Unmanned aerial vehicle spraying control method and device, electronic equipment and computer readable medium

Abstract

This disclosure presents embodiments of a drone painting control method, apparatus, electronic device, and computer-readable medium. One specific implementation of the method includes: scanning a work area to be painted to obtain a three-dimensional model; projecting the image to be painted onto the three-dimensional model to obtain a texture mapping image; dividing the texture mapping image into a raster set to obtain a raster sub-map; for each raster sub-map, generating primary color ratio information based on the color value of each pixel included in the raster sub-map, and generating a painting command based on the primary color ratio information and the corresponding drone coordinates; determining a painting command sequence corresponding to each painting command; for each painting command, controlling the painting drone to fly to the drone coordinates corresponding to the painting command, and controlling the painting drone to extract paint according to the primary color ratio information included in the painting command for painting. This implementation can improve painting efficiency and accuracy.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of edge computing technology, and more specifically to drone painting control methods, apparatus, electronic devices, and computer-readable media. Background Technology

[0002] Currently, the level of intelligence and automation in building exterior painting operations remains low. At present, the common methods used for painting operations are manual spraying or drone spraying.

[0003] However, when using the above methods, a common technical problem is that manual spraying is prone to uneven spraying, and existing drone spraying requires repeated paint changes to adjust the color, which reduces the accuracy and efficiency of spraying. Summary of the Invention

[0004] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0005] Some embodiments of this disclosure provide drone painting control methods, apparatuses, electronic devices, and computer-readable media to address the technical problems mentioned in the background section above.

[0006] In a first aspect, some embodiments of this disclosure provide a drone painting control method, the method comprising: scanning a work area to be painted using a painting drone to obtain a three-dimensional model to be painted; projecting a preset image to be painted onto the three-dimensional model to be painted to obtain a texture mapping image, wherein each pixel in the texture mapping image corresponds to three-dimensional surface coordinates; dividing the texture mapping image into a grid to obtain a grid sub-atlas, wherein each grid image in the grid sub-atlas corresponds to drone coordinates; for each grid image in the grid sub-atlas, generating primary color ratio information based on the color value of each pixel included in the grid image, and generating a painting command based on the primary color ratio information and the drone coordinates corresponding to the grid image; determining a painting command sequence corresponding to each generated painting command; for each painting command in the painting command sequence, controlling the painting drone to fly to the drone coordinates corresponding to the painting command, and controlling the painting drone to extract paint according to the primary color ratio information included in the painting command for painting.

[0007] Secondly, some embodiments of this disclosure provide a drone painting control device, the device comprising: a scanning unit configured to scan a painting work area using a painting drone to obtain a three-dimensional model to be painted; a projection unit configured to project a preset image to be painted onto the three-dimensional model to be painted to obtain a texture mapping image, wherein each pixel in the texture mapping image corresponds to three-dimensional surface coordinates; a grid division unit configured to perform grid division on the texture mapping image to obtain a grid sub-atlas, wherein each grid image in the grid sub-atlas corresponds to drone coordinates; and a generation unit configured to... For each grid subgraph in the aforementioned grid subgraph set, a three-primary-color ratio information is generated based on the color value of each pixel included in the aforementioned grid subgraph, and a spraying instruction is generated based on the three-primary-color ratio information and the drone coordinates corresponding to the aforementioned grid subgraph; a determining unit is configured to determine the spraying instruction sequence corresponding to each generated spraying instruction; a controlling unit is configured to, for each spraying instruction in the aforementioned spraying instruction sequence, control the spraying drone to fly to the drone coordinates corresponding to the aforementioned spraying instruction, and control the spraying drone to extract paint according to the three-primary-color ratio information included in the aforementioned spraying instruction for spraying.

