CP 4: Autonomous In-Field Intervention

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

PhenoRob PhD Student Jan Weyler talks about his research within Core Project 4: Autonomous In-Field Intervention.

Precision Weed Management Enabled by Robotics and Robotics Vision

PhenoRob PhD Student Alireza Ahmadi talks about his research within Core Project 4: Autonomous In-Field Intervention.

Topic Introduction: UAV Remote Sensing for Improving Crop Models

PhenoRob PhD Student Jordan Bates talks about his research within Core Project 4: Autonomous In-Field Intervention.

AgroC Model Development and Parameterization to Characterize Plant-soil System

PhenoRob PhD Student Rajina Bajracharya talks about her research within Core Project 4: Autonomous In-Field Intervention.

Developing New Algorithms for Autonomous Decision Making to Optimize Robotic Farming

PhenoRob Junior Research Group Leader Marija Popovic talks about her research within Core Project 4: Autonomous In-Field Intervention.

Developing Weed Management Strategies for Autonomous Field Robots

PhenoRob PhD Student Marie Zingsheim talks about her research within Core Project 4: Autonomous In-Field Intervention.