Service Robot Applications Research Articles

New Comer in the Bakery Store: A Long-Term Exploratory Study Toward Design of Useful Service Robot Applications

AbstractIn this study, we report a 6-month empirical study on a service robot deployed in a bakery shop. Recently, potential applications of service robots have been increasingly explored. However, further empirical knowledge is required to determine the optimal approach to design service robots for useful applications. We also address “usefulness” from two perspectives: the effects of a robot on customers’ shopping behavior and the practical benefits the robot could provide for human workers in its working environment. The results show that our robot achieved long-term effects on product recommendations for customers who visited the bakery store on a regular basis (weekly) but not for other customers. A thematic analysis of the interviews reflected the practical values that the staff expected from the robot. Based on these findings, we we outline key considerations for designing effective long-term service robot applications.

Service robots in my workplace: effects of employee-service robot co-work experiences on psychological empowerment

ABSTRACT With increased application of service robots in the hospitality industry, many employees nowadays are required to work with service robots. Existing studies mainly focused on the impact of service robots on customers, but ignored the existence of employee-service robot (ESR) interaction. This study explores the relationship between ESR co-work experience and psychological empowerment. Data were collected from 318 hospitality employees in China and PLS-SEM was employed for a causal-predictive analysis. Our results show that ESR co-work experience can not only improve employee trust toward service robots, but also affect trust toward organizations, and these two types of trust further affect psychological empowerment (i.e. goal internalization, authority and capability). Some of these relationships are significantly affected by gender, with the proposed impacts being stronger among male employees. The theoretical contributions and managerial implications of our paper for hospitality robotics and human resource management are subsequently discussed.

An empirical investigation of users' switching intention to public service robots: From the perspective of PPM framework

In recent years, the application of artificial intelligence (AI) technology has become increasingly common in the public sector. Users have been switching their experiences in handling businesses from interactions with human staff to those with robots. Prior studies have focused on investigating the key factors that influence users' adoption of public service robots; however, only a few have considered users' switching behaviors from traditional human services to robotic ones. This study employs a push–pull–mooring (PPM) framework derived from the human migration field to understand the factors that affect users' switching intentions in the context of public service robot applications. The research model was tested with 419 valid responses among users who had experienced both human services and public service robots in Chinese government service halls. The structural equation modeling (SEM) method was applied to quantitatively analyze the data. This study sheds new light on the key determinants of users' switching intentions toward public service robots from the perspectives of push, pull, and mooring effects. The results can help practitioners and managers understand users' intentions for such switches and make scientific decisions to encourage citizens' positive responses to service robots.

The applications and prospects of intelligent services robots in medicine

With the rapid growth of the ageing population and the increasing demand for medical services, the medical market is facing great challenges and opportunities. Intelligent service robots can provide various medical services, such as patient monitoring, drug distribution, medical record management, etc., which can improve medical efficiency, reduce the burden of medical staff, and have the advantage of 24-hour uninterrupted service. However, the application of intelligent service robots in the medical field still faces some challenges, such as technical limitations, legal and ethical issues. In addition, there are also differences in patient acceptance and demand for intelligent service robots. Based on the summary of intelligent medical treatment, this paper will introduce the application of intelligent service robots, study the application and prospect of intelligent service robots in medical treatment and the innovation of intelligent service robots in business models. Through literature review, SWOT analysis and data, the paper explains the wide application of intelligent service robots and their future opportunities and challenges.

Application and Consequences of Service Robots in Tourism and Hospitality Scenarios: A Systematic Literature Review

ABSTRACT This study comprehensively reviews the literature on robotics’ uses in the tourism and hospitality industries. Through descriptive and content analyses, 121 articles on robotics applications were examined. The results of this investigation showed that the majority of studies were carried out in the setting of hospitality. This article identified potential directions for future academic research. The adoption of robots was discussed in terms of its practical ramifications for industry practitioners.

