Najat Al-rashed
Papers
1
Total Citations
4
H-Index
1
About
Najat Al-rashed is a robotics researcher whose work focuses on intelligent control systems for autonomous navigation in challenging environments. Her key contributions lie in applying bio-inspired optimization algorithms—such as the Bacterial Foraging Algorithm (BFA)—to enhance the performance of fuzzy logic controllers for mobile robots. In her most cited paper, "BFA optimized intelligent controller for path following unicycle robot over irregular terrains" (2015, 4 citations), she addresses a critical gap in robotics: the difficulty of path tracking on uneven, non-regular surfaces. By integrating BFA with a hybrid fuzzy controller, she demonstrates improved adaptability and precision for differential drive robots operating in real-world, unstructured terrains. This work is notable for moving beyond idealized laboratory conditions toward practical, off-road applications. Al-rashed’s research sits at the intersection of computational intelligence and field robotics, offering solutions that are both theoretically sound and practically deployable. Her contributions are valuable for students and researchers interested in autonomous systems, optimization-driven control, and the challenges of robot mobility in irregular environments.
Research Focus
Key Achievements
Top Papers
- 1