VIRDO++: Real-World, Visuo-tactile Dynamics and Perception of Deformable ObjectsDownload PDF

16 Jun 2022, 10:45 (modified: 16 Nov 2022, 02:11)CoRL 2022 PosterReaders: Everyone
Student First Author: yes
Keywords: Deformable Object Manipulation, Multimodal Representation Learning
Abstract: 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 (VIRDO) 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.
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