Abstract: To solve the problem of traversal multi-goal path planning for unmanned cruise ships, a hybrid path planning method is proposed. This method is divided into two parts. Firstly, the multi-goal path planning problem is transformed into the travel salesman problem and an improved grey wolf optimizer (GWO) algorithm is used to calculate the multi-goal cruise sequence. In view of the unconsidered environmental factors in the traditional GWO algorithm, the environmental impact factors are introduced into the fitness function to reflect the impact of obstacles and unknown areas on multi-goal sequence planning. Secondly, based on the planned goal sequence, the A* algorithm is combined with the improved artificial potential field (APF) method to complete the single-goal path planning between each goal. The goal nonreachable problem of the traditional artificial potential field method is solved by the optimized repulsive potential function. Finally, the comparative simulation experiments with other two algorithms in ordinary and complex environment are carried out. The experimental results verifies the effectiveness of the proposed hybrid algorithm. Through the statistical analysis of experimental results, the proposed hybrid algorithm exhibits better performance than other two methods in terms of distance and time costs, and the effectiveness of the proposed hybrid algorithm is verified..

Key words: unmanned cruise ships, multi-target path planning, improved grey wolf optimizer algorithm, A* algorithm, improved artificial potential field method