Robot Users Research Articles

Disparities in robot adoption among U.S. manufacturers: a critical economic development challenge

ABSTRACT The growing recognition of industrial robots as a source of innovation and competitiveness for manufacturing is motivating calls for a supportive industrial ecology and policy framework. However, little is known about factors that stimulate robot adoption at the firm level. Based on survey results of 428 manufacturing establishments, this study examines 1) the current diffusion of robotics in manufacturing and 2) establishment- and region-level characteristics associated with robot adoption. Our analysis showsthat while earlier robot adopters were mainly large establishments in the automotive sector, robots are now penetrating small- and medium-sized establishments and other sectors. Furthermore, being in a a region with a large pool of existing robot users and robot-related skilled labour positively affects establishments’ decisions on robot adoption. These trends suggest cumulative advantage (and disadvantage) regarding technology upgrading and a need for policies that can encourage wider adoption of robots.

Nurses’ View towards the Use of Robotic during Pandemic COVID-19 in Indonesia: A Qualitative Study

Background: Rapid advances in artificial intelligence and robotics have alleviated difficulties for patients, hospitals, and the industry as a whole. However, the health care system is identically human-centered at its core, and many healthcare professions may not be ready to work with robots. Understanding nurses' views toward robotics can help integrate robotic technologies into future patient care.
 Objectives: This study aimed to explore how nurses view using robotics during the COVID-19 pandemic.
 Methods: This study used a qualitative descriptive technique to registered nurses who provide direct care to the patients with COVID-19 recruited from two hospitals in Indonesia. Purposive sampling was used to select respondents with criteria of those who had worked for at least one year and were willing to participate—the analysis used qualitative content analysis.
 Results: A total of 20 female nurses with an average age of 32.8 ± 4.0 years participated in this study. The qualitative findings revealed three themes with nine sub-themes, namely the use of robotic in nursing care (sub-theme: reducing the risk of COVID-19 transmission, monitoring patients remotely, and helping in providing care), the burden of using robotic in nursing care (sub-theme: digital literacy in nursing care, culture difference in providing care, changing care practice habits, and safety concern, and attitude toward robotic in nursing care (sub-theme: negative response).
 Conclusions: This study explored nurses' views on the usage of robotics during the pandemic COVID-10. It implies that a strategic plan would have many benefits and limitations, such as nursing care burden, negative attitude, and cultural awareness.

An algorithm to reduce human-robot interface compliance errors in posture estimation in wearable robots.

Assistive forces transmitted from wearable robots to the robot's users are often defined by controllers that rely on the accurate estimation of the human posture. The compliant nature of the human-robot interface can negatively affect the robot's ability to estimate the posture. In this article, we present a novel algorithm that uses machine learning to correct these errors in posture estimation. For that, we recorded motion capture data and robot performance data from a group of participants (n=8; 4 females) who walked on a treadmill while wearing a wearable robot, the Myosuit. Participants walked on level ground at various gait speeds and levels of support from the Myosuit. We used optical motion capture data to measure the relative displacement between the person and the Myosuit. We then combined this data with data derived from the robot to train a model, using a grading boosting algorithm (XGBoost), that corrected for the mechanical compliance errors in posture estimation. For the Myosuit controller, we were particularly interested in the angle of the thigh segment. Using our algorithm, the estimated thigh segment's angle RMS error was reduced from 6.3° (2.3°) to 2.5° (1.0°), mean (standard deviation). The average maximum error was reduced from 13.1° (4.9°) to 5.9° (2.1°). These improvements in posture estimation were observed for all of the considered assistance force levels and walking speeds. This suggests that ML-based algorithms provide a promising opportunity to be used in combination with wearable-robot sensors for an accurate user posture estimation.

Considering physical workload and workforce diversity in a Collaborative Assembly Line Balancing (C-ALB) optimization model.

