N. Hamdan

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About

N. Hamdan is a leading researcher in robotics and autonomous systems, specializing in neural network-based control and path planning for mobile robots and multi-agent groups. Their work addresses critical challenges in uncertain and constrained environments, where traditional algorithms fall short. Hamdan’s most impactful contribution, "Neural Network Based Control System for Robots Group Operating in 2-d Uncertain Environment" (2020, 16 citations), introduces a deep learning framework that enables a team of robots to collaboratively estimate environmental states, optimize path planning, and dynamically adjust trajectories through real-time interaction—a breakthrough for coordinated swarm operations. Complementing this, their 2021 study on "Path planning method for mobile robot with maneuver restrictions" (6 citations) innovatively models velocity-dependent constraints as virtual obstacles, allowing robots to navigate safely at varying speeds. This dual focus on group coordination and individual maneuverability has practical implications for warehouse logistics, search-and-rescue, and autonomous driving. Hamdan’s work is notable for bridging theoretical control theory with deployable neural architectures, earning recognition for advancing robust, adaptive robotics in unpredictable settings.