A method and system for pattern recognition of unmanned aerial vehicle flight conditions

A pattern recognition and unmanned aerial vehicle technology, applied in the direction of character and pattern recognition, neural learning methods, control/regulation systems, etc., to achieve strong generalization ability and improve accuracy

Active Publication Date: 2022-05-31
山西朔铭科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the above problems, the present invention provides a method and system for UAV flight condition pattern recognition, which can identify the UAV flight condition pattern in the absence of prior category label information and the state variables of the UAV have complex correlations. Effective and reliable identification

Method used

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  • A method and system for pattern recognition of unmanned aerial vehicle flight conditions
  • A method and system for pattern recognition of unmanned aerial vehicle flight conditions
  • A method and system for pattern recognition of unmanned aerial vehicle flight conditions

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Embodiment 1

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[0124] where σ( ) is a Dirac function.

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[0146] Given the number of iterations L, the steps S44 to S49 are iteratively executed until the number of iterations is reached, and the drone flight is completed.

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Embodiment 2

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Abstract

The invention relates to the technical field of unmanned aerial vehicle control. Aiming at the problem of pattern recognition of flight conditions during the flight of the unmanned aerial vehicle, the present invention proposes a method and system for pattern recognition of the flight conditions of the unmanned aerial vehicle. The flight working condition pattern recognition process of the present invention comprises: UAV flight working condition training data acquisition stage, UAV working condition pattern off-line classification stage, UAV working condition pattern online matching stage three main links, through constructing unmanned The working condition data network during the multiple flights of the drone can not only record the working conditions at different moments during the flight of the drone, but also effectively express the complex correlation between them, which helps to obtain robustness and interpretability. More reliable pattern recognition results of UAV flight conditions. In addition, the graph variational autoencoder structure is used to construct the UAV flight condition pattern classification model, so that the model has a certain generation ability, so that the UAV flight condition pattern recognition process has a stronger generalization ability.

Description

A method and system for pattern recognition of UAV flight conditions technical field The present invention relates to unmanned aerial vehicle control technical field, particularly a kind of unmanned aerial vehicle flight condition pattern recognition method and system. Background technique [0002] UAV is a kind of unmanned flight controlled by long-range radio signal or trajectory planning software carried by itself. device. Compared with traditional manned aerial vehicles, the autonomy and survivability of drones have been significantly improved, and they can replace humans Complete tasks in various harsh environments without worrying about the safety of the driver, and can be used to perform high-risk tasks Therefore, it has been widely used in many fields such as military, engineering and scientific research. In order to ensure that the drone can efficiently complete the established tasks The stability of the health state during flight and operation is particul...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G05D1/10
CPCG06N3/084G05D1/101G06N3/045G06F18/22G06F18/214G06F18/24155Y02T10/40
Inventor 杜航原白亮王文剑
Owner 山西朔铭科技有限公司
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