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Peer-Review Record

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

Mathematics 2025, 13(22), 3612; https://doi.org/10.3390/math13223612
by Yongqing Zhang, Pingan Peng *, Liguan Wang, Mingyu Lei, Ru Lei, Chaowei Zhang, Ya Liu, Xianyang Qiu and Zhaohao Wu
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Mathematics 2025, 13(22), 3612; https://doi.org/10.3390/math13223612
Submission received: 24 September 2025 / Revised: 25 October 2025 / Accepted: 30 October 2025 / Published: 11 November 2025

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Authors have reported work on borehole trajectory, few suggestion are expected 

    • The paper mentions using static bias compensation and Butterworth filtering. What changes can be anticipated if Kalman filtering or machine learning-based bias modelling are used?
    • Given the cubic spline interpolation used to align displacement and attitude data, how does interpolation error affect the final trajectory reconstruction, especially in high-dynamic scenarios?
    • The experiments were conducted in simulated PVC pipes, what will be expected outcomes in real system
    • What are the limitations of the robot’s mobility in terms of borehole diameter, curvature, and surface roughness? Is the system adaptable to different borehole geometries?
    • what communication protocol is used for real-time data transmission in deep boreholes?
    • Could the authors elaborate on how the proportional and integral gains were selected?
    • Authors are requested to compare the performance with other fusion algorithms such as Extended Kalman Filters (EKF) or Unscented Kalman Filters (UKF)?
    • how does interpolation error affect trajectory accuracy, especially under high-dynamic motion conditions?
    • What are the limitations of the robot’s mobility in terms of borehole diameter, curvature, and surface roughness?
    • Is the system adaptable to varying borehole geometries?
    • Could the authors elaborate on how the fusion strategy specifically mitigates long-term drift compared to traditional methods?
    • In Pipe 2, which includes steep inclines and bends, how does the system handle transitions in curvature? Is there any degradation in performance at sharp directional changes?
    • Could this approach be extended to a swarm of robots for parallel surveying in large-scale mining operations?

 

Author Response

"Please see the attachment.“

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The research topic sounds interesting and promising, but some improvements in writing must be highlighted:

  1. This manuscript is too long for a paper, 10 - 15 pages are enough.
  2. Many unnecessary parts are written in the manuscript, but some important parts, like Figure 6, still lack of explanation.

Comments for author File: Comments.pdf

Author Response

 "Please see the attachment."

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Figures 13, 14, 16 and 17 show a larger error in the discrete inclinometer curve. Is this comparable with the reference trajectory? A 2-m error is too large for the measurements taken.

Author Response

 "Please see the attachment."

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Authors have satisfactorily revised the paper

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