Dynamic Locally Optimized Path Planning For Unmanned Surface Vehicle Under High Sea Conditions

The rapid development of artificial intelligence algorithms has promoted the intelligent transformation of the shipbuilding industry, and unmanned surface vehicle (USV) have become prominent representative products. However, in the case of offshore sailing, high sea state environmental impact may be encountered, and the wind, current and waves of the environment will change with time, so it is necessary to take into account the impact of wind, ocean currents and waves on the energy consumption and driving safety during the collision avoidance process of USV in real scenarios. Therefore, this paper introduces an Informed Affected DWA algorithm, called IA-DWA, that combines wind, current and wave assessment calculations, while improving the assessment methods of energy consumption and navigation safety. Simulation results show that, compared with Affected DWA algorithm, IA-DWA algorithm greatly improves time efficiency, energy consumption, and safety, and achieves collision avoidance.