予期せぬ感覚を捉える：残差触覚表現によるResTacVLAの接触豊富な操作
Feeling the Unexpected: ResTacVLA for Contact-Rich Manipulation via Residual Tactile Representation
視覚言語行動モデルに触覚を統合する際、視覚特徴が触覚を覆い隠す問題を解決するため、視覚予測と実際の触覚の差を残差表現として用い、視覚的に予測できない重要な接触イベントを捉えるResTacVLAを提案した。
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著者: Pengwei Zhang, Bin Xie, Xinpan Meng, Xinyu Guo, Ce Hao, Fang Deng, Long Cheng, Tiancai Wang
分類: cs.RO
原文アブストラクト
Tactile perception is indispensable for contact-rich manipulation, yet integrating it into Vision-Language-Action (VLA) models often induces modality collapse, where high-bandwidth visual features overshadow sparse tactile cues. Inspired by Predictive Coding, a neural mechanism where the brain attenuates predictable inputs to prioritize surprising stimuli, we propose ResTacVLA. Rather than treating tactile data as raw input, we reformulate it as a Residual Tactile Representation capturing the discrepancy between visual priors and physical sensations. By filtering out visually predictable dynamics, this formulation transforms sparse tactile signals into dense, high-value information gain, thereby inherently resolving the bandwidth mismatch. These residuals are discretized through a Vector Quantized (VQ) bottleneck into Latent Contact Primitives that capture critical events missed by vision. Analogous to the neural surprise signal, we leverage the uncertainty of the visual prior to adaptively gate tactile integration, prioritizing residuals specifically during visually unreliable phases to explicitly prevent visual dominance. Experimental results show that ResTacVLA consistently outperforms all baselines on a diverse set of contact-rich manipulation tasks, while remaining robust to unexpected dynamic disturbances. Project page: https://awilekong.github.io/ResTacVLA/
関連論文
- 接触を伴うロボット操作のための表現整合型触覚グラウンディング触覚/VLA/操作
