Sanghun Kang
Papers
2
Total Citations
49
H-Index
2
About
Sanghun Kang is a pioneering researcher in bio-inspired robotics and reinforcement learning, whose work bridges the gap between biological flight mechanisms and autonomous drone control. His primary research areas include flapping-wing drone dynamics, sensor-based flight control, and sim-to-real transfer learning. Kang’s most impactful contribution is his 2024 study on wing-strain-based flight control, where he drew inspiration from insect mechanoreceptors (campaniform sensilla) to develop a reinforcement learning framework that enables drones to detect and respond to complex aerodynamic loads—a feat that has garnered 42 citations and represents a significant step toward replicating the wind-sensing abilities of biological flight. Additionally, his 2023 work on optimizing reinforcement learning for the Furuta pendulum demonstrates his expertise in overcoming the temporal and spatial constraints of transferring virtual models to real-world environments, earning 7 citations. Kang’s research not only advances autonomous aerial robotics but also provides a blueprint for integrating biological principles into engineering systems, making his work essential reading for students and researchers interested in the intersection of machine learning, biomechanics, and drone technology.
Research Focus
Key Achievements
Top Papers
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- 2