A method and apparatus for controlling a UAV, an electronic device, and a storage medium

Abstract

Embodiments of the present application disclose a kind of unmanned aerial vehicle control method, device, electronic equipment and storage medium, the method includes: control candidate unmanned aerial vehicle according to preset flight parameter to target device flight, to target device is collided;Obtain the detection data obtained by detecting target device after candidate unmanned aerial vehicle collision;According to the detection data, determine the parameter data of target unmanned aerial vehicle for patrol, to select target unmanned aerial vehicle according to the parameter data and control the target unmanned aerial vehicle carries out patrol.This technical solution determines the unmanned aerial vehicle patrol parameter data by the detection data of target device, effectively minimizes the damage to target device in the unmanned aerial vehicle patrol process, improves the security of target device, ensures the safe and stable operation of target device.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of drone technology, and in particular to a drone control method, device, electronic device, and storage medium. Background Art

[0002] At present, in addition to being used in military or civilian fields, drones can also be used for patrol work in the commercial field. The use of drones for patrol work has the characteristics of less terrain restrictions, low cost, simple operation, rapid deployment and high inspection efficiency.

[0003] Substations are characterized by high equipment density, high equipment complexity, and easy damage. When using drones to inspect substation equipment, there is a possibility that the drone will collide with the substation equipment, which in turn may cause damage to the substation equipment, the drone itself, and the structure, affecting the safe and stable operation of the substation. Summary of the Invention

[0004] The present application provides a drone control method, device, electronic device, and storage medium to improve the operating parameters of the drone and avoid or reduce damage to target equipment during the drone's patrol process.

[0005] In a first aspect, an embodiment of the present invention provides a method for controlling a drone, comprising:

[0006] Controlling the candidate UAV to fly towards the target device according to preset flight parameters to collide with the target device;

[0007] Acquire detection data obtained by detecting the target device after the candidate UAV collides;

[0008] According to the detection data, parameter data of a target UAV for patrolling is determined, so as to select a target UAV according to the parameter data and control the target UAV to patrol.

[0009] In a second aspect, an embodiment of the present invention provides a drone control device, comprising:

[0010] The UAV control module is used to control the candidate UAV to fly towards the target device according to preset flight parameters to collide with the target device;

[0011] A detection data acquisition module is used to obtain detection data obtained by detecting the target device after the candidate drone collides;

[0012] The parameter data determination module is used to determine the parameter data of the target UAV used for patrol according to the detection data, so as to select the target UAV according to the parameter data and control the target UAV to patrol.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0014] one or more processors;

[0015] a storage device for storing one or more programs;

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the drone control method as described in any of the above embodiments.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the drone control method as described in any of the above embodiments.

[0018] Embodiments of the present application provide a drone control method, device, electronic device, and storage medium. The technical solution of the embodiments of the present application involves controlling a candidate drone to fly toward a target device according to preset flight parameters, causing the target device to collide with the target device; obtaining detection data obtained by detecting the target device after the candidate drone has collided with the target drone; and determining parameter data of a target drone for patrolling based on the detection data, thereby selecting a target drone based on the parameter data and controlling the target drone to patrol. This technical solution determines drone patrol parameter data based on the detection data of the target device, effectively minimizing damage to the target device during the drone patrol process, improving the safety of the target device, and ensuring the safe and stable operation of the target device. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the originals and elements are not necessarily drawn to scale.

[0020] Figure 1 This is a flow chart of a drone control method provided in Example 1 of the present invention;

[0021] Figure 2 This is a flow chart of a drone control method provided in Example 2 of the present invention;

[0022] Figure 3 A schematic diagram of an image collector for a drone control method provided in the second embodiment of the present invention;

[0023] Figure 4 A schematic diagram of a protective net for a drone control method provided in Example 2 of the present invention;

[0024] Figure 5This is a schematic structural diagram of a drone control device provided in Example 3 of the present invention;

[0025] Figure 6 This is a structural diagram of an electronic device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0026] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. Furthermore, the embodiments and features of the embodiments of the present invention may be combined with one another unless there is a conflict. It should also be noted that, for ease of description, the drawings only illustrate portions relevant to the present invention, not all of the components.

[0027] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the steps as sequential processes, many of the steps can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the steps can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0028] In order to better understand the embodiments of the present invention, the relevant technologies are introduced below.

