CN-121979228-A - MAGICDRAW-based unmanned plane bee colony dynamic role allocation control method and system

CN121979228ACN 121979228 ACN121979228 ACN 121979228ACN-121979228-A

Abstract

The invention relates to a MAGICDRAW-based unmanned aerial vehicle bee colony dynamic role allocation control method and system, which comprise the steps of defining unmanned aerial vehicle bee colony node role allocation requirements on MAGICDRAW tools, judging whether a node needs to take over according to definition after the node is disabled, calculating the health degree of the node according to health degree parameters broadcasted by the unmanned aerial vehicle node, judging whether the node has a fault, determining role allocation take over cost of candidate unmanned aerial vehicle nodes under the fault condition, taking over the candidate unmanned aerial vehicle nodes with the minimum take over cost for the fault unmanned aerial vehicle nodes, and synchronizing cluster topology update information generated after take over to all unmanned aerial vehicle nodes. The unmanned bee colony dynamic role allocation control system is constructed by utilizing the system modeling method of MAGICDRAW tools, and the system design is traceable, verifiable and realizable through unified modeling and rapid integration of multiple views, so that the dynamic allocation of unmanned bee colony roles in complex countermeasure scenes is satisfied.

Inventors

ZHAO LIQIANG
MA YUECHEN
SONG GUOPENG
YANG ZHIHONG
Chen Fengxiao

Assignees

航天时代飞鸿技术有限公司

Dates

Publication Date: 20260505
Application Date: 20251212

Claims (10)

1. MAGICDRAW-based unmanned aerial vehicle bee colony dynamic role allocation control method is characterized by comprising the following steps of: S1, defining unmanned aerial vehicle swarm node role allocation requirements on a MAGICDRAW platform, and judging whether a node needs to take over according to the definition after the node is disabled; s2, calculating the health degree of the node according to the health degree parameter broadcasted by the unmanned aerial vehicle node; S3, judging whether the node has a fault or not; S4, determining role allocation succession cost of the candidate unmanned aerial vehicle nodes under the condition of faults; S5, taking over the candidate unmanned aerial vehicle node with the minimum take-over cost for taking over the failed unmanned aerial vehicle node; s6, synchronizing cluster topology updating information generated after succession to all unmanned aerial vehicle nodes.
2. The method of claim 1, wherein the health parameters include power level, signal strength, and load status.
3. The method of claim 2, wherein the health is a sum of products of the power content, the signal strength, and the load status and the corresponding weights.
4. The method of claim 1, wherein the MAGICDRAW platform comprises a data layer and a control layer.
5. The method of claim 1, wherein the take-over cost is a sum of a task complexity factor divided by a health factor and a distance penalty factor, wherein the task complexity factor is a difficulty factor for the candidate drone to transition from the current role to the disabled drone role, and the distance penalty factor is a cost factor for the candidate drone to move to a predetermined task of the disabled drone that is unknown.
6. The method of claim 1, wherein the criterion in S3 is that the unmanned node loses heartbeat packets or that the health is continuously less than a specified threshold.
7. The method of claim 1, further comprising building a simulation test environment, and performing allocation and switching according to roles of the unmanned aerial vehicle swarm data failure nodes.
8. A MAGICDRAW-based unmanned aerial vehicle swarm dynamic role allocation control system, characterized in that the system is adapted to implement the method of any of claims 1-7, comprising the following modules: The role allocation requirement module is used for defining the role allocation requirement of the unmanned aerial vehicle swarm nodes on the MAGICDRAW platform, and judging whether the node needs to take over or not according to the definition after the node is disabled; The health degree detection module is used for calculating the health degree of the node according to the health degree parameters broadcast by the unmanned aerial vehicle node; the fault triggering module is used for judging whether the node has a fault or not; The dynamic role allocation module is used for determining role allocation succession cost of the candidate unmanned aerial vehicle nodes under the condition of faults; the role switching execution module is used for taking over the candidate unmanned aerial vehicle node with the minimum take-over cost for taking over the failed unmanned aerial vehicle node; And the updating module is used for synchronizing cluster topology updating information generated after succession to all unmanned aerial vehicle nodes.
9. A computer storage medium, characterized in that the medium has stored thereon a computer program which is executed by a processor to implement the method of any of claims 1-7.
10. An electronic device, the electronic device comprising: A memory storing executable instructions; A processor executing the executable instructions in the memory to implement the method of any of claims 1-7.

