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This is a Experimental Study study.

October 15, 2025Open Access

KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills

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The method achieves significantly lower tracking errors compared to existing approaches, ensuring more accurate imitation.
By utilizing a bi-level optimization problem, the framework adapts tracking accuracy based on real-time errors.
An asymmetric actor-critic framework is employed for effective policy training in dynamic motion tasks.
The developed control policies are successfully deployed on the Unitree G1 robot, showcasing stable behaviors.

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New framework demonstrates lower tracking errors in humanoid robots imitating Kungfu and dance movements.

Xie et al. (2025) studied this question.

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