Trajectory Planning-Aided Cooperative Localization for Multi-AUV Networks Under Harsh Communication Conditions: A Co-Designed Approach

In the operation of multiple autonomous underwater vehicle (AUV) networks, AUV self-localization, inter-AUV communication, and AUV trajectory planning (collectively referred to as LCP) are fundamental technologies. Among them, accurate position estimation is often a prerequisite for effective planning, while communication is essential in both parts. Previous studies have typically addressed these three areas independently, yet their conflicting demands on resources, objectives, etc., frequently pose significant challenges to performance improvement. This paper investigates the LCP from an integrated perspective and a co-designed approach jointly addresses all of them is proposed based on graphical models and belief propagation. Specifically, guided by the various underwater communication conditions, a cooperative localization algorithm for AUVs is designed with the assistance from trajectory planning. Different from the previous, planning results are directly used for localization to resist harsh communications, rather than indirectly affecting localization accuracy by, for example, optimizing geometric relationships. As a result, the feedback enhancement from trajectory planning to AUV localization is realized and the mechanism of their mutual promotion for different communication conditions is achieved. Moreover, considering the changing trajectories, the proposed cooperative localization algorithm is further refined for underwater obstacle-avoidance scenarios. Various simulations and field experiments validate that the proposed algorithm can improve the overall performance of LCP by comparisons with state-of-the-art alternative methods.