Mohamed G Abd Elfatah

Papers

Total Citations

H-Index

About

Mohamed G Abd Elfatah is a researcher focused on advancing mobile robotics through stochastic modeling and estimation techniques. His core research lies at the intersection of mobile robot localization, path planning, and stochastic differential equations (SDEs), with particular emphasis on applications in high-stakes environments. Abd Elfatah’s most significant contribution is the application of the Euler–Maruyama algorithm to estimate mobile robot position in the presence of white noise and time delays—a critical challenge for teleoperated systems. His foundational 2019 paper on this method, cited 7 times, demonstrates its utility for obstacle avoidance and sensor fusion. He further refined this approach with the Milstein algorithm in 2021, offering higher-order accuracy for SDE-based navigation. Notably, his 2023 work extends these techniques to nuclear emergency and security scenarios, integrating radiation sensors for unmanned ground vehicles (UGVs) in hazardous zones. This applied focus highlights the real-world impact of his research, bridging theoretical stochastic calculus with practical, life-saving robotics. With a growing citation record, Abd Elfatah is establishing himself as a specialist in robust, noise-tolerant navigation for autonomous systems operating under uncertainty.