Unmanned aerial vehicle inspection path planning method based on random optimization

A technology of random optimization and inspection path, applied in the direction of navigation calculation tools, etc., can solve the problems of difficulty in ensuring the efficient execution of UAV tasks, and failure to comprehensively consider the business needs of UAV systems.

Active Publication Date: 2020-08-14
浙江浙能天然气运行有限公司 +2
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AI Technical Summary

Problems solved by technology

Most of the existing research considers the UAV path planning problem, but does not comprehensively consider the business requirements of the UAV system, that is, the charging of the UAV midway, and it is difficult to ensure the efficient execution of UAV tasks.

Method used

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  • Unmanned aerial vehicle inspection path planning method based on random optimization
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  • Unmanned aerial vehicle inspection path planning method based on random optimization

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Embodiment Construction

[0066] In order to illustrate the embodiments of the present invention more clearly, the specific implementation manners of the present invention will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other accompanying drawings based on these drawings and obtain other implementations.

[0067] The UAV inspection path planning method based on random optimization in the embodiment of the present invention is divided into two major contents:

[0068] First, solve the problem of target assignment tasks;

[0069] UAV target assignment task is the main function of the global planning task in the early stage, and the overall task is decomposed into a collection of several single UAV tasks;

[0070] Second, solve the problem of UAV inspection path planning;

[0071] UAV inspection path planning is the core of la...

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Abstract

The invention relates to an unmanned aerial vehicle inspection path planning method based on random optimization. The method comprises the steps of S1 modeling all unmanned aerial vehicles, starting nodes of tasks, target nodes of the tasks and charging stations; S2 modeling a first constraint condition; S3 modeling a first optimization target; S4 randomly optimizing and solving the first optimization target to obtain a solution of an unmanned aerial vehicle target allocation task; S5 modeling the single unmanned aerial vehicle and the starting node, the target node and the charging station ofthe target task corresponding to the single unmanned aerial vehicle; S6 modeling a second constraint condition, wherein the second constraint condition comprises an environment constraint, a maximumflight distance constraint, a maximum turning angle constraint and a turning adjustment distance constraint, and the maximum flight distance constraint considers flight distance recovery of the unmanned aerial vehicle after the unmanned aerial vehicle is charged at the charging station; S7 modeling a second optimization target, wherein the second optimization target comprises a path voyage cost function; and S8 randomly optimizing and solving the second optimization target to obtain an optimal solution of unmanned aerial vehicle inspection path planning. According to the invention, more efficient task execution of the unmanned aerial vehicle is ensured.

Description

technical field [0001] The invention belongs to the technical field of pipeline inspection, and in particular relates to a random optimization-based UAV inspection path planning method. Background technique [0002] Pipeline inspection is an important guarantee for the safety of oil and gas pipelines. At present, oil and gas pipelines are equipped with early warning systems, such as distributed optical fiber early warning systems; when the early warning system has an early warning, it is necessary to confirm the early warning information on site to ensure the accuracy of the early warning. However, the distribution area of ​​oil and gas pipelines often has a complex surface environment, and the distribution of early warning points has a large span, which brings certain difficulties to manual inspection. [0003] The traditional manual inspection method not only has a large workload, is time-consuming and laborious, but also has certain safety hazards, such as untimely manag...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 陈积明滕卫明解剑波范海东杨秦敏张国民李清毅向星任沈佳园丁楠周君良
Owner 浙江浙能天然气运行有限公司
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