CN112987793B - Spraying method and device based on unmanned aerial vehicle, electronic equipment and medium - Google Patents
Spraying method and device based on unmanned aerial vehicle, electronic equipment and medium Download PDFInfo
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Abstract
The present disclosure relates to a spraying method apparatus, an electronic device, and a medium based on an unmanned aerial vehicle; wherein, the method comprises the following steps: determining a first characteristic area and a second characteristic area in the unmanned aerial vehicle operation process; wherein the first characteristic area comprises a crop canopy vortex area and the second characteristic area comprises a droplet deposition area; determining the distance between the center point of the first characteristic region and the center point of the second characteristic region, and determining the area difference between the area of the first characteristic region and the area of the second characteristic region; and adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference. The utility model discloses the operation parameter that this disclosed embodiment can adjust unmanned aerial vehicle at the operation in-process is so that crop canopy vortex region and droplet deposition area overlap, and canopy vortex region initiative contains droplet deposition area to improve the spraying precision, obtain the best operation effect.
Description
Technical Field
The present disclosure relates to the field of unmanned aerial vehicle technologies, and in particular, to a spraying method and apparatus, an electronic device, and a medium based on an unmanned aerial vehicle.
Background
The plant protection unmanned aerial vehicle is used as novel pesticide application equipment and is developed rapidly. Can produce decurrent rotor wind field during plant protection unmanned aerial vehicle operation, can produce the perturbation action to the crop canopy, the plant that is in the canopy vortex often takes place swing, blade upset phenomenon, and this has very big influence to droplet penetrability.
When the unmanned aerial vehicle rapidly advances in the operation process, both a fog droplet flow deposition area and a crop canopy vortex area lag behind, and under different operation speeds, due to different attenuation degrees of the movement speeds of different particles, the positions of air flow and fog droplets when the air flow and the fog droplets reach the crop canopy are different, so that the fog droplets are difficult to deposit in the canopy vortex area in time after blades are overturned in a rotor wind field, and the spraying effect is seriously influenced; thereby make plant protection unmanned aerial vehicle's operating efficiency greatly reduced.
Disclosure of Invention
In order to solve the above technical problems, or at least partially solve the above technical problems, the present disclosure provides a spraying method, apparatus, electronic device and medium based on an unmanned aerial vehicle.
In a first aspect, the present disclosure provides a drone-based spraying method, the method comprising:
determining a first characteristic area and a second characteristic area in the unmanned aerial vehicle operation process; wherein the first feature area comprises a crop canopy vortex area and the second feature area comprises a droplet deposition area;
determining the distance between the center point of the first characteristic region and the center point of the second characteristic region, and determining the area difference between the area of the first characteristic region and the area of the second characteristic region;
and adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference.
Optionally, the determining a first characteristic region and a second characteristic region in the unmanned aerial vehicle operation process includes:
acquiring operation parameters and meteorological parameters of the unmanned aerial vehicle in an operation process; wherein the operation parameters comprise at least one of flight speed, flight height, droplet particle size and model; the meteorological parameters comprise at least one of air temperature, humidity, wind speed and wind direction;
inputting the operation parameters into a first recognition model obtained by pre-training, and determining a first characteristic region according to the output of the first recognition model; the first recognition model is obtained by training according to a first historical characteristic region and historical operation parameters;
inputting the meteorological parameters into a second recognition model obtained by pre-training, and determining a second characteristic region according to the output of the second recognition model; and the second identification model is obtained by training according to a second historical characteristic region and historical meteorological parameters.
Optionally, the determining a first characteristic region and a second characteristic region in the unmanned aerial vehicle operation process includes:
acquiring a working image of the unmanned aerial vehicle during working;
performing segmentation processing on the operation image to obtain a first characteristic region and a second characteristic region; wherein the segmentation process includes at least one of an optical flow method, an inter-frame difference method, and a background subtraction method.
