Multidisciplinary Design Approach for Implementation of Interactive Services

Human robot interaction (HRI) is core to the design of service robots. The interaction during a service application determines how a user perceives the robot, which affects the user's experience and how well the user accepts the robot and its services. During the last decade, robotics service applications in close proximity to human users have been a popular research area. Research in related fields such as computer vision has also made significant advances to make available many interaction algorithms for HRI. However, we argue that there is only minimum utilization of these algorithms in the construction of HRI needed in actual service robots, despite their availability. This is partly because these algorithms have inherent limitations and only solve some of the HRI issues required in a complete service scenario in real environments. In this paper, a new general design approach is proposed to utilize modeling languages UML and UMLi to describe a service scenario and model the HRI required in a complete service. These models can be further used to elicit sometimes hidden HRI requirements from limitations in the interaction algorithms used. This approach helps multidisciplinary research to make HRI design decisions early at the design stage and guide implementation by software engineers. A user identification service scenario was designed, implemented and used as the case study of this design approach. It was integrated with a medication reminder application on a robot which was deployed and evaluated with the older people in a retirement village in New Zealand.

PurposeThe purpose of this study is to empirically investigate what aspects of service robot interactions with customers can lead to meaningful outcomes in the view of customers. The study examines functional and emotional elements of AI service robots in terms of meaningful outcomes.Design/methodology/approachThis study highlights AI service robots' meaningful outcomes as a viable research problem and proposes a research model utilizing the Stimulus-Organism-Response (SOR) framework. As an empirical approach, 260 datasets were collected from customers who have experience with AI service restaurants in China.FindingsThe study examines the functional and emotional elements of AI-powered service robots on the attitude of and meaningful outcomes for customers. The results showed that the emotional (perceived friendliness and perceived coolness) and functional (perceived safety and robot competence) attributes of human–robot interactions (HRI) significantly affect the attitude toward using service robots. Second, the attitude toward using service robots significantly influences the experiential outcome and instrumental outcome of meaningful engagement.Research limitations/implicationsThis study highlights two elements (i.e. functional and emotional) of HRI effectiveness using two metrics: experiential and performance outcomes. Future studies should generalize the research findings of service robots in the current study using a larger quantity of data from various service fields.Originality/valueAs the first empirical study highlighting the customer experience with service robots, this study opens up a feasible research direction for the service industry to pursue in terms of conducting HRI studies from the view of customers. It identifies a research model pursuant to customers' experience with HRI in creating meaningful outcomes and it theoretically extends the SOR model to the hospitality study, focusing on the HRI issue.

Purpose The adoption of service robots in the hospitality and tourism industries has transformed service encounters into human–robot interactions. This study aims to investigate whether service providers can benefit from increasing recovery effort when service robots are involved. Design/methodology/approach Drawing on the theory of mind perception, the study employed field and online experiments to examine the effects of robotic service recovery strategies on customer forgiveness and satisfaction. This mixed-methods approach ensures robust and ecologically valid findings. Findings The results reveal that higher recovery effort by a service robot positively influences customer forgiveness, which in turn increases customer satisfaction. Interestingly, when customers attribute less blame to the robot and perceive stronger rapport with it, increasing recovery effort does not yield additional positive effects. Practical implications This study offers practical guidance for restaurant managers on managing robotic service failures and improving the effectiveness of recovery efforts and outcomes. Originality/value This research offers novel insights into the dynamics of service recovery in human–robot interactions. It demonstrates that service robots can foster customer forgiveness through cost-effective recovery strategies, offering both theoretical and practical implications for the restaurant industry. Also, the findings advance our understanding of how mind perception attribution shapes robotic service recovery outcomes and provide actionable guidance for optimizing service robot recovery strategies in real-world contexts.

This paper presents the design of a tele-operated service robot to assist in high-pressure cleaning tasks. The robot consists in a mobile base with three wheels and a pan-tilt system sited over the mobile base. A water-jet gun is mounted on the pan-tilt system as End-Effector (EE). The robot is remotely manipulated through a PC gamepad. A static analysis is carried out to analyse the repulsion and reaction forces of waterjet. A prototype is manufactured from a proposed conceptual design. Preliminary experimental tests are carried out to demonstrate the capabilities and effectiveness of the robot during a simulated cleaning task.KeywordsService robotMobile basePan-tiltCleaningHigh-pressureStatic analysis

