WO2020093497A1 - Système et procédé d'opération de précision pour véhicule aérien sans pilote de protection de plantes, et support d'informations lisible par ordinateur - Google Patents

Système et procédé d'opération de précision pour véhicule aérien sans pilote de protection de plantes, et support d'informations lisible par ordinateur Download PDF

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Publication number
WO2020093497A1
WO2020093497A1 PCT/CN2018/119052 CN2018119052W WO2020093497A1 WO 2020093497 A1 WO2020093497 A1 WO 2020093497A1 CN 2018119052 W CN2018119052 W CN 2018119052W WO 2020093497 A1 WO2020093497 A1 WO 2020093497A1
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WO
WIPO (PCT)
Prior art keywords
plant protection
parcel
plot
data
image data
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Application number
PCT/CN2018/119052
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English (en)
Chinese (zh)
Inventor
朱秋阳
索高宇
陈方杰
关家豪
刘祖富
Original Assignee
深圳市翔农创新科技有限公司
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Publication of WO2020093497A1 publication Critical patent/WO2020093497A1/fr

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

  • the present application relates to the technical field of unmanned aerial vehicles, in particular to a plant protection unmanned aerial vehicle precision operating system, method and computer-readable storage medium.
  • the cloud server is used to send preset parcel boundary data and parcel obstacle data corresponding to current plant protection operation requirements to the acquisition module;
  • the calling unit is configured to call preset parcel boundary data and parcel obstacle data corresponding to the parcel marking information from the cloud server according to the parcel marking information, and transfer the land Block boundary data and the block obstacle data are sent to the route generation module.
  • the plant protection UAV precision operation system further includes a mapping UAV and an image processing module;
  • the image splicing unit is configured to receive the image data and send the image data spliced according to a preset splicing rule to the editing unit;
  • the image stitching unit includes a three-dimensional stitching subunit and a conversion subunit;
  • the ground control terminal sets route information based on the parcel boundary data and the parcel obstacle data;
  • the ground control terminal controls the plant protection drone to perform plant protection operations according to the route information.
  • the ground control terminal obtains plot marking information corresponding to the plot to be protected; the plot marking information includes at least one of the following: plot number, plot name, plot preset Point coordinates
  • the ground control terminal calls preset parcel boundary data and parcel obstacle data corresponding to the parcel marking information from the cloud server.
  • the method further includes:
  • the surveying drone In response to the received surveying instruction for the target plot, the surveying drone performs aerial survey on the target plot to obtain image data; the target plot includes the plot to be plant protected;
  • the image processing module processes the image data according to a preset image processing rule, and sends the processed image data to the cloud server; the processed image data includes information corresponding to the parcel mark information Parcel boundary data and parcel obstacle data.
  • the image stitching unit stitches the image data, and sends the stitched image data to the editing unit;
  • the editing unit edits the parcel boundary data and parcel obstacle data for the stitched image data, and sends the edited image data to the cloud server.
  • FIG. 2 is a schematic flow chart of the first embodiment of the plant protection drone precision operation method of the application
  • FIG. 4 is a schematic flow chart of a third embodiment of the plant protection drone precision operation method of the application.
  • Icons 10, cloud server; 20, ground control terminal; 21, acquisition module; 22, route generation module; 23, control module; 30, plant protection UAV; 40, surveying and mapping UAV; 50, image processing module; 51 , Video splicing unit; 52, editing unit.
  • the acquisition module 21 is called from the cloud server 10 according to the current plant protection operation needs of the plot protection, specifically from the boundary of the plot as described above
  • the image data completed by information marking such as obstacles call the parcel boundary data and parcel obstacle data corresponding to the parcel requiring plant protection, and send the parcel boundary data and parcel obstacle data to the Route generation module 22.
  • This application implemented the ground control terminal 20 according to the preset Accurate boundary information and field obstacle information of the operation plots, set up precise plant protection drone 30 spraying operation route for the drone to execute plant protection operation, thereby improving the spraying accuracy of drone plant protection operation, avoiding In addition, waste of resources such as pesticides and fertilizers has been eliminated.
  • the identification unit is used to obtain plot mark information corresponding to the plot to be protected based on current plant protection operation requirements; the plot mark information includes at least one of the following: plot number, plot name, plot The coordinates of the preset point;
  • the image processing module 50 is configured to receive the image data and send the image data processed according to preset image processing rules to the cloud server 10; the processed image data includes the parcel The parcel boundary data and the parcel obstacle data corresponding to the marker information.
  • the surveying and mapping drone 40 is equipped with a multi-channel multi-spectral aerial survey camera for aerial survey, which improves the fit between the aerial survey results and the actual terrain, which is helpful for users to accurately mark the plant protection work area based on the highly consistent aerial survey images, and improve plant protection The accuracy of the operation.
  • a multi-channel multi-spectral aerial survey camera for aerial survey which improves the fit between the aerial survey results and the actual terrain, which is helpful for users to accurately mark the plant protection work area based on the highly consistent aerial survey images, and improve plant protection The accuracy of the operation.
  • the plant protection operation requirement includes information such as the plot to be plant protected, the type of crop in the plot, the plant protection type, and the spraying operation time.
  • the acquisition module is based on the current plant protection operation requirements, specifically based on the current plant protection operation For the plots requiring plant protection in the demand, call the preset plot boundary data and plot obstacle data corresponding to the plots requiring plant protection in the current plant protection operation requirement from the cloud server, and transfer the plot boundary data and The block obstacle data is sent to the route generating module for generating a route.
  • the plot boundary data and plot obstacle data matching the feature information are used to generate a plant protection drone precise operation route, which improves the drone plant protection operation.
  • the accuracy of spraying avoids the waste of pesticides, fertilizers and other resources.
  • Step S102 the image processing module processes the image data according to a preset image processing rule, and sends the processed image data to the cloud server; the processed image data includes the parcel The parcel boundary data and the parcel obstacle data corresponding to the marker information.
  • the plant protection drone precision operation device may include a processor (such as a central processing unit), a communication bus, an input port, and an output port, Memory.
  • the communication bus is used to realize the connection and communication between these components; the input port is used for data input; the output port is used for data output, the memory can be a high-speed RAM memory, or a stable memory, such as a disk memory, the memory is optional It may also be a storage device independent of the aforementioned processor.
  • the memory as a computer-readable storage medium may include an operating system, a network communication module, an application program module, and computer-readable instructions.
  • the network communication module is mainly used to connect to the server and perform data communication with the server; and the processor can call computer-readable instructions stored in the memory and perform the steps of the plant protection drone precision operation method provided by the embodiments of the present application:
  • the embodiments of the present application also provide a computer-readable storage medium that stores computer-readable instructions stored on the storage medium, and the computer-readable instructions are implemented by the processor to implement the plant protection drone precision operation method as described above
  • the computer-readable storage medium may be a non-volatile readable storage medium.
  • each block in the flowchart or block diagram may represent a module, program segment, or part of code that contains one or more of the Executable instructions.
  • the functions noted in the block may occur out of the order noted in the figures. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can also be executed in reverse order, depending on the functions involved.
  • the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application essentially or part of the contribution to the existing technology or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to enable a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes.
  • ROM read-only memory
  • RAM Random Access Memory

