English(EN) VTAM: Efficient Visuo-Tactile World-Action Models for Contact-Rich Manipulation without Tactile Pretraining

VTAM模型在无需预训练的情况下实现了高效的视觉-触觉操作

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-06 05:00

研究人员开发了VTAM，这是一种高效的视觉-触觉世界-动作模型，专为接触式操作任务而设计。该模型不需要触觉或动作预训练，并利用共享的冻结视频VAE和用于RGB及触觉观察的Transformer权重。VTAM在真实机器人和模拟任务上的表现优于现有基线，在推理速度显著提高的同时，表现与经过广泛预训练的模型相当。 AI

影响该模型通过减少对广泛触觉预训练的需求并提高推理速度，有可能加速机器人操作的进步。

排序理由该集群包含一篇详细介绍机器人新模型的学术论文。[lever_c_research降级：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) · Haoran Yuan, Weigang Yi, Zhenyu Zhang, Wendi Chen, Yuchen Mo, Jiashi Yin, Xinzhuo Li, Yue Luo, Jialin Li, Xiangyu Zeng, Chuan Wen, Cewu Lu, Katherine Driggs-Campbell, Ismini Lourentzou · 2026-11-06 05:00

VTAM：高效的视觉-触觉世界-动作模型，用于无需触觉预训练的富接触操作

arXiv:2603.23481v2 Announce Type: replace-cross Abstract: Tactile vision-language-action models (VLAs) and tactile world-action models (WAMs) are a promising new paradigm for contact-rich manipulation, but existing models either underutilize touch, rely on large-scale tactile pre…

本文如何被排名

报道来源 [1]

VTAM：高效的视觉-触觉世界-动作模型，用于无需触觉预训练的富接触操作

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