Service Robots Research Articles

Expressing Anger with Robot for Tackling the Onset of Robot Abuse

Service robots in public spaces can sometimes become victims of ‘abuse’, manifesting as persistent blocking of the robot’s path, physical violence such as pushing or pulling, or abusive language. This kind of abuse can be a serious obstacle to the deployment of robots. We studied the possibility of mitigating obstructive behaviour towards the robot, which is known to happen in the early stages of robot abuse, by having the robot express anger-like emotions. We identified and implemented three distinct anger behaviours: furious, quiet, and scolding anger. Through an online video survey, we confirmed that all three designed robot behaviours were perceived as expressions of anger. Finally, we ran an in-lab experiment with child participants to study the influence of the robot’s expressions of anger on children’s obstructive behaviours. The results show that ‘furious anger’ was effective in reducing the frequency of obstructions, whereas the other two anger types were not.

A lightweight real-time detection method of small objects for home service robots

A lightweight real-time detection method of small objects for home service robots

Breaking into the black box of customer perception towards robot service: Empirical evidence from service sector

The advent of artificial intelligence and machine learning has enabled robots to serve in consumer market for a better customer experience. Nevertheless, acceptance of robotic technology among consumers is still lacking. Therefore, this study has developed an integrated model with robot appearance, expectation confirmation model, diffusion of innovation and theory of planned behavior and empirically investigates customer intention to use service robot. The research model is empirically tested with 349 responses retrieved from customers visiting retail stores. Statistical results have revealed that customer innovativeness, compatibility, behavioral control, expectation confirmation, service robot appearance and subjective norms explained R2 80.1 % variance in customer attitude to use service robot. Practically, this research has suggested that policy makers should pay attention in innovativeness, compatibility, perceived behavioral control, expectation confirmation, robot appearance and subjective norms to boost robot service acceptance among customers. This study is original as it develops an integrated model with the combination robot appearance, theory of planned behavior, expectation confirmation and diffusion of innovation theory. In addition to that customer self-identity is conceptualized as moderating factor and hence distinguishing current research with past studies.

Endoscopic Robotic Mitral Operating Room as a Microsystem for Safety and Sustainability.

Safety and sustainability are key elements of a robotic mitral valve (MV) program at any stage of development. Challenges include the positioning of the surgeon at the robotic console, increasing patient complexity, and upstream administrative staffing difficulties. We instituted a systems approach to maximize patient safety and maintain robotic service viability. A single dedicated robotic operating room (OR) was equipped as a microsystem with team training in the operative steps, ergonomics, digital tools, and an explicit culture of safety. Outcomes of all robotic mitral procedures including concomitant procedures in the microsystem OR by a single surgeon were retrospectively reviewed. From January 2014 through December 2023, 1,529 consecutive MV patients were operated with an endoscopic robotic approach. Ten patients (0.65%) were converted to conventional approaches. Overall, 1,300 MV repairs (85%) were performed with residual MV regurgitation of none to trace in 1,205 patients (92.7%), mild in 92 patients (7.1%), and moderate in 3 patients (0.23%). MV replacements were performed in 229 patients (15%) with no paravalvular leaks. Mortality was 0.08% in the repair group and 0.87% in the replacement group. No deaths have occurred in the last 38 months. Stroke occurred in 0.31% of repair patients and 1.3% of replacement patients. One patient developed transient renal failure. Organization of the robotic OR as a microsystem is associated with surgical efficacy and very low morbidity and mortality. A comparable microsystem approach using all or select components may promote safety and sustainability for robotic MV programs at all levels.

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.

Revolutionizing retail: The transformative power of service robots on shopping dynamics

The retail sector is witnessing a significant transition as Retail Service Robots (RSRs) become more widely deployed. This paper investigates the factors influencing customer acceptance of RSRs based on their interaction experiences with these robots. While existing literature predominantly examines human-robot interaction (HRI) from a technological perspective, there is a lack of focus on the social dimensions of interacting with physical robots. Through this study we are trying to fill this gap by looking into the factors that influence customer acceptance and rejection of RSRs. A qualitative study addressed this gap, gathering data from 38 participants through open-ended essays. We identified 15 dimensions clustered into two primary themes: reasons for and against RSRs customer acceptance. Reasons for consumer acceptance of RSRs include conversational agility, performance expectancy, immersion, perceived anthropomorphism, interactivity, authenticity, intimacy, and homophily. Conversely, reasons against consumer acceptance encompass vulnerability, technological complexity, exhaustion, stiff kinesics, technology readiness, social anxiety, and privacy concerns. The implication of our study extends RSRs literature by exploring crucial factors for RSRs adoption. This study also provides actionable insights for retail managers and service robot developers to build a favourable environment for RSRs adoption.

