Papers

4

Total Citations

42

H-Index

3

About

Pedro Cobos Arribas is a researcher specializing in hardware architectures for real-time computer vision, with a particular focus on FPGA-based systems applied to robotics and autonomous navigation. His work centers on translating computationally intensive vision algorithms into efficient hardware implementations capable of operating at the high frequencies demanded by real-world robotic environments. Among his most notable contributions is the FPGA implementation of the Santos-Victor optical flow algorithm, which demonstrated the viability of deploying sophisticated motion-detection techniques on programmable hardware for robot guidance applications. Building on this, Cobos Arribas developed a versatile FPGA-based development board tailored for real-time vision laboratories, integrating digital camera interfaces and dedicated memory architectures to support rapid prototyping. His 2005 work further extended these capabilities to include obstacle detection through time-to-contact estimation, broadening the practical utility of such systems in control applications. His doctoral research laid the theoretical and architectural foundation for extracting optical invariants from monocular optical flow in active vision systems. Collectively, his publications have accumulated over 40 citations, reflecting steady influence within the specialized community of embedded vision and robotics hardware design. His contributions remain a meaningful reference for researchers developing low-latency vision processing pipelines.

Research Focus

Key Achievements

3
H-Index
4
Papers
42
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
FPGA implementation of Santos-Victor optical flow algorithm for real-time image processing: an useful attempt
16 citations · 2003
📈 Most Prolific Year: 2003 (2 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Universidad Politécnica de Madrid, Centro de Estudios Políticos y Constitucionales

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago