Unmanned aerial vehicle cluster collaborative inspection method and system

Abstract

The invention discloses an unmanned aerial vehicle cluster collaborative inspection method and system. The method comprises the following steps: acquiring a target inspection area and an unmanned aerial vehicle inspection type of the target inspection area; determining a target parking point of the unmanned aerial vehicle in each target inspection area; determining a target unmanned aerial vehicle group of the next round of inspection task through the target parking point; and sending the next round of inspection task to the unmanned aerial vehicle corresponding to the target unmanned aerial vehicle group, and triggering the unmanned aerial vehicle to perform collaborative inspection according to the next round of inspection task. According to the invention, the target parking point of each unmanned aerial vehicle in the target inspection area is determined, then the target unmanned aerial vehicle group of the next inspection task is determined, and the next inspection task is sent to the unmanned aerial vehicle corresponding to the target unmanned aerial vehicle group, so that a new unmanned aerial vehicle group is screened in the original target inspection area to carry out collaborative inspection of the next inspection task. The next round of cooperative inspection of the two unmanned aerial vehicles screened based on the target parking point is more convenient and faster, and the efficiency of executing the next round of cooperative inspection task can be improved to a certain extent.

Description

Technical Field

[0001] The present invention relates to the technical field of drone cluster inspection, and in particular to a drone cluster collaborative inspection method and system. Background Art

[0002] With the advancement of science and technology and the development of drone technology, drones have been widely used in many fields. Drone cluster inspection, as an efficient and flexible inspection method, has received more and more attention in recent years. By using a cluster of multiple drones for inspection, it can not only cover a larger inspection area, but also improve the accuracy and efficiency of the inspection, reduce labor costs, and reduce inspection risks.

[0003] However, there are some urgent problems to be solved in the existing drone cluster inspection mode. The traditional drone cluster inspection method usually involves using an inspection vehicle to carry the drone to a designated parking point, where the drone takes off to perform the inspection task and returns to the parking point after completion. The inspection vehicle then transports the drone to the next parking point to continue to perform a new inspection task. Although this method can meet the inspection needs to a certain extent, it also brings many challenges. First, since the drone must travel back and forth between each parking point, this not only increases the flight time and energy consumption, but also may lead to a decrease in inspection efficiency. Secondly, when the time for each drone in the cluster to complete the inspection task is inconsistent, those drones that complete the task earlier must wait for other drones until all drones complete the task and regroup at a unified gathering point before starting the next round of task allocation. In addition, the existing drone cluster inspection system has limited response capabilities to emergencies. For example, when encountering urgent inspection needs or sudden changes in environmental conditions, it is difficult to quickly adjust the inspection plan, which may affect the success rate and safety of the inspection task.

[0004] In response to the above problems, an improved UAV cluster collaborative inspection method is urgently needed, which aims to improve the overall efficiency and flexibility of UAV clusters in performing inspection tasks by optimizing the communication coordination mechanism, task allocation strategy and dynamic adjustment of inspection paths between UAVs. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a drone cluster collaborative inspection method and system, which aims to improve the overall efficiency and flexibility of the drone cluster in performing inspection tasks by optimizing the communication coordination mechanism, task allocation strategy and dynamic adjustment of inspection paths between drones.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for collaborative inspection of drone clusters, including: obtaining a target inspection area and the drone inspection type of the target inspection area; determining a target parking point for drones in each target inspection area according to the drone inspection type; determining a target drone group for the next round of inspection tasks through the target parking point; sending the next round of inspection tasks to the drones corresponding to the target drone group, and triggering the drones to perform collaborative inspections according to the next round of inspection tasks.

[0009] As a preferred solution of the drone cluster collaborative inspection method described in the present invention, the acquisition of the target inspection area and the drone inspection type of the target inspection area includes:

[0010] Obtain the position coordinates of each drone in the drone cluster, match the position coordinates of each drone with the coordinate range corresponding to the target inspection area, and determine the drones located in the target inspection area;

[0011] Send a type request instruction to the drone in the target inspection area, triggering the drone in the target inspection area to feedback the inspection type.

[0012] As a preferred solution of the drone cluster collaborative inspection method of the present invention, the step of determining the target parking point of the drones in each target inspection area includes:

[0013] Using a preset parking point database to perform a table lookup operation on the inspection type of the drone to obtain a target parking point corresponding to each inspection type;

[0014] The target parking point corresponding to each of the found inspection types is determined as the target parking point of the corresponding drone, wherein the corresponding relationship between the inspection type and the target parking point is stored in the parking point database.

