VIRDO: Visio-tactile Implicit Representations of Deformable Objects
February 02, 2022 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Youngsun Wi, Pete Florence, Andy Zeng, Nima Fazeli
arXiv ID
2202.00868
Category
cs.RO: Robotics
Citations
51
Venue
IEEE International Conference on Robotics and Automation
Last Checked
5 months ago
Abstract
Deformable object manipulation requires computationally efficient representations that are compatible with robotic sensing modalities. In this paper, we present VIRDO:an implicit, multi-modal, and continuous representation for deformable-elastic objects. VIRDO operates directly on visual (point cloud) and tactile (reaction forces) modalities and learns rich latent embeddings of contact locations and forces to predict object deformations subject to external contacts.Here, we demonstrate VIRDOs ability to: i) produce high-fidelity cross-modal reconstructions with dense unsupervised correspondences, ii) generalize to unseen contact formations,and iii) state-estimation with partial visio-tactile feedback
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