Distributed unmanned ship cluster division and formation control method

Abstract

The invention discloses a distributed unmanned ship cluster division and formation control method, which comprises the following steps: S1, performing environmental perception on a target region by adopting a method of combining a Bayesian network and a body in an information fusion technology; S2, determining the number of required unmanned ships according to the characteristic of a task and a navigation environment, dividing unnamed clusters, and determining feasible formation patterns; S3, selecting an optimal task formation pattern or a secondary optimal task formation pattern from the feasible formation patterns according to an optimization index and a performance index of the task; S4, performing simulation and testing: performing modeling simulation according to the selected task formation pattern and the navigation environment, and testing the robustness and the fault tolerance of the task formation pattern, then ending. According to the method, a collaborative formation pattern of the unmanned ship clusters can be efficiently and flexibly changed, and the method has the advantages of safety, stability and reliability.

Description

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AI Technical Summary

Benefits of technology

This technology helps improve the security and performance of an Unmanned Boat (UB) system by making it more efficient or flexible than traditional methods like manned boats. It also optimizes tasks based on factors such as distance from other ships that may be affected with them.

Problems solved by technology

This patents discuss how current methods used for managing dronyscopic ships lack flexibly across varying terrains and scenarios while optimally navigating them over terrain. Current systems rely heavily on individual vessels equipped with specific components like radars (radial) technology to achieve their desired goals. Additionally, existing approaches focus primarily on forming stable structures around the vessel itself without taking advantage of its own dynamics.

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