Optionally, the determining a distance between the center point of the first feature region and the center point of the second feature region includes:
carrying out contour extraction on the first characteristic region to obtain an enclosing region of the first characteristic region; extracting the outline of the second characteristic region to obtain an enclosing region of the second characteristic region;
determining the coordinates of the central point of the first characteristic region according to the surrounding region of the first characteristic region; determining the coordinates of the central point of the second characteristic region according to the surrounding region of the second characteristic region;
and calculating the distance between the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region.
Optionally, the determining an area difference between the area of the first feature region and the area of the second feature region includes:
and calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region.
Optionally, the determining a distance between the center point of the first feature region and the center point of the second feature region includes:
determining a first flight included angle of the first characteristic region and a second flight included angle of the second characteristic region according to the operation image;
determining a first lag distance according to the first flight angle and the flight height of the unmanned aerial vehicle; determining a second lag distance according to the second flight angle and the flight height of the unmanned aerial vehicle;
and taking the distance difference between the first lag distance and the second lag distance as the distance between the center point of the first feature region and the center point of the second feature region.
Optionally, the adjusting the operation parameters of the drone according to the distance and the area difference includes:
detecting whether the area difference is larger than a preset threshold value or not, and whether the distance is equal to the preset threshold value or not;
if not, adjusting at least one of the flying speed, the flying height and the droplet particle size of the unmanned aerial vehicle, so that the area difference is larger than a preset threshold value, and the distance is equal to the preset threshold value.
In a second aspect, the present disclosure also provides a spraying apparatus based on an unmanned aerial vehicle, including:
the first determining module is used for determining a first characteristic region and a second characteristic region in the unmanned aerial vehicle operation process; wherein the first feature area comprises a crop canopy vortex area and the second feature area comprises a droplet deposition area;
a second determining module, configured to determine a distance between a center point of the first feature region and a center point of the second feature region, and determine an area difference between an area of the first feature region and an area of the second feature region;
and the parameter adjusting module is used for adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference.
Optionally, the first determining module is specifically configured to:
acquiring operation parameters and meteorological parameters of the unmanned aerial vehicle in an operation process; wherein the operation parameters comprise at least one of flight speed, flight height, droplet particle size and model; the meteorological parameters comprise at least one of air temperature, humidity, wind speed and wind direction;
inputting the operation parameters into a first recognition model obtained by pre-training, and determining a first characteristic region according to the output of the first recognition model; the first recognition model is obtained by training according to a first historical characteristic region and historical operation parameters;
inputting the meteorological parameters into a second recognition model obtained by pre-training, and determining a second characteristic region according to the output of the second recognition model; and the second identification model is obtained by training according to a second historical characteristic region and historical meteorological parameters.
Optionally, the first determining module is specifically configured to:
acquiring an operation image of the unmanned aerial vehicle during operation;
performing segmentation processing on the operation image to obtain a first characteristic region and a second characteristic region; wherein the segmentation process includes at least one of an optical flow method, an inter-frame difference method, and a background subtraction method.
Optionally, the second determining module is specifically configured to:
carrying out contour extraction on the first characteristic region to obtain an enclosing region of the first characteristic region; extracting the outline of the second characteristic region to obtain an enclosing region of the second characteristic region;
determining the coordinates of the center point of the first characteristic region according to the surrounding region of the first characteristic region; determining the coordinates of the central point of the second characteristic region according to the surrounding region of the second characteristic region;
and calculating the distance between the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region.
Optionally, the second determining module is specifically configured to:
and calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinates of the central point of the first characteristic region and the coordinates of the central point of the second characteristic region.
Optionally, the second determining module is specifically configured to:
determining a first flight angle of the first characteristic region and a second flight angle of the second characteristic region according to the operation image;
determining a first lag distance according to the first flight angle and the flight height of the unmanned aerial vehicle; determining a second lag distance according to the second flight angle and the flight height of the unmanned aerial vehicle;
and taking the distance difference between the first lag distance and the second lag distance as the distance between the center point of the first feature region and the center point of the second feature region.
