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Decision algorithm-based data analysis method for redundant sensor of unmanned aerial vehicle

A decision-making algorithm and data analysis technology, applied in special data processing applications, geometric CAD, design optimization/simulation, etc., can solve problems such as unsmooth conversion, insufficient use of multiple sets of sensor data, etc., to improve the smoothness of conversion, improve reliability effect

Active Publication Date: 2021-07-27
HEFEI SIWILL INTELLIGENT
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AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem of insufficient use of multiple sets of sensor data and unsmooth conversion in the self-driving platform, the present invention provides a data analysis method for redundant sensors of UAVs based on decision-making algorithms. The specific scheme is as follows:

Method used

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  • Decision algorithm-based data analysis method for redundant sensor of unmanned aerial vehicle

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Embodiment 1

[0075] In this embodiment, the number of redundant sensors of the UAV is 2, that is, there is only one auxiliary sensor as an example. Aux_index_spec represents the index of the auxiliary sensor set by the user, and the same is true for other identifiers, which will not be repeated here.

[0076] First cycle:

[0077] S1. Set the index of the main sensor set by the user in the self-driving platform of the drone as Pri_index_spec, and the index of the auxiliary sensor set by the user as Aux_index_spec to obtain sensor data;

[0078] S2. Perform normalization processing on the data error reading counts Pri_Count_st and Aux_Count_st at the start time, and record them as Normal_pri and Normal_aux;

[0079] Calculate the expected variable, and calculate the corresponding variance as Varince_pri and Varince_aux;

[0080] Normalize the variance data, recorded as Varince_normal_pri and Varince_normal_aux;

[0081] S3. Set the register reading error decision-making weight factor Coun...

Embodiment 2

[0119] In this embodiment, the number of redundant sensors of the drone is 3 as an example, that is, one main sensor and two auxiliary sensors, which are recorded as auxiliary sensor 1 and auxiliary sensor 2 .

[0120] First cycle:

[0121] S1. Set the index of the main sensor set by the user in the self-driving platform of the drone to be Pri_index_spec, and the index of the auxiliary sensor set by the user to be Aux1_index_spec and Aux2_index_spec to obtain sensor data;

[0122] S2. Normalize the data error reading counts Pri_Count_st, Aux1_Count_st, and Aux2_Count_st at the start time, and record them as Normal_pri and Normal_aux1,

[0123] Normal_aux2;

[0124] Calculate the expected variable, and calculate the corresponding variance as Varince_pri and Varince_aux1, Varince_aux2;

[0125] Normalize the variance data, recorded as Varince_normal_pri and Varince_normal_aux1, Varince_normal_aux2;

[0126] S3. Set the register reading error decision-making weight factor Coun...

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Abstract

The invention relates to the field of unmanned aerial vehicle design, in particular to a decision algorithm-based data analysis method for a redundant sensor of an unmanned aerial vehicle, and the method comprises the following steps: S1, obtaining data of a main sensor and an auxiliary sensor in a period; S2, processing the obtained data; and S3, performing health scoring on the main sensor and the auxiliary sensor based on a result processed in the step S2, and setting corresponding sensors as the main sensor and the auxiliary sensor after system calculation. The method has the beneficial effects that the data of multiple groups of sensors are analyzed based on a decision algorithm, so that the data used in decision and subsequent resolving applications are smoother.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicle design, in particular to a data analysis method for redundant sensors of unmanned aerial vehicles based on decision-making algorithms. Background technique [0002] Unmanned aerial vehicles (UAVs) refer to unmanned aerial vehicles or aircrafts, which are controllable, perform multi-tasking and can be used repeatedly. Various types of UAVs play different roles in different fields. The development of UAVs generally uses various new materials and technologies, and various key technologies are also paid attention to by the academic and engineering circles. Under the background of today's informatization, networking and systemization, drones will develop more rapidly. Defect and deficiency of prior art: [0003] At present, UAVs realize functions such as manual control and autonomous navigation control of UAVs through the flight control self-driving platform. In order to ensure the stability a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20G06F30/15
CPCG06F30/20G06F30/15
Inventor 辛艳峰黄桃丽周起如管才路
Owner HEFEI SIWILL INTELLIGENT
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