Highly Stretchable and Sensitive Strain Sensor Based on Porous Materials and Rhombic‐Mesh Structures for Robot Teleoperation

Author:

Ye Zhiqiu1ORCID,Pang Gaoyang2ORCID,Liang Yihao1,Lv Honghao1,Xu Kaichen1,Wu Haiteng3,Yang Geng4ORCID

Affiliation:

1. State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou 310000 China

2. School of Electrical and Information Engineering University of Sydney Sydney NSW 2006 Australia

3. Hangzhou Shenhao Technology Co. LTD. Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou 310000 China

4. State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Zhejiang University Hangzhou 310000 China

Abstract

AbstractWearable sensors for human motion capture offer a promising human–robot interface to control robots in the teleoperation scenario, where robots could function as the second body of human operators to fulfill tasks remotely and accurately. In this paper, a novel strain sensor based on a soft polyurethane (PU) sponge and carbon nanotubes (CNT) is designed for motion capture of human joints. The unique 3D porous microstructure of the PU‐CNT sponge provides the sensor with high sensitivity. To bridge the gap between the high sensitivity and high stretchability of the strain sensor, a rhombic‐mesh structure with optimized geometric parameters, in conjunction with a pre‐compression design, is proposed for strain sensor prototyping, which endows the sensor with an extra elongation rate during the stretching process. The proposed PU‐CNT strain sensor manifests promising sensing performance with a stretchability of up to 300% and a maximum gauge factor of 3893, together with long‐term durability, low detection limit, and fast response capacity. Finally, the validation of the strain sensor is carried out by deploying the sensor on a human elbow to realize the teleoperation of a robot arm, which could be monitored through the digital twin model of the robot in a real‐time manner.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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