Automated Steering Control for Articulated Off-Highway Machines

Automated steering control is a more and more important function for Articulated Off-Highway Machines (AOHMs) operating in construction, mining, and forestry. Their articulation-based kinematics enable high maneuverability but also introduce challenges for lateral control, particularly when tracking paths with large curvature or frequent directional changes. In the forestry industry, AOHMs must achieve precise and stable path tracking in unstructured environments, where disturbances and dynamic path updates are common. This paper investigates a combined control approach that combines a Pure Pursuit (PP) and a Stanley (ST) controller into a feedforward–feedback framework tailored to AOHMs. As an example application in an AOHM, a forwarder is used in simulations on four representative paths—circular, sinusoidal, straight, and real-world trajectories—in both forward and backward driving. The results show that the PP-ST controller consistently outperforms the individual controllers, achieving maximum lateral errors below 0.2 ‍m across all test paths. Robustness analysis under dynamic steering and velocity noise, payload variation, and initial offsets demonstrates convergence in all cases, with steady-state lateral errors remaining within 0.1 ‍m. Even for extreme orientation deviations at the initial position, the controller eventually corrects the trajectory and returns to the reference path. Overall, the PP–ST controller provides accurate, stable, and robust lateral control for articulated off-highway machines in representative forestry scenarios.