Chenxi Han

Ph.D. student·Tsinghua University

Chenxi Han

Hi there! I’m Chenxi Han, a Ph.D. student at Tsinghua University. My research focuses on reinforcement learning, imitation learning, and manipulation models for humanoid robots. I am advised by Prof. Houde Liu at the Tsinghua AI & Robot Lab and co-founded ZERITH, where I work on motion control and robot learning. I aim to enable robots to perform tasks more accurately and quickly in real-world settings while continually learning and improving.

Publications

Selected papers on robot learning, design, and control.

  1. Figure from PRIOR: Perceptive Learning for Humanoid Locomotion with Reference Gait Priors

    Chenxi Han*, Shilu He*, Yi Cheng, Linqi Ye, Houde Liu

    PDFarXiv
    Overview

    Combining parameterized gait priors with terrain perception for natural, terrain-adaptive humanoid locomotion.

  2. Figure from PMG: Parameterized Motion Generator for Human-like Locomotion Control

    Chenxi Han*, Yuheng Min*, Zihao Huang, Ao Hong, Hang Liu, Yi Cheng, Houde Liu

    PDFProjectWatch demoarXiv
    Overview

    A compact motion generator that synthesizes human-like reference trajectories for imitation and reinforcement learning.

  3. Figure from Safe expeditious whole-body control of mobile manipulators for collision avoidance

    Bingjie Chen, Yancong Wei, Rihao Liu, Chenxi Han, Houde Liu, Chongkun Xia, Liang Han, Bin Liang

    PDF
    Overview

    A CBF-QP whole-body controller for safe, real-time collision avoidance with mobile manipulators in dynamic environments.

  4. Figure from Structural Optimization of Lightweight Bipedal Robot via SERL

    Yi Cheng*, Chenxi Han*, Yuheng Min, LinQi Ye, Houde Liu†, Hang Liu, Bin Liang

    PDFProjectWatch demoarXiv
    Overview

    Reinforcement learning and evolutionary search for lightweight bipedal robot design and improved locomotion.

  5. Figure from Visual servoing-based pneumatic hair transplantation mechanism for robotic FUE surgery

    Fulin Jia, Shenghao Yang, Chenxi Han, Junye Li, Xuanru Han, Chao Zhang, Jiaole Wang†

    PDFWatch demo
    Overview

    A pneumatic mechanism with visual feedback for precise, automated follicular unit extraction surgery.

Curriculum vitae

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