A path planning method based on an improved synchronous bidirectional A-star algorithm and grey wolf optimization algorithm is proposed for the multi-objective cruising path planning problem of unmanned boats. Firstly, the traditional A-star algorithm has been improved by introducing a synchronous bidirectional search strategy and dynamic weight adjustment, reducing path redundancy points and algorithm computation time. Then, the cruise path planning problem is transformed into a classic traveling salesman problem and solved using an improved grey wolf optimization algorithm to obtain the optimal cruise path. The experimental results show that the method proposed in this paper is superior to traditional methods in terms of total distance, number of turns, and computation time in path planning. It can effectively improve the cruising efficiency and safety of unmanned boats and provide a reliable solution for multi-target point cruising tasks of unmanned boats.