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

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.

Robust distance measurement using illumination map estimation and MAHNet in underground coal mines

“…This ensures that the associated CDF-based Gamma parameter remains at an adequate level and does not drop to 0. The corresponding truncated adaptive Gamma parameter is denoted as equation (9),…”

“…Furthermore, several studies have investigated binocular stereo vision techniques to obtain 3D scene information and perform specific measurements in coal mines. In [9], a binocular vision-based method was introduced for locating anchor drilling holes in coal mine roadways. Reference [10] presented a coal weight measurement method of belt conveyor using binocular vision, and [11] proposed a binocular vision-based measurement method to determine the attitude and straightness of hydraulic support groups.…”

An omnidirectional spatial monocular visual localization and tracking method for indoor unmanned aerial vehicles based on the two-axis rotary table

“…However, the amount of image processing is huge, and UAV self-localization is susceptible to environmental light factors. Binocular vision techniques have high localization accuracy and can localize a single feature point in space according to the relative position parameters of the two cameras calibrated in advance [14][15][16]. However, the disadvantage is that it is not easy to carry because the position of the two cameras needs to be calibrated in advance and the layout cannot be changed once calibrated, and the field of view of the positioning is relatively small because the field of view must be located in the common area of the cameras.…”

Research on the Positioning Method of Steel Belt Anchor Holes Applied in Coal Mine Underground

“…Ge et al [14] used an improved SSD-MobileNetV2 model for detecting anchor holes in coal mines. Lei et al [15] employed a binocular vision technique to locate anchor holes in coal mine tunnels, but the accuracy of these methods can still be impacted by factors such as dust and poor lighting in mine tunnels.…”