Hesham M. El-Batsh
Papers
1
Total Citations
16
H-Index
1
About
Hesham M. El-Batsh is a researcher specializing in robotics, artificial intelligence, and autonomous navigation systems, with a particular focus on intelligent control and obstacle avoidance in dynamic environments. His major contribution lies in developing neural network-based reactive algorithms that enable mobile robots to navigate safely through unknown and unpredictable settings. In his most-cited work, "Mobile Robot Obstacle Avoidance Based on Neural Network with a Standardization Technique" (2021, 16 citations), El-Batsh addresses the critical challenge of real-time adaptation to dynamic obstacles—a key limitation in many traditional path-planning approaches. By implementing online data updating at each step, his method allows robots to respond quickly to sudden environmental changes, mirroring real-world conditions where workspace dynamics are constant. This work stands out for its practical relevance to applications such as autonomous vehicles, warehouse logistics, and search-and-rescue operations. El-Batsh’s research bridges the gap between theoretical neural network models and robust, real-time robotic control, offering a scalable solution for intelligent navigation. His contributions are valuable for students and engineers seeking to understand how AI can enhance robot autonomy in complex, ever-changing environments.
Research Focus
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Top Papers
- 1