Research on the Body Positioning Method of Bolting Robots Based on Monocular Vision

被引:2
|
作者
Hao, Xuedi [1 ,2 ]
Zhang, Yiming [1 ]
Yang, Xueqiang [3 ]
Zhang, Jinglin [4 ]
Wen, Rusen [1 ]
Wu, Zhenlong [1 ]
Jia, Han [1 ]
机构
[1] China Univ Min & Technol Beijing, Coll Mech & Elect Engn, Beijing 100083, Peoples R China
[2] Minist Emergency Management, Key Lab Intelligent Min & Robot, Beijing 100083, Peoples R China
[3] Beijing Inst Control & Elect Technol, Beijing 100038, Peoples R China
[4] Beijing Tianma Intelligent Control Technol Co Ltd, Beijing 100029, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 18期
基金
中国国家自然科学基金;
关键词
monocular vision; bolt robot; positioning measurement; DR algorithm;
D O I
10.3390/app131810183
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Aiming at the intelligent design of underground roadway support and the precise positioning of unmanned full excavation faces, a positioning and measurement method of bolt robots based on the monocular vision principle was proposed. In this paper, a vehicle body positioning model based on image data was established. The data were obtained with a camera, and the conversion between image coordinates and world coordinates was carried out through coordinate system conversion. A monocular vision positioning system of the bolt robot was designed, and the simulation's experimental model was established. Under the simulation's experimental conditions, the effective positioning distance of the monocular vision positioning system was measured. An experimental platform for the bolt robot was designed, and real-time human positioning data measurement of the vehicle was carried out. The experimental error was analyzed, and the reliability of the method was proven. This method realizes the real-time positioning of underground mines through the bolt robot, improves the accuracy and efficiency of the positioning, and lays a foundation for the positioning control of the heading face and the unmanned bolt robot.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Subway Train Positioning Based on Monocular Vision and Optical Camera Communication
    Zhang Yanpeng
    Zhu Dongya
    Ma Junming
    Meng Nan
    LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (16)
  • [32] Planar-Based Visual Positioning for a Mobile Robot with Monocular Vision
    Guo, Yang
    Xiao, Zheng
    Chen, Hui
    Huang, Ling
    CLOUD COMPUTING AND SECURITY, PT I, 2017, 10602
  • [33] Real-Time Positioning and Orienting of Pallets Based on Monocular Vision
    Byun, Sungmin
    Kim, Minhwan
    20TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, VOL 2, PROCEEDINGS, 2008, : 505 - 508
  • [34] Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching
    Wei-Ping Ma
    Wen-Xin Li
    Peng-Xia Cao
    International Journal of Automation and Computing, 2020, 17 : 562 - 571
  • [35] Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching
    Wei-Ping Ma
    Wen-Xin Li
    Peng-Xia Cao
    International Journal of Automation and Computing, 2020, 17 (04) : 562 - 571
  • [36] Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching
    Ma, Wei-Ping
    Li, Wen-Xin
    Cao, Peng-Xia
    INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING, 2020, 17 (04) : 562 - 571
  • [37] Vision based fruit recognition and positioning technology for harvesting robots
    Yang, Yingyan
    Han, Yuxiao
    Li, Shuai
    Yang, Yuanda
    Zhang, Man
    Li, Han
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2023, 213
  • [38] Research Progress of Obstacle Detection Based on Monocular Vision
    Wu, Qiang
    Wei, Jie
    Li, Xuwen
    2014 TENTH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP 2014), 2014, : 195 - 198
  • [39] Research on Pedestrian Detection Algorithm Based on Monocular Vision
    Lei, Yi
    Huang, Zhijie
    2018 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS 2018), 2018, : 161 - 163
  • [40] Monocular vision pose determination-based large rigid-body docking method
    Luo, Hua
    Zhang, Ke
    Su, Yu
    Zhong, Kai
    Li, Zhongwei
    Guo, Jing
    Guo, Chao
    MEASUREMENT, 2022, 204