Modular robotic platform for precision agriculture
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Date
2024-12-19
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Abstract
This thesis focuses on the development of a modular robotic platform designed to enhance precision agriculture, specifically targeting crop row detection and management. The research investigates the design and implementation of an autonomous movement system that utilizes the YOLOv8 model for accurate crop row detection. The platform integrates advanced machine
learning algorithms and robotics to improve operational efficiency in agricultural practices. Key performance metrics, including precision and recall, were evaluated to assess the effectiveness of the system in real-world agricultural settings. The results indicate significant improvements in crop detection capabilities, demonstrating the potential of modular robotics to address current challenges in precision agriculture.
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Keywords
Modular robotic platform, Precision agriculture, Autonomous movement system, Crop row detection, Agricultural robot