours (biomimetic or neutral) were used to investigate if their rotation on a rod (e.g. hiding behaviour) elicited the same behaviour in neighbouring locusts. Locusts' responses were affected by different robotic demonstrators, observing a significant impact of the biomimetic silhouette in reducing the latency duration, and in promoting social learning (e.g. locusts displaying hiding behaviour after observing it in robotic demonstrators). A significant impact of colour patterns in triggering socially induced hiding behaviour was also recorded, especially when the biomimetic silhouette was coloured with the gregarious-like pattern. This research indicates gregarious locusts exploit social information in specific ecological contexts, providing basic knowledge on the complex behavioural ecology and social biology in invertebrates. The proposed animal-robot interaction paradigm shows the role of robots as carrier of social information to living organisms, suggesting social biorobotics as advanced and sustainable approach for socio-biology investigation, and environmental management. [ABSTRACT FROM AUTHOR]

As robotic agents become increasingly pervasive in our lives, recent works have shown promising results on the use of emotions on social drones. However, further research is needed to determine the appropriateness of these emotions in various contexts. We here investigate the appropriateness of seven drone emotional states. In a series of six workshops ( N = 30 ) consisting of both individual and group activities, we studied emotion appropriateness for six drone metaphors across the two most popular and radically different domains for Human–Drone Interaction namely: Emergency and Entertainment. Within diverse situations of interactions, participants were able to identify the appropriateness of each emotion. Our results describe how each emotion was found both appropriate and inappropriate depending on context. We provide insights into unique opportunities generated by the perceived emotion appropriateness, depending on different roles of drone emotions in interactions with people. We conclude with design considerations for future social robotic agents, including the importance of using a broad range of emotions, the use of a neutral expression, the temporality of emotions, and novel applications to interaction design. This work contributes to the understanding of the inner workings of emotion appropriateness in drones, providing researchers with a starting point for future work on social flying robots. [ABSTRACT FROM AUTHOR]

This research seeks to identify the factors that affect people's decision to purchase, or to not purchase, social robots for their homes. To this aim, we focus on a specific technological use case: behavior and habit change. As consumer behavior research suggests that preferred designs and price sensitivity will vary between those who are technology early adopters and those who are mainstream adopters, we look at how self-classification influences the aforementioned areas. To this end, we interview 18 individuals to identify behavioral change goals and note reactions to three videos of technology for habit change. In addition to assessing willingness-to-pay (WTP) by using established methods in market research, holistic product design cards are also created to aid this process and to support user design. Additionally, we compare how people's purchase-based designs differ from their ideal designs. We find that although early adopters prefer domestic robots to be human-like in form and behavior, they exhibit significant downgrading, especially to a more device-like form, due to price. Alternatively, we find that those in the mainstream prefer technology that is not human-like in form or behavior, and that privacy concerns and a desire for control have significant impacts on their designs. [ABSTRACT FROM AUTHOR]

Increasingly, roboticists have to pay attention to cultural norms and expectations. But roboticists have generally worked with a relatively narrow understanding of culture, based on nationality. This contrasts with the rich and diverse understandings of culture from disciplines as diverse as sociology, philosophy, and anthropology. Here we draw on the philosophy of science literature on scientific terminology to argue that culture is a conceptually fragmented concept: the concept has no unified definition, and alternative definitions of culture are useful for different areas within robotics. We argue that this has important implications for robotics. We consider two possible reactions to this situation. One claims that, despite the lack of a unified definition, the concept of culture still fulfils useful roles within robotics, and ought to be preserved. The other argues that the problems with the concept are so great that the concept ought to be eliminated from discussions in robotics. We argue in favour of the former option. [ABSTRACT FROM AUTHOR]

One of the most challenging goals in social robotics is implementing emotional skills. Making robots capable of expressing and deciphering emotions is considered crucial for allowing humans to socially interact with them. In addition to presenting technical challenges, the implementation of artificial emotions in artificial systems raises intriguing ethical issues. In this paper, moving from the case study of a human android, we present a relational perspective on human–robot interaction, claiming that, since robots are material objects not endowed with subjectivity, only an asymmetrical relationship can be established between robots and humans. Based on this claim, we deal with some of the most relevant issues in roboethics, such as transparency, trust, and authenticity. We conclude suggesting that a machine-centered approach to ethics should be abandoned in favor of a relational approach, which revalues the centrality of human being in the Human–Robot Interaction. [ABSTRACT FROM AUTHOR]

