Locating Anchor Drilling Holes Based on Binocular Vision in Coal Mine Roadways

Mengyu Lei, Xuhui Zhang (), Zheng Dong, Jicheng Wan, Chao Zhang and Guangming Zhang
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Mengyu Lei: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Xuhui Zhang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Zheng Dong: 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
Chao Zhang: College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Guangming Zhang: Faculty of Engineering and Technology, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK

Mathematics, 2023, vol. 11, issue 20, 1-18

Abstract: The implementation of roof bolt support within a coal mine roadway has the capacity to bolster the stability of the encompassing rock strata and thereby mitigate the potential for accidents. To enhance the automation of support operations, this paper introduces a binocular vision positioning method for drilling holes, which relies on the adaptive adjustment of parameters. Through the establishment of a predictive model, the correlation between the radius of the target circular hole in the image and the shooting distance is ascertained. Based on the structural model of the anchor drilling robot and the related sensing data, the shooting distance range is defined. Exploiting the geometric constraints inherent to adjacent anchor holes, the precise identification of anchor holes is detected by a Hough transformer with an adaptive parameter-adjusted method. On this basis, the matching of the anchor hole contour is realized by using linear slope and geometric constraints, and the spatial coordinates of the anchor hole center in the camera coordinate system are determined based on the binocular vision positioning principle. The outcomes of the experiments reveal that the method attains a positioning accuracy of 95.2%, with an absolute error of around 1.52 mm. When compared with manual operation, this technique distinctly enhances drilling accuracy and augments support efficiency.

Keywords: binocular vision system; spatial coordinate; positioning technology; matching method; drilling holes (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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