Mohamed Nadour
Papers
7
Total Citations
57
H-Index
5
About
Mohamed Nadour is a researcher specializing in autonomous mobile robotics, with a focus on intelligent navigation systems that integrate fuzzy logic control and computer vision. His work centers on developing robust, biologically inspired solutions for robot motion in complex environments, particularly through the application of Type-1 and Type-2 fuzzy logic controllers and optical flow algorithms. Nadour’s most cited paper (2019, 23 citations) introduces a mobile robot visual navigation system that combines fuzzy logic with optical flow approaches, enabling goal-seeking and obstacle-avoidance behaviors. He has further advanced this field by proposing Takagi-Sugeno fuzzy controllers for autonomous motion and flood-fill algorithms for maze navigation (2022, 8 citations). His recent contributions include comparing Lucas-Kanade and Horn-Schunck optical flow methods for visual navigation (2024, 6 citations) and developing robust fuzzy controllers for differential robot trajectory tracking (2024, 3 citations). With a cumulative citation count exceeding 50, Nadour’s work bridges theoretical fuzzy logic with practical robotic applications, offering scalable frameworks for autonomous systems operating in unstructured environments. His research is particularly valuable for students and engineers seeking to implement vision-based, intelligent control in mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Type-1 and Type-2 Fuzzy Logic Controllers for Autonomous Robotic Motion10 citations · 2019
- 3
- 4Type-1 and Type-2 Fuzzy Techniques: Application to Robotic Systems6 citations · 2023
- 5
- 6
- 7Mobile Robot Visual Navigation Systems using Optical Flow1 citations · 2023