A Method for Assessing the Reliability of the Pepper Robot in Handling Office Documents: A Case Study.

Humanoid robots are increasingly being utilized in various activities involving humans, as they can facilitate certain tasks and provide benefits to users. Humanoid service robots possess capabilities akin to human performance, often proving advantageous due to their operational speed and immunity to fatigue. Within the scope of this study, Pepper, a humanoid robot renowned for its fidelity in mimicking human gestures and behavior, serves as the focal point. Tasked with aiding office occupants in object manipulation and relocation, Pepper underwent a targeted reliability assessment. This assessment encompassed the development of a reliability block diagram (RBD), alongside meticulous analyses of individual components and system functionality across diverse operational scenarios.

Regulating learning module for patient monitoring interactive event detecting robots

Process automation robots in smart healthcare services are reliable in providing interactive patient services. The patient requirements are identified and approached through automated learning and responses. A Regulating Learning Interaction Module (RLIM) using Sigmoid Optimized Neural Networks is designed for robots in such sensitive environments. This learning module trains the robots for various services/ user interactions over patient demands. In particular, the patient interacting features on monitoring and responses/ event triggering are induced through the learning. The miscommunicated interactions are streamlined using sigmoid optimization from the conditional neural layers for assessment. This assessment delivers the possible choices to improve event detection/ response delivery. The neural network regulates the training patterns from the user inputs, histories, and patient diagnosis data for which the events are detected. This event relates the patient with the diagnosis, assistance, and monitoring for better assistance. The performance of this proposed module is validated using interaction detection, response precision, event generation rate, and miscommunication.

Humans Vs. Service Robots as Social Actors in Persuasion Settings

Our study departs from existing research, which primarily focuses on the benefits of automated social presence in customer service. Instead, we investigate the potential downsides of a service robot’s social presence in marketing persuasion, particularly its influence on consumers’ use of persuasion knowledge. Across five experiments, we aim to: (1) identify factors affecting the social presence of a salesclerk as a persuasion agent (type of service provider, persuasive intent, and robot appearance); and (2) reveal that anthropomorphized service robots in persuasion contexts lead to a decrease in perceived salesclerk sincerity (i.e., social presence effect), ultimately impacting consumer attitudes and behaviors. Additionally, we explore the mechanism behind the social presence effect by examining the moderating role of consumers’ dispositional persuasion knowledge. By applying the persuasion knowledge model to robot-mediated service encounters, this research offers valuable insights into the potential drawbacks of using anthropomorphic robots for marketing persuasion in service relationships.

EP230 - A Closed Loop Audit for Peri-Operative Outcomes Comparing Laparoscopic and Robotic-Assisted Nephroureterectomy for Upper Tract Transitional Cell Carcinoma

Abstract Introduction Transitional cell carcinoma (TCC) of the upper urinary tract (localised high-risk disease) is treated with a radical nephroureterectomy (RNU). Evidence shows laparoscopic and robotic-assisted RNU have similar oncological outcomes to open RNU, but improved peri-operative outcomes, namely length of stay (LOS) and time to mitomycin C (MMC) – given to reduce bladder recurrence. Standard The European Association of Urology (EAU) Guidelines suggest MMC instillation should occur 2-10 days after RNU. Aim To determine if this standard was being met in a single tertiary centre following laparoscopic RNU, and if the expansion of the robotics service has improved this and other peri-operative outcomes. Methods Retrospective data was collected from patient notes and collated in an excel spreadsheet for descriptive statistical analysis. Results The first loop analysed laparoscopic procedures (n = 36). The average LOS was 5 days (SD = 3.7±) and the average time to MMC was 14 days (SD = 6.7±). Bladder recurrence occurred in 41% (n = 14) of this cohort, over an average follow up time of 30.6 months. The second loop analysed robotic-assisted procedures (n = 33). The average LOS was 4 days (SD = 2.23±) and the average time to MMC was 2 days (SD = 0.57±). Bladder recurrence occurred in 30% (n = 8) of this cohort, over an average follow up time of 13 months. Conclusion Both procedures are safe and effective with satisfactory oncological outcomes. By expanding the robotics service, the average LOS and time to MMC decreased. Disease recurrence was higher in the laparoscopic cohort, but the follow-up period was longer.

