Papers
17
Total Citations
142
H-Index
8
About
Jeong-Jung Kim is a robotics researcher whose work spans bipedal locomotion, human-robot interaction, and agricultural automation. His most influential contributions focus on bio-inspired control methods for walking robots, particularly through the use of Central Pattern Generators (CPG) and Particle Swarm Optimization (PSO). His 2009 paper on CPG parameter search using nonparametric estimation-based PSO (36 citations) remains his most cited work, demonstrating a novel approach to optimizing biped walking gaits. Kim has also made significant advances in push recovery and fall avoidance for humanoid robots, developing state classification methods using support vector machines to detect and prevent falls. In human-robot collaboration, he applied fuzzy logic to damping controllers for safer physical interaction. More recently, Kim has explored smart greenhouse automation, analyzing work efficiency of heterogeneous robot teams for crop harvesting (2022). His diverse portfolio includes work on modular manipulation systems and collision-free path planning for 7-DOF manipulators. With over 120 total citations across his publications, Kim’s research continues to bridge the gap between theoretical control methods and practical robotic applications in both industrial and agricultural settings.
Research Focus
Key Achievements
Top Papers
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- 2An Artificial Pneumatic Muscle Control Method on the Limited Space18 citations · 2006
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- 4Continuous steps toward humanoid push recovery11 citations · 2009
- 5Falling avoidance of biped robot using state classification10 citations · 2008
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