Core Project 4 aims at converting the collected data into robotic actions in the fields, exploiting digital avatars. Precise robotic weeding, for example, seeks to intervene in a minimally invasive way, reducing the amount of inputs such as herbicides. This project develops autonomous field aerial and ground robots that detect and identify individual plants, weed mapping the field to treat individual plants with the most appropriate intervention. The robots precisely apply nitrogen fertilizer enabled by digital avatars that predict the plant nutrient demand and probable losses in the field.
Research Videos
Image-based Plant Phenotyping
Precision Weed Management Enabled by Robotics and Robotics Vision
Topic Introduction: UAV Remote Sensing for Improving Crop Models
AgroC Model Development and Parameterization to Characterize Plant-soil System
Developing New Algorithms for Autonomous Decision Making to Optimize Robotic Farming
Developing Weed Management Strategies for Autonomous Field Robots