Robotic Object Perception Based on Multispectral Few-Shot Coupled Learning

In order to enable intelligent robots to recognize unknown objects as accurately as human beings, object perception research is of great significance in service and industrial robot application scenarios. However, object perception using spectral measurements under few-shot learning usually leads to a poor result because of inadequate training samples. To overcome this problem, this work proposes a novel few-shot learning with coupled dictionary learning (FSL-CDL) framework. First, a hybrid feature fusion method is developed to extract the multiple dimension-reduced features of original spectral measurements to build the hybrid features. Then, based on the hybrid features, a multitask coupled learning method is developed to effectively recognize unknown objects under few-shot learning. In this method, two coupling patterns, i.e., interspectroscopy coupling and intraspectroscopy coupling, effectively bridge the gap between two spectral measurements. Finally, the proposed FSL-CDL is compared with other advanced algorithms on the SMM50 dataset, and reaches 97.5% and 98.4% recognition accuracy under one-shot and five-shot learning, respectively, which are better than other algorithms. Besides, FSL-CDL can be extended to other perception tasks which contains multiple heterogeneous measurements.

Development of robust sensor packages for autonomous underwater vehicles

New generations of robots are designed to support humans with a variety of partially or fully automated services. Such flexible and mobile service robots cooperate with humans or even act completely independent. To achieve this, it is necessary to significantly improve their capabilities in terms of environment perception, data processing and movement. At the same time, they must meet the highest standards of reliability and safety. Innovative electronics enable the necessary improvements and thus appropriate robot behavior. The aim of the Bionic RoboSkin project is to enhance the possibilities of a robot platform that is capable of autonomously navigating its respective environment by means of a flexible bionic sensor skin. The sensor platform is an autonomous underwater vehicle [AUV] that is based on the bionic principles of a Manta Ray [1, 2, 3]. The newly developed sensor skin consists of a textile composite as a carrier for sensor elements and provides moisture-resistant electrical connections for energy supply and communication. The integrated sensor modules enable both the detection of touch and approach and the exploration of the environment. The functionality of the sensor skin is targeting two service robotics applications: autonomous surveying of underwater structures (e.g. inspection of pipelines) and semi-autonomous geo-exploration in difficult-to-access areas (e.g. monitoring in tunnel construction). As a result, the paper presents the concept of a modular packaging platform for the use in a harsh marine environment. The technologies used for the miniaturization of the sensor module by PCB embedding and for outer housing development will be discussed in detail and a strong focus is put on packaging material properties in sub-marine conditions.

Toward Adaptive Human–Robot Collaboration for the Inclusion of People with Disabilities in Manual Labor Tasks

While human–robot collaboration is already integrated in industrial and service robotics applications, it is only used with able-bodied workers. However, collaboration through assistive robots is a major driver toward the inclusion of people with disabilities, which was demonstrated in recent research projects. Currently, inclusive robot workplaces have to be customized toward the work process and the individual needs of the person. Within, robots act along a fixed schedule and are not able to adapt to changes within the process or the needs of the interacting person. Hence, such workplaces are expensive and unappealing for companies of the first labor market, and do not realize the full potential of the technology. In this work, we propose a generalized approach toward the inclusion of people with disabilities with collaborative robots. To this end, we propose a system that analyzes the in situ capabilities of a person using a two-stage reasoning approach. The methodology is based on an ontology that allows the matchmaking of individual capabilities with process requirements. Capabilities are modeled in two time frames, through which fast (e.g., fatigue) and slow effects (e.g., worsening of illness) become distinguishable. The matchmaking is used in task allocation to establish high-level control over the assistive system. By this approach, inclusive workplaces become autonomously adaptive to the in situ capabilities of the individual person, without the need for customization. Therefore, collaborative workplaces become not only inclusive, but a contributor toward a labor market for all.

Specification, stochastic modeling and analysis of interactive service robotic applications

Assistive robotic systems are quickly becoming a core technology for the service sector as they are understood capable of supporting people in need of assistance in a wide variety of tasks. This step poses a number of ethical and technological questions. The research community is wondering how service robotics can be a step forward in human care and aid, and how robotics applications can be realized in order to put the human role at the forefront. Therefore, there is a growing demand for frameworks supporting robotic application designers in a “human-aware” development process. This paper presents a model-driven framework for analyzing and developing human–robot interactive scenarios in non-industrial settings with significant sources of uncertainty. The framework’s core is a formal model of the agents at play – the humans and the robot – and the robot’s mission, which is then put through verification to estimate the probability of completing the mission. The model captures non-trivial features related to human behavior, specifically the unpredictability of human choices and physiological aspects tied to their state of health. To foster the framework’s accessibility, we present a verification tool-agnostic Domain-Specific Language that allows designers lacking expertise in formal modeling to configure the interactive scenarios in a user-friendly manner. We compare the formal analysis outputs with results obtained by deploying benchmark scenarios in the physical environment with a real mobile robot to assess whether the formal model adheres to reality and whether the verification results are accurate. The entire development pipeline is then tested on several scenarios from the healthcare setting to assess its flexibility and effectiveness in the application design process.