Optionally, the parameter adjusting module is specifically configured to:
detecting whether the area difference is larger than a preset threshold value or not, and whether the distance is equal to the preset threshold value or not;
if not, adjusting at least one of the flying speed, the flying height and the droplet particle size of the unmanned aerial vehicle, so that the area difference is larger than a preset threshold value, and the distance is equal to the preset threshold value.
In a third aspect, the present disclosure also provides an electronic device, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the drone-based nebulization method of any of the embodiments of the present invention.
In a fourth aspect, the present disclosure also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the drone-based spraying method of any one of the embodiments of the present invention.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages: can adjust unmanned aerial vehicle's operation parameter at the operation in-process so that crop canopy vortex region overlaps with droplet deposition area, and canopy vortex region initiative contains droplet deposition area to improve the spraying precision, obtain the best operation effect.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present disclosure, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a spraying method based on an unmanned aerial vehicle according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart diagram of another drone-based spraying method provided by an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of another unmanned aerial vehicle-based spraying method provided by the embodiment of the present disclosure;
fig. 4 is a schematic diagram of the operation of the drone;
fig. 5 is a schematic structural diagram of an unmanned aerial vehicle-based spraying device provided by an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, aspects of the present disclosure will be further described below. It should be noted that the embodiments and features of the embodiments of the present disclosure may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced in other ways than those described herein; it is to be understood that the embodiments disclosed in the specification are only a few embodiments of the present disclosure, and not all embodiments.
Fig. 1 is a schematic flow chart of a spraying method based on an unmanned aerial vehicle according to an embodiment of the present disclosure. This embodiment is applicable in the condition that utilizes unmanned aerial vehicle to carry out the plant protection operation. The method of the embodiment can be executed by a spraying device based on a unmanned aerial vehicle, and the device can be realized in a hardware and/or software manner and can be configured in electronic equipment. The spraying method based on the unmanned aerial vehicle can be achieved according to any embodiment of the application. As shown in fig. 1, the method specifically includes the following steps:
s110, determining a first characteristic area and a second characteristic area in the unmanned aerial vehicle operation process; wherein the first characteristic region comprises a crop canopy swirl region and the second characteristic region comprises a droplet deposition region.
Because unmanned aerial vehicle ignores natural wind power factor when the operation, when unmanned aerial vehicle is in the suspension, the rotor wind field can cause certain disturbance to the crop canopy, and crop canopy vortex area appears to can influence the penetrability of droplet. The crop canopy vortex area and the fog drop deposition area are both located below the unmanned aerial vehicle, and if the crop canopy vortex area and the fog drop deposition area are overlapped in the spraying process and the crop canopy vortex area actively contains the fog drop deposition area, fog drops can be effectively deposited on the lower layer and the back face of blades in a plant, so that the effective absorption of spraying is realized.
In this embodiment, the first characteristic area and the second characteristic area are two areas formed on crops when the unmanned aerial vehicle operates; the two regions are effectively analyzed, so that the first characteristic region and the second characteristic region can approach to overlap on a vertical plane, and the working efficiency of the unmanned aerial vehicle is improved.
And S120, determining the distance between the center point of the first characteristic region and the center point of the second characteristic region, and determining the area difference between the area of the first characteristic region and the area of the second characteristic region.
In this embodiment, the distance between the center point of the first feature region and the center point of the second feature region can effectively reflect the position deviation between the first feature region and the second feature region; the difference between the area of the first characteristic region and the area of the second characteristic region can directly reflect the size difference of the two regions, so that the coverage relation between the first characteristic region and the second characteristic region can be effectively judged.
S130, adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference.
The processes of a crop canopy vortex area and a fog drop deposition area generated by the unmanned aerial vehicle during operation are dynamic, so that the positions of the crop canopy vortex area and the fog drop deposition area are difficult to directly measure; therefore, this embodiment is through carrying out the adjustment of operation parameter in real time based on distance and the area deviation in two regions at unmanned aerial vehicle operation in-process to make the overlap of crop canopy vortex region and droplet deposition area, and crop canopy vortex region initiative contains droplet deposition area, thereby improves the spraying precision, makes unmanned aerial vehicle's operation effect reach the best.
