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arXiv cs.AI· Tianhai Liang, Shiyi Guo, Baiye Cheng, Zhengrong Xue, Han Zhang, Huazhe Xu·· 15 小时前AI 评分34

ArrayTac:可连续调节形状、刚度与摩擦力的闭环压电触觉平台

ArrayTac: A Closed-Loop Piezoelectric Tactile Platform for Continuously Tunable Rendering of Shape, Stiffness, and Friction

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ArrayTac 是一个闭环压电触觉平台,可在 4×4 执行器阵列上同时连续调节形状、刚度和摩擦力三种触觉维度。每个单元集成三级微杠杆放大器与末端霍尔效应反馈,实现最高 5 mm 位移、超过 500 Hz 的阵列刷新率和 123 Hz 闭环带宽。

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Abstract:Human touch depends on the integration of shape, stiffness, and friction, yet existing tactile displays cannot render these cues together as continuously tunable, high-fidelity signals for intuitive perception. We present ArrayTac, a closed-loop piezoelectric tactile platform that simultaneously renders these three tactile dimensions with continuous tunability on a 4 by 4 actuator array. Each unit integrates a three-stage micro-lever amplifier with end-effector Hall-effect feedback, enabling up to 5 mm displacement, an array refresh rate greater than 500 Hz, and a closed-loop bandwidth of 123 Hz. In psychophysical experiments, naive participants identified three-dimensional shapes and distinguished multiple stiffness and friction levels through touch alone without training. We further demonstrate image-to-touch rendering from an RGB image and remote palpation of a medical-grade breast tumor phantom across a distance of more than 1,000 km, in which all 11 participants correctly identified the number and type of tumors with a sub-centimeter mean localization error. Together, these results establish ArrayTac as a programmable multidimensional tactile rendering platform that bridges digital representations, physical environments, and human tactile perception, enabling intuitive tactile communication between humans and machines.
Comments: Project website: this https URL
Subjects: Robotics (cs.RO); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
Cite as: arXiv:2603.13829 [cs.RO]
  (or arXiv:2603.13829v3 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2603.13829

arXiv-issued DOI via DataCite

Submission history

From: Tianhai Liang [view email]
[v1] Sat, 14 Mar 2026 08:23:26 UTC (14,593 KB)
[v2] Fri, 17 Apr 2026 08:51:31 UTC (28,562 KB)
[v3] Mon, 26 Oct 2026 03:47:55 UTC (7,153 KB)

来源:arXiv cs.AI · arxiv.org