Resumen

MARZOA TANCO, M.; TRINIDAD BARNECH, G.; BENAVIDES, F.  y  TEJERA LOPEZ, G.. Integrating advanced robotics for precision agriculture and sustainability: A MINA efforts divulgation compendium. Agrocienc. Urug. [online]. 2025, vol.29, e1528.  Epub 01-Dic-2025. ISSN 2730-5066.  https://doi.org/10.31285/agro.29.1528.

Agricultural production is a cornerstone of Uruguay's economy, contributing significantly to its GDP with an impact of approximately 11 points. This sector is characterized by its high technological demand and a declining labor force. Traditionally, the agricultural workforce has not required extensive technical skills, but the rapid advancement of technology necessitates a shift towards more technologically adept labor. Thus, the adoption of advanced technologies and the retraining of the workforce are imperative. Labor retraining within the agricultural domain is essential to fortify the sector's competitiveness, sustainability, and resilience amidst contemporary challenges. Precision agriculture advocates integrating cutting-edge technologies to optimize crop management and agricultural resource utilization. Implementing autonomous robotics has the potential to mitigate labor requirements, foster workforce technological education, and propel advancements toward precision agriculture. Founded in 2013, the MINA group at the Faculty of Engineering of the University of the Republic (Uruguay) has been actively engaged in robotics projects tailored for agricultural applications. Initially focusing on orchards of pome fruits from 2013 to 2023, the group undertook tasks such as harvest support and estimation of harvest quantity and quality. Subsequently, efforts have been directed towards pest control measures targeting pests such as birds and ants, and weed management. This paper delineates the intricacies of these distinct projects, elucidating the technologies employed and developed, outlining achieved results to date, and envisaging the potential for widespread adoption of this technology at a feasible cost.

Palabras clave : autonomous robot navigation; computer vision; artificial neural networks; precision agriculture.

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