可捕捉接触式灵巧操作的智能触觉手套，兼顾手部自由度与精准感知。
ART-Glove: Articulated Tactile Glove for Contact-Grounded Dexterous Interaction Capture
- 16个刚性表面覆盖手掌与手指，22个关节模拟人体手部运动。
- 同步采集22自由度关节数据与2048触点触觉信号，采样率120Hz。
- 适合机器人灵巧操作学习、人机交互研究等场景使用。
我们提出ART-Glove，一种用于捕捉接触式灵巧操作的可动触觉手套，同时保持人类手部灵活性。该手套通过16个刚性功能面覆盖手指、拇指和掌心，显式表达手部接触几何结构；22个解剖对齐的关节连接这些表面，使它们在灵巧操作中能跟随人体手部运动。基于编码器的传感系统追踪表面运动，密集压阻式触觉传感记录同一表面上的接触信息。整个系统以120 Hz频率同步捕获22自由度关节数据和2048触点触觉数据。我们在运动自由度、关节传感、触觉传感及丰富接触交互捕捉等实验中评估了ART-Glove，证明其在保留人类操作灵活性的同时，能够有效记录支持下游灵巧机器人学习的接触相关数据。
原文摘要 · Abstract (English)
We present ART-Glove, an articulated tactile glove designed to capture contact-grounded dexterous demonstrations while preserving human dexterity. ART-Glove makes hand-side contact geometry explicit with 16 rigid functional surfaces covering the fingers, thumb, and palm. Twenty-two anatomically aligned joints connect these surfaces and allow them to follow human hand motion during dexterous manipulation. Encoder-based sensing tracks surface motion, while dense piezoresistive tactile sensing records contact over the same surfaces. The complete system captures synchronized 22-DoF joint measurements and 2048-taxel tactile measurements at 120 Hz. We evaluate ART-Glove across experiments on motion freedom, joint sensing, tactile sensing, and contact-rich interaction capture, demonstrating its ability to preserve human dexterity while recording contact-grounded information that can support downstream dexterous robot learning.
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