[0015] As a preferred solution of the drone cluster collaborative inspection method of the present invention, the target drone group for determining the next round of inspection tasks includes:

[0016] Obtaining the inspection task corresponding to the target parking point, that is, using the target parking point to perform a table lookup operation in a preset first data table, finding the inspection route corresponding to the target parking point, and determining the found inspection route as the current inspection route of the corresponding drone, wherein the preset first data table stores the correspondence between the target parking point and the inspection route;

[0017] Determine the next round of inspection tasks according to the inspection tasks, that is, use the current inspection task to perform a table lookup operation in a preset second data table to find out the next inspection task corresponding to the current inspection task, and the preset second data table stores the corresponding relationship between the current inspection task and the next inspection task;

[0018] For the target inspection area, two drones whose target parking points are within a preset range are determined as the target drone group for the next round of inspection tasks.

[0019] As a preferred scheme of the drone cluster collaborative inspection method described in the present invention, wherein: the distance between the target parking points is within a preset range, which means that the distance between the target parking points of two drones is zero, that is, the target parking points of the two drones are the same, or the distance between the target parking points of the two drones is less than a preset threshold.

[0020] As a preferred solution of the drone cluster collaborative inspection method of the present invention, the sending of the next round of inspection tasks to the drones corresponding to the target drone group includes:

[0021] When the drones corresponding to the target drone group complete the current inspection task and return to their respective target parking points, the next inspection task is sent to the drones corresponding to the target drone group.

[0022] As a preferred solution of the drone cluster collaborative inspection method of the present invention, wherein: triggering the drones to perform collaborative inspection according to the next round of inspection tasks includes:

[0023] Divide the inspection route into two inspection sub-routes;

[0024] The two inspection sub-routes are sent to two drones in the target drone group respectively, triggering the two drones in the drone group to perform inspections according to the two inspection sub-routes respectively;

[0025] By sending different inspection routes to the two drones corresponding to the target drone group, a new drone group can be selected within the original target inspection area to perform collaborative inspection for the next inspection task.

[0026] In a second aspect, the present invention provides a drone cluster collaborative inspection system, comprising:

[0027] The area acquisition module is used to obtain the target inspection area and the drone inspection type of the target inspection area;

[0028] A parking point determination module, used to determine the target parking point of the drone in each target inspection area according to the drone inspection type;

[0029] The collaborative inspection module is used to determine the target drone group for the next round of inspection tasks through the target parking point, send the next round of inspection tasks to the drones corresponding to the target drone group, and trigger the drones to perform collaborative inspections according to the next round of inspection tasks.

[0030] In a third aspect, the present invention provides an electronic device, comprising:

[0031] Memory and processor;

[0032] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the drone cluster collaborative inspection method are implemented.

[0033] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the drone cluster collaborative inspection method.

[0034] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a method and system for collaborative inspection of drone clusters, which can determine the target parking point of each drone in the target inspection area according to different inspection types by acquiring the target inspection area and determining that there are multiple drones in the target inspection area, and at the same time acquiring the inspection type of the drones in the target inspection area, so as to facilitate the determination of the target drone group for the next inspection task, and by sending the next inspection task to the drone corresponding to the target drone group, it is possible to select a new drone group in the original target inspection area to perform collaborative inspection for the next inspection task. Since the drones will return to the parking point after the inspection, it is more convenient and quicker for the two drones selected based on the target parking point to perform the next round of collaborative inspection, which can improve the efficiency of executing the next round of collaborative inspection tasks to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0036] Figure 1 The figure is a logical diagram of the overall process of the UAV cluster collaborative inspection method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0038] Example 1

[0039] Reference Figure 1 As an embodiment of the present invention, a method for coordinated inspection of a drone cluster is provided, which improves the overall efficiency and flexibility of the drone cluster in performing inspection tasks by optimizing the communication coordination mechanism, task allocation strategy and dynamic adjustment of inspection paths between drones. Figure 1 The specific steps shown include:

[0040] S100: Obtain the target inspection area and the drone inspection type of the target inspection area;

[0041] S200: Determine a target parking point for the drone in each target inspection area according to the drone inspection type;

[0042] S300: Determine the target drone group for the next round of inspection task through the target parking point;

[0043] S400: Send the next round of inspection tasks to the drones corresponding to the target drone group, and trigger the drones to perform collaborative inspections according to the next round of inspection tasks.

