Carlos Cerrada

Universidad Nacional de Educación a Distancia

Papers

4

Total Citations

15

H-Index

3

About

Carlos Cerrada’s research lies at the intersection of robotics, computer vision, and 3D scene understanding, with a focus on enabling machines to perceive and interact with complex environments. His major contributions include developing methods for moving surface extraction using hexagonal perfect submaps projection, a technique that advanced 3D feature tracking for dynamic scenes. In visual servoing, Cerrada pioneered well-structured control strategies that integrate CCD cameras with robot manipulators, addressing the closed-loop dynamics challenges posed by computer vision feedback—a foundational step toward precise, vision-guided automation. He also introduced the objects layout graph for parsing 3D complex scenes from single range images, tackling obstacles like occlusion, cluttering, and oblique surfaces without shape restrictions. His work on distributed control systems for experimental robotic cells with 3D vision further underscores his commitment to practical, integrated robotics. While his citation counts (ranging from 2 to 5) reflect a focused, niche impact, Cerrada’s contributions are notable for their technical rigor and early exploration of challenges—such as real-time 3D tracking and unstructured scene analysis—that remain central to modern robotics and autonomous systems.

Research Focus

Key Achievements

3
H-Index
4
Papers
15
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Moving surface extraction based on unordered hexagonal perfect submaps projection: Applications to 3D feature tracking
5 citations · 2008
📈 Most Prolific Year: 2008 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Universidad Nacional de Educación a Distancia

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago