FlexiGroBots envisions an open platform integrating and leveraging existing technology platforms and components, digital transformation initiatives and ecosystems, and reference models and standards.


  • More versatility by using the same robots for different observation and intervention tasks within various missions throughout the crop life cycle
  • More cooperation between ground and aerial robots to accomplish complex missions
  • More data to power into AI-driven agricultural operations, taken from a variety of sources and shared between Agri-Food industry stakeholders
  • More autonomy for real-time adaption of mission plans and robots’ fine-grained behaviour at crop level considering operational conditions and real-time insights
  • More precision in agricultural operations to carry out specific tasks with advanced accuracy for reducing costs and environmental footprint

The platform offers two main capabilities to empower roboticist, engineers and service providers to build and deploy flexible heterogeneous multi-robot systems in the Agri-Food sector:

  • Mission Control Centre: provides services for a semi-autonomous operation of complex multi-robot missions and for keeping the human operator in the loop during operations as well as mission planning.
  • Agricultural Data Space (ADS): complements current platforms and technologies by providing services for agricultural data sharing, processing and trading, while bringing together different stakeholders to benefit from each other’s data.


  1. Operator GUI: Graphical User Interface elements for the human operator to remain in the control loop.
  2. Mission Supervision: Including semi-autonomy processes such as adaptive mission planning and fault recovery.
  3. Mission Planning: For easier and more flexible definition, instantiation and enactment of plans for complex multi-robot configurations.
  4. Geospatial data processing toolset: Including Earth Observation (EO) data cubes and interfaces.
  5. AI Platform: Comprising libraries and tools to cover the whole ML model life cycle, including a marketplace of AI methods and models.
  6. Common Data Space services implementing IDSA reference architecture to realise a data value chain maximising synergies, collaboration and trading around data while ensuring data sovereign, governance and security for data-powered digital ecosystems.