M. A. Massoud
Papers
1
Total Citations
25
H-Index
1
About
M. A. Massoud is a researcher in robotics and intelligent systems, with a primary focus on autonomous navigation and path-planning algorithms. Their most notable contribution is the development of an intelligent maze-solving robot that integrates image processing with graph theory algorithms, enabling the robot to rapidly and reliably determine the shortest path through a line maze. This work, published in 2017 and cited 25 times, addresses a fundamental challenge in mobile robotics: the trade-off between speed and accuracy in real-time navigation. By combining visual data with algorithmic optimization, Massoud's approach allows the robot to efficiently map and traverse complex environments without relying on pre-programmed routes. This research has practical implications for autonomous vehicles, warehouse logistics, and search-and-rescue operations. Massoud's work stands out for its interdisciplinary methodology, bridging computer vision and theoretical graph algorithms to solve a classic robotics problem. Their contributions continue to influence the design of cost-effective, intelligent navigation systems for educational and industrial applications.
Research Focus
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Top Papers
- 1