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SceneSmith 为机器人模拟生成逼真的室内场景

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了 SceneSmith，一个新颖的代理框架，旨在为机器人训练模拟生成逼真的室内环境。该系统采用分层方法，通过交互式 VLM 代理根据自然语言提示创建场景，并结合资产生成和物理属性估算。SceneSmith 生成的物体数量明显多于以往的方法，碰撞少且物理稳定性高，在用户研究中实现了高度逼真和提示忠实度。 AI

影响 为家庭机器人提供更多样化和复杂的训练环境，可能加速其开发和部署。

排序理由 该集群包含一篇详细介绍生成模拟环境新方法的学术论文。[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 →

SceneSmith 为机器人模拟生成逼真的室内场景

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该集群包含一篇详细介绍生成模拟环境新方法的学术论文。[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) · Nicholas Pfaff, Thomas Cohn, Sergey Zakharov, Rick Cory, Russ Tedrake ·

    SceneSmith：生成可用于仿真的室内场景的智能体

    arXiv:2602.09153v2 Announce Type: replace-cross Abstract: Simulation has become a key tool for training and evaluating home robots at scale, yet existing environments fail to capture the diversity and physical complexity of real indoor spaces. Current scene synthesis methods prod…

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