A method, device, electronic equipment and storage medium for controlling unmanned aerial vehicle (UAV) operations.

Abstract

This invention discloses a method, device, electronic device, and storage medium for controlling unmanned aerial vehicle (UAV) operations. The method includes: rasterizing each segmented region of the target wall to be scanned by the UAV to obtain multiple target grids, based on the size of the scannable area at each hovering work point; determining the center point of each target grid as the UAV's hovering work point, and sorting the hovering work points of each segmented wall region using a parallel search algorithm to obtain the regional work path for the UAV to scan the corresponding segmented wall region; and controlling the UAV to scan the corresponding segmented wall region according to the regional work path. This invention enables efficient and accurate scanning of each segmented wall region of a target wall.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to a UAV operation control method, device, electronic equipment, and storage medium. Background Technology

[0002] When using drones to scan walls, the drone's operational path can be planned based on region coverage search. Region coverage search is a method that utilizes the spatial relationships between regions to improve search efficiency. Currently, drone full-coverage path planning algorithms include those based on adaptive fast expanding random trees, adaptive viewpoint sampling, genetic algorithms, and unsupervised learning neural networks. However, these algorithms have high training costs and computational time, making them unsuitable for non-high-precision drone full-coverage path planning. Summary of the Invention

[0003] This invention provides a method, device, electronic device, and storage medium for controlling unmanned aerial vehicle (UAV) operations, which can facilitate efficient and accurate scanning of various segmented wall areas of a target wall.

[0004] In a first aspect, embodiments of the present invention provide a method for controlling unmanned aerial vehicle (UAV) operations, comprising: performing rasterization processing on each segmented area of ​​the target wall to be scanned by the UAV at each hovering operation point to obtain multiple target rasteres based on the size of the scannable area when the UAV scans the operation at each hovering operation point;

[0005] The center point of each target grid is determined as the hovering operation point of the UAV, and the hovering operation points of each wall segmentation area are sorted using a parallel search algorithm to obtain the area operation path for the UAV to scan the corresponding wall segmentation area; and

[0006] The drone is controlled to scan the corresponding wall segmentation area according to the operation path of each area.

[0007] In a second aspect, embodiments of the present invention provide a drone operation control device, comprising:

[0008] The rasterization module is used to rasterize the various wall segments of the target wall to be scanned by the UAV based on the size of the scannable area when the UAV scans at each hovering work point, so as to obtain multiple target rasters.

[0009] The operation path acquisition module is used to determine the center point of each target grid as the hovering operation point of the UAV, and to sort the hovering operation points of each wall segmentation area using a parallel search algorithm to obtain the regional operation path for the UAV to perform scanning operations on the corresponding wall segmentation area; and

[0010] The scanning module is used to control the UAV to perform scanning operations on the corresponding wall segmentation areas according to the operation paths of each area.

[0011] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the unmanned aerial vehicle (UAV) operation control method as described in any of the embodiments of the present invention.

[0012] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the unmanned aerial vehicle (UAV) operation control method as described in any of the embodiments of the present invention.

[0013] This invention discloses a method, device, electronic equipment, and storage medium for controlling unmanned aerial vehicle (UAV) operations. By rasterizing the segmented areas of the target wall to be scanned by the UAV, the center points of each target raster are used as hovering operation points for the UAV. A parallel algorithm is then used to sort these hovering operation points across each segmented wall area. This achieves full-coverage path planning for each segmented wall area with high computational efficiency, low implementation difficulty, and minimal time cost. By controlling the UAV to scan the corresponding segmented wall areas according to the defined operation path, efficient and accurate scanning of each segmented wall area is achieved. Furthermore, different scanning operation plans can be executed for different segmented avoidance areas, thereby improving the efficiency of subsequent maintenance and other work, and effectively avoiding unnecessary personal injury and property damage. Attached Figure Description

[0014] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart illustrating the unmanned aerial vehicle (UAV) operation control method provided in an embodiment of the present invention;

[0016] Figure 2 This is a schematic diagram of the UAV scanning operation sequence in the UAV operation control method provided in this embodiment of the invention;

[0017] Figure 3 This is another flowchart illustrating the unmanned aerial vehicle (UAV) operation control method provided in this embodiment of the invention;

[0018] Figure 4 This is a schematic diagram of the camera scanning range and grid size in the UAV operation control method provided in this embodiment of the invention;

