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Unmanned aerial vehicle track route planning method applied to community distribution

A path planning and unmanned aerial vehicle technology, applied in the general control system, three-dimensional position/course control, vehicle position/route/height control, etc., can solve problems such as not being smooth enough, the quality of the path result is not high, and far from the optimal path , to achieve high-quality results, optimal paths, and improved efficiency and accuracy

Inactive Publication Date: 2019-12-03
SOUTHWEST JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for the UAV track path planning for community delivery, the disadvantages of the RRT algorithm are usually that the path results obtained are of low quality, such as including edges and corners, not smooth enough, etc., and are usually far from the optimal path.

Method used

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  • Unmanned aerial vehicle track route planning method applied to community distribution
  • Unmanned aerial vehicle track route planning method applied to community distribution
  • Unmanned aerial vehicle track route planning method applied to community distribution

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0046] Such as figure 1 As shown, the UAV track path planning method for community distribution in this embodiment includes the following steps:

[0047] S100, using the RRT algorithm to generate a random sampling point t ran , use the RRT algorithm to find from the root node t ini to the target point t goa The trajectory path of the UAV;

[0048] S200, for random sampling point t ran The selection of is optimized and the random sampling point t ran The generation process is optimized, and the optimized UAV track path is obtained.

[0049] The above uses the RRT algorithm to find the root node t ini to the target point t goa The specific implementation steps of the planning path include the following:

[0050] S101. Determine the fixed point of the automatic unmanned cabinet supporting the drone as the random tree root node t ini , obtain the three-dimensional geographic location information of the fixed point of the automatic unmanned cabinet from the three-dimension...

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Abstract

The invention discloses an unmanned aerial vehicle track route planning method applied to community distribution. The method comprises the following steps: S100, generating a random sampling point tran with a RRT algorithm, and finding an unmanned aerial vehicle track route from a root node tini to a target point tgoa with the RRT algorithm; and S200, optimizing the selection of the random sampling point tran and the generation process of the random sampling point tran to obtain an optimized unmanned aerial vehicle track route. Through adoption of the unmanned aerial vehicle track route planning method applied to community distribution, high route result quality is achieved for the community distribution, and the route is optimal. From the four aspects of a step length, a deflection angleand a parent node selected for the random sampling point, as well as the influence of the community distribution characteristic on the step length and the deflection angle, the unmanned aerial vehicletrack route searching efficiency and accuracy are improved.

Description

technical field [0001] The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to an unmanned aerial vehicle track path planning method for community delivery. Background technique [0002] The community distribution route is planned to pick up and depart from the unmanned cabinet of the community terminal, and deliver the goods to the target location and dock with the home decoration receiving column. It is required to meet the technical constraints such as the maneuverability constraints of the UAV itself, the space-time constraints of the flight space, and the total amount of fuel carried by the UAV. Delivery constraints such as the number of orders for a single delivery. Based on the constraint conditions, in order to meet the task requirements, the performance indicators are selected with fast delivery speed, high accuracy and strong timeliness. [0003] The selection of trajectory path planning algorithm plays a decisive ro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/10G05B13/04
CPCG05B13/042G05D1/101
Inventor 李若愚王坤陈豪杰陈晓锦窦烨涵高梦雅
Owner SOUTHWEST JIAOTONG UNIV
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