Papers
4
Total Citations
35
H-Index
2
About
Da-Un Jung is a robotics researcher whose work centers on the critical challenge of odometry calibration for wheeled mobile robots. His primary research focus is the development of precise, practical methods to correct systematic errors in robot navigation, ensuring that robots can accurately estimate their position and orientation during movement. Jung’s major contribution lies in his innovative use of experimental orientation errors as a calibration metric, a technique that simplifies the calibration process while maintaining high accuracy. His most cited work, "Accurate calibration of systematic errors for car-like mobile robots using experimental orientation errors" (2016), has garnered 22 citations and demonstrates a clear, effective approach for this robot class. He has also designed specialized test tracks for two-wheel differential and car-like robots, as detailed in his 2014 and 2017 papers. By focusing on end-heading errors rather than complex full-trajectory data, Jung’s methods offer a streamlined, reliable solution for improving mobile robot localization—a foundational need in autonomous systems. His research provides a valuable resource for engineers and researchers seeking to enhance robot navigation accuracy in real-world applications.
Research Focus
Key Achievements
Top Papers
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- 4Odometry calibration for car-like mobile robots1 citations · 2017