CN116430892A

CN116430892A - Working method, system, device and storage medium based on plant protection unmanned aerial vehicle group

Info

Publication number: CN116430892A
Application number: CN202310247977.2A
Authority: CN
Inventors: 海伟; 李宇炫; 陈波; 吴晓清; 张胜光
Original assignee: Shenzhen Wugu Network Technology Co ltd
Current assignee: Shenzhen Wugu Network Technology Co ltd
Priority date: 2023-03-07
Filing date: 2023-03-07
Publication date: 2023-07-14

Abstract

The invention is applicable to the technical field of unmanned aerial vehicles, and provides a working method, a system, a device and a storage medium based on a plant protection unmanned aerial vehicle group, wherein the method comprises the following steps: determining a target working area according to the digital map; generating a terrain model and a vegetation model of the target operation area; dividing the target operation area into a plurality of sub-areas according to the terrain model and the vegetation model to obtain a division result; distributing corresponding operation tasks to each plant protection unmanned aerial vehicle according to the division result; according to the operation tasks corresponding to each plant protection unmanned aerial vehicle, planning an operation path corresponding to each plant protection unmanned aerial vehicle; and controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to the corresponding operation paths. The invention not only can improve the working efficiency and save the labor cost, but also can effectively avoid the resource waste.

Description

Working method, system, device and storage medium based on plant protection unmanned aerial vehicle group

Technical Field

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an operation method, system and device based on a plant protection unmanned aerial vehicle group and a storage medium.

Background

At present, manual labor and simple mechanical work are mainly adopted for agricultural plant protection operation, and the efficiency of the agricultural plant protection operation is gradually reduced because the labor force for young and old engaged in the agricultural plant protection operation is gradually reduced, the labor cost is increased increasingly, and in the operation process, the resource waste is easily caused.

Disclosure of Invention

In view of the above, the embodiments of the present invention provide a method, a system, a device and a storage medium for operation based on a plant protection unmanned aerial vehicle group, so as to solve the problem of low efficiency of agricultural plant protection operation in the prior art.

A first aspect of an embodiment of the present invention provides a method for operating a plant protection unmanned aerial vehicle group, including:

determining a target operation area according to the digital map;

generating a terrain model and a vegetation model of the target operation area;

dividing the target operation area into a plurality of sub-areas according to the terrain model and the vegetation model to obtain a division result;

distributing corresponding operation tasks to each plant protection unmanned aerial vehicle according to the division result;

according to the operation tasks corresponding to each plant protection unmanned aerial vehicle, planning an operation path corresponding to each plant protection unmanned aerial vehicle;

and controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to the corresponding operation paths.

A second aspect of an embodiment of the present invention provides an operating system, including;

the data acquisition and processing module is used for generating a digital map and determining a target operation area according to the digital map;

the model building module is used for generating a terrain model and a vegetation model of the target operation area;

the region dividing module is used for dividing the target operation region into a plurality of sub-regions according to the terrain model and the vegetation model to obtain a dividing result;

the task distribution module is used for distributing corresponding operation tasks to each plant protection unmanned aerial vehicle according to the division result;

the path planning module is used for planning a corresponding operation path of each plant protection unmanned aerial vehicle according to the corresponding operation task of each plant protection unmanned aerial vehicle;

and the control module is used for controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to corresponding operation paths.

A third aspect of the embodiment of the present invention provides a working device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the working method based on the plant protection unmanned aerial vehicle group according to the first aspect of the embodiment of the present invention when executing the computer program.

A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium storing a computer program, which when executed by a processor implements a plant protection unmanned aerial vehicle-based working method according to the first aspect of the embodiments of the present invention.

According to the working method based on the plant protection unmanned aerial vehicle group, which is provided by the first aspect of the embodiment of the invention, a target working area is determined according to the digital map; generating a terrain model and a vegetation model of the target operation area; dividing the target operation area into a plurality of sub-areas according to the terrain model and the vegetation model to obtain a division result; distributing corresponding operation tasks to each plant protection unmanned aerial vehicle according to the division result; according to the operation tasks corresponding to each plant protection unmanned aerial vehicle, planning an operation path corresponding to each plant protection unmanned aerial vehicle; and controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to the corresponding operation paths. The invention not only can improve the working efficiency and save the labor cost, but also can effectively avoid the waste of resources.

