Fatima Zahrae Saber
Papers
2
Total Citations
15
H-Index
2
About
Fatima Zahrae Saber is a rising researcher at the forefront of autonomous mobile robotics, specializing in the integration of artificial intelligence with navigation systems. Her work bridges classical robotics with cutting-edge deep learning and large language models (LLMs), addressing critical challenges in obstacle avoidance and path planning. Her most-cited survey (2025, 10 citations) provides a comprehensive taxonomy of navigation techniques, from traditional graph-based methods to modern AI-driven approaches, serving as a vital resource for the field. In a subsequent study (2025, 5 citations), Saber introduces an innovative framework that leverages GPT-4.1 mini for waypoint-guided trajectory planning, combined with ensemble learning for action prediction—a solution designed to overcome the memory and computational limitations of conventional algorithms in complex environments. This work exemplifies her ability to harness LLMs for real-time robotic decision-making. Though early in her career, Saber’s contributions are already shaping the next generation of autonomous systems, offering scalable, intelligent solutions that promise to redefine mobile robot navigation in dynamic, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2