Baidaa AlKhlidi

Papers

Total Citations

H-Index

About

Baidaa AlKhlidi is a researcher focused on advancing autonomous navigation and intelligent robotic systems. Her primary research areas include optimal robotic path planning, swarm intelligence algorithms, and fuzzy logic optimization. Her most notable contribution is the development of an Adjusted Fuzzy Particle Swarm Optimization (FPSO) algorithm, which addresses the complex challenge of determining the shortest, most time-efficient path for mobile robots navigating obstacle-filled environments. This work, detailed in her highly cited 2021 paper, has garnered significant attention, accumulating 11 citations and demonstrating its impact on the field of robotics and artificial intelligence. By integrating fuzzy logic with particle swarm optimization, AlKhlidi has provided a robust solution for real-time route planning that balances efficiency and adaptability. Her research holds practical implications for autonomous vehicles, warehouse logistics, and search-and-rescue operations. With a growing citation record and a focus on intelligent search algorithms, Baidaa AlKhlidi is establishing herself as a promising voice in the intersection of computational intelligence and robotics, offering innovative tools for the next generation of autonomous systems.