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Title: Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications
Authors: Jin, Tao
Sun, Zhongda
Li, Long
Zhang, Quan
Zhu, Minglu
Zhang, Zixuan 
Yuan, Guangjie
Chen, Tao
Tian, Yingzhong
Hou, Xuyan
Lee, Chengkuo 
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
Issue Date: 23-Oct-2020
Citation: Jin, Tao, Sun, Zhongda, Li, Long, Zhang, Quan, Zhu, Minglu, Zhang, Zixuan, Yuan, Guangjie, Chen, Tao, Tian, Yingzhong, Hou, Xuyan, Lee, Chengkuo (2020-10-23). Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications. NATURE COMMUNICATIONS 11 (1). ScholarBank@NUS Repository.
Abstract: Designing efficient sensors for soft robotics aiming at human machine interaction remains a challenge. Here, we report a smart soft-robotic gripper system based on triboelectric nanogenerator sensors to capture the continuous motion and tactile information for soft gripper. With the special distributed electrodes, the tactile sensor can perceive the contact position and area of external stimuli. The gear-based length sensor with a stretchable strip allows the continuous detection of elongation via the sequential contact of each tooth. The triboelectric sensory information collected during the operation of soft gripper is further trained by support vector machine algorithm to identify diverse objects with an accuracy of 98.1%. Demonstration of digital twin applications, which show the object identification and duplicate robotic manipulation in virtual environment according to the real-time operation of the soft-robotic gripper system, is successfully created for virtual assembly lines and unmanned warehouse applications.
ISSN: 20411723
DOI: 10.1038/s41467-020-19059-3
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