Author ORCID Identifier
https://orcid.org/0009-0003-9164-2526
Date Available
8-12-2025
Year of Publication
2025
Document Type
Master's Thesis
Degree Name
Master of Science in Mining Engineering (MSMIE)
College
Engineering
Department/School/Program
Mining Engineering
Faculty
Pedram Roghanchi
Faculty
Steven Schafrik
Abstract
Underground mining environments pose unique safety challenges for workers due to poor visibility, unstable ground conditions, and the absence of GPS signals. To adhere to safety and health standards, underground mines are required to perform safety inspections regularly. Conventional safety inspections require personnel to enter the hazardous environment, highlighting the need for a safer, remote alternative. The use of UAVs for safety inspection in underground mines is a somewhat novel idea but has shown great promise. While Unmanned Aerial Vehicles (UAVs) cannot eliminate all hazards associated with mining, they provide critical support by accessing hazardous or restricted zones that are unsafe for personnel to enter. This thesis presents the development and validation of an autonomous UAV flight control system for remote inspection in room-and-pillar underground mines. The proposed system integrates the PX4 flight stack with MAVSDK for offboard control and employs Visual-Inertial Odometry (VIO) for real-time localization in GPS-denied environments. A series of test flights were conducted in both an indoor drone cage and an underground mine to evaluate the UAV’s performance in executing key inspection tasks, including stable hovering, incremental movement, and controlled flight around vertical obstructions. Results demonstrated consistent maneuverability in confined spaces, with significant improvements in VIO stability under enhanced lighting conditions. This research offers a scalable and repeatable solution for autonomous UAV-based mine inspections, reducing human exposure to risk and enhancing the reliability of underground safety assessments.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2025.322
Funding Information
This study was funded by the National Institute for Occupational Safety and Health (NIOSH) under the award #U60OH012351 in 2023.
Recommended Citation
Joao, Kiazoa M., "AN AUTONOMOUS ROBOTIC INSPECTION SYSTEM FOR UNDERGROUND MINES USING UNMANNED AERIAL VEHICLES (UAVs)" (2025). Theses and Dissertations--Mining Engineering. 92.
https://uknowledge.uky.edu/mng_etds/92