It will be appreciated that the advantages of the second to fourth aspects may be found in the relevant description of the first aspect and are not repeated here.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a first flow chart of a method of operation based on a plant protection unmanned aerial vehicle group according to an embodiment of the present invention;

FIG. 2 is a second flow chart of a method of operation based on a plant protection unmanned aerial vehicle group according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of an operating system according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a working device according to an embodiment of the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the invention. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

The unmanned aerial vehicle for protecting agriculture and forestry is one unmanned aerial vehicle comprising flying platform, navigation flying control and spraying mechanism, and features that the spraying operation is realized via remote control on ground or navigation flying control, so that pesticide, seed, water, powder, etc. are sprayed.

The traditional agricultural production operation is mostly completed by manpower, which is time-consuming and labor-consuming, and also easily causes resource waste and a great amount of expenditure of labor cost. The working method based on the plant protection unmanned aerial vehicle provided by the embodiment of the invention can save a great amount of labor cost, improve the working efficiency and reduce the waste of resources.

As shown in fig. 1, the operation method based on the plant protection unmanned aerial vehicle group provided by the embodiment of the invention includes the following steps S101 to S106:

step S101, determining a target working area according to the digital map, and proceeding to step S102.

In application, the digital map is a map generated by electronic computer control, is a screen map based on digital drawing technology, is a visual real map, is stored in a computer and other devices in a digital mode to be convenient to review, and has the advantages that the proportion of the digital map can be enlarged, reduced or rotated without affecting the display effect.

In one embodiment, the digitized map includes at least terrain information, crop type information, vegetation height information, and obstacle information.

In application, the crop types may be: grain crops taking rice, corn, beans, potatoes, highland barley, broad beans and wheat as main crops; oil crops mainly comprising oilseeds, vines, sinapis radix, peanuts, flax, sunflowers and the like; vegetable crops mainly comprising radishes, cabbages, celery, leeks, garlic, onions, carrots, melons, lotus flowers, jerusalem artichoke, sword beans, coriander, lettuce, yellow flowers, peppers, cucumbers, tomatoes, coriander and the like; fruits such as pear, green plum, apple, peach, apricot, walnut, plum, cherry, strawberry, fructus tsaoko, and red date; wild fruits mainly comprising fructus Pyri, wild apricot, wild peach, wild jujube, mountain cherry, and Hippophae rhamnoides; the feed crops such as corn, green manure, astragalus sinicus and the like are used; medicinal crops mainly comprising ginseng, angelica, honeysuckle, mint, mugwort and the like; or other crop types, are merely examples of general crop types and are not meant to be limiting.

In application, the digital map may include other information such as vegetation density information in addition to terrain information, crop type information, vegetation height information, and obstacle information, and this is merely an example of general information and is not limiting.

Step S102, a terrain model and a vegetation model of the target working area are generated, and the process proceeds to step S103.

In the application, after the target working area is determined, a terrain model and a vegetation model of the target working area are generated according to a digital map and a three-dimensional reconstruction technology.

In application, three-dimensional reconstruction refers to the creation of a mathematical model for a three-dimensional object that is suitable for computer representation and processing, which is the basis for processing, manipulating, and analyzing its properties in a computer environment.

Step S103, dividing the target operation area into a plurality of sub-areas according to the terrain model and the vegetation model to obtain a division result, and entering step S104.

In application, the terrain model and the vegetation model can reflect the terrain and vegetation information of the target operation area more intuitively, the target operation area can be divided according to the vegetation density, the vegetation height and the vegetation type, and each divided sub-area corresponds to a corresponding plant protection unmanned aerial vehicle.

In one embodiment, the target operation area is divided into a plurality of sub-areas according to vegetation type and vegetation height information in the vegetation model, and each sub-area corresponds to one vegetation type and one vegetation height range.

In application, the target operation area is further divided, so that the accurate operation of the plant protection unmanned aerial vehicle is facilitated.

Step S104, according to the division result, corresponding operation tasks are distributed to each plant protection unmanned aerial vehicle, and the step S105 is performed.

In application, after the target operation area is divided into a plurality of sub-areas, each sub-area is allocated to a corresponding plant protection unmanned aerial vehicle, so that the plant protection unmanned aerial vehicle corresponds to the sub-area to be operated one by one.

