Rania Zouaoui

Papers

Total Citations

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About

Rania Zouaoui is a researcher whose work lies at the intersection of robotics, computer vision, and intelligent control systems. Her primary research focuses on visual servoing for mobile robots, particularly the Koala platform, where she has pioneered the use of radial basis function (RBF) neural networks to enhance 2D visual servoing performance. Her most cited paper, "2D Visual Servoing of Wheeled Mobile Robot by Neural Networks" (2013, 5 citations), addresses a critical challenge in robotics: the interaction matrix that governs the relationship between camera motion and visual feature changes. By integrating neural networks, Zouaoui’s work enables more adaptive and robust robot navigation in dynamic environments, reducing reliance on precise system models. This contribution is particularly valuable for applications in autonomous navigation and industrial automation, where real-time visual feedback is essential. While her citation count reflects a focused, early-career impact, her methodological innovation—combining neural network learning with classical visual servoing—offers a foundation for future advancements in intelligent robotics. Her research continues to inspire students and researchers exploring the synergy between machine learning and robotic control systems.