Norm2Tex: 視触覚シミュレーションをテクスチャで拡張
Norm2Tex: Augmenting Visuo-Tactile Simulations with Texture
ノーマルマップから高周波の表面詳細を視覚ベース触覚シミュレータに組み込み、シミュレーションと実世界の触覚データのギャップを埋めるプラグイン手法を提案。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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4. どうやって有効だと検証した？
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著者: Seongjin Bien, Débora Oliveira Makowski, Roberto Calandra, Florian Walter, Wolfram Burgard
分類: cs.RO
原文アブストラクト
Large-scale datasets are essential for training generalist robot control policies. Collecting real-world tactile data is costly and time-consuming, motivating the use of tactile simulations. However, current tactile simulators capture only overall contact geometry and miss fine details like texture. This results in a significant domain shift between simulated and real tactile data. To address this gap, we introduce Norm2Tex, a plug-in method that augments simulations of vision-based tactile sensors with high-frequency surface details from normal map textures. By modifying the target object's depth map before a tactile simulator's rendering pipeline, Norm2Tex seamlessly integrates into different tactile simulators. We also evaluate sim-to-real transfer using material classification and a reinforcement learning task. Our results show that Norm2Tex preserves material-dependent tactile information across domains, improving texture recognition and producing material-dependent control behavior in the real world.