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  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

Système et procédé d'opération de précision pour un véhicule aérien sans pilote de protection de plantes, et support de d'informations. Le système comprend un serveur en nuage (10), un terminal de commande au sol (20) et au moins un véhicule aérien sans pilote de protection de plantes (30), qui sont en liaison de communication les uns avec les autres, le terminal de commande au sol (20) comprenant un module d'acquisition (21), un module de génération d'itinéraire (22) et un module de commande (23) ; selon l'exigence d'opération de protection de plantes en cours, le serveur en nuage (10) envoie des données de limite de tracé prédéfinies et des données de barrière de tracé correspondant à l'exigence d'opération de protection de plantes au module d'acquisition (21) ; le module d'acquisition (21) envoie les données de limite de tracé et les données de barrière de tracé reçues au module de génération d'itinéraire (22) ; le module de génération d'itinéraire (22) règle, selon une règle de définition d'itinéraire prédéfinie, des informations d'itinéraire sur la base des données de limite de tracé et des données de barrière de tracé, et envoie les informations d'itinéraire au module de commande (23) ; et le véhicule aérien sans pilote de protection de plantes (30) réalise une opération de protection de plantes en fonction des informations d'itinéraire reçues par le module de commande (23). La précision de pulvérisation d'une opération de protection de plantes d'un véhicule aérien sans pilote est améliorée, et le gaspillage de ressources, tels que des pesticides et des engrais chimiques, est évité.
PCT/CN2018/119052 2018-11-06 2018-12-04 Système et procédé d'opération de précision pour véhicule aérien sans pilote de protection de plantes, et support d'informations lisible par ordinateur WO2020093497A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811312466.XA CN109343567A (zh) 2018-11-06 2018-11-06 植保无人机精准作业系统及方法
CN201811312466.X 2018-11-06

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WO2020093497A1 true WO2020093497A1 (fr) 2020-05-14

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US11800246B2 (en) 2022-02-01 2023-10-24 Landscan Llc Systems and methods for multispectral landscape mapping

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CN110018693A (zh) * 2019-03-31 2019-07-16 四川极云智飞科技有限公司 基于rtk技术的无人机精准植树造林方法及其系统
WO2021087724A1 (fr) * 2019-11-05 2021-05-14 深圳市大疆创新科技有限公司 Procédé de commande, dispositif de commande, plateforme mobile et système de commande
CN112269387A (zh) * 2020-10-29 2021-01-26 久瓴(上海)智能科技有限公司 农林作业任务处理方法、装置、计算机设备和存储介质
CN114787740A (zh) * 2020-11-09 2022-07-22 深圳市大疆创新科技有限公司 无人机控制方法、装置与控制终端
CN113239864A (zh) * 2021-05-31 2021-08-10 南通大学 一种适用于农业调查的无人机的路线规划方法
CN113247265B (zh) * 2021-06-28 2021-12-21 泗县汉和智能装备科技有限公司 一种基于大数据的植保无人机农药精准喷施系统
CN113821055A (zh) * 2021-09-29 2021-12-21 广州极飞科技股份有限公司 飞行控制方法、装置、电子设备及可读存储介质

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