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原文摘要

Fully autonomous tractor-trailer systems are increasingly deployed in logistics, agriculture, and industrial environments, where precise and robust path-tracking capabilities are essential. However, the articulation between the tractor and the trailer introduces additional nonlinearities and significantly complicates lateral and longitudinal control, particularly during reversing maneuvers. This paper introduces a novel path-tracking algorithm specifically designed for articulated vehicles with a single trailer. The proposed method combines a lateral control law applied at the trailer level with a short-horizon predictive adjustment of the tractor steering angle, ensuring stable convergence toward the desired path in both forward and backward motion. The approach is geometry-based and requires no per-vehicle calibration or training. Simulation studies in a high-fidelity physics simulator show steady-state or final lateral errors of $0.02$--$0.05$~m on straight-line, circular, and reverse docking trajectories, which is of the same order of magnitude as, or lower than, the errors reported in the literature. Real-world experiments on a small-scale tractor--trailer robot, with the whole controller running on a low-cost microcontroller, further confirm the feasibility of the approach, with lateral errors below 13~mm during repeated reverse docking maneuvers despite a pose detection latency of about 200~ms.