Amr Elsharkawy

Technical University of Munich, Alexandria University

Papers

Total Citations

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About

Amr Elsharkawy is a researcher at the forefront of robotics and precision engineering, with a focus on model-based uncertainty quantification and dynamic systems analysis. His work addresses critical challenges in robotic machining and surgical robotics, where accuracy and reliability are paramount. Elsharkawy's most cited paper, "Methodology for model-based uncertainty quantification of the vibrational properties of machining robots" (2021, 26 citations), introduces a rigorous framework to predict and mitigate vibrational uncertainties in industrial robots, enhancing their performance in high-precision tasks. His earlier study, "Dynamic analysis with optimum trajectory planning of multiple degree-of-freedom surgical micro-robot" (2018, 20 citations), develops kinematic and dynamic models using the Denavit–Hartenberg algorithm and Lagrange techniques to optimize trajectory planning for surgical micro-robots, advancing minimally invasive surgery. Through these contributions, Elsharkawy bridges theoretical modeling with practical applications, offering tools that improve robotic accuracy in both manufacturing and medical domains. His work not only garners citations but also inspires further research into robust robotic systems, making him a notable figure in the intersection of robotics, dynamics, and uncertainty analysis.