[0029] Example 1

[0030] Figure 1 This is a flowchart of a drone control method provided in Example 1 of the present invention. This embodiment is applicable to drone patrols. Specifically, the drone control method can be executed by a drone control device, which can be implemented via software and / or hardware and integrated into an electronic device. Furthermore, the electronic device includes, but is not limited to, desktop computers, laptops, smartphones, servers, and other electronic devices.

[0031] like Figure 1 As shown, the method specifically includes the following steps:

[0032] S110 , controlling the candidate UAV to fly toward the target device according to preset flight parameters to collide with the target device.

[0033] The candidate UAVs can be at least two UAVs, the at least two UAVs can be of different models, and the different models can have different characteristics. The different characteristics of the candidate UAVs can be different in material, weight, volume, and structure of the UAV. The flight parameters can be flight parameters during the candidate UAV colliding with the target device, such as flight speed, distance from the target device, and flight angle.

[0034] In the embodiments of the present application, the candidate UAV can directly collide with the target device to determine the damage degree of the target device, and according to the damage degree of the target device, the parameters of the target UAV for patrolling the target device are determined to keep the target device safe and stable.

[0035] Specifically, the flight speed signal and flight route information can be received, and the candidate UAV is controlled to collide with the target device at a preset flight parameter. After the collision is completed, if a continue collision signal is received, the candidate UAV is controlled to collide with the remaining part of the target device or collide with another target device. If no continue collision signal is received, the candidate UAV that can normally work is switched to collide with the remaining part of the target device or collide with another target device. Further, whether the candidate UAV can be normally used can be determined by a worker, and the worker can select to continue to collide or switch the candidate UAV according to whether the appearance of the candidate UAV is intact. The candidate UAV colliding with the target device can also be artificially controlled. An operator controls the flight route, flight speed, and other parameters of the candidate UAV through a remote controller, and then controls the candidate UAV to collide with the target device.

[0036] In S120, detection data obtained by detecting the target device after the candidate UAV collides with the target device is acquired.

[0037] The detection data can reflect the deformation of the target device and the change of the properties of the target device, and the change of the properties of the target device includes but is not limited to the change of the insulation and the change of the resistance. The detection data can be obtained by the following process: after the collision of the candidate UAV is completed, an image collector is controlled to collect images of the surface of the target device to obtain a deformation image of the surface of the target device. The deformation of the surface of the target device in the deformation image is detected and recognized to determine the detection data of the target device after being collided by the candidate UAV. The change of the properties of the target device can be the change of the resistance and the change of the insulation, which can be read from a resistance detection device and an insulation detection device.

[0038] In an embodiment of the present application, the target device may exhibit varying degrees of damage after being hit. In order to determine the degree of damage to the target device after being hit, it is necessary to obtain detection data of the impacted part. Specifically, after the candidate drone collides with the target device, it sends a collision completion signal to the central processing unit. The central processing unit controls the image acquisition device to obtain a deformation pattern of the impacted part of the target device. The central processing unit also controls the resistance detection device and the insulation detection device to detect the resistance and insulation of the target device, thereby obtaining detection data. Among them, the location information of the impacted part of the target device can be the location information of the device that the candidate drone's flight route passes through.

[0039] Optionally, the property changes of the target device can be measured by testing or detecting equipment. For example, the insulation of the target device can be checked by an insulation resistance test to detect whether the insulation device has reduced the insulation effect due to damage; the resistance of the circuit can be checked by a loop resistance test. Insulation resistance testing and loop resistance testing are existing technologies and will not be described in detail in the embodiments of this application. More obvious deformations of the target device can be obtained through manual observation, such as missing, scratched or broken parts of the target device. The damaged location of the target device can be manually marked and the degree of damage can be recorded.

[0040] For example, if a porcelain bottle that serves as an insulator in a substation is hit, a penetration test can be used to determine the deformation of the porcelain bottle. Specifically, a penetration reagent is placed on the porcelain bottle. After the porcelain bottle dries, a developer is applied to adsorb the penetration reagent that has penetrated into the defect to the surface, revealing the defect traces, and then the deformation of the porcelain bottle can be determined.

[0041] In an embodiment of the present application, detection data can be obtained through an image collector, a resistance detection device, and an insulation detection device, and detection data input by an operator can also be obtained. The detection data input by the operator can be obtained by direct observation, insulation resistance testing, loop resistance testing, and penetration testing.