Development of Cloud Autonomous System for Enhancing the Performance of Robots’ Path

With the development of computer technology and artificial intelligence (AI), service robots are widely used in our daily life. At the same time, the manufacturing cost of the robots is too expensive for almost all small companies. The greatest technical limitations are the design of the service robot and the resource sharing of the robot groups. Path planning for robots is one of the issues playing an important role in every application of service robots. Path optimization, fast computation, and minimum computation time are required in all applications. This paper aims to propose the Google Cloud Computing Platform and Amazon Web Service (AWS) platforms for robot path planning. The aim is to identify the effect and impact of using a cloud computing platform for service robots. The cloud approach shifts the computation load from robots to the cloud server. Three different path-planning algorithms were considered to find the path for robots using the Google Cloud Computing Platform, while with AWS, three different types of environments, namely dense, moderate, and sparse, were selected to run the path-planning algorithms for robots. The paper presents the comparison and analysis of the results carried out for robot path planning using cloud services with that of the traditional approach. The proposed approach of using a cloud platform performs better in this case. The time factor is crucially diagnosed and presented in the paper. The major advantage derived from this experiment is that as the size of the environment increases, the respective relative delay decreases. This proves that increasing the scale of work can be beneficial by using cloud platforms. The result obtained using the proposed methodology proves that using cloud platforms improves the efficiency of path planning. The result reveals that using the cloud computing platform for service robots can change the entire perspective of using service robots in the future. The main advantage is that with the increase in the scale of services, the system remains stable, while the traditional system starts deteriorating in terms of performance.

Applications and Implications of Service Robots in Hospitality Sector: A Case Study

Purpose–Previous research has emphasized that service robots cause radically change current service production and delivery practices and, consequently, service management and marketing strategies. This research explores the use of current state-of-the-art service robotics in the hospitality industry and aims to better understand how this technology can transform service operations. Design/Methodology/Approach–An exploratory qualitative approach was adopted for this study. Case study pattern and holistic single case pattern were preferred from qualitative research patterns as the method of inquiry. This qualitative study was conducted using a thematic analysis approach.The criterion sampling method was performed to collect data with one participant through in-depth, semi-structured individual interview. Data were analyzed using a thematic approach that built on a priori themes or categories were adopted for data analysis. Findings –Analysis of participant’s perspectives and experiences showed the 8 themes of the roles of service robotics in service encounters including substitute, support, supporting new business models, improve, differentiate, creative experiences & competition, upskill, and data collection. Unlike the previous research, supporting new business models, creative experiences & competition, and data collection were also found as new technology roles specific to service robots. By developing a new conceptual DRiTE Model (Development of Robotics in Tourism Ecosystem), the research not only contributes theoretical implications to the literature but also offers business strategies (management, marketing, etc.) for hospitality firms to manage innovative, automated service offerings. Discussion –Despite previous research having extensively discussed the use of technology in services, it can be interpreted that the current global tourism industry on the use of robotics in service encounters is still in its infancy. Over time, these micro-scale changes will evolve to form a global ecosystem. This means that the way they do business will change on a global scale through various diffusion areas such as brand, service type or stakeholder network. The paper’s novelty and uniqueness lie in suggesting a new conceptual DRiTE of addressing the implications ofthis research and offering insight for hospitality services-related managers into how to effectively research implications can be implemented.

