AI enhanced robotics systems for smart manufacturing (AI, Data and Robotics - Made in Europe Partnerships) (IA) -

Expected Outcome

Projects are expected to contribute to the following outcomes:

• Provide safe, highly flexible, reconfigurable and modular solutions, allowing fast response to repurposing changes in production requirements, reducing considerably programming effort and configuration time for new products;
• Demonstrate significant improvements towards a meaningful and seamless social collaboration in teams of human workers, autonomous agents and robots by exploiting the latest advancements in AI, robotics and Social Sciences and Humanities (SSH);
• Create a network of open-access pilots to allow new users, especially students, start-ups, representatives from the makers’ community and SMEs, to experiment new technologies and to enable data and knowledge sharing through the European industrial ecosystems.

Scope

EU and Associated countries need to strengthen their capacity to manufacture and re-manufacture goods in a sustainable and competitive way to be ready to expand into new value chains. The recent crisis has also shown the importance of resilient, flexible, reconfigurable and responsive data-driven manufacturing lines.

Projects should seize the opportunities arising from the latest state-of the art-developments in AI and robotics to deploy intelligent and autonomous systems for flexible production.

Research activities should be multi-disciplinary and address all of the following areas:

• Development of robust, easy to use, explainable and compliant AI tools for manufacturing environments that require minimal learning and can be configured without highly skilled personnel;
• Implement and integrate the latest research findings on technologies such as sensors, actuators, control, edge computing, haptic technologies, mechatronics, robotics and autonomous systems to enhance collaborative robotics systems in order to develop advanced smart manufacturing human-machine collaborative systems ensuring safe physical and social interactions and efficient collaboration with human workers;
• Demonstrate complex, safe and efficient collaboration between multiple agents simultaneously, e.g. humans, autonomous agents, industrial machinery, AGVs and collaborative robots;
• SSH should provide a variety of human-centric approaches to develop smooth collaboration in the human-machine teams; to improve user experience; and increase awareness comfort, trust, skill and safety (physical and social) of workers in highly automated industrial environments by incorporating a greater understanding of linguistic, historic, and cultural concerns of end-users and workers , while taking into consideration a gender and intersectional perspective;
• Demonstrate results in at least three large-scale industrial use-cases, targeting sectors and tasks typically difficult to automate.

Proposals submitted under this topic should include a business case and exploitation strategy, as outlined in the introduction to this Destination.

Research must build on existing standards or contribute to standardisation. Interoperability for data sharing should be addressed. Additionally, a strategy for skills development should be presented, associating social partners when relevant.

All projects should build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms.

In order to achieve the expected outcomes, international cooperation is encouraged, in particular with Japan and/or South Korea in view of the long cooperation with EU on AI, robotics and manufacturing.

This topic implements jointly the co-programmed European Partnerships Made in Europe and AI, Data and Robotics.

Activities are expected to start at TRL 5 and achieve TRL 7 by the end of the project – see General Annex B.

Socio-economic science and humanitiesInternational CooperationCo-programmed European PartnershipsCo-programmed European Partnerships

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