From complexity to commercial readiness: industry insights on bridging gaps in human-robot interaction and social robot navigation

SummarySocial robots that can interact and communicate with people are growing in popularity for use at home and in customer-service, education, and healthcare settings. Although growing evidence suggests that co-operative and emotionally aligned social robots could benefit users across the lifespan, controversy continues about the ethical implications of these devices and their potential harms. In this perspective, we explore this balance between benefit and risk through the lens of human-robot relationships. We review the definitions and purposes of social robots, explore their philosophical and psychological status, and relate research on human-human and human-animal relationships to the emerging literature on human-robot relationships. Advocating a relational rather than essentialist view, we consider the balance of benefits and harms that can arise from different types of relationship with social robots and conclude by considering the role of researchers in understanding the ethical and societal impacts of social robotics.

There is an actual trend for humanizing technological artifacts, especially social robots. However, human‐like social robots trigger negative attitudes by threatening human uniqueness as well as humanness. The present paper presents the development of the Belief in Human Nature Uniqueness Scale (BHNUS) to assess the individual tendency to deny social robots the possibility to have human features considered to be the hallmarks of humanness. The validation of the BHNUS was completed along seven studies, with a total of 1044 Portuguese participants. Results showed that BHNUS had good structural qualities (Studies 1 and 2), as well as good convergent and discriminant validities. BHNUS was correlated with negative attitudes towards robots, religiosity, and interest for science fiction (Study 3), attribution of traits of warmth to robots (Study 4), positive and negative emotional appraisal (Study 5), perspective taking (Study 6), and attitudes towards the development of robots with human features (Study 7). The importance of the BHNUS regarding the development of social robots and human–robot interaction is discussed.If you were to insist I was a robot, you might not consider me capable of love in some mystic human sense, but you would not be able to distinguish my reactions from that which you would call love so what difference would it make?Isaac Asimov (1982) in Foundation’s Edge, p. 420

Robots have been gradually leaving laboratory and factory environments and moving into human populated environments. Various social robots have been developed with the ability to exhibit social behaviors and collaborate with non-expert users in different situations. In order to increase the degree of collaboration between humans and the robots in human–robot joint action systems, these robots need to achieve higher levels of interaction with humans. However, many social robots are operated under teleoperation modes or pre-programmed scenarios. Based on homeostatic drive theory, this paper presents the development of a novel collaborative behavior controller for social robots to jointly perform tasks with users in human–robot interaction (HRI) experiments. Manual work during the experiments is reduced, and the experimenters can focus more on the interaction. We propose a hybrid concept for the behavior decision-making process, which combines the hierarchical approach and parallel-rooted, ordered, slip-stack hierarchical architecture. Emotions are associated with behaviors by using the two-dimensional space model of valence and arousal. We validate the usage of the behavior controller by a joint attention HRI scenario in which the NAO robot and a therapist jointly interact with children.

Social robots are increasingly used within public spaces, including museum settings. This quasi-systematic review identifies and synthesizes the evidence on social robots that have recently been deployed in museum settings. It specifically focuses on their intended purpose, their acceptability and factors important for successful human–robot interaction in this setting. Four databases (PsycINFO, SCOPUS, ACM Digital Library and IEEE Xplore) were systematically searched to retrieve literature published within the last 10 years on human–robot interaction studies with social robots deployed in museum settings. Due to the heterogeneous nature of the studies, qualitative and quantitative findings were summarized. A total of 604 items were identified, of which 12 were included in the review. Robots in 11 studies were physical and 1 was an embodied conversational agent presented as a virtual robot. In 75% of the studies ( n = 9), the purpose of the robots was to act as museum guides, while in 17% ( n = 2) they entertained visitors and in 8% ( n = 1) the robot taught visitors in a museum outreach programme. Overall, many of the robots were found to be acceptable for use within museum settings. Three main themes for successful social human–robot interaction were evident across the findings: (1) facial expressions, (2) movement and (3) communication and speech. There is a great opportunity for social robots to be deployed within museum settings, as guides, educators, entertainers or a combination thereof. State-of-the-art methods have led to the development of museum robots that are more capable of social interaction; however, more work is required to develop speech capabilities that work in the ‘wild’. Future work should combine the factors that have been identified within this review to improve human–robot interaction.

