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Gray-Box Model Predictive Control for Articulated Dump Trucks via Gaussian Process Learning of Sideslip

arXiv · AI, language, vision and robotics · article · Sep 23, 2026 · UTC

The growing demand for automation in the mining industry, particularly for the autonomous operation of articulated dump trucks (ADTs), has drawn increased attention to accurate vehicle modeling. The importance of such models lies in their use in model predictive control (MPC), model-based estimation methods, and vehicle simulation. While dynamic modeling offers a viable solution for these purposes, it is associated with complex setup and parametrization and may require recalibration in changing operating environments. As a result, kinematic models have dominated ADT modeling, especially in MPC

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