Papers
8
Total Citations
126
H-Index
6
About
Gunwoo Noh is a leading researcher in the design and optimization of continuum and concentric-tube robots for minimally invasive surgery. His work focuses on overcoming critical challenges in these flexible, needle-like manipulators—particularly instability caused by torsional deformation and the need for variable stiffness. Noh’s most cited paper, “Anisotropic Patterning to Reduce Instability of Concentric-Tube Robots” (2015, 58 citations), introduced a novel approach to patterning tubes to suppress unwanted twisting, directly expanding the safe workspace and tool path for these devices. He has since advanced the field by integrating deep neural networks with metaheuristic optimization to rapidly design patterned tubes that achieve variable stiffness, as seen in his 2021 work on asymmetric patterns (22 citations) and his 2023 DNN-metaheuristics study (17 citations). His 2024 paper on auxetic patterns further pushes the boundaries of tunable mechanical properties. Beyond robotics, Noh has contributed to surgical guidance systems, including a markerless approach for keyhole neurosurgery. His work has garnered over 125 citations, reflecting its impact on making continuum robots more stable, adaptable, and practical for clinical use.
Research Focus
Key Achievements
Top Papers
- 1Anisotropic Patterning to Reduce Instability of Concentric-Tube Robots58 citations · 2015
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- 3Design of patterns in tubular robots using DNN-metaheuristics optimization17 citations · 2023
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