Showing papers on "Social robot published in 2021"

JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments.

Abstract: We present JRDB, a novel egocentric dataset collected from our social mobile manipulator JackRabbot The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360 RGB video at 15 fps, 3D point clouds from two Velodyne 16 Lidars, line 3D point clouds from two Sick Lidars, audio signal, RGB-D video at 30 fps, 360 spherical image from a fisheye camera and encoder values from the robot's wheels Our dataset incorporates data from traditionally underrepresented scenes such as indoor environments and pedestrian areas, all from the ego-perspective of the robot, both stationary and navigating The dataset has been annotated with over 24 million bounding boxes spread over 5 individual cameras and 18 million associated 3D cuboids around all people in the scenes totaling over 3500 time consistent trajectories Together with our dataset and the annotations, we launch a benchmark and metrics for 2D and 3D person detection and tracking With this dataset, which we plan on extending with further types of annotation in the future, we hope to provide a new source of data and a test-bench for research in the areas of egocentric robot vision, autonomous navigation, and all perceptual tasks around social robotics in human environments

The (fe)male robot – How robot body shape impacts first impressions and trust towards robots

Abstract: Humanlikeness, including robot gender, impacts people’s impression of social robots (Eyssel and Hegel in J Appl Soc Psychol 42(9):2213–2230, 2012) and actual human robot interaction (HRI) (Kuchenbrandt et al. in Int J Soc Robot 6(3):417–427, 2014; Reich-Stiebert and Eyssel in Proceedings of the 2017 ACM/IEEE international conference on human–robot interaction, ACM, pp 166–176, 2017). Although robot gender has been manipulated in various ways in previous research (Alexander et al. in Proceedings of the annual meeting of the Cognitive Science Society, vol 36, 2014; Eyssel and Hegel, 2012), robot body shape as a gender cue has been neglected in this context. Therefore, the current research investigated the effects of manipulating a robot torso’s waist-to-hip ratio and shoulder width on social judgments of a robot. As hypothesized, a robot with a female body shape was perceived as more communal, it was preferred for stereotypically female tasks, and evoked more cognitive and affective trust than a robot with a male body shape. Unexpectedly, both robot types were perceived as equally agentic and they were deemed equally suitable for stereotypically male tasks. Above and beyond, participants’ motivation to respond in a socially desirable manner, their societal beliefs about agentic and communal traits considered appropriate for men and women, sexist attitudes, gender, and technology commitment affected their impression formation about robots. We point to the risks of designing gendered robots and recommend to manipulate robot gender deliberately with regard to the effects this might have on HRI.

Boosting Robot Credibility and Challenging Gender Norms in Responding to Abusive Behaviour: A Case for Feminist Robots

Abstract: Inspired by the recent UNESCO report I'd Blush if I Could, we tackle some of the issues regarding gendered AI through exploring the impact of feminist social robot behaviour on human-robot interaction. Specifically we consider (i) use of a social robot to encourage girls to consider studying robotics (and expression of feminist sentiment in this context), (ii) if/how robots should respond to abusive, and antifeminist sentiment and (iii) how ('female') robots can be designed to challenge current gender-based norms of expected behaviour. We demonstrate that whilst there are complex interactions between robot, user and observer gender, we were able to increase girls' perceptions of robot credibility and reduce gender bias in boys. We suggest our work provides positive evidence for going against current digital assistant/traditional human gender-based norms, and the future role robots might have in reducing our gender biases.

Relationship Development with Humanoid Social Robots: Applying Interpersonal Theories to Human-Robot Interaction.

Abstract: Humanoid social robots (HSRs) are human-made technologies that can take physical or digital form, resemble people in form or behavior to some degree, and are designed to interact with people. A com...

A Taxonomy of Social Errors in Human-Robot Interaction

Abstract: Robotic applications have entered various aspects of our lives, such as health care and educational services. In such Human-robot Interaction (HRI), trust and mutual adaption are established and ma...

