Flight mission planning and management system and method for cooperation of multiple unmanned aerial vehicles

By adopting the path planning method of genetic algorithm and A* algorithm in the multi-UAV task planning system, combining real-time obstacle avoidance strategies and task priority scheduling, the problems of insufficient real-time, poor adaptability and low reliability of multi-UAV task planning in the existing technology in large-scale, dynamic and complex environments are solved, and efficient, flexible and robust task planning and management effects are achieved.

CN119645084AActive Publication Date: 2025-03-18TIANJIN ZERO ONE INTELLIGENT TECH CO LTD
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Patent Information

Application Number
CN202510186186.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-20
Publication Date
2025-03-18
Estimated Expiration
2045-02-20

AI Technical Summary

Technical Problem

When dealing with large-scale, dynamic and complex environments, the existing multi-UAV mission planning methods have problems such as insufficient real-time, poor adaptability and low reliability, which are difficult to meet the needs of practical applications.

Method used

A flight mission planning and management system for multi-UAV collaborative cooperation is proposed, and efficient, flexible and robust task planning and management are achieved through path planning based on genetic algorithms and A* algorithms, real-time obstacle avoidance strategies and task priority scheduling.

Benefits of technology

Reduce task complexity through regional decomposition and parameter division, optimize resource matching, improve task planning precision and feasibility, achieve efficient, smooth, energy-saving and safe path planning, and improve the quality and efficiency of multi-UAV collaborative task planning.

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Abstract

The invention relates to the technical field of unmanned aerial vehicles, in particular to a flight mission planning and management system and method for cooperation of multiple unmanned aerial vehicles, and the method comprises the steps: decomposing a flight region of an unmanned aerial vehicle based on a flight mission of the unmanned aerial vehicle, and dividing the flight region; path planning is carried out in the flight area of the unmanned aerial vehicle, global flight path planning is carried out by adopting a genetic algorithm, and local flight path planning is carried out by adopting an A * algorithm after the global path planning; an obstacle avoidance strategy of the unmanned aerial vehicle in the flight process is constructed, and after the obstacle avoidance strategy is triggered, local flight path planning is carried out again; according to unmanned aerial vehicle flight task constraints, a priority judgment criterion of multiple unmanned aerial vehicle tasks is formulated, and unmanned aerial vehicle resources are allocated and dispatched. The intelligent level of unmanned aerial vehicle task planning can be remarkably improved, the adaptability to complex environments is enhanced, flight safety and efficient task execution are ensured, and a landing technical support is provided for actual application of the unmanned aerial vehicle.
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