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English(EN) REACT: Rolling Denoising and Dual Decoupling for Reactive Robot Control with VLA Models

新的REACT框架利用VLA模型提升机器人控制的反应速度

研究人员开发了REACT,一个旨在增强基于流的视觉-语言-动作(VLA)模型在机器人控制中反应速度的新框架。该系统维护一个持久的动作缓冲区,允许在部署前根据最新观察结果持续优化动作。通过解耦感知、VLM编码、去噪和动作执行,REACT能够在计算约束下实现高频更新和动作流式传输。在RoboTwin 2.0基准测试和真实机器人任务上的演示表明,与现有方法相比,任务成功率有所提高,反应延迟降低,轨迹也更平滑。 AI

影响 通过提高VLA模型的反应速度和平滑度来增强机器人控制,可能支持更复杂的现实世界应用。

排序理由 该集群包含一篇详细介绍机器人控制新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的REACT框架利用VLA模型提升机器人控制的反应速度

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该集群包含一篇详细介绍机器人控制新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Houlong Xiong, Zhenqi Qiu, Zechen Wang, Suohang Zhang, Yiyu Ren, Wanting Xu, Hongfei Niu, Chengyang He, Ge Sun, Ran Cheng, Qian Zhu ·

    REACT:用于具有VLA模型的反应式机器人控制的滚动去噪和双解耦

    arXiv:2610.12007v1 Announce Type: cross Abstract: Flow-based vision-language-action (VLA) models generate action chunks for temporally coherent robot motion, but chunked control creates a fundamental closed-loop trade-off: long chunks provide smooth execution, whereas frequent re…