Papers
18
Total Citations
123
H-Index
8
About
Nadia Saadia is a robotics and control systems researcher whose work spans intelligent control, visual servoing, rehabilitation robotics, and human-robot interaction. With a career stretching over two decades, she has made significant contributions to adaptive and robust control methodologies, particularly sliding mode control, fuzzy logic, and neural network-based approaches applied to complex robotic systems. Her early foundational work explored neural network paradigms for trajectory planning and assembly robot control, establishing her commitment to intelligent, model-free approaches for nonlinear systems. She later advanced visual tracking by combining SURF feature detection with image-based visual servoing for robust target tracking (18 citations), and developed adaptive force-vision controllers using fuzzy sliding mode techniques for robot manipulators navigating uncertain environments (14 citations). Her research also extends into medical robotics, including instrumented ultrasound probe systems supporting tele-echography applications (11 citations). More recently, Saadia has directed her expertise toward rehabilitation engineering, designing sophisticated model-free adaptive controllers integrating super-twisting algorithms and RBF/MLP neural networks for 10-DOF lower limb exoskeletons, work that has already attracted notable early citations. Spanning autonomous vehicles, assistive robots with ontology-driven multimodal fusion, and rehabilitation devices, her diverse portfolio reflects a sustained dedication to making intelligent robotic systems safer, more adaptive, and more accessible across clinical and industrial domains.
Research Focus
Key Achievements
Top Papers
- 1Target tracking based on SURF and image based visual servoing18 citations · 2012
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- 6Neural hybrid control of manipulators, stability analysis9 citations · 2001
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- 10A neural network-based approach for an assembly cell control6 citations · 2007