Rana Alabdan
Papers
1
Total Citations
10
H-Index
1
About
Rana Alabdan is a researcher whose work lies at the intersection of robotics, artificial intelligence, and autonomous navigation. Her primary research focuses on developing intelligent path planning algorithms for mobile robots operating in complex, obstacle-rich environments. Her most cited work introduces the Generalized Laser Simulator (GLS) algorithm, a novel approach that enables mobile robots to autonomously identify feasible paths while navigating around both static and dynamic obstacles to reach a target. This contribution addresses a critical challenge in robotics: ensuring safe and efficient real-time navigation in unpredictable settings. With her top-cited paper accumulating 10 citations, Alabdan’s research demonstrates practical significance in advancing autonomous systems. Her work is particularly relevant for applications in warehouse logistics, search-and-rescue operations, and autonomous vehicles, where robust obstacle avoidance is essential. By developing algorithms that mimic laser-based sensing for path planning, Alabdan contributes to making mobile robots more reliable and adaptable in real-world scenarios, marking her as an emerging voice in the field of intelligent robotics and control systems.
Research Focus
Key Achievements
Top Papers
- 1