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The Motivation

Farmers today face several problems when seeking technological solutions to address real-time decision making and monitoring needs on their fields. There’s a lack of flexibility of the actual robotic systems due to the fact that they are built and developed to solve specialized tasks, leading to expensive monitoring and control processes and a lack of ROI for farmers.

FlexiGroBots addresses the growing market needs for new robotic technologies and their adoption by ensuring efficient automation of precision agriculture operations and flexible use of multi-robot systems.

  • Multifunctional robotics
    Lack of robotic solutions that allow to conduct a wide variety of monitoring, control or intervention tasks in the farm
  • Multi-robot cooperation:
    Lack of efficient control of heterogeneous robots and smart mission scheduling
  • Autonomy and awareness
    Lack of efficient control of heterogeneous robots and smart mission scheduling.
  • Actionable data
    Lack of accurate insights about the fields and crops to inform robotic system on field problem areas or estimate appropriate action.
define reference

Define a reference architecture and enablers for building mission control of heterogeneous multi-robot systems for precision agriculture

reference enablers
Reference architecture and enablers for secure and sovereign data exchange across companies, domains and national borders in the agricultural domain
ai driven robotics
Develop AI-driven robotics methods and services for advanced and near-real-time analytics, automated decisions and decision-support during precision agriculture operations
analysis
Contribute to the analysis of trustworthy AI-driven for heterogeneous multi-robot systems regarding transparency, human agency and oversight, privacy and data governance, technical robustness and safety
Concept
Demonstrate FlexiGroBots concept of flexible heterogeneous multi-robot system through demonstration with various levels of complexity regarding crops, number and types of robots used
validation
Perform Large scale industry validation in real-world scenarios and environments with varying levels of complexity regarding geographical regions, weather conditions, and national regulations
Solutions
Investigate, develop and demonstrate new solutions and services that arise from the intensive use of Machine Learning (ML) and AI-driven robotic systems in precision agriculture operations
AI4EU
Reinforce AI4EU AI-on-demand-platform by reusing and extending the existing assets and know-how to address the requirements of agriculture robotic platforms, in particular, a marketplace for AI-drive robotics components
Guidelines
Develop guidelines for the usage of robotics in Agri-Food considering ethics, regulations and trust requirements
Network
Enable the network of robotics and agriculture Digital Innovation Hubs with the capability to demonstrate and pilot solutions based on flexible heterogeneous multi-robot systems solutions