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The COVID-19 pandemic has led to a surge of interest in research work involving the development of robotic systems that reduce human-to-human interaction, as such a technology can greatly benefit healthcare industries in preventing the spread of highly infectious diseases. An indoor service robot is built and equipped with wheel odometry and a 2D LiDAR. However, the presence of the systematic odometry errors is evident during field testing. Hence, the possibility of minimizing systematic odometry errors is inspected using various methods of calculation, namely: UMBmark, Lee's and Jung's. The methods all use the Bidirectional Square Path test, performed together with ROS. It is found that Jung's method is the most appropriate method showing a 20.4% improvement compared to the uncalibrated dead reckoning accuracy. Moreover, it is found that the presence of slippage, a nonsystematic error, greatly affects the return position errors of the robot. Consequently, it is recommended to improve the design of the wheelbase to minimize the effects of nonsystematic errors. © 2022 IEEE.
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Purpose: This paper aims to investigate potential consumers' willingness to pay for robot-delivered services in travel, tourism and hospitality, and the factors that shape their willingness to pay. Design/methodology/approach: An online survey yielded a sample of 1,573 respondents from 99 countries. Independent samples t-test, Analysis of variance (ANOVA), cluster, factor and regression analyses were used. Findings: Respondents expected to pay less for robot-delivered services than human-delivered services. Two clusters were identified: one cluster willing to pay nearly the same price for robotic services as for human-delivered services, whilst the other expected deep discounts for robotic services. The willingness-to-pay was positively associated with the attitudes towards robots in tourism, robotic service experience expectations, men and household size. It was negatively associated to travel frequency, age and education. Research limitations/implications: The paper's main limitation is its exploratory nature and the use of a hypothetical scenario in measuring respondents' willingness to pay. The data were gathered prior to the COVID-19 pandemic and do not reflect the potential changes in perceptions of robots due to the pandemic. Practical implications: Practitioners need to focus on improving the attitudes towards robots in tourism because they are strongly and positively related to the willingness to pay. The marketing messages need to form positive expectations about robotic services. Originality/value: This is one of the first papers to investigate consumers' willingness to pay for robot-delivered services in travel, tourism and hospitality and factors that shape their willingness to pay. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
There has been an increase of interest and demand in the usage of logistic indoor service robots that are designed to minimize interactions between humans due to the occurrence of the COVID-19 outbreak. The application of the rising technology in the medical sector has great benefits in the industry, such as the prevention of the spread of highly infectious diseases using distance as a factor. Rooting from the purpose of the said robot, the main focus should be the ease of navigation through achieving the desired trajectory, in order to maximize the functionality, prevent collision, reduce user maneuvering difficulties, and such. Hence, this paper is focused on improving the trajectory errors on the robot navigation performance based on different control system designs specifically, a physical joystick controller and a mobile-based Bluetooth application controller. The design of the joystick is based on a pivot as its base which is directed to all angles and the design of the Bluetooth app is based on fourdirectional buttons that will operate upon clicking, and switching to other buttons to change commands. With this, the researchers conducted linear path and rotational tests using both remote control modes that are based on five varying speed values of 0.75 m/s, 0.5m/s, 0.35m/s, 0.25m/s, and 0.15 m/s. Based on the data analysis, the yielded results showed that using the Bluetooth app lowers the robot's trajectory error by 50% to 60% compared to using ajoystick to navigate to the desired point. Thus, the researchers concluded that the design of a control system greatly affects the robot navigation in achieving the desired trajectory. Considering the nonsystematic errors, a calibration based on the hardware structure design specifically on the caster wheel is recommended. © 2023 IEEE.
