Fahad Alblehai
Papers
2
Total Citations
6
H-Index
1
About
Fahad Alblehai is a rising researcher at the intersection of medical robotics and intelligent control systems. His work focuses on enhancing robotic autonomy and human-robot interaction through advanced deep learning and optimization algorithms. Alblehai’s most prominent contribution, published in 2025, introduces a novel method for controlling spider-like medical robots by combining Capsule Neural Networks (CNNs) with a Modified Spring Search Algorithm (MSSA). This approach achieves remarkable efficiency in gesture recognition, enabling precise and intuitive control for delicate medical procedures. The paper has already garnered 5 citations, signaling its early impact in the field. In related work, Alblehai addressed a critical challenge in robotic navigation by proposing a dynamic obstacle avoidance method using YOLOv5-based object detection. This study, published in 2024, tackles the persistent problem of unknown background interference in complex environments, offering a robust solution for real-time navigation. While his citation counts are currently modest, Alblehai’s innovative integration of capsule networks with bio-inspired optimization marks a promising direction for next-generation medical robotics, positioning him as a researcher to watch in the evolving landscape of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2