Papers
2
Total Citations
6
H-Index
2
About
Kamel Guesmi is an emerging researcher specializing in intelligent control systems and mobile robotics, with a particular focus on the development of advanced control methodologies for autonomous robotic platforms. His work centers on bridging fuzzy logic and predictive control techniques to address the complex challenges inherent in nonholonomic mobile robot navigation and trajectory tracking. Guesmi's most notable contributions lie in the design and implementation of fuzzy predictive controllers for differential-drive mobile robots. His research tackles a critical gap in the field — the limitations of linear models when applied to inherently nonlinear nonholonomic systems — by introducing innovative hybrid strategies that combine the interpretability of fuzzy logic with the anticipatory power of predictive control. A particularly distinctive aspect of his work involves managing trajectory tracking across two successive and distinct paths within a shared reference framework, a scenario with significant practical implications for real-world robotic deployment. Though still in the early stages of building his citation profile, with his recent 2023 and 2024 publications each accumulating citations, Guesmi's research addresses timely and practically relevant problems in autonomous systems. His contributions offer promising foundations for students and engineers seeking robust, intelligent solutions for mobile robot path planning and control in dynamic environments.
Research Focus
Key Achievements
Top Papers
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