This article proposes an integrative approach to robotics research, based on bringing interdisciplinarity into the lab. Such an approach will facilitate researchers across various fields in gaining a more nuanced understanding of technology, how it is developed, and its potential impacts. We describe how a philosopher spent time embedded in robotics labs in different European countries as part of an interdisciplinary team, gaining insights into their work and perspectives, including how robotics researchers view ethical issues related to robotics research. Focusing on issues raised by the EU Parliamentary Motion on Robotics, we developed a seminar and questionnaire that investigated questions of ethics, electronic personhood and the role of policy in research ethics. Our findings highlight that while robotics researchers care about the ethical implications of their work and support policy that addresses ethical concerns, they believe there to be significant misunderstandings in how policy makers view robotics and AI, as well as a lack of understanding of, and trust in, the role that experts outside of robotics can play in regulating robotics research effectively. We propose that an integrative approach can break down these misunderstandings by demystifying the way that knowledge is created across different fields. [ABSTRACT FROM AUTHOR]

Social robotic platforms are increasingly entering into human social practices, but to date the question of control and direction of innovation processes surrounding social robotics is still highly debated. In this paper I seek to make a two-fold contribution. Firstly, I critically discuss the "Collingridge Dilemma", also known as the "dilemma of control" in Science and Technologies Studies, and contemporary efforts to address such a dilemma. I demonstrate how such efforts have neglected some wider implications of the dilemma, whose relevance is instead crucial for addressing ethical implications in social robotics. Secondly, to help improve the understanding of control in social robotics, I investigate two guiding principles that have been identified in responsible innovation literature, e.g., inclusion and responsiveness, and I identify potential methods and paradigms to put them into practice. The general aim of this paper is thus to bridge the gap between the theoretical assumptions of responsible innovation and its realisation in practice, as well as to explicitly integrate social robotics with an ethical dimension that can improve the inclusiveness, transdisciplinarity, and social sustainability of this emerging field. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recent works have identified both risks and opportunities afforded by robot gendering. Specifically, robot gendering risks the propagation of harmful gender stereotypes, but may positively influence robot acceptance/impact, and/or actually offer a vehicle with which to educate about and challenge traditional gender stereotypes. Our work sits at the intersection of these ideas, to explore whether robot gendering might impact robot credibility and persuasiveness specifically when that robot is being used to try and dispel gender stereotypes and change interactant attitudes. Whilst we demonstrate no universal impact of robot gendering on first impressions of the robot, we demonstrate complex interactions between robot gendering, interactant gender and observer gender which emerge when the robot engages in challenging gender stereotypes. Combined with previous work, our results paint a mixed picture regarding how best to utilise robot gendering when challenging gender stereotypes this way. Specifically, whilst we find some potential evidence in favour of utilising male presenting robots for maximum impact in this context, we question whether this actually reflects the kind of gender biases we actually set out to challenge with this work. [ABSTRACT FROM AUTHOR]

In the forthcoming decade, interactions between humans and robots are expected to increase gradually. The attitudes that individuals hold towards robots will play a pivotal role in predicting their behavior towards these novel artificial agents, as well as their acceptance across multiple societal pillars. Despite the significant impact of attitudes on the success of human-robot interactions, no existing measure of attitudes towards humanoid robots currently meets the rigorous psychometric standards, particularly in terms of the percentage of variance explained. In this study, we introduce a new measure of attitudes towards robots (ARM), building upon previous scales on the topic, and provide evidence for the scale's internal and external validity. Through three experiments, we selected the most reliable items pertaining to attitudes towards robots (derived from previous attitudes towards robots' questionnaires), identified common factors, and tested the internal and external validity of the newly developed measure. Our findings reveal 15 items, underlying attitudes towards robots, divided into three primary factors: prior anxiety, prior acceptability, and prior anthropomorphism. We report the development and validation of the scale, and discuss the identified dimensions in relation to the literature on human-robot interactions and the psychology of robot perception. [ABSTRACT FROM AUTHOR]

Group identity is important in moral judgments and decisions. People generally favor others who belong to their own group and are more reluctant to report their group members' wrongdoings to authorities. The current research extends this idea to examine the impact of intergroup relationship on moral judgments in the context of human-robot interaction (HRI). Our results showed that although neither group identity (ingroup or outgroup) nor agent type (human or robot) of the wrongdoers influenced the likelihood to report the wrongdoings, attitudes towards the wrongdoer depended on their group identity. The wrongdoers were evaluated more negatively when they were an ingroup instead of an outgroup member, be it human or robot. Moreover, human wrongdoers were ascribed lesser mental capacities than other humans. The current work highlights the interplay of intergroup dynamics and HRI in the moral domain, providing practical implications for building more cooperative human-robot teams. [ABSTRACT FROM AUTHOR]