[0042] S130: Determine parameter data of a target UAV for patrolling based on the detection data, select a target UAV based on the parameter data, and control the target UAV to patrol.

[0043] The target drone may be the candidate drone that causes the least damage to the target device when colliding with the target drone. Parameter data includes, but is not limited to, the target drone's patrol speed, the patrol distance between the target drone and the target device, and the target drone's patrol route. Specifically, the target drone's parameter data can be adaptively determined based on the test data. For example, if at least two candidate drones of different models collide with the target device, and at least two of the candidate drones have identical flight parameters, the candidate drone with the smallest change in the target device's test data is selected as the target drone. If the candidate drones collide with the target device at high, medium, and low speeds, and damage is caused by the high-speed collision but not by the medium and low-speed collisions, the target drone's flight speed for patrolling may be medium. If the candidate drone strikes different parts of the target device at high speed, and at least one part is damaged, the flight speed used for patrolling the target device cannot be high. The flight speed must be reduced and the collision test repeated until no part of the target device is damaged. This speed is then determined as the patrol flight speed.

[0044] The technical solution of the embodiments of the present application controls a candidate drone to fly toward a target device according to preset flight parameters, causing it to collide with the target device; obtains detection data from the target device after the candidate drone has collided with the target device; and, based on the detection data, determines parameter data for a target drone used for patrolling, selects a target drone based on the parameter data, and controls the target drone to conduct the patrol. This technical solution determines drone patrol parameter data based on the detection data from the target device, effectively minimizing damage to the target device during the drone patrol process, improving the safety of the target device and ensuring the safe and stable operation of the target device.

[0045] In an embodiment of the present application, optionally, attention association information of each part of the target device is obtained; wherein the attention association information includes at least one of information on the susceptibility of each part to damage, information on the probability of appearing in a route of preset flight parameters, and information on the degree of impact on the operation of the target device after damage; based on the attention association information, an attention matrix of each part of the target device is determined, and the attention of each part is sorted according to the attention matrix; and the target part on the target device is determined according to the attention sort.

[0046] The target part can be a location requiring particular attention, and multiple collisions can be performed on the target part. In this scheme, each part of the target device has different characteristics. Based on these characteristics, three types of attention-related information can be distinguished: damage susceptibility information affected by the target device's structure and material, probability information within the route of the preset flight parameters, and information about the impact of damage on the target device's operation. Based on this attention-related information, an attention matrix is ​​listed for each part of the target device. Each attention matrix includes three numbers, representing a piece of attention-related information. Each piece of attention-related information is represented numerically according to its importance, from high to low: 4, 3, 2, and 1. For example, the attention matrix for a part is [4, 3, 3]. The damage susceptibility information for this part is 4, indicating that it is easily damaged, the probability information within the route of the preset flight parameters is 3, and the impact information on the operation of the target device after damage is 3. The attention matrix for another part can be [1, 2, 3]. The damage susceptibility information for this part is 1, indicating that it is not easily damaged, the probability information within the route of the preset flight parameters is 2, and the impact information on the operation of the target device after damage is 3.

[0047] Furthermore, the attention is sorted according to the attention matrix of each part. For example, if the attention matrix of a part is [4,3,3], the attention size of the part can be 4*a+3*b+3*c, where a, b, and c represent the weights of each attention-related information respectively. This embodiment of the present application does not limit this. The parts are sorted according to their attention size. Parts with large attention values ​​can be used as target parts. For example, if the target device has 6 parts in total, 2 parts need to be selected as target parts. If the attention sizes of the 6 parts are 12, 10, 11, 6, 4 and 7 respectively, the parts with attention matrices of 11 and 12 are selected as target parts.

[0048] Specifically, the attention matrix, attention size and the number of target parts can be pre-set and input into the hard disk. The embodiment of the present application can read each attention matrix, attention size and the number of target parts from the hard disk.

[0049] In this solution, further, the candidate UAV is controlled to fly toward the target device according to preset flight parameters to collide with the target device, including: controlling the candidate UAV to fly toward the target part on the target device according to preset flight parameters to collide with the target part on the target device.