[0008] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0009] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0010] The various embodiments disclosed above have the following beneficial effects: The drone painting control method of some embodiments of this disclosure improves the accuracy and efficiency of painting. First, by automating the process, the accuracy of painting is improved, avoiding the problem of uneven painting that easily occurs when relying solely on visual judgment during manual painting. Next, the paint ratio is dynamically changed according to different RGB values, thereby changing the paint color. Through automatic mixing, the problems of work interruption, efficiency loss, and unnatural color transitions caused by frequent paint changes in traditional drone painting are solved, thus improving the accuracy and efficiency of painting. Attached Figure Description

[0011] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0012] Figure 1 This is a flowchart of some embodiments of the UAV spraying control method according to the present disclosure; Figure 2 This is a schematic diagram of a spraying drone according to some embodiments of the drone spraying control method disclosed herein; Figure 3 This is a schematic diagram of the structure of some embodiments of the drone painting control device according to the present disclosure; Figure 4 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0013] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0014] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0015] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0016] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0017] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0018] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] Figure 1This is a flow 100 according to some embodiments of the drone painting control method disclosed herein. The drone painting control method includes the following steps: Step 101: Use a spraying drone to scan the area to be sprayed to obtain a three-dimensional model of the area to be sprayed.

[0020] In some embodiments, the execution entity (e.g., a computing device) of the UAV spraying control method can scan the work area to be sprayed using the spraying UAV to obtain a 3D model of the area to be sprayed. The execution entity can be an edge computing device. The execution entity can be deployed within the spraying UAV to control it. The spraying UAV may include: a camera, an aircraft, a peristaltic pump, a ducted motor, and the aforementioned edge computing device. The spraying UAV can be used to spray paint the exterior facade of buildings. The spraying UAV can be as follows: Figure 2 As shown. The area to be sprayed can be the outer surface of a building.

[0021] Optionally, the aforementioned execution entity may use a spraying drone to scan the work area to be sprayed to obtain a three-dimensional model of the area to be sprayed, which may include the following steps: The first step involves controlling the painting drone to fly along a preset trajectory and capturing video of the work area to be painted using the aforementioned camera. The preset trajectory can be a sequence of multiple pre-planned 3D coordinate points. This preset trajectory ensures that the drone can comprehensively cover the entire work area to be painted and acquire sufficient multi-view image data for 3D reconstruction. In practice, the executing entity can control the painting drone to fly along the preset trajectory, capturing video of the work area to be painted using the camera mounted on the drone during flight.

[0022] The second step is to perform 3D reconstruction on the video of the work area to be sprayed, obtaining a 3D model of the building to be sprayed. This 3D model can be a 3D model of the building to be sprayed. In practice, the executing entity can first use a preset 3D reconstruction algorithm to perform 3D reconstruction on the video of the work area to be sprayed, obtaining the 3D model. This 3D reconstruction algorithm can include, but is not limited to, ORB-SLAM (Vision-Based Simultaneous Localization and Mapping) and SFM (Structure of Motion) algorithms.

[0023] Optionally, the aforementioned executing entity can transmit the video of the work area to be painted to a preset cloud platform. Then, based on the cloud platform, the aforementioned 3D reconstruction algorithm can be used to perform 3D reconstruction of the video of the work area to be painted, obtaining a 3D model of the area to be painted. The aforementioned edge computing device can communicate with the cloud platform wirelessly. The cloud platform can be a cloud computing platform used for handling complex calculations.

[0024] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0025] Step 102: Project the preset image to be sprayed onto the above-mentioned three-dimensional model to be sprayed to obtain a texture mapping image.

[0026] In some embodiments, the execution entity can project a preset image to be sprayed onto the three-dimensional model to be sprayed to obtain a texture mapping image. Each pixel in the texture mapping image corresponds to three-dimensional surface coordinates. These three-dimensional surface coordinates can be the three-dimensional coordinates of points in the three-dimensional model to be sprayed. In practice, the preset image to be sprayed can be projected onto the target area of ​​the three-dimensional model using orthogonal projection, thereby determining the corresponding position of each pixel in the three-dimensional space and identifying the projected image as a texture mapping image. The target area can be a predefined wall area to be sprayed. The target area can be represented by preset vertex coordinates. For example, when the target wall area is a square area, it can be represented as: (x_1, y_1, z_1), (x_2, y_2, z_2), (x_3, y_3, z_3), (x_4, y_4, z_4).

