Jeong Won Choi

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About

Jeong Won Choi is a robotics researcher whose work focuses on advancing localization and perception for autonomous systems using unconventional visual sensors. His key research areas include ego-motion estimation, omnidirectional vision, and real-time robotic navigation. Choi’s major contribution is a novel localization algorithm that leverages Lucas-Kanade Optical Flow and warped images from fisheye lenses mounted on robots, enabling accurate position tracking without relying on external landmarks. By exploiting the wide field of view of omnidirectional image sensors, his approach enhances real-time view-based recognition, a critical capability for robots operating in dynamic environments. His most-cited paper, “Localization using Ego Motion based on Fisheye Warping Image” (2014), has garnered 3 citations, reflecting its foundational role in sensor-based navigation research. This work demonstrates Choi’s ability to integrate computer vision techniques with practical robotic constraints, offering a cost-effective solution for autonomous localization. His achievements highlight the potential of fish-eye cameras in reducing computational load while maintaining robustness, making his contributions valuable for students and researchers exploring visual odometry and sensor fusion in mobile robotics.