A bilevel task allocation method for heterogeneous multi-UUV recovery system

This paper presents a novel task allocation method for multiple unmanned underwater vehicles (multi-UUV) recovery systems. Specifically, a bilevel model that enjoys the advantages of centralized and distributed methods is constructed for mothership and cooperative constraints. In the centralized upper-level, an improved Gaussian mixture mode (IGMM) is presented, and an improved discrete crow search algorithm (IDCSA) is proposed. Thus, the leaders are clustered into subgroups, and the matching relationship between motherships and subgroups is established. In the distributed lower-level, the proposed consensus-based bundle algorithm with group constraint (CBBA-GC) addresses the allocation problem between subgroups and heterogeneous follower UUVs. It is found that the proposed bilevel method can achieve conflict-free and load-balanced multi-UUV recovery task allocation when the communication capability of each UUV and motherships recovery ability are heterogeneous.