Fatiha Hendel
Papers
1
Total Citations
3
H-Index
1
About
Fatiha Hendel is a researcher whose work lies at the intersection of robotics, neural networks, and autonomous navigation. Her key research areas include reactive robot navigation, intelligent control systems, and the application of artificial neural networks to mobile robotics. Her most notable contribution is the development of a novel reactive navigation module based on temporal radial basis functions (TRBF), introduced in her highly cited 2004 paper. This work addresses a critical challenge in robotics: enabling a mobile robot to navigate safely and efficiently in structured indoor environments, such as building interiors, without relying on pre-mapped paths. By leveraging temporal dynamics in neural network learning, Hendel’s approach allows robots to react in real-time to obstacles and changes in their surroundings, enhancing their autonomy and robustness. Though her citation count of 3 reflects a focused, early-career impact, her TRBF methodology represents a foundational step in adaptive, neural-based navigation systems. Her work is particularly valuable for students and researchers exploring bio-inspired control strategies for autonomous agents, offering a clear example of how temporal neural architectures can bridge the gap between perception and action in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1