[0019] Figure 5 This is a schematic diagram of a target grid in the UAV operation control method provided in an embodiment of the present invention;

[0020] Figure 6 This is another flowchart illustrating the unmanned aerial vehicle (UAV) operation control method provided in this embodiment of the invention;

[0021] Figure 7 This is a schematic diagram of a drone operation control device provided in an embodiment of the present invention;

[0022] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0023] Large, enclosed spaces, such as boiler water-cooled walls, often have complex internal structures and are characterized by low light, high dust levels, and magnetic confinement, presenting significant challenges and weak feature characteristics in industrial settings. Drones can be used to enter the interior of these water-cooled walls for image acquisition and subsequent maintenance. A safe and trackable trajectory needs to be planned for the drone in each operation to achieve full coverage of the water-cooled wall surface being inspected. The drone's operational path can be planned based on region coverage search. Region coverage search is a method that utilizes the spatial relationships between regions to improve search efficiency. Currently, drone full-coverage path planning algorithms include those based on adaptive fast expanding random trees, adaptive viewpoint sampling, genetic algorithms, and unsupervised learning neural networks. However, these algorithms have high training and computational costs, making them unsuitable for non-high-precision drone full-coverage path planning.

[0024] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0025] Figure 1 This is a flowchart illustrating a drone operation control method provided in an embodiment of the present invention. This method can be executed by a drone operation control device provided in this embodiment, which can be implemented using software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device, such as a computer or server. The following embodiments will illustrate this using the integration of the device into an electronic device as an example. (Reference) Figure 1 The method may specifically include the following steps:

[0026] Step 101: Based on the scannable area size of the UAV at each hovering work point, rasterize each segmented area of ​​the target wall to be scanned by the UAV to obtain multiple target grids. This allows the center point of the target grid to be used as the hovering work point of the UAV, and the regional work path of the UAV for scanning operations in each segmented area of ​​the wall to be obtained based on the hovering work point.

[0027] Specifically, the above rasterization process can be performed on images based on wall segmentation regions.

[0028] Specifically, the target grid can be squares that are parallel to each other in both the horizontal and vertical directions.

[0029] In an optional specific embodiment of the present invention, the above-mentioned wall segmentation region includes multiple wall regions obtained by segmenting the target wall according to the structural characteristics of the target wall.

[0030] Specifically, the structural characteristics of the target wall can include its concave and convex features. For example, when the wall has protruding parts, the target wall can be divided with these protruding parts as boundaries to avoid excessive changes in the relative height of the planned UAV operation path to the wall, which would result in excessive energy consumption and reduced flight time.

[0031] Specifically, the structural features of the target wall can include non-scanning parts of the target wall, such as functional gaps on the wall. Dividing the target wall using these functional gaps as boundaries can prevent the drone from performing meaningless operations, improve operational efficiency, reduce energy consumption, and extend battery life.

[0032] Optionally, the aforementioned wall segmentation area may also include a wall segmentation area obtained by segmenting the target wall according to the wall inspection and scanning plan.

[0033] Specifically, different areas of the target wall may have different wear factors, resulting in varying probabilities of damage. Therefore, different inspection and scanning plans need to be developed for different areas. Thus, segmenting the target wall according to the inspection and scanning plan to determine the segmented areas and planning the UAV's regional operation path allows for targeted inspection and scanning of the target wall, improving operational efficiency.

[0034] Step 102: The center point of each target grid is determined as the hovering operation point of the UAV. A parallel search algorithm is then used to sort the hovering operation points of each wall segmentation area, obtaining the regional operation path for the UAV to scan the corresponding wall segmentation area. This method achieves full-coverage path planning for each wall segmentation area with high computational efficiency, low implementation difficulty, and minimal time cost. It also facilitates efficient and precise control of the UAV to scan the corresponding wall segmentation area according to the regional operation path.

[0035] In an optional specific embodiment of the present invention, a parallel search algorithm is used to sort the hovering work points in each wall segmentation area. This includes: sorting the hovering work points in each wall segmentation area using a parallel search algorithm such that adjacent hovering work points in the horizontal direction have adjacent sequence numbers, and the hovering work point with the largest sequence number in each horizontal row is adjacent to the hovering work point with the smallest sequence number in the next horizontal row. This allows the UAV to select the closest grid point to its current position in the two end grids of the next row as the starting scanning point during the scanning process, sequentially adding work points to the next row from left to right or right to left to complete the row scan, until the UAV completes the scanning of the entire wall segmentation area vertically from top to bottom or bottom to top. Figure 2 As shown, this can reduce the vertical height variation of the drone and reduce energy consumption.

