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arXiv · 2603.09565

ReTac-ACT: A State-Gated Vision-Tactile Fusion Transformer for Precision Assembly

Minchi Ruan·LiangQing Zhou·Hongtong Li·Zongtao Wang·ZhaoMing Lu·Jianwei Zhang·Bin Fang
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Abstract

Precision assembly requires sub-millimeter corrections in contact-rich "last-millimeter" regions where visual feedback fails due to occlusion from the end-effector and workpiece. We present ReTac-ACT (Reconstruction-enhanced Tactile ACT), a vision-tactile imitation learning policy that addresses this challenge through three synergistic mechanisms: (i) bidirectional cross-attention enabling reciprocal visuo-tactile feature enhancement before fusion, (ii) a proprioception-conditioned gating network that dynamically elevates tactile reliance when visual occlusion occurs, and (iii) a tactile reconstruction objective enforcing learning of manipulation-relevant contact information rather than generic visual textures. Evaluated on the standardized NIST Assembly Task Board M1 benchmark, ReTac-ACT achieves 90% peg-in-hole success, substantially outperforming vision-only and generalist baseline methods, and maintains 80% success at industrial-grade 0.1mm clearance. Ablation studies validate that each architectural component is indispensable. The ReTac-ACT codebase and a vision-tactile demonstration dataset covering various clearance levels with both visual and tactile features will be released to support reproducible research.

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Minchi Ruan, LiangQing Zhou, Hongtong Li, Zongtao Wang, ZhaoMing Lu, Jianwei Zhang, Bin Fang. 2026-03-10. ReTac-ACT: A State-Gated Vision-Tactile Fusion Transformer for Precision Assembly. https://arxiv.org/abs/2603.09565

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