VIRDO++: 変形可能物体の実世界における視触覚ダイナミクスと知覚
VIRDO++: Real-World, Visuo-tactile Dynamics and Perception of Deformable Objects
視覚と触覚を統合したニューラル陰関数表現により、変形可能物体の状態推定と変形ダイナミクス予測を実世界で実現し、未知物体や接触形態への汎化を示した。
著者: Youngsun Wi, Andy Zeng, Pete Florence, Nima Fazeli
分類: cs.RO
原文アブストラクト
Deformable objects manipulation can benefit from representations that seamlessly integrate vision and touch while handling occlusions. In this work, we present a novel approach for, and real-world demonstration of, multimodal visuo-tactile state-estimation and dynamics prediction for deformable objects. Our approach, VIRDO++, builds on recent progress in multimodal neural implicit representations for deformable object state-estimation [1] via a new formulation for deformation dynamics and a complementary state-estimation algorithm that (i) maintains a belief over deformations, and (ii) enables practical real-world application by removing the need for privileged contact information. In the context of two real-world robotic tasks, we show:(i) high-fidelity cross-modal state-estimation and prediction of deformable objects from partial visuo-tactile feedback, and (ii) generalization to unseen objects and contact formations.