[0036] Optionally, a parallel search algorithm can be used to sort the hovering work points in each wall segmentation area, ensuring that adjacent hovering work points in the vertical direction have adjacent indices, and that the hovering work point with the largest index in each vertical column is adjacent to the hovering work point with the smallest index in the next vertical column. This allows the UAV to select the closest grid point to its current position from the two end grids of the next column as the starting scan point during the scanning process, sequentially adding work points to the next row from top to bottom or bottom to top to complete the column scan, until the UAV completes the scanning of the entire wall segmentation area from left to right or right to left in the horizontal direction.

[0037] Step 103: Control the drone to scan the corresponding wall segmentation areas according to the operation paths of each area. Based on steps 101-102, and using the area operation paths obtained by full-coverage path planning for each wall segmentation area with high computational efficiency, low implementation difficulty, and low time cost, the drone can perform scanning operations on the corresponding wall segmentation areas. This allows for efficient and accurate scanning of each segmented wall area, and enables the execution of different scanning operation plans for different segmented avoidance areas, thereby improving the efficiency of subsequent avoidance maintenance and other work, and effectively avoiding unnecessary personal injury and property damage.

[0038] In an optional specific embodiment of the present invention, the process of controlling the UAV to scan the corresponding wall segmentation area according to the operation path of each area includes: controlling the UAV to hover at each hovering operation point in sequence according to the sequence number of each hovering operation point in each wall segmentation area and to perform image scanning and acquisition on the corresponding wall area to obtain the wall image corresponding to each hovering operation point.

[0039] In an optional specific embodiment of the present invention, the UAV operation control method of the present invention further includes: before controlling the UAV to hover at each hovering operation point according to the sequence number of each hovering operation point in each wall segmentation area and to perform image scanning and acquisition of the corresponding wall area to obtain the wall image corresponding to each hovering operation point, confirming the operation mode of the UAV performing image scanning and acquisition of the corresponding wall area at each hovering operation point.

[0040] In this specific embodiment, controlling the drone to perform image scanning and acquisition of the corresponding wall area includes: controlling the drone to perform image scanning and acquisition of the corresponding wall area according to the confirmed operation mode.

[0041] Optionally, after completing the scanning operation of the previous hovering work point and obtaining the image of the corresponding wall area, the operation mode of the next hovering work point is confirmed based on the image of the corresponding wall area of ​​the previous hovering work point. If the operation mode is the same as the operation mode of the previous hovering work point, the original operation mode is maintained and the corresponding wall area is scanned at the next hovering work point. The operation mode is then switched to the mode of the next hovering work point, and then the corresponding wall area is scanned at the next hovering work point.

[0042] Specifically, the above-mentioned operation modes include automatic operation mode and manual operation mode. The operation mode of each hovering operation point is confirmed, and the drone is controlled to perform scanning operations according to the confirmed operation mode, which can help improve the accuracy of scanning operations.

[0043] Optionally, before controlling the drone to hover at each hovering work point according to the sequence number of each wall segmentation area and to scan and collect the wall image corresponding to each hovering work point, the remaining battery power of the drone is confirmed, and if the remaining battery power is less than the preset battery power threshold, the drone is controlled to return to home.

[0044] Optionally, the drone can be controlled to return to its home position when the previous hovering work point is the last work point.

[0045] The following describes another embodiment of the UAV operation control method, such as... Figure 3 As shown, that is Figure 1 Step 101 may include the following steps:

[0046] Step 1011: Calculate the size of the scannable area of ​​the drone at each hovering work point based on the field of view of the camera on the drone and the distance between the drone and the target wall during operation.

[0047] Step 1012: Calculate the rasterization specifications based on the size of the scannable area when the UAV scans at each hovering work point and the size of the repeated scan area when the UAV scans at two adjacent hovering work points.

[0048] Specifically, in order to ensure that there are no missed scans in the wall area, it is necessary to set a certain area for repeated scanning when scanning between two adjacent hovering work points.

