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    You are at:Home»News»Autonomous ag»Autonomous Loading Technology Takes a Step Forward 

    Autonomous Loading Technology Takes a Step Forward 

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    By admin on November 18, 2025 Autonomous ag, News

    A major development in autonomous material-handling technology for agriculture was showcased at Agritechnica 2025, where Claas introduced the Torion Autonomy connect, the first fully autonomous wheel loader designed specifically for agricultural operations. Aimed at biogas plants and dairy units, the system demonstrated how labour-intensive silage management tasks could be handled without an operator. 

    Developed in partnership with Liebherr, the autonomous loader used a combination of LiDAR-based environmental scanning and advanced AI to create a digital twin of its working area. This allowed the machine to plan and adapt its work cycle without the need for external surveying equipment or pre-mapped routes. The system also performed automated pile analysis, enabling it to detect material, calculate loading points, and select the most efficient route for every movement. 

    Through Claas connect, operators were able to pre-plan tasks using a small number of intuitive inputs, allowing the machine to carry out repetitive loading and material-handling operations with minimal supervision. The technology did not rely on GPS, making it fully functional inside buildings, feed sheds, or locations with canopy cover. 

    The machine operated in both fully autonomous and manual modes, offering operational flexibility for farms requiring multi-purpose loader capability. According to Claas, the technology represented a significant step towards automated silage logistics, especially for businesses facing skilled labour shortages or looking to optimise repetitive daily tasks. 

    The autonomous system independently executed work cycles, responded to environmental changes, and handled precision tasks such as accurate material pick-up and stacking, marking a major advance in autonomous feeding and biogas-plant workflows. 

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