[0027] Optionally, the execution entity projects a preset image to be sprayed onto the three-dimensional model to be sprayed to obtain a texture mapping image, which may include the following steps: The first step is to segment the target area model from the aforementioned 3D model to be sprayed, based on the preset target area information. This target area information can include the 3D coordinates of each vertex of the wall area to be sprayed. In practice, firstly, a target spatial range can be determined in 3D space based on the target area information. This target spatial range can be a flat 3D region with a certain thickness tolerance, using the wall area to be sprayed as a reference. Next, all 3D points in the aforementioned 3D model to be sprayed are traversed. For each 3D point, it is determined whether its spatial position is within the aforementioned target spatial range. Finally, all 3D points whose spatial positions are within the aforementioned target spatial range are extracted and combined to form the target area model.

[0028] The second step is to perform texture coordinate unrolling on the target region model to obtain a texture coordinate set. Each texture coordinate in this set corresponds one-to-one with each 3D point in the target region model. In practice, a pre-defined UV unrolling algorithm can be used to perform texture coordinate unrolling on the target region model to obtain the texture coordinate set. This UV unrolling algorithm can be the LSCM (Least Squares Conformal Mapping) algorithm.

[0029] The third step involves using the preset image to be sprayed as a texture map and mapping it to the aforementioned texture coordinate set to generate a texture-mapped image. In practice, texture mapping technology can be used to use the preset image to be sprayed as a texture map and map it to the aforementioned texture coordinate set to generate a texture-mapped image.

[0030] As an example, the image to be sprayed is mapped as a texture map to the texture coordinate set, that is, the two-dimensional pixel coordinates (i, j) of the image to be sprayed are mapped to texture coordinates (u, v) through translation and scaling. Then, based on the one-to-one correspondence between texture coordinates and three-dimensional surface coordinates, the correspondence between each pixel in the image to be sprayed and the three-dimensional surface coordinates (x, y, z) is determined, thus obtaining a texture-mapped image with pixel-to-three-dimensional coordinate mapping.

[0031] Step 103: Divide the texture mapping image into a raster to obtain a raster sub-atlas.

[0032] In some embodiments, the execution entity may perform rasterization on the texture mapping image to obtain a raster sub-atlas. Each raster image in the raster sub-atlas corresponds to UAV coordinates.

[0033] Optionally, the execution entity may perform rasterization on the texture mapping image to obtain a raster sub-atlas, which may include the following steps: The first step involves uniformly dividing the texture mapping image into a grid based on a preset grid density, resulting in an initial raster sub-atlas. The grid density can be the product of the number of raster rows and the number of raster columns. The number of raster rows represents the number of rows that divide the texture mapping image vertically. The number of raster columns represents the number of columns that divide the texture mapping image horizontally.

[0034] As an example, when the grid partitioning density is M×N, the height of the initial raster sub-image is the height of the texture mapping image divided by M, and the width of the initial raster sub-image is the width of the texture mapping image divided by N. Based on the grid partitioning density, the texture mapping image is divided into M×N initial raster sub-images to obtain an initial raster image set.

[0035] The second step involves performing the following steps for each initial raster map in the aforementioned initial raster sub-set: The first sub-step involves generating the grid center point coordinates and grid surface normal vectors based on the 3D surface coordinates of each pixel in the initial grid sub-image. The initial grid sub-image may contain multiple pixels, each with its own 3D surface coordinates. In practice, the average of the 3D surface coordinates of all pixels in the initial grid sub-image can be used to determine the grid center point coordinates. Then, a plane fitting technique can be used to determine the plane corresponding to the 3D surface coordinates of each pixel. Finally, the normal vector of this plane is determined as the grid surface normal vector. The plane fitting technique can include, but is not limited to, SVD decomposition and least squares methods.

