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Outline

The Generation Method of Panoramic Color Point Cloud and Its Application in Distribution Network Operation Control

Author(s): Huikang Wen1, Baojun Liu1, Zixin Li1, Guohui Liu1
1Jiangmen Kaiping Power Supply Bureau,Guangdong Power Grid Co.,Ltd.; Jiangmen Kaiping 529300, China

Abstract

Due to the occlusion of the measured object and the limitation of the field of view of the lidar, the data of a single lidar cannot achieve the effect of panoramic color point cloud. In this paper, the multi-view point cloud data and image data obtained by three sets of distribution network operation safety behavior pre-control devices with lidar and camera are used to obtain the complete three-dimensional information and RGB information of the distribution network area. Due to the simultaneous scanning of multiple devices, the panoramic color point cloud data has increased significantly, which puts tremendous pressure on data transmission. In this paper, we propose a Real-time Color Suream Draco (RCS-Draco) algorithm based on the Google Draco geometric compression library. The algorithm is integrated into the ROS framework, and the point cloud stream is encoded and decoded in real time with the help of ROS message flow, which improves the real-time performance of the algorithm. By establishing an optimal clipping model, the point clouds are cropped and filtered, the drift and outlier point clouds are removed, and the compression efficiency of the compression algorithm is improved. Experiments show that the average compression ratio of the RCS-Draco algorithm can reach up to 77%, the average compression and decompression time is less than 0.035s, the average position error is less than 0.05m, and the average attribute error is less than 35. The fusion test proves that the RCS-Draco algorithm is superior to the Draco algorithm in various indicators.

Keywords
2D and 3D image fusion technology, panoramic color point cloud, distribution network operation scenarios, real time vr monitoring, point cloud flow, multi lidar scanning fusion, multi perspective point cloud data fusion
  • Received: 30/08/2024
  • Accepted: 01/10/2024
  • Published: 30/11/2024

References

  1. Zheng, X., & Wu, G. (2021). Kinodynamic planning with reachability prediction for PTL maintenance robot. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 235(8), 1417-1432.

  2. Baba, A. (2022). A new design of a flying robot, with advanced computer vision techniques to perform self-maintenance of smart grids. Journal of King Saud University-Computer and Information Sciences, 34(5), 2252-2261.

  3. Sekiguchi, N., Tanaka, T., & Kaneko, S. I. (2005, December). Self maintenance robot system using physical information learning for mobile robot with visual sensors. In Optomechatronic Systems Control (Vol. 6052, pp. 71-80). SPIE.

  4. Zhi, H. (2020, November). Remote performance evaluation, life prediction and fault diagnosis of RV reducer for industrial robot. In Journal of Physics: Conference Series (Vol. 1676, No. 1, p. 012212). IOP Publishing.

  5. Nentwich, C. and Reinhart, G., 2021. Towards data acquisition for predictive maintenance of industrial robots. Procedia CIRP, 104, pp.62-67.

  6. Qiu, Y., Qian, K., Liang, L., Weng, Z., Huang, Z., & Yan, Y. (2021, November). Research and Application of Full-Link Management Intellectual Inspection Robot with Remote Pre-Control and Information Digitization. In Journal of Physics: Conference Series (Vol. 2083, No. 3, p. 032077). IOP Publishing.

  7. Narasaki, S., Kawaguchi, N., Hirano, M., Nakaoji, T., Ezaki, Y., Saruta, Y., … & Sato, T. (2020, December). Development of labor-saving system for the maintenance of the telescopes under the extreme environment using a remote-controlled robot. In Observatory Operations: Strategies, Processes, and Systems VIII (Vol. 11449, pp. 532-539). SPIE.

  8. Yan, Y., Jiang, W., Zou, D., Quan, W., Li, H. J., Lei, Y., & Zhou, Z. F. (2020). Research on mechanism configuration and coordinated control for power distribution network live working robot. Industrial Robot: The International Journal of Robotics Research and Application, 47(3), 453-462.

  9. Jiang, W., Yan, Y., Zhang, A., Yu, L., Zuo, G., Li, H. J., & Chen, W. (2019). Live maintenance robot for high-voltage transmission lines. Industrial Robot: The International Journal of Robotics Research and Application, 46(5), 711-718.

  10. Jiang, W., Zhou, Z., Yan, Y., Wu, G., Yu, L., Li, H. J., & Chen, W. (2018). Fuzzy control-based bolt tightening for power cable maintenance robot. Industrial Robot: An International Journal, 45(4), 561-571.

  11. Shi, D., Zhang, W., Zhang, W., Ju, L., & Ding, X. (2021). Human-centred adaptive control of lower limb rehabilitation robot based on human–robot interaction dynamic model. Mechanism and Machine Theory, 162, 104340.

  12. Cui, J., Wang, P., Sun, T., Ma, S., Liu, S., Kang, R., & Guo, F. (2022). Design and experiments of a novel quadruped robot with tensegrity legs. Mechanism and Machine Theory, 171, 104781.

  13. Wu, X., Cui, H., Chen, W., Xie, Y., Zhao, H., & Bai, W. (2020). Integral dynamics modelling of chain-like space robot based on n-order dual number. Acta Astronautica, 177, 552-560.

  14. Guo, F., Cheng, G., & Pang, Y. (2022). Explicit dynamic modeling with joint friction and coupling analysis of a 5-DOF hybrid polishing robot. Mechanism and Machine Theory, 167, 104509.

  15. Huynh, H. N., Assadi, H., Dambly, V., Rivière-Lorphèvre, E., & Verlinden, O. (2021). Direct method for updating flexible multibody systems applied to a milling robot. Robotics and Computer-Integrated Manufacturing, 68, 102049.

  16. Gaber, A. N. A., Eldrainy, Y. A., & Awad, T. H. (2021). Uncertainty solution of robot parameters using fuzzy position control applied for an automotive cracked exhaust system inspection. Alexandria Engineering Journal, 60(2), 2355-2367.

  17. Pulloquinga, J. L., Mata, V., Valera, A., Zamora-Ortiz, P., Díaz-Rodríguez, M., & Zambrano, I. (2021). Experimental analysis of Type II singularities and assembly change points in a 3UPS+ RPU parallel robot. Mechanism and Machine Theory, 158, 104242.

  18. Dong, C., Liu, H., Xiao, J., & Huang, T. (2021). Dynamic modeling and design of a 5-DOF hybrid robot for machining. Mechanism and Machine Theory, 165, 104438.

  19. Meng, Q., Liu, X. J., & Xie, F. (2022). Design and development of a Schönflies-motion parallel robot with articulated platforms and closed-loop passive limbs. Robotics and Computer-Integrated Manufacturing, 77, 102352.

  20. Li, G., Zhu, W., Dong, H., & Ke, Y. (2021). Stiffness-oriented performance indices defined on two-dimensional manifold for 6-DOF industrial robot. Robotics and Computer-Integrated Manufacturing, 68, 102076.

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