Research on Positioning Method of Coal Mine Mining Equipment Based on Monocular Vision

Rui Yu, Xinqiu Fang (), Chengjun Hu, Xiuyu Yang, Xuhui Zhang, Chao Zhang, Wenjuan Yang, Qinghua Mao and Jicheng Wan
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Rui Yu: School of Mines, China University of Mining and Technology, Xuzhou 221116, China
Xinqiu Fang: School of Mines, China University of Mining and Technology, Xuzhou 221116, China
Chengjun Hu: College of Energy and Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
Xiuyu Yang: Wangjialing Coal Mine, China Coal Husain Group Co., Ltd., Yuncheng 043300, China
Xuhui Zhang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Chao Zhang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Wenjuan Yang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Qinghua Mao: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Jicheng Wan: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China

Energies, 2022, vol. 15, issue 21, 1-14

Abstract: In view of the insufficient characteristics and depth acquisition difficulties encountered in the process of uniocular vision measurement, the posture measurement scheme of tunneling equipment based on uniocular vision was proposed in this study. The positioning process of coal mine tunneling equipment based on monocular vision was proposed to extract the environmental features and match the features, and the RANSAC algorithm was used to eliminate the pair of mismatching points. This was done to solve the optimized matching pair and realize the pose estimation of the camera. The pose solution model based on the triangulation depth calculation method was proposed, and the PNP solution method was adopted based on the three-dimensional spatial point coordinates so as to improve the visual measurement accuracy and stability and lay the foundation for the 3D reconstruction of the roadway. This was done to simulate the downhole environment to build an experimental verification platform for monocular visual positioning. The experimental results showed that the position measurement accuracy of the uniocular visual roadheader positioning method within 60 mm and 1.3° could realize the accurate registration of the point cloud in the global coordinate system. The time required for the whole monocular visual positioning was only 179 ms, so it had good real-time performance.

Keywords: monocular vision; 3D reconstruction; equipment position; intelligent tunneling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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