Abdulrahman Alruban
Papers
1
Total Citations
10
H-Index
1
About
Abdulrahman Alruban is a researcher focused on advancing autonomous mobile robotics, with a particular emphasis on intelligent path planning and real-time obstacle avoidance. His most notable contribution is the development of the Generalized Laser Simulator (GLS) algorithm, a novel approach that enables mobile robots to navigate safely and efficiently through environments cluttered with both static and dynamic obstacles. This work, published in 2022 and garnering 10 citations, addresses a critical challenge in robotics: ensuring robust, collision-free navigation without relying on computationally expensive sensors. By simulating laser range-finder data, the GLS algorithm allows robots to identify feasible paths and reach targets reliably, even in unpredictable settings. Alruban’s research sits at the intersection of control systems, artificial intelligence, and sensor simulation, offering practical solutions for real-world deployment in warehouses, search-and-rescue missions, and autonomous transportation. His work is particularly valuable for students and engineers seeking efficient, scalable algorithms for mobile robot autonomy. As the field moves toward more adaptive and resource-constrained systems, Alruban’s contributions provide a solid foundation for future innovations in autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1