Jinhong Noh
Papers
2
Total Citations
5
H-Index
2
About
Jinhong Noh is a robotics researcher whose work focuses on enhancing mobile robot autonomy in complex, real-world environments. Her key research areas include LiDAR-based perception, safe navigation, and trajectory planning. Noh’s major contributions address critical challenges in robot mobility: she pioneered a LiDAR point cloud augmentation method that enables robots to detect transparent obstacles like glass walls and doors—a notoriously difficult problem for standard sensors. This work, published in 2022, has already garnered 3 citations for its practical impact on indoor navigation safety. Earlier, in 2015, she developed a novel trajectory planning algorithm for waypoint tracking that accounts for kinematic constraints, offering superior smoothness and robustness over conventional methods. This foundational work, with 2 citations, demonstrated her early focus on bridging theoretical motion planning with real-world applicability. Noh’s research is notable for its direct relevance to mobile robot deployment in human-centric spaces, where glass structures and tight maneuvering are common. Her achievements highlight a career dedicated to making robots safer and more reliable in everyday environments, from warehouses to hospitals.
Research Focus
Key Achievements
Top Papers
- 1
- 2Trajectory planning toward the waypoint for mobile robot2 citations · 2015