In one embodiment, according to the division result, corresponding operation tasks are distributed to each plant protection unmanned aerial vehicle through a genetic algorithm, an ant colony algorithm and a particle swarm algorithm.

In application, the genetic algorithm (GeneticAlgorithm, GA) is a randomized search method which is evolved by referring to the evolution rules of the win-win condition and the survival of the fittest in the biological world, has inherent hidden parallelism and better global optimizing capability, can automatically acquire and guide an optimized search space by adopting the probabilistic optimizing method, and adaptively adjusts the search direction without determining rules.

In application, the ant colony algorithm (Ant Colony Optimization, ACO), also known as ant algorithm, is a probabilistic algorithm used to find an optimized path in the graph.

In application, a particle swarm optimization (Particle Swarm Optimization, PSO), also known as a particle swarm optimization algorithm or a bird swarm foraging algorithm, belongs to one of the evolutionary algorithms, has the characteristics of easy implementation, high precision, fast convergence and the like, and searches for a global optimal solution by following the currently searched optimal value.

In application, when corresponding operation tasks are distributed to each plant protection unmanned aerial vehicle through a genetic algorithm, an ant colony algorithm and a particle swarm algorithm, the area of each unmanned aerial vehicle responsible for operation can be made to be as close as possible to the limit value of the movement range of the unmanned aerial vehicle, so that the maximum operation efficiency and coverage rate are realized.

Step 105, according to the job task corresponding to each plant protection unmanned aerial vehicle, planning a job path corresponding to each plant protection unmanned aerial vehicle, and entering step 106.

In one embodiment, the job task is a spray task.

In the application, the operation task can be one or more of a plurality of operation tasks such as water application, fertilization, pesticide spraying and the like on crops, and the invention does not limit the operation task.

In the application, on the basis of task allocation, a greedy algorithm, a Hungary algorithm and other path planning algorithms can be used for planning an optimal path for each unmanned aerial vehicle, so that the action route of each unmanned aerial vehicle is shortest and the spraying efficiency is highest when the corresponding task is completed.

In application, greedy algorithms, also known as greedy algorithms, refer to the fact that when solving a problem, the choice that is currently seen to be best is always made. That is, the greedy algorithm does not take into account overall optimality, and what he does is just a locally optimal solution in a sense, the greedy algorithm does not get an overall optimal solution for all problems, but rather generates an overall optimal solution or an approximation of an overall optimal solution for many problems over a fairly broad range.

In application, the Hungarian algorithm (Hungarian) is a combinatorial optimization algorithm that solves the task allocation problem in polynomial time.

And S106, controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to the corresponding operation paths.

In the application, after the path planning is completed, each unmanned aerial vehicle is controlled to complete a corresponding operation task according to a corresponding operation path.

In one embodiment, as shown in fig. 2, step S106 includes the following steps S1061 to S1063:

step S1061, collecting characteristic data of sub-areas on the operation path corresponding to each plant protection unmanned aerial vehicle, and entering step S1062.

In one embodiment, the characteristic data includes a location of vegetation and a sprayed amount.

In applications, the characteristic data may be acquired by sensors or other means.

In the application, if the job task is water application, the characteristic data includes: soil moisture, applied water amount, water evaporation amount, soil water loss amount and the like; for different operation tasks, the acquired characteristic data are different, so that in each operation process, corresponding characteristic data are required to be acquired according to actual requirements.

Step S1062, adjusting the operation parameters of each plant protection unmanned aerial vehicle according to the characteristic data, and entering step S1063.

In the application, in the process of controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to corresponding operation paths, operation parameters are controlled and adjusted by adopting methods such as a PID controller, a fuzzy controller, a genetic algorithm and the like or other methods.

In application, the PID controller refers to a controller which performs control according to the proportion, integral and derivative of deviation, and is an automatic controller which is most widely used.

In application, the fuzzy controller can be a controller which uses a special fuzzy chip to carry out real-time fuzzy reasoning and decision, or can be a controller which uses a general microcomputer or chip to carry out real-time table look-up control.

In one embodiment, the operating parameters include flight altitude, flight speed, spray angle, and degree of opening and closing of the spray valve.