Wow It’s a Robot! Customer-Motivated Innovativeness, Hotel Image, and Intention to Stay at Chinese Hotels

ABSTRACT Building on the Diffusion of Innovation Theory (DIT), the present study examined the influence of consumer-motivated innovativeness on the overall image of a hotel with service robots and subsequently, the intention to stay at the hotel in China. Three dimensions of consumer-motivated innovativeness, i.e., functional, hedonic, and cognitive were measured. A total of 235 valid responses were collected and analyzed using SPSS 23 and SmartPLS 3.0 software. The findings supported the significant roles of the three consumer-motivated innovativeness dimensions on overall image as well as intention to stay. Overall image was found to mediate the effects of functionally and hedonically motivated innovativeness on intention to stay, but not for the effect of cognitively motivated innovativeness. These findings are consistent with the Elaboration Likelihood Model (ELM), wherein overall image is used as a cue by individuals who are driven by functional and heuristic innovativeness, rather than those driven by cognitive innovativeness. The results contribute to a better understanding of consumer responses to the application of service robots as a marketing attraction and a management tool to improve operational efficiency.

Model-Driven Development of Service Robot Applications Dealing With Uncertain Human Behavior

In the future, robots will interact with humans in highly variable and unpredictable settings, such as healthcare and home assistance. Frameworks are, therefore, fundamental to analyze and develop interactive robotic applications that can deal by design with the uncertainty of human behavioral and physiological features. Our framework is built upon formal modeling, verification, and learning techniques providing sound mathematical guarantees of human wellbeing preservation throughout the interaction and timely mission completion despite the uncertainties at play. The framework’s workflow makes it accessible to professional figures without expertise in formal methods, and the high degree of automation minimizes the manual effort required throughout the toolchain. The development of toolchain has been tested on use cases from the healthcare setting, in which human behavior is unconstrained, and subjects are often in critical mental or physical conditions.

Solution of World Robot Challenge 2020 Partner Robot Challenge (Real Space)

The World Robot Challenge is an international competition for the social implementation of robots. Among them, the Partner Robot Challenge (Real Space) is a category that focuses on domestic service robots, competing to achieve simple tasks such as tidying a room, avoiding small obstacles, grasping a specified object from the shelf, and delivering an object to a waving person. In this category, we focused on the theme of ‘Keep Moving’ and worked on researching and developing technologies for object recognition, grasping, and other tasks. For object recognition, we propose an automatic dataset generator using a physics simulator and generate about 490,000 images in two hours. We trained it with an instance segmentation model, achieving an accuracy of about 79.3% in all games. For object grasping, we installed a three-dimensional sensor on the robot hand, and achieved successful grasping with high accuracy of about 79.6% (88.9% excluding failures due to hardware problems) in all games. In addition, we propose a motion synthesis method that simultaneously performs movement and posture transition to achieve high-speed motion. When navigation is executed, the robot changes to the navigation posture while aiming for the goal. Before reaching the goal, it changes the posture for the following action. As a result, we realized a speedup of about 1.32 times in the pick-and-place task. In the tidy-up task, the robot could clear an average of 14 objects and a maximum of 16 objects in 15 minutes. In the obstacle avoidance task, the robot succeeded five times out of six games, and in the delivery task, it succeeded four times out of six games. Throughout all the tasks, we scored 800 points twice, the highest score in the world, and won the championship. This research is aimed at the practical application of domestic service robots. We believe that the results presented in this paper demonstrate the practicality of domestic service robots in a well-developed environment. The video of the finals is available at https://youtu.be/ElUb8bfSC34?t=5511 (right side). The our source code using the simulator is available at https://github.com/Hibikino-Musashi-Home/hma_wrs_sim_ws.

Robotic employees vs. human employees: Customers’ perceived authenticity at casual dining restaurants

Cost-saving and sanitation considerations and the challenge of labor shortages have catalyzed the application of service robots in restaurants. Although service robots can perform multiple roles and functions, more research attention is needed in hospitality contexts on how different combinations of using robots and humans at different product/service layers may influence customers’ experiences and behavioral intentions. Building on the literature of product level theory and authenticity, this study empirically investigated this issue with data collected from 364 customers in China. The results show that the use of robots in core and facilitating product levels is less effective in improving consumers’ perceived service and brand authenticity. Consumers’ perceived service authenticity positively influences their brand authenticity and repurchase intention. Consumers’ perceived brand authenticity only positively affects their repurchase intention. Both theoretical and managerial implications are discussed in this paper.

Findings From A Qualitative Field Study with An Autonomous Robot in Public: Exploration of User Reactions and Conflicts

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.

