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author:

Duan, Zhiqiang (Duan, Zhiqiang.) [1] | Liu, Lekang (Liu, Lekang.) [2] | Zhu, Jun (Zhu, Jun.) [3] | Wu, Ruilin (Wu, Ruilin.) [4] | Wang, Yan (Wang, Yan.) [5] | Yuan, Xiaohu (Yuan, Xiaohu.) [6] | Liao, Longlong (Liao, Longlong.) [7] (Scholars:廖龙龙)

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Abstract:

During social interactions, people can obtain a great deal of important information from their tactile senses to improve their relationship with their surroundings. The development of similar capabilities in robots will contribute to the success of intuitive human-robot interaction in the future. In this paper, a tactile sensing method based on the principle of electrical impedance tomography (EIT) is introduced, which with the help of EIT technology and combined with the flexible piezoresistive material Velostat, thin, lightweight, stretchable, and flexible skin can be designed for robots, and at the same time, information about the touch position, duration, and intensity can be acquired, and the image reconstruction is carried out using a dual finite element model, and the experimental results show that based on the flexible The experimental results show that the EIT tactile sensing technology based on the flexible material Velostat can be applied to robotic flexible skin applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Keyword:

Electric impedance Electric impedance measurement Electric impedance tomography Human robot interaction Image reconstruction

Community:

  • [ 1 ] [Duan, Zhiqiang]College of Computer and Data Science/College of Software, FuZhou University, Fuzhou, China
  • [ 2 ] [Liu, Lekang]School of Physics and Electronic Information, Yantai University, Yantai, China
  • [ 3 ] [Zhu, Jun]School of Automation, Nanjing University of Information Science and Technology, Nanjing, China
  • [ 4 ] [Wu, Ruilin]School of Automation, Nanjing University of Information Science and Technology, Nanjing, China
  • [ 5 ] [Wang, Yan]School of Physics and Electronic Information, Yantai University, Yantai, China
  • [ 6 ] [Yuan, Xiaohu]Beijing Embodied Intelligent Technology Co., Ltd., Beijing, China
  • [ 7 ] [Liao, Longlong]College of Computer and Data Science/College of Software, FuZhou University, Fuzhou, China

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ISSN: 1865-0929

Year: 2024

Volume: 2029 CCIS

Page: 123-131

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 4

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