Imitation is a vital skill that humans leverage in various situations. Humans achieve imitation by observing others with apparent ease. Yet, in reality, it is computationally expensive to model on artificial agents (e.g., social robots) to acquire new skills by imitating an expert agent. Although learning through imitation has been extensively addressed in the robotic literature, most studies focus on answering the following questions: what to imitate and how to imitate. In this conceptual paper, we focus on one of the overlooked questions of imitation through observation: who to imitate. We present possible answers to the who-to-imitate question by exploring motivational factors documented in psychological research and their possible implementation in robotics. To this end, we focus on two critical instances of the who-to-imitate question that guide agents to prioritize one demonstrator over another: outcome expectancies, viewed as the anticipated learning gains, and efficacy expectations, viewed as the anticipated costs of performing actions, respectively. [ABSTRACT FROM AUTHOR]

The creation of lifelike machines involves animation principles as much as technical challenges. Researchers in various fields, including the arts, games, and social robotics, work to create a semblance of life, intelligence, and sensibility in machines. However, attempts to induce this semblance frequently result in unintended, unlifelike, or repulsive characterizations. The contribution of this study is a framework that analyzes, describes, and identifies how various devices, from anthropomorphic robots to household appliances, display lifelike qualities. Based on an extensive examination of lifelike machines in various fields, the authors propose that lifelikeness arises from articulating four expressive elements: body, behavior, setting, and name. This present study shows that components can be mutually supportive or contradictory and have the potential to modify the impression of each other, showing that lifelike qualities in machines rely not on realistic depictions of life but on balancing the unfamiliar and the familiar aspects in the machines. [ABSTRACT FROM AUTHOR]

During the past two decades, robots have been increasingly deployed in games. Researchers use games to better understand human-robot interaction and, in turn, the inclusion of social robots during gameplay creates new opportunities for novel game experiences. The contributions from social robotics and games communities cover a large spectrum of research questions using a wide variety of scenarios. In this article, we present the first comprehensive survey of the deployment of robots in games. We organise our findings according to four dimensions: (1) the societal impact of robots in games, (2) games as a research platform, (3) social interactions in games, and (4) game scenarios and materials. We discuss some significant research achievements and potential research avenues for the gaming and social robotics communities. This article describes the state of the art of the research on robots in games in the hope that it will assist researchers to contextualise their work in the field, to adhere to best practices and to identify future areas of research and multidisciplinary collaboration. [ABSTRACT FROM AUTHOR]

Both designers and users of social robots tend to anthropomorphize robots. Focusing on the question how to conceptualize the relation between robots and humans, this paper first outlines two opposite philosophical views regarding this relation, which are connected to various normative responses to anthropomorphism and anthropomorphization. Then it argues for a third view: navigating between what it calls "naïve instrumentalism" and "uncritical posthumanism", it develops a hermeneutic, relational, and critical approach. Paradoxically, by unpacking the human dimension of robotics in its use and development, this view enables a critical discussion of anthropomorphizing robots. At the same time, and again somewhat paradoxically, it avoids a naïve instrumentalist position by taking robots' role as an instrument in a larger con-technology seriously. As such, the third view questions the dualism assumed in the debate. The paper then explores what this means for the field of social robotics and the education of computer scientists and engineers. It proposes a reform based on a relational understanding of the field itself and offers suggestions for the role of users-citizens. [ABSTRACT FROM AUTHOR]

Hybrid military teams, formed by human warfighters and autonomous artificial agents, represent the technological future of Defence operations. Both the potential and the inherent limitations of current technology are well-known, but the cognitive–behavioral and motivational aspects of human–robot interaction on the battlefield have yet to be systematically investigated. To lay the theoretical and methodological foundation of this scientific investigation, our position paper critically examines how the military personnel's spontaneous tendency to anthropomorphize artificial autonomous agents can affect operations of hybrid military teams in multiple ways. We will argue that the psychological impact of anthropomorphism on military personnel is neither easily avoidable nor necessarily detrimental. Correctly identifying the multi-level cognitive mechanisms that underpin implicit and explicit forms of anthropomorphism allows us to increase the efficacy of human–agent interaction. We will argue that, within hybrid teams, the capability to communicate with teammates, allies, civilians, and adversaries relies on embodied social cognition processes that are inherently geared toward anthropomorphism and leverage its effects. By updating both the design of autonomous artificial agents and the training of human troops to account for these processes, their reciprocal coordination can be augmented. [ABSTRACT FROM AUTHOR]

