Abstract:

In modern mining practices, a new goal for the industry is a fully autonomous mine. Most original equipment manufacturers (OEMs) are working towards automating their equipment or parts of the machine’s functionality, but once all the machinery is automated, making them all work together will be necessary to fully automate production. This will increase production, worker safety, and overall efficiency. A centralized computer system, monitoring each piece of equipment’s individual data stream, can ultimately replace today’s dispatch rooms. The system automatically dispatches all vehicles based on measured conditions around the mine and adapt to changes as they happen, such as unplanned maintenance, stockpile backups, blending changes, production target changes and blast scheduling changes. The centralized computer system is controlled by an artificial intelligence (AI) algorithm that is able optimize to a certain predetermined goal based on the current measurements provided by the machines. This type of system can be classified as a centralized heterogeneous robot swarm as all vehicles are working towards a common goal and controlled by a centralized computer, but each robot has a different specific task. The AI optimizes the scenario by altering paths of vehicles, changing loading and drop off points, vehicle speeds, and loading conditions to ensure the predetermined goal can be achieved. A goal must be chosen for the fleet based on each mine’s individual needs. Training this algorithm must be done for each installation and mine to suit individual needs and different fleet configurations. A scaled down proof of concept has been created to showcase the AI and fleet behaviors for certain scenarios to show how the fleet automatically makes schedule changes.

Biography of the presenter: Ryan Kealey is in the second year of his master’s program at Queen's University under the supervision of Dr. Yuksel Asli Sari at the Robert M. Buchan Department of Mining at Queen’s University. He graduated with a BASc in mining engineering mechanical option in 2019. During his undergrad Ryan completed a 12-month internship with MacLean Engineering as a hydraulic and mechanical designer. The following summer before his final year of his undergraduate degree, he worked with the Offroad Robotics Lab under the supervision of Dr. Joshua Marshall on a NSERC Engage project with Maclean to create concepts for a robotic underground scissor bolter. A prototype platform called the IBEX was constructed as a proof of concept and is currently still being improved upon on in the lab by other researchers. In the summer of 2019, he worked at DRDC Suffield in the Autonomous Systems UGV group creating a Lidar based gesture recognition software to control large robots. His research interests include mine automation, autonomous mining robots, and using AI to control autonomous mining fleets. In his spare time Ryan likes to play guitar, snowboard and hike.

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Oscar Rielo