Papers

16

Total Citations

145

H-Index

8

About

Laura Celentano is an accomplished researcher whose work spans flexible robot modeling, robust control theory, and uncertain nonlinear systems. Based at the intersection of applied mathematics and robotics engineering, she has made significant contributions to how complex robotic systems are modeled and controlled under real-world uncertainties. Her early work established computationally efficient frameworks for simulating robot dynamics, with her 2006 paper on forward dynamics simulation and her 2011 assumed modes method (26 citations) laying foundational groundwork for flexible robot modeling. She extended this further by tackling robots with varying cross sections and large link deformations, addressing challenges that classical approaches struggled to handle efficiently. Celentano's control theory contributions are equally notable. Her development of pseudo-PD, pseudo-PID, and proportional-integral robust controllers for uncertain MIMO systems — each garnering 10–14 citations — provides engineers with systematic, chattering-free design methods applicable to a broad class of nonlinear systems including industrial robots and scanning devices. Her 2018 unified approach to robust controller design elegantly consolidates these results across diverse engineering applications. Beyond theoretical contributions, her work on a robotic fire-fighting system for tunnels demonstrates a commitment to socially impactful engineering. With a steadily growing citation record, Celentano represents a rigorous and versatile voice in modern control and robotics research.

Research Focus

Key Achievements

8
H-Index
16
Papers
145
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A computationally efficient method for modeling flexible robots based on the assumed modes method
26 citations · 2011
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Naples Federico II, Ingegneria dei Trasporti (Italy), Federico II University Hospital

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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