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A UAV track planning method based on spatial geometric features

A technology of track planning and geometric features, which is applied in three-dimensional position/channel control, instruments, control/regulation systems, etc., and can solve problems such as difficulty in accurately giving optimal track planning routes

Active Publication Date: 2021-11-05
DONGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Based on machine learning, reinforcement learning and other related algorithm models, it is difficult to accurately give the optimal trajectory planning route when the flight data attributes of UAVs are limited or some behavior attributes are missing.

Method used

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  • A UAV track planning method based on spatial geometric features
  • A UAV track planning method based on spatial geometric features
  • A UAV track planning method based on spatial geometric features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0047] For a drone, when it is assumed that it is defined to limit the flying height, we can map the planned space to two-dimensional space, such as image 3 Indicated. exist image 3 In accordance with the algorithm provided by the present invention, we will easily think of the starting coordinate of the drone (X "by translation of the coordinate system. 1 Y 1 ) Changes to (0, 0), change the end coordinates to (X m Y m ), Then the line equation of the connection starting to the end point is: Y m X-X m y = 0. Hypothesis m Y m ) = (5, 6), the center coordinate of the threat area 1 is The center coordinate of the threat area 2 is And the radius of the threat area is R 1 = R 2 = 2, then from the start-up to the end point of the line equation is: 6x-5y = 0. Point (2, 8) to line: 6x-5y = 0 distance is: Similarly, points (4, 4) to line: 6x-5y = 0 distance is: Then according to the algorithm 1, the optimal path is the straight line from the starting point from the drone, such as image ...

Embodiment 2

[0049] For a drone, when it is assumed that it is defined to limit the flying height, we can map the planned space to two-dimensional space, such as Figure 4 Indicated. exist Figure 4 In accordance with the algorithm provided by the present invention, we will easily think of the starting coordinate of the drone (X "by translation of the coordinate system. 1 Y 1 ) Changes to (0, 0), change the end coordinates to (X m Y m ), Then the line equation of the connection starting to the end point is: Y m X-X m y = 0. Hypothesis m Y m ) = (5, 5), the center coordinate of the threat area 1 is The center coordinate of the threat area 2 is And the radius of the threat area is R 1 = R 2 = 1, then the straight line equation from the starting point to the end point is: x-y = 0. Point (3.414, 2)) to the straight line: X-Y = 0 distance is: Similarly, points (2, 3.414) to the line: X-Y = 0 distance is: So according to algorithm 1, we calculate from (0, 0) and (5, 5) to threat area 1 (in For th...

Embodiment 3

[0051] For a drone, when it is assumed that its flight height is not fixed, its planned space is 3-dimensional space, such as Figure 5 Indicated. exist Figure 5 In accordance with the algorithm provided by the present invention, we will easily think of the starting coordinate of the drone (X "by translation of the coordinate system. 1 Y 1 ,z 1 ) Changed to (0, 0, 0), the end point coordinate changes to (X m Y m ,z m . Hypothesis m Y m ,z m ) = (5, 5, 5), rim 1 = 2 = 1. From point (2.5, 0.5, 1) and (0.5, 2.5, 2) to the connection (X 1 Y 1 ,z 1 ) And (x m Y m ,z m The distance between the straight line is greater than 1, then the optimal path is the straight line from the start of the drone to the end, such as Figure 5 The middle line is shown. Similarly, the threat area in the three-dimensional space covers a straight line from the starting point to the focus, and its optimal path calculation method can be patterned in Example 2.

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Abstract

The present invention relates to a UAV track planning method based on spatial geometric features. Firstly, by analyzing the behavior data of the UAV, the flight conditions and the flight environment of the UAV are analyzed to obtain the planning space of the UAV ; Then, through the description of the constraints on the behavior of the UAV, the flight limit function of the UAV is determined, and the optimal objective function is given according to the corresponding environmental constraints and the flight restrictions of the UAV itself, and through the spatial geometric characteristics, find Optimal flight path for drones. The present invention has the following characteristics: Utilizing the flight restrictions and environmental constraints of the UAV, the trajectory planning problem of the UAV can be formalized into spatial geometric features; Under environmental constraints, the optimal trajectory planning method for UAVs can be given.

Description

Technical field [0001] The present invention relates to an automatic aeroacket planning method. Background technique [0002] With the development of drone technology, more and more drones are applied to alternative pilots to implement some high-risk tasks, many areas such as search and rescue, disaster monitoring, etc. A perfect task planning system is an important guarantee for drones to successfully complete the task, where track plan is the core part of the task planning system. UAVA planning requires drone to plan the optimal or most satisfactory flight track. Thus, the problem of drone aerial trading is an important means of improving the safety performance of drone and ensuring the excellent means of completion of the drone. [0003] The existing drone aerial trading program mainly adopts optimization algorithm and machine learning technology. The technique of optimizing algorithm is mainly by collecting three-dimensional geographic data, based on intelligent optimization ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/10
CPCG05D1/101
Inventor 赵培海王咪咪
Owner DONGHUA UNIV