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Multi-objective quantum-behaved particle swarm algorithm-based unmanned aerial vehicle cooperative task distribution method

A technology of quantum particle swarms and task allocation, applied in resource allocation, multi-programming devices, biological neural network models, etc.

Inactive Publication Date: 2017-08-15
NORTHWESTERN POLYTECHNICAL UNIV
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  • Application Information

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Problems solved by technology

At present, there are few studies on multi-objective UAV cooperative task assignment, and there is no method that can solve the problem of multi-objective UAV cooperative task assignment under complex constraints.

Method used

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  • Multi-objective quantum-behaved particle swarm algorithm-based unmanned aerial vehicle cooperative task distribution method
  • Multi-objective quantum-behaved particle swarm algorithm-based unmanned aerial vehicle cooperative task distribution method
  • Multi-objective quantum-behaved particle swarm algorithm-based unmanned aerial vehicle cooperative task distribution method

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example 1

[0286] Example 1: Assume that 4 UAVs perform tasks on 2 targets, and assign tasks to them. According to the permutation and combination knowledge, there are 1620 allocation schemes for this simple problem. Using the exhaustive method to obtain all the allocation schemes and comparing them, it can be obtained that only 5 of the 1620 schemes are non-dominated solutions. It also constitutes the Pareto front end of this problem, and the allocation schemes corresponding to the five solutions are shown in the left half of Table 5. Finally, the algorithm of the present invention also outputs 5 solutions, which are completely consistent with the results obtained by the exhaustive method, as shown in the right half of Table 5. Similarly, when 4 UAVs are fighting against 3 targets, 30,720 solutions are obtained through the exhaustive method, including 13 non-dominated solutions, and the algorithm of the present invention can also find all Pareto front-end solutions. Therefore, the algo...

example 2

[0289] Example 2: Using the collaborative task assignment method based on the multi-objective quantum particle swarm optimization algorithm to solve the problem of setting task scenarios, the results obtained are as follows: figure 2 , which represents the distribution of non-dominated solutions of the obtained problem in the target space.

[0290] image 3 , Figure 4 , Figure 5 The iterative graphs of the optimal values ​​of the three objective functions in the update process are given respectively. It can be seen from the figure that with the update and iteration of the particles, the three objective functions are optimized, and finally converge to a stable value, which corresponds to the final optimal solution of the three objective functions. Depend on figure 2 It can be seen that the distribution of non-dominated solutions in the external population output by the algorithm is scattered, and the diversity of the population is guaranteed. Therefore, the algorithm is...

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Abstract

The invention provides a multi-objective quantum-behaved particle swarm algorithm-based unmanned aerial vehicle cooperative task distribution method. According to the method, an unmanned aerial vehicle cooperative task distribution model is established; and three indexes such as an objective earlier-stage task execution success probability, an unmanned aerial vehicle survival probability and a task completion time in an unmanned aerial vehicle cooperation task distribution problem respectively serve as optimized objective functions of a multi-objective task distribution problem, so that the simultaneous optimization of the three indexes is realized. Aiming at the characteristics of the unmanned aerial vehicle cooperation task distribution problem, a repairing operator aiming at the earlier task constraint and a repairing operator aiming at the in-task constraint are designed, so that the quality of solution in populations is improved; and a new population variation mechanism, so that the convergence speed of the algorithm is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of computer simulation and method optimization, and relates to a UAV cooperative task assignment method, which can be used to calculate UAV cooperative task assignment schemes under multiple optimization targets under the condition that UAVs perform various tasks cooperatively . Background technique [0002] Cooperative task assignment is one of the key technologies in multi-UAV cooperative mission planning. According to the relevant information of the task execution area obtained, it can provide task execution command sequences for multiple UAVs and assign corresponding UAVs to carry out corresponding tasks. Through UAV collaborative task assignment, pre-offline task assignment can be performed before the task is executed, and the global information of the mission area can be used to provide an ideal execution plan for the UAV to perform tasks. [0003] At present, the research on cooperative task assignme...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06N3/02
CPCG06F9/50G06N3/02
Inventor 周德云李枭扬王鹏飞潘潜杨振张堃
Owner NORTHWESTERN POLYTECHNICAL UNIV
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