Mohamed Masmoudi
Papers
16
Total Citations
222
H-Index
6
About
Mohamed Masmoudi is a prolific researcher specializing in autonomous mobile robotics, intelligent control systems, and embedded hardware implementation. His work sits at the intersection of artificial intelligence and robotics, with a particular focus on applying fuzzy logic, neural networks, and neuro-fuzzy approaches to real-world navigation challenges. Masmoudi's most celebrated contribution — his 2016 paper on fuzzy logic-based control for autonomous mobile robot navigation, which has garnered 139 citations — introduced a unified trajectory-tracking controller capable of simultaneously handling navigation and obstacle avoidance, a significant departure from conventional dual-controller architectures. His research consistently bridges theoretical AI methodologies with practical hardware deployment, demonstrated through multiple FPGA implementations of fuzzy and fuzzy-PI controllers for mobile and omnidirectional robotic systems. Masmoudi has also made notable advances in vision-based autonomous driving using artificial neural networks and camera-only input systems, as well as versatile autonomous parking algorithms. His repeated focus on newly designed robot prototypes reflects a commitment to end-to-end system development, from mechanical design through intelligent control. Across his body of work, Masmoudi has cultivated a meaningful research legacy in intelligent mechatronics, making his publications particularly valuable for students and engineers exploring embedded AI in robotics.
Research Focus
Key Achievements
Top Papers
- 1Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation139 citations · 2016
- 2FPGA implementation of fuzzy wall-following control10 citations · 2005
- 3
- 4
- 5
- 6Implementations approches of neural networks lane following system7 citations · 2012
- 7
- 8
- 9
- 10