Description

MAGICDRAW-based unmanned plane bee colony dynamic role allocation control method and system Technical Field The invention belongs to the technical field of unmanned aerial vehicle bee colony control and distribution decision making, and particularly relates to a MAGICDRAW-based unmanned aerial vehicle bee colony dynamic role distribution control method and system. Background The unmanned aerial vehicle bee colony system has important application value in the fields of military collaborative combat, disaster emergency response, wide area logistics scheduling and the like, and has the core challenge of maintaining the efficient collaboration and robustness of the bee colony in a complex, dynamic and interference environment. The traditional centralized architecture has single point failure risk, but the full distributed architecture has low decision efficiency, and is difficult to adapt to sudden interferences such as node damage, electromagnetic suppression and the like. Meanwhile, the traditional development mode of handwriting codes and discrete simulation has the problems of difficult requirement tracing, multi-view cutting, document code disjointing and the like, so that the efficient cooperation of the bee colony in a complex dynamic environment cannot be met, and the unmanned plane bee colony dynamic role allocation control method and system based on MAGICDRAW are required. Disclosure of Invention The invention provides a MAGICDRAW-based unmanned aerial vehicle bee colony dynamic role allocation control method and a MAGICDRAW-based unmanned aerial vehicle bee colony dynamic role allocation control system for solving the problems of role allocation stiffness, low resource utilization efficiency and communication protocol coupling in an opposing environment of an unmanned aerial vehicle bee colony system. A control method for dynamic role allocation of unmanned aerial vehicle bee colony based on MAGICDRAW, the method comprising the following steps: S1, defining role allocation requirements of unmanned aerial vehicle swarm nodes on MAGICDRAW, and judging whether the node needs to take over according to definition after a certain node is disabled; s2, calculating the health degree of the node according to the health degree parameter broadcasted by the unmanned aerial vehicle node; S3, judging whether the node has a fault or not; S4, determining role allocation succession cost of the candidate unmanned aerial vehicle nodes under the condition of faults; S5, taking over the candidate unmanned aerial vehicle node with the minimum take-over cost for taking over the failed unmanned aerial vehicle node; s6, synchronizing cluster topology updating information generated after succession to all unmanned aerial vehicle nodes. Aspects and any of the foregoing, further providing an implementation, the health parameter includes a power level, a signal strength, and a load status. Aspects and any of the possible implementations as described above, further providing an implementation, wherein the health is a sum of products of the power content, the signal strength, and the load status and the corresponding weights. Aspects and any one of the possible implementations as described above, further provide an implementation of building a control architecture including a data layer and a control layer through MAGICDRAW. In accordance with the above aspect and any one of the possible implementations, there is further provided an implementation in which the take-over cost is a sum of a value obtained by dividing a task complexity factor by a health factor and a distance penalty factor, where the task complexity factor is a difficulty factor of the candidate drone to switch from the current role to the disabled drone role, and the distance penalty factor is a cost factor of the candidate drone to move to the disabled drone unknown to the predetermined task. In the aspect and any possible implementation manner as described above, there is further provided an implementation manner, where the criterion in S3 is that the unmanned node loses a heartbeat packet or the health is continuously smaller than a specified threshold. Aspects and any possible implementation manner as described above, further providing an implementation manner, and further including setting up a simulation test environment, and distributing and switching according to roles of the unmanned aerial vehicle bee colony data fault nodes. The invention also provides a MAGICDRAW-based unmanned plane bee colony dynamic role allocation control system, which is used for realizing the method and comprises the following modules: The role allocation requirement module is used for defining the role allocation requirement of the unmanned aerial vehicle swarm nodes on the MAGICDRAW platform, and judging whether the node needs to take over or not according to the definition after the node is disabled; The health degree detection module is used for calculating the health degree o