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SPRINT framework enables humanoid robots to sprint at 6 m/s

By PulseAugur Editorial · [2 sources] ·

Researchers have developed SPRINT, a new framework that uses efficient, frequency-adaptive spectral priors to enable humanoid robots to perform athletic sprints. This approach addresses the lack of suitable kinematic data and stability issues in existing systems by characterizing human locomotion in the frequency domain. The SPRINT policy demonstrated zero-shot sim-to-real transfer on the Unitree G1 platform, achieving a peak sprinting speed of 6 m/s while maintaining natural movement. AI

IMPACT Establishes frequency-adaptive spectral priors as a data-efficient method for humanoid robot locomotion.

RANK_REASON The cluster contains an academic paper detailing a new framework and its experimental results.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

SPRINT framework enables humanoid robots to sprint at 6 m/s

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The cluster contains an academic paper detailing a new framework and its experimental results.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Yantong Wei, Kaihong Huang, Hainan Pan, Jiawei Luo, Jiawei Zhou, Ziyan Mai, Zhiwen Zeng, Yaonan Wang, Huimin Lu ·

    SPRINT: Efficient Spectral Priors for Humanoid Athletic Sprints

    arXiv:2605.28549v1 Announce Type: cross Abstract: The pursuit of humanoid athletic sprints is hindered by a scarcity of humanoid-viable kinematic reference data and the inability of existing frameworks to maintain stability during sprints. To overcome these limitations, we introd…

  2. arXiv cs.LG TIER_1 English(EN) · Huimin Lu ·

    SPRINT: Efficient Spectral Priors for Humanoid Athletic Sprints

    The pursuit of humanoid athletic sprints is hindered by a scarcity of humanoid-viable kinematic reference data and the inability of existing frameworks to maintain stability during sprints. To overcome these limitations, we introduce SPRINT, a novel framework driven by efficient,…

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