Cooperative positioning of underwater unmanned vehicle clusters based on factor graphs

With the increasing humanity marine activities, underwater UUV Cluster have become the main carriers for marine environment monitoring and marine resources development. Undersea development has shifted away from single-use UUV missions, and the difficulty of positioning within underwater UUV clusters has made this area particularly challenging for applications. The paper suggests a method of cooperative positioning for underwater UUV clusters, which is supported by factor graphs and addresses the issues mentioned above. The approach utilizes factor graphs and the product theory to combine range information between underwater UUV clusters, resulting in a distributed cooperative positioning architecture for each UUV, and multiple confocal positioning models that can predict their flight path. In the experimental tests, the proposed method is compared to the existing methods with respect to positioning accuracy and convergence speed, and the results demonstrate the proposed method has higher positioning accuracy and faster convergence speed, and has good suppression capability for mutation errors.