Ehab Said
Papers
5
Total Citations
167
H-Index
3
About
Ehab Said is a robotics researcher specializing in autonomous navigation, trajectory tracking, and motion control for mobile robots operating in complex environments. His work focuses on tracked and legged robotic platforms, with key contributions in path planning, kinematic modeling, and control system optimization. Said’s most-cited paper, “ROS-based trajectory tracking control for autonomous tracked vehicle using optimized backstepping and sliding mode control” (2022), has garnered 121 citations, demonstrating significant impact in the field of robust control for off-road autonomous vehicles. He also developed a real-time path planning approach using teaching–learning-based optimization (2022, 35 citations), which efficiently balances path smoothness and obstacle avoidance in cluttered settings. Earlier work includes indoor path planning for tracked mobile robots using Dijkstra’s algorithm and ROS (2021), and kinematic modeling of multi-turning gaits for hexapod walking robots (2024). His recent research on optimal trajectory tracking using modified PID and backstepping control (2025) addresses challenges in military and search-and-rescue applications. Said’s integration of optimization algorithms with ROS-based implementations makes his work highly relevant for students and researchers advancing autonomous ground vehicle technologies.
Research Focus
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