Mohamed Shelkamy
Papers
1
Total Citations
21
H-Index
1
About
Mohamed Shelkamy is a researcher whose work sits at the intersection of robotics, optimization, and artificial intelligence, with a particular focus on the coordination of multi-robot systems. His most cited paper, "Comparative Analysis of Various Optimization Techniques for Solving Multi-Robot Task Allocation Problem" (2020), has garnered 21 citations and addresses one of the most pressing challenges in modern robotics: efficiently assigning tasks to fleets of robots. This work systematically evaluates different optimization methods, providing a critical benchmark for researchers tackling the Multi-Robot Task Allocation (MRTA) problem—a cornerstone for applications ranging from warehouse automation to search-and-rescue missions. By offering a clear comparative framework, Shelkamy’s analysis helps practitioners select the most effective algorithms for real-world deployments. His contributions are particularly timely given the global surge in robotic dependency, and his research serves as a practical guide for advancing autonomous coordination. Through this work, Shelkamy has established himself as a thoughtful contributor to the field, bridging theoretical optimization with actionable insights for multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1