Salim Refoufi

About

Salim Refoufi is a robotics researcher whose work focuses on intelligent control systems, autonomous navigation, and path planning for mobile and manipulator robots. His most influential contribution, "Control of a manipulator robot by neuro-fuzzy subsets form approach control optimized by the genetic algorithms" (2018), has garnered 29 citations, showcasing his expertise in combining neural networks, fuzzy logic, and genetic algorithms to enhance robotic precision and adaptability. Refoufi has also advanced autonomous navigation through hybrid path-planning algorithms, as seen in his 2024 paper on integrating A-Star with artificial potential fields for global and local planning. His comparative studies on trajectory tracking controls for differential wheeled mobile robots (2022) and intelligent navigation using laser and camera sensors (2023) further demonstrate his commitment to robust, sensor-driven solutions. By merging optimization techniques with real-world robotic challenges, Refoufi’s work provides foundational insights for students and researchers in robotics, control theory, and artificial intelligence, bridging theoretical algorithms with practical autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Control of a manipulator robot by neuro-fuzzy subsets form approach control optimized by the genetic algorithms

   29 citations · 2018
2. 2
   Mobile Robot Path Planning Based on A-Star Algorithm and Artificial Potential Field Method for Autonomous Navigation

   3 citations · 2024
3. 3
   A Comparative Trajectory Tracking Controls of a Mobile Robot

   2 citations · 2022
4. 4
   Comparative intelligent Navigation of Pioneer Mobile Robot using laser and camera sensors

   1 citations · 2023

Key Collaborators

Contact & Links