In application, the operation parameters of the plant protection unmanned aerial vehicle in the operation process are adjusted according to the acquired characteristic data, and after each time the characteristic data is monitored to be changed, one or more of the operation parameters of the plant protection unmanned aerial vehicle are adjusted in time, so that the operation quality and efficiency of the plant protection unmanned aerial vehicle are ensured.

In the application, the operation parameters of the plant protection unmanned aerial vehicle can be dynamically adjusted according to the weather conditions during operation, and whether the operation is continuously finished is judged.

And step S1063, controlling each plant protection unmanned aerial vehicle to complete a corresponding operation task according to a corresponding operation path according to the operation parameters of each plant protection unmanned aerial vehicle.

In the application, the plant protection unmanned aerial vehicle returns to the drop point after completing the corresponding operation task according to the operation parameters and the operation path.

In one embodiment, step S106 is followed by:

and generating a working result according to the working task completion condition of each plant protection unmanned aerial vehicle and transmitting the working result to a server.

In the application, when all plant protection unmanned aerial vehicles complete the operation tasks of all subareas of the target operation area, the operation result data of the current operation is generated, and the operation result data is uploaded to a server for storage and analysis.

In one embodiment, step S101 is preceded by:

setting a plurality of flying points and landing points of the plant protection unmanned aerial vehicle around the land to be operated;

scanning and measuring the land parcel to be operated to obtain basic information of the land parcel to be operated, wherein the basic information comprises topographic information and vegetation information of the land parcel to be operated;

and generating a digital map according to the basic information.

In application, by arranging a plurality of flying points and landing points of the plant protection unmanned aerial vehicle around the land to be operated, the orderly take-off and landing of the plant protection unmanned aerial vehicle can be ensured, the plant protection unmanned aerial vehicle can obtain basic information such as crop position information, topographic information and the like of the land to be operated according to the operation task through a sensor and global positioning system (Global Positioning System, GPS) technology, and then a digital map is generated according to the obtained basic information.

In application, if the operation task is fertilization, based on a digital map, the problems of over fertilization or insufficient fertilization and the like can be avoided by planning a three-dimensional spray array mode, and the fertilization uniformity can be improved, so that the yield and quality of crops are improved.

In application, if the operation task is pesticide application, based on a digital map, information such as concentration and distribution of a spraying agent, crop growth state and the like is acquired through data acquisition and processing, so that powerful support can be provided for subsequent decisions.

In application, the operation method based on the plant protection unmanned aerial vehicle group is not limited to operations such as water application, fertilization, pesticide application and the like, can improve the operation efficiency, reduce the labor cost, simultaneously reduce the waste of corresponding resources, effectively avoid the damage of pesticides to workers in some pesticide application operation processes, and ensure the life health of the workers.

As shown in fig. 3, an embodiment of the present application further provides an operating system 200, including: the system comprises a data acquisition and processing module 201, a model building module 202, a region dividing module 203, a task allocation module 204, a path planning module 205 and a control module 206.

The data acquisition and processing module 201 is used for generating a digital map and determining a target operation area according to the digital map;

a model building module 202 for generating a terrain model and a vegetation model of the target working area;

the region dividing module 203 is configured to divide the target operation region into a plurality of sub-regions according to the terrain model and the vegetation model, so as to obtain a division result;

the task allocation module 204 is configured to allocate a corresponding job task to each plant protection unmanned aerial vehicle according to the division result;

the path planning module 205 is configured to plan a working path corresponding to each plant protection unmanned aerial vehicle according to a working task corresponding to each plant protection unmanned aerial vehicle;

and the control module 206 is used for controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to corresponding operation paths.

As shown in fig. 4, the embodiment of the present application further provides a working device 3, including: at least one processor 31 (only one processor is shown in fig. 4), a memory 32 and a computer program 33 stored in the memory 32 and executable on the at least one processor 31, the steps of the various method embodiments described above being implemented when the computer program 33 is executed by the processor 31.

In an application, the work device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that fig. 4 is merely an example of a 4-job apparatus and is not intended to be limiting, and that a job apparatus may include more or less components than those illustrated, or may combine some components, or may include different components, for example, input and output devices, which may include a display, a keyboard, a mouse, etc., and network access devices, which may include wired or wireless communication modules.

