his thesis presents the development of a GPS-driven autonomous navigation system designed for precision agriculture, specifically targeting vineyard management. Conducted in collaboration with beSharp spa and commissioned by Q8 Italia, the project aims to enhance the efficiency and accuracy of vineyard operations by enabling a self-driving robot to autonomously navigate and detect grapevine diseases. Leveraging the capabilities of Amazon Web Services (AWS), the system offers scalable, cost-effective, and reliable real-time navigation solutions. The research focuses on the architectural design, implementation process, and challenges encountered during development. By integrating advanced robotics and cloud computing technologies, this work contributes significantly to the field of precision agriculture, setting the foundation for future advancements in autonomous agricultural robotics. The thesis is organized into four main chapters: an introduction to the research objectives and the state of the art in robot navigation, a detailed discussion of the software architecture, the development and results of simulation and implementation, and a conclusion outlining experimental results and future work. This comprehensive approach not only demonstrates the practical application of the developed system but also provides valuable insights for ongoing and future research in precision agriculture.