The method comprises the steps of determining a first characteristic area and a second characteristic area in the operation process of the unmanned aerial vehicle; wherein the first characteristic area comprises a crop canopy vortex area and the second characteristic area comprises a droplet deposition area; determining the distance between the center point of the first characteristic region and the center point of the second characteristic region, and determining the area difference between the area of the first characteristic region and the area of the second characteristic region; and adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference. The utility model discloses the operation parameter that this disclosed embodiment can adjust unmanned aerial vehicle at the operation in-process is so that crop canopy vortex region and droplet deposition area overlap, and canopy vortex region initiative contains droplet deposition area to improve the spraying precision, obtain the best operation effect.
Fig. 2 is a schematic flow chart of another unmanned aerial vehicle-based spraying method provided in the embodiment of the present disclosure. The embodiment is further expanded and optimized on the basis of the above embodiment, and can be combined with any optional options in the above technical solutions. As shown in fig. 2, the method includes:
s210, acquiring operation parameters and meteorological parameters of the unmanned aerial vehicle in the operation process.
In the embodiment, the operation parameter includes at least one of flight speed, flight altitude, droplet size and model; the meteorological parameters include at least one of air temperature, humidity, wind speed, and wind direction.
The operation parameters of the unmanned aerial vehicle can be manually set in advance, and when the operation parameters are obtained, the operation parameters preset by the unmanned aerial vehicle can be read through a control system of the unmanned aerial vehicle; and local meteorological data is acquired based on the cloud server.
S220, inputting the operation parameters into a first recognition model obtained through pre-training, and determining a first characteristic region according to the output of the first recognition model; the first recognition model is obtained by training according to the first historical characteristic region and the historical operation parameters.
In this embodiment, the first recognition model obtained by pre-training may be a mathematical model obtained by using experimental and Computational Fluid Dynamics (CFD) research to obtain the operation parameters of the unmanned aerial vehicle and the crop canopy vortex region.
S230, inputting meteorological parameters into a second recognition model obtained through pre-training, and determining a second characteristic region according to the output of the second recognition model; and the second identification model is obtained by training according to the second historical characteristic region and the historical meteorological parameters.
In this embodiment, the second recognition model obtained by pre-training may be a mathematical model obtained by using a test and Computational Fluid Dynamics (CFD) study to obtain the operation parameters of the unmanned aerial vehicle and the droplet deposition area.
According to the embodiment, the crop canopy vortex area and the fog drop deposition area are effectively and quickly determined according to the input information of the model through the pre-trained recognition model, and the problem that the accurate area is difficult to directly acquire manually is solved.
S240, extracting the outline of the first characteristic region to obtain an enclosing region of the first characteristic region; and extracting the outline of the second characteristic region to obtain a surrounding region of the second characteristic region.
In this embodiment, the enclosing region of the first feature region is a boundary shape formed by boundary points of the first feature region; the surrounding area of the second feature area is a boundary shape composed of boundary points of the second feature area.
Specifically, the first feature region and the second feature region may be subjected to contour extraction by a contour extraction method, a boundary tracking method, a region growing method, or a region splitting and merging method, so as to obtain a boundary shape of the first feature region and a boundary shape of the second feature region.
S250, determining the coordinates of the central point of the first characteristic region according to the surrounding region of the first characteristic region; determining the coordinates of the central point of the second characteristic region according to the surrounding region of the second characteristic region; the distance between the coordinates of the center point of the first feature region and the coordinates of the center point of the second feature region is calculated.
In this embodiment, a distance formula between two points may be used to calculate a distance between the coordinates of the center point of the first feature region and the coordinates of the center point of the second feature region; see, in particular, the following equation (1).