[0044] It should be noted that the present invention provides a method and system for collaborative inspection of drone clusters. By acquiring a target inspection area and determining that there are multiple drones in the target inspection area, and acquiring the inspection type of the drones in the target inspection area at the same time, the target parking point of each drone in the target inspection area can be determined according to different inspection types, so that the target drone group for the next inspection task can be determined easily. By sending the next inspection task to the drone corresponding to the target drone group, a new drone group can be selected in the original target inspection area to perform collaborative inspection of the next inspection task. Since the drones will return to the parking point after the inspection, it is more convenient and quicker for the two drones selected based on the target parking point to perform the next round of collaborative inspection, which can improve the efficiency of executing the next round of collaborative inspection tasks to a certain extent.

[0045] In the embodiment of the present application, the above step S100 includes the following sub-steps A1-A2;

[0046] In A1: the server obtains the target inspection area, and there are multiple drones in the target inspection area;

[0047] In A2: the server determines the drones located in the target inspection area, and obtains the inspection type of the drones in the target inspection area;

[0048] In a feasible implementation, the position coordinates of each drone in the drone cluster are obtained, and the position coordinates of each drone are matched with the coordinate range corresponding to the target inspection area to determine the drone located in the target inspection area; when the position coordinates of the drone are within the coordinate range corresponding to the target inspection area, the drone is determined to be a drone in the target inspection area;

[0049] In a feasible implementation, a type request instruction is sent to the drone in the target inspection area, triggering the drone in the target inspection area to feedback the inspection type, for example, the inspection type includes equipment fault inspection, power line inspection, etc.

[0050] It should be noted that the above step S100 can obtain the target inspection area and the drone inspection type of the target inspection area, providing clear guidance and basis for the subsequent inspection task planning and execution. By clarifying the target inspection area and inspection type, the system can allocate resources more accurately, select appropriate drone models and configurations, ensure the efficiency and pertinence of the inspection tasks, and help identify and prepare special equipment or technologies that may be needed in advance, thereby improving the accuracy and reliability of the inspection, and ensuring that the inspection tasks can proceed smoothly and achieve the expected results.

[0051] In the embodiment of the present application, the above step S200 determines the target parking point of the drone in each target inspection area according to the drone inspection type, including:

[0052] Use the preset parking point database to look up the inspection types of drones and obtain the target parking points corresponding to each inspection type;

[0053] The target parking point corresponding to each patrol type found out is determined as the target parking point of the corresponding drone, wherein the corresponding relationship between the patrol type and the target parking point is stored in the parking point database.

[0054] It should be noted that the above step S200 can not only ensure that the drone is in the optimal starting position before the inspection task begins, but also effectively reduce the idle time and energy consumption of the drone, thereby improving the inspection efficiency. By rationally planning the target parking point, the system can better adapt to different types of inspection tasks, ensuring that the drone can respond quickly and be flexibly dispatched when performing tasks, thereby improving the operating efficiency and reliability of the entire inspection system.

[0055] In the embodiment of the present application, the above step S300 determines the target drone group for the next round of inspection task through the target parking point, and the target drone group includes at least two drones, and specifically includes the following sub-steps C1 to C3:

[0056] In C1: obtain the inspection task corresponding to the target parking point;

[0057] In C2: the next round of inspection tasks is determined according to the inspection tasks corresponding to the target parking point;

[0058] In C3: for the target inspection area, two drones whose distances between the target parking points are within a preset range are determined as the target drone group for the next round of inspection mission;

[0059] In a feasible implementation, the inspection task corresponding to the target parking point is obtained, that is, a table lookup operation is performed in a preset first data table using the target parking point to find out the inspection route corresponding to the target parking point, and the found inspection route is determined as the current inspection route of the corresponding drone, wherein the preset first data table stores the correspondence between the target parking point and the inspection route;

[0060] In a feasible implementation, the next round of inspection tasks is determined based on the inspection tasks, that is, the current inspection task is used to perform a table lookup operation in a preset second data table to find out the next inspection task corresponding to the current inspection task. The preset second data table stores the correspondence between the current inspection task and the next inspection task; for example, the next inspection task includes the next inspection route, and the second data table stores the next inspection route corresponding to the current inspection route.