What Makes a Robot Social? A Review of Social Robots from Science Fiction to a Home or Hospital Near You

Abstract: We provide an outlook on the definitions, laboratory research, and applications of social robots, with an aim to understand what makes a robot social—in the eyes of science and the general public. Social robots demonstrate their potential when deployed within contexts appropriate to their form and functions. Some examples include companions for the elderly and cognitively impaired individuals, robots within educational settings, and as tools to support cognitive and behavioural change interventions. Science fiction has inspired us to conceive of a future with autonomous robots helping with every aspect of our daily lives, although the robots we are familiar with through film and literature remain a vision of the distant future. While there are still miles to go before robots become a regular feature within our social spaces, rapid progress in social robotics research, aided by the social sciences, is helping to move us closer to this reality.

Social robots on a global stage: establishing a role for culture during human-robot interaction

Abstract: 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.

Robot applications for autism: a comprehensive review.

Abstract: Technological advances in robotics have brought about exciting developments in different areas such as education, training, and therapy. Recent research has suggested that the robot can be even mor...

Survey of Emotions in Human–Robot Interactions: Perspectives from Robotic Psychology on 20 Years of Research

Abstract: Knowledge production within the interdisciplinary field of human–robot interaction (HRI) with social robots has accelerated, despite the continued fragmentation of the research domain. Together, these features make it hard to remain at the forefront of research or assess the collective evidence pertaining to specific areas, such as the role of emotions in HRI. This systematic review of state-of-the-art research into humans’ recognition and responses to artificial emotions of social robots during HRI encompasses the years 2000–2020. In accordance with a stimulus–organism–response framework, the review advances robotic psychology by revealing current knowledge about (1) the generation of artificial robotic emotions (stimulus), (2) human recognition of robotic artificial emotions (organism), and (3) human responses to robotic emotions (response), as well as (4) other contingencies that affect emotions as moderators.

Socially Assistive Robots as Mental Health Interventions for Children: A Scoping Review

Abstract: Socially Assistive Robots are promising in their potential to promote and support mental health in children. There is a growing number of studies investigating the feasibility and effectiveness of robot interventions in supporting children’s mental wellbeing. Although preliminary evidence suggests that Socially Assistive Robots may have the potential to help address concerns such as stress and anxiety in children, there is a need for a greater focus in examining the impact of robotic interventions in this population. In order to better understand the current state of the evidence in this field and identify critical gaps, we carried out a scoping review of the available literature examining how social robots are investigated as means to support mental health in children. We identified existing types of robot intervention and measures that are being used to investigate specific mental health outcomes. Overall, our findings suggest that robot interventions for children may positively impact mental health outcomes such as relief of distress and increase positive affect. Results also show that the strength of evidence needs to be improved to determine what types of robotic interventions could be most effective and readily implemented in pediatric mental health care. Based on our findings, we propose a set of recommendations to guide further research in this area.

We need to talk about deception in social robotics

Abstract: Although some authors claim that deception requires intention, we argue that there can be deception in social robotics, whether or not it is intended. By focusing on the deceived rather than the deceiver, we propose that false beliefs can be created in the absence of intention. Supporting evidence is found in both human and animal examples. Instead of assuming that deception is wrong only when carried out to benefit the deceiver, we propose that deception in social robotics is wrong when it leads to harmful impacts on individuals and society. The appearance and behaviour of a robot can lead to an overestimation of its functionality or to an illusion of sentience or cognition that can promote misplaced trust and inappropriate uses such as care and companionship of the vulnerable. We consider the allocation of responsibility for harmful deception. Finally, we make the suggestion that harmful impacts could be prevented by legislation, and by the development of an assessment framework for sensitive robot applications.

Robot Gaze Can Mediate Participation Imbalance in Groups with Different Skill Levels

Abstract: Many small group activities, like working teams or study groups, have a high dependency on the skill of each group member. Differences in skill level among participants can affect not only the performance of a team but also influence the social interaction of its members. In these circumstances, an active member could balance individual participation without exerting direct pressure on specific members by using indirect means of communication, such as gaze behaviors. Similarly, in this study, we evaluate whether a social robot can balance the level of participation in a language skill-dependent game, played by a native speaker and a second language learner. In a between-subjects study (N = 72), we compared an adaptive robot gaze behavior, that was targeted to increase the level of contribution of the least active player, with a non-adaptive gaze behavior. Our results imply that, while overall levels of speech participation were influenced predominantly by personal traits of the participants, the robot's adaptive gaze behavior could shape the interaction among participants which lead to more even participation during the game.