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The Internet of Drones (IoD) allows drones to collaborate safely while operating in a restricted airspace for numerous applications in Industry 4.0 world. Energy efficiency and sharing sensing data are the main challenges in swarm-drone collaboration for performing complex tasks effectively and efficiently in real-time. Information security of consensus achievement is required for multi-drone collaboration in the presence of Byzantine drones. Byzantine drones may be enough to cause present swarm coordination techniques to collapse, resulting in unpredictable or calamitous results. One or more Byzantine drones may lead to failure in consensus while exploring the environment. Moreover, Blockchain technology is in the early stage for swarm drone collaboration. Therefore, we introduce a novel blockchain-based approach to managing multi-drone collaboration during a swarm operation. Within drone swarms, blockchain technology is utilized as a communication tool to broadcast instructions to the swarm. This paper aims to improve the security of the consensus achievement process of multi-drone collaboration, energy efficiency, and connectivity during the environment's exploration while maintaining consensus achievement effectiveness. Improving the security of consensus achievement among drones will increase the possibility and stability of multi-drone applications by improving connectivity and energy efficiency in the smart world and solving real environmental issues.
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In view of the fact that Covid-19 is highly contagious, which poses great threat and inconvenience to people's production and life, a multifunctional robot control system with single-chip microcomputer as the control core is designed, aiming at the problems of centralized isolation points in communities, complicated situation and difficult management. Firstly, Gmapping algorithm is used to realize the robot's autonomous positioning and avoidance. Secondly, a three-degree-of-freedom robot arm is designed to disinfect any indoor space. Finally, Gmapping algorithm is used to recognize and measure the temperature of human face. Through the simulation experiment, this method can improve the efficiency of searching the shortest path and carry out disinfection work while reducing human contact, improving public safety and has practical value. © 2023 IEEE.
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Robot services have become an essential competitive differentiator in the hospitality and tourism industry. Seminal studies indicate the need for more profound knowledge about the factors that can increase the acceptance of service robots. This paper investigates the relationship between informational cues and acceptance of service robots through a meta-analysis. Our study also analyzes the acceptance of service robots through contextual characteristics moderators. The results showed that perceived robot trust influences the relationship between informational cues (anthropomorphism and social influence) and acceptance of service robots. By analyzing previous studies, our framework demonstrates that acceptance of service robots has increased more after the COVID pandemic than before the COVID pandemic. Furthermore, the relationship between attitude toward robots and robot usage intention tends to be greater in humanoid service robots (than social robots) and analytical intelligence (than mechanical intelligence). © 2023 Taylor & Francis Group, LLC.
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Accelerated by the COVID-19 pandemic, anthropomorphic service robots are continuously penetrating various domains of our daily lives. With this development, the urge for an interdisciplinary approach to responsibly design human-robot interaction (HRI), with particular attention to human dignity, privacy, compliance, and transparency, increases. This paper contributes to design science, in developing a new artifact, i.e., an interdisciplinary framework for designing responsible HRI with anthropomorphic service robots, which covers the three design science research cycles. Furthermore, we propose a multi-method approach by applying this interdisciplinary framework. Thereby, our finding offer implications for designing HRI in a responsible manner. © 2022 IEEE Computer Society. All rights reserved.
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In-person banking is still an important part of financial services around the world. Hybrid bank branches with service robots can improve efficiency and reduce operating costs. An efficient autonomous Know-Your-Customer (KYC) is required for hybrid banking. In this paper, an automated deep learning-based framework for interbank KYC in robot-based cyber-physical banking is proposed. A deep biometric architecture was used to model the customer’s KYC and anonymise the collected visual data to ensure the customer’s privacy. The symmetric-asymmetric encryption-decryption module in addition to the blockchain network was used for secure and decentralized transmission and validation of the biometric information. A high-capacity fragile watermarking algorithm based on the integer-to-integer discrete wavelet transform in combination with the Z6 and A6 lattice vector quantization for the secure transmission and storage of in-person banking documents is also proposed. The proposed framework was simulated and validated using a Pepper humanoid robot for the automated biometric-based collection of handwritten bank checks from customers adhering to COVID-19 pandemic safety guidelines. The biometric information of bank customers such as fingerprint and name is embedded as a watermark in the related bank documents using the proposed framework. The results show that the proposed security protection framework can embed more biometric data in bank documents in comparison with similar algorithms. Furthermore, the quality of the secured bank documents is 20% higher in comparison with other proposed algorithms. Also, the hierarchal visual information communication and storage module that anonymizes the identity of people in videos collected by robots can satisfy the privacy requirements of the banks. Overall, the proposed framework can provide a rapid, efficient, and cost-effective inter-bank solution for future in-person banking while adhering to the security requirements and banking regulations. Author
