Unmanned aerial vehicle cluster path planning method and system based on artificial potential field method

Abstract

The invention discloses an unmanned aerial vehicle path planning method and system based on an artificial potential field method. The method comprises the steps: dividing a space planning region intoa plurality of discrete three-dimensional space grids according to space information grids, and removing the three-dimensional space grids only containing obstacles; acquiring position information ofunmanned aerial vehicle clusters; and clustering and grouping the unmanned aerial vehicle clusters, and generating a path planning scheme of each clustering center after clustering and grouping of theunmanned aerial vehicle clusters according to an artificial potential field method, wherein the path planning scheme of each group of unmanned aerial vehicles after clustering and grouping of the unmanned aerial vehicle cluster is consistent with the path planning scheme of each clustering center. According to the invention, the space planning area is divided through a grid method, unequal division is carried out on the vertical height, grids where obstacles are located are removed, the search space is reduced, the calculation efficiency is improved, the time consumed for path planning through the artificial potential field method is shorter, the method is more suitable for a dynamic environment, the search efficiency is improved on the premise that the planning quality is guaranteed, andthe maneuverability of a path finding algorithm is enhanced.

Description

technical field [0001] The invention belongs to the field of path planning, and in particular relates to a UAV cluster path planning method and system based on an artificial potential field method. Background technique [0002] Unmanned aerial vehicles have the characteristics of flexible action and easy operation, and are widely used in military and civilian fields. Unmanned aerial vehicles have shown great advantages in the process of performing missions at low altitudes. In the process of realizing autonomous control of unmanned aerial vehicles, trajectory planning is an extremely important link. The unmanned aerial vehicle needs to fly from the starting point to the final target point along a certain track under the premise of avoiding obstacles. [0003] At present, commonly used obstacle avoidance and path planning algorithms generally have two types of methods: global path planning and local path planning. Global path planning is suitable for a state where the enviro...

AI Technical Summary

Problems solved by technology

[0009] The technical problem to be solved by the present invention is the problem of long planning time and slow speed when the existing UAV cluster performs path planning, and a UAV cluster path planning method based on the artificial potential field method that can improve the path planning efficiency is proposed and system

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