STAR

AI systems in industrial plants must be safe, trusted and secure, even when operating in dynamic, unstructured and
unpredictable environments. STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe reliable and trusted human centric AI systems in manufacturing environments. STAR research and make available to novel technologies that will enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, it research technologies that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. STAR’s research and integration leading edge AI technologies with wide applicability in manufacturing environments, including:
•Active learning systems that boost safety and accelerate the acquisition of knowledge.
•Simulated reality systems that accelerate Reinforcement Learning (RL) in human robot collaboration scenarios.
•Explainable AI (XAI) systems that boost the transparency of industrial systems and increase the trust on them.
•Human Centric digital twins enabling worker monitoring for safer and trustful production processes.
•Advanced RL techniques for optimal navigation of mobile robots and for the detection of safety zones in industrial plants.
•Cyber-defence mechanisms for sophisticated poisoning and evasion attacks against deep neural networks operating over industrial data.

These technologies will be validated in challenging scenarios in manufacturing lines in the areas of quality management,
human robot collaboration and AI-based agile manufacturing. STAR eliminate security and safety barriers against
deploying sophisticated AI systems in production lines. The results will be fully integrated into existing EU-wide initiatives (EFFRA, AI4EU), as a means of enabling researchers and the European industry to deploy and leverage advanced AI
solutions in production lines.

Reason for applying to HSbooster.eu services

STAR project would like to provide input to CEN CENELEC initiatives taking into account the approval of EU AI Act with a special focus on manufacturing area. The project needs to learn how to concentrate the inputs towards specific Work Groups and align them with peer projects, as the ones in ICT-38 AI-MAN.STAR project would like to provide input to CEN CENELEC initiatives taking into account the approval of EU AI Act with a special focus on manufacturing area. The project needs to learn how to concentrate the inputs towards specific Work Groups and align them with peer projects, as the ones in ICT-38 AI-MAN.