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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

机器人通过生成的音频和视频学习力控制

研究人员开发了一种新颖的方法,通过整合音频生成和视频生成来改进机器人操纵。该方法解决了纯运动学轨迹的局限性,这些轨迹在需要精确力控制的任务中常常失败。通过利用生成的接触声音的响度来塑造所需的力剖面,系统可以从自然语言提示中推导出运动轨迹和力参数。这种力感知系统已在 Franka Panda 机器人上成功演示,能够在先前方法失败的富接触场景中进行操纵,并且还可以作为训练新策略的数据生成引擎。 AI

影响 这项研究可能带来更强大、更多功能的机器人操纵能力,尤其是在复杂、依赖接触的任务中。

排序理由 该集群包含一篇详细介绍机器人学新研究方法的学术论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

机器人通过生成的音频和视频学习力控制

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报道来源 [2]

  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…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    梦见接触的声音:利用视频和音频生成进行零样本力感知操纵和数据生成

    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-rich tasks where appropriate contact forces are esse…