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This research aims to enhance humanoid robots' balance using a sophisticated learning approach.

December 21, 2025Open Access

HuB: Learning Extreme Humanoid Balance

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This research aims to enhance humanoid robots' balance using a sophisticated learning approach.
Developed HuB, a unified framework integrating reference motion refinement and balance-aware policy learning.
Validated the approach on the Unitree G1 humanoid robot.
Tested performance on balance tasks, including Swallow Balance and Bruce Lee's Kick.
Demonstrated stable performance under physical disturbances like a soccer strike.
Baseline methods failed in achieving stability during the same tasks.

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Our framework improves balance control in humanoids through robust policy learning, suggesting new paths for stable locomotion.

Zhang et al. (2025) studied this question.

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