Focus Area 3
Proximal Sensing with Autonomous Robots
Scientific Hypothesis
- Fusing multi-modal sensor data improves the 3D model and anomaly detection.
- Long-term sensing data enhances models for plant growth and intercropping system performance
Aims
- Develop AI models to represent plant structures and detect anomalies using sensor input.
- Build a long-term, evolving dataset of intercropping systems for training and testing AI models.
Area leadership
Please contact us if you have any questions regarding the research area
Visited 55 times, 1 visit(s) today





© Copyright. The Robotic Intercropping partnes have copyright to all photos used on the webpage.
© 2025-2030 - A research project funded by Novo Nordisk Foundation