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Agro - Well

ARISE & AGRO-WELL: Advancing Human-Centred Robotics in Agriculture

  • Feb 25
  • 1 min read


AGRO-WELL is pleased to announce its collaboration with ARISE a Horizon Europe funded initiative developing advanced AI-driven robotic solutions for critical sectors, including agriculture and energy.

ARISE focuses on building flexible, reconfigurable robotic platforms powered by artificial intelligence, capable of performing complex manipulation tasks in dynamic environments. In agriculture, such technologies have the potential to support activities like precision handling, harvesting operations, and infrastructure maintenance, while ensuring safe and efficient human-robot interaction.

This collaboration strengthens AGRO-WELL’s commitment to promoting smart farming solutions that place farmers’ wellbeing, occupational safety, and working conditions at the centre of technological innovation.

Together, AGRO-WELL and ARISE aim to:

  • Support the safe integration of AI-enabled robotics in agricultural environments

  • Exchange knowledge on technologies that reduce physical workload and prevent machinery-related risks

  • Foster cross-project synergies within the Horizon Europe ecosystem

  • Engage stakeholders in shaping a human-centred digital transition in agriculture

Smart farming must be not only productive and sustainable, but also safe and socially responsible. Through this collaboration, AGRO-WELL and ARISE contribute to building a future where technological progress and human wellbeing advance hand in hand.


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More info at CORDIS

Project coordination

 

Technical University of Munich
Professor Johannes Sauer
Dr. Fabian Frick


Contact Emails

 

agro-well.pur@mgt.tum.de
fabian.frick@tum.de

Key facts

 

Call: HORIZON-CL6-2024-GOVERNANCE-01
Type of action: Horizon Europe Research and Innovation Actions
Duration: November 2024 - October 2029 (60 months)
Consortium: 13 partners across 7 countries
Coordinator: Technical University of Munich
Total budget: €4,998,670 

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The AGRO-WELL project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101182923.

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 the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

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