Robotics

Autonomous robotic system developed to monitor underground mines

West Virginia University engineers have developed an autonomous robotic system designed to monitor the structural integrity and safety of underground maps, which could prevent mining accidents.
By Olivia Miller October 17, 2019
Researchers from the Statler College of Engineering and Mineral Resources are developing an autonomous robotic system to monitor the structural integrity and safety of underground mines. Pictured are Yu Gu and Jason Gross, of the Statler College; Barry Fink and Richard Rohrssen, of Laurel Aggregates; and Berk Tulu and Guilherme Pereira, of the Statler College. Courtesy: Paige Nesbit, West Virginia University

Injuries and deaths caused by roof collapses and falling debris, common culprits for underground mine accidents, could be prevented by the unlikely force of robots and drones, according to research by West Virginia University engineers. They have developed an autonomous robotic system designed to monitor the structural integrity and safety of underground maps.

By using a combination of remote vehicles that consist of an unmanned aerial vehicle attached to an unmanned ground vehicle, the team will provide high-resolution 3D maps for assessment of pillar and roof damage.

The researchers were awarded a $750,000 grant from the Alpha Foundation to conduct this research on the health and safety of underground miners.

“Ultimately, this project will develop an early warning system that will notify the mine engineers for elevated hazardous conditions in underground stone mines,” said Ihsan Berk Tulu, assistant professor of mining engineering.

According to Tulu, in underground mines in the United States, “fall of ground”-related accidents are one of the leading causes of injuries. This occurs when part of the roof or a pillar collapses. Although underground stone mines have generally experienced good ground stability, a recent mine pillar collapse in Whitney, Pennsylvania and reported roof fall accidents in other mines highlight the potential safety impact on the miners.

“The autonomous robotic early warning system for monitoring stone mines will enable a rapid response to detected degradations in pillar and roof stability,” Tulu said. “Successful development and deployment of this system is expected to reduce injuries of underground stone mine workers.

“While the initial problem is associated with pillar stability and design, the techniques developed in this research would be easily adaptable to the underground coal and metal/nonmetal mining sectors,” Tulu said. “The autonomous robots mapping ability would also be adaptable to facilitate search and rescue efforts in case of an accident.”

The researchers will leverage similar technology to what is currently under development for underground tunnel rescue operations by the WVU robotics team to develop the robotic system. The system will then be deployed to Laurel Aggregates underground stone mine in Lake Lynn, Penn., for additional testing.

West Virginia University

www.wvu.edu

– Edited by Chris Vavra, production editor, Control Engineering, CFE Media & Technology, cvavra@cfemedia.com.


Olivia Miller
Author Bio: Olivia Miller, communications specialist of marketing and communications, West Virginia University