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English(EN) Dreaming the Sound of Contact: Leveraging Video and Audio Generation for Zero-Shot Force-Aware Manipulation and Data Generation

机器人利用生成的视频和音频学习力感知操纵

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的机器人操纵方法，该方法集成了生成的视频和音频来创建力感知轨迹。该方法通过利用生成的接触声音的响度来塑造所需的力剖面，解决了纯运动学轨迹的局限性。该系统在 Franka Panda 机器人上成功执行了这些力感知轨迹，在仅运动学方法失败的富接触任务中展示了改进的操纵能力。此外，该流程还可作为训练闭环策略的数据生成引擎。 AI

影响 通过将力反馈整合到学习到的操纵策略中，使机器人能够执行更复杂、富接触的任务。

排序理由 详细介绍机器人操纵新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

机器人利用生成的视频和音频学习力感知操纵

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详细介绍机器人操纵新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Guanhua Ji, Tianyu Li, Dayoon Suh, Yuqian Zhang, Boyan Zhang, Nadia Figueroa ·

    梦见接触之声：利用视频和音频生成实现零样本力感知操控和数据生成

    arXiv:2609.19137v1 Announce Type: cross Abstract: Recent advances in video generation allow robots to learn manipulation trajectories from generated videos. However, these approaches produce purely kinematic trajectories that lack force information, causing failures in contact-ri…

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