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Engineering 2024年第1期32卷 202-216页

作者： Hangxin Liu Zeyu Zhang Ziyuan Jiao Zhenliang Zhang Minchen Li chenfanfu jiang Yixin Zhu Song-Chun Zhu National Key Laboratory of General Artificial Intelligence Beijing Institute for General Artificial Intelligence(BIGAI)Beijing 100080China Center for Vision CognitionLearning and AutonomyUniversity of CaliforniaLos AngelesCA 90095USA Multi-Physics Lagrangian-Eulerian Simulations Laboratory Department of MathematicsUniversity of CaliforniaLos AngelesCA 90095USA Institute for Artificial Intelligence Peking UniversityBeijing 100871China Department of Automation Tsinghua UniversityBeijing 100084China

In this work,we present a reconfigurable data glove design to capture different modes of human hand-object interactions,which are critical in training embodied artificial intelligence(AI)agents for fine manipulation *** achieve various downstream tasks with distinct features,our reconfigurable data glove operates in three modes sharing a unified backbone design that reconstructs hand gestures in real *** the tactile-sensing mode,the glove system aggregates manipulation force via customized force sensors made from a soft and thin piezoresistive material;this design minimizes interference during complex hand *** virtual reality(VR)mode enables real-time interaction in a physically plausible fashion:A caging-based approach is devised to determine stable grasps by detecting collision *** a state-of-the-art finite element method,the simulation mode collects data on fine-grained four-dimensionalmanipulation events comprising hand and object motions in three-dimensional space and how the object's physical properties(e.g.,stress and energy)change in accordance with manipulation over ***,the glove system presented here is the first to use high-fidelity simulation to investigate the unobservable physical and causal factors behind manipulation *** a series of experiments,we characterize our data glove in terms of individual sensors and the overall *** specifically,we evaluate the system's three modes by①recording hand gestures and associated forces,②improving manipulation fluency in VR,and③producing realistic simulation effects of various tool uses,*** on these three modes,our reconfigurable data glove collects and reconstructs fine-grained human grasp data in both physical and virtual environments,thereby opening up new avenues for the learning of manipulation skills for embodied AI agents.

关键词： Data glove Tactile sensing Virtual reality Physics-based simulation

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