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Purpose: The purpose of this paper is to investigate the influencing factors of generation Z (Gen Z) consumers' revisit intentions to robotic restaurants in the post-pandemic times. Design/methodology/approach: Using a sample of Gen Z consumers with dining experiences in an Indian restaurant using service robots, the study empirically tests a research framework based on stimulus–organism–response theory. Findings: The study explains how Gen Z consumer's perceptions of functional attributes (i.e. perceived usefulness and perceived ease of use), socio-emotional attribute (i.e. perceived safety) and relational attribute (i.e. trust) shape their attitude, which in turn leads to their evaluations of performance outcomes and intention to revisit the robotic restaurants. The findings also indicate that perceived risk reduction of viral infection moderates the impact of performance outcomes on revisit intention. Originality/value: Due to the outbreak of COVID-19 pandemic, the changing preferences of consumers have resulted in an increase in demand for restaurants offering robotic services. To support the long-term viability of service robots in restaurant services, the current study investigates what elements of service robots can determine consumers' intentions to revisit the robotic restaurants during post-pandemic times. © 2023, Emerald Publishing Limited.
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The Coronavirus disease 2019 (COVID-19) pandemic has led to a catastrophic public health emergency that impacted the global society's prosperity, health, and security. Concurrently, the swift technological development over the recent decades has enabled the rising implementation of robots in various industries. In particular, there is a growing demand for robotic technology in the healthcare sector as a precautionary measure since they significantly reduce the risk of cross-infection through interpersonal contact among medical professionals by shifting to computerized routine tasks. Therefore, this paper presents a comprehensive review of the use of robots in the healthcare sector during and post-COVID-19 pandemic. This paper highlights the increasing demand and adoption of robotic technology during and post-pandemic COVID-19 in healthcare sector. The benefits to the society and engineering managers, and challenges in implementing robotic technology in the healthcare sector are provided at the end of this paper before the paper ends with a concise conclusion. IEEE
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Prevention of infectious diseases as the Covid-19 is of essential importance for the well-being of humanity. This is especially so at hospitals, where many vulnerable individuals frequent. Hand disinfection is one of the methods for preventing communicable diseases. In this paper we introduce a new modular mobile service robot designed for hand disinfection in hospitals and other public spaces. It consists of two separable parts: the driving base and the disinfection stand. The base was made in a horseshoe shape which allows it to lift its payload (the stand) near its center of gravity and distribute the weight evenly on its four wheels. The stand is able to function both in conjunction with the base and also autonomously. The whole robot was designed with social interaction in mind to achieve better hand sanitization compliance, which is of essential importance in hospitals for preventing infectious diseases. We conducted a test of how well the robot is able to find and approach people in its vicinity who face different directions. Even though the robot does not achieve its goal position ideally, it always ends up facing the user, which is even more important for starting an interaction than reaching its goal position very precisely. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Virtual Reality (VR) and simulation continue po-sitioning as suitable tools for fine-tuning processes otherwise impossible in real life. Such is the case of Aether, a mobile service robot for elderly care developed during the COVID-19 pandemic. Aether's development was negatively impacted due to restrictions placed on accessing long-term care facilities that impeded testing object tracking, elderly tracking, fall detection, and human-robot interactions. Our efforts to maximize Aether's development led us to create a digital twin where the core functionality is replicated to train the machine learning modules to optimize the robot's responses before real-world deployment. However, the digital twin creation requires significant authoring to ensure the virtual environment matches the real one by employing 3D technical artistry skills, which demands a professional knowledgeable in this domain. This paper presents a sandbox prototype for scene customization that allows importing, positioning, scaling, and saving changes for mobile robot simulation. Our preliminary testing of the sandbox has focused on usability to understand how the setting up of the environment is perceived. Preliminary results indicate that the sandbox is usable with improvements pertaining to improving the manipulation of the objects. © 2022 IEEE.
