Papers

10

Total Citations

66

H-Index

4

About

Seong Hyeon Hong is a robotics researcher whose work sits at the intersection of autonomous navigation, intelligent manufacturing, and edge computing. His primary contributions lie in two key areas: developing efficient path planning algorithms for mobile robots and creating sophisticated anomaly detection systems for robotic manipulators. In path planning, Hong pioneered hybrid approaches that combine adaptive visibility graphs with genetic algorithms and Dijkstra’s method, achieving faster computation by offloading initialization to edge computing platforms—work that has garnered over 25 citations. His most impactful research, however, focuses on operational health monitoring: he introduced generative adversarial network (GAN)-based frameworks that audit energy consumption as a side-channel to detect cyber and physical anomalies in robotic manipulators. This energy auditing approach, detailed in multiple papers accumulating over 30 citations, offers a non-intrusive way to safeguard smart manufacturing systems. Hong also developed a low-cost indoor positioning system using overhead cameras and ArUco markers, making robotics research more accessible for education. His recent work extends to ANN-based model predictive visual servoing, demonstrating a sustained commitment to bridging AI and practical robotics.

Research Focus

Key Achievements

4
H-Index
10
Papers
66
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Hybrid path planning based on adaptive visibility graph initialization and edge computing for mobile robots
20 citations · 2023
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Florida Institute of Technology, University of South Carolina

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago