Lazhar Khriji

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About

Lazhar Khriji is a leading figure in mobile robotics and intelligent control systems, whose work has fundamentally advanced autonomous navigation in complex environments. His research focuses on integrating machine learning and computational intelligence to solve the critical challenge of robot navigation, particularly in crowded and unpredictable settings. Khriji’s most influential contribution, "Mobile Robot Navigation Based on Q-Learning Technique" (2011, 51 citations), demonstrates how reinforcement learning can overcome the limitations of traditional navigation methods. This work addresses the critical problem of excessively large state spaces in real-world obstacle-dense environments, providing a robust framework for autonomous decision-making. His earlier foundational study, "A Fuzzy Logic Based Navigation of a Mobile Robot" (2008), established a successful approach for handling both modeled and unmodeled obstacles in dynamic surroundings. Through these contributions, Khriji has shown how combining fuzzy logic with Q-learning can create more adaptive and intelligent navigation systems. His research continues to influence the development of autonomous robots capable of operating safely in human-centric spaces, making him a key contributor to the evolution of intelligent mobile robotics.