Feten Hmeyda
Papers
1
Total Citations
6
H-Index
1
About
Feten Hmeyda is a researcher specializing in autonomous robotics, control systems, and intelligent path planning. Her work focuses on integrating computer vision and optimization algorithms to enhance mobile robot navigation. Her most-cited paper, "Camera-based autonomous mobile robot path planning and trajectory tracking using PSO algorithm and PID controller" (2017, 6 citations), introduces a novel method that uses a USB camera to capture top-view images of a robot’s environment, processes them to detect static obstacles, and employs Particle Swarm Optimization (PSO) alongside PID control to generate safe, optimal paths. This contribution bridges image processing and control theory, offering a practical solution for real-time autonomous navigation. Hmeyda’s research demonstrates the potential of combining low-cost hardware with intelligent algorithms, making robotics more accessible. Her work has been cited in studies exploring similar hybrid control approaches, highlighting its relevance in advancing autonomous systems. Through her innovative integration of camera-based perception and optimization-driven control, Hmeyda continues to contribute to the development of smarter, more efficient mobile robots.
Research Focus
Key Achievements
Top Papers
- 1