Background: Impaired upper extremity function due to muscle paresis or paralysis has a major impact on independent living and quality of life (QoL). Assistive technology (AT) for upper extremity function (i.e. dynamic arm supports and robotic arms) can increase a client’s independence. Previous studies revealed that clients often use AT not to their full potential, due to suboptimal provision of these devices in usual care. Objective: To optimize the process of providing AT for impaired upper extremity function and to evaluate its (cost-)effectiveness compared with care as usual. Methods: Development of a protocol to guide the AT provision process in an optimized way according to generic Dutch guidelines; a quasi-experimental study with non-randomized, consecutive inclusion of a control group (n = 48) receiving care as usual and of an intervention group (optimized provision process) (n = 48); and a cost-effectiveness and cost-utility analysis from societal perspective will be performed. The primary outcome is clients’ satisfaction with the AT and related services, measured with the Quebec User Evaluation of Satisfaction with AT (Dutch version; D-QUEST). Secondary outcomes comprise complaints of the upper extremity, restrictions in activities, QoL, medical consumption and societal cost. Measurements are taken at baseline and at 3, 6 and 9 months follow-up.
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Greenhouses are in need of new monitoring tools, as they size grow bigger and bigger but still using old labour intensive methods ways of caring for the crop. HiPerGreen is set out to create a new tool, which can drive onto the pre-existing heating pipes to provide a birds eye perspective for image analysis purposes. However, clear images are necessary for consistent usable data. This presentation resumes the steps taken during the reporting: the optimisation of a rail based system towards clear images. This is done through analysis of resulting images, understanding vibrations and oscillations, and finally presents results based on prototyping. Moreover, a re-design of the electronics and hardware was also introduce to facilitate prototyping. The results are promising, laying within the requirements.
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This study investigates what pupils aged 10-12 can learn from working with robots, assuming that understanding robotics is a sign of technological literacy. We conducted cognitive and conceptual analysis to develop a frame of reference for determining pupils' understanding of robotics. Four perspectives were distinguished with increasing sophistication; psychological, technological, function, and controlled system. Using Lego Mindstorms NXT robots, as an example of a Direct Manipulation Environment, we developed and conducted a lesson plan to investigate pupils' reasoning patterns. There is ample evidence that pupils have little difficulty in understanding that robots are man-made technological and functional artifacts. Pupils' understanding of the controlled system concept, more specifically the complex sense-reason-act loop that is characteristic of robotics, can be fostered by means of problem solving tasks. The results are discussed with respect to pupils' developing technological literacy and the possibilities for teaching and learning in primary education.
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Growing volumes of wood are being used in construction, interior architecture, and product design, resulting in increasing amounts of wood waste. Using this waste is challenging, because it is too labor-intensive to process large volumes of uneven wood pieces that vary in geometry, quality, and origin. The project “Circular Wood for the Neighborhood” researches how advanced computational design and robotic production approaches can be used to create meaningful applications from waste wood. shifting the perception of circular wood as a simply harvested stream, towards a material with unique aesthetics of its own right. The complexity of the material is suggested to be tackled by switching from the object-oriented design towards designing soft systems. The system developed uses a bottom-up approach where each piece of wood aggregates according to certain parameters and the designed medium is mainly rule-sets and connections. The system is able to produce many options and bring the end-user for a meaningful co-design instead of choosing from the pre-designed options. Material-driven design algorithms were developed, which can be used by designers and end-users to design bespoke products from waste wood. In the first of three case studies, a small furniture item (“coffee table”) was designed from an old door, harvested from a renovation project. For its production, two principle approaches were developed: with or without preprocessing the wood. The principles were tested with an industrial robotic arm and available waste wood. A first prototype was made using the generated aggregation from the system, parametric production processes and robotic fabrication.
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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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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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Dutch industrial manufacturers are confronted a new and promising industrial robot: the collaborative robot (cobot). These small robotic arms are revolutionary as they allow direct and safe interaction with production workers for the very first time. The direct interaction between production worker and cobot has the potential to not only increase efficiency, but also enhance flexibility as it can align the strengths of (wo)man and machine more thoroughly. Currently, Dutch manufacturers are experimenting with cobots. To obtain a first understanding about the use of cobots in Dutch industrial practice and what the consequences are for operators and production work, we conducted an exploratory interview study (N=61). We learnt that most cobots under study are used for the production of one or a few large product batches (mass production) and work highly autonomous. The interaction between cobot and production worker is limited and reduced to operators preventing the cobot from falling into a standstill. The results tend to be in line with traditional industrial automation practices: an overemphasis on leveraging the technology’s potential and limited attention for the production workers’ work design and decision latitude. HR professionals were not involved and, therefore, miss out on a crucial opportunity to be of an added value.
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Het project PreciSIAlandbouw heeft precisielandbouwtechnieken ontwikkeld en gevalideerd op vijf thema's: sensortechnologie, kennis en advies, robotisering, digitalisering, en verdienmodellen. Dit rapport bevat de resultaten van robotisering. Er zijn modules ontwikkeld om gewas en onkruid te onderscheiden en locaties van plantdetails nauwkeurig te bepalen.Hogeschool Saxion, lectoraat Lectoraat Smart Mechatronics and Robotics
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Interactive design is an emerging trend in dementia care environments. This article describes a research project aiming at the design and development of novel spatial objects with narrative attributes that incorporate embedded technology and textiles to support the wellbeing of people living with dementia. In collaboration with people with dementia, this interdisciplinary research project focuses on the question of how innovative spatial objects can be incorporated into dementia long-term care settings, transforming the space into a comforting and playful narrative environment that can enhance self-esteem while also facilitating communication between people living with dementia, family, and staff members. The research methodologies applied are qualitative, including Action Research. Participatory design methods with the experts by experience—the people with dementia—and health professionals have been used to inform the study. Early findings from this research are presented as design solutions comprising a series of spatial object prototypes with embedded technology and textiles. The prototypes were evaluated primarily by researchers, health professionals, academics, and design practitioners in terms of functionality, aesthetics, and their potential to stimulate engagement. The research is ongoing, and the aim is to evaluate the prototypes by using ethnographic and sensory ethnography methods and, consequently, further develop them through co-design workshops with people living with dementia.
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Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for a given coordination graph is therefore a central subroutine in cooperative multi-agent reinforcement learning (MARL). Much research in MARL focuses on how to gradually update the parameters of the coordination graph, whilst leaving the solving of the coordination graph up to a known typically exact and generic subroutine. However, exact methods { e.g., Variable Elimination { do not scale well, and generic methods do not exploit the MARL setting of gradually updating a coordination graph and recomputing the joint action to select. In this paper, we examine what happens if we use a heuristic method, i.e., local search, to select joint actions in MARL, and whether we can use outcome of this local search from a previous time-step to speed up and improve local search. We show empirically that by using local search, we can scale up to many agents and complex coordination graphs, and that by reusing joint actions from the previous time-step to initialise local search, we can both improve the quality of the joint actions found and the speed with which these joint actions are found.
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