Behavior modeling and collaborative optimization method and system for unmanned aerial vehicle clustering process

A collaborative optimization and unmanned aerial vehicle technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of lack of quantitative representation in research and optimal design of unmanned aerial vehicle clusters, and achieve the effect of behavior prediction

Pending Publication Date: 2022-05-13
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

However, the existing methods have not conducted in-depth research from the perspective of "individual-group-top" in the emergence process, and the optimal design of UAV clusters also lacks quantitative characterization

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  • Behavior modeling and collaborative optimization method and system for unmanned aerial vehicle clustering process
  • Behavior modeling and collaborative optimization method and system for unmanned aerial vehicle clustering process
  • Behavior modeling and collaborative optimization method and system for unmanned aerial vehicle clustering process

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Embodiment Construction

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0048] The purpose of the present invention is to provide a UAV cluster process behavior modeling and collaborative optimization method and system, which can effectively realize the behavior prediction of the UAV cluster, avoid the decision-making from falling into local optimum, and help to explore and influence the top-level design The underlying optimal decision parameters of .

[0049] In order to make the above objects, features and advantages of the pres...

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Abstract

The invention relates to an unmanned aerial vehicle clustering process behavior modeling and collaborative optimization method and system. The method comprises the steps of performing hierarchical decomposition on an unmanned aerial vehicle cluster system by adopting a top-down layer-by-layer decomposition strategy, and determining an individual decision layer, a group behavior layer and a top design layer; acquiring sample data of the unmanned aerial vehicle cluster system by using a NetLogo simulation platform; respectively establishing a function mapping relationship between the individual decision and the group behavior and a function mapping relationship between the group behavior and the top design by using the BPNN; taking task completion degree, design cost and design efficiency as optimization objectives, taking a parameter range of an individual decision-making layer as a constraint condition, and constructing a target function of multi-objective optimization based on a mapping relation of two functions; and performing global search on the target function of the multi-target optimization based on NSGA-II to determine a global optimal solution. According to the method, behavior prediction of the unmanned aerial vehicle cluster can be effectively realized, the decision is prevented from falling into local optimum, and bottom-layer optimal decision parameters influencing top-layer design can be explored.

Description

technical field [0001] The invention relates to the field of group intelligence behavior, in particular to a method and system for modeling and collaborative optimization of unmanned aerial vehicle cluster process behavior. Background technique [0002] The UAV cluster is composed of a certain number of homogeneous and heterogeneous UAVs, etc., using sensors for information interaction, and real-time adjustment through feedback to achieve specified tasks. Compared with single drones, drone clusters involve larger scale, higher coordination, and stronger intelligence. Nowadays, UAV swarm technology has been widely used in national defense construction and civilian fields. Its research focuses on how to model the process behavior of UAV swarms and optimize the efficiency of collaboration. It has the ability to adapt to complex, changeable and uncertain environments. ability. [0003] Due to the emergent self-organization of UAV swarms, individual decisions tend to lead to lo...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/084G06N3/045
Inventor 明振军丁伟阎艳王国新郝佳姚丽亚
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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