Unmanned aerial vehicle cluster grazing method based on Flocking algorithm

Abstract

The invention discloses an unmanned aerial vehicle cluster grazing method based on a Flocking algorithm, and the method comprises the following steps: S1, building an unmanned aerial vehicle grazing model: an unmanned aerial vehicle threatens a sheep flock during grazing, and prevents livestock from walking into a circle which takes the unmanned aerial vehicle as the center of a circle with the radius of five meters; unmanned aerial vehicles for grazing comprise a shaping unmanned aerial vehicle and an expelling unmanned aerial vehicle; and the shaping unmanned aerial vehicle obtains the real-time shape of the flock of sheep through real-time camera shooting and image recognition; s2, forming a movable sheepfold by using the shaping unmanned aerial vehicle; s3, determining the advancing direction of the flock of sheep; s4, defining a first-level warning area; s5, grazing by using the shaping unmanned aerial vehicle; and S6, setting a secondary warning area and monitoring livestock in the area. According to the invention, the effectiveness, stability and automation of driving are improved, and the applicable scene is broadened.

Description

technical field [0001] The invention relates to the grazing of unmanned aerial vehicles, in particular to a grazing method of unmanned aerial vehicles based on a Locking algorithm. Background technique [0002] In recent years, more and more people have invested in the research of applying drones to animal husbandry. The existing technology has been able to provide a general framework of grazing methods and systems based on UAVs, which can monitor and plan the direction of the herd, guide the sheep to complete feeding on time, avoid other sheep and other behaviors, in route planning, pasture selection, There have been great achievements in monitoring sheep flocks and improving the utilization rate of high-quality grass sources. [0003] After determining the forward route, in the specific scheme of driving the flock to the destination through the drone, the existing scheme includes: (1) Guide the flock to go: control the drone to reach the current position of the leading li...

AI Technical Summary

Problems solved by technology

[0004] In solution (1), by guiding the leader of the flock to adjust the position of the flock, it is impossible to solve the problem that the leader loses control and does not obey the command when encountering some dangers; some livestock do not follow the leader and run away from the herd.

may cause substantial losses

The plan of driving the flock to adjust the position in the scheme (2) is only a general discussion at present, and it does not talk about how to cooperate with the driving of the specific UAV group, how to determine the expected driving position of each UAV, etc.

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