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The science of robotics is considered one of the most practical sciences in all fields. The application of this science is visible in all kinds of work fields and related fields, from construction activities to activities in the fields of medicine or even social services. One of the social services that are very widely used, is delivering items and orders to customers. This work is the duty of people who are called waiters. This job has very few benefits for people working in this field. Also, things like illness can cause some delay in the employer's work or not complete his work in some cases, also in situations such as when contagious diseases have spread, the direct communication of people within a short distance can cause more spread of the disease. The devices ordered by the customers could increase the speed of work and have a low-risk connection, the costs of the employer could be reduced, perfect service could be given to the customers, and the workforce could be employed for more useful work. This robot is specifically designed to use for reception in the conference hall of the growth center of Kharazmi University to receive the people present in this conference hall, but as mentioned above, these robots can be used in other places such as hospitals for delivering medicines to patients, also can be used in restaurants to deliver customer's orders to them. With this replacement, the speed of catering increases, at the same time, there is no lack of accuracy, and the issue that becomes more important with the spread of the contagious disease Covid-19 is hygiene, which can achieve several important goals in this field with this replacement. Specifically, during the reception, the distance between the host and the guest is less than one meter and is unsafe. Also, there is a possibility that each of the parties is a carrier of contagious diseases, and these problems are solved by this replacement. © 2022 IEEE.
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Service Robots, Artificial Intelligence (AI), and Service Automation have shown to be increasingly advantageous to hotel businesses. Especially, during the COVID-19 pandemic, hotels are starting to adopt artificial intelligence (AI) and robotics to increase the quality of their service. The are several studies have examined the costs and benefits of implementing these smart technologies, only a few of them have investigated the impact on hotel employees job performance. The purpose of this study is to investigate whether hotel employees' self-efficacy, their attitude on technology adoption, and their relationship quality with supervisor can affect their job performance. A convenience sample method was used to select respondents. The survey was distributed to employees of five- and four-star hotels in Jakarta who worked with technology equipment daily. There were 171 research participants involved in this study. Primary data was gathered using a questionnaire survey and analyzed quantitatively using SmartPLS to test for causal relationships in the data. The outcome of this research found that there is a positive significance relationship between employees' self-efficacy and their job performance, employees' relationship quality and their job performance, and also with their attitude on smart technology adoption and their job performance. These findings contribute to the impact of smart technology adoption literature, particularly in smart technology adoption in hospitality industry. © 2022 IEEE.
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Nowadays, service robots are highly anticipated in an aging society with low birthrates due to a shortage of human workers. Furthermore, COVID-19 avoids daily human communication in person. To utilize service robots in such a society, several types of robots are necessary to cope with the aforementioned society's various problems. Through collaboration with various types of robots, we have proposed and demonstrated an architecture for providing a broader range of services through this study. This architecture eliminates robot interface differences and allows the connection of various robots with a common communication protocol. In the teleoperation experiment, we could connect various types of robots manufactured by different companies using a general-purpose interface unit and we could teleoperate them via the Internet. We also confirmed in the collaboration experiment that the robots can be connected regardless of their functions by managing them according to their functions. Our architecture has verified the function to make collaboration of different types of robots both in teleoperation and collaborative tasks by different robots. In the future, we will conduct experiments to evaluate the practical services that service robots can provide in actual facilities such as shopping malls. © 2023 IEEE.
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PurposeThe COVID-19 pandemic has made contactless services such as those provided by robots increasingly pervasive. Some stores are gradually adopting service robots to sell products, which has not been explored in previous research. This study aims to explore how appearance personification of service robots affects customer decision-making in the product recommendation context.Design/methodology/approachBased on authentic in-store product recommendation service interactions, an experiment for three simulated scenarios was conducted and data was collected from 338 valid samples.FindingsThe results show appearance personification has a positive impact on customer purchase behavior while it has negative impacts on customer decision time and degree of hesitation.Originality/valueThis study not only enriches the literature on application scenarios of service robots but also supplements the literature on various customer decision-making variables in the field of service robots. It provides important practical guidance for designing robots to optimize their impact on customer decision-making.
