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English(EN) Gym-Anything for Robotics: Scaling physical simulations with digital agents

AI代理生成逼真的机器人模拟，用于具身AI训练

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了用于机器人的Gym-Anything，这是一个使用编码代理创建逼真机器人模拟的框架。该方法旨在克服手动创建模拟的瓶颈，从而能够大规模训练具身AI模型。该系统基于美国GDP数据生成模拟，以涵盖经济上有价值的任务，并包含一个用于审计和改进的对抗性循环。由此产生的RoboWorld数据集包含25个模拟，其中包含25个测试和175个训练RL环境，旨在突破当前前沿模型的界限。 AI

影响 通过自动化模拟创建，实现具身AI模型的大规模训练，可能加速现实世界的迁移。

排序理由 详细介绍机器人模拟新框架和数据集的研究论文。[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 →

AI代理生成逼真的机器人模拟，用于具身AI训练

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详细介绍机器人模拟新框架和数据集的研究论文。[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) · Pranjal Aggarwal, Sean Welleck ·

    Gym-Anything for Robotics: 使用数字代理扩展物理模拟

    arXiv:2610.40565v1 Announce Type: cross Abstract: Realistic, fast robotics simulations could enable large-scale training of embodied AI models that transfer to the real world. However, despite decades of progress, available simulations cover only a narrow range of real-world task…

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