Azzeddine Bakdi

Papers

Total Citations

245

H-Index

About

Dr. Azzeddine Bakdi is a leading researcher in robotics and intelligent control systems, with a primary focus on autonomous navigation, path planning, and adaptive control. His most influential work, "Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control" (2016, 245 citations), pioneered a hybrid approach that combines genetic algorithms for global path optimization with adaptive fuzzy-logic controllers for real-time trajectory execution. This seminal contribution addressed critical challenges in mobile robotics, enabling more efficient and robust navigation in dynamic environments. Dr. Bakdi's research has significantly advanced the integration of computational intelligence with control theory, demonstrating how evolutionary algorithms can enhance fuzzy-logic systems for practical robotic applications. His work has been widely adopted in autonomous vehicle research and industrial robotics, with his 2016 paper serving as a foundational reference for subsequent studies in intelligent path planning. Beyond this landmark publication, Dr. Bakdi continues to explore the intersection of machine learning, optimization, and control, contributing to the development of more adaptive and autonomous robotic systems.