Resumen
A new method is proposed for the dynamic obstacle avoidance problem of unmanned surface vehicles (USVs) under the international regulations for preventing collisions at sea (COLREGs), which applies the particle swarm optimization algorithm (PSO) to the dynamic window approach (DWA) to reduce the optimal trajectory finding the time and improve the timeliness of obstacle avoidance. Meanwhile, a fuzzy control algorithm is designed to dynamically adjust the weight coefficients of the velocity and obstacle distance terms in the cost function of the DWA algorithm to adapt to the changes in the environment. The proposed dynamic obstacle avoidance method is experimentally validated, in which proposed PSO combined with the DWA algorithm (PSO-CCDWA) results in a 42.1%, 11.2% and 28.0% reduction in the navigation time of the USVs in three encounter-situations of COLREGs than that of the classical DWA algorithm (CCDWA) conforming to the conventional COLREGs, respectively. The fuzzy control combined with the DWA algorithm (FUZZY-CCDWA) reduces the distance traveled by 15.8%, 0.9% and 2.8%, respectively, over the CCDWA algorithm in the three encounter scenarios. Finally, the effectiveness of the proposed dynamic obstacle avoidance method is further verified in a practical navigation experiment of a USV named ?Buffalo?.