This study presents a literature review focused on nonverbal communication in human-robot interaction (HRI) that involves service robots with social capabilities. We aim to list the types of robots used and nonverbal communication cues examined in the reviewed studies; and the main research objectives, participant characteristics, data collection methods, and primary findings of these studies. To achieve this, we used the databases of WoS, Scopus and EBSCO to conduct a literature review on utilization of nonverbal cues by both humans and robots during HRI. The results obtained from 39 relevant open access academic papers published from 2006 to 2023 suggest that enhancing the quality of communication between humans and service robots must be improved, while there are several aspects that require more thorough exploring, needed to strengthen robot self-efficacy, trust and trustworthiness in HRI or overcome cultural differences. The results emphasize the importance of nonverbal communication in shaping the dynamics of interactions between humans and service robots.

This study presents a literature review focused on nonverbal communication in human-robot interaction (HRI) that involves service robots with social capabilities. We aim to list the types of robots used and nonverbal communication cues examined in the reviewed studies; and the main research objectives, participant characteristics, data collection methods, and primary findings of these studies. To achieve this, we conducted a literature review of 39 relevant open access academic papers published from 2006 to 2023 that examined the utilization of nonverbal cues by both humans and robots during HRI. The results suggest that enhancing the quality of communication between humans and service robots must be improved, while there are several aspects that require more thorough exploring, needed to strengthen robot self-efficacy, trust and trustworthiness in HRI or overcome cultural differences. The results emphasize the importance of nonverbal communication in shaping the dynamics of interactions between humans and service robots.

Mobile robots are already applied in factories and hospitals, merely to do a distinct task. It is envisioned that robots assist in households soon. Those service robots will have to cope with several situations and tasks and of course with sophisticated human-robot interactions (HRI). Therefore, a robot has not only to consider social rules with respect to proxemics, it must detect in which (interaction) situation it is in and act accordingly. With respect to spatial HRI, we concentrate on the use of non-verbal communication. This chapter stresses the meaning of both, machine movements as signals towards a human and human body language. Considering these aspects will make interaction simpler and smoother. An observational study is presented to acquire a concept of spatial prompting by a robot and by a human. When a person and robot meet in a narrow hallway in order to pass by, they have to make room for each other. But how can a robot make sure that both really want to pass by instead of starting interaction? This especially concerns narrow, non-artificial surroundings. Which social signals are expected by the user and on the other side, can be generated or processed by a robot? The results will show what an appropriate passing behaviour is and how to distinguish between passage situations and others. The results shed light upon the readability of signals in spatial HRI.

PurposeRetailers are increasingly considering the introduction of service robots in their stores to support or even replace service staff. Service robots can execute service scripts during the service encounter that can influence customer interactions and the overall experience. While the role of service agents is well documented, more research is needed to understand customer responses to a technology-infused servicescape and to investigate the value of service robots as interaction partners. The purpose of this study is to examine the degree of customer immersion in human-human or human-robot interactions across different stages of the service experience and to understand how immersion affects store visit duration under each condition.Design/methodology/approachAn experimental field study was developed to test the research hypotheses. The study was conducted in a retail store selling premium Italian leather goods with 50 respondents randomly allocated to one of two experimental conditions, interaction with a service robot or interaction with a human sales associate. Participants’ biometrics were collected to measure their immersion in the service encounter and to assess its impact on store visit duration.FindingsThe interaction with a service robot increases the level of customer immersion during the service encounter’s welcome and surprise moments. Immersion positively affects visit duration. However, participants exposed to a robot sales associate reported a shorter visit duration as compared to those who interacted with a human sales associate.Originality/valueThis study contributes to the emerging service and retail marketing literature on service robot applications applying a neuroscientific approach to the study of human–robot interactions across different moments of the service encounter. For managers, this study shows the conditions under which service robots can be successfully implemented in retail stores in accordance with the type of task performed and the degree of immersion generated in customers.

Error handling in multimodal voice-enabled interfaces of tour-guide robots using graphical models

Social navigation framework for assistive robots in human inhabited unknown environments

A novel affective policy has been developed for a service robot, which emphasizes on assistance scenarios focusing on the needs of persons with mild cognitive impairment (MCI) and at early Alzheimer’s disease (AD) stages, at home. This chapter introduces a theoretical framework whose main contribution is twofold; the first one concerns a study on detecting user emotions during human–robot interaction, and the second one concerns the translation of the detected user emotions, into short-term (e.g. half-hour) and long-term (e.g. daily-long) user mood estimates. Alongside, mappings are established between recognized user affect and effects on the robot’s cognitive functions that drive the robot’s assistive behaviour. This results into either the engagement of the service robot in some assistive intervention, aiming to induce more positive outlooks, e.g. stimulating a contact with relatives or friends, or modifications in the way that the robot provides assistance so as to induce a positive feeling of care to the user. Within this chapter, we also propose specific application scenarios of Ambient Assisted Living, on which the current theoretical study can be applied, enabling a service robot to adapt its assistive behaviour based on its user mood and emotions, enabling thus the user to maintain positive affect where possible.