Wherein x is a An abscissa which is a center point of the first feature region; y is a The ordinate is the central point of the first characteristic region; x is the number of b The abscissa is the center point of the second characteristic region; y is b Is the ordinate of the centre point of the second feature area.
And S260, calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinates of the central point of the first characteristic region and the coordinates of the central point of the second characteristic region.
In this embodiment, if the first feature region and the second feature region are regular patterns, the area calculation of the first feature region and the area calculation of the second feature region may be performed according to the area calculation manner of the regular patterns, and the area difference between the first feature region and the second feature region is obtained; if the first feature region and the second feature region are irregular patterns, the area thereof can be predicted to find the area difference between the two.
According to the embodiment, the distance between the coordinate of the center point of the first characteristic region and the coordinate of the center point of the second characteristic region and the area difference between the area of the first characteristic region and the area of the second characteristic region can be accurately calculated according to the coordinate of the center point of the first characteristic region and the coordinate of the center point of the second characteristic region.
S270, adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference.
Fig. 3 is a schematic flow chart of another spraying method based on an unmanned aerial vehicle according to an embodiment of the present disclosure. The embodiment is further expanded and optimized on the basis of the above embodiment, and can be combined with any optional options in the above technical solutions. As shown in fig. 3, the method includes:
s310, acquiring a working image during unmanned aerial vehicle working.
In the embodiment, the image information acquisition assembly is installed on the unmanned aerial vehicle, so that the image information of the first characteristic region and the second characteristic region is acquired and returned to the unmanned aerial vehicle during the operation of the unmanned aerial vehicle; specifically, the graphic information acquisition assembly can be installed directly over the unmanned aerial vehicle and on the side to gather image information.
The graphic types of the operation images acquired in this embodiment may include a red green blue (GRB) image, a full-color image, a depth image, a thermal infrared image, a hyperspectral image, a multispectral image, and a point cloud image.
S320, performing segmentation processing on the job image to obtain a first characteristic region and a second characteristic region; wherein the segmentation process includes at least one of an optical flow method, an inter-frame difference method, and a background subtraction method.
In the present embodiment, the first feature region and the second feature region may be distinguished by performing segmentation processing on the job image based on a boundary point thereof.
The embodiment also provides a method for determining the first characteristic region and the second characteristic region according to the working image of the unmanned aerial vehicle, and more identification methods are provided for determining the first characteristic region and the second characteristic region.
S330, determining a first flight angle of the first characteristic region and a second flight angle of the second characteristic region according to the operation image.
In this embodiment, a first flight included angle of the first characteristic region is an included angle between the unmanned aerial vehicle and the first characteristic region, the included angle being a reference line in a direction perpendicular to the ground; a second flight included angle of the second characteristic area is an included angle between the unmanned aerial vehicle and the second characteristic area, wherein the direction perpendicular to the ground is used as a reference line; specifically, fig. 4 can be seen, and fig. 4 is a schematic working diagram of the unmanned aerial vehicle; in fig. 4, the first included flight angle is α; the second included flight angle is β.
S340, determining a first lag distance according to the first flight included angle and the flight height of the unmanned aerial vehicle; determining a second lag distance according to the second flight angle and the flight height of the unmanned aerial vehicle; and taking the distance difference between the first lag distance and the second lag distance as the distance between the center point of the first characteristic region and the center point of the second characteristic region.
In the present embodiment, see fig. 4; the flight height of the unmanned aerial vehicle is a preset parameter value H; the first lag distance is L; the second lag distance is B; the distance between the center point of the first feature region and the center point of the second feature region can be seen in the following formula (2).
d＝L-B＝tanα·H-tanβ·H (2)
The embodiment also provides an optional method for calculating the distance between the center point of the first characteristic region and the center point of the second characteristic region, wherein the optional method can calculate the included angle between the first characteristic region and the second characteristic region according to the operation image so as to calculate the distance between the center point of the first characteristic region and the center point of the second characteristic region.