Perceived robot personality affects social attention in real-time human-robot interaction

Consumer acceptance of social robots in domestic settings: A human-robot interaction perspective

Chapter 10 - Computational Analysis of Affect, Personality, and Engagement in Human–Robot Interactions

Creativity is a complex human process evaluated through psychometric tasks, mostly in relation to divergent thinking (DT) or the capacity to generate new ideas. In social robotics, creativity has been supported in different interactions with social robots, in which the Human Robot Interaction (HRI) supports the participants’ creativity. However, as scores are typically used for such evaluations, they struggle to capture the inherent creative process involved in a task. In this paper, we focus on creative problem solving in Human Robot Interaction considering the edit distance by analyzing the evolution of the different configurations of a set of modular robotic cubes during the task resolution. For this objective, we consider the three DT components of fluidity, flexibility, and innovation as evaluated in the Alternate Use Test task. We then operationalize the edit distance (ED), usually used for quantifying the minimum number of operations required to transform one configuration into another. ED is a way to compute the differences between two intermediate creative solutions. We engaged 224 participants in playing the CreaCube task, and then we analyzed the videos for identifying in time each of the configurations. The results allow us to maintain the hypothesis related to the DT components in relation to ED and discuss the implications of this study in social robotics.

A wearable sensor vest for social humanoid robots with GPGPU, IoT, and modular software architecture

Soon service robots will be employed in public spaces with frequent human-robot interaction (HRI). To achieve a safe, trustworthy and acceptable HRI, service robots need to be equipped with interaction strategies suitable for the robot, user, and context. To gain realistic insights into the initial user reactions and challenges that arise when a mechanoid, autonomous service robot in public is applied, a field study with three data sources was conducted. In a first step, lay users’ intuitive reactions to a cleaning robot at a train station were observed (N = 344). Second, passersby’s preferences for HRI interaction strategies were explored in interviews (n = 54). As a third step, trust and acceptance of the robot were assessed with questionnaires (n = 32). Identified challenges were social robot navigation in crowded places also applicable to vulnerable passersby, inclusive communication modalities, information of staff and public about the service robot application and the need for conflict resolution strategies to avoid an inefficient robot (e.g., testing behavior, path is blocked). This study provides insights into naive HRI in public and illustrates challenges, provides recommendations supported by literature and highlights aspects for future research to inspire a research agenda in the field of public HRI.

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

With the growth in the number of market-available social robots, there is an increasing interest in research on the usage of social robots in education. This paper proposes a summary of trends highlighting current research directions and potential research gaps for social robots in education. We are interested in design aspects and instructional setups used to evaluate social robotics system in an educational setting. The literature demonstrates that as the field grows, setup, methodology, and demographics targeted by social robotics applications seem to settle and standardize—a tutoring Nao robot with a tablet in front of a child seems the stereotypical social educational robotics setup. An updated review on social robots in education is presented here. We propose, first, an analysis of the pioneering works in the field. Secondly, we explore the potential for education to be the ideal context to investigate central human-robot interaction research questions. A trend analysis is then proposed demonstrating the potential for educational context to nest impactful research from human-robot interaction.

