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UAV route planning method based on operator cognitive load

A cognitive load and route planning technology, applied in navigation computing tools, three-dimensional position/course control, vehicle position/route/altitude control, etc., can solve the problem of unbalanced operator workload and UAV autonomy, etc. To achieve the effect of ensuring task completion rate, reducing workload and improving task completion

Active Publication Date: 2021-10-01
NORTHWESTERN POLYTECHNICAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problem that the existing route planning cannot balance the workload of the operator and the autonomy of the UAV, the present invention proposes a UAV route planning method that considers the cognitive load of the operator. Cognitive state, flexible route selection to realize man-machine cooperation to complete tasks

Method used

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  • UAV route planning method based on operator cognitive load
  • UAV route planning method based on operator cognitive load
  • UAV route planning method based on operator cognitive load

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0123] Example 1: When UAVs fly in formation, route planning is required when performing missions.

[0124] Step1: Calculate operator cognitive load

[0125] The UAV obtains the current physiological state of the operator to calculate the cognitive load of the operator. The acquired physiological data and processing of the operator are as follows:

[0126] table 5

[0127]

[0128] The operator's cognitive load calculated by formula (1-1) is 0.72.

[0129] Step2: Calculating the threat cost influence parameter P rc

[0130] Table 8 shows the UAV parameters and corresponding data that need to be obtained.

[0131] Table 6

[0132]

[0133]

[0134] According to formula (1-2), the threat cost influence parameter P is calculated rc is 0.19.

[0135] Step3: Use the improved A* algorithm for route planning

[0136] The influence parameter of the route cost obtained in step2 is 0.19, and the avoidance distance is calculated: D=16.2, and the route is planned by using...

example 2

[0140] Example 2: UAV formation flight, after completing the mission, path planning when returning home.

[0141] Step1: Calculate operator cognitive load

[0142] The UAV obtains the current physiological state of the operator to evaluate the cognitive load of the operator. The obtained physiological parameters of the operator are as follows:

[0143] Table 8

[0144]

[0145] According to formula (1-1), the cognitive load of the current operator is calculated to be 0.14.

[0146] Step2: Calculating the threat cost influence parameter P rc

[0147] Table 11 shows the parameters and corresponding data that need to be obtained

[0148] Table 9

[0149]

[0150] According to formula (1-2), calculate the threat cost influence parameter P rc It is 0.89, indicating that both the operator and the UAV are in good condition.

[0151] Step3: Use the improved A* algorithm for route planning

[0152] According to the influence parameter of the threat cost obtained in Step2 ...

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Abstract

The present invention provides an unmanned aerial vehicle route planning method based on the operator's cognitive load, which relates to the field of unmanned aerial vehicles. The avoidance distance function is obtained by using the operator's cognitive load calculation model and the calculation model of the route cost influencing parameters, and then based on the Improved A* algorithm for route planning. The present invention takes the comprehensive value of the human-machine state as one of the parameters of the cost function of route planning, so that the UAV can choose a more aggressive route to complete the task quickly and efficiently when the man-machine state is good; When the state is poor, choose a conservative route to improve your own safety and ensure the mission completion rate. The invention solves the problem of the previous air route planning, which only considers the threat area of ​​the enemy, and does not consider the state of itself and the operator, improves the autonomy and intelligence of the UAV, and the integration of man-machine state improves the safety mission completion while reducing operator workload.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicles, in particular to a route planning method. Background technique [0002] When facing the threat of obstacles, the UAV needs to interact with the operator and perform route planning to ensure that the UAV can reach the mission area safely. The research on the route planning of the UAV is an important guarantee for the UAV to complete the mission. [0003] However, in the practical application of UAV route planning, the traditional method is generally that the operator manually sets the waypoints or the UAV autonomously performs route planning according to the mission requirements. The method for the operator to manually set waypoints is difficult to achieve when the operator has a heavy workload, and will lead to a decrease in mission efficiency; while the traditional UAV autonomous route planning is often only based on mission requirements and threat areas. Considering the cognitive state...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/20G05D1/10
CPCG01C21/20G05D1/101
Inventor 陈军程龙陈晓威雷腾
Owner NORTHWESTERN POLYTECHNICAL UNIV
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