Papers
7
Total Citations
58
H-Index
4
About
Chanyoung Jung is a robotics researcher whose work spans autonomous systems, state estimation, and robot mechanism design. His most significant contribution to date is his development of an adaptive keyframe generation-based LiDAR Inertial Odometry (LIO) algorithm, published in 2023 and already accumulating 25 citations, which enables fast and accurate localization and mapping for both aerial and ground robots operating in challenging underground environments. This work reflects his deep expertise in SLAM and sensor fusion technologies critical to field robotics. Jung's research portfolio demonstrates impressive breadth. His early work on optimizing in-pipe cleaning robot mechanisms (10 citations) addressed practical infrastructure challenges in urban environments, while his involvement with Team CoSTAR's NeBula autonomy solution for the DARPA Subterranean Challenge highlights his contributions to large-scale autonomous exploration. He has also contributed to competitive robotics through the Mohamed Bin Zayed International Robotics Challenge and, more recently, to high-speed autonomous racing as part of Team KAIST at the Indy Autonomous Challenge, pushing the boundaries of perception, planning, and control under extreme conditions. Across these diverse domains, Jung consistently bridges theoretical innovation with real-world robotic deployment.
Research Focus
Key Achievements
Top Papers
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- 2Optimal Mechanism Design of In-pipe Cleaning Robot10 citations · 2012
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