And S350, calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region.
S360, adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference.
In this embodiment, optionally, adjusting an operation parameter of the drone according to the distance and the area difference includes:
detecting whether the area difference is larger than a preset threshold value or not and whether the distance is equal to the preset threshold value or not;
if not, adjusting at least one of the flying speed, the flying height and the droplet particle size of the unmanned aerial vehicle, so that the area difference is larger than a preset threshold value, and the distance is equal to the preset threshold value.
The preset threshold of the present embodiment can approach zero. When the area difference between the first characteristic area and the second characteristic area is larger than zero and the distance is equal to zero, the fog drop deposition area can be overlapped in the crop canopy vortex area, and the effective penetration of the fog drops is realized.
This embodiment is through the area difference at unmanned aerial vehicle's operation in-process real-time supervision first characteristic region and second characteristic region to and whether the distance of the central point of first characteristic region to the central point of second characteristic region satisfies the preset condition, with this judgement whether need adjust the operation parameter, thereby realize effective control at unmanned aerial vehicle's operation in-process.
Fig. 5 is a schematic structural diagram of a spraying apparatus based on an unmanned aerial vehicle according to an embodiment of the present disclosure; the device is configured in electronic equipment, can realize the spraying method based on unmanned aerial vehicle that this application arbitrary embodiment said. The device specifically comprises the following steps:
a first determining module 510, configured to determine a first characteristic region and a second characteristic region in an operation process of the unmanned aerial vehicle; wherein the first feature area comprises a crop canopy vortex area and the second feature area comprises a droplet deposition area;
a second determining module 520, configured to determine a distance between a center point of the first feature region and a center point of the second feature region, and determine an area difference between an area of the first feature region and an area of the second feature region;
a parameter adjusting module 530, configured to adjust an operation parameter of the unmanned aerial vehicle according to the distance and the area difference.
In this embodiment, optionally, the first determining module 510 is specifically configured to:
acquiring operation parameters and meteorological parameters of the unmanned aerial vehicle in an operation process; wherein the operation parameters comprise at least one of flight speed, flight height, droplet particle size and model; the meteorological parameters comprise at least one of air temperature, humidity, wind speed and wind direction;
inputting the operation parameters into a first recognition model obtained by pre-training, and determining a first characteristic region according to the output of the first recognition model; the first recognition model is obtained by training according to a first historical characteristic region and historical operation parameters;
inputting the meteorological parameters into a second recognition model obtained by pre-training, and determining a second characteristic region according to the output of the second recognition model; and the second identification model is obtained by training according to a second historical characteristic region and historical meteorological parameters.
In this embodiment, optionally, the first determining module 510 is specifically configured to:
acquiring a working image of the unmanned aerial vehicle during working;
performing segmentation processing on the operation image to obtain a first characteristic region and a second characteristic region; wherein the segmentation process includes at least one of an optical flow method, an inter-frame difference method, and a background subtraction method.
In this embodiment, optionally, the second determining module 520 is specifically configured to:
carrying out contour extraction on the first characteristic region to obtain an enclosing region of the first characteristic region; extracting the outline of the second characteristic region to obtain an enclosing region of the second characteristic region;
determining the coordinates of the center point of the first characteristic region according to the surrounding region of the first characteristic region; determining the coordinates of the central point of the second characteristic region according to the surrounding region of the second characteristic region;
and calculating the distance between the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region.
In this embodiment, optionally, the second determining module 520 is specifically configured to:
and calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinates of the central point of the first characteristic region and the coordinates of the central point of the second characteristic region.
In this embodiment, optionally, the second determining module 520 is specifically configured to:
determining a first flight angle of the first characteristic region and a second flight angle of the second characteristic region according to the operation image;
determining a first lag distance according to the first flight angle and the flight height of the unmanned aerial vehicle; determining a second lag distance according to the second flight angle and the flight height of the unmanned aerial vehicle;
and taking the distance difference between the first lag distance and the second lag distance as the distance between the center point of the first feature region and the center point of the second feature region.