In comparison to the traditional usage of robots, Cobotization (Human-Robot collaboration) can be considered as an effective way to increase the productivity of assembly lines while ensuring job security and flexibility. However, successful implementation of human-robot collaboration scenarios requires adapted decision support tools. Workforce diversity can be mentioned as one of the factors that should be included to study its impact on both the performance of the production system and on ergonomics. Accordingly, in this research, a new bi-objective optimization model for the collaborative assembly line with Cobots is proposed to simultaneously minimize the cycle time and the physical workload of human operators. The workforce diversity of human operators is modeled through experience level and physical ability. To analyze the benefits of the developed model, a comparison between the different solutions from the Pareto front is conducted. The results show that the utilization of Cobots can reduce both cycle time and physical workload in the assembly line.

A review on digitalization on pharmacological experiment

Pharmacology is primarily concerned with clinical pharmacokinetics and pharmacodynamics, yet as pharmacological mechanisms. Ostwald Schmiedeberg, the "Father of Pharmacology" within the 19th century. The pharmaceutical industry must embrace variety of technologies, like 3D printing, precision medicine, or patient design, silico trials, animal testing, and side impacts on human and animal participants. Three differing kinds of exploration patterns are proposed: hypothetical, methodical, and even-minded. Growing the archive concept, reengineering abstracting, and planning interdisciplinary models are hypothetical requirements.Digital transformation has shifted projects during a type of industries. Encourage pharmaceutical companies to seem for a brand new strategy to deal with computerised benefits that are currently available. Projects in a very range of industries are changed because of digital transformation. Encourage pharmaceutical businesses to develop a replacement strategy for managing currently accessible computerised benefits. Increased usage of robots, automation solutions, and computerization are all a part of the digitalization process, which allows for cost savings, increased efficiency and production, and greater adaptability to vary.The healthcare industry is being transformed by digitalisation. The pharmaceutical sector, being an important component of healthcare, isn't any exception. Pharma businesses are already using new technology and innovations to enhance pharmaceutical development and patient care. More data on pharmaceutical efficacy and improved quality of life for patients is being demanded by healthcare payers and other pharma consumers. For building and operating large-scale system-level pharmacology models utilised within the drug development process, a spread of software tools are available. Scientists is also obliged to use many modelling tools, looking on the challenge, which could raise model project duration, IT costs, etc. As a result, having one platform that permits for the setup and execution of large-scale simulations for models created using various modelling tools is very important.

How do children answer questions from a physically present humanoid robot?

AbstractThe present study investigated whether Japanese 3‐, 4‐, and 5‐year‐old children exhibit a yes bias to questions from a physically present humanoid robot, Nao. The robot asked the children yes‐no questions about familiar and unfamiliar objects. To both types of questions, the 3‐year‐old children exhibited a yes bias while the 5‐year‐old children exhibited a nay‐saying bias to questions about unfamiliar objects. The 4‐year‐old children did not exhibit any response biases. These results were not dramatically different from children's response tendencies toward humans reported in previous studies. The results demonstrate that as children might not spontaneously discriminate a real humanoid robot from humans in social situations, they do not hesitate to answer its questions. Robot usage in education and childcare is discussed.

Service robots are an option for contactless services due to the COVID-19 pandemic in the hotels

The development of robotics in the current COVID-19 pandemic scenario can change the face of the industries. Robots are becoming more prominent in the hospitality industry. In this scenario, the usage of service robots for hotels is the best option. This study is performed using TAM and TRI theories. The constructs selected for the study are perceived ease of use, perceived usefulness, attitudes, behavioural intention, discomfort, insecurity, and trust. Survey-based research is carried out with the help of a questionnaire. The target population are the employees working in the hotels. Ten hypotheses are proposed for the study. This study highlights the acceptance of service robots in the hotels of India. Out of ten proposed hypothesis, five hypotheses were accepted, and the rest were rejected. For data analysis, structural equation modelling in AMOS 20.0 was carried out. This study will help the managers and the top management in the adoption of service robots.

