From the pubisher's website: This paper aims to chart the (moral) values from a robotic industry's perspective regarding the introduction of robots in education. To our knowledge, no studies thus far have addressed this perspective in considering the moral values within this robotic domain. However, their values could conflict with the values upheld by other relevant stakeholders, such as the values of teachers, parents or children. Hence, it is crucial to take the various perspectives of relevant stakeholder's moral values into account. For this study, multiple focus group sessions (n=3) were conducted in The Netherlands with representatives (n=13) of robotic companies on their views of robots in primary education. Their perceptions in terms of opportunities and concerns, were then linked to business values reported in the extant literature. Results show that out of 26 business values, mainly six business values appeared relevant for robot tutors: 1) profitability, 2) productivity, 3 & 4) innovation and creativity, 5) competitiveness, and 6) risk orientation organization. https://doi.org/10.1109/DEVLRN.2019.8850726
DOCUMENT
Abstract: Background: There has been a rapid increase in the population of senior citizens in many countries. The shortage of caregivers is becoming a pressing concern. Robots are being deployed in an attempt to fill this gap and reduce the workload of caregivers. This study explores how healthcare robots are perceived by trainee care professionals. Methods: A total of 2365 students at different vocational levels completed a questionnaire, rating ethical statements regarding beneficence, maleficence, justice, autonomy, utility, and use intentions with regard to three different types of robots (assistive, monitoring, and companion) along with six control variables: gender, age, school year, technical skills, interest in technology, and enjoying working with computers.
DOCUMENT
Through a qualitative examination, the moral evaluations of Dutch care professionals regarding healthcare robots for eldercare in terms of biomedical ethical principles and non-utility are researched. Results showed that care professionals primarily focused on maleficence (potential harm done by the robot), deriving from diminishing human contact. Worries about potential maleficence were more pronounced from intermediate compared to higher educated professionals. However, both groups deemed companion robots more beneficiary than devices that monitor and assist, which were deemed potentially harmful physically and psychologically. The perceived utility was not related to the professionals' moral stances, countering prevailing views. Increasing patient's autonomy by applying robot care was not part of the discussion and justice as a moral evaluation was rarely mentioned. Awareness of the care professionals' point of view is important for policymakers, educational institutes, and for developers of healthcare robots to tailor designs to the wants of older adults along with the needs of the much-undervalued eldercare professionals.
DOCUMENT
Dit essay geeft een systeemvisie op het ontwikkelen van embedded software voor slimme systemen: (mobiele) robots en sensornetwerken.
DOCUMENT
The number of applications in which industrial robots share their working environment with people is increasing. Robots appropriate for such applications are equipped with safety systems according to ISO/TS 15066:2016 and are often referred to as collaborative robots (cobots). Due to the nature of human-robot collaboration, the working environment of cobots is subjected to unforeseeable modifications caused by people. Vision systems are often used to increase the adaptability of cobots, but they usually require knowledge of the objects to be manipulated. The application of machine learning techniques can increase the flexibility by enabling the control system of a cobot to continuously learn and adapt to unexpected changes in the working environment. In this paper we address this issue by investigating the use of Reinforcement Learning (RL) to control a cobot to perform pick-and-place tasks. We present the implementation of a control system that can adapt to changes in position and enables a cobot to grasp objects which were not part of the training. Our proposed system uses deep Q-learning to process color and depth images and generates an (Formula presented.) -greedy policy to define robot actions. The Q-values are estimated using Convolution Neural Networks (CNNs) based on pre-trained models for feature extraction. To reduce training time, we implement a simulation environment to first train the RL agent, then we apply the resulting system on a real cobot. System performance is compared when using the pre-trained CNN models ResNext, DenseNet, MobileNet, and MNASNet. Simulation and experimental results validate the proposed approach and show that our system reaches a grasping success rate of 89.9% when manipulating a never-seen object operating with the pre-trained CNN model MobileNet.
DOCUMENT
Within the profile Technical Information Technology (ICT Department) the most important specializations are Embedded Software and Industrial Automation. About half of the Technical Information curriculum consists of learning modules, the other half is organized in projects. The whole study lasts four years. After two-and-a-half year students choose a specialization. Before the choice is made students have several occasions in which they learn something about the possible fields of specialization. In the first and second year there are two modules about Industrial Automation. First there is a module on actuators, sensors and interfacing, later a module on production systems. Finally there is an Industrial Automation project. In this project groups of students get the assignment to develop the control for a scale model flexible automation cell or to develop a monitoring system for this cell. In the last year of their studies students participate in a larger Industrial Automation project, often with an assignment from Industry. Here also the possibility exists to join multidisciplinary projects (IPD; integrated product development).
