Jo-Hwan Kim
Papers
2
Total Citations
11
H-Index
2
About
Jo-Hwan Kim is a robotics researcher whose work centers on humanoid locomotion, trajectory generation, and bipedal stability. His major contributions lie in developing efficient, optimal motion planning algorithms that enable humanoid robots to perform complex tasks such as ascending and descending staircases and executing directional turns during walking. In his most cited work, "Generation of optimal trajectories for ascending and descending a stair of a humanoid based on uDEAS" (2009, 8 citations), Kim introduced a blending polynomial approach combined with the univariate dynamic encoding algorithm for searches (uDEAS) to generate stable, efficient stair-climbing gaits for commercial humanoids. This work addresses a critical challenge in real-world humanoid deployment: navigating uneven terrain. Building on this foundation, his subsequent paper "A New Trajectory Generation Scheme for Direction Turning in Biped Walking" (2010, 3 citations) extended his methodology to include turning motions, adding sagittal plane joints to the robot model to maintain stability while changing direction. Though his citation counts are modest, Kim’s contributions are notable for their practical focus on implementing theoretically sound control strategies on physical robots, bridging the gap between simulation and real-world humanoid performance.
Research Focus
Key Achievements
Top Papers
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