Papers
20
Total Citations
229
H-Index
10
About
Sung-Eui Yoon is a leading researcher in robotics and artificial intelligence, whose work spans motion planning, sound source localization, and human-robot interaction. His major contributions include developing novel algorithms for path planning in complex environments, such as the selective retraction-based RRT planner that efficiently navigates narrow passages, and the anytime RRBT for handling uncertainty and dynamic obstacles. Yoon has also pioneered reflection-aware and diffraction-aware sound localization methods, enabling robots to pinpoint sound sources in challenging indoor and non-line-of-sight conditions. His work on real-time collision-free inverse kinematics (RCIK) using deep learning has achieved significant impact, with over 19 citations. With a total of more than 189 citations across his top papers, Yoon’s research is highly influential, particularly in advancing robot navigation, task planning, and sensor-based perception. Notable achievements include his optimization-based path planning for person following and kinodynamic comfort trajectory planning for car-like robots, which address practical challenges in service robotics and autonomous mobility.
Research Focus
Key Achievements
Top Papers
- 1Reflection-Aware Sound Source Localization42 citations · 2018
- 2A Selective Retraction-Based RRT Planner for Various Environments33 citations · 2014
- 3
- 4Anytime RRBT for handling uncertainty and dynamic objects16 citations · 2016
- 5Optimization-based Path Planning for Person Following using Following Field15 citations · 2020
- 6Diffraction-Aware Sound Localization for a Non-Line-of-Sight Source14 citations · 2019
- 7Kinodynamic Comfort Trajectory Planning for Car-Like Robots14 citations · 2018
- 8Automated task planning using object arrangement optimization13 citations · 2018
- 9
- 10