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Title: Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self-Powered Sensor Enhanced Soft Robotic Manipulator
Authors: Sun, Zhongda
Zhu, Minglu
Zhang, Zixuan 
Chen, Zhaocong
Shi, Qiongfeng 
Shan, Xuechuan
Yeow, Raye Chen Hua 
Lee, Chengkuo 
Keywords: artificial intelligence
object recognition
soft manipulator
virtual/augmented reality
Issue Date: 26-May-2021
Publisher: John Wiley and Sons Inc
Citation: Sun, Zhongda, Zhu, Minglu, Zhang, Zixuan, Chen, Zhaocong, Shi, Qiongfeng, Shan, Xuechuan, Yeow, Raye Chen Hua, Lee, Chengkuo (2021-05-26). Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self-Powered Sensor Enhanced Soft Robotic Manipulator. Advanced Science 8 (14) : 2100230. ScholarBank@NUS Repository.
Rights: Attribution 4.0 International
Abstract: Rapid advancements of artificial intelligence of things (AIoT) technology pave the way for developing a digital-twin-based remote interactive system for advanced robotic-enabled industrial automation and virtual shopping. The embedded multifunctional perception system is urged for better interaction and user experience. To realize such a system, a smart soft robotic manipulator is presented that consists of a triboelectric nanogenerator tactile (T-TENG) and length (L-TENG) sensor, as well as a poly(vinylidene fluoride) (PVDF) pyroelectric temperature sensor. With the aid of machine learning (ML) for data processing, the fusion of the T-TENG and L-TENG sensors can realize the automatic recognition of the grasped objects with the accuracy of 97.143% for 28 different shapes of objects, while the temperature distribution can also be obtained through the pyroelectric sensor. By leveraging the IoT and artificial intelligence (AI) analytics, a digital-twin-based virtual shop is successfully implemented to provide the users with real-time feedback about the details of the product. In general, by offering a more immersive experience in human–machine interactions, the proposed remote interactive system shows the great potential of being the advanced human–machine interface for the applications of the unmanned working space. © 2021 The Authors. Advanced Science published by Wiley-VCH GmbH
Source Title: Advanced Science
ISSN: 2198-3844
DOI: 10.1002/advs.202100230
Rights: Attribution 4.0 International
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