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About

Atef Hamouda is a leading researcher in mobile robotics, specializing in path planning and navigation for autonomous systems. His core contributions lie in developing novel algorithms that generate smooth, feasible, and optimal trajectories for mobile robots in static environments. Hamouda’s work is distinguished by his pioneering use of Non-Uniform Rational B-Splines (NURBS) curves—a powerful mathematical tool from computer-aided design—to replace traditional, jagged polyline paths with continuous, curvature-optimized routes. His most influential paper, “A New Path Generation Algorithm Based on Accurate NURBS Curves” (2016, 17 citations), introduces a roadmap algorithm that transforms shortest-path polylines into smooth, dynamically feasible trajectories. This work, along with his multi-objective and genetic algorithm-based approaches (e.g., “NURBS Based Multi-objective Path Planning,” 6 citations), demonstrates how NURBS can simultaneously optimize path length, smoothness, and safety. By bridging graph-based planning with advanced curve modeling, Hamouda has provided a robust framework for real-world robot navigation, impacting fields from warehouse automation to autonomous vehicles. His research remains a key reference for engineers seeking to balance computational efficiency with path quality.