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arXiv · 2210.06463

Holo-Dex: Teaching Dexterity with Immersive Mixed Reality

Sridhar Pandian Arunachalam·Irmak Güzey·Soumith Chintala·Lerrel Pinto
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Abstract

A fundamental challenge in teaching robots is to provide an effective interface for human teachers to demonstrate useful skills to a robot. This challenge is exacerbated in dexterous manipulation, where teaching high-dimensional, contact-rich behaviors often require esoteric teleoperation tools. In this work, we present Holo-Dex, a framework for dexterous manipulation that places a teacher in an immersive mixed reality through commodity VR headsets. The high-fidelity hand pose estimator onboard the headset is used to teleoperate the robot and collect demonstrations for a variety of general-purpose dexterous tasks. Given these demonstrations, we use powerful feature learning combined with non-parametric imitation to train dexterous skills. Our experiments on six common dexterous tasks, including in-hand rotation, spinning, and bottle opening, indicate that Holo-Dex can both collect high-quality demonstration data and train skills in a matter of hours. Finally, we find that our trained skills can exhibit generalization on objects not seen in training. Videos of Holo-Dex are available at https://holo-dex.github.io.

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BibTeXRIS

Sridhar Pandian Arunachalam, Irmak Güzey, Soumith Chintala, Lerrel Pinto. 2022-10-12. Holo-Dex: Teaching Dexterity with Immersive Mixed Reality. https://arxiv.org/abs/2210.06463

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