In this embodiment, optionally, the parameter adjusting module 530 is specifically configured to:
detecting whether the area difference is larger than a preset threshold value or not, and whether the distance is equal to the preset threshold value or not;
if not, adjusting at least one of the flying speed, the flying height and the droplet particle size of the unmanned aerial vehicle, so that the area difference is larger than a preset threshold value, and the distance is equal to the preset threshold value.
By the spraying device based on the unmanned aerial vehicle, the operation parameters of the unmanned aerial vehicle can be adjusted in the operation process, so that the crop canopy vortex area and the droplet deposition area are overlapped, and the canopy vortex area actively comprises the droplet deposition area, so that the spraying precision is improved, and the optimal operation effect is obtained.
The spraying device based on the unmanned aerial vehicle provided by the embodiment of the invention can execute the spraying method based on the unmanned aerial vehicle provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Fig. 6 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. As shown in fig. 6, the electronic device includes a processor 610, a memory 620, an input device 630, and an output device 640; the number of the processors 610 in the electronic device may be one or more, and one processor 610 is taken as an example in fig. 6; the processor 610, the memory 620, the input device 630 and the output device 640 in the electronic apparatus may be connected by a bus or other means, and the connection by the bus is exemplified in fig. 6.
The memory 620, as a computer-readable storage medium, may be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the drone-based nebulization method in embodiments of the present invention. The processor 610 executes various functional applications and data processing of the electronic device by executing software programs, instructions and modules stored in the memory 620, so as to implement the drone-based spraying method provided by the embodiment of the present invention.
The memory 620 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 620 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 620 can further include memory located remotely from the processor 610, which can be connected to an electronic device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 630 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device, and may include a keyboard, a mouse, and the like. The output device 640 may include a display device such as a display screen.
The disclosed embodiments also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are used to implement the drone-based spraying method provided by the embodiments of the present invention.
Of course, the storage medium provided by the embodiments of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the operations of the method described above, and may also perform related operations in the unmanned aerial vehicle-based spraying method provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly can be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the above search apparatus, each included unit and module are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The previous description is only for the purpose of describing particular embodiments of the present disclosure, so as to enable those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. A drone-based spraying method, the method comprising:
determining a first characteristic area and a second characteristic area in the unmanned aerial vehicle operation process; wherein the first feature area comprises a crop canopy vortex area and the second feature area comprises a droplet deposition area;
determining a distance between a center point of the first feature region and a center point of the second feature region, and determining an area difference between an area of the first feature region and an area of the second feature region;
adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference;
the determining a first characteristic region and a second characteristic region in the unmanned aerial vehicle operation process comprises:
acquiring operation parameters and meteorological parameters of the unmanned aerial vehicle in an operation process; wherein the operation parameters comprise at least one of flight speed, flight height, droplet particle size and model; the meteorological parameters comprise at least one of air temperature, humidity, wind speed and wind direction;
inputting the operation parameters into a first recognition model obtained by pre-training, and determining a first characteristic region according to the output of the first recognition model; the first recognition model is obtained by training according to a first historical characteristic region and historical operation parameters;
inputting the meteorological parameters into a second recognition model obtained by pre-training, and determining a second characteristic region according to the output of the second recognition model; the second identification model is obtained by training according to a second historical characteristic region and historical meteorological parameters;
the determining the distance between the center point of the first feature region and the center point of the second feature region includes:
carrying out contour extraction on the first characteristic region to obtain an enclosing region of the first characteristic region; extracting the outline of the second characteristic region to obtain an enclosing region of the second characteristic region;
determining the coordinates of the center point of the first characteristic region according to the surrounding region of the first characteristic region; determining the coordinates of the central point of the second characteristic region according to the surrounding region of the second characteristic region;
calculating the distance between the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region;
the determining an area difference between the area of the first feature region and the area of the second feature region comprises:
calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region;
the adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference comprises:
detecting whether the area difference is larger than a preset threshold value or not, and whether the distance is equal to the preset threshold value or not;
if not, adjusting at least one of the flying speed, the flying height and the droplet particle size of the unmanned aerial vehicle, so that the area difference is larger than a preset threshold value, and the distance is equal to the preset threshold value.
