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arXiv · 2606.15338

SimWeaver: Zero-Shot RGB Sim-to-Real for Deformable Manipulation

Wenkang Hu·Haoran Wang·Yitong Li·Liu Liu·Mengao Zhao·Lai Jiang·Xincheng Tang·Junhang Wei·Zhengjie Shu·Zhendong Wang·Zhizhong Su·Huamin Wang·Ruigang Yang
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Abstract

RGB sim-to-real for deformable manipulation has remained largely unsolved without real-world fine-tuning. We present SimWeaver, which trains zero-shot RGB VLA policies on 200 simulated demonstrations per task, reaching above 80% per-task and 91% average real-world success across 5 diverse deformable tasks including plastic-bag manipulation, without teleoperation or per-task calibration. SimWeaver combines a reliable measurement-backed simulator (SimWeaver-Sim) with an extensible asset framework supporting single-image generation(SimWeaver-Asset), a deterministic topology-aware trajectory synthesizer (SimWeaver-Syn), and a sim-to-real protocol with ISP-aware photometric augmentation (SimWeaver-Real). On silk grasping, the sim-trained policy reaches 100% under visual distribution shifts where real-data baselines drop to 9-70%, at two orders of magnitude lower per-trajectory cost. We will release SimWeaver and a representative asset subset. Project page: https://simweaver.github.io/

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Wenkang Hu, Haoran Wang, Yitong Li, Liu Liu, Mengao Zhao, Lai Jiang, Xincheng Tang, Junhang Wei, Zhengjie Shu, Zhendong Wang, Zhizhong Su, Huamin Wang, Ruigang Yang. 2026-06-13. SimWeaver: Zero-Shot RGB Sim-to-Real for Deformable Manipulation. https://arxiv.org/abs/2606.15338

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