Zixiao Zhu

Positioning errors introduced by low-precision navigation devices can affect the overall accuracy of a positioning system. To address this issue, this paper proposes a master-slave multi-AUV collaborative navigation method based on hierarchical reinforcement learning. First, a collaborative navigation system is modeled as a discrete semi-Markov process with defined state and action sets and reward functions. Second, trajectory planning is performed using a hierarchical reinforcement learning-based approach combined with the polar Kalman filter to reduce the positioning error of slave AUVs, realizing collaborative navigation in multi-slave AUV scenarios. The proposed collaborative navigation method is analyzed and validated by simulation experiments in terms of the relative distance between the master and slave AUVs and the positioning error of a slave AUV. The research results show that the proposed method can not only successfully reduce the observation and positioning errors of slave AUVs in the collaborative navigation process but can also effectively maintain the relative measurement distance between the master and slave AUVs within an appropriate range.

To reduce the cooperative positioning error and improve the navigation accuracy, a single master–slave AUV cooperative navigation method is proposed in this paper, which mainly focuses on planning the optimal path of the master AUV by the time difference (TD) method, under the premise that the path of the slave AUV has been planned. First, the model of multi-AUV cooperative navigation is established, and the observable problem of the system is analyzed. Second, for the single master–slave AUV cooperative navigation system, a Markov decision process (MDP)-based multi-AUV cooperative navigation model is established, and the master AUV path planning method is designed based on the TD method. Finally, the extended Kalman filter (EKF) and unscented Kalman filter (UKF) nonlinear filtering algorithms are applied to simulate and verify the algorithm that is proposed in this paper. The results show that the theoretical positioning error of the slave AUV can be controlled to about 3.2m by planning the path of the master AUV using the TD method. This method can not only reduce the observation error and positioning error of the slave AUV during the whole cooperative navigation process, but also keep the relative measurement distance between the master AUV and the slave AUV within an appropriate range.