[0036] The second sub-step involves translating the coordinates of the grid center point along the direction of the grid surface normal vector, based on a preset wall safety distance, to obtain the translated coordinates. The wall safety distance can be a preset length, such as 46cm, but is not specifically limited here.

[0037] As an example, assuming the grid center point coordinates are (x, y, z), the grid surface normal vector is (1, 0, 0), and the wall safety distance is 0.46m, then the grid center point coordinates after translation are (x+0.46, y, z).

[0038] The third sub-step involves determining the UAV coordinates corresponding to the aforementioned translation coordinates based on preset safe altitude information. This safe altitude information may include the minimum acceptable altitude for UAV flight.

[0039] As an example, assume the safety height information is 0.8m. When the z-value of the above translation coordinate is less than the above safety height information, the above safety height information of 0.8m can be determined as z.

[0040] The fourth sub-step involves generating a raster submap based on the initial raster submap, the raster surface normal vector, and the UAV coordinates. In practice, the initial raster submap, the raster surface normal vector, and the UAV coordinates can be collectively defined as a single raster submap. For example, the raster surface normal vector and the UAV coordinates can be used as labels for the initial raster submap to generate the raster submap.

[0041] Step 104: For each grid image in the above grid image set, generate the three primary color ratio information based on the color value of each pixel included in the grid image, and generate a spraying command based on the three primary color ratio information and the UAV coordinates corresponding to the grid image.

[0042] In some embodiments, the execution entity can generate primary color ratio information for each grid image in the grid image set, based on the color value of each pixel included in the grid image, and generate a spraying command based on the primary color ratio information and the UAV coordinates corresponding to the grid image. The color values ​​can be RGB values. These color values ​​may include red, green, and blue components.

[0043] Optionally, the execution entity generates the primary color ratio information based on the color value of each pixel included in the raster subgraph, which may include the following steps: First, for each pixel included in the above raster submap, perform the following steps: The first sub-step involves converting the color values ​​of the aforementioned pixels to obtain the three primary color information. This information includes the cyan, magenta, and yellow components. In practice, the red, green, and blue components of the pixels can be converted using the following formulas to obtain the cyan, magenta, and yellow components. These cyan, magenta, and yellow components are then identified as the three primary color information.

[0044] .

[0045] In this context, C represents the cyan component, M represents the magenta component, Y represents the yellow component, R represents the red component, G represents the green component, and B represents the blue component.

[0046] The second sub-step involves normalizing the aforementioned three primary color information to obtain normalized three primary color information. This normalized information may include a normalized cyan component, a normalized magenta component, and a normalized yellow component. In practice, firstly, the cyan, magenta, and yellow components can be summed to obtain the total paint concentration. Then, the ratio between the cyan component and the total paint concentration can be determined as the normalized cyan component. Similarly, the ratio between the magenta component and the total paint concentration can be determined as the normalized magenta component. Finally, the ratio between the yellow component and the total paint concentration can be determined as the normalized yellow component.

[0047] The second step is to generate the proportions of the three primary colors based on the determined normalized cyan, magenta, and yellow components. In practice, firstly, the sum of the determined normalized cyan components can be used to determine the overall cyan component. Next, the sum of the determined normalized magenta components can be used to determine the overall magenta component. Secondly, the sum of the determined normalized yellow components can be used to determine the overall yellow component. Finally, the proportional relationships between the overall cyan, overall magenta, and overall yellow components can be determined as the proportions of the three primary colors.

[0048] Step 105: Determine the spraying instruction sequence corresponding to each of the generated spraying instructions.

[0049] In some embodiments, the executing entity can determine the sequence of spraying instructions corresponding to each generated spraying instruction. In practice, the instructions can be sorted according to the spatial positional relationship of the UAV coordinates corresponding to each spraying instruction to generate an ordered sequence of spraying instructions.