Service robots are increasingly transforming customer service by automating tasks traditionally performed by human employees, creating a hybrid of technological and human interaction across various industries. This chapter examines the integration of service robots into sectors such as hospitality, retail, healthcare, and finance, focusing on their impact on customer experience (CX)The findings highlight that motivations for adopting service robots include productivity gains, novelty, and convenience (Ivanov & Webster, 2019), while barriers such as high costs, privacy concerns, and limited social acceptance remain significant (Bartneck et al., 2020; Gursoy et al., 2019). This study contributes to the growing discourse on human-robot interaction, offering practical insights for organizations and suggesting future research directions, such as longitudinal studies on customer loyalty and the ethical implications of widespread service robot deployment (Huang & Rust, 2021; Belanche et al., 2021a).

Current designerly research in human–robot interaction (HRI) is often exploring how to reframe HRI research toward designerly approaches that are more situated, reflective, critical, and inclusive. While arguably underrepresented in the flagship conference and journal in the field (i.e., ACM/IEEE HRI Conference, ACM Transaction on HRI), such work is concerned to pose and examine deeper critical questions about the design and use of robots in society as lenses into a bigger phenomenon. Connecting with Chapter 6, in this chapter Ljungblad and Gamboa, provide an overview of the current socio-technical discourse around critical approaches in HRI. To this end, they introduce Critical Robotics, a conceptual structure aiming to support the formation of alternative research approaches and strengthen alternative epistemological grounds for HRI research, and propose topics for future critical research in HRI.

Interactions between consumers and humanoid service robots will soon be part of routine marketplace experiences. It is still unclear, however, whether consumers might react favorably to these humanoid robots. Previous findings have been inconsistent. Some studies showed that people experienced high sensory stimulation from interacting with service humanoids and subsequently evaluated their service experiences more favorably (Esch et al., 2020; Yam et al., 2020), while other studies showed that people felt stressed and timid by interacting with service humanoids, resulting in overall discomfort (Kim et al., 2019; Mende et al., 2019). Such discomfort is also referred to as the “uncanny valley” effect (Mori, 1970). We wish to explore a novel route to counteract the uncanny valley effect. One solution to reduce the eerie response is to make the humanoids even more ‘like us,’ ironically (Hansen et al., 2005). Specifically, we seek to show that embracing the imperfect side of humans can improve the consumer-robot interaction, thereby dodging potential “uncanny valley” effects. In the field of social psychology, presenting ‘clumsiness’ tends to humanize social agents who are viewed as distant and superior and subsequently improve their likability (Aronson et al., 1966). Humans are not perfect, and humanoids do not have to be either. We seek to show that imperfectness of machines as a function of appearing clumsy can rather improve human-robot interaction. We predict that clumsiness of robots serves as low-power signals in human-robot interactions and helps reduce eerie responses since clumsiness might make the humanoids less threatening. Previous research suggests that people tend to trust service robots more when they feel more comfortable interacting with the robots (Pixteren et al., 2019). As we predict clumsy robots will make people feel more at ease and more in control (power) in human-robot interaction, it is expected that clumsy robots will also make people trust the robots more and subsequently be more favorable of the robots. Thus, paradoxically, people might find robots that make clumsy mistakes more likable if the ‘clumsiness’ of robots makes the robot appear less ‘eerie.’

Intelligent robotic systems will be found in several fields of everyday life in the near future. This implies an easy handling of an interaction with service robots by naive persons. Up till now many problems in human-robot interaction do exist; one of them is the great variety of human communication and behavior. Thus system designers often cannot anticipate human behavior which leads to frustrated users. We have devised a tool to analyze and code human and robot behavior during human-robot interaction, which can serve as a first stepping stone toward recognizing, automating coding and adapting robot behavior in order to obtain successful interactions. The tool called Interaction Analysis Protocol was used in different interaction scenarios between robot and human being. In this paper we present an experiment within which the robot acts as receptionist. The analysis and coded behaviors are based on the Interaction Analysis Protocol.