Yun Won Choi

Papers

Total Citations

H-Index

About

Yun Won Choi is a robotics researcher specializing in localization, navigation, and sensor fusion for mobile robots. His work centers on developing robust algorithms that enable robots to perceive and move through their environments with greater accuracy. Choi’s major contributions include the creation of an image stabilization system using an Extended Kalman Filter (EKF), which enhances mobile robot stability during movement. He is perhaps best known for his work on Laser Image SLAM (Simultaneous Localization and Mapping), where he proposed a novel algorithm that fuses laser range data with image matching to improve localization precision—a significant advance over traditional encoder-based methods. His research also explores innovative ego-motion estimation techniques using fisheye warping images and Lucas-Kanade Optical Flow, leveraging omnidirectional sensors for real-time, view-based recognition. While his citation counts (ranging from 3 to 7) reflect a focused, early-career impact, Choi’s contributions are technically notable for their practical integration of Kalman filtering, optical flow, and multi-sensor data, offering valuable insights for researchers developing autonomous navigation systems in complex, real-world environments.