Planning for multiple autonomous drilling machines

Autonomous vehicles are becoming key components in industrial automation. A key area of application is mining, where use of autonomous machines is achieving the important goal of removing human operators from dangerous situations. Moreover, AI-based solutions for fleet management have the potential to make mining operations more efficient, and significant increases in productivity can be achieved if fleet operations are optimized and streamlined.

Atlas Copco and Örebro University have joined forces to achieve these goals through Semantic Robots’ research profile. Together we are developing complete solutions to address the problem of autonomous fleet management in open-pit mining. Key advances in the fields of constraint-based reasoning – hybrid problem solving, integrated motion planning and coordination – are necessary to bring about complete fleet management solutions.

Researchers from Semantic Robots and developers from Atlas Copco are working together to elicit and refine the problem specification, demonstrate research prototypes, and integrate key solutions into product prototypes. Several patent applications have resulted from this collaboration. For more information on the research results achieved so far please see the following publications:

Mansouri, M., Lagriffoul F., Pecora F. (2017) Multi-Vehicle Routing with Nonholonomic Constraints and Dense Dynamic Obstacles. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)