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Visual Navigation for a Power Transmission Line Inspection Robot

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Computational Intelligence (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4114))

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Abstract

Inspection robot must plan its behavior to negotiate obstacles according to their types when it is crawling along the power transmission line. For this purpose, a visual navigation system is designed to recognize the obstacles and locate their positions by stereovision.We propose a structure-constrained obstacle recognition algorithm based on improved circle detection methods to recognize obstacles from complex background robustly. After the obstacle is recognized, a region based stereo matching algorithm is used to search the correspondence points in the stereo images, and the position of the obstacle relative to the robot is calculated by 3D reconstruction. Experiments with simulation and real transmission line show its effectiveness.

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Author information

Authors and Affiliations

  1. Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100080, China

    Yunchu Zhang, Siyao Fu, Xiaoguang Zhao, Zize Liang, Min Tan & Yongqian Zhang

  2. School of Information and Electric Engineering, Shandong University of Architecture and Engineering, Jinan 250101, China

    Yunchu Zhang

Authors
  1. Yunchu Zhang
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  2. Siyao Fu
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  3. Xiaoguang Zhao
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  4. Zize Liang
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  5. Min Tan
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  6. Yongqian Zhang
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines , Chinese Academy of Sciences , Anhui, Hefei, China

    De-Shuang Huang

  2. Queen’s University , Belfast, UK

    Kang Li  & George William Irwin  & 

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, Y., Fu, S., Zhao, X., Liang, Z., Tan, M., Zhang, Y. (2006). Visual Navigation for a Power Transmission Line Inspection Robot. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_111

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  • DOI: https://doi.org/10.1007/978-3-540-37275-2_111

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37274-5

  • Online ISBN: 978-3-540-37275-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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