Hussein Hamdy Shehata
Papers
4
Total Citations
30
H-Index
3
About
Hussein Hamdy Shehata is a robotics researcher whose work centers on autonomous navigation, path planning, and obstacle avoidance for mobile robots operating in dynamic, unknown environments. His major contributions lie in developing intelligent algorithms that enable robots to react safely and efficiently to unpredictable obstacles. His most-cited paper, "Mobile Robot Obstacle Avoidance Based on Neural Network with a Standardization Technique" (2021, 16 citations), introduces a reactive algorithm that updates data online to handle rapidly changing surroundings—a critical capability for real-world applications. Shehata has also advanced multi-objective optimization in robotics, as seen in his work on potential field optimization using genetic algorithms (2014, 9 citations) and smooth path planning via non-dominated sorting genetic algorithms (2014, 3 citations). His research bridges theoretical optimization and practical deployment, with a case study on virtual obstacle parameter optimization (2016, 2 citations) further demonstrating his applied focus. By tackling the core challenge of uncertainty in autonomous navigation, Shehata’s work provides foundational tools for safer, more adaptive robotic systems, making his research valuable for students and engineers developing next-generation autonomous vehicles and service robots.
Research Focus
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Top Papers
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