[0050] As an example, a zigzag spatial sequence can be used to arrange spraying instructions to form a coherent and efficient work path. This reduces the flight movement and attitude adjustment of the spraying drone, improving overall work efficiency.

[0051] Step 106: For each spraying instruction in the above spraying instruction sequence, control the spraying drone to fly to the drone coordinates corresponding to the above spraying instruction, and control the spraying drone to extract paint according to the three primary color ratio information included in the above spraying instruction for spraying.

[0052] In some embodiments, the executing entity can, for each spraying instruction in the spraying instruction sequence, control the spraying drone to fly to the drone coordinates corresponding to the spraying instruction, and control the spraying drone to extract paint according to the three primary color ratio information included in the spraying instruction for spraying. In practice, for each spraying instruction in the spraying instruction sequence, the executing entity can first control the spraying drone to fly to the drone coordinates corresponding to the spraying instruction. Once it is determined that the spraying drone has reached the drone coordinates and is in a stable state, it can control the spraying drone to extract and spray paint according to the three primary color ratio information included in the spraying instruction. After spraying is completed, the executing entity can determine that the spraying instruction has been executed and continue to execute the next spraying instruction.

[0053] Optionally, the aforementioned executing entity controls the aforementioned painting drone to extract paint according to the three primary color ratio information included in the aforementioned painting instruction for painting, which may include the following steps: The first step involves controlling the peristaltic pump included in the painting drone to extract and mix the three primary colors of paint, according to the proportions of the three primary colors included in the painting instructions. This peristaltic pump may include three independent pump heads. These three independent pump heads are respectively connected to cyan, magenta, and yellow paint hoses. These hoses are used to deliver the paint.

[0054] As an example, assume the primary color ratio information corresponding to the above spraying instruction is cyan: magenta: yellow = 0.7:0.1:0.2. The executing entity can drive the pump head responsible for cyan paint to extrude 0.7 unit volume of cyan paint; drive the pump head responsible for magenta paint to extrude 0.1 unit volume of magenta paint; and drive the pump head responsible for yellow paint to extrude 0.2 parts of yellow paint, so that the three colors of paint enter the mixing chamber for mixing. The mixing chamber can be a device for mixing the three colors of paint. The mixing chamber is a connecting component located between the peristaltic pump and the ducted motor. The mixing chamber can include an inlet end and an outlet end. The inlet of the mixing chamber can be connected to the output end of the peristaltic pump. The outlet end of the mixing chamber can be connected to the input end of the ducted motor.

[0055] Optionally, the mixing chamber may be designed with a static mixer to promote rapid and uniform mixing of different colored paints, ensuring the accuracy of the final sprayed color.

[0056] The second step involves controlling the aforementioned ducted motor to spray out the mixed paint. This ducted motor can be positioned at the other end of the mixing chamber to spray out the paint pushed out by the peristaltic pump.

[0057] Optionally, after step 106 above, the executing entity may also control the painting drone to return to its home position in response to determining that all painting commands in the painting command sequence have been executed. In practice, after all painting commands in the painting command sequence have been executed, the executing entity can control the painting drone to automatically return to a preset takeoff point or parking point.

[0058] Further reference Figure 3 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a drone spraying control device, which are similar to... Figure 1 Corresponding to the method embodiments shown, this drone painting control device can be specifically applied to various electronic devices.