Multi-robot systems are moving into human spaces, such as working with people in factories (Bacula et al., in: Companion of the 2020 ACM/IEEE international conference on human–robot interaction, pp 119–121, 2020) or in emergency support (Wagner in Front Robot AI 8, 2021; Baxter et al., in: Autonomous robots and agents, Springer, pp 9–16, 2007) and it is crucial to consider how robots can communicate with the humans in the space. Our work evaluates a parameter framework to allow multi-robot groups of x, y, θ robots to effectively communicate using expressive motion. While expressive motion has been extensively studied in single robots (Knight et al., in: 2016 IEEE international conference on intelligent robots and systems (IROS), IEEE, 2016; Bacula and LaViers in Int J Soc Robot, 1–16, 2020; Dragan et al., in: 2013 8th ACM/IEEE international conference on human–robot interaction (HRI), IEEE, pp 301–308, 2013; Kirby et al., in: The 18th IEEE international symposium on robot and human interactive communication, 2009, RO-MAN 2009, IEEE, pp 607–612, 2009), moving to multi-robots creates new challenges as the state space expands and becomes more complex. We evaluate a hierarchical framework of six parameters to generate multi-robot expressive motion consisting of: (1) relative direction, (2) coherence, (3) relative speed, (4) relative start time, (5) proximity, and (6) geometry. We conducted six independent online studies to explore each parameter, finding that four out of six of the parameters had significant impact on people's perception of the multi-robot group. Additional takeaways of our studies clarify what humans interpret as a robot group, when the group is perceived positively versus negatively, and the critical role of architectural floor plan in interpreting robot intent. [ABSTRACT FROM AUTHOR]

In response to theorists of the social-relational turn as a framework for making sense of how humans relate with social robots, I offer an in-depth critique into underlying arguments related to differences in origin as a foundational reason for dismissing posthumanist perspectives in social robotics. In particular, I argue that critical posthumanist sensibilities for social robotics can offer generative accounts for making sense of the relation among, between, and with humans and social robots. Unpacking how arguments separating humans and robots related to origin—genesis—collapse when considering critical posthumanist insights on anthropogenesis, biogenesis, and technogenesis, I explore the value of a critical posthumanist approach in social robotics. A critical posthumanism for social robotics displaces dichotomous nature-culture or natural-artificial binaries and instead embraces an entangled view of relationality. This essay starts to work toward realizing posthumanism's critical sensibilities that take into account the scalar impact of the planetary meta-condition of the Anthropocene on humans, robots, and their relations. [ABSTRACT FROM AUTHOR]

With the development of the economy and the improvement of people's living standard, social robotics gradually enter into daily lives of individuals. Human–robot interaction is the basic function of social robotics, and how to achieve better experience of human–robot interaction is an important issue in the field of social robotics. Single-person pose estimation is the core technology for human–robot interaction in social robots. Benefiting from the development of deep learning, single-person pose estimation has made great progress. This paper reviews the development of single-person pose estimation from four aspects: data augmentation, the evolution of SPPE model, learning target and post-processing. Besides, we give the commonly used datasets and evaluation metrics. Finally, the problems of SPPE are discussed and the future research trends are given. [ABSTRACT FROM AUTHOR]

Robots that are devised for assisting and interacting with humans are becoming fundamental in many applications, including in healthcare, education, and entertainment. For these robots, the capacity to exhibit affective states plays a crucial role in creating emotional bonding with the user. In this work, we present an affective architecture that grounds biological foundations to shape the affective state of the Mini social robot in terms of mood and emotion blending. The affective state depends upon the perception of stimuli in the environment, which influence how the robot behaves and affectively communicates with other peers. According to research in neuroscience, mood typically rules our affective state in the long run, while emotions do it in the short term, although both processes can overlap. Consequently, the model that is presented in this manuscript deals with emotion and mood blending towards expressing the robot's internal state to the users. Thus, the primary novelty of our affective model is the expression of: (i) mood, (ii) punctual emotional reactions to stimuli, and (iii) the decay that mood and emotion undergo with time. The system evaluation explored whether users can correctly perceive the mood and emotions that the robot is expressing. In an online survey, users evaluated the robot's expressions showing different moods and emotions. The results reveal that users could correctly perceive the robot's mood and emotion. However, emotions were more easily recognized, probably because they are more intense affective states and mainly arise as a stimuli reaction. To conclude the manuscript, a case study shows how our model modulates Mini's expressiveness depending on its affective state during a human-robot interaction scenario. [ABSTRACT FROM AUTHOR]

