Advertisement

Research on Anti-fall Algorithms of Substation Intelligent Inspection Robot

  • Xiangqian Wu
  • Dongsong Li
  • Tianli Liu
  • Xuesong Li
  • Chuanyou Zhang
  • Jian Li
  • Guangting Shao
  • Yafei Wang
  • Yan Deng
  • Guoqing YangEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1084)

Abstract

A fall protection method of intelligent patrol robot based on binocular vision is presented in the paper, and the safe running of robot is realized in substation. A binocular camera is installed on the intelligent inspection robot of the substation, and the front road surface of the inspection robot is photographed by a binocular camera. The disparity map is computed by the current road image obtained by the left and right camera, and the actual distance between the two cameras is obtained. By comparing with the preset distance threshold to determine whether the front is a dangerous area. Experimental results show that the proposed method has high accuracy and strong robustness. It can effectively avoid the fall protection of the inspection robot, reduce the damage caused by the drop of the inspection robot and improve the security during the patrolling process of the inspection robot.

Keywords

Substation Inspection robot Fall protection Binocular vision Disparity map 

References

  1. 1.
    Zhou, L.H., Zhang, Y.S., Sun, Y., et al.: Development and application of equipment inspection robot for smart substations. Autom. Electr. Power Syst. 35(19), 85–88, 96 (2011)Google Scholar
  2. 2.
    Yang, X.D., Huang, Y.Z., Li, J.G., et al.: Research status review of robots applied in substations for equipment inspection. Shandong Electr. Power 42(1), 30–34 (2015)Google Scholar
  3. 3.
    Peng, X.Y., Jin, L., Wang, K., et al.: Design and application of robot inspection system in substation. Electr. Power 51(2), 82–89 (2018)Google Scholar
  4. 4.
    Ding, S.K., Li, J.: Analysis and countermeasures of substation inspection robot in the practical application. Distrib. Utilization 33(1), 80–82 (2016)MathSciNetGoogle Scholar
  5. 5.
    Zhang, E.S.: Research on ranging algorithm based on binocular stereo vision algorithm. Inner Mongolia University, pp. 1–62 (2018)Google Scholar
  6. 6.
    Guo, P., Du, H.: Study on the robotic binocular distance measurement. Wirel. Internet Technol. 15(5), 99–101 (2018)Google Scholar
  7. 7.
    Wang, Y.X., Zhang, J.M., Kan, J.M.: Hardware platform of target positioning and ranging system based on binocular vision. Comput. Eng. 7, 214–218, 223 (2013)Google Scholar
  8. 8.
    Zhang, Y.J., Pan, Y., Wu, C.: Distance measurement of binocular CCD camera on vehicle-mounted system. Inf. Secur. Technol. 7(1), 57–62 (2016)Google Scholar
  9. 9.
    Xu, S.S., Wang, Y.Q., Zhang, Z.Y.: Extracting disparity map from bifocal monocular stereo vision in a novel way. J. Comput. Appl. 32(2), 341–343, 378 (2011)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Xiangqian Wu
    • 1
  • Dongsong Li
    • 2
  • Tianli Liu
    • 2
  • Xuesong Li
    • 2
  • Chuanyou Zhang
    • 2
  • Jian Li
    • 2
  • Guangting Shao
    • 2
  • Yafei Wang
    • 2
  • Yan Deng
    • 2
  • Guoqing Yang
    • 2
    Email author
  1. 1.Production Technology DepartmentGuizhou Power Grid Co., Ltd.GuiyangChina
  2. 2.Robotics Cause DepartmentShandong Luneng Intelligence Technology Co., Ltd.JinanChina

Personalised recommendations