Reframing HRI Design Opportunities for Social Robots: Lessons Learnt from a Service Robotics Case Study Approach Using UX for HRI

Research Hotspots and Trends of Social Robot Interaction Design: A Bibliometric Analysis

(1) Background: Social robot interaction design is crucial for determining user acceptance and experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a bibliometric perspective. Therefore, we conducted this study in order to identify the latest research progress and evolution trajectory of research hotspots in social robot interaction design over the last decade. (2) Methods: We conducted a comprehensive review based on 2416 papers related to social robot interaction design obtained from the Web of Science (WOS) database. Our review utilized bibliometric techniques and integrated VOSviewer and CiteSpace to construct a knowledge map. (3) Conclusions: The current research hotspots of social robot interaction design mainly focus on #1 the study of human-robot relationships in social robots, #2 research on the emotional design of social robots, #3 research on social robots for children's psychotherapy, #4 research on companion robots for elderly rehabilitation, and #5 research on educational social robots. The reference co-citation analysis identifies the classic literature that forms the basis of the current research, which provides theoretical guidance and methods for the current research. Finally, we discuss several future research directions and challenges in this field.

A biologically inspired decision-making system for the autonomous adaptive behavior of social robots

The decisions made by social robots while they fulfill their tasks have a strong influence on their performance. In these contexts, autonomous social robots must exhibit adaptive and social-based behavior to make appropriate decisions and operate correctly in complex and dynamic scenarios. This paper presents a Decision-Making System for social robots working on long-term interactions like cognitive stimulation or entertainment. The Decision-making System employs the robot's sensors, user information, and a biologically inspired module to replicate how human behavior emerges in the robot. Besides, the system personalizes the interaction to maintain the users' engagement while adapting to their features and preferences, overcoming possible interaction limitations. The system evaluation was in terms of usability, performance metrics, and user perceptions. We used the Mini social robot as the device where we integrated the architecture and carried out the experimentation. The usability evaluation consisted of 30 participants interacting with the autonomous robot in 30 min sessions. Then, 19 participants evaluated their perceptions of robot attributes of the Godspeed questionnaire by playing with the robot in 30 min sessions. The participants rated the Decision-making System with excellent usability (81.08 out of 100 points), perceiving the robot as intelligent (4.28 out of 5), animated (4.07 out of 5), and likable (4.16 out of 5). However, they also rated Mini as unsafe (security perceived as 3.15 out of 5), probably because users could not influence the robot's decisions.

Should my robot know what's best for me? Human–robot interaction between user experience and ethical design

To integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles.

Effects of Social Robotics in Promoting Physical Activity in the Shared Workspace

This paper presents a design study exploring the effects of a social robot in facilitating people to participate in light-intensity exercises after a long duration of sitting in a shared workspace. A smart system based on a trolley-like robot, called the Anti-Sedentary Robot, was developed to realize the health intervention as follows. To start, the robot could navigate to the location of a sedentary worker to invite them to participate in a temporal voluntary service of returning items. Upon the invitation being accepted, the robot would then move with the worker to return the item and simultaneously provide guidance for physical exercises. Based on the Anti-Sedentary Robot, a within-subject study (n = 18) was carried out to examine exercise motivations and psychological benefits of our design by making comparisons between a robot-guided intervention and a human-guided intervention. Quantitative results showed that the health intervention based on the Anti-Sedentary Robot increased intrinsic motivations and provided acute mental benefits compared to the human-guided intervention. Qualitative findings suggested that the Anti-sedentary Robot could combat work-related sedentary behaviors due to the pleasant system interactivity and the provision of reciprocal voluntary tasks. We discuss implications for the future development of social robots for office vitality based on our research findings.

A Systematic Review for Service Humanoid Robotics Model in Hospitality

Nowadays, the Fourth Industrial Revolution has brought artificial intelligence to the forefront, and more and more intelligent robots begin to be used in the hospitality industry. In this study, the application of service humanoid robots in the hospitality industry is investigated based on Cardiff Metropolitan University EUREKA Robotics Lab’s robot as reported by Lab (in Eureka robotics lab, 2017, https://www.cardiffmet.ac.uk/technologies/Pages/EUREKA-Robotics-Lab.aspx). The research ontology of this study is post-positivism. The research philosophy of this research is phenomenology. Phenomenological studies have indicated that this phenomenon can only be truly understood and experienced through subjective immersive research directly involving researchers, and the interaction among researchers is an integral part of the research. In this study, the data are collated through case researches and experimental interviews. Finally, Some proposals for transforming the traditional hospitality industry into the direction of intelligence is summarized. In future research, a technical model combining artificial intelligence will be further developed.

The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot Interaction

The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutual understanding of each other’s actions and intentions. In this paper, we motivate and present a systematic user experience (UX) evaluation framework of action and intention recognition between humans and robots from a UX perspective, because there is an identified lack of this kind of evaluation methodology. The evaluation framework is packaged into a methodological approach called ANEMONE (action and intention recognition in human robot interaction). ANEMONE has its foundation in cultural-historical activity theory (AT) as the theoretical lens, the seven stages of action model, and user experience (UX) evaluation methodology, which together are useful in motivating and framing the work presented in this paper. The proposed methodological approach of ANEMONE provides guidance on how to measure, assess, and evaluate the mutual recognition of actions and intentions between humans and robots for investigators of UX evaluation. The paper ends with a discussion, addresses future work, and some concluding remarks.

A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots

As social robots become more common, there is a need to understand how people perceive and interact with such technology. This systematic review seeks to estimate people’s attitudes toward, trust in, anxiety associated with, and acceptance of social robots; as well as factors that are associated with these beliefs. Ninety-seven studies were identified with a combined sample of over 13,000 participants and a standardized score was computed for each in order to represent the valence (positive, negative, or neutral) and magnitude (on a scale from 1 to − 1) of people’s beliefs about robots. Potential moderating factors such as the robots’ domain of application and design, the type of exposure to the robot, and the characteristics of potential users were also investigated. The findings suggest that people generally have positive attitudes towards social robots and are willing to interact with them. This finding may challenge some of the existing doubt surrounding the adoption of robotics in social domains of application but more research is needed to fully understand the factors that influence attitudes.