Application of AI and robotics in hospitality sector: A resource gain and resource loss perspective

Artificial intelligence (AI) and robots are increasingly becoming a part of workplaces across the globe. The hospitality sector has also adopted the usage of AI, robots, and other modern technologies to welcome visitors, as well as to provide services during their visits. This increasing trend of technology usage has led to employment uncertainty and higher turnover intention (TI) among employees. As such, this study examined the relationship of AI and robotics awareness among hospitality employees with TI through the moderating role of mutual trust (MT) and competitive psychological climate (CPC). Data were gathered from 330 staff (managers, supervisors, receptionists, & room service providers) employed at 3- and 5-star hotels in Lahore, Pakistan. As a result, AI and robotics awareness displayed significantly positive relationship with TI. Next, MT antagonistically moderated the relationship of AI and robotics awareness with TI. However, CPC did not moderate the link of AI and robotics awareness with TI. Some study drawbacks and directions for future research endeavour are demarcated.

The Effect of COVID-19 on Airline Transportation Services: A Study on Service Robot Usage Intention

Robots have started to be used in the service sector as well as in the manufacturing industry. The use of service robots in airport services, tourism, and hospital services also brings many advantages. Because of the COVID-19 pandemic, reducing physical contact and providing hygiene are essential benefits of service robots. For this purpose, the effect of COVID-19 fear on perceived trust in service robots and the intention to use them at airports was investigated in this study. For analysis, data were collected from 730 participants from 64 different countries, by questionnaire. The data were analyzed with the SPSS and AMOS package programs. As a result of the structural equation model analysis, it was determined that COVID-19 fear affects perceived trust in service robots and the intention to use them positively, and perceived trust also affects the intention to use service robots positively. In addition, as a result of the Process Macro analysis, it was found that perceived trust has a high mediating effect on the effect of COVID-19 fear on the intention to use. The research results show that people’s attitudes towards COVID-19 shape the perception of robot usage in air transport services.

Role of remote presence robot in healthcare facilities

This article is focused mainly on the role of the remote presence robot in health care facilities. This article has a view of the advantages, disadvantages, objectives, uses of RPRT in health care settings, and in different departments, and precautions to be taken while using RPR. In recent decades the usage of remote presence robots has been used in many clinical settings like ICU, emergency departments, medical, surgical, neurological units, and operating rooms. Remote presence robot technology RPRT, is an advanced robotics device technology that enables health care professionals to provide real-time clinical services to patients. This has been increasing in both outpatient and inpatient settings. RPRT in medical education can teach the professional curriculum to students in an interactive way as teachers do. RPR can even enable teachers to teach and interact with students remotely. The world's first hospital to introduce remote presence robots in the university of California, Los Angeles in its neurosurgery intensive care unit. The application of RPRT will increase doctor access for patients, families, and hospital staff in clinical care settings.

A review on drug induced hypersensitivity reactions

This article is focused mainly on the role of the remote presence robot in health care facilities. This article has a view of the advantages, disadvantages, objectives, uses of RPRT in health care settings, and in different departments, and precautions to be taken while using RPR. In recent decades the usage of remote presence robots has been used in many clinical settings like ICU, emergency departments, medical, surgical, neurological units, and operating rooms. Remote presence robot technology RPRT, is an advanced robotics device technology that enables health care professionals to provide real-time clinical services to patients. This has been increasing in both outpatient and inpatient settings. RPRT in medical education can teach the professional curriculum to students in an interactive way as teachers do. RPR can even enable teachers to teach and interact with students remotely. The world's first hospital to introduce remote presence robots in the university of California, Los Angeles in its neurosurgery intensive care unit. The application of RPRT will increase doctor access for patients, families, and hospital staff in clinical care settings.

A review on role of biomarkers in diagnosis and treatments of various cancers

This article is focused mainly on the role of the remote presence robot in health care facilities. This article has a view of the advantages, disadvantages, objectives, uses of RPRT in health care settings, and in different departments, and precautions to be taken while using RPR. In recent decades the usage of remote presence robots has been used in many clinical settings like ICU, emergency departments, medical, surgical, neurological units, and operating rooms. Remote presence robot technology RPRT, is an advanced robotics device technology that enables health care professionals to provide real-time clinical services to patients. This has been increasing in both outpatient and inpatient settings. RPRT in medical education can teach the professional curriculum to students in an interactive way as teachers do. RPR can even enable teachers to teach and interact with students remotely. The world's first hospital to introduce remote presence robots in the university of California, Los Angeles in its neurosurgery intensive care unit. The application of RPRT will increase doctor access for patients, families, and hospital staff in clinical care settings.

