SimEX 框架使用模拟来训练机器人在现实世界中的任务

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员开发了 SimEX，一个将模拟实验与现实世界机器人控制相结合的新型框架。这种方法允许由大型语言模型驱动的编码代理，通过首先在模拟中进行开放式迭代来构建机器人工具箱，从而高效地获得物理能力。然后，代理使用最少的物理试验来完善该工具箱和模拟器，纠正模拟器以诊断和修复故障。SimEX 已成功应用于毛巾折叠和盘子操作等复杂的现实世界操作任务，仅需 10 分钟的物理交互。 AI

影响使编码代理能够高效地获得物理机器人技能，可能加速具身智能的发展。

排序理由该项目是一篇学术论文，详细介绍了一个新的机器人研究框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Jiaheng Hu, Roberto Martin-Martin, Peter Stone, Rocky Duan, Zhenyu Jiang, Guanya Shi · 2026-10-01 04:00

SimEX: 模拟集成机器人自主研究

arXiv:2609.38982v1 Announce Type: cross Abstract: Coding agents powered by large language models (LLMs) have shown remarkable abilities to autonomously reason about and achieve goals in the digital world. However, bringing this success to the physical world remains challenging. O…

本文如何被排名

报道来源 [1]

SimEX: 模拟集成机器人自主研究

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