Nowadays it is widely accepted that information and communication technologies can open up new lines of support and enrich later life. But what about robots? In 1985, the book A Robot in Every Home by Mike Higgins was published. It provided an overview of the available first-generation personal robots such as Topo, Hero 1, RB5X, Hubot, Hero Jr., Turtle Tot, FED, Dingbot, Verbot, and Omnibot. Although they were restricted in use, Higgins took up the issue of whether “robots can be companions” and forecasted that pet robots would in the future provide companionship – without the constraints of a living animal or a human being. Robots may be suitable for people with all kinds of restrictions and disabilities (e.g., dementia): They never get tired, they never complain, they are “patient,” and they never take personal offense. In the meantime, these ideas have found their way into reality. For about 15 years, Paro, a cuddly therapeutic seal, has been tested in different pilot projects around the world and is now available internationally. Paro was designed for therapeutic purposes and is a good example of a social and emotional robot, defined as a technical system able to interact with human beings in such a way that these interactions can be regarded as “emotional.” Its main purpose is to be a companion, of course, though not exclusively, for people with cognitive impairments. Personal and service robotics is advancing quickly, and a variety of prototypes have already been tested in real-life settings. The abilities of these robots are far beyond those of Paro. Both types of robot have in common that people tend to deal with them as if they are real living “subjects.” On the other hand, these developments raise concerns and issues that need to be discussed from a scientific perspective. What empirical evidence is available that social and emotional robots do in fact enrich or facilitate daily life, as measured in terms of an outcome related to aging well, such as communication, social exchange, independence, or well-being? Is it ethical to use robots in the provision of care for the elderly? Do these devices really contribute to better care? Can they be regarded as providing a therapeutic intervention? Will they replace professional staff? What outcomes have been postulated, and how can the effects be measured? What will happen to caring processes and society if human interaction is replaced by human-robot interaction? These questions should be dealt with as soon as possible, particularly in view of today’s international discussions: China, for example, expects every second household to be equipped with social robots in the very near future (see the discussion at the International Conference of Social Robotics ICSR 2012 in Chengdu, China; Chen, 2012). The debate is necessary in order to participate in and shape robotic developments and their fields of application – especially when these are vulnerable groups. The present issue of GeroPsych sheds some light on these topics by giving an overview of ongoing research and discussions on emotional and social robotics. The first contribution on evidence and deploymentbased research into care for the elderly using socially assistive robots by Thorsten Kolling and colleagues presents a review of evaluation studies on Paro as well as an insight into their shortcomings, and develops ideas to overcome these. The experiences gathered to date with Paro as a therapeutic robot in nursing care homes in Denmark, Germany, and the UK are highlighted in the contribution of Barbara Klein and colleagues. Unlike Paro, Care-O-Bot looks like a robot and has many more functions and capabilities. Patrizia Marti and Jelle Stienstra have studied the extent to which interaction with this robot companion helps elderly people to live independently in their homes in Italy. The difficulties of developing an adequate research design for robot interventions in care homes specialized in psychogeriatric care are reflected in the contribution of Roger Bemelmans and colleagues. Dealing with robots evokes many ethical concerns, which are systematically analyzed in the contribution by Catrin Misselhorn and colleagues. GeroPsych, 26 (2), 2013, 81–82

A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation . While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algorithms that tackle social navigation remains hard because it involves not just robotic agents moving in static environments but also dynamic human agents and their perceptions of the appropriateness of robot behavior. In contrast, clear, repeatable, and accessible benchmarks have accelerated progress in fields like computer vision, natural language processing and traditional robot navigation by enabling researchers to fairly compare algorithms, revealing limitations of existing solutions and illuminating promising new directions. We believe the same approach can benefit social navigation. In this article, we pave the road toward common, widely accessible, and repeatable benchmarking criteria to evaluate social robot navigation. Our contributions include (a) a definition of a socially navigating robot as one that respects the principles of safety, comfort, legibility, politeness, social competency, agent understanding, proactivity, and responsiveness to context, (b) guidelines for the use of metrics, development of scenarios, benchmarks, datasets, and simulators to evaluate social navigation, and (c) a design of a social navigation metrics framework to make it easier to compare results from different simulators, robots, and datasets.

The detailed description of behaviour of the interacting parties is becoming more and more important in human-robot interaction (HRI), especially in social robotics (SR). With the rise in the number of publications, there is a substantial need for the objective and comprehensive description of implemented robot behaviours to ensure comparability and reproducibility of the studies. Ethograms and the meticulous analysis of behaviour was introduced long ago in animal behaviour research (cf. ethology). The adoption of this method in SR and HRI can ensure the desired clarity over robot behaviours, while also providing added benefits during robot development, behaviour modelling and analysis of HRI experiments. We provide an overview of the possible uses and advantages of ethograms in HRI, and propose a general framework for describing behaviour which can be adapted to the requirements of specific studies.