Concept & objectives

About AGIMUS

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AGIMUS aims to deliver open-source breakthrough innovation in AI-powered agile production.The solutions and their impact will be demonstrated and thoroughly stress tested in 3 testing zones (i.e., CNRS, CTU, and INRIA), as well as 3 industrial pilots in Europe (i.e, AIRBUS, KLEEMANN, and THIMM), under numerous diverse real-world case studies and scenarios (different tools, environments, processes, etc.). The project's key objectives are to identify and map the needs and challenges for delivering solutions that can sustainably support agile production, to identify and leverage existing open data, tools, and platforms for next-generation AI-powered robotics, to analyse the needs, challenges, and available data for agile production in the context of introducing design guidelines for next-generation AI-powered robotics and to co-design the AGIMUS’s system requirements and architecture, covering both functional and non-functional aspects towards a higher level of autonomy.

Project objectives

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  • Significantly accelerate the introduction and deployment of a robotic system to a new agile production environment through advanced perception and understanding of human-centric feedback
  • Increase the level of autonomy by leveraging enriched edge-computing decision making, driven by next-generation AI offline training and advanced control policies that adapt online to unforeseen situations
  • Ancillary services for further increasing the level of autonomy by incorporating energy-efficient practises and 5G technologies
  • Demonstrate, evaluate, and validate AGIMUS in consortium testing zones and real-world industrial case studies under a variety of expected and unexpected situations
  • Ensure trustworthiness, privacy, security, and ethics by design, while leveraging lessons
  • Establish synergies and cohesion activities while also exchanging knowledge and driving the sustainable exploitation of results in line with the objectives of the AI, Data and Robotics Partnership.

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This work is supported by the AGIMUS project funded by the European Union under GA no.101070165. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.

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