High-Fidelity Grasping in Virtual Reality using a Glove-based System

Liu, Hangxin; Zhang, Zhenliang; Xie, Xu; Zhu, Yixin; Liu, Yue; Wang, Yongtian; Zhu, Song-Chun

doi:10.1109/icra.2019.8794230

Cited by 73Teleoperation and Haptic SystemsHand Gesture Recognition SystemsInteractive and Immersive Displays

The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.

High-Fidelity Grasping in Virtual Reality using a Glove-based System

Liu, Hangxin, Zhang, Zhenliang, Xie, Xu, Zhu, Yixin, Liu, Yue, Wang, Yongtian, Zhu, Song-Chun·2019·2019 International Conference on Robotics and Automation (ICRA)

DOI 10.1109/icra.2019.8794230

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Abstract

This paper presents a design that jointly provides hand pose sensing, hand localization, and haptic feedback to facilitate real-time stable grasps in Virtual Reality (VR). The design is based on an easy-to-replicate glove-based system that can reliably perform (i) a high-fidelity hand pose sensing in real time through a network of 15 IMUs, and (ii) the hand localization using a Vive Tracker. The supported physics-based simulation in VR is capable of detecting collisions and contact points for virtual object manipulation, which drives the collision event to trigger the physical vibration motors on the glove to signal the user, providing a better realism inside virtual environments. A caging-based approach using collision geometry is integrated to determine whether a grasp is stable. In the experiment, we showcase successful grasps of virtual objects with large geometry variations. Comparing to the popular LeapMotion sensor, we demonstrate the proposed glove-based design yields a higher success rate in various tasks in VR. We hope such a glove-based system can simplify the data collection of human manipulations with VR.

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Authors: Liu, H., Zhang, Z., Xie, X., Zhu, Y., Liu, Y., Wang, Y., & Zhu, S.-C.
Affiliations: University of California, Los Angeles (US)
Beijing Institute of Technology (CN)
ORCID: Liu, Hangxin
Zhang, Zhenliang
Zhu, Yixin
Liu, Yue
Wang, Yongtian
Zhu, Song-Chun
Venue: 2019 International Conference on Robotics and Automation (ICRA)
Publisher: IEEE
Published: 2019-05
Pages: 5180-5186
ISSN: 1050-4729 (ISSN-L)
DOI: 10.1109/icra.2019.8794230
OpenAlex: W2968653604
Cited by: 73
References: 31
Citations by year: 2026: 8 · 2025: 15 · 2024: 8 · 2023: 13 · 2022: 8 · 2021: 10 · 2020: 8 · 2019: 3
FWCI: 19.70
Type: conference paper
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
Locations: Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (publishedVersion)
Topics: Physical Sciences › Engineering › Mechanical Engineering › Teleoperation and Haptic Systems
Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
Keywords: virtual reality, hand tracking, haptic feedback, hand localization, inertial measurement unit, collision detection, grasp stability, physical simulation

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High-Fidelity Grasping in Virtual Reality using a Glove-based System

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