Vladimir Kuts

Customization requirements in modern manufacturing demand a closer collaboration between operators and automated technologies, leading to a novel Human-Robot Collaboration (HRC) and interaction (HRI) paradigm aimed at augmenting human capabilities in the workplace. Digital Twin (DT) and Immersive technologies (XR) support the inclusion of the human operator in simulation-based interfaces intended for safe, efficient, multimodal, and adaptive HRI. The design and implementation of these interfaces are not yet adequately addressed. This project aims to define what is the current approach to the requirement definition for DT and XR by analyzing the potentials and challenges of the adoption of DT interfaces and other types of input methods in the HRC context, their allocation in the Human-Computer Interaction (HCI), and the state of current experimental research in this field as bringing the human back to the loop bring us the Industry 5.0 concept within industrial and healthcare domains

Particle accelerators are a key asset of the European Research Area. Their use spans from the large installations devoted to fundamental science to a wealth of facilities providing X-ray or neutron beams to a wide range of scientific disciplines. Beyond scientific laboratories, their use in medicine and industry is rapidly growing. Notwithstanding their high level of maturity, particle accelerators are now facing critical challenges related to the size and performance of the facilities envisaged for the next step of particle physics research, to the increasing demands to accelerators for applied science, and to the specific needs of societal applications. In this crucial moment for accelerator evolution, I.FAST aims at enhancing innovation in and from accelerator-based Research Infrastructures (RI) by developing innovative breakthrough technologies common to multiple accelerator platforms, and by defining strategic roadmaps for future developments. I.FAST will focus the technological R&D on long-term sustainability of accelerator-based research, with the goal of developing more performant and affordable technologies, and of reducing power consumption and impact of accelerator facilities, thus paving the way to a sustainable next-generation of accelerators. By involving industry as a co-innovation partner via the 17 industrial companies in the Consortium, 12 of which SME’s, I.FASTwill generate and maintain an innovation ecosystem around the accelerator-based RIs that will sustain the long-term evolution of accelerator technologies in Europe. To achieve its goals, I.FAST will explore new alternative accelerator concepts and promote advanced prototyping of key technologies. These include, among others, techniques to increase brightness and reduce dimensions of synchrotron light sources, advanced superconducting technologies to produce higher fields with lower consumption, and strategies and technologies to improve energy efficiency.

Autonomous driving is no longer just an idea of technology vision, instead a real technical trend all over the world. The continuing development to a further level of autonomy requires more from energy optimization. The optimization of electric propulsion drive systems of self-driving electric vehicles by using autonomous and monitoring sensors are not often discussed. The goal of the proposal is to develop a specialized unsupervised prognosis and control platform for such energy system performance estimation. This goal requires the development of several test platforms and digital twins. A digital twin is composed of three components – the physical entities in the real world, their virtual models, and the connected data/view that ties the two worlds together.