Multi-unmanned aerial vehicle dynamic route planning method based on space and time collaboration

Abstract

The invention provides a multi-unmanned aerial vehicle dynamic route planning method based on space and time collaboration. The problems of space anti-collision and time collaboration of multiple unmanned aerial vehicles are solved in comparison with a single-machine A* route planning algorithm in the process of solving a coordinated route. The method comprises the steps of considering anti-collision constraint, a pace-consistent planning process, time collaboration cost and providing suggested average flight rate in planning; the method has the advantages that a simpler calculation structureis provided, the calculation speed meets an actual use requirement, the optimal route cost can be met when the actual requirement is met by the solved speed through the parameter adjusting, the factors such as risks and flight time in the actual flight of the unmanned aerial vehicle are coordinated; and meanwhile, a coping mechanism for the suddenly-appearing area needing to be avoided is designedin the method, the method is more oriented to an actual application scene, and therefore, the availability of the multi-unmanned aerial vehicle collaborative dynamic route planning is improved.

Description

technical field [0001] The invention relates to the field of algorithm design and simulation, in particular to a dynamic route planning method for an unmanned aerial vehicle. Background technique [0002] When multiple UAVs complete specific tasks, such as security monitoring and disposal, and launch at the same time, from the starting point of each UAV to the mission point, it is necessary to carry out route planning that satisfies certain spatial constraints and time coordination, that is, multiple UAVs interact with each other. A certain safe distance should be kept between them, and the mission point should be reached within a certain time error range. In the process of completing the mission, the UAV may encounter mountain peaks, bad weather areas, etc. At this time, the UAV needs to fly around these areas to the mission point. In addition, during the flight of the UAV to complete a specific task, it is necessary to consider factors such as limited load energy and lowe...

AI Technical Summary

Problems solved by technology

The constraints of these algorithms are the constant flight environment from the starting point to the target point, and adapting to a single UAV without considering multi-aircraft coordination factors, which makes the existing route planning algorithms unusable

[0004] During the research process, the inventor found that the UAV route planning algorithm based on the sparse A* algorithm cannot be directly applied to multi-aircraft scenarios, because it does not support quantity expansion , and the lack of spatial anti-collision constraints necessary for multi-machine route planning

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