Multi-center unmanned aerial vehicle selection method for unmanned aerial vehicle distributed task planning

Abstract

The invention discloses a multi-center unmanned aerial vehicle selection method for unmanned aerial vehicle distributed task planning. The method comprises the following steps: inputting source data to all other unmanned aerial vehicles through a data acquisition module of each unmanned aerial vehicle in an unmanned aerial vehicle group; generating a direct communication link between every two unmanned aerial vehicles of the unmanned aerial vehicle group; determining a central unmanned aerial vehicle; and determining a communication link between the central unmanned aerial vehicles. According to the method, the plurality of central unmanned aerial vehicles can be quickly elected to continue to execute task planning, on one hand, the unmanned aerial vehicle group can be prevented from being paralyzed when single-point failure occurs, and on the other hand, the number of the unmanned aerial vehicles participating in task planning can be effectively reduced, so that the communication information amount is reduced.

Description

technical field [0001] The invention relates to the technical field of unmanned aerial vehicles, in particular to a multi-center unmanned aerial vehicle selection method for centralized and distributed mission planning of unmanned aerial vehicles. Background technique [0002] With the advantages of adaptability, flexibility and low cost in 4D ("Dall", "Dirty", "Dangerous", "Deep") environments, UAVs are increasingly used in complex mission scenarios, such as battlefields Intelligence collection and attack, urban fire extinguishing, unmanned express delivery, power grid inspection, plant protection, etc. Among them, in the process of cooperative mission execution by multiple UAVs or UAV clusters, due to the constraints of mission requirements, flight environment and UAVs themselves, complex mission planning problems need to be solved. The mission planning problem is to find the optimal match between UAVs and tasks given N available UAVs and M tasks, so as to maximize the to...

AI Technical Summary

Problems solved by technology

Since all UAVs are required to complete the mission through information interaction, the mission planning has the problem of a large amount of communication information, that is, the amount of communication information or the number of information interactions increases exponentially with the increase in the number of UAVs.

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