Mhamed Sayyouri
Papers
8
Total Citations
51
H-Index
4
About
Mhamed Sayyouri is a rising force in robotics and intelligent control, whose work bridges computer vision, optimization, and autonomous systems. His primary research focuses on visual servoing—using camera feedback to guide robot motion—and the application of advanced metaheuristic algorithms for precise control. Sayyouri’s most influential contribution, "Image-Based Visual Servoing Techniques for Robot Control" (2022, 14 citations), provides a comprehensive comparison of geometric-primitive-based methods, establishing a foundational reference for the field. He further advanced this domain with "Image Registration Using the Arithmetic Optimization Algorithm for Robotic Visual Servoing" (2025, 12 citations), introducing a novel intensity-based registration technique that enhances robotic perception. In mobile robotics, his "Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots" (2025, 12 citations) demonstrates a significant leap in trajectory tracking and stability by integrating chaotic dynamics into optimization. Sayyouri also tackles classic challenges, such as the singularity problem in planar robots, with metaheuristic solutions. His recent work on FPGA-based real-time optimization showcases his push toward hardware-accelerated, context-aware systems. With a growing citation record and a portfolio spanning manipulators, mobile robots, and embedded intelligence, Sayyouri is establishing himself as a key innovator in next-generation robotic control.
Research Focus
Key Achievements
Top Papers
- 1Image-Based Visual Servoing Techniques for Robot Control14 citations · 2022
- 2
- 3Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots12 citations · 2025
- 4
- 5Visual Servoing of a 3R Robot by Metaheuristic Algorithms3 citations · 2023
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