[0050] In this solution, a focus matrix is ​​established for each part of the target device to identify target parts that require special attention. These parts are likely to be critical or easily damaged. Therefore, it is important to monitor the damage to these parts during the candidate drone's patrol. This allows the appropriate parameters and data to be used to control the target drone's patrol and minimize damage to the target parts. For parts not considered a priority, there is no need to control the candidate drone to collide with them, reducing workload and power consumption. This solution ensures that the candidate drones collide with the target parts, ensuring that key parts are tested and verified, and reducing unnecessary drone collisions.

[0051] Example 2

[0052] Figure 2 This is a flowchart of a drone control method provided by Example 2 of the present invention. This example is an optimization based on the above example and specifically describes the control signals. It should be noted that any technical details not fully described in this example can be referred to in any of the above examples.

[0053] Specifically, such as Figure 2 As shown, the method specifically includes the following steps:

[0054] S210: Control the candidate UAV to fly toward the target device according to preset flight parameters to collide with the target device.

[0055] In an embodiment of the present application, optionally, the preset flight parameters include at least one preset route, at least one preset speed, and at least one flight distance, wherein the flight distance is the distance between the candidate UAV flight starting point and the target device.

[0056] Specifically, the candidate drone uses a preset route, preset speed, and flight distance as variables, and follows the single variable principle to collide with the target device. For example, if the preset route and preset speed are the same, the flight distance can be changed to control the candidate drone to collide with the target device; if the preset route and flight distance are the same, the preset speed can be changed to control the candidate drone to collide with the target device; if the preset speed and flight distance are the same, the preset route can be changed to control the candidate drone to collide with the target device. For example, the preset route can be set in the corresponding control software of the candidate drone, the preset speed can be set to 1m / s, 3m / s, and 5m / s, and the flight distance can be set to 1.5m, 3m, and 5m.

[0057] In this solution, candidate drones are controlled to collide with target devices under different circumstances through different preset routes, preset speeds, and flight distances to ensure that the collision results are real and reliable.

[0058] S220, obtaining, by means of at least one image collector disposed in the flight path of the candidate UAV, an image of the surface of the target device when the candidate UAV collides with the target device; and determining, based on the image of the surface of the target device, detection data of the target device after being collided with the candidate UAV.

[0059] The image collector can be a high-speed camera, and the installation position can be Figure 3 The position in Figure 3 The number and installation locations of image collectors are examples only; the specific number and installation locations are not limited. Specifically, because most target devices are not easily damaged and their deformation is very small and difficult to observe, image collectors can be used to record device deformation to facilitate determination of the location and extent of deformation.

[0060] Optionally, the image collector can collect the posture information of the candidate drone at the moment of impact, determine the specific information of the impact, and provide a reference for the target device detection data. For example, the results of the impact of the candidate drone's sturdy main body and elastic shock-absorbing parts on the target device are often different. The former is likely to damage the target device, while the latter is likely not to damage the target device. These comprehensive considerations can be used to correct the detection data of the target device.

[0061] In an embodiment of the present application, optionally, at least one image collector arranged in the flight route of the candidate UAV is used to collect flight images of the candidate UAV during flight; based on the flight images, the actual flight parameters of the candidate UAV are determined; and based on the real-time flight parameters and preset flight parameters, the flight process of the candidate UAV is corrected and controlled.

[0062] Among them, the flight image can be Figure 3 The series of images captured by the high-speed cameras shown can reflect the instantaneous flight status of the candidate drone. Specifically, by capturing flight images of the candidate drone to the right of its heading using high-speed cameras 1 and 3, and capturing flight images of the candidate drone to the left of its heading using high-speed cameras 2 and 4, the actual flight attitude and flight parameters of the candidate drone can be determined, and the flight parameters of the candidate drone can be corrected. For example, if the preset flight speed is 5m / s and the actual measured speed is 5.2m / s, then this collision is recorded as a collision at a speed of 5.2m / s. In this solution, the actual flight parameters of the candidate drone are obtained through the image collector, avoiding errors between the detection data and the corresponding flight parameters.

[0063] S230: Determine parameter data of a target UAV for patrolling based on the detection data, select a target UAV based on the parameter data, and control the target UAV to patrol.

