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Liu Cao
Hello there! I'm Liu Cao, currently a first-year PhD student in IIIS,
Tsinghua University, advised by Prof. Mengdi Xu on Humanoid Robots and Whole-body Control. Before that, I received
my bachelor's degree from EE, Tsinghua University.
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Repository
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Unified Reference Motion Tracking Policy
We implement a unified reference motion tracking policy for humanoid robots. The whole training framework is built upon Facet, following the data processing pipeline from BeyondMimic and PHC.
humanoid robot
whole-body control
motion tracking
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Research
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Fine-Tuning Hard-to-Simulate Objectives for Quadruped Locomotion:
A Case Study on Total Power Saving
Ruiqian Nai, Jiacheng You, Liu Cao, Hanchen Cui, Shiyuan Zhang, Huazhe Xu, Yang Gao, IEEE International Conference on Robotics and Automation (ICRA), 2025 project page / arXiv Better locomotion using real-world data. Our approach achieves a 24-28% net reduction in power consumption |
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Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated
Robot Response
Junfeng Long*, Zirui Wang*, Quanyi Li, Jiawei Gao, Liu Cao, Jiangmiao Pang *Equal contribution International Conference on Learning Representations (ICLR), 2024 project page / arXiv We present the Hybrid Internal Model, a method enabling the control policy to estimate environmental disturbances by only explicitly estimating velocity and implicitly simulating the system's response. |
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Detecting Vulnerable Nodes in Urban Infrastructure
Interdependent Network
Jinzhu Mao*, Liu Cao*, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li *Equal contribution ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023 code / arXiv We model the interdependent network as a heterogeneous graph and propose a system based on graph neural network with reinforcement learning, which can be trained on real-world data, to characterize the vulnerability of the city system accurately. |
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