The impact of service principal (service robot vs. human staff) on service quality: The mediating role of service principal attribute

In the context of the wide application of service robots, customers will question whether service robots or human staff provide higher service quality. Grounded in means-ends chain theory, this study explores the difference in SERVQUAL and in the driving mechanisms of different principals (i.e., service robots and human staff). The proposed model is examined through two scenario simulation experiments (restaurant and hotel contexts). The results show that reliability, responsiveness and empathy are influenced by different service principals (Study 1) and that the service principal's attributes mediate the relationships between the service principal and the dimensions of service quality (i.e., reliability, responsiveness and empathy) (Study 2). This study is the first to explore the specific differences in SERVQUAL from the perspective of the service principal. The findings may aid managers in selecting and using service robots more reasonably and help different service principals cooperate well.

Velocity Estimation and Cost Map Generation for Dynamic Obstacle Avoidance of ROS Based AMR

In the past few years, due to the growth of the open-source community and the popularity of perceptual computing resources, the ROS (Robotic Operating System)Ecosystem has been widely shared and used in academia, industrial applications, and service fields. With the advantages of reusability of algorithms and system modularity, service robot applications are flourishing via the released ROS navigation framework. In the ROS navigation framework, the grid cost maps are majorly designed for path planning and obstacle avoidance with range sensors. However, the robot will often collide with dynamic obstacles since the velocity information is not considered within the navigation framework in time. This study aims to improve the feasibility of high-speed dynamic obstacle avoidance for an ROS-based mobile robot. In order to enable the robot to detect and estimate dynamic obstacles from a first-person perspective, vision tracking and a laser ranger with an Extend Kalman Filter (EKF) have been applied. In addition, an innovative velocity obstacle layer with truncated distance is implemented for the path planner to analyze the performances between the simulated and actual avoidance behavior. Finally, via the velocity obstacle layer, as the robot faces the high-speed obstacle, safe navigation can be achieved.

Perception for Autonomous Systems: A Measurement Perspective on Localization and Positioning

Autonomous systems are nowadays having an undisputed pervasiveness in modern society. Autonomous driving cars as well as applications of service robots (e.g., cleaning robots, companion robots, intelligent healthcare solutions, tour guided systems) are becoming more and more popular, and a general acceptance is now developing around such systems. Nonetheless, one of the major hurdles in building such applications relies on the capability of autonomous systems to understand their surroundings and then plan proper actions. The most popular solutions, which are gaining more and more attention, rely on artificial intelligence and deep learning as a means to perceive the structured and complex natural environment. Nonetheless, classical concepts of metrology, such as standard uncertainty, accuracy and precision, are still necessary for a clear and effective understanding of modern autonomous systems applications. In this paper, some fundamental measurement concepts will be reviewed in light of the autonomous systems domain, with an emphasis on localization and positioning problems for mobile robots. In particular, we will discuss and present the main issues and concepts that build around the statistical approach to measurements and the main role of uncertainties.

An architecture for mission coordination of heterogeneous robots

Context:Robots can potentially collaborate to execute a variety of tasks in the service robots domain. However, developing applications of service robots can be complex due to the high level of uncertainty and required level of autonomy. Objective:We aim at contributing an architecture for the development of applications, capable of coordinating multi-robot missions, and that promotes modifiability and seamless integration of independently developed components. Method:In this work, we introduce MissionControl: an ensemble-based architecture to coordinate missions of heterogeneous robots to autonomously form coalitions. MissionControl comprises a component model and a runtime environment. The component model specifies how the system can be extended for different robot’s behaviors and environments. The runtime environment provides the processes required for coordinating the execution of missions at runtime. Results:We evaluated MissionControl in a simulated environment in the healthcare domain. We randomly generated 81 scenarios with uncertainty in the robots’ initial configurations. Then, each scenario was executed 8 times (i.e. 648 runs), where we evaluated the feasibility and efficiency of MissionControl for autonomously forming coalitions against a baseline approach that uses a random robot allocation. Statistical hypotheses testing yielded that MissionControl was able to achieve higher success rates while reducing the required time to conclude a mission, when compared to a baseline approach. We also perform an evaluation of the key quality attributes of the architecture, i.e. modifiability and integrability. Conclusions:MissionControl demonstrated itself able to coordinate multi-robot missions by autonomously assigning missions. Despite the error-prone robotic mission environment and demanding computational resources, MissionControl led to a significant increase in the success rate, while also decreasing the time required to conclude robotic missions when compared to a baseline approach.