About

David Navarro is a researcher whose work spans the intersection of embedded vision systems, robotics, and intelligent automation. His early contributions focused on neuromorphic and bio-inspired hardware, most notably the development of a silicon CMOS retina capable of real-time movement estimation — a compact, efficient circuit fabricated in a standard 0.35 μm CMOS process that demonstrated how biological visual principles could be translated into practical imaging hardware, earning 7 citations. More recently, Navarro has turned his attention to collaborative robotics within the Industry 4.0 paradigm, contributing a trajectory generation system for the UR5 cobot that enables precise motion planning across both 2D and 3D surfaces, reflecting the growing importance of human-robot collaboration in modern manufacturing. His work on the NAO™ humanoid robot further demonstrates his versatility, applying system identification techniques to approximate dynamic models for a commercially closed platform — an achievement that opens new avenues for advanced control strategies on otherwise opaque systems. Across his career, Navarro has consistently bridged low-level hardware design and high-level robotic intelligence, making his research particularly valuable for engineers and students working at the frontier of smart sensing and autonomous systems.

Research Focus

Key Achievements

2
H-Index
3
Papers
13
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
A block matching approach for movement estimation in a CMOS retina: principle and results
7 citations · 2004
📈 Most Prolific Year: 2004 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, Tecnológico de Monterrey

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago