This paper proposes the use of close-distance optical flow measurements to enhance the Extended Kalman Filter (EKF) position and velocity estimation accuracy of Unmanned Aerial Vehicle (UAV) with the use of existing infrastructure in a GPS-denied environment. The scenario assumed in this project involves a UAV navigating through a mine shaft with a stationary central steel cable that passes through the shaft's center. The UAV has a special design with a hole in the center that allows it to fly up and down while keeping the central cable in its geometric center. The UAV is equipped with a camera facing parallel to the cable at a close and constant distance. Using optical flow algorithms, we can estimate the vertical velocity of the UAV. Using the EKF filter, we aim to integrate these velocity measurements with existing measurements from the Inertial Measurement Unit (IMU), magnetometer, and barometer, to improve the accuracy of the UAV's vertical velocity and height measurements.

This article investigates the causes of occasional flight instability observed in Unmanned Aerial Vehicles (UAVs). The issue manifests as unexpected oscillations that can lead to emergency landings. The analysis focuses on delays in the Extended Kalman Filter (EKF) algorithm used to estimate the drone’s attitude, position, and velocity. These delays disrupt the flight stabilization process. The research identifies two potential causes for the delays. First cause is magnetic field distrurbances created by UAV motors and external magnetic fields (e.g., power lines) that can interfere with magnetometer readings, leading to extended EKF calculations. Second cause is EKF fusion step implementation of the PX4-ECL library combining magnetometer data with other sensor measurements, which can become computionally expensive, especially when dealing with inconsistent magnetic field readings. This can significantly increase EKF processing time. The authors propose a solution of moving the magnetic field estimation calculations to a separate, lower-priority thread. This would prevent them from blocking the main EKF loop and causing delays. The implemented monitoring techniques allow for continuous observation of the real-time operating system’s behavior. Since addressing the identified issues, no significant problems have been encountered during flights. However, ongoing monitoring is crucial due to the infrequent and unpredictable nature of the disturbances.

This article investigates the feasibility of using cost-effective photogrammetry for monitoring convergence and lining deformation in the SW-4 mineshaft operated by KGHM. The study begins with a detailed description of the geological and operational environment of the mineshaft, with particular emphasis on the challenges posed by the rheological behavior of rock salt, which can lead to time-dependent deformations impacting shaft stability and safety. The methodology includes an overview of conventional convergence measurement techniques currently in use, followed by the design and implementation of a custom stereo-photogrammetric research platform. This platform was subjected to comprehensive validation, both in surface conditions and within the underground environment of the shaft. Surface trials incorporated comparative analysis with data acquired using a professional terrestrial laser scanner to assess the accuracy and reliability of the photogrammetric approach. Despite certain limitations in data acquisition due to the harsh underground conditions, two successful photogrammetric surveys were conducted within a shaft interval previously measured using high-precision laser tachymetry. These trials produced two dense point clouds that enabled precise measurement of displacement in both the shaft lining and the mining face over a four-month period. The results demonstrate the potential of this approach for detecting small-scale deformations and suggest that, with minor refinements to data capture and processing workflows, the proposed method can become a valuable tool for long-term monitoring and geomechanical analysis in the SW-4 rock salt section.

Underground mining operations depend heavily on vertical shafts for access, ventilation, and ore transport, making their structural integrity and safety critical to overall mine performance. Traditional shaft inspections, though rigorous, are limited by human accessibility, environmental hazards, and subjective evaluation. This study presents the development and initial testing of a novel unmanned aerial vehicle (UAV) system designed specifically for shaft inspections in deep mining environments. The research focuses on the GG-1 shaft in Kwielice, Poland—the country’s deepest operational shaft—where challenging conditions such as high ventilation airflow, confined geometry, and absence of GNSS signals necessitated innovative solutions. A custom-built hexacopter equipped with high-resolution cameras and photogrammetric capabilities was deployed to capture detailed visual and spatial data. This article presents complementary path of UAV evolution, from concept, early development stage and results without positioning system through to the description of final results including positioning system and all six cameras until results of high-altitude flights. Results demonstrate that UAV-based inspection can deliver sufficient precision for identifying structural irregularities, documenting shaft infrastructure, and enhancing safety monitoring. The findings highlight the potential of UAV technology as a complementary tool to conventional inspections, offering improved data quality, reduced risk to personnel, and a new approach to shaft maintenance.