Renzo Fabrizio Carpio
Papers
6
Total Citations
167
H-Index
5
About
Renzo Fabrizio Carpio is a leading researcher at the intersection of precision agriculture, robotics, and artificial intelligence, whose work is transforming how we manage complex farming systems. His primary contributions lie in developing data-driven pest detection and autonomous robotic solutions for large-scale orchards, particularly hazelnut cultivation. Carpio’s most influential work, a YOLO-based pest detection system (97 citations), pioneered early pest identification using deep learning, directly supporting the H2020 European Project PANTHEON. He further advanced the field by formulating a multi-Steiner Traveling Salesman Problem for route optimization (32 citations), enabling heterogeneous robots to efficiently cover agricultural tasks. His integrated pest monitoring system (14 citations) and autonomous spraying robot architecture for sucker management (14 citations) demonstrate a comprehensive approach to precision farming, from detection to intervention. Earlier work on swarm aggregation algorithms for bar-shaped multi-agent systems (6 citations) and task allocation frameworks (4 citations) rounds out his expertise in multi-robot coordination. Carpio’s research is notable for its direct impact on sustainable agriculture, offering scalable, real-world solutions that reduce chemical use and improve crop yields through intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1A YOLO-Based Pest Detection System for Precision Agriculture97 citations · 2021
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