The uncanny valley hypothesis (UVH) suggests that almost, but not fully, humanlike artificial characters elicit a feeling of eeriness or discomfort in observers. This study used Natural Language Processing of YouTube comments to provide ecologically-valid, non-laboratory results about people's emotional reactions toward robots. It contains analyses of 224,544 comments from 1515 videos showing robots from a wide humanlikeness spectrum. The humanlikeness scores were acquired from the Anthropomorphic roBOT database. The analysis showed that people use words related to eeriness to describe very humanlike robots. Humanlikeness was linearly related to both general sentiment and perceptions of eeriness—-more humanlike robots elicit more negative emotions. One of the subscales of humanlikeness, Facial Features, showed a UVH-like relationship with both sentiment and eeriness. The exploratory analysis demonstrated that the most suitable words for measuring the self-reported uncanny valley effect are: 'scary' and 'creepy'. In contrast to theoretical expectations, the results showed that humanlikeness was not related to either pleasantness or attractiveness. Finally, it was also found that the size of robots influences sentiment toward the robots. According to the analysis, the reason behind this is the perception of smaller robots as more playable (as toys), although the prediction that bigger robots would be perceived as more threatening was not supported. [ABSTRACT FROM AUTHOR]

There is a growing body of work reporting on experimental work on social robotics (SR) used for persuasive purposes. We report a comprehensive review on persuasive social robotics research with the aim to better inform their design, by summarizing literature on factors impacting their persuasiveness. From 54 papers, we extracted the SR's design features evaluated in the studies and the evidence of their efficacy. We identified five main categories in the factors that were evaluated: modality, interaction, social character, context and persuasive strategies. Our literature review finds generally consistent effects for factors in modality, interaction and context, whereas more mixed results were shown for social character and persuasive strategies. This review further summarizes findings on interaction effects of multiple factors for the persuasiveness of social robots. Finally, based on the analysis of the papers reviewed, suggestions for factor expression design and evaluation, and the potential for using qualitative methods and more longer-term studies are discussed. [ABSTRACT FROM AUTHOR]

The article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm for Dialogue Management that selects the most appropriate conversation topic depending on the user input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible, the user intention to drive the conversation in specific directions while avoiding purely reactive responses to what the user says. To measure the quality of the conversation, the article reports the tests performed with 100 recruited participants, comparing five conversational agents: (i) an agent addressing dialogue flow management based only on the detection of keywords in the speech, (ii) an agent based both on the detection of keywords and the Content Classification feature of Google Cloud Natural Language, (iii) an agent that picks conversation topics randomly, (iv) a human pretending to be a chatbot, and (v) one of the most famous chatbots worldwide: Replika. The subjective perception of the participants is measured both with the SASSI (Subjective Assessment of Speech System Interfaces) tool, as well as with a custom survey for measuring the subjective perception of coherence. [ABSTRACT FROM AUTHOR]

As the Fourth Industrial Revolution advances, socially-situated robots are increasingly not exclusively human-like (i.e. humanoids). They also include socially interactive animaloids. How does this myriad of socially intelligent artefacts emerge as members of a cyber-physical social system in which they are accorded the standing of social robots? And how are we to account for the nature of the universe-of-meaning that emerges from this human-artificial social reality? Utilizing conceptual tools derived from the philosophical fields of phenomenology and "new materialism", I proffer a theoretic account of robotic sociality. I postulate how robots become members of a cyber-physical social network that is cohabited with sapient humans. Two novel functional constructs are introduced in the process: "the humanoidic" and "the robosphere". The former illuminates that spontaneous bestowal of sociality on robots is tantamount to a recognition of their social agency. I then demonstrate how this psychical process of the recognition of these humanoidic artefacts instantiates an emergence of a shared human–robot cyber-physical world of relational meaning-making, a robosphere. As a corroboration of the self-manifestation of the robosphere as a concrete social system, it is shown that Industry 4.0 adumbrates Society 4.0, a cybernetic social formation, and the envisioned advance of this into the more technocratic super-smart Society 5.0. [ABSTRACT FROM AUTHOR]

Recent research suggests that implicit self-theories—a theory predicated on the idea that people's underlying beliefs about whether self-attributes, such as intelligence, are malleable (incremental theory) or unchangeable (entity theory), can influence people's perceptions of emerging social robots developed for everyday use. Other avenues of research have identified a close link between ability and effort-focused praise and the promotion of individual implicit self-theories. In line with these findings, we posit that implicit self-theories and robot-delivered praise can interactively influence the way people evaluate a social robot, after a challenging task. Specifically, we show empirically that those endorsing more of an entity theory, indicate more favorable responses to a robot that delivers ability praise than to one that delivers effort praise. In addition, we show that those endorsing more of an incremental theory, remain largely unaffected by either praise type, and instead evaluate a robot favorably regardless of the praise it delivers. Together, these findings expand the state-of-the-art, by providing evidence of an interactive match between implicit self-theories and ability, and effort-focused praise in the context of a human-robot interaction. [ABSTRACT FROM AUTHOR]

