Research on a Rapid and Accurate Reconstruction Method for Underground Mine Borehole Trajectories Based on a Novel Robot

Yongqing Zhang, Pingan Peng (), Liguan Wang, Mingyu Lei, Ru Lei, Chaowei Zhang, Ya Liu, Xianyang Qiu and Zhaohao Wu
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Yongqing Zhang: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Pingan Peng: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Liguan Wang: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Mingyu Lei: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Ru Lei: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Chaowei Zhang: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Ya Liu: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Xianyang Qiu: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Zhaohao Wu: School of Resources and Safety Engineering, Central South University, Changsha 410083, China

Mathematics, 2025, vol. 13, issue 22, 1-28

Abstract: A vast number of boreholes in underground mining operations are often plagued by deviation issues, which severely impact both production efficiency and safety. The accurate and rapid acquisition of borehole trajectories is fundamental for subsequent deviation control and correction. However, existing inclinometers are limited by their operational efficiency and estimation accuracy, making them inadequate for large-scale measurement demands. To address this, this paper proposes a novel method for the rapid and accurate reconstruction of underground mine borehole trajectories using a robotic system. We employ a custom-designed robot equipped with an Inertial Measurement Unit (IMU) and a displacement sensor, which travels stably while collecting real-time attitude and depth information. Algorithmically, a complementary filter is used to fuse data from the gyroscope with that from the accelerometer and magnetometer, overcoming both integration drift and environmental disturbances. A cubic spline interpolation algorithm is then utilized to time-register the low-sampling-rate displacement data with the high-frequency attitude data, creating a time-synchronized sequence of ‘attitude–displacement increment’ pairs. Finally, the 3D borehole trajectory is accurately reconstructed by mapping the attitude quaternions to direction vectors and recursively accumulating the displacement increments. Comparative experiments demonstrate that the proposed method significantly improves efficiency. On a complex trajectory, the maximum and mean errors were reduced to 0.38 m and 0.18 m, respectively. This level of accuracy is far superior to that of the conventional static point-by-point measurement mode and effectively suppresses the accumulation of dynamic errors. This work provides a new solution for routine borehole trajectory surveying in mining operations.

Keywords: underground mine; borehole deviation; complementary filter; trajectory reconstruction; robotic surveying (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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