In application, the display may be a display screen, which may be a thin film transistor liquid crystal display (Thin Film Transistor Liquid Crystal Display, TFT-LCD), a liquid crystal display (Liquid Crystal Display, LCD), an Organic Light-Emitting Diode (OLED), a quantum dot Light Emitting Diode (Quantum Dot Light Emitting Diodes, QLED) display screen, a seven-segment or eight-segment nixie tube, or the like.

In an application, the communication module may comprise a wireless communication module or a wired communication module. The wireless communication module may include at least one of a wireless fidelity (WiFi) unit, a Bluetooth (Bluetooth) unit, a Zigbee (Zigbee) unit, a mobile communication network unit, a global navigation satellite system (Global Navigation Satellite System, GNSS) unit, a frequency modulation (Frequency Modulation, FM) unit, a near field wireless communication technology (Near Field Communication, NFC) unit, etc., and the wired communication module may include at least one of an Ethernet (Ethernet) unit, an asymmetric digital subscriber line (Asymmetric Digital Subscriber Line, ADSL) unit, a network fiber to the home (Fiber To The Home, FTTH) unit, etc.

In application, the processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

In applications, the memory may be an internal storage unit of the working device, such as a hard disk or a memory of the working device, in some embodiments. The memory may also be an external storage device of the working device in other embodiments, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the working device. Further, the memory may also include both an internal storage unit and an external storage device of the working device. The memory is used to store an operating system, application programs, boot Loader (Boot Loader), data, and other programs, etc., such as program code for a computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

It should be noted that, because the content of information interaction and execution process between the modules/units is based on the same concept as the embodiment of the present invention, specific functions and technical effects thereof may be referred to in the embodiment of the present invention, and will not be described herein.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

The embodiments of the present application also provide a computer readable storage medium storing a computer program, where the computer program can implement the steps in the above-mentioned method embodiments when executed by a processor.

Embodiments of the present application provide a computer program product enabling a working device to carry out the steps of the method embodiments described above when the computer program product is run on the working device.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program may implement the steps of each of the method embodiments described above when executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to an apparatus/terminal device, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. The operation method based on the plant protection unmanned aerial vehicle group is characterized by comprising the following steps of:

determining a target operation area according to the digital map;

generating a terrain model and a vegetation model of the target operation area;

2. The plant protection unmanned aerial vehicle-based operation method according to claim 1, wherein the digital map includes at least terrain information, crop type information, vegetation height information, and obstacle information.

3. The plant protection unmanned aerial vehicle-based operation method according to claim 1, wherein the dividing the target operation area into a plurality of sub-areas according to the terrain model and the vegetation model comprises:

dividing the target operation area into a plurality of sub-areas according to vegetation type and vegetation height information in the vegetation model, wherein each sub-area corresponds to one vegetation type and one vegetation height range.

4. The plant protection unmanned aerial vehicle-based operation method according to claim 1, wherein the allocating a corresponding operation task to each plant protection unmanned aerial vehicle according to the division result comprises:

and distributing corresponding operation tasks to each plant protection unmanned aerial vehicle through a genetic algorithm, an ant colony algorithm and a particle swarm algorithm according to the division result.

5. The plant protection unmanned aerial vehicle group-based operation method according to claim 1, wherein the operation task is a spraying task;

and controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to corresponding operation paths, wherein the control comprises the following steps:

collecting characteristic data of sub-areas on a corresponding working path of each plant protection unmanned aerial vehicle, wherein the characteristic data comprise vegetation positions and sprayed amounts;

according to the characteristic data, adjusting operation parameters of each plant protection unmanned aerial vehicle, wherein the operation parameters comprise flight height, flight speed, spraying angle and opening and closing degree of a spraying valve;

and controlling each plant protection unmanned aerial vehicle to complete corresponding operation tasks according to corresponding operation paths according to the operation parameters of each plant protection unmanned aerial vehicle.

6. The plant protection unmanned aerial vehicle-based operation method according to claim 5, wherein controlling each plant protection unmanned aerial vehicle to complete the corresponding operation task according to the corresponding operation path comprises:

7. The plant protection unmanned aerial vehicle-based operation method according to claim 1, comprising, before the determining the target operation area based on the digitized map:

and generating a digital map according to the basic information.

8. An operating system, comprising;

9. A working device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the plant protection unmanned aerial vehicle-based working method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the plant protection unmanned aerial vehicle group-based operation method according to any one of claims 1 to 7.