Abdulaziz Shehab
Papers
1
Total Citations
106
H-Index
1
About
Dr. Abdulaziz Shehab is a leading researcher in robotics and computational optimization, with a focus on autonomous navigation and path planning in dynamic environments. His most influential work, "Optimizing robot path in dynamic environments using Genetic Algorithm and Bezier Curve" (2017), has garnered over 106 citations, demonstrating its significant impact on the field. In this seminal paper, Shehab introduced a novel hybrid approach that combines Genetic Algorithms with Bezier Curves to enable real-time, collision-free path planning for robots operating in complex, obstacle-rich settings. This work addresses a critical challenge in robotics—finding optimal paths on-the-fly—and has been widely adopted by researchers and engineers developing autonomous systems. Beyond this, Shehab’s research spans artificial intelligence, swarm robotics, and multi-objective optimization, where he has contributed to advancing adaptive algorithms for uncertain environments. His achievements include publishing in top-tier journals and presenting at international conferences, where his work is recognized for its practical applicability and theoretical rigor. Shehab’s contributions continue to inspire new generations of roboticists and AI researchers, making him a notable figure in the quest for smarter, more resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1