Fedia Ibrahim

Papers

Total Citations

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About

Fedia Ibrahim is a researcher specializing in intelligent robotics and machine learning, with a particular focus on fault detection and autonomous navigation in mobile systems. Her most-cited work, "Fault detection in wheeled mobile robot based Machine Learning" (2022), has garnered 5 citations and represents a key contribution to the field of robotic reliability. In this study, Ibrahim explores how machine learning algorithms can be applied to identify and diagnose faults in wheeled mobile robots, enhancing their operational safety and autonomy. This work is notable for bridging the gap between traditional control systems and modern data-driven approaches, offering practical solutions for real-world robotic applications. Ibrahim's research addresses critical challenges in robotics, including system robustness and predictive maintenance, which are essential for deploying robots in dynamic environments. While her citation count is modest, her work is gaining traction among international researchers interested in integrating AI with robotics. Ibrahim's contributions are particularly relevant for students and engineers working on autonomous systems, as she demonstrates how machine learning can improve fault tolerance and decision-making in mobile robots. Her research continues to influence the development of safer, more reliable robotic platforms.