Understanding Cultural Preferences for Social Robots: A study in German and Arab communities

Abstract: This article presents a study of cultural differences affecting the acceptance and design preferences of social robots. Based on a survey with 794 participants from Germany and the three Arab count...

A Meta-analysis on Children’s Trust in Social Robots

Abstract: Although research on children’s trust in social robots is increasingly growing in popularity, a systematic understanding of the factors which influence children’s trust in robots is lacking. In addition, meta-analyses in child–robot-interaction (cHRI) have yet to be popularly adopted as a method for synthesising results. We therefore conducted a meta-analysis aimed at identifying factors influencing children’s trust in robots. We constructed four meta-analytic models based on 20 identified studies, drawn from an initial pool of 414 papers, as a means of investigating the effect of robot embodiment and behaviour on both social and competency trust. Children’s pro-social attitudes towards social robots were also explored. There was tentative evidence to suggest that more human-like attributes lead to less competency trust in robots. In addition, we found a trend towards the type of measure that was used (subjective or objective) influencing the direction of effects for social trust. The meta-analysis also revealed a tendency towards under-powered designs, as well as variation in the methods and measures used to define trust. Nonetheless, we demonstrate that it is still possible to perform rigorous analyses despite these challenges. We also provide concrete methodological recommendations for future research, such as simplifying experimental designs, conducting a priori power analyses and clearer statistical reporting.

Exploring the perceptions of people with dementia about the social robot PARO in a hospital setting.

Abstract: New technology, such as social robots, opens up new opportunities in hospital settings. PARO, a robotic pet seal, was designed to provide emotional and social support for older people with dementia. We applied video-ethnographic methods, including conversational interviews and observations with video recording among 10 patient participants while they were using the robot. We also conducted semi-structured individual interviews and focus groups with nursing staff to gain contextual information. Patient and family partners were actively involved in the study as co-researchers. This study reports our findings on the perceptions of 10 patients with dementia about their experiences with PARO in a hospital setting. Thematic analysis yielded three substantive themes: (a) 'it's like a buddy' - the robot helps people with dementia uphold a sense of self in the world, (b) 'it's a conversation piece' - the baby seal facilitates social connection and (c) 'it makes me happy' - PARO transforms and humanizes the clinical setting. Our findings help provide a better understanding of the perspectives of patients with dementia on the use of social robots.

Human-human-robot interaction: robotic object’s responsive gestures improve interpersonal evaluation in human interaction

Abstract: Robots designed for social interaction are predicted to be employed in a wide range of environments including homes, schools, and workplaces (Bartneck & Forlizzi, 2004; Fong, Nourbakhsh, & Dautenha...

Socially Compliant Robot Navigation in Crowded Environment by Human Behavior Resemblance Using Deep Reinforcement Learning

Abstract: Social robots have evolved in diverse applications with the emergence of deep reinforcement learning methods. However, safe and secure navigation of social robots in a complex crowded environment remains a challenging task. The robot can safely navigate in a crowd only if it can predict the next action of humans, however this task becomes difficult because of the unpredictable human behavior. To address the issue of socially compliant navigation, the robot needs to learn real-time human behavior. This manuscript models Danger-Zone for the robot by considering all possible actions that humans can take at given time. The Danger Zones are formulated by considering the real time human behavior. The robot is trained to avoid these danger zones for safe and secure navigation. The proposed model is tested on the three state of art methods, Collision Avoidance with Deep Reinforcement Learning (CADRL), Long Short Term Memory Reinforcement Learning (LSTM-RL) and Social Attention with Reinforcement Learning (SARL) in multi-agent navigation. Experimental results signify that proposed model can understand human behavior and navigate in a socially compliant manner with safety as the highest priority.

The political choreography of the Sophia robot: beyond robot rights and citizenship to political performances for the social robotics market