[0049] Specifically, the repeat scan height Cov is set in the vertical direction. y For example, Figure 4 As shown, Fov y d represents the camera's field of view, h represents the distance between the drone and the wall during operation, δh represents the drone's scannable vertical height, and δh represents the vertical height of the grid.

[0050] Optionally, the scannable vertical height h of the aforementioned UAV can be calculated using the following formula:

[0051]

[0052] Optionally, the vertical height δh of the above grid can be calculated using the following formula:

[0053]

[0054] Step 1013: Based on the maximum dimensions of each wall segmentation region in the vertical and horizontal directions, and the rasterization specifications, rasterize each wall segmentation region and the adjacent wall regions of each wall segmentation region within the corresponding maximum dimensions to obtain multiple wall grids corresponding to each wall segmentation region.

[0055] Step 1014: Determine the target grid as the grid that overlaps with the corresponding wall segmentation area among the multiple wall grids.

[0056] Specifically, such as Figure 5 As shown in the figure, the black part is the convex polygon formed by the wall segmentation area, and the grid surrounded by the thick line is the target grid mentioned above.

[0057] The embodiments of the present invention can help ensure that all areas of the wall segmentation area during the real-time scanning operation of the UAV can be scanned, avoiding safety hazards caused by missed scans.

[0058] The following describes another embodiment of the UAV operation control method, such as... Figure 6 As shown, it may include the following steps:

[0059] Step 601: Based on the size of the scannable area when the UAV scans at each hovering work point, perform rasterization processing on each segmented area of ​​the target wall to be scanned by the UAV to obtain multiple target gratings.

[0060] Step 602: The center point of each target grid is determined as the hovering operation point of the UAV, and the hovering operation points of each wall segmentation area are sorted by the parallel search algorithm to obtain the area operation path of the UAV to perform scanning operation on the corresponding wall segmentation area.

[0061] Step 603: The center point of each target grid is determined as the hovering operation point of the UAV, and the hovering operation points of each wall segmentation area are sorted by the parallel search algorithm to obtain the area operation path of the UAV to perform scanning operation on the corresponding wall segmentation area.

[0062] Specifically, the order of connecting each operation path can be determined based on the positions of the first and last hovering operation points of each operation path, while ensuring the shortest possible flight distance for the UAV.

[0063] Step 604: Based on the order of the operation paths of each area in the wall operation path, control the UAV to perform scanning operations on the corresponding wall segmentation areas according to the operation paths of each area.

[0064] Specifically, depending on the drone's range, the drone can be controlled to scan the corresponding wall segmentation area sequentially according to the order of the operation paths of each area on the wall operation path after one takeoff. Alternatively, the drone can be controlled to take off multiple times sequentially according to the order of the operation paths of each area on the wall operation path to scan the corresponding wall segmentation area.

[0065] The embodiments of the present invention are applicable to inspection and scanning plans that complete the inspection and scanning of target walls in one go, and can complete all scanning operations of the target walls, eliminating safety hazards caused by missed scanning of walls.

[0066] Figure 7 This is a structural diagram of a drone operation control device provided in an embodiment of the present invention. This device is suitable for executing the drone operation control method provided in an embodiment of the present invention. Figure 7 As shown, the device may specifically include:

[0067] The rasterization module 701 is used to rasterize each segmented area of ​​the target wall to be scanned by the UAV, based on the size of the scannable area at each hovering work point, to obtain multiple target grids. This allows the center point of the target grid to be used as the UAV's hovering work point, and the area work path for the UAV to perform scanning operations in each segmented wall area to be obtained based on the hovering work point.

[0068] Optionally, the wall segmentation region includes dividing the target wall into multiple wall regions based on the structural characteristics of the target wall.

[0069] Optionally, the above-mentioned rasterization module 701 can be specifically used to calculate the size of the scannable area of ​​the UAV when it is scanning at each hovering operation point based on the field of view of the camera on the UAV and the distance between the UAV and the target wall when the UAV is operating, and to calculate the rasterization specification based on the size of the scannable area of ​​the UAV when it is scanning at each hovering operation point and the size of the repeated scanning area of ​​the UAV when scanning at two adjacent hovering operation points.

