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About

Zhenghan Chen is a leading researcher in humanoid robotics, with a focus on achieving natural, lifelike locomotion and whole-body motion imitation. His work addresses the fundamental challenge of bridging the gap between human movement and robotic capability. Chen’s most impactful contribution is his comprehensive review of humanoid robots (2025, 26 citations), which serves as a critical resource for the field, synthesizing progress, challenges, and future directions. He has developed a novel Generative Motion Prior (GMP) that enables natural locomotion without relying on unstable style rewards, a significant advance over previous methods. Chen also introduced a real-time motion and foothold planning framework for legged robots navigating discrete terrain, enhancing autonomy in complex environments. His whole-body motion imitation framework allows full-size humanoid robots to replicate diverse, expressive human movements despite kinematic and dynamic differences. With a citation count exceeding 30, Chen’s work is shaping the next generation of humanoid robots, aiming to make them more autonomous, natural, and capable of seamless interaction with human society.