This article introduces a five-tiered route planner for accessing multiple
nodes with multiple autonomous underwater vehicles (AUVs) that enables
efficient task completion in stochastic ocean environments. First, the
pre-planning tier solves the single-AUV routing problem to find the optimal
giant route (GR), estimates the number of required AUVs based on GR
segmentation, and allocates nodes for each AUV to access. Second, the route
planning tier plans individual routes for each AUV. During navigation, the path
planning tier provides each AUV with physical paths between any two points,
while the actuation tier is responsible for path tracking and obstacle
avoidance. Finally, in the stochastic ocean environment, deviations from the
initial plan may occur, thus, an auction-based coordination tier drives online
task coordination among AUVs in a distributed manner. Simulation experiments
are conducted in multiple different scenarios to test the performance of the
proposed planner, and the promising results show that the proposed method
reduces AUV usage by 7.5% compared with the existing methods. When using the
same number of AUVs, the fleet equipped with the proposed planner achieves a
6.2% improvement in average task completion rate