REFAS, Yassine Maachou2025-09-112025-09-112024-12-19http://dspace.ensa.dz/handle/123456789/3931This 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.enModular robotic platformPrecision agricultureAutonomous movement systemCrop row detectionAgricultural robotThesis