Three-dimensional group unmanned aerial vehicle parallel type multi-target search cooperative operation method

A machine-parallel, unmanned aerial vehicle technology, applied in the field of unmanned aerial vehicle target search

Active Publication Date: 2020-08-25
HUNAN UNIV OF SCI & TECH
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Problems solved by technology

However, the multi-UAV research based on this method is mostly limi

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  • Three-dimensional group unmanned aerial vehicle parallel type multi-target search cooperative operation method
  • Three-dimensional group unmanned aerial vehicle parallel type multi-target search cooperative operation method
  • Three-dimensional group unmanned aerial vehicle parallel type multi-target search cooperative operation method

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Embodiment Construction

[0092] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0093] like figure 1 As shown, a 3D swarm unmanned aerial vehicle parallel multi-target search collaborative operation method includes the following steps:

[0094] Step 1: Construct a three-dimensional space search environment, set various parameters, randomly initialize the position and speed of the group UAVs, and randomly initialize the position of the target.

[0095] In the closed three-dimensional space R 3 In , the multi-target search problem of swarm UAVs can be represented by triples {U,T,E}:

[0096] (1) Search subject U: U={U i , i=1,2,...,N}, wherein, N>>M, N represents the number of drones in the group, and M represents the number of targets;

[0097] (2) Search object T: T={T j ,j=1,2,...,M},M>>1;

[0098] (3) Search environment E: dynamic unknown environment; wherein, the UAV swarm detects the radio frequency signal sent by the com...

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Abstract

The invention discloses a three-dimensional group unmanned aerial vehicle parallel type multi-target search cooperative operation method. The method comprises the following steps that a program is initialized; one-time self-organizing division is completed according to a multi-target distribution model of the response threshold; on the basis of a multi-target distribution model of sub-group scalehomogenization, resource allocation inside the sub-groups is carried out, and secondary distribution is completed; fine-grained target search is carried out by adopting an adaptive inertia weight extended particle swarm algorithm based on kinematics constraint characteristics; if the unmanned aerial vehicles in all the subgroups are close to the search target, the search is considered to be successful, otherwise, iteration is continued, and the positions and speeds of the unmanned aerial vehicles are continuously updated, a group unmanned aerial vehicle parallel search performance index evaluation model is established, and then convergence proving and analysis on the evaluation model is carried out. The method is advantaged in that parallel search efficiency of the group unmanned aerial vehicle is improved, problems that particles are prone to falling into local optimal points and search efficiency is too low are effectively solved, and system energy consumption and search time consumption are greatly reduced.

Description

technical field [0001] The invention relates to a target search method for unmanned aerial vehicles, in particular to a three-dimensional group unmanned aerial vehicle parallel multi-target search collaborative operation method. Background technique [0002] Inspired by the group behavior of social insects such as ants and bees, scholars have proposed the concept of swarm intelligence, that is, collective intelligence emerging from a group of simple agents. The swarm robot system is a typical artificial swarm intelligence system, which consists of a large number of isomorphic autonomous robots with a simple structure. Through the coordination and cooperation of robots with limited individual capabilities under a specific mechanism, the system can emerge intelligent behaviors to complete relatively complex tasks. [0003] Object search is one of the most common tasks in swarm robotic systems. According to the number of searched objects, object search can be divided into sin...

Claims

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Application Information

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IPC IPC(8): G05D1/12G06N3/00
CPCG05D1/12G06N3/006
Inventor 张红强何昕杰吴亮红周少武刘朝华陈磊周游
Owner HUNAN UNIV OF SCI & TECH
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