2. The method of claim 1, wherein determining the first and second characteristic regions during operation of the drone comprises:
acquiring a working image of the unmanned aerial vehicle during working;
performing segmentation processing on the operation image to obtain a first characteristic region and a second characteristic region; wherein the segmentation process comprises at least one of an optical flow method, an inter-frame difference method and background subtraction.
3. The method of claim 2, wherein determining the distance between the center point of the first feature region and the center point of the second feature region comprises:
determining a first flight angle of the first characteristic region and a second flight angle of the second characteristic region according to the operation image;
determining a first lag distance according to the first flight angle and the flight height of the unmanned aerial vehicle; determining a second lag distance according to the second flight angle and the flight height of the unmanned aerial vehicle;
and taking the distance difference between the first lag distance and the second lag distance as the distance between the center point of the first feature region and the center point of the second feature region.
4. A atomizer based on unmanned aerial vehicle, its characterized in that, the device includes:
the first determining module is used for determining a first characteristic region and a second characteristic region in the unmanned aerial vehicle operation process; wherein the first feature area comprises a crop canopy vortex area and the second feature area comprises a droplet deposition area;
a second determining module, configured to determine a distance between a center point of the first feature region and a center point of the second feature region, and determine an area difference between an area of the first feature region and an area of the second feature region;
the parameter adjusting module is used for adjusting the operation parameters of the unmanned aerial vehicle according to the distance and the area difference;
the first determining module is used for determining a first characteristic area and a second characteristic area in the unmanned aerial vehicle operation process, and is specifically used for:
acquiring operation parameters and meteorological parameters of the unmanned aerial vehicle in an operation process; wherein the operation parameters comprise at least one of flight speed, flight height, droplet particle size and model; the meteorological parameters comprise at least one of air temperature, humidity, wind speed and wind direction;
inputting the operation parameters into a first recognition model obtained by pre-training, and determining a first characteristic region according to the output of the first recognition model; the first recognition model is obtained by training according to a first historical characteristic region and historical operation parameters;
inputting the meteorological parameters into a second recognition model obtained by pre-training, and determining a second characteristic region according to the output of the second recognition model; the second identification model is obtained by training according to a second historical characteristic region and historical meteorological parameters;
the second determining module is configured to determine a distance between a center point of the first feature region and a center point of the second feature region, and is specifically configured to:
carrying out contour extraction on the first characteristic region to obtain an enclosing region of the first characteristic region; extracting the outline of the second characteristic region to obtain an enclosing region of the second characteristic region;
determining the coordinates of the center point of the first characteristic region according to the surrounding region of the first characteristic region; determining the coordinates of the central point of the second characteristic region according to the surrounding region of the second characteristic region;
calculating the distance between the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region;
the second determining module is configured to determine an area difference between the area of the first feature region and the area of the second feature region, and specifically configured to:
calculating the area difference between the area of the first characteristic region and the area of the second characteristic region according to the coordinate of the central point of the first characteristic region and the coordinate of the central point of the second characteristic region;
the parameter adjusting module adjusts the operation parameters of the unmanned aerial vehicle according to the distance and the area difference, and is specifically used for:
detecting whether the area difference is larger than a preset threshold value or not, and whether the distance is equal to the preset threshold value or not;
if not, adjusting at least one of the flying speed, the flying height and the droplet particle size of the unmanned aerial vehicle, so that the area difference is larger than a preset threshold value, and the distance is equal to the preset threshold value.
5. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the drone-based nebulization method of any one of claims 1-3.
6. A computer-readable storage medium, on which a computer program is stored, which program, when executed by a processor, implements the drone-based spraying method of any one of claims 1 to 3.
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