Research on global path planning of ships based on improved DQN algorithm

Objective In order to improve the economy and safety of ship navigation path in the actual sea environment, a ship global path planning method with improved Deep Q Network (DQN) algorithm is proposed

Method First, the preferential experience replay mechanism is introduced to give higher weights to important samples to improve learning efficiency. Then, the network structure of DQN is improved through duel network and noise network, so that it can evaluate the value of specific states and actions more accurately, and at the same time have certain exploration and generalization.

Result The experimental results show that compared with the A* algorithm and DQN algorithm, the improved algorithm reduces the path length by 1.9% and 1.0%, and the number of turning points by 62.5% and 25%, respectively, in the Marine environment near Maynila.

Conclusion It is verified that the improved DQN algorithm can plan the effective path more economically and rationally.