Papers
6
Total Citations
71
H-Index
4
About
JongHun Choe is a leading roboticist specializing in legged locomotion, robot design optimization, and autonomous mobility. His most impactful work centers on the development of efficient and robust quadruped and bipedal robots, with a focus on bridging the gap between mechanical design and real-time control. Choe’s seminal 2022 paper on the KAIST HOUND quadruped (30 citations) introduced a groundbreaking mixed-integer nonlinear optimization method for gear train design, enabling the robot to achieve a target speed of 3 m/s with minimal energy cost—a key contribution to fast, efficient locomotion. In 2023, his work on a seamless reaction strategy for bipedal walking (22 citations) leveraged Nonlinear Model Predictive Control (NMPC) to integrate ankle, hip, and footstep adjustments, dramatically improving disturbance rejection and robustness in dynamic environments. Earlier, Choe demonstrated his versatility with the TuskBot platform (2017, 8 citations), a novel wheeled robot that uses a passive “tusk” structure to climb stairs of varying dimensions without active sensing—a clever solution to a classic indoor mobility challenge. His research consistently emphasizes practical, optimization-driven design and real-time control, making him a notable figure in advancing agile, resilient robots for complex terrains.
Research Focus
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Top Papers
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