This scholarship aims to pioneer the development of open-source robotics to create cost-effective agricultural digital twins, bridging the gap between digital and physical farming systems. By leveraging the versatility and accessibility of open-source platforms, it will focus on designing, developing, and implementing robotic systems capable of accurately simulating agricultural environments. These digital twins will enable farmers to predict crop outcomes, optimize resource allocation, and mitigate risks by providing a virtual representation of their fields, thus facilitating informed decision-making processes. Key objectives include the development of scalable and modular robotic platforms that can be customized to suit diverse agricultural needs, the integration of advanced sensors and AI algorithms for real-time data processing and simulation, and the establishment of a framework for the seamless transition between digital twins and their physical counterparts. The project will also explore innovative approaches to reduce costs and improve the accessibility of robotics in agriculture, making cutting-edge technology available to a wider range of users.