Curvature-Coupled Adaptive Vector-Field Integral Line-of-Sight Guidance for Unmanned Surface Vehicle Path Following
Rongxia Ma, Bufan Zhou, Mingming Xu, Yunfei Wu, Hang Shi, Yusheng Yang, Xiaohan Guo, Yangmin XieAchieving high-accuracy path following remains challenging for an unmanned surface vehicle (USV) in narrow waterways with time-varying curvature and straight–curve transitions; fixed-parameter line-of-sight (LOS) guidance can cause delayed response, overshoot, and steady-state cross-track error. This paper proposes a curvature-coupled adaptive vector-field integral LOS (AVFILOS) guidance law. It incorporates curvature-adaptive guidance: a lookahead distance regulated by curvature and cross-track error and a field-source radius that contracts with curvature to strengthen centripetal correction in high-curvature regions. A fuzzy adaptive proportional–integral–derivative (PID) controller tracks surge speed and heading. A stability analysis establishes local exponential stability for straight and constant-curvature paths and local ISS with local uniform ultimate boundedness for time-varying curvature under a bounded-rate condition. Across six elliptical and sinusoidal cases, AVFILOS achieved an average root mean square error (RMSE(ye)) of 0.1325 m, reducing RMSE(ye) by 90.6%, 63.6%, and 37.2% compared with LOS, time-varying LOS (TLOS), and vector-field integral LOS (VFILOS), respectively. Its average maximum absolute cross-track error (Max(|ye|)) was 0.3478 m, with reductions of 88.2%, 48.2%, and 30.7%. The ablation and sensitivity results indicate that coupled adaptive mechanisms improve curved-path tracking and reduce overshoot. The simulations indicate that AVFILOS is promising for cross-track-error-sensitive USV navigation.