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    Sandvik AutoMine Aura: mine-wide automation shift explained for engineers

    May 27, 2026|

    Reviewed by Joe Ashwell

    Sandvik AutoMine Aura: mine-wide automation shift explained for engineers

    First reported on Australian Mining

    30 Second Briefing

    Sandvik has launched AutoMine Aura, a next-generation underground automation platform that overhauls its 20‑year‑old AutoMine system with full situational awareness and a new software architecture. The platform is designed to coordinate mixed fleets of loaders and trucks across multiple levels, integrating collision avoidance, real‑time 3D visualisation and high‑precision localisation over mine‑wide networks. For engineers, the key shift is from machine‑centric automation to a mine‑wide, data‑driven control layer that can support higher traffic densities and more complex autonomous haulage layouts.

    Technical Brief

    • For other OEMs’ automation roadmaps, Aura signals a shift towards mine‑level operating systems rather than isolated vehicle automation.

    Our Take

    In our database of 1183 Mining stories, Sandvik appears frequently in Product-tagged pieces, and the pairing of AutoMine Aura with the upgraded Toro LH208L low-profile loader suggests Sandvik is targeting highly mechanised, low-headroom underground operations where full automation can unlock extra face time.

    The 2024 acquisition of Universal Field Robots, referenced in a related article, indicates Sandvik is already planning for AutoMine Aura to extend beyond traditional loaders and trucks to mixed fleets that include diesel and battery-electric robotic carriers, which will matter for brownfield sites retrofitting automation in stages.

    With AutoMine now more than 20 years old, this ‘first-of-its-kind’ platform launch in Australia positions Sandvik to defend its installed base against newer automation entrants, especially in jurisdictions where early AutoMine adopters are reaching decision points on life-extension versus wholesale system replacement.

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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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