Francisco M. Campos

Instituto Politécnico de Lisboa

Papers

10

Total Citations

60

H-Index

4

About

Francisco M. Campos is a robotics and engineering education researcher whose work spans robot perception, middleware development, and educational technology. His most impactful research addresses robot visual localization, where he has pioneered the use of non-quantized local image features—such as SIFT—for global localization, demonstrating their superior discriminativity over traditional quantized representations. His 2014 paper on local feature fusion for visual localization, which evaluates multiple classifier combination approaches, has garnered 20 citations and remains his most cited work. Campos has also contributed significantly to multi-robot system development, notably through his work on the FAMOUSO middleware, which enables flexible communication for distributed robotic applications combining real and virtual components. More recently, he has advanced soft robotics with a multifunctional pneumatic gripper for handling sensitive products, and developed Ardosia, an integrated learning platform that combines circuit simulation with robotics to enhance electronics education. His photorealistic digital twin for a tank truck washing robotic system demonstrates his commitment to bridging simulation and real-world industrial applications. Through his diverse contributions, Campos has established himself as a versatile researcher advancing both the theoretical foundations and practical applications of robotics.

Research Focus

Key Achievements

4
H-Index
10
Papers
60
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Robot Visual Localization Through Local Feature Fusion: An Evaluation of Multiple Classifiers Combination Approaches
20 citations · 2014
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Instituto Politécnico de Lisboa

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago