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.