A Multifunctional Tactile Sensory System for Robotic Intelligent Identification and Manipulation Perception.

Humans recognize and manipulate objects relying on the multidimensional force features captured by the tactile sense of skin during the manipulation. Since the current sensors integrated in robots cannot support the robots to sense the multiple interaction states between manipulator and objects, achieving human-like perception and analytical capabilities remains a major challenge for service robots. Prompted by the tactile perception involved in robots performing complex tasks, a multimodal tactile sensory system is presented to provide in situ simultaneous sensing for robots when approaching, touching, and manipulating objects. The system comprises a capacitive sensor owning the high sensitivity of 1.11E-2pFmm-1, a triboelectricity nanogenerator with the fast response speed of 30ms, and a pressure sensor array capable of 3D force detection. By Combining transfer learning models, which fuses multimodal tactile information to achieve high-precision (up to 95%) recognition of the multi-featured targets such as random hardness and texture information under random sampling conditions, including random grasp force and velocity. This sensory system is expected to enhance the intelligent recognition and behavior-planning capabilities of autonomous robots when performing complex tasks in undefined surrounding environments.

ORB Visual and WiFi Online RSSI fusion SLAM

Simultaneous Localization and Mapping (SLAM) technologies are indispensable for indoor service robots, enabling them to navigate through and interact with environments. Visual SLAM systems often encounter significant challenges such as dynamic obstacles, variable lighting, feature scarcity, and perceptual aliasing in real-world scenarios. By merging the precise environmental mapping capabilities of visual SLAM with the ubiquity and stability of WiFi signals, our method effectively addresses the limitations typically associated with visual SLAM. Notably, our fusion technique leverages existing WiFi infrastructure, thus providing a cost-effective improvement in spatial awareness without the extensive offline database requirements of WiFi RSSI-based localization. Comparative performance evaluations highlight that our graph optimization-based approach not only surpasses the original ORBSLAM3 method but also significantly outperforms the Extended Kalman Filter (EKF) in terms of accuracy, particularly in environments characterized by poor lighting, feature-less scenes, and significant occlusions. This is evidenced by a reduced Root Mean Square Error (RMSE) in localization: 3.09m for our method versus 4.02m for EKF. This enhancement in precision underscores the potential of our integrated system to advance indoor navigation technologies, making it a crucial development in the field of robotics and automated systems.

CLOi-Mapper: Consistent, Lightweight, Robust, and Incremental Mapper With Embedded Systems for Commercial Robot Services

CLOi-Mapper: Consistent, Lightweight, Robust, and Incremental Mapper With Embedded Systems for Commercial Robot Services

Methodology for Design of Hydrogen Robot for Medical Needs

The paper examines the concept of creating a Collaborative Service Robot powered by a Hydrogen Fuel Cell designed to assist in medical facilities. The characteristics of this robot are analyzed and its advantages are highlighted, from the point of view of ecological operation and long life during the patient service activities in a hospital facility. Some key features and benefits of Hydrogen Fuel Cell-powered robots are compared to battery-powered robots and the positives in this comparison are shown. The advantages of modern Collaborative Robots used as Service Robots in inpatient service processes in a hospital are presented. It shows the possibility, based on the competence and expertise of the authors in the field of Service Mobile Collaborative Robots, to create and implement one for the needs of human service in medical facilities, which will be powered by a hydrogen fuel cell. The main characteristics of the created mobile collaborative service robots of the ``AnRI'' series (Anthropomorphic Robot with Intelligence) are briefly indicated, where ``AnRI-1'' is equipped with a manipulator with a three-finger gripper, and ``AnRI-2'' is an information robot equipped with a large screen on top. The article analyzes the process of creating these collaborative robots, realizing several important elements of the control system, such as its development with elements of Artificial Intelligence. The advantages of hydrogen power and increased reliability of the general complex of systems in these Collaborative Mobile Robots and their possibility to be used effectively in the realization of medical care are emphasized.

A cognitive strategy for service robots in recognizing emotional attribute of objects

A cognitive strategy for service robots in recognizing emotional attribute of objects

Exploring the reasons behind guests’ disregard for service robots in the hospitality: conceptualising the role of physical engagement in human-robot interaction

ABSTRACT This exploratory study aims to theoretically and empirically examine why hotel guests often overlook service robots by conceptualising the role of physical engagement in enhancing human-robot interaction. Using unobtrusive observation and semi-structured interviews, the study identifies phenomena related to the gap between observing and using hospitality service robots, as well as identifies the underlying dimensions of physical engagement. The results reveal that physical engagement consists of five key dimensions: distance dimension, visual dimension, guiding dimension, usability dimension, and performance dimension. Additionally, the study introduces a framework for consumer physical engagement with service robots in hotels, systematically enhancing our understanding of human-robot interaction in the hospitality industry. These findings provide valuable insights for hospitality practitioners to enhance robot adoption and operational efficiency.

