Mohamed Jallouli
Papers
9
Total Citations
63
H-Index
5
About
Mohamed Jallouli is a robotics researcher whose work centers on autonomous mobile robot navigation, intelligent control systems, and motion planning. Over more than a decade of scholarly output, he has made significant contributions to the intersection of fuzzy logic, genetic algorithms, and reactive control strategies for robotic systems operating in complex, real-world environments. Jallouli's most influential work focuses on developing hierarchical and hybrid fuzzy logic controllers (HFLC and FLC) optimized through genetic algorithms to enable mobile robots to navigate efficiently toward targets while avoiding obstacles — a challenge at the heart of autonomous robotics. His 2016 paper on optimal trajectory planning using HFLC has garnered 14 citations, while his work on intelligent mobile manipulator navigation using adaptive-fuzzy control follows closely with 13. His early 2009 contributions laid foundational groundwork in genetic-design fuzzy controllers, collectively accumulating further recognition from the research community. A distinctive thread in Jallouli's research is the Deformable Virtual Zone (DVZ) framework, which he applied to wheelchair robots and omnidirectional platforms, merging safety-aware reactive behaviors with fuzzy control. His combined encoder and visual control approach to robot localization further demonstrates his breadth across perception, planning, and control — making his body of work an important reference for researchers advancing intelligent, real-world robot autonomy.
Research Focus
Key Achievements
Top Papers
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- 7DVZ-based obstacle avoidance control of a wheelchair mobile robot5 citations · 2011
- 8An effective fuzzy-DVZ controller for an omnidirectional mobile robot4 citations · 2012
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