Projects
InnoGuard: Hybrid and Generative Intelligence for Trustworthy Autonomous Cyber-Physical Systems

InnoGuard: Hybrid and Generative Intelligence for Trustworthy Autonomous Cyber-Physical Systems

Duration
4 years

The Hybrid and Generative Intelligence for Trustworthy Autonomous Cyber-Physical Systems (InnoGuard) project will improve the trustworthiness of Autonomous Cyber-Physical Systems (ACPS) with AI methods, boost environmental sustainability by making more energy-efficient using AI, including Large Language Models (LLMs), and test these techniques in open-source systems such as enabled with Robot Operating Systems (ROS). The main aim is to create new ways to ensure the quality of Autonomous Cyber-Physical Systems (ACPS), making them trustworthy, reliable, and legally compliant.

InnoGuard aims to make sure that the next wave of smart machines (called autonomous cyber-physical systems or ACPS) can be trusted and relied upon. The project includes an initiative to train early stage researchers to find new ways to check the quality of ACPS and make them safer and more dependable. Specifically, they're focusing on using AI to automatically assess ACPS quality and improve their behaviour over time. The project will also address the issues around how to make sure ACPS are secure, respect privacy, and can handle unexpected situations smoothly.

This project is designed to address the novel challenges imposed by quality assurance of Autonomous Cyber-Physical Systems (ACPS), which have integrated Artificial Intelligence (AI) components. The project also aims to increase the energy efficiency of ACPSs through AI methods, including Large Language Models (LLMs), and validate such techniques to improve their environmental sustainability as well as the trustworthiness of AI methods.

The InnoGuard project is coordinated by Mondragon Unibertsitatea (MGEP) as a consortium with 7 partners, including Simula as a partner. 

Funding

This project is funded by the Horizon Europe programme under Call HORIZON-MSCA-2023-DN-01 (external link to the call).

The MSCA Doctoral Networks funds InnoGuard.

Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the Granting authority can be held responsible for them.

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