Service robots in hospitality: a cognitive appraisal perspective on job insecurity, turnover intentions, and generational differences

Service robots in hospitality: a cognitive appraisal perspective on job insecurity, turnover intentions, and generational differences

Real-Time Indoor Visible Light Positioning (VLP) Using Long Short Term Memory Neural Network (LSTM-NN) with Principal Component Analysis (PCA).

New applications such as augmented reality/virtual reality (AR/VR), Internet-of-Things (IOT), autonomous mobile robot (AMR) services, etc., require high reliability and high accuracy real-time positioning and tracking of persons and devices in indoor areas. Among the different visible-light-positioning (VLP) schemes, such as proximity, time-of-arrival (TOA), time-difference-of-arrival (TDOA), angle-of-arrival (AOA), and received-signal-strength (RSS), the RSS scheme is relatively easy to implement. Among these VLP methods, the RSS method is simple and efficient. As the received optical power has an inverse relationship with the distance between the LED transmitter (Tx) and the photodiode (PD) receiver (Rx), position information can be estimated by studying the received optical power from different Txs. In this work, we propose and experimentally demonstrate a real-time VLP system utilizing long short-term memory neural network (LSTM-NN) with principal component analysis (PCA) to mitigate high positioning error, particularly at the positioning unit cell boundaries. Experimental results show that in a positioning unit cell of 100 × 100 × 250 cm3, the average positioning error is 5.912 cm when using LSTM-NN only. By utilizing the PCA, we can observe that the positioning accuracy can be significantly enhanced to 1.806 cm, particularly at the unit cell boundaries and cell corners, showing a positioning error reduction of 69.45%. In the cumulative distribution function (CDF) measurements, when using only the LSTM-NN model, the positioning error of 95% of the experimental data is >15 cm; while using the LSTM-NN with PCA model, the error is reduced to <5 cm. In addition, we also experimentally demonstrate that the proposed real-time VLP system can also be used to predict the direction and the trajectory of the moving Rx.

Facing AI with knowledge: an investigative study on the utilisation of service robots and employee knowledge management behaviours

ABSTRACT Knowledge is the source of competitive advantage for employees in the labour market and for businesses in the services market. While academic research on knowledge management has made significant progress, the impact of robotic utilisation on the knowledge management behaviour of service employees remains limited, particularly with respect to the entry of artificial intelligence and robots into tourism and hospitality settings. Drawing on stress coping theory, this paper explores the mechanisms through which the utilisation of service robots influences employee knowledge management behaviour. Through a survey of 347 hotel employees, we conduct a multiple regression analysis on the data. The findings indicate that the utilisation of service robots positively influences employees’ knowledge management behaviours, with learning tensions partially mediating this relationship, and a paradox mindset negatively moderating the impact of learning tensions on knowledge management behaviour. The research findings theoretically enrich the body of knowledge in the areas of service robots, human-robot interaction, and knowledge management. Practically, the research conclusions provide insights for tourism and hospitality organisations adopting robots on how to embrace change, leverage the learning tensions and paradox mindset, and thereby fostering a more engaged and motivated workforce in the realm of knowledge management.

Exploring the affordances of service robots and the effects on frontline employees in China: a qualitative research in hotels

Purpose This study aims to investigate the affordances of service robots (SRs) in hotels and their effects on frontline employees (FLEs). Design/methodology/approach Purposive and referral samplings methods were used to conduct 28 semistructured interviews with hotel FLEs, and the transcribed manuscript was analyzed based on grounded theory. Findings The study identifies six dimensions of SR affordances: physical, sensory, task, safety, social and emotional affordances. The main effects of SR affordances on FLEs involve reducing work stress and mental fatigue and increasing positive emotions in the psychological aspects of FLEs. In terms of behavioral aspects, shifts in task priorities and enhancements in SR usage behaviors were observed. Accordingly, a mechanistic framework was revealed through which SR affordances influence FLEs via direct and indirect interactions between FLEs and SRs. Originality/value This paper expands robotics research from a supply-side perspective and is one of the few studies to investigate SR affordances in the field of hospitality research. Findings of this study provide practical guidelines for designing and implementing SRs to support hotel FLEs in their daily work.