A method and system for task allocation and resource scheduling of an unmanned underwater vehicle

CN122284402APending Publication Date: 2026-06-26BEIJING ZHONGAN INTELLIGENT INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING ZHONGAN INTELLIGENT INFORMATION TECH CO LTD
Filing Date
2026-02-28
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

In dynamic and highly disruptive maritime combat scenarios, the centralized control architecture of existing unmanned underwater vehicle swarms is vulnerable to attack and failure, making it difficult to respond quickly to local threats. The timing synchronization accuracy decreases, resulting in insufficient mission execution accuracy and coordination capabilities.

Method used

A distributed negotiation and reputation evaluation mechanism is adopted, and task allocation is carried out in combination with fish and bird flock rules. Disturbances are predicted and compensated through environmental digital twin model. A hierarchical control architecture and a time-series architecture are constructed to realize adaptive motion control and resource scheduling. Robust time-series estimation and filtering are introduced to suppress noise interference. A dual-mode operation and online learning mechanism is designed.

Benefits of technology

It enhances the survivability and mission resilience of unmanned underwater vehicle swarms in adversarial environments, ensures high-precision coordination and autonomy in complex marine environments, and enables adaptive adjustment of formation modes to achieve system self-optimization and improved survivability.

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Abstract

This invention belongs to the field of unmanned underwater vehicle (UUV) swarm collaborative control technology, and provides a method and system for task allocation and resource scheduling of UUVs. The method includes biomimetic swarm intelligent decision generation, closed-loop transformation from decision to motion control, anti-interference timing synchronization and resource coordination, and system-level integration and security assurance. It adopts a fully distributed task negotiation and reputation evaluation mechanism, eliminating dependence on a single central node and improving the survivability and mission resilience of the swarm in adversarial environments. By introducing an environmental digital twin model for feedforward compensation and combining it with hierarchical adaptive control, a closed-loop transformation from intelligent decision-making to precise motion is achieved, overcoming control deviations caused by ocean disturbances and ensuring the accuracy of complex maneuvers and formation coordination. A hierarchical anti-interference timing synchronization system is constructed to suppress impulse noise, maintaining a high-precision time base at the microsecond to millisecond level even in harsh environments, thereby ensuring accurate coordination of cross-platform resource scheduling.
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