Social robots have increasingly been entering children's daily lives and their domestic environment. Whereas various studies have shown children's enthusiasm towards social robots in, for example, an educational context, little is known about children's acceptance—or rejection—of domestic social robots. This paper aimed at filling this research gap by developing a model of children's intention to adopt a social robot at home, based on the Theory of Planned Behavior. Relying on data from a survey among 570 children aged eight to nine, we found that, before having ever interacted with the robot in real life, 82% of the children were willing to adopt the robot at home. Children's adoption intention was mainly predicted by hedonic attitudes and social norms, as well as by their general attitude towards robots, which was linked to adoption both directly and indirectly through hedonic attitudes and social norms. Our findings suggest that entertainment-related and normative considerations drive children's intention to adopt a domestic social robot. [ABSTRACT FROM AUTHOR]

The emerging field of social robotics comprises several multidisciplinary applications. Anxiety and stress therapies can greatly benefit by socio-emotional support provided by robots, although the intervention of social robots as effective treatment needs to be fully understood. Herein, Paracheirodon innesi, a social fish species, was used to interact with a robotic fish to understand intrinsic and extrinsic mechanisms causing anxiety, and how social robots can be effectively used as anxiety treatments. In the first experiment we tested the effects of a conspecific-mimicking robot on the fish tendency to swim in the bottom when transferred in a new tank. Here, P. innesi spent a significantly longer time in the upper section of the test tank when the robotic fish was present, clearly indicating a reduction of their state of anxiety due to social stimuli. The second experiment was based on a modification of the dark/light preference test, since many teleost fish are scototactic, preferring dark environments. However, when the robotic fish was placed in the white half of the test tank, P. innesi individuals swam longer in this section otherwise aversive. Social support provided by the robotic fish in both experiments produced a better recovery from anxiety due to social buffering, a phenomenon regulated by specific neural mechanisms. This study provides new insights on the evolution and mechanisms of social buffering to reduce anxiety, as well as on the use of social robots as an alternative to traditional approaches in treating anxiety symptoms. [ABSTRACT FROM AUTHOR]

For some years now, the use of social, anthropomorphic robots in various situations has been on the rise. These are robots developed to interact with humans and are equipped with corresponding extremities. They already support human users in various industries, such as retail, gastronomy, hotels, education and healthcare. During such Human-Robot Interaction (HRI) scenarios, physical touch plays a central role in the various applications of social robots as interactive non-verbal behaviour is a key factor in making the interaction more natural. Shaking hands is a simple, natural interaction used commonly in many social contexts and is seen as a symbol of greeting, farewell and congratulations. In this paper, we take a look at the existing state of Human-Robot Handshaking research, categorise the works based on their focus areas, draw out the major findings of these areas while analysing their pitfalls. We mainly see that some form of synchronisation exists during the different phases of the interaction. In addition to this, we also find that additional factors like gaze, voice facial expressions etc. can affect the perception of a robotic handshake and that internal factors like personality and mood can affect the way in which handshaking behaviours are executed by humans. Based on the findings and insights, we finally discuss possible ways forward for research on such physically interactive behaviours. [ABSTRACT FROM AUTHOR]

With this study we wanted to extend the research on personality traits and the similarity- and complementarity-attraction effects in HRI, and explore which demographic variables might affect them. For that purpose, we conducted a study with 46 participants under a pairwise robot comparison experimental design, combining verbal and non-verbal behaviors, and complementing the results with qualitative data. We found out that the similarity-attraction effect was supported although we could not find any demographic variable to predict it. [ABSTRACT FROM AUTHOR]

The field of human–robot interaction (HRI) is young and highly inter-disciplinary, and the approaches, standards and methods proper to it are still in the process of negotiation. This paper reviews the use of qualitative methods and approaches in the HRI literature in order to contribute to the development of a foundation of approaches and methodologies for these new research areas. In total, 73 papers that use qualitative methods were systematically reviewed. The review reveals that there is widespread use of qualitative methods in HRI, but very different approaches to reporting on it, and high variance in the rigour with which the approaches are applied. We also identify the key qualitative methods used. A major contribution of this paper is a taxonomy categorizing qualitative research in HRI in two dimensions: by 'study type' and based on the specific qualitative method used. [ABSTRACT FROM AUTHOR]

