Motivation

Precision agriculture relies on accurate mapping and navigation systems to optimise operations. In vineyard management, detecting features such as vine rows, posts and trunks is crucial for tasks like automated harvesting, pruning and monitoring plant health. This project aims to utilise drone imagery to detect these features, generate detailed vineyard maps and support robot navigation within these environments. By using computer vision techniques and deep learning algorithms, the goal is to develop a robust system for automatic feature extraction that can guide robotic systems in navigating complex vineyard landscapes with high precision.

Required Skills

• Programming skills in Python.
• Experience with image processing, computer vision, or deep learning frameworks (e.g., OpenCV, TensorFlow, PyTorch).
• Experience in working with geographic information systems (GIS) and mapping tools.
• Knowledge of robotics navigation and control (ROS2 preferred, but not necessary).
• Interest in agricultural robotics, precision agriculture and real-world applications.
• Problem solving mindset and ability to work independently and in teams.

Skills to Be Gained

This project provides an opportunity to develop skills in drone technology, computer vision and agricultural robotics. You will gain hands-on experience in processing drone imagery, advanced image recognition techniques and mapping data.

This project is suitable as a final year project for students at Lincoln studying Computer Science, Games or Robotics, or as an internship in robotics research. If you are interested, fill out our Expression of Interest Form, choosing Dr Jonathan Cox (jcox@lincoln.ac.uk) and Dr Rajitha de Silva (ODeSilva@lincoln.ac.uk) as the researchers to supervise the project.