Flight control method for scheduling massive unmanned aerial vehicle cluster work

By introducing energy-saving path planning, space protection model, anti-collision strategies and autonomous obstacle avoidance algorithms into drone cluster control technology, the shortcomings of drone clusters in flight energy saving, collision avoidance and battery life are solved, and more efficient, stable and intelligent drone cluster operations are achieved.

CN119717857APending Publication Date: 2025-03-28JIANGXI PROVINCIAL MILITARY & CIVILIAN INTEGRATION RES INST +1
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Patent Information

Application Number
CN202411876953.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-19
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

The existing drone cluster control technology has shortcomings in flight energy saving, collision avoidance and battery life, especially the lithium battery with limited energy density limits the battery life of the drone.

Method used

A flight control method is proposed to schedule a large number of drone cluster operations. It can find the optimal path through the drone energy-saving path planning and obstacle avoidance algorithm, use the cost function to select the most energy-saving path, establish a clustered drone space protection model, formulate anti-collision strategies and anti-collision algorithms, and autonomous flight obstacle avoidance strategies for drone collisions.

Benefits of technology

It improves the performance, stability and mission execution efficiency of the drone cluster, extends the battery life of the drone, enhances the autonomous flight capabilities and intelligent decision-making level of the drone, and enables it to better adapt to complex environments and mission needs.

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Abstract

The invention belongs to the technical field of unmanned aerial vehicles, and particularly discloses a flight control method for scheduling a large number of unmanned aerial vehicle cluster operations, and the method comprises the following steps: S1, finding out an optimal path through an unmanned aerial vehicle energy-saving path planning obstacle avoidance algorithm; s2, selecting the most energy-saving path for flight through a cost function; s3, establishing a cluster unmanned aerial vehicle space protection model; s4, formulating an anti-collision strategy and an anti-collision algorithm to avoid potential collision conflicts; s5, formulating an unmanned aerial vehicle collision autonomous flight obstacle avoidance strategy to guarantee safe flight of the unmanned aerial vehicle; according to the invention, a plurality of key technical fields of an unmanned aerial vehicle cluster cooperation technology, an intelligent flight control technology, a communication technology, a simulation and test technology and an artificial intelligence and machine learning technology are integrated, and efficient cooperation operation and intelligent scheduling of the unmanned aerial vehicle cluster are realized, so that the unmanned aerial vehicle cluster can better adapt to complex environments and task requirements; and the flight efficiency of the unmanned aerial vehicle is improved.
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