Robots are now operating in workspaces occupied by humans and the robots often need to avoid people while travelling to their desired goal. Humans follow some navigation conventions while walking, called as social cues, like avoiding an oncoming person from the left. It is important for the robots to display the same social cues to be socially accepted by the humans. Current works in social robot motion planning are limited to maintenance of a socially compliant distance. This paper exhibits a socialistic behavior of a robot avoiding an oncoming human by the preferred side. This paper extends the social force model to incorporate the social cues by adding new social forces. The paper also extends the geometric approach to incorporate the social cues by selecting the geometric gap as per the social preference. Finally, we propose a novel hybrid approach combining the social potential field and geometric method, wherein the preferred gap for navigation adds a new social force to the robot. The proposed approach maintains the proactive nature of the geometric approach as well as retains the reactive nature of the social force model. The hybrid method maintains a larger clearance and generates safer trajectories as compared to the baseline social potential field and follow the gap methods. The experiments are done with the Pioneer LX robot using vision cameras and a lidar for navigation operating at the Centre of Intelligent Robotics at IIIT Allahabad. [ABSTRACT FROM AUTHOR]

Robotic agents designed to assist people across a variety of social and service settings are becoming increasingly prevalent across the world. Here we synthesise two decades of empirical evidence from human–robot interaction (HRI) research to focus on cultural influences on expectations towards and responses to social robots, as well as the utility of robots displaying culturally specific social cues for improving human engagement. Findings suggest complex and intricate relationships between culture and human cognition in the context of HRI. The studies reviewed here transcend the often-studied and prototypical east–west dichotomy of cultures, and explore how people's perceptions of robots are informed by their national culture as well as their experiences with robots. Many of the findings presented in this review raise intriguing questions concerning future directions for robotics designers and cultural psychologists, in terms of conceptualising and delivering culturally sensitive robots. We point out that such development is currently limited by heterogenous methods and low statistical power, which contribute to a concerning lack of generalisability. We also propose several avenues through which future work may begin to address these shortcomings. In sum, we highlight the critical role of culture in mediating efforts to develop robots aligned with human users' cultural backgrounds, and argue for further research into the role of culturally-informed robotic development in facilitating human–robot interaction. [ABSTRACT FROM AUTHOR]

This project implements an assistive robotic platform in a mathematics high school class to support the professor's teaching process while analyzing its performance by using a gamification approach and the Octalysis framework. The results obtained from this study evaluated both the platform usability and the general class perception from the students and the professors involved in the experimentation. This paper demonstrates that the implementation of a robotic platform as a supportive tool for the professor improves the class' dynamism and the cooperative behavior of the students, by following the Octalysis approach. Finally, the results helped to determine a better role assignment for future cases where the professor implements a robotic platform during class, leaving the theoretical explanations and class control to the professor, and giving the robot the role of enhancing the activities and review exercises. [ABSTRACT FROM AUTHOR]

The "Computers are social actors" (CASA) assumption (Nass and Moon in J Soc Issues 56:81–103, 2000. https://doi.org/10.1111/0022-4537.00153) states that humans apply social norms and expectations to technical devices. One such norm is to distort one's own response in a socially desirable direction during interviews. However, findings for such an effect are mixed in the literature. Therefore, a new study on the effect of social desirability bias in human–robot evaluation was conducted, aiming for a conceptual replication of previous findings. In a between-subject laboratory experiment, N = 107 participants had to evaluate the robot and the interaction quality after a short conversation in three different groups: In one group, the evaluation was conducted using (1) the same robot of the former interaction, (2) a different robot, (3) a tablet computer. According to the CASA assumption, it was expected, that evaluations on likability and quality of interaction, are higher in the condition with the same robot conducting the evaluation, compared to a different robot or a tablet computer because robots are treated as social actors and hence humans distort ratings in a socially desirable direction. Based on previous findings, we expected robots to evoke higher anthropomorphism and feelings of social presence compared to the tablet computer as potential explanation. However, the data did not support the hypotheses. Low sample size, low statistical power, lack of measurement validation and other problems that could lead to an overestimation of effect sizes—in this study and the literature in general—are discussed in light of the replicability crisis. [ABSTRACT FROM AUTHOR]

The indoor environmental quality (IEQ) monitoring inside buildings where people spend most of their time is essential for ensuring their well-being. Traditional approaches based on Building Automation and Control Systems consider buildings equipped with many different sensors. Unfortunately, the sensors are not always placed for taking the measurements at the right positions. Besides, users could feel a negative perception due to continuous supervision. The present work proposes an approach based on a social humanoid robot that monitors indoor environmental quality. It friendly interacts with occupants providing appropriate suggestions. Particularly, the social robot has been endowed with cognitive capabilities that ground on (i) a proper ontology that formalizes the IEQ domain, (ii) on formal definitions of normative standards based on deontic logic, and (iii) on algorithms for reasoning about the compliance of the environment with the normative standards. The proposed approach has been experimentally verified in some offices of the National Research Council of Italy located in Palermo, and it has involved ten participants. It is worth noting that at the end of the measurement campaign appears that in some cases, compliance with the standard does not imply the user's well-being and vice versa. [ABSTRACT FROM AUTHOR]