Enabling Security Services in Socially Assistive Robot Scenarios for Healthcare Applications.

Today’s IoT deployments are highly complex, heterogeneous and constantly changing. This poses severe security challenges such as limited end-to-end security support, lack of cross-platform cross-vertical security interoperability as well as the lack of security services that can be readily applied by security practitioners and third party developers. Overall, these require scalable, decentralized and intelligent IoT security mechanisms and services which are addressed by the SecureIoT project. This paper presents the definition, implementation and validation of a SecureIoT-enabled socially assisted robots (SAR) usage scenario. The aim of the SAR scenario is to integrate and validate the SecureIoT services in the scope of personalized healthcare and ambient assistive living (AAL) scenarios, involving the integration of two AAL platforms, namely QTrobot (QT) and CloudCare2U (CC2U). This includes risk assessment of communications security, predictive analysis of security risks, implementing access control policies to enhance the security of solution, and auditing of the solution against security, safety and privacy guidelines and regulations. Future perspectives include the extension of this security paradigm by securing the integration of healthcare platforms with IoT solutions, such as Healthentia with QTRobot, by means of a system product assurance process for cyber-security in healthcare applications, through the PANACEA toolkit.

User perception of medical service robots in hospital wards: a cross-sectional study.

BackgroundRecently, there have been various developments in medical service robots (MSRs). However, few studies have examined the perceptions of those who use it. The purpose of this study is to identify user perceptions of MSRs.MethodsWe conducted a survey of 320 patients, doctors, and nurses. The contents of the survey were organized as follows: external appearances, perceptions, expected utilization, possible safety accidents, and awareness of their responsibilities. Statistical analyses were performed using t-test, chi-square test, and analysis of variance.ResultsThe most preferred appearance was the animal type, with a screen. The overall average score of positive questions was 3.64±0.98 of 5 points and that of negative questions was 3.24±0.99. Thus, the results revealed that the participants had positive perceptions of MSR. The overall average of all expected utilization was 4.05±0.84. The most expected utilization was to guide hospital facilities. The most worrisome accident was exposure to personal information. Moreover, participants thought that the overall responsibility of the robot user (hospital) was greater than that of the robot manufacturer in the case of safety accidents.ConclusionThe perceptions of MSRs used in hospital wards were positive, and the overall expected utilization was high. It is necessary to recognize safety accidents for such robots, and sufficient attention is required when developing and manufacturing robots.

Toward energy-efficient online Complete Coverage Path Planning of a ship hull maintenance robot based on Glasius Bio-inspired Neural Network

Regular Ship hull maintenance is an essential for sustainability. The maintenance work of ship hulls that involve human labor suffers from many shortcomings. Maintenance robots have been introduced for drydocks to eliminate these shortcomings. An energy-efficient Complete Coverage Path Planning (CCPP) is a crucial requirement from a ship hull maintenance robot. This paper proposes a novel energy-efficient CCPP method based on Glasius Bioinspired Neural Network (GBNN) for a ship hull inspection robot. The proposed method accounts for a comprehensive energy model for path planning. This energy model reflects the energy usage of a ship hull maintenance robot due to changes in direction, distance, and vertical position. Furthermore, the proposed method is effective for dynamic workspaces since it performs online path planning. These are the major contributions made to state of the art by the work proposed in this paper. The behavior and the performance of the proposed method have been compared against state of the art through simulations considering Hornbill, a multipurpose ship hull maintenance robot. The validation confirms the ability of the proposed in realizing a complete coverage of a given dynamic workspace. According to the statistical outcomes of the comparison, the performance of the proposed method significantly surpasses that of the state-of-the-art methods in terms of energy usage. Therefore, the proposed method contributes to the development of energy-efficient CCPP methods for a ship hull maintenance robot.