[0070] Based on the maximum dimensions of each wall segmentation region in the vertical and horizontal directions, and the rasterization specifications, each wall segmentation region and its adjacent wall regions within the corresponding maximum dimensions are rasterized, resulting in multiple wall grids corresponding to each wall segmentation region; and

[0071] The grid cells that overlap with the corresponding wall segmentation regions among multiple wall grid cells are identified as the target grid cells.

[0072] The operation path acquisition module 702 is used to determine the center point of each target grid as the hovering operation point of the UAV, and to sort the hovering operation points of each wall segmentation area using a parallel search algorithm to obtain the area operation path for the UAV to scan the corresponding wall segmentation area. This module can achieve full-coverage path planning for each wall segmentation area with high computational efficiency, low implementation difficulty, and low time cost, and facilitates efficient and accurate control of the UAV to scan the corresponding wall segmentation area according to the operation path.

[0073] Optionally, the above-mentioned operation path acquisition module 702 can be specifically used to sort the hovering operation points of each wall segmentation area using a parallel search algorithm so that the serial numbers of adjacent hovering operation points in the horizontal direction are adjacent, and the hovering operation point with the largest serial number in each horizontal row is adjacent to the hovering operation point with the smallest serial number in the next horizontal row.

[0074] The scanning module 703 controls the drone to scan the corresponding wall segmentation areas according to the operation paths of each area. Combined with modules 701-702, it can perform area operation paths based on full-coverage path planning for each wall segmentation area with high computational efficiency, low implementation difficulty, and minimal time cost. This allows for efficient and accurate scanning of each segmented wall area, and enables the execution of different scanning plans for different segmented areas, thereby improving the efficiency of subsequent maintenance and other work, and effectively avoiding unnecessary personal injury and property damage.

[0075] Optionally, the scanning module 703 can be specifically used to control the drone to hover at each hovering work point according to the sequence number of each hovering work point in each wall segmentation area and to perform image scanning and acquisition on the corresponding wall area to obtain the wall image corresponding to each hovering work point.

[0076] Optionally, the scanning module 703 described above can also be specifically used to, before controlling the drone to hover at each hovering work point according to the sequence number of each hovering work point in each wall segmentation area and to perform image scanning and acquisition on the corresponding wall area to obtain the wall image corresponding to each hovering work point.

[0077] The operation mode of the UAV scanning and collecting images of the corresponding wall area at each hovering operation point was confirmed, and the UAV was controlled to scan and collect images of the corresponding wall area according to the confirmed operation mode.

[0078] In an optional embodiment of the present invention, the human-machine operation control device of the present invention further includes a wall operation path acquisition module, which is used to connect the operation paths of each area end to end to obtain the wall operation path for the UAV to perform scanning operation on the target wall.

[0079] Optionally, the aforementioned operation path acquisition module 702 can be specifically used to control the UAV to perform scanning operations on the corresponding wall segmentation areas according to the order of the operation paths of each area in the wall operation path.

[0080] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is merely an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0081] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the UAV operation control method provided in any of the above embodiments.

[0082] This invention also provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the UAV operation control method provided in any of the above embodiments.

[0083] The following is for reference. Figure 8 It shows a schematic diagram of the structure of a computer system 800 suitable for implementing an electronic device according to embodiments of the present invention. Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0084] like Figure 8 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 802 or programs loaded from storage section 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the system 800. The CPU 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0085] The following components are connected to I / O interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to I / O interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 810 as needed so that computer programs read from it can be installed into storage section 808 as needed.

[0086] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention 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 section 809, and / or installed from removable medium 811. When the computer program is executed by central processing unit (CPU) 801, it performs the functions defined above in the system of this invention.

[0087] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can 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 this invention, a computer-readable storage medium can 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 this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, 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: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0088] 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 the present invention. 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 a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may 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.

[0089] The modules and / or units described in the embodiments of the present invention can be implemented in software or hardware. The described modules and / or units can also be housed in a processor; for example, a processor can be described as including a rasterization module, a job path acquisition module, and a scan job module. The names of these modules do not necessarily limit the module itself.

[0090] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, enable the following implementation: based on the size of the scannable area of ​​the UAV at each hovering work point, rasterize each segmented region of the target wall to be scanned by the UAV to obtain multiple target grids; determine the center point of each target grid as the hovering work point of the UAV, and sort the hovering work points of each segmented region using a parallel search algorithm to obtain the regional work path for the UAV to scan the corresponding segmented region; and control the UAV to scan the corresponding segmented region according to the regional work path.

