Souhaib Louda
Papers
2
Total Citations
5
H-Index
2
About
Souhaib Louda is advancing the frontier of autonomous mobile robotics through innovative control and path-planning strategies. His research centers on intelligent navigation, trajectory tracking, and obstacle avoidance, with a particular focus on overcoming the computational and model-dependent limitations of classical algorithms. In his highly cited 2024 work, Louda introduced a hybrid path-planning framework that synergizes the A-Star algorithm with the Artificial Potential Field method, enabling robust global and local navigation. He further refined autonomous control in a 2025 study by integrating fuzzy logic with Dynamic Feedback Linearization, creating an adaptive system that efficiently handles trajectory tracking and real-time obstacle avoidance with reduced computational overhead. Though early in his career, his contributions are already gaining traction, with his papers accumulating citations that signal growing influence in the field. Louda’s work is particularly notable for its practical applicability, offering computationally efficient solutions that bridge the gap between theoretical control methods and real-world robotic deployment. For students and researchers, his research provides a compelling blueprint for building more intelligent, responsive, and resource-efficient autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2