Mamoun Adel Hafez

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About

Mamoun Adel Hafez is a leading researcher in mobile robotics and intelligent control systems, with a particular focus on real-time path planning and obstacle avoidance for autonomous agents operating in dynamic indoor environments. His most-cited work, "A reduced cascaded fuzzy logic controller for dynamic window weights optimization" (2018, 16 citations), addresses a critical challenge in robotics: enabling mobile robots to navigate safely and efficiently under strict processing constraints. Hafez advanced the dynamic window approach—a cornerstone technique for collision-free navigation—by introducing a cascaded fuzzy logic controller that dynamically optimizes the weights of the objective function used to select the robot’s optimal velocity. This innovation significantly improves the robot’s ability to adapt to changing surroundings without sacrificing computational speed. His contributions are particularly valuable for applications requiring rapid decision-making, such as service robotics and autonomous exploration. By bridging fuzzy logic with real-time control, Hafez has provided a practical framework that enhances both the safety and performance of autonomous mobile systems, marking him as a notable figure in the field of intelligent robotics.