Mohamed Elhoseny
Papers
5
Total Citations
432
H-Index
5
About
Mohamed Elhoseny is a leading researcher in robotics, artificial intelligence, and precision agriculture, whose work bridges autonomous systems and real-world applications. His most influential contributions center on optimizing robot path planning in dynamic environments, where he pioneered the use of Bezier curves combined with modified Genetic Algorithms (GA). His seminal 2017 paper on this topic has garnered 266 citations, establishing a foundational approach for enabling robots to navigate complex, obstacle-filled spaces efficiently. Elhoseny further advanced the field by exploring collaborative task assignment for interconnected, affective robots, targeting autonomous healthcare assistance—a domain with significant societal impact. Beyond robotics, he has applied embedded systems and autonomous low-cost robots to precision agriculture, developing tools for greenhouse monitoring and soil mapping that enhance agricultural efficiency and sustainability. With over 400 total citations, Elhoseny’s work demonstrates a clear trajectory from algorithmic innovation to practical deployment. His research not only solves core challenges in autonomous navigation but also translates these solutions into tangible benefits for healthcare and agriculture, making him a pivotal figure in applied robotics and intelligent systems.
Research Focus
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