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author:

Liu, Lekang (Liu, Lekang.) [1] | Zhu, Jun (Zhu, Jun.) [2] | Duan, Zhiqiang (Duan, Zhiqiang.) [3] | Xu, Jiaxin (Xu, Jiaxin.) [4] | Ren, Jie (Ren, Jie.) [5] | Dong, Yanzhi (Dong, Yanzhi.) [6]

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EI

Abstract:

With the rapid development of robotics technology, it has become crucial for robots to effectively perceive the sense of touch. This helps intelligent robots better understand their surroundings, improves their perception and interaction capabilities, and is directly related to the robot's motion decision-making and human-robot interaction safety. Electrical impedance tomography is a non-invasive medical imaging technique that can reconstruct the conductivity distribution of a conductive domain using a small amount of boundary voltage data. It demonstrates the unique advantages of large-area tactile sensors for human-computer interaction. In this paper, we present a tactile sensor system based on electrical impedance tomography. A robotic arm sensor with 16 electrodes was designed and prepared using 3D printing technology, a data acquisition hardware system and an upper computer image reconstruction software system were built. The sensor was applied to the robotic arm as an 'electronic skin', and several physical interaction experiments were conducted. The experimental results show that the sensor is of great significance in realizing the tactile sensing function of robots and human-computer interaction. © 2023 IEEE.

Keyword:

3D printing Data acquisition Decision making Electric impedance Electric impedance measurement Electric impedance tomography Human computer interaction Human robot interaction Image reconstruction Intelligent robots Medical imaging Robotic arms

Community:

  • [ 1 ] [Liu, Lekang]Yantai University, School of Physics and Electronic Information, Yantai, China
  • [ 2 ] [Zhu, Jun]Nanjing University of Information Science and Technology, School of Automation, Nanjing, China
  • [ 3 ] [Duan, Zhiqiang]Fuzhou University, College of Computer and Data Science, Fuzhou, China
  • [ 4 ] [Xu, Jiaxin]Yantai University, School of Physics and Electronic Information, Yantai, China
  • [ 5 ] [Ren, Jie]Yantai University, School of Physics and Electronic Information, Yantai, China
  • [ 6 ] [Dong, Yanzhi]Yantai University, School of Physics and Electronic Information, Yantai, China

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Year: 2023

Page: 389-393

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 8

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