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 will 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 will research technologies that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. STAR’s will 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 will 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.
Field of science
- /social sciences/educational sciences/pedagogy/active learning
- /natural sciences/computer and information sciences/artificial intelligence/computational intelligence
- /natural sciences/computer and information sciences/artificial intelligence/machine learning/reinforcement learning
- /social sciences/economics and business/economics/production economics
Call for proposal
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Funding SchemeRIA - Research and Innovation action
3100 354 Pombal