Emad A. Elsheikh
Papers
7
Total Citations
43
H-Index
4
About
Emad A. Elsheikh is a robotics and control systems researcher whose work centers on autonomous mobile robots, intelligent control algorithms, and embedded systems for real-time applications. His most influential contributions lie in the domain of visual servoing and path planning for non-holonomic wheeled mobile robots (WMRs), where he developed practical algorithms integrating Multi-Stencils Fast Marching for path planning with decentralized fuzzy logic controllers (FLCs) for path following — work that has collectively garnered over 28 citations. His 2016 series of papers established robust frameworks for indoor robot navigation using overhead IP-camera systems, demonstrating practical real-world implementation rather than purely theoretical models. Beyond mobile robotics, Elsheikh has made notable contributions to robot manipulator control, designing embedded adaptive 2-DOF PID controllers supervised by fuzzy logic systems to address real-time nonlinearities and disturbances. His more recent work pushes further into advanced optimization, employing biogeography-based optimization (BBO) for fractional-order interval type-2 fuzzy PID controllers, reflecting a sustained commitment to robust, intelligent control under uncertainty. His integration of deep learning with embedded control for industrial sorting applications underscores a broadening research vision that bridges classical control theory with modern artificial intelligence — positioning him as a versatile contributor to intelligent robotics systems.
Research Focus
Key Achievements
Top Papers
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- 5Embedded Fuzzy PD Controller for Robot Manipulator4 citations · 2021
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