TY - GEN
T1 - High-fidelity grasping in virtual reality using a glove-based system
AU - Liu, Hangxin
AU - Zhang, Zhenliang
AU - Xie, Xu
AU - Zhu, Yixin
AU - Liu, Yue
AU - Wang, Yongtian
AU - Zhu, Song Chun
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85071487381&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2019.8794230
DO - 10.1109/ICRA.2019.8794230
M3 - Conference contribution
AN - SCOPUS:85071487381
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 5180
EP - 5186
BT - 2019 International Conference on Robotics and Automation, ICRA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Robotics and Automation, ICRA 2019
Y2 - 20 May 2019 through 24 May 2019
ER -