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Intelligent Industrial Auxiliary System Based on AR Technology

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Data Science (ICPCSEE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1629))

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Abstract

The traditional industrial assembly method is inefficient, and it is difficult to meet the needs of rapid production in modern society. Although many virtual assembly systems based on augmented reality technology have appeared in recent years, most of these assembly systems are noninteractive, nonintelligent, and inefficient. In response to this problem, we combined AR technology and AI technology to design and implement a strong interactive, high-intelligence virtual assembly guidance system in four levels. Finally, we took a UAV assembly as an example to show our design results. Operators can use this system to quickly master the assembly process. Finally, according to some problems encountered in the process of system implementation, the improvement direction of the virtual assembly system is proposed, and the future development of the AR auxiliary industry is proposed. This article describes the functions and implementation process of the four levels of the AR assembly system in detail, which can help readers quickly understand the connection between AR technology and AI technology and understand the principle of the virtual assembly guidance system.

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Author information

Authors and Affiliations

  1. School of Geophysics and Information Technology, China University of Geosciences, Beijing, China

    Tao Wang & Linyan Guo

  2. China Academy of Information and Communications Technology, Beijing, China

    Xinqi Shen

  3. School of Information Engineering, China University of Geosciences, Beijing, China

    Junpei Ma & Zhuorui Chang

Authors
  1. Tao Wang
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  2. Xinqi Shen
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  3. Junpei Ma
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  4. Zhuorui Chang
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  5. Linyan Guo
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Corresponding author

Correspondence to Linyan Guo .

Editor information

Editors and Affiliations

  1. Southwest Petroleum University, Chengdu, China

    Yang Wang

  2. University of Electronic Science and Technology of China, Chengdu, China

    Guobin Zhu

  3. Harbin Engineering University, Harbin, China

    Qilong Han

  4. Southwest Petroleum University, Chengdu, China

    Liehui Zhang

  5. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  6. National Academy of Guo Ding Institute of Data Sciences, Beijing, China

    Zeguang Lu

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Wang, T., Shen, X., Ma, J., Chang, Z., Guo, L. (2022). Intelligent Industrial Auxiliary System Based on AR Technology. In: Wang, Y., Zhu, G., Han, Q., Zhang, L., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2022. Communications in Computer and Information Science, vol 1629. Springer, Singapore. https://doi.org/10.1007/978-981-19-5209-8_15

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  • DOI: https://doi.org/10.1007/978-981-19-5209-8_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-5208-1

  • Online ISBN: 978-981-19-5209-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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