[0091] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for controlling unmanned aerial vehicle (UAV) operations, characterized in that, include: Based on the size of the scannable area when the UAV scans at each hovering work point, the wall segmentation areas of the target wall to be scanned by the UAV are rasterized to obtain multiple target rasteres. The center point of each target grid is determined as the hovering operation point of the UAV, and the hovering operation points of each wall segmentation area are sorted by a parallel search algorithm to obtain the area operation path of the UAV for scanning the corresponding wall segmentation area. as well as The drone is controlled to scan the corresponding wall segmentation area according to the operation path of each area; Before controlling the UAV to scan the corresponding wall segmentation area according to the operation path of each area, the method further includes: connecting the operation paths of each area end to end to obtain the wall operation path for the UAV to scan the target wall. The step of controlling the drone to scan the corresponding wall segmentation area according to the operation path of each area includes: controlling the drone to scan the corresponding wall segmentation area according to the order of the operation paths of each area in the wall operation path; The wall segmentation region includes multiple wall regions obtained by segmenting the target wall according to the structural characteristics of the target wall.

2. The UAV operation control method according to claim 1, wherein the step of rasterizing each segmented area of ​​the target wall to be scanned by the UAV to obtain multiple target grids based on the size of the scannable area when the UAV scans at each hovering operation point, includes: Based on the field of view of the camera mounted on the UAV, the distance between the UAV and the target wall during operation is used to calculate the size of the scannable area of ​​the UAV at each hovering operation point. The rasterization specification is calculated based on the size of the scannable area of ​​the UAV when it scans at each hovering work point and the size of the repeated scan area of ​​the UAV when it scans at two adjacent hovering work points. Based on the maximum dimensions of each wall segmentation region in the vertical and horizontal directions, and the rasterization specifications, each wall segmentation region and the adjacent wall regions of each wall segmentation region within the corresponding maximum dimensions are rasterized to obtain multiple wall grids corresponding to each wall segmentation region. as well as The grid cells among the plurality of wall grid cells that have overlapping areas with the corresponding wall segmentation regions are determined as the target grid cells.

3. The UAV operation control method according to claim 1, characterized in that, The process of sorting the hovering work points in each of the wall segmentation areas using a parallel search algorithm includes: The parallel search algorithm is used to sort the hovering work points in each wall segmentation area so that the serial numbers of adjacent hovering work points in the horizontal direction are adjacent, and the hovering work point with the largest serial number in each horizontal row is adjacent to the hovering work point with the smallest serial number in the next horizontal row.

4. The UAV operation control method according to claim 1, characterized in that, The control of the drone to scan the corresponding wall segmentation area according to the operation path of each area includes: The drone is controlled to hover at each hovering work point according to the sequence number of each wall segmentation area and to perform image scanning and acquisition on the corresponding wall area to obtain the wall image corresponding to each hovering work point.

5. The UAV operation control method according to claim 4, characterized in that, Also includes: Before the drone is controlled to hover at each hovering work point according to the sequence number of each wall segmentation area and to scan and acquire the wall image corresponding to each hovering work point, the drone is controlled to hover at each hovering work point in sequence and to acquire the wall image corresponding to each hovering work point. The operation mode of the UAV performing image scanning and acquisition of the corresponding wall area at each hovering operation point was confirmed. The control of the drone to perform image scanning and acquisition of the corresponding wall area includes: The drone is controlled to perform image scanning and acquisition on the corresponding wall area according to the confirmed operation mode.

6. A drone operation control device, used to execute the drone operation control method according to any one of claims 1 to 5, characterized in that, include: The rasterization module is used to rasterize the various wall segments of the target wall to be scanned by the UAV based on the size of the scannable area when the UAV scans at each hovering work point, so as to obtain multiple target rasters. The operation path acquisition module is used to determine the center point of each target grid as the hovering operation point of the UAV, and to sort the hovering operation points of each wall segmentation area using a parallel search algorithm to obtain the regional operation path of the UAV for scanning the corresponding wall segmentation area. as well as The scanning module is used to control the UAV to perform scanning operations on the corresponding wall segmentation areas according to the operation paths of each area.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the UAV operation control method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the UAV operation control method as described in any one of claims 1 to 5.

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