Eyad Alkhayat

King Fahd University of Petroleum and Minerals

Papers

Total Citations

H-Index

About

Eyad Alkhayat’s research lies at the intersection of embedded systems, fuzzy logic control, and mobile robotics, with a focus on enabling intelligent navigation in unknown environments. His most cited work, “Design and implementation of fuzzy-logic based obstacle-avoidance and target-reaching algorithms on NI’s embedded-FPGA robotic platform” (2013), demonstrates a pioneering approach to real-time autonomous control. In this study, Alkhayat designed, simulated, and implemented two fuzzy-logic algorithms on an FPGA-based robotic platform: one dedicated to obstacle avoidance, and a more advanced version that simultaneously avoids obstacles while reaching a predefined target. By leveraging the parallel processing power of FPGAs, his work achieved efficient, low-latency decision-making critical for autonomous systems. Though his citation count (6) is modest, the research represents a foundational contribution to embedded fuzzy control, showcasing how hardware-software co-design can enhance robot autonomy. Alkhayat’s work is particularly notable for its practical implementation on National Instruments’ embedded-FPGA platform, bridging theoretical fuzzy logic with real-world robotic applications. His contributions offer valuable insights for students and researchers exploring embedded intelligence, real-time control, and autonomous navigation in resource-constrained environments.