Design Optimization for the Stability of Concentric Tube Robots

Concentric tube robots are catheter-sized continuum robots that show dexterous movement for minimally invasive surgical procedures. However, one of the major challenges to the practical usage of concentric tube robots is their instability, which potentially leads to the risk of tissue rupture. The snapping problem is caused by tubes having a high bending to torsional stiffness ratio (BTSR). Past efforts have shown that anisotropic patterning on tubes can alleviate the snapping problem. This research investigates the design optimization of patterns to minimize BTSR while satisfying stiffness constraints. Using topology optimization methods, rhombus-shaped patterns were identified as the ideal shape for stability. The generated designs were validated through finite element analysis and experimental testing to show the change of BTSR and the elimination of the snapping problem. Extensive parametric study is performed to analysis the sensitivity of the design parameters and provide the design guidelines. While satisfying the constraints, the proposed design method demonstrated 0.28 of BTSR with a rhombus angle of 60 degrees and a volume fraction of 0.55. The optimized design potentially improves the workspace and versatile trajectories of concentric tube manipulators.

Service Robots Usage in Marketing Hospitality in China

Since the coronavirus disease 2019(COVID-19) has had brought severe impact on all aspects of the world. A series of interpersonal distancing methods such as ensuring effective and safe social distancing among people, wearing masks, and traffic lockdown measures are also continuing to take effect to curb the continuing outbreak of the COVID-19 (“Advice for the public on COVID-19”, 2020). In response to the globally spread of COVID-19, many advanced technologies in the field of Artificial Intelligence (AI) were applied rapidly and played an essential role in the operation for several months. There are many different leading technology categories in the field of artificial intelligence and many different sub-categories within each main technology categories. Moreover, since the AGI technology does not yet reach the basic human intelligence level, this study will focus on the impact of service robots, which are already widely used in the NAI application category, on hospitality marketing in the current situation in China. In this paper the aim is to assess the effectiveness of use of service robots in Marketing Hospitality Industry during the pandemic through a quantitative study.

Intraoperative Use of Robotics With Navigation for Pedicle Screw Placement in Treatment of Pediatric High-grade Spondylolisthesis: A Preliminary Report.

Accurate pedicle screw placement is critical to surgically correct pediatric high-grade spondylolisthesis (HGS). The recent advent of robotics coupled with computer-assisted navigation (RAN) may represent a novel option to improve surgical outcomes of HGS, secondary to enhanced pedicle screw placement safety. This series presents the HGS-RAN technique adopted by our site, describing its surgical outcomes and feasibility. Consecutive patients with a diagnosis of HGS (Meyerding grade III to V), operated on using RAN from 2019 to 2020 at a single-center were reviewed. Demographics, screw accuracy, sagittal L5-S1 parameters, complications, and perioperative outcomes were described. All patients were treated with instrumentation, decompression, posterior lumbar interbody fusion, and reduction. Robotic time included anatomic registration to end of screw placement. Screw accuracy-defined as a screw placed safely within the planned intrapedicular trajectory-was characterized by the Gertzbein-Robbins system for patients with additional 3-dimensional imaging. Ten HGS patients, with an average age of 13.7 years old, were included in the series. All 62 screws were placed without neurological deficit or complication. Seven patients had additional 3-dimensional imaging to assess screw accuracy (42 of 62 screws). One hundred percent of screws were placed safely with no pedicle breaches (Gertzbein-Robbins-grade A). Thirty screws (48%) were placed through separate incisions that were percutaneous/transmuscular and 32 screws (52%) were inserted through the main incision. There were statistically significant improvements in L5 slippage (P=0.002) and lumbosacral angle (P=0.002), reflecting successful HGS correction. The total median operative time was 324 minutes with the robotic usage time consuming a median of 72 minutes. Median estimated blood loss was 150 mL, and length-of-stay was a median 3 days. This case-series demonstrates that RAN represents a viable option for HGS repair, indicated by high screw placement accuracy, safety, and L5-S1 slippage correction. Surgeons looking to adopt an emerging technique to enhance safety and correction of pediatric HGS should consider the RAN platform. Level IV-therapeutic study.