[0059] like Figure 3 As shown, the drone painting control device 300 in some embodiments includes: a scanning unit 301, a projection unit 302, a grid division unit 303, a generation unit 304, a determination unit 305, and a control unit 306. The scanning unit 301 is configured to scan the painting work area using the painting drone to obtain a three-dimensional model to be painted; the projection unit 302 is configured to project a preset image to be painted onto the three-dimensional model to be painted to obtain a texture mapping image, wherein each pixel in the texture mapping image corresponds to three-dimensional surface coordinates; the grid division unit 303 is configured to perform grid division on the texture mapping image to obtain a grid sub-atlas, wherein each grid sub-atlas corresponds to drone coordinates; the generation unit 304 is configured to generate each pixel in the grid sub-atlas... A grid sub-map is generated, and based on the color value of each pixel included in the grid sub-map, three primary color ratio information is generated. A spraying instruction is generated based on the three primary color ratio information and the drone coordinates corresponding to the grid sub-map. A determining unit 305 is configured to determine the spraying instruction sequence corresponding to each generated spraying instruction. A control unit 306 is configured to, for each spraying instruction in the spraying instruction sequence, control the spraying drone to fly to the drone coordinates corresponding to the spraying instruction, and control the spraying drone to extract paint according to the three primary color ratio information included in the spraying instruction for spraying.

[0060] It is understandable that the units described in the UAV painting control device 300 are similar to those in the reference. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the UAV painting control device 300 and the units contained therein, and will not be repeated here.

[0061] The following is for reference. Figure 4It shows a schematic diagram of the structure of an electronic device 400 (e.g., a computing device) suitable for implementing some embodiments of the present disclosure. Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0062] like Figure 4 As shown, the electronic device 400 may include a processing unit 401 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM 402) or a program loaded from a storage device 408 into a random access memory (RAM 403). The RAM 403 also stores various programs and data required for the operation of the electronic device 400. The processing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0063] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic device 400 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 An electronic device 400 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 4 Each box shown can represent a device or multiple devices as needed.

[0064] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 409, or installed from storage device 408, or installed from ROM 402. When the computer program is executed by processing device 401, it performs the functions defined above in the methods of some embodiments of this disclosure.

[0065] It should be noted that, in some embodiments of this disclosure, the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0066] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0067] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs. When the aforementioned one or more programs are executed by the electronic device, the electronic device causes the following: a spraying drone scans the area to be sprayed to obtain a three-dimensional model to be sprayed; a preset image to be sprayed is projected onto the three-dimensional model to obtain a texture mapping image, wherein each pixel in the texture mapping image corresponds to three-dimensional surface coordinates; the texture mapping image is rasterized to obtain a raster sub-atlas, wherein each raster in the raster sub-atlas corresponds to drone coordinates; for each raster in the raster sub-atlas, three primary color ratio information is generated based on the color value of each pixel included in the raster, and a spraying instruction is generated based on the three primary color ratio information and the drone coordinates corresponding to the raster; a spraying instruction sequence corresponding to each generated spraying instruction is determined; for each spraying instruction in the spraying instruction sequence, the spraying drone is controlled to fly to the drone coordinates corresponding to the spraying instruction, and the spraying drone is controlled to extract paint according to the three primary color ratio information included in the spraying instruction for spraying.

[0068] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0069] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0070] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0071] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for controlling the spraying of paint on a drone, characterized in that, include: A spraying drone is used to scan the area to be sprayed, and a three-dimensional model of the area to be sprayed is obtained. The preset image to be sprayed is projected onto the three-dimensional model to be sprayed to obtain a texture mapping image, wherein each pixel in the texture mapping image corresponds to a three-dimensional surface coordinate. The texture mapping image is divided into grids to obtain a grid sub-map set, wherein each grid map in the grid sub-map set corresponds to UAV coordinates; For each grid image in the grid sub-image set, the three primary color ratio information is generated based on the color value of each pixel included in the grid image, and the spraying command is generated based on the three primary color ratio information and the UAV coordinates corresponding to the grid image; Determine the spraying instruction sequence corresponding to each generated spraying instruction; For each spraying instruction in the spraying instruction sequence, the spraying drone is controlled to fly to the drone coordinates corresponding to the spraying instruction, and the spraying drone is controlled to extract paint according to the three primary color ratio information included in the spraying instruction for spraying.

2. The method according to claim 1, characterized in that, The method further includes: In response to determining that each spraying command in the spraying command sequence has been executed, the spraying drone is controlled to return to its home position.

