A multi-UAV cooperative target search method based on multi-swarm ant colony algorithm

Abstract

A method for multi-UAV cooperative target search based on multi-group ant colony algorithm, including modeling the search environment of UAVs; according to the modeled environment, using multi-group ant colony cooperative algorithm search. The same group of ants has the function of guiding each other, and different groups of ants have the function of mutual repulsion, which can not only increase the diversity of solutions, increase the synergy among multiple UAVs, but also choose the direction with the highest probability of containing the target as much as possible to avoid Greedy selection increases the diversity of choices, and dynamically adjusts the search income of the target after discovering a target, avoids repeated searches for the target due to the influence of the target expectation factor, and selects the best path in each generation for pheromone Update to promote the algorithm to move closer to a better path. Realize the path coordination of UAVs when searching for multiple UAVs, avoid the phenomenon of excessive path overlap and repeated searching of targets due to the influence of pheromones and target heuristic factors, reduce search costs, and improve search efficiency.

Description

technical field [0001] The invention relates to a multi-UAV cooperative target search method, in particular to a multi-UAV cooperative target search method based on a multi-group ant colony algorithm. Background technique [0002] UAV-related technologies play an important role in civilian and scientific research fields, and are increasingly used in aerial video shooting, agricultural and forestry drug spraying, regional map surveying, alpine geological survey, high-voltage line inspection, mountain express delivery, post-disaster emergency rescue, etc. more extensive. In addition, under the influence of artificial intelligence, electronic communication technology, the Internet, image recognition, sensors, and the Internet of Things, UAVs are not limited to single-plane flight, but between multiple UAVs, multi-UAVs and smart cars. An unmanned control system that works collaboratively is established. In the entire collaborative system, the drones, the drones and the smart ca...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a multi-unmanned aerial vehicle collaborative target search method based on the multi-group ant colony algorithm, to solve the multi-unmanned aerial vehicles due to the influence of pheromone in the ant colony algorithm and the influence of factors such as target expectations. When searching for targets, paths overlap, targets are searched repeatedly, drones collide, etc.

[0005] The present invention is aimed at the shortcoming that the ant colony algorithm lacks the negative feedback mechanism in the existing research and cannot better realize multi-UAV cooperation, and the Voronoi diagram is also more suitable for the characteristics of single-machine track planning, and the designed ants of the same group have mutual The role of guidance, different groups of ants are mutually exclusive, the precise combination of ants can increase the diversity of solutions, and the integration of algorithms such as dynamic adjustment of target income and time-space coordination can further increase the synergy between multiple drones In order to solve the problems caused by the influence of pheromone in the ant colony algorithm and the influence of target expectation factors, the paths of multiple drones overlap when searching for targets, the target is repeatedly searched, and the problems of drone collisions are constantly improved. Algorithms that enable it to collaboratively plan the routes of multi-UAVs in target search in a fixed area

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