[0061] In a feasible implementation, the distance between the target parking points of the two drones is within a preset range, which means that the distance between the target parking points of the two drones is zero, that is, the target parking points of the two drones are the same. Alternatively, the distance between the target parking points of the two drones is within a preset range, which means that the distance between the target parking points of the two drones is less than a preset threshold.

[0062] It should be noted that the above step S300 can ensure that the task allocation of each drone group is more scientific and reasonable, avoid waste of resources and repeated inspections, and improve the execution efficiency and coordination of inspection tasks. At the same time, the drone group selection based on the target parking point can also ensure that the drone reaches the inspection starting point in the shortest time, reduce waiting time, and improve the response speed and flexibility of the overall inspection system, so as to better adapt to complex and changing inspection needs.

[0063] In an embodiment of the present application, the above-mentioned step S400 sends the next round of inspection tasks to the drones corresponding to the target drone group, and triggers the drones to perform collaborative inspections according to the next round of inspection tasks, including: when the drones corresponding to the target drone group complete the current inspection tasks and return to their respective target parking points, the next inspection task is sent to the drones corresponding to the target drone group.

[0064] In a feasible implementation, triggering the drones to perform collaborative inspections according to the next round of inspection tasks includes: dividing the inspection route into two inspection sub-routes; sending the two inspection sub-routes to two drones in the target drone group respectively, triggering the two drones in the drone group to perform inspections according to the two inspection sub-routes respectively; and by sending different inspection routes to the two drones corresponding to the target drone group respectively, a new drone group is selected within the original target inspection area to perform collaborative inspections for the next inspection task.

[0065] It should be noted that the above step S400 can not only ensure the timely issuance and execution of tasks, but also realize efficient collaboration and resource optimization between drones, and improve the quality and efficiency of inspection tasks. At the same time, this automated task distribution and execution mechanism reduces the necessity of human intervention, reduces the risk of operational errors, ensures the continuity and stability of the inspection process, and thus better adapts to complex and changing inspection needs.

[0066] For example, in the process of using drones to inspect the transmission line, when there are multiple drones inspecting the set area, the set area is determined as the target inspection area. Then, the position coordinates of each drone in the drone cluster are obtained. And the drones whose position coordinates belong to the coordinate range corresponding to the target inspection area are determined as drones located in the target inspection area. For example, drone A, drone B and drone C are located in the target inspection area. The server sends type requests to drone A, drone B and drone C respectively. Drone A, drone B and drone C respectively feedback their respective inspection types to the server. The server finds the target parking points corresponding to each drone in the parking point database according to each inspection type. For example, the inspection type of drone A is power line inspection, corresponding to the target parking point A'. The inspection type of drone B is power line inspection, corresponding to the target parking point A'. The inspection type of drone C is equipment fault inspection, corresponding to the target parking point B'. The server finds the current inspection route in the first data table according to each target parking point. Then find the next inspection route in the second data table according to the current inspection route. The target parking points of drone A and drone B are both target parking points A'. Therefore, drone A and drone B are determined as the target drone group for the next inspection task. The server divides the next inspection route into two inspection sub-routes, for example, inspection sub-route 1 and inspection sub-route 2. When drone A and drone B complete the current inspection route and return to the target parking point A', the two inspection sub-routes are sent to drone A and drone B respectively, for example, inspection sub-route 1 is sent to drone A, and inspection sub-route 2 is sent to drone B. Drone A and drone B are triggered to perform inspections according to inspection sub-route 1 and inspection sub-route 2 respectively.

[0067] The above is a schematic scheme of a drone cluster collaborative inspection method of this embodiment. It should be noted that the technical scheme of the drone cluster collaborative inspection system and the technical scheme of the drone cluster collaborative inspection method described above belong to the same concept. For details not described in detail in the technical scheme of the drone cluster collaborative inspection system in this embodiment, please refer to the description of the technical scheme of the drone cluster collaborative inspection method described above.

[0068] This embodiment also provides a drone cluster collaborative inspection system, including:

[0069] The area acquisition module is used to obtain the target inspection area and the drone inspection type of the target inspection area;

[0070] The parking point determination module is used to determine the target parking point of the drone in each target inspection area according to the drone inspection type;

[0071] The collaborative inspection module is used to determine the target drone group for the next round of inspection tasks through the target parking point, send the next round of inspection tasks to the drones corresponding to the target drone group, and trigger the drones to perform collaborative inspections according to the next round of inspection tasks.

