Hee‐Hyol Lee
Papers
7
Total Citations
79
H-Index
5
About
Hee-Hyol Lee is a pioneering robotics researcher whose work bridges the critical gap between autonomous navigation and assistive healthcare technologies. His primary research areas include path planning for disaster response robots, multi-robot coordination, and wearable assistive devices for rehabilitation. Lee’s most impactful contribution is the development of the Adaptive Informed RRT* algorithm, which introduces elliptical sampling pools to achieve asymptotically optimal path planning in narrow passages—a breakthrough that has garnered 22 citations since 2024. For large-scale disaster scenarios, he created the auto-splitting D* lite method, enabling rescue robots to efficiently navigate dynamic, partially known environments while avoiding unnecessary exploration. In healthcare robotics, Lee designed an ankle assistive robot with an instantly gait-adaptive method (11 citations) and a Kinect-based motion recognition system using Kalman filters for upper-limb support, demonstrating his commitment to addressing aging populations’ needs. His work on multi-robot-multi-target path planning for disaster areas, which integrates A* algorithm optimization with Kalman filter position estimation, has been cited 8 times. Lee’s research consistently emphasizes practical, real-world applications—from cooperative robot group behavior control to neural-network-driven path planning—making him a key figure in advancing both autonomous systems and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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- 2Auto-splitting D* lite path planning for large disaster area22 citations · 2022
- 3Development of an Ankle Assistive Robot with Instantly Gait-Adaptive Method11 citations · 2023
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