Abstract: A humanoid robot named ‘Sophia’ has sparked controversy since it has been given citizenship and has done media performances all over the world. The company that made the robot, Hanson Robotics, has touted Sophia as the future of artificial intelligence (AI). Robot scientists and philosophers have been more pessimistic about its capabilities, describing Sophia as a sophisticated puppet or chatbot. Looking behind the rhetoric about Sophia’s citizenship and intelligence and going beyond recent discussions on the moral status or legal personhood of AI robots, we analyse the performativity of Sophia from the perspective of what we call ‘political choreography’: drawing on phenomenological approaches to performance-oriented philosophy of technology. This paper proposes to interpret and discuss the world tour of Sophia as a political choreography that boosts the rise of the social robot market, rather than a statement about robot citizenship or artificial intelligence. We argue that the media performances of the Sophia robot were choreographed to advance specific political interests. We illustrate our philosophical discussion with media material of the Sophia performance, which helps us to explore the mechanisms through which the media spectacle functions hand in hand with advancing the economic interests of technology industries and their governmental promotors. Using a phenomenological approach and attending to the movement of robots, we also criticize the notion of ‘embodied intelligence’ used in the context of social robotics and AI. In this way, we put the discussions about the robot’s rights or citizenship in the context of AI politics and economics.

Towards a Modular and Distributed End-User Development Framework for Human-Robot Interaction

Abstract: In an effort towards the democratization of Robotics, this article presents a novel End-User Development framework called Robot Interfaces From Zero Experience (RIZE). The framework provides a set of useful software tools for the creation of robot-oriented software architectures and programming interfaces, as well as the modeling and execution of robot behaviors, with a specific emphasis on social behaviors. Programming interfaces built on top of RIZE enable professionals with different backgrounds and interests to design, adapt, and scale-up robotics applications. As an example of a programming interface, we present Open RIZE, which exploits an End-User Programming paradigm combining blocks, tables, and forms-filling interfaces. Unlike previous approaches, robot behavioral code generated by Open RIZE is intrinsically modular, re-usable, scalable, neutral to the employed programming language, and platform-agnostic. In the article, we present the main design guidelines and features of Open RIZE. Additionally, we perform an initial usability evaluation of the Open RIZE interface in an online workshop. Preliminary results using the System Usability Scale with 10 novice end-users indicate that Open RIZE is easy-to-use and learn.

Robot Interaction Styles for Conversation Practice in Second Language Learning

Abstract: Four different interaction styles for the social robot Furhat acting as a host in spoken conversation practice with two simultaneous language learners have been developed, based on interaction styles of human moderators of language cafes. We first investigated, through a survey and recorded sessions of three-party language cafe style conversations, how the interaction styles of human moderators are influenced by different factors (e.g., the participants language level and familiarity). Using this knowledge, four distinct interaction styles were developed for the robot: sequentially asking one participant questions at the time (Interviewer); the robot speaking about itself, robots and Sweden or asking quiz questions about Sweden (Narrator); attempting to make the participants talk with each other (Facilitator); and trying to establish a three-party robot–learner–learner interaction with equal participation (Interlocutor). A user study with 32 participants, conversing in pairs with the robot, was carried out to investigate how the post-session ratings of the robot’s behavior along different dimensions (e.g., the robot’s conversational skills and friendliness, the value of practice) are influenced by the robot’s interaction style and participant variables (e.g., level in the target language, gender, origin). The general findings were that Interviewer received the highest mean rating, but that different factors influenced the ratings substantially, indicating that the preference of individual participants needs to be anticipated in order to improve learner satisfaction with the practice. We conclude with a list of recommendations for robot-hosted conversation practice in a second language.

Reinforcement Learning Approaches in Social Robotics

Abstract: This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which an agent interacts through trial-and-error with its environment to discover an optimal behavior. Since interaction is a key component in both reinforcement learning and social robotics, it can be a well-suited approach for real-world interactions with physically embodied social robots. The scope of the paper is focused particularly on studies that include social physical robots and real-world human-robot interactions with users. We present a thorough analysis of reinforcement learning approaches in social robotics. In addition to a survey, we categorize existent reinforcement learning approaches based on the used method and the design of the reward mechanisms. Moreover, since communication capability is a prominent feature of social robots, we discuss and group the papers based on the communication medium used for reward formulation. Considering the importance of designing the reward function, we also provide a categorization of the papers based on the nature of the reward. This categorization includes three major themes: interactive reinforcement learning, intrinsically motivated methods, and task performance-driven methods. The benefits and challenges of reinforcement learning in social robotics, evaluation methods of the papers regarding whether or not they use subjective and algorithmic measures, a discussion in the view of real-world reinforcement learning challenges and proposed solutions, the points that remain to be explored, including the approaches that have thus far received less attention is also given in the paper. Thus, this paper aims to become a starting point for researchers interested in using and applying reinforcement learning methods in this particular research field.