🤖 AI Summary
This work addresses the challenge of capturing high-fidelity manipulation demonstrations rich in contact information while preserving human dexterity. The authors propose a novel tactile glove that, for the first time, integrates an anatomically aligned 22-degree-of-freedom joint structure, explicit contact geometry, and a high-resolution piezoresistive tactile array with 2048 sensing elements into a single wearable system. By covering the fingers, thumb, and palm with 16 rigid functional surfaces, the glove simultaneously records joint kinematics and tactile signals at 120 Hz, enabling synchronized, contact-aware capture of dexterous hand motions. This approach provides high-quality, contact-grounded demonstration data essential for advancing dexterous robotic learning.
📝 Abstract
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.