English(EN) SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining

SMART系统使用合成数据进行机器人铰接对象操作

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员开发了SMART系统，该系统旨在通过大规模合成预训练来改进机器人对铰接对象的操纵。该系统利用具有感知意识设计的模拟平台SMART-Sim，生成了跨越各种任务和对象的超过一百万个演示。在这些合成数据上预训练的视觉-语言-动作模型在模拟基准测试中表现出竞争力，并实现了面向现实操作任务的零样本模拟到现实迁移。 AI

影响这项研究通过利用合成数据进行模拟到现实迁移，有可能显著提升机器人操纵能力。

排序理由该集群包含一篇详细介绍新系统和数据集的学术论文，用于AI研究。[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) · Jicong Ao, Shuhan Jiang, Yuling Zhong, Yanwen Liu, Yuhan Gao, Jiangyuan Zhao, Yang Zhang, Shiqiang Zhu, Chenjia Bai, Xuelong Li · 2026-10-07 04:00

SMART：通过大规模合成预训练实现零样本模拟到现实的铰接对象操作

arXiv:2610.07652v1 Announce Type: cross Abstract: The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations for these interactions remains challenging due to the precise contact and constra…

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报道来源 [1]

SMART：通过大规模合成预训练实现零样本模拟到现实的铰接对象操作

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