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
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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.
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Social robots have been introduced in different fields such as retail, health care and education. Primary education in the Netherlands (and elsewhere) recently faced new challenges because of the COVID-19 pandemic, lockdowns and quarantines including students falling behind and teachers burdened with high workloads. Together with two Dutch municipalities and nine primary schools we are exploring the long-term use of social robots to study how social robots might support teachers in primary education, with a focus on mathematics education. This paper presents an explorative study to define requirements for a social robot math tutor. Multiple focus groups were held with the two main stakeholders, namely teachers and students. During the focus groups the aim was 1) to understand the current situation of mathematics education in the upper primary school level, 2) to identify the problems that teachers and students encounter in mathematics education, and 3) to identify opportunities for deploying a social robot math tutor in primary education from the perspective of both the teachers and students. The results inform the development of social robots and opportunities for pedagogical methods used in math teaching, child-robot interaction and potential support for teachers in the classroom
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Dit essay geeft een systeemvisie op het ontwikkelen van embedded software voor slimme systemen: (mobiele) robots en sensornetwerken.
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Background: Older adults are a rapidly growing group world-wide, requiring an increasing amount of healthcare. Technological innovations such as care robots may support the growing demand for care. However, hardly any studies address those who will most closely collaborate with care robots: the (trainee) healthcare professional. Methods: This study examined the moral considerations, perceptions of utility, and acceptance among trainee healthcare professionals toward different types of care robots in an experimental questionnaire design (N = 357). We also examined possible differences between participants’ intermediate and higher educational levels. Results: The results show that potential maleficence of care robots dominated the discussion in both educational groups. Assisting robots were seen as potentially the most maleficent. Both groups deemed companion robots least maleficent and most acceptable, while monitoring robots were perceived as least useful. Results further show that the acceptance of robots in care was more strongly associated with the participants’ moral considerations than with utility. Conclusions: Professional care education should include moral considerations and utility of robotics as emerging care technology. The healthcare and nursing students of today will collaborate with the robotic colleagues of tomorrow
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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.
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Using the latest industrial robot technology, the collaborative robot (cobot), industrial manufacturers work towards high-mix low-volume production systems that could satisfy a diversifying customer demand. As the utilization of the cobot’s potential depends on the dynamic interaction with operators, one would expect HR professionals to play a central role in this implementation process. However, cobot-related literature is unanimous: HR is not involved. This is in line with the results of our study in 2019 on seventeen cobot experiments in Dutch industrial manufacturing companies. To explore what human cobot collaboration emerges when engineers and line managers take the lead in their design, we revisited the data from our previous interview study (N=53). HR was absent in all implementations. We found that line managers and engineers prepared operators for rigid human-cobot collaborations that were aimed at getting the cobot to work, enhancing production efficiency and handling a few batches of mass-produced goods (low-mix, high-volume). Furthermore, the collaborations all showed signs of being difficult to sustain over time and posed a direct threat to operators’ well-being. To protect operators’ future of work and build towards interdependent human-cobot collaboration suitable for high-mix low-volume production, we propose an approach in which operators themselves, and HR too, are much more involved in the cobot implementation process. Operators should be allowed and supported to design, program, operate, and repair as much of their human-cobot workstations themselves as possible. To support this, HR has to familiarize itself with the cobot technology, secure operators’ decision latitude, facilitate the required support, and become the work design expert that helps operators co-design sustainable cobot applications that optimally utilize the strengths of both man and machine.
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Robot tutors provide new opportunities for education. However, they also introduce moral challenges. This study reports a systematic literature re-view (N = 256) aimed at identifying the moral considerations related to ro-bots in education. While our findings suggest that robot tutors hold great potential for improving education, there are multiple values of both (special needs) children and teachers that are impacted (positively and negatively) by its introduction. Positive values related to robot tutors are: psychological welfare and happiness, efficiency, freedom from bias and usability. However, there are also concerns that robot tutors may negatively impact these same values. Other concerns relate to the values of friendship and attachment, human contact, deception and trust, privacy, security, safety and accountability. All these values relate to children and teachers. The moral values of other stakeholder groups, such as parents, are overlooked in the existing literature. The results suggest that, while there is a potential for ap-plying robot tutors in a morally justified way, there are imported stake-holder groups that need to be consulted to also take their moral values into consideration by implementing tutor robots in an educational setting. (from Narcis.nl)
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Collaborative robot arms (cobots) are gaining a strong foothold in contemporary manufacturing workplaces. While more information about the cobot’s impact becomes available, crucial design, work perception, performance, and strategic implications are systematically overlooked. Following a modern sociotechnical systems design theory (MSTS) perspective, which lies at the heart of workplace innovation literature, we studied if, how, and why the cobot made production units more resilient and strategically relevant. We ran a comparative case study involving 15 Dutch small- and medium-sized manufacturing enterprises (SMEs) and 36 interviewees (managers and operators). The results describe how the cobots are designed as autonomous and rigid mini-robots, handling one or a few high-quantity products in ways that are not inherently more reliable and efficient. Operators interacting with the cobots experience stronger motivational work characteristics, but the cobot’s autonomous and stable operation also provokes classic out-of-the-loop problems. Consequently, cobot-equipped production units do not always perform better. Nonetheless, SMEs deem their units strategically relevant since they (indirectly) improve financial flexibility, increase production capacity, streamline future automation projects, and accommodate the resolution of labor scarcity issues. This research creates a pathway for more MSTS and workplace innovation research at the crossroads of human-robot interaction, organisational design, production management, applied psychology, and entrepreneurship. Practical implications are provided and discussed elaborately.
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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.
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