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

PubDate: May 2019

Teams: UCLA Center for Vision;Beijing Institute of Technology;International Center for AI and Robot Autonomy

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

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

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.