RETRACTED ARTICLE: A full freedom pose measurement method for industrial robot based on reinforcement learning algorithm

In this current era, the field of robotics has made much advancement and has also produced novelties than any other advanced research areas. The usage of robots has become an imperative part of the defense-oriented applications. The missions which are difficult to be performed by human beings can certainly be accomplished by the robots nowadays. The most crucial part for an industrial- and defense-based robot is to perform pose movements accurately for optimal usage of robotics as a replacement of human beings. This paper proposes a comprehensive introduction to the proposed hybrid approach PSO–RL which uses reinforcement learning (RL) and Particle swarm optimization (PSO). It summarizes the usage of proposed PSO-RL for pose measurement of robots in defense and industrial manufacturing systems. The hybrid PSO–RL is a promising technique for measuring poses in robots with accuracy and for optimizing obstacle avoidance error. In this paper, robot’s core movements are analyzed; speed of movements is given importance, and an attempt is made to provide more accurate moves with high precision. In order to optimize the efficiency of robotic operations, a full freedom pose measurement method based on PSO–RL is proposed. By using the characteristics of two-wheel independent driving industrial robot, the performance of the robot in three moving modes is evaluated. The experimental results show that the proposed PSO-RL method has the advantages of high accuracy, high measurement efficiency, high success rate of grabbing and avoiding obstacles. It outperforms the existing methods such as least square method and micro-displacement cyclic correction method with respect to maximum error, RMSE score and time complexity.

The Increasing Centrality of Robotic Technology in the Context of Nursing Care: Bioethical Implications Analyzed through a Scoping Review Approach.

At the dawn of the fourth industrial revolution, the healthcare industry is experiencing a momentous shift in the direction of increasingly pervasive technologization of care. If, up until the 2000s, imagining healthcare provided by robots was a purely futuristic fantasy, today, such a scenario is in fact a concrete reality, especially in some countries, such as Japan, where nursing care is largely delivered by assistive and social robots in both public and private healthcare settings, as well as in home care. This revolution in the context of care, already underway in many countries and destined to take place soon on a global scale, raises obvious ethical issues, related primarily to the progressive dehumanization of healthcare, a process which, moreover, has undergone an important acceleration following the outbreak of the COVID-19 pandemic, which has made it necessary to devise new systems to deliver healthcare services while minimizing interhuman contact. According to leading industry experts, nurses will be the primary users of healthcare robots in the short term. The aim of this study is to provide a general overview, through a scoping review approach, of the most relevant ethical issues that have emerged in the nursing care field in relation to the increasingly decisive role that service robots play in the provision of care. Specifically, through the adoption of the population-concept-context framework, we formulated this broad question: what are the most relevant ethical issues directly impacting clinical practice that arise in nursing care delivered by assistive and social robots? We conducted the review according to the five-step methodology outlined by Arksey and O'Malley. The first two steps, formulating the main research question and carrying out the literature search, were performed based on the population-context-concept (PCC) framework suggested by the Joanna Briggs Institute. Starting from an initial quota of 2,328 scientific papers, we performed an initial screening through a computer system by eliminating duplicated and non-English language articles. The next step consisted of selection based on a reading of the titles and abstracts, adopting four precise exclusion criteria: articles related to a nonnursing environment, articles dealing with bioethical aspects in a marginal way, articles related to technological devices other than robots, and articles that did not treat the dynamics of human-robot relationships in depth. Of the 2,328 titles and abstracts screened, we included 14. The results of the 14 papers revealed the existence of nonnegligible difficulties in the integration of robotic systems within nursing, leading to a lively search for new theoretical ethical frameworks, in which robots can find a place; concurrent with this exploration are the frantic attempts to identify the best ethical design system applicable to robots who work alongside nurses in hospital wards. In the final part of the paper, we also proposed considerations about the Italian nursing context and the legal implications of nursing care provided by robots in light of the Italian legislative panorama. Regarding future perspectives, this paper offers insights regarding robot engagement strategies within nursing.