The REXASI-PRO project aims to release a novel engineering framework. The REXASI-PRO project aims to release a novel engineering framework to develop greener and Trustworthy Artificial Intelligence solutions. In the methodology, safety, security, and explainability are entangled. In addition, throughout the entire lifecycle of the framework, ethics aspects will be continuously monitored. To this end, the REXASI-PRO project introduces several novelties. The project will develop in parallel the design of novel trustworthy-by-construction solutions for social navigations and a methodology to certify the robustness of AI-based autonomous vehicles for people with reduced mobility. The trustworthy-by-construction social navigation algorithms will exploit mathematical models of social robots. The robots will be trained by using both implicit and explicit communication. REXASI-PRO methodology augments existing system-level and item-level engineering frameworks by leveraging novel eXplainability methods to improve the entire system's robustness. REXASIPRO will release additional verification and validation approaches for safety and security with the AI in the loop. Among the other developments, a novel learning paradigm embeds safety requirements in Deep Neural Network for planning algorithms, runtime monitoring based on conformal prediction regions, trustable sensing, and secure communication. The methodology will be used to certify the robustness of both autonomous wheelchairs and flying robots. The flying robots will be equipped with unbiased machine learning solutions for people detection that will be reliable also in an emergency. Thus, REXASI-PRO will make the AI solutions greener. To this end, both an AI-based orchestrator to augment the intelligence of the robots and topological methods will be developed. The REXASI-PRO framework will be demonstrated by enabling the collaboration among autonomous wheelchairs and flying robots to help people with reduced mobility.

As an interdisciplinary endeavour, the GREET network brings together leading institutions and companies in Cyber-Physical System (CPS), AI, software engineering and cognitive interaction research across Europe with the aim of training a new generation of scientists, technologists, and entrepreneurs that will move Europe into a leading role in the scientific and technological innovation in Generative AI-driven CPS, its proactivity and explainability. Linking the leading academic and industrial partners in the above areas, GREET will form an effective and unique training network powerfully combining the best research training with a range of academic and industrial placements, specialist research and knowledge transfer workshops. It will develop and train a new generation of young researchers through a set of key research projects, developing breakthrough CPS systems and services that feature generative cognition, explainee-aware generative explainability, and transparent proactivity in highly secured CPS eco-environments. It will shape the delivery of training in the novel generative AI-driven CPS across Europe: delivering key insights into the science and models of the proposed CPS, setting up its scientific foundation, and equipping the DN’s recruited Doctoral Candidates with skills to drive the next innovative steps in this key area of generative AI-driven CPS. These steps include building a sustainable innovation ecosphere and community, disseminating and exploiting this new CPS’s learning and understanding of the eco-internals, eco-surroundings and eco-dynamics in many vital societal and economic services, including Industry 5.0, smart city, healthcare, energy, emergency handling, social robotics and elderly care. The innovation perspective of these new CPS is substantial, which will be particularly important for handling services that involve humans and in critical situations, e.g., in emergency and hazardous environments.

The revolutionary opportunities opened by eXtended Reality (XR) technologies will only materialize if concepts, techniques, and tools are provisioned to ensure the social acceptance of XR systems. For that, we need XR systems that are not just innovative and functionally complex, but also provide an experience that: satisfies the goals and needs of the user, is in compliance with the social context in which the system is being used, and is transparent, safe, secure, explainable and is trusted by the user. However, current generations of XR systems fail to provide the XR experience they were envisioned for since state-of-the-art models and technologies of XR systems fail to ensure full-fledged social acceptance. A truly XR experience requires a major paradigm shift in the way XR systems are designed, implemented, deployed and consumed. The SERMAS project will develop innovative, formal and systematic methodologies and technologies to model, develop, analyze, test and user-study socially-acceptable XR systems. This will be achieved by pursuing the following four main objectives: 1. Follow an inter-disciplinary, multi-sectorial, case-study-driven, scientific and technological methodology to implement the SERMAS Toolkit, a set of methods and tools that will greatly simplify the design, development, deployment, and management of socially-acceptable XR systems. 2. Apply the Toolkit to industrial case studies drawn from real-world application scenarios, thus paving the way to transferring project results to industrial practice. This will be possible through the active participation in the consortium of the developers of mass-use industrial XR applications. 3. Enable innovators to leverage the Toolkit to improve the social acceptance and cut down the time-to-market of their XR systems, thereby enhancing the competitiveness of the vendors. 4. Produce the wider SERMAS Methodology to position the use of the Toolkit and enlarge its outreach.

Agile Production crucially depends on the effectivity of intralogistics processes. Robots as components of these processes have the potential to be a game changer provided they are highly flexible, capable, cost- and energy-efficient, safe and able to operate in work environments shared with humans. However, the current state of the art falls short of providing these capabilities given the requirements for future production systems. Thus, DARKO sets out to realize a new generation of agile production robots that have energy-efficient elastic actuators to execute highly dynamic motions; are able to operate safely within unknown, changing environments; are easy (cost-efficient) to deploy; have predictive planning capabilities to decide for most efficient actions while limiting associated risks; and are aware of humans and their intentions to smoothly and intuitively interact with them. To maximise its impact, DARKO is aligned with use cases at the largest manufacturer of home appliances in Europe. It will demonstrate, in relevant scenarios, autonomous capabilities significantly beyond the current state of the art in dynamic manipulation (e.g., throwing of goods, picking and placing objects while in motion), perception, mapping, risk management, motion planning and human-robot interaction. Beyond its impact through improved capabilities in these areas, DARKO will provide answers to the questions where and how dynamic manipulation should be integrated as the most efficient solution in intralogistics. Since arm manipulators can, in principle, display super-human performance in terms of accuracy and repeatability, the value of integrating dynamic manipulation, e.g. throwing, into transport processes may well exceed current expectations. The DARKO consortium is uniquely placed to tackle this ambitious and challenging project. It brings together leading academic and corporate researchers, technology providers and end-users, with the required long-standing expertise.

The VIPPSTAR project aims to offer the first holistic framework for a life-long enhancement of health, well-being, and autonomy of children and adolescents with Visual Impairment (VI). We will support a personalized prevention of the profound and sometimes irreversible impacts of VI on individual psychological, educational, and social competence. VI can be identifiable shortly after birth, persists throughout the lifetime and is likely to have an impact on all areas of development. VIPPSTAR will include families and young individuals to overcome the burden of VI and achieve a healthy, independent life and full rights to engage critically and safely with future digital technologies for health, including AI systems. Self empowerment and agency will be promoted moving from healthcare support to family, then self-administered serious gaming, personalized eLearning, and assistant-based coaching. The system will be co-designed together with youths to support a healthy physical and mental growth to adulthood. As a key innovation, we will study body image and identity development in youth with VI and consider its impact on digital media use in youth with VI, drawing concepts to develop personalized programs to prevent inadequate nutrition, limited mobility, and addiction to social media. A dedicated surveillance network will be established to collect data in different socio-economic and geographical groups to obtain an evidence-based comparison of the new programs with the national standard of care. All aspects on ethics, data protection, and AI use will be harmonized with the relevant EU regulations and guidelines for trustworthy AI: VIPPSTAR will establish the first regulatory Sandbox for digital health services in children and youths with VI, collaborating with regulators and stakeholders according to the AI.Act principles, also contributing to other EU initiatives.