DOCUMENT
While social robots bring new opportunities for education, they also come with moral challenges. Therefore, there is a need for moral guidelines for the responsible implementation of these robots. When developing such guidelines, it is important to include different stakeholder perspectives. Existing (qualitative) studies regarding these perspectives however mainly focus on single stakeholders. In this exploratory study, we examine and compare the attitudes of multiple stakeholders on the use of social robots in primary education, using a novel questionnaire that covers various aspects of moral issues mentioned in earlier studies. Furthermore, we also group the stakeholders based on similarities in attitudes and examine which socio-demographic characteristics influence these attitude types. Based on the results, we identify five distinct attitude profiles and show that the probability of belonging to a specific profile is affected by such characteristics as stakeholder type, age, education and income. Our results also indicate that social robots have the potential to be implemented in education in a morally responsible way that takes into account the attitudes of various stakeholders, although there are multiple moral issues that need to be addressed first. Finally, we present seven (practical) implications for a responsible application of social robots in education following from our results. These implications provide valuable insights into how social robots should be implemented
MULTIFILE
The challenges facing primary education are significant: a growing teacher shortage, relatively high administrative burdens that contribute to work-related stress and an increasing diversity of children in the classroom. A promising new technology that can help teachers and children meet these challenges is the social robot. These physical robots often use artificial intelligence and can communicate with children by taking on social roles, such as that of a fellow classmate or teaching assistant. Previous research shows that the use of social robots can lead to better results in several ways than when traditional educational technologies are applied. However, social robots not only bring opportunities but also lead to new ethical questions. In my PhD research, I investigated the moral considerations of different stakeholders, such as parents and teachers, to create the first guideline for the responsible design and use of social robots for primary education. Various research methods were used for this study. First of all, a large, international literature study was carried out on the advantages and disadvantages of social robots, in which 256 studies were ultimately analysed. Focus group sessions were then held with stakeholders: a total of 118 parents of primary school children, representatives of the robotics industry, educational policymakers, government education advisors, teachers and primary school children contributed. Based on the insights from the literature review and the focus group sessions, a questionnaire was drawn up and distributed to all stakeholders. Based on 515 responses, we then classified stakeholder moral considerations. In the last study, based on in-depth interviews with teachers who used robots in their daily teaching and who supervised the child-robot interaction of >2500 unique children, we studied the influence of social robots on children's social-emotional development. Our research shows that social robots can have advantages and disadvantages for primary education. The diversity of disadvantages makes the responsible implementation of robots complex. However, overall, despite their concerns, all stakeholder groups viewed social robots as a potentially valuable tool. Many stakeholders are concerned about the possible negative effect of robots on children's social-emotional development. Our research shows that social robots currently do not seem to harm children's social-emotional development when used responsibly. However, some children seem to be more sensitive to excessive attachment to robots. Our research also shows that how people think about robots is influenced by several factors. For example, low-income stakeholders have a more sceptical attitude towards social robots in education. Other factors, such as age and level of education, were also strong predictors of the moral considerations of stakeholders. This research has resulted in a guideline for the responsible use of social robots as teaching assistants, which can be used by primary schools and robot builders. The guideline provides schools with tools, such as involving parents in advance and using robots to encourage human contact. School administrators are also given insight into possible reactions from parents and other parties involved. The guideline also offers guidelines for safeguarding privacy, such as data minimization and improving the technical infrastructure of schools and robots; which still often leaves much to be desired. In short, the findings from this thesis provide a solid stepping stone for schools, robot designers, programmers and engineers to develop and use social robots in education in a morally responsible manner. This research has thus paved the way for more research into robots as assistive technology in primary education.
LINK
BACKGROUND: Rapid technological development has been opening new possibilities for children with disabilities. In particular, robots can enable and create new opportunities in therapy, rehabilitation, education, or leisure. OBJECTIVE: The aim of this article is to share experiences, challenges and learned lessons by the authors, all of them with experience conducting research in the field of robotics for children with disabilities, and to propose future directions for research and development. METHODS: The article is the result of several consensus meetings to establish future research priorities in this field. CONCLUSIONS: This article outlines a research agenda for the future of robotics in childcare and supports the establishment of R4C – Robots for Children, a network of experts aimed at sharing ideas, promoting innovative research, and developing good practices on the use of robots for children with disabilities. RESULTS: Robots have a huge potential to support children with disabilities: they can play the role of a play buddy, of a mediator when interacting with other children or adults, they can promote social interaction, and transfer children from the role of a spectator of the surrounding world to the role of an active participant. To fulfill their potential, robots have to be “smart”, stable and reliable, easy to use and program, and give the just-right amount of support adapted to the needs of the child. Interdisciplinary collaboration combined with user centered design is necessary to make robotic applications successful. Furthermore, real-life contexts to test and implement robotic interventions are essential to refine them according to real needs.
DOCUMENT
In recent years, a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organizations alike. This article discusses the current state of the art in the adoption of Industry 4.0 technologies within the construction industry. Increasing complexity in onsite construction projects coupled with the need for higher productivity is leading to increased interest in the potential use of Industry 4.0 technologies. This article discusses the relevance of the following key Industry 4.0 technologies to construction: data analytics and artificial intelligence, robotics and automation, building information management, sensors and wearables, digital twin, and industrial connectivity. Industrial connectivity is a key aspect as it ensures that all Industry 4.0 technologies are interconnected allowing the full benefits to be realized. This article also presents a research agenda for the adoption of Industry 4.0 technologies within the construction sector, a three-phase use of intelligent assets from the point of manufacture up to after build, and a four-staged R&D process for the implementation of smart wearables in a digital enhanced construction site.
DOCUMENT
