A Stable Path Following Algorithm Based on Adaptive Target Points for Unmanned Surface Vehicles

This study proposes a stable and robust path following algorithm for Unmanned Surface Vehicles (USVs). The main objective of this paper is to optimize a key parameter in the improved algorithm to minimize tracking errors. In this study, firstly a stability criterion is developed to limit this parameter and make stable navigation. This model determines the unique target points for each time step using the optimum and flexible parameter in contrast fixed value used in previous studies. The proposed stability criterion and the turning rate data obtained from the previous time step are used to determine this optimum parameter. It provides smooth and precise navigation at critical points like as sharp turning maneuvers. Moreover, it includes saturation for maximum turning rate to make realistic navigation. The proposed model in this study reduces tracking errors by around 20% compared to the conventional carrot-chasing algorithm. Finally, a numerical simulator for USVs in the Matlab environment has been included in the Appendix to support the work of other researchers.