A key feature of the humanoid social robot is its face. A robot face is not simply a technical choice, as faces communicate identity, affect and interpersonal spatial relations, and can be key to perceptions about the virtuousness of the robot. To address the significance of the robot face we develop a transdisciplinary reading of faces that compares how science, art and philosophy offer critical knowledges to inform the design of social robotics. Science understands face perception as a physiological, neurological and psychological process that perceives identity, emotion and spatial relations. Art provides a diverse repertoire of stylised faces in visual culture that reiterates the role of likeness, affect and social space. Art presents faces as ethically loaded, such as the war face, the blessed face and the abstracted face. Philosophy proposes the influence of a machine of faciality that abstracts the face as black holes on a white wall, invoking subjectivity and significance. In the second half of the paper we use qualitative visual analysis to develop a classification of robot faces: realistic; symbolic; blank; tech; and screen. We argue that design choice has philosophical, aesthetic and ethical consequences, as people are highly sensitive to the appearance, behaviour and social space of people, robots and their faces. [ABSTRACT FROM AUTHOR]

The unceasing aging of the population is leading to new problems in developed countries. Robots represent an opportunity to extend the period of independent living of the elderly as well as to ameliorate their economic burden and social problems. We present a new social robot, Mini, specifically designed to assist and accompany the elderly in their daily life either at home or in a nursing facility. Based on the results of several meetings with experts in this field, we have built a robot able to provide services in the areas of safety, entertainment, personal assistance and stimulation. Mini supports elders and caregivers in cognitive and mental tasks. We present the robot platform and describe the software architecture, particularly focussing on the human–robot interaction. We give in detail how the robot operates and the interrelation of the different modules of the robot in a real use case. In the last part of the paper, we evaluated how users perceive the robot. Participants reported interesting results in terms of usability, appearance, and satisfaction. This paper describes all aspects of the design and development of a new social robot that can be used by other researchers who face the multiple challenges of creating a new robotic platform for older people. [ABSTRACT FROM AUTHOR]

As the field of social robotics has been dynamically growing and expanding over various areas of research and application, in which robots can be of assistance and companionship for humans, this paper offers a different perspective on a role that social robots can also play, namely the role of informing us about flexibility of human mechanisms of social cognition. The paper focuses on studies in which robots have been used as a new type of "stimuli" in psychological experiments to examine whether similar mechanisms of social cognition would be activated in interaction with a robot, as would be elicited in interaction with another human. Analysing studies in which a direct comparison has been made between a robot and a human agent, the paper examines whether for robot agents, the brain re-uses the same mechanisms that have been developed for interaction with other humans in terms of perception, action representation, attention and higher-order social cognition. Based on this analysis, the paper concludes that the human socio-cognitive mechanisms, in adult brains, are sufficiently flexible to be re-used for robotic agents, at least for those that have some level of resemblance to humans. [ABSTRACT FROM AUTHOR]

This study investigates the level of familiarity and interest of students towards social robotics through a survey conducted with the Electrical Engineering and Computer Science Students at Heriot-Watt University in the UK and Electrical Engineering Students at Xidian University in China. The results indicate that whereas there is no significant difference in the level of familiarity within the three groups of students and no significant difference in the level of interest between the Electrical Engineering and Computer Science Students at Heriot Watt University, there is a statistically significant difference in the level of interest towards social robotics between the Heriot-Watt University and Xidian University Students. Xidian University Students demonstrate a higher level of interest towards social robotics. The qualitative analysis shows that many of the Xidian University Students are willing to perceive and have robots as companions whereas none of the Heriot-Watt University Students show such or similar tendency. This observation indicates that cultural background plays a significant role in interests and preferences of the students towards social robotics. [ABSTRACT FROM AUTHOR]

In recent years there has been an increasing interest in deploying robotic systems in public environments able to effectively interact with people. To properly work in the wild, such systems should be robust and be able to deal with complex and unpredictable events that seldom happen in controlled laboratory conditions. Moreover, having to deal with untrained users adds further complexity to the problem and makes the task of defining effective interactions especially difficult. In this work, a Cognitive System that relies on planning is extended with adaptive capabilities and embedded in a Tiago robot. The result is a system able to help a person to complete a predefined game by offering various degrees of assistance. The robot may decide to change the level of assistance depending on factors such as the state of the game or the user performance at a given time. We conducted two days of experiments during a public fair. We selected random users to interact with the robot and only for one time. We show that, despite the short-term nature of human–robot interactions, the robot can effectively adapt its way of providing help, leading to better user performances as compared to a robot not providing this degree of flexibility. [ABSTRACT FROM AUTHOR]