School of Instrument Science and Engineering, Southeast University，Nanjing 210096, China
In order to improve the path planning efficiency of unmanned ships when performing water sampling tasks, a path planning algorithm combining ant colony algorithm and firefly algorithm is proposed. Firstly, when constructing the shortest path network, the steering angle cost heuristic function is introduced into the traditional ant colony algorithm to reduce frequent turns in the path search results. Then, redundant nodes in the search results are removed to further reduce the number of turns of the unmanned ship, so that the obtained path is more suitable for the unmanned ship. Finally, when solving the optimal sampling order, an improved firefly algorithm is designed based on random correction, which improves the convergence speed of the algorithm. The simulation results show that the algorithm designed in this paper can complete the path planning task of water sampling task. Compared with the traditional algorithm, the search efficiency is higher and the total path length is effectively shortened.