Francesc Pozo
Papers
2
Total Citations
8
H-Index
2
About
Francesc Pozo is a leading researcher in structural health monitoring (SHM), machine learning, and control systems for robotic and aerospace applications. His work focuses on developing intelligent, data-driven methods for damage detection and classification in critical structures, particularly for unmanned aerial vehicles (UAVs) and robotic manipulators. A key contribution is his pioneering application of machine learning algorithms to classify structural damage in UAVs, as demonstrated in his highly cited 2017 paper, which has garnered 6 citations for its practical impact on autonomous surveillance and monitoring. Pozo also advanced the field of robot control with his work on computed-torque-plus-compensation-plus-chattering controllers, providing robust solutions for complex manipulator dynamics. His research bridges theoretical control engineering with real-world deployment, addressing challenges in topology optimisation and multiscale analysis. With a career spanning over a decade, Pozo’s contributions are essential reading for students and researchers interested in the intersection of smart robotics, vibration-based damage identification, and adaptive control systems.
Research Focus
Key Achievements
Top Papers
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