3. The method according to claim 1, characterized in that, The painting drone includes a camera; The method of scanning the work area to be sprayed using a spraying drone to obtain a three-dimensional model of the area to be sprayed includes: The spraying drone is controlled to fly along a preset trajectory, and the camera is used to capture video of the area to be sprayed, thus obtaining a video of the area to be sprayed. The video of the work area to be sprayed is reconstructed in three dimensions to obtain a three-dimensional model of the area to be sprayed.

4. The method according to claim 1, characterized in that, The step of projecting a preset image to be sprayed onto the three-dimensional model to be sprayed to obtain a texture mapping image includes: Based on the preset target area information, the target area model is segmented from the three-dimensional model to be sprayed; The target region model is unfolded using texture coordinates to obtain a texture coordinate set; The preset image to be sprayed is used as a texture map and mapped to the texture coordinate set to generate a texture mapping image.

5. The method according to claim 1, characterized in that, The step of rasterizing the texture mapping image to obtain a raster sub-atlas includes: Based on a preset grid division density, the texture mapping image is uniformly divided into grids to obtain an initial raster atlas; For each initial raster map in the initial raster sub-set, perform the following steps: Based on the three-dimensional surface coordinates of each pixel in the initial raster sub-image, generate the coordinates of the raster center point and the raster surface normal vector. Based on a preset wall safety distance, the coordinates of the center point of the grid are translated along the direction of the normal vector of the grid surface to obtain the translation coordinates; Based on the preset safe altitude information, determine the UAV coordinates corresponding to the translation coordinates; A grid map is generated based on the initial grid map, the grid surface normal vector, and the UAV coordinates.

6. The method according to claim 1, characterized in that, The step of generating the three primary color ratio information based on the color value of each pixel included in the raster submap includes: For each pixel included in the raster submap, perform the following steps: The color value of the pixel is converted to obtain the three primary color information, wherein the three primary color information includes the cyan component, the magenta component and the yellow component; The three primary color information is normalized to obtain normalized three primary color information, wherein the normalized three primary color information includes a normalized cyan component, a normalized magenta component, and a normalized yellow component. Based on the determined normalized cyan component, normalized magenta component, and normalized yellow component, the proportion information of the three primary colors is generated.

7. The method according to claim 1, characterized in that, The painting drone includes a peristaltic pump and a ducted motor; and the method for controlling the painting drone to extract paint according to the three primary color ratio information included in the painting instruction for painting includes: According to the three primary color ratio information included in the spraying instruction, the peristaltic pump included in the spraying drone is controlled to extract and mix the three colors of paint; The ducted motor is controlled to spray out the mixed paint.

8. A drone painting control device, characterized in that, include: The scanning unit is configured to scan the area to be sprayed using a spraying drone to obtain a three-dimensional model of the area to be sprayed. The projection unit is configured to project a preset image to be sprayed onto the three-dimensional model to be sprayed to obtain a texture mapping image, wherein each pixel in the texture mapping image corresponds to a three-dimensional surface coordinate. A raster division unit is configured to perform raster division on the texture mapping image to obtain a raster sub-map set, wherein each raster map in the raster sub-map set corresponds to UAV coordinates; The generation unit is configured to generate primary color ratio information based on the color value of each pixel included in the grid sub-graph of the grid sub-graph set, and to generate a spraying command based on the primary color ratio information and the UAV coordinates corresponding to the grid sub-graph. The determining unit is configured to determine the sequence of spraying instructions corresponding to each generated spraying instruction; The control unit is configured to, for each spraying instruction in the spraying instruction sequence, control the spraying drone to fly to the drone coordinates corresponding to the spraying instruction, and control the spraying drone to extract paint according to the three primary color ratio information included in the spraying instruction for spraying.

9. An electronic device, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 7.

10. A computer-readable medium, characterized in that, It stores a computer program thereon, wherein the computer program, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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