Hardware-software co-design of inspection robot system

被引：0
|
作者：
Bi F. [1 ]
Zhou G. [2 ]
Zhang C. [2 ]
Ji S. [2 ]
Peng L. [3 ,4 ]
Yan R. [3 ,4 ]
机构：
[1] PetroChina Natural Gas Marketing Company, Beijing
[2] Beijing Elitenect Technologies Company, Beijing
[3] Department of Electronic Engineering, Tsinghua University, Beijing
[4] Beijing National Research Center for Information Science and Technology, Beijing
来源：
Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science) | 2024年 / 48卷 / 03期
关键词：
deep learning; inspection robot; mobile positioning; object perception; text recognition;
D O I：
10.3969/j.issn.1673-5005.2024.03.020
中图分类号：
学科分类号：
摘要：
Aiming to two major problems of mobile positioning and object perception, the hardware-software co-design schemes of inspection robot system were explored. For the mobile positioning, a simultaneous localization and mapping strategy by combining LiDAR, monocular camera, inertial measurement unit, GPS and other sensors was designed, and an improved visual positioning scheme was introduced by using the ArUco marker road sign detection. For the object perception, taking the task of meter information extraction as an example, the deep learning based meter detection, localization and text recognition methods were adopted. The results show that, by incorporating the 5G mobile communication and Wi-Fi network communication functions, an intelligent inspection robot system with network management platform is implemented. The developed inspection robot system has met the requirements in practical applications, which effectively enhances the automation and intelligence level of inspection. © 2024 University of Petroleum, China. All rights reserved.
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页码：180 / 187
页数：7
相关论文
共 17 条
  • [1] STEELE J P, HAN Q, KARKI H, Et al., Development of an oil and gas refinery inspection robot [ R ], (2014)
  • [2] HE Yurong, SONG Zhichao, ZHANG Yanming, Et al., Review on application of machine learning in hydraulic fracturing, Journal of China University of Petroleum (Edition of Natural Science), 45, 6, pp. 127-135, (2021)
  • [3] ZHAO Junyou, ZHANG Yaning, BI Xiaodong, Et al., Optimum design of magnetic adsorption structure and machine performance test for sand blasting and rust-removing wall-climbing robot, Journal of China University of Petroleum(Edition of Natural Science), 44, 4, pp. 94-99, (2020)
  • [4] ZHENG Jie, SHANG Zuyue, DOU Yihua, Et al., R&D for modular synchronous autonomous variable diameter gas pipeline robot, China Petroleum Machinery, 51, 11, pp. 154-162, (2023)
  • [5] DING Jianxin, LI Xuesong, SONG Xianzhi, Et al., Multiobjective collaborative optimization method for ROP improvement,drag reduction and hole cleaning in horizontal well drilling [ J ], China Petroleum Machinery, 51, 11, pp. 1-10, (2023)
  • [6] LIU Biao, Application of explosion proof inspection robot in natural gas distribution station [ J ], Chemical Enterprise Management, 28, 21, pp. 196-198, (2021)
  • [7] CADENA C, CARLONE L, CARRILLO H, Et al., Past, present, and future of simultaneous localization and mapping: toward the robust-perception age[J], IEEE Transactions on Robotics, 32, 6, pp. 1309-1332, (2016)
  • [8] KANG Lei, ZHENG Haowei, Research on automatic recognition algorithm of pointer instrument based on machine vision, Technology Supervision in Petroleum Industry, 38, 3, pp. 20-23, (2022)
  • [9] LIU Huizhou, HU Jinqiu, ZHANG Laibin, Et al., Accurate identification and early-warning of faults of fracturing equipments based on infrared thermal imaging and convolutional neural network, Journal of China University of Petroleum (Edition of Natural Science), 45, 1, pp. 158-166, (2021)
  • [10] QIN T, LI P, SHEN S., VINS-Mono: a robust and versatile monocular visual-inertial state estimator[J], IEEE Transactions on Robotics, 34, 4, pp. 1004-1020, (2018)
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