George F. Fragulis
Papers
8
Total Citations
301
H-Index
5
About
George F. Fragulis is a researcher working at the intersection of robotics, machine vision, and intelligent control systems, with a growing body of work that spans both theoretical foundations and practical applications. His most influential contribution—a comprehensive 2024 review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition—has amassed an impressive 239 citations, establishing him as a significant voice in the machine and robotic vision community. His research extends into autonomous navigation, where his work on probabilistic visual loop-closure detection addresses a core challenge in simultaneous localization and mapping. Fragulis has also made notable contributions to control theory, developing fuzzy logic controllers for the notoriously difficult double inverted pendulum problem, alongside neural adaptive nonlinear control strategies for bipedal walking robots operating in complex environments. Particularly noteworthy is his humanitarian-oriented research exploring robotic applications in Autism Spectrum Disorder diagnosis and emotion recognition, reflecting a commitment to socially impactful technology. From early mechatronic design projects to cutting-edge deep learning surveys, his trajectory demonstrates a researcher progressively integrating artificial intelligence with robotics to address real-world challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2Sequence-based mapping for probabilistic visual loop-closure detection18 citations · 2021
- 3
- 4
- 5
- 6
- 7A Fuzzy Logic Controller for Double Inverted Pendulum on a Cart4 citations · 2021
- 8