Papers
9
Total Citations
233
H-Index
7
About
Mingeuk Kim is a leading roboticist whose work centers on humanoid robot control, mobile robot stabilization, and autonomous navigation in complex environments. His most impactful contribution came through Team KAIST's success in the DARPA Robotics Challenge Finals, where he helped develop the DRC-HUBO+ system—a feat documented in his most-cited paper (127 citations) that detailed the robot's design and control strategies for disaster-response tasks. Kim pioneered the use of the Zero-Moment Point (ZMP) stabilization method for rapid four-wheeled mobile platforms, enabling high-speed movement without tipping—a breakthrough captured in his 2012 and 2010 papers (21 and 10 citations, respectively). He also advanced human-robot interaction by developing strategies for humanoid robots to drive and egress utility vehicles (11 citations), and created the Optimal Velocity selection using Velocity Obstacle (OVVO) method for navigating crowded dynamic spaces (38 citations). More recently, his work on adaptive multi-robot exploration using edge-weighted path planning (2025) addresses scalability challenges in search-and-rescue and planetary exploration. With over 220 total citations, Kim's research bridges fundamental stability theory with practical, high-stakes applications—from disaster response to autonomous delivery systems.
Research Focus
Key Achievements
Top Papers
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- 6Design and Development of a Variable Configuration Delivery Robot Platform10 citations · 2019
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