Eyad A. Feilat
Papers
3
Total Citations
135
H-Index
3
About
Eyad A. Feilat is a researcher whose work has made notable contributions to the field of autonomous robotics and intelligent motion planning systems. His research focuses primarily on mobile robot navigation, fuzzy logic systems, and dynamic environment modeling — areas that sit at the intersection of artificial intelligence and robotics engineering. Feilat is perhaps best recognized for his pioneering development of fuzzy potential field methodologies for autonomous mobile robot motion planning. His landmark 2011 paper, "Autonomous Mobile Robot Dynamic Motion Planning Using Hybrid Fuzzy Potential Field," has garnered over 112 citations, establishing it as a significant reference in the robotics community. This work built upon his earlier 2009 research, which introduced a novel fuzzy potential field framework that employs dual fuzzy models to compute attractive and repulsive forces governing robot movement in dynamic environments — a meaningful advance over traditional potential field approaches that struggle with real-world unpredictability. By integrating fuzzy logic with classical potential field theory, Feilat addressed longstanding challenges in robot path planning, particularly in environments where obstacles and targets change over time. His contributions have influenced subsequent research in intelligent navigation systems, making his work an important touchstone for students and engineers developing next-generation autonomous robotic platforms.
Research Focus
Key Achievements
Top Papers
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