Ki-Baek Lee
Papers
2
Total Citations
35
H-Index
2
About
Ki-Baek Lee is a robotics researcher whose work focuses on the intersection of evolutionary computation and humanoid robot locomotion. His primary research areas include multiobjective optimization for robot navigation, central pattern generator (CPG)-based gait generation, and stable walking pattern synthesis. Lee’s most notable contribution is an online multiobjective evolutionary approach for humanoid robot navigation, which decomposes complex navigation problems into smaller, local multiobjective optimization problems (MOPs)—a novel framework that has garnered 30 citations for its practical efficiency in dynamic environments. In a related line of work, he developed a method for stable walking by integrating evolutionary optimized CPGs with a modifiable walking pattern generator (MWPG), specifically incorporating vertical center of mass (COM) and foot motions to enhance balance and adaptability. Though his citation counts are modest, his work represents a meaningful step toward bridging evolutionary algorithms with real-time robotic control. Lee’s research is particularly relevant for students and engineers interested in bio-inspired locomotion, multiobjective decision-making, and the application of evolutionary techniques to physical systems.
Research Focus
Key Achievements
Top Papers
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