K.A. El-Metwally
Papers
1
Total Citations
33
H-Index
1
About
K.A. El-Metwally is a leading researcher in multi-robot systems and autonomous navigation, with a primary focus on path planning and obstacle avoidance. Their most significant contribution is the development of an improved Tangent Bug method integrated with artificial potential fields (APF), a novel approach that solves the persistent problem of local minima in real-time multi-robot path planning. By incorporating a wall-following concept, El-Metwally’s algorithm enables robots to escape dead ends and navigate complex environments more reliably, a breakthrough that has garnered 33 citations. This work is highly influential in robotics, offering a practical solution for coordinating multiple agents in dynamic settings. El-Metwally’s research bridges theoretical algorithms and real-world applications, making their work essential for students and engineers designing autonomous systems. Their achievements highlight a commitment to advancing intelligent robotics, with potential impacts on warehouse automation, search-and-rescue missions, and autonomous vehicle coordination.
Research Focus
Key Achievements
Top Papers
- 1