About

Mohammed Mestari is a researcher whose work sits at the intersection of robotics, autonomous systems, and human-robot interaction. His research spans several interconnected areas, including mobile robot navigation, trajectory planning, social robotics, and intelligent sensing, with a particular focus on developing practical computational methods for real-world robotic challenges. Mestari's most significant contributions center on autonomous navigation and path planning for four-wheel robots. Through innovative application of the Decomposition-Coordination (DC) method, he has tackled complex nonlinear optimization problems governing robot kinematics and dynamics, enabling safer obstacle avoidance and more efficient trajectory execution. His 2015 trajectory planning paper, garnering 8 citations, laid foundational groundwork that subsequent studies in reactive path planning have built upon. His most-cited work (20 citations) explores social robots as cyber-physical actors in entertainment and education, reflecting a broader interest in expanding robotics beyond industrial settings into human-centered environments. Complementing this, his research on fuzzy lattice reasoning for human head-pose estimation demonstrates a commitment to advancing the perceptual intelligence necessary for meaningful human-robot interaction. Collectively, Mestari's portfolio signals a researcher steadily building expertise across mobile robotics and socially aware autonomous systems, making his work valuable reading for students navigating these rapidly evolving fields.

Research Focus

Key Achievements

3
H-Index
6
Papers
39
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Social Robots as Cyber-Physical Actors in Entertainment and Education
20 citations · 2019
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Hassan II Casablanca, Université Hassan II Mohammedia, École Normale Supérieure de l'Enseignement Technique de Mohammedia

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago