Papers
2
Total Citations
45
H-Index
2
About
Min-Jae Lee is a pioneering researcher in robotics, specializing in motion planning and humanoid robot control. His work addresses critical challenges in autonomous navigation and stable human-robot interaction. Lee’s most influential contribution, “Experimental evaluation of robot path planning by artificial potential field approach with simulated annealing” (2003, 37 citations), tackles the notorious local minima problem in artificial potential field methods. By integrating simulated annealing, he developed a more robust path planner that enables robots to escape traps and reach goals efficiently—a foundational advance for practical motion planning. In his later work, “Whole body imitation of human motion with humanoid robot via ZMP stability criterion” (2015, 8 citations), Lee focused on real-time human motion imitation using the KIBO humanoid. He introduced zero moment point (ZMP) stability criteria to prevent falls, enabling safer and more natural human-robot interaction. This research bridges the gap between human motion capture and stable robot execution, with implications for assistive robotics and entertainment. Lee’s contributions have shaped both theoretical frameworks and practical implementations in robotics, inspiring further work on adaptive and stable robot behaviors.
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