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English(EN) SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control

SCRIPT模型通过语言和扩散技术推进人形控制

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员开发了SCRIPT，这是一种新颖的扩散策略，专为使用自然语言指令控制基于物理的人形机器人而设计。该方法利用联合动作-状态-文本扩散 Transformer (JAST-DiT) 将语言语义与控制动力学相结合。SCRIPT 还包含一个非线性历史条件机制，用于稳定的长时程控制，并采用具有混合奖励的强化学习 (RLHR) 来增强性能。 AI

影响 引入了一个新的语言驱动人形控制框架，可能能够实现更复杂具身智能体。

排序理由 该集群包含一篇详细介绍人形控制新模型和方法论的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

报道来源 [3]

  1. arXiv cs.LG TIER_1 English(EN) · Jingyan Zhang, Han Liang, Ruichi Zhang, Bin Li, Juze Zhang, Xin Chen, Jingya Wang, Lan Xu, Jingyi Yu ·

    SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control

    arXiv:2605.22894v1 Announce Type: cross Abstract: Controlling physics-based humanoids from natural-language instructions is a critical step toward general-purpose embodied agents. However, existing methods remain constrained by a tension between semantic expressiveness and physic…

  2. arXiv cs.CV TIER_1 English(EN) · Bin Li, Ruichi Zhang, Han Liang, Jingyan Zhang, Juze Zhang, Xin Chen, Jingya Wang ·

    MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

    arXiv:2605.26006v1 Announce Type: new Abstract: Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typically follow either a two-stage paradigm that combines kinematic motion generation …

  3. arXiv cs.CV TIER_1 English(EN) · Jingya Wang ·

    MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control

    Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typically follow either a two-stage paradigm that combines kinematic motion generation with physics-based tracking, or an end-to-end im…

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