Author supplied: The production system described in this paper in an im- plementation of an agile agent-based production system. This system is designed to meet the requirements of modern production, where short time to market, requirement-driven production and low cost small quan- tity production are important issues. The production is done on special devices called equiplets. A grid of these equiplets connected by a fast network is capable of producing a variety of diverent products in parallel. The multi-agent-based software infrastructure is responsible for the agile manufacturing. A product agent is responsible for the production of a single product and equiplet agents will perform the production steps to assemble the product. This paper describes this multiagent-based production system with the focus on the product agent.
Author supplied: The production system described in this paper in an implementation of an agile agent-based production system. This system is designed to meet the requirements of modern production, where short time to market, requirementdriven production and low cost small quantity production are important issues. The production is done on special devices called equiplets. A grid of these equiplets connected by a fast network is capable of producing a variety of different products in parallel. The multi-agent-based software infrastructure is responsible for the agile manufacturing. A product agent is responsible for the production of a single product and equiplet agents will perform the production steps to assemble the product. This paper describes this multiagent-based production system with the focus on the product agent. Presented at EUMAS 2013 ( 11th European Workshop on Multi-Agent Systems) , At Toulouse.
From the article: The ethics guidelines put forward by the AI High Level Expert Group (AI-HLEG) present a list of seven key requirements that Human-centered, trustworthy AI systems should meet. These guidelines are useful for the evaluation of AI systems, but can be complemented by applied methods and tools for the development of trustworthy AI systems in practice. In this position paper we propose a framework for translating the AI-HLEG ethics guidelines into the specific context within which an AI system operates. This approach aligns well with a set of Agile principles commonly employed in software engineering. http://ceur-ws.org/Vol-2659/
In greenhouse horticulture harvesting is a major bottleneck. Using robots for automatic reaping can reduce human workload and increase efficiency. Currently, ‘rigid body’ robotic grippers are used for automated reaping of tomatoes, sweet peppers, etc. However, this kind of robotic grasping and manipulation technique cannot be used for harvesting soft fruit and vegetables as it will cause damage to the crop. Thus, a ‘soft gripper’ needs to be developed. Nature is a source of inspiration for temporary adhesion systems, as many species, e.g., frogs and snails, are able to grip a stem or leave, even upside down, with firm adhesion without leaving any damage. Furthermore, larger animals have paws that are made of highly deformable and soft material with adjustable grip size and place holders. Since many animals solved similar problems of adhesion, friction, contact surface and pinch force, we will use biomimetics for the design and realization of the soft gripper. With this interdisciplinary field of research we aim to model and develop functionality by mimicking biological forms and processes and translating them to the synthesis of materials, synthetic systems or machines. Preliminary interviews with tech companies showed that also in other fields such as manufacturing and medical instruments, adjustable soft and smart grippers will be a huge opportunity in automation, allowing the handling of fragile objects.
In Nederland heeft slechts 1% van de blinden een blindengeleidehond, terwijl een geleidehond het ideale hulpmiddel voor de doelgroep is. Een hond neemt de zichtfunctie over en neemt autonome navigatiebeslissingen wat een aanzienlijke fysieke energiebesparing oplevert voor de gebruiker. Helaas is een blindengeleidehond niet geschikt voor iedereen met een visuele beperking. Blindsight Mobility ontwikkelt een elektronisch sensor-gestuurd alternatief van een blindengeleidehond dat voor een bredere doelgroep toegankelijk is. Met moderne technieken brengt het zijn omgeving in kaart en begeleidt zijn gebruiker aan de hand, net als een geleidehond. Daarbovenop worden functionaliteiten toegevoegd die alleen mogelijk zijn met een elektronisch hulpmiddel.
The maritime transport industry is facing a series of challenges due to the phasing out of fossil fuels and the challenges from decarbonization. The proposal of proper alternatives is not a straightforward process. While the current generation of ship design software offers results, there is a clear missed potential in new software technologies like machine learning and data science. This leads to the question: how can we use modern computational technologies like data analysis and machine learning to enhance the ship design process, considering the tools from the wider industry and the industry’s readiness to embrace new technologies and solutions? The obbjective of this PD project is to bridge the critical gap between the maritime industry's pressing need for innovative solutions for a more agile Ship Design Process; and the current limitations in software tools and methodologies available via the implementation into Ship Design specific software of the new generation of computational technologies available, as big data science and machine learning.
