Mohamed Saad Saleh

Papers

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About

Mohamed Saad Saleh is a leading researcher in intelligent robotics and autonomous navigation systems, with a particular focus on adaptive control strategies for mobile robots. His most-cited work, "Optimal Mobile Robot Navigation for Obstacle Avoidance Based on ANFIS Controller," introduces a novel sensor-based steering angle control method that leverages the Adaptive Neuro-Fuzzy Inference System (ANFIS) to enable wheeled robots to navigate dynamic environments while avoiding collisions. This contribution addresses a long-standing challenge in robotics—the movement control of automated wheeled platforms—by integrating fuzzy logic with neural network learning to achieve real-time adaptability. With 3 citations already in its early publication year (2025), this paper signals growing recognition of his approach to merging soft computing techniques with practical robotic applications. Saleh’s research bridges the gap between theoretical control systems and real-world deployment, offering scalable solutions for autonomous navigation in cluttered or unpredictable settings. His work is particularly valuable for students and engineers seeking to understand how hybrid AI models can enhance robot autonomy, making him a notable voice in the evolution of intelligent mobile systems.