Virginia Riego del Castillo

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About

Virginia Riego del Castillo is a leading researcher at the intersection of computer vision and agricultural robotics, with a focus on developing intelligent systems for livestock management. Her most impactful work introduces a vision-based module for herding with a sheepdog robot, addressing the critical challenge of protecting grazing animals from predators like the Iberian wolf in difficult-to-access terrain. This foundational paper, with 17 citations, demonstrates how autonomous robots can replicate traditional herding behaviors using real-time visual feedback. Building on this, she has advanced animal detection by adapting the state-of-the-art YOLOv8 deep learning architecture, achieving robust identification of livestock in complex outdoor environments—a key enabler for practical deployment. Beyond agriculture, her research extends to human safety with a computer vision system for hand SOS gesture detection, showcasing her versatility in applying visual recognition to urgent scenarios. With a growing citation impact, del Castillo’s work is pioneering the integration of robotics and AI into sustainable farming, offering tangible solutions for predator deterrence and labor reduction. Her contributions are particularly relevant for researchers in precision agriculture, animal-computer interaction, and field robotics, where her systems promise to transform traditional herding into a data-driven, automated practice.