Mohamed Talea
Papers
3
Total Citations
17
H-Index
2
About
Mohamed Talea is a leading researcher at the intersection of multi-robot systems, task allocation, and warehouse automation. His work focuses on developing intelligent coordination frameworks that improve the fairness, efficiency, and scalability of heterogeneous robotic teams. In his highly cited 2023 paper, Talea introduced a novel method for multi-robot task allocation that goes beyond conventional efficiency metrics to balance task distribution across robots—enhancing system fairness, speed, and cost-effectiveness. This work has garnered 14 citations, reflecting its significance in addressing real-world coordination challenges. More recently, Talea has advanced the field of logistics automation with a 2025 study proposing an integrated framework for autonomous pick-and-deliver tasks in warehouses, tackling the dual challenges of task allocation and path planning to optimize picking speed and energy use. He has also explored the extension of neutrosophic graph theory to robotic systems, demonstrating a commitment to foundational mathematical tools for uncertain environments. Talea’s research is essential reading for engineers and scientists working on scalable, fair, and practical multi-robot coordination.
Research Focus
Key Achievements
Top Papers
- 1
- 2Trends on Extension and Applications of Neutrosophic Graphs to Robots2 citations · 2021
- 3