Year of Publication


Degree Name

Master of Science in Mining Engineering (MSMIE)

Document Type

Master's Thesis




Mining Engineering

First Advisor

Dr. Steven J. Schafrik


The mining sector is currently in the stage of adopting more automation, and with it, robotics. Autonomous bolting in underground environments remains a hot topic for the mining industry. Roof bolter operators are exposed to hazardous conditions due to their proximity to the unsupported roof, loose bolts, and heavy spinning mass. Prolonged exposure to the risk inevitably leads to accidents and injuries.

The current thesis presents the development of a robotic assembly capable of carrying out the entire sequence of roof bolting operations in full and partial autonomous sensor-driven rock bolting operations to achieve a high-impact health and safety intervention for equipment operators. The automation of a complete cycle of drill steel positioning, drilling, bolt orientation and placement, resin placement, and bolt securing is discussed using an anthropomorphic robotic arm.A human-computer interface is developed to enable the interaction of the operators with the machines. Collision detection techniques will have to be implemented to minimize the impact after an unexpected collision has occurred. A robust failure-detection protocol is developed to check the vital parameters of robot operations continuously. This unique approach to automation of small materials handling is described with lessons learned.

A user-centered GUI has been developed that allows for a human user to control and monitor the autonomous roof bolter. Preliminary tests have been conducted in a mock mine to evaluate the developed system's performance. In addition, a number of di fferent scenarios simulating typical missions that a roof bolter needs to undertake in an underground coal mine were tested.

Digital Object Identifier (DOI)

Funding Information

This study was supported by the Alpha Foundation for the Improvement of Mine Safety and Health in 2019.