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Robotics significantly influence retail and consumer services. The COVID-19 pandemic further amplified the rise of service robots (SRs) through social distancing measures. While robots are embraced widely by retailers and service providers, consumers' interaction with SRs remains an intriguing avenue of research across contexts. By taking a relative social power perspective, we report on a series of pre- and intra-COVID-19 studies. Our findings suggest that Gen-Z consumers hold more positive attitudes towards SRs perceived as lower in power vis-à-vis the human user. The longitudinal nature of our study also reveals that while attitudes towards such low-power services turned more negative during the COVID-19 pandemic, attitudes towards SRs that are high in power vis-à-vis the human user remained stable. In practical terms, while Gen-Z consumers hold more positive attitudes towards low-power robots, such service providers also face the challenge of relatively changeable attitudes towards them, especially during crisis times. © 2022 The Author(s)
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Purpose: The purpose of this study is to examine how consumers perceive the importance of using robot technologies for 12 services evaluated under two categories considering the technology acceptance model (TAM). Design/methodology/approach: The conceptual model analysis used structural equation modeling with the partial least squares estimation method, considering 638 responses. Findings: The results revealed that the perceived importance (PI) of robotic service delivery tasks under "room division” and "food and beverage and secondary services” affect perceived usefulness (PU) and perceived ease of use (PEOU) differently. Besides, PEOU and PU significantly influence attitudes toward using robot-staffed hotels. Research limitations/implications: The nonprobability convenience sampling method was used as the data collection method. Future studies that prefer probabilistic methods will open a different perspective for evaluating the results. Practical implications: This study's empirical findings reveal which robot-delivered services are found significant by the customers and contribute to increased customer satisfaction and loyalty. In addition, it guides accurate demand and investment planning for the tourism and hospitality industry in the post-COVID-19 era. Originality/value: To the best of the authors' knowledge, previous literature has not tested or confirmed the effects of PI related to two groups of robotic service delivery tasks on utilitarian variables. This study contributes to the literature by examining how different robotic service delivery tasks are linked to the TAM framework in a hotel setting. © 2022, Emerald Publishing Limited.
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Robots are adopted in numerous tourism and hospitality segments, including restaurants. This study aims to empirically investigate the service robots' (SRs) acceptance among fast-food employees across two cultures – Egypt and Malaysia - and examines the moderating role of culture on usage intention. Extending the UTAUT model, Hofstede's culture dimensions, and relevant literature, a survey was developed for data collection from a convenient sample of employees in two international fast-food chains. Structural equation modelling was used for hypotheses-testing purposes. The results revealed that four UTAUT main constructs explain 62% and 44% of fast-food employees' behavioural intention to adopt robots in Egypt and Malaysia, respectively. The findings revealed that easiness-of-use, recommendations of trusted people to use robots, and knowledge and skills required to use robots affect the intention of usage by fast-food employees. This study extends the research of robotics' adoption in tourism and hospitality and consequently supports the planning for the post-Covid-19 resume. It provides several theoretical and operational implications for future research. © 2022 Elsevier Ltd
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In recent years, due to the impact of COVID-19 around the world, there has been a serious shortage of medical resources. In order to supplement the manpower and fear that medical staff's contact with patients will cause a breach in the epidemic, reduce the workload of nurses, and help nurses perform repetitive tasks so that nurses can concentrate more on the patient's condition. Therefore, this paper proposes M-Robot, which is a friendly interface service robot based on the Android system and can be controlled by voice, touch, and remote control in the medical care field. The system is mainly divided into two parts. One is the web server. The web server is divided into two parts: front-end and back-end. The front-end is responsible for friendly user interface management, and the back-end is for accessing the SQLite database, as well as processing speech recognition and semantic understanding in voice services. In the other part, we use TEMI robot to develop and complete the desired service. Its service content includes environment introduction, delivery service, questionnaire survey, broadcast car, scheduling reminder, follow-up record, and patient instruction video. In the voice control mode, the user can say the wake-up word to the robot and say the required service content, and the robot will execute after receiving the message;in the remote control mode, we provide a friendly web interface for remote control. As well as the information needed to manage various services. © 2022 IEEE.