[0064] For example, if the parameter data of the candidate UAV is: flight speed 5 m / s, flight distance 2 m, and based on this parameter data, the target device is collided, the detection data of the target device changes, the parameter data of the target UAV needs to be adjusted. If the parameter data of the candidate UAV is: flight speed 4 m / s, flight distance 1 m, and based on this parameter data, the target device is collided, the detection data of the target device does not change, and the parameter data of the target UAV can be this parameter data.

[0065] In the embodiment of the application, the parameter data of the target UAV for patrol is determined according to the detection data, including: according to at least one of the deformation data, the insulation resistance detection data and the loop resistance detection data in the detection data, determining a candidate UAV that satisfies at least one of the following: the minimum deformation after colliding with the target device; the candidate UAV corresponding to the normal insulation resistance detection data; the candidate UAV corresponding to the normal loop resistance detection data; determining the parameter data of the target UAV according to at least one of the model information, the material information and the preset flight parameter of the candidate UAV.

[0066] In the embodiment of the application, the parameter data of the target UAV for patrol is determined according to the detection data, including: according to at least one of the deformation data, the insulation resistance detection data and the loop resistance detection data in the detection data, determining a candidate UAV that satisfies at least one of the following: the minimum deformation after colliding with the target device; the candidate UAV corresponding to the normal insulation resistance detection data; the candidate UAV corresponding to the normal loop resistance detection data; determining the parameter data of the target UAV according to at least one of the model information, the material information and the preset flight parameter of the candidate UAV.

[0067] For example, two candidate drone models are selected, where one candidate drone is heavier and the other candidate drone is lighter. If the detection data of the two candidate drones after colliding with the target device are the same or similar, the determined target drone parameter data may include the two candidate drone model information; if the detection data of the two candidate drones after colliding with the target device are different, and the heavier candidate drone causes a larger deformation and property change of the target device, then the determined target drone parameter data includes the lighter candidate drone model. Similarly, if the material information and preset flight parameters of the candidate drones have an impact on the detection data of the target device, then the determined target drone parameter data includes the material information or preset flight parameters that cause the target device to have a smaller deformation and property change. The embodiment of the present application does not limit the number of candidate drones.

[0068] In this solution, the parameter data of the candidate drone that causes the smallest deformation and property change of the target device is determined. Based on the model information, material information and at least one of the preset flight parameters of the candidate drone, the parameter data of the target drone can be determined, so that subsequent target drone inspections are more standardized and the safe and stable operation of the target device is guaranteed.

[0069] In the embodiment of this application, Figure 4 As shown, in order to prevent the candidate drone from colliding with the target equipment and falling to the ground to cause secondary damage, a protective net can be installed around the target equipment to prevent the candidate drone from accidentally colliding with other equipment during flight, and to avoid direct collision between the candidate drone and the ground, thereby protecting the candidate drone's blades and other components.

[0070] A drone control method provided in the second embodiment of the present invention is optimized based on the above embodiment. It uses an image collector to determine the degree of deformation of the target device, thereby improving the accuracy of the target device detection data and making the candidate drone parameter data determined based on the detection data more valuable for reference.

[0071] In an embodiment of the present application, if the detection data of a target device changes, a warning signal can be issued to alert the operator that the target device is fragile and requires additional protective equipment during the target drone inspection. Based on the warning signal, the operator can adaptively add a protective net to the target device and / or a shock absorber to the target drone. Warning signals include, but are not limited to, buzzer signals and warning light signals.

[0072] Example 3

[0073] Figure 5 This is a schematic diagram of the structure of a drone control device provided in Example 3 of the present invention. The drone control device provided in this embodiment includes:

[0074] The UAV control module 310 is used to control the candidate UAV to fly toward the target device according to preset flight parameters to collide with the target device;

[0075] A detection data acquisition module 320 is used to obtain detection data obtained by detecting the target device after the candidate drone collides with the target device;

[0076] The parameter data determination module 330 is used to determine the parameter data of the target UAV used for patrolling according to the detection data, so as to select the target UAV according to the parameter data and control the target UAV to patrol.

[0077] Optionally, the preset flight parameters include at least one preset route, at least one preset speed, and at least one flight distance, wherein the flight distance is the distance between the flight starting point of the candidate UAV and the target device.

[0078] Furthermore, the parameter data determination module 330 includes:

[0079] The candidate drone determining unit is configured to determine a candidate drone that satisfies at least one of the following conditions based on at least one of the deformation data