Autonomous tractor re-charging strategy

Overview

The tractors in this pilot will optimise battery charging through edge analytics and AI predictions, either autonomously or via a farmer-controlled app, minimizing battery use, extending lifespan, and reducing costs for improved sustainability.

 

Expected Outcomes

  • To optimise navigation and scheduling of tasks within the field using AI utilities from the Marketplace to cut downtime and energy waste. 
    • KPI: Time to collect, analyse and act upon (un)expected event: reduction of 70% (over current 2h).
  • To validate predictive charging and scheduling, minimising downtime and CO2 footprint.
    • KPI: Reduction of greenhouse gas emissions (kgCO2-eq.) 0.24-0.48kg per kg of kiwi produced (over current 0.6 to 1.2 kgCO2-eq.)

This use case is now available in the hourglass canvas, mapping the relevant stakeholders against the capabilities required for delivery and uptake. Explore it to identify who needs to be engaged, what is already in place, and where capability gaps remain

View this use case on the hourglass model
Country:
Spain
Domain:
Agrifood
Part of: Pilot 6: Smart re-charging and efficiency of robot tractors in large fruit production fields
Projects: O-CEI
TRL: 4-6: Validation and Prototype
Involved partners:
farming illustration