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    Greenland Resources’ Malmbjerg and LTU BOREAS: automation takeaways for mine planners

    May 22, 2026|

    Reviewed by Tom Sullivan

    First reported on International Mining – News

    30 Second Briefing

    Greenland Resources has joined Luleå Tekniska Universitet’s BOREAS consortium, alongside 12 other partners, to develop autonomous robotic systems for its Malmbjerg molybdenum project in central-east Greenland. The collaboration targets robotic support for construction, operation and maintenance in remote, high-relief terrain, where steep slopes, ice, and limited access complicate conventional open-pit development. For mine planners and geotechnical teams, the work signals future deployment of field robots for tasks such as bench inspection, slope monitoring and infrastructure upkeep under Arctic conditions.

    Technical Brief

    • Agreement makes Greenland Resources A/S a formal industrial partner within LTU’s BOREAS consortium.
    • BOREAS scope explicitly targets autonomous systems for construction, operations and maintenance phases, not just production drilling.
    • Robotics work is framed around Arctic, high-relief logistics constraints rather than generic open-pit automation.
    • LTU-led work packages are expected to integrate field robotics, sensing and autonomy software for outdoor mining tasks.
    • Research methods will likely include hardware-in-the-loop testing and field trials in cold-climate testbeds before Malmbjerg deployment.
    • Immediate applications envisaged include robotic support for remote infrastructure maintenance and inspection under severe weather windows.
    • Scope is limited to “support” functions; primary extraction and haulage automation are outside the named BOREAS remit.

    Our Take

    With 12 other participants in the BOREAS project alongside LTU and Greenland Resources, Malmbjerg is likely to benefit from a multi-vendor automation ecosystem rather than a single OEM solution, which can reduce lock-in risk for a remote Greenland deployment.

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    Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.

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