[0072] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0073] This embodiment also provides an electronic device, which includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for collaborative inspection of drone clusters is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0074] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method proposed in the above embodiment is implemented.

[0075] The storage medium proposed in this embodiment and the method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0076] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0077] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0078] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0079] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0082] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0083] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A drone cluster collaborative inspection method, characterized in that: include: Obtain the target inspection area and the drone inspection type of the target inspection area; Determine the target parking point of the drone in each target inspection area according to the drone inspection type; Determine the target drone group for the next round of inspection task through the target parking point; Send the next round of inspection tasks to the drones corresponding to the target drone group, and trigger the drones to perform collaborative inspections according to the next round of inspection tasks.

2. The drone cluster collaborative inspection method according to claim 1, characterized in that: The acquisition of the target inspection area and the drone inspection type of the target inspection area includes: Obtain the position coordinates of each drone in the drone cluster, match the position coordinates of each drone with the coordinate range corresponding to the target inspection area, and determine the drones located in the target inspection area; Send a type request instruction to the drone in the target inspection area, triggering the drone in the target inspection area to feedback the inspection type.

3. The drone cluster collaborative inspection method according to claim 2, characterized in that: Determining the target parking point of the drone in each target inspection area includes: Using a preset parking point database to perform a table lookup operation on the inspection type of the drone to obtain a target parking point corresponding to each inspection type; The target parking point corresponding to each of the found inspection types is determined as the target parking point of the corresponding drone, wherein the corresponding relationship between the inspection type and the target parking point is stored in the parking point database.

4. The drone cluster collaborative inspection method according to claim 3, characterized in that: The target drone group for determining the next round of inspection tasks includes: Obtaining the inspection task corresponding to the target parking point, that is, using the target parking point to perform a table lookup operation in a preset first data table, finding the inspection route corresponding to the target parking point, and determining the found inspection route as the current inspection route of the corresponding drone, wherein the preset first data table stores the correspondence between the target parking point and the inspection route; Determine the next round of inspection tasks according to the inspection tasks, that is, use the current inspection task to perform a table lookup operation in a preset second data table to find out the next inspection task corresponding to the current inspection task, and the preset second data table stores the corresponding relationship between the current inspection task and the next inspection task; For the target inspection area, two drones whose target parking points are within a preset range are determined as the target drone group for the next round of inspection tasks.

5. The drone cluster collaborative inspection method according to claim 4, characterized in that: The distance between the target parking points is within the preset range, which means that the distance between the target parking points of the two UAVs is zero, that is, the target parking points of the two UAVs are the same, or the distance between the target parking points of the two UAVs is less than a preset threshold.

6. The drone cluster collaborative inspection method according to claim 5, characterized in that: The sending of the next round of inspection tasks to the drones corresponding to the target drone group includes: When the drones corresponding to the target drone group complete the current inspection task and return to their respective target parking points, the next inspection task is sent to the drones corresponding to the target drone group.

7. The drone cluster collaborative inspection method according to claim 6, characterized in that: The triggering of the drone to perform collaborative inspection according to the next round of inspection tasks includes: Divide the inspection route into two inspection sub-routes; The two inspection sub-routes are sent to two drones in the target drone group respectively, triggering the two drones in the drone group to perform inspections according to the two inspection sub-routes respectively; By sending different inspection routes to the two drones corresponding to the target drone group, a new drone group can be selected within the original target inspection area to perform collaborative inspection for the next inspection task.

8. A system using the drone cluster collaborative inspection method according to any one of claims 1 to 7, characterized in that: include: The area acquisition module is used to obtain the target inspection area and the drone inspection type of the target inspection area; A parking point determination module, used to determine the target parking point of the drone in each target inspection area according to the drone inspection type; The collaborative inspection module is used to determine the target drone group for the next round of inspection tasks through the target parking point, send the next round of inspection tasks to the drones corresponding to the target drone group, and trigger the drones to perform collaborative inspections according to the next round of inspection tasks.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the drone cluster collaborative inspection method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the drone cluster collaborative inspection method described in any one of claims 1 to 7.

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