A Scalable Robotic Approach for Sustainable Viticulture in Developing Regions

Viticulture in developing regions, particularly in Peru, faces persistent challenges due to climate variability, resource constraints, and limited access to advanced mechanization. Precision agriculture technologies (PATs) have improved sustainability and efficiency in vineyard management; however, their high costs and complex infrastructure requirements prevent small and medium-sized farms (SMFs) from integrating these solutions. This study presents AgriRover, a scalable, autonomous robotic platform designed to overcome these barriers. The system integrates real-time environmental sensing, adaptive navigation, and energy-efficient automation, providing a cost-effective alternative to commercial autonomous viticulture vehicles. By analyzing existing technological solutions, this research highlights the advantages of mobile monitoring over fixed sensor networks and outlines a modular approach to sustainable viticulture. The study demonstrates how AgriRover's design principles address economic and environmental constraints, positioning it as a viable solution for smallholder farmers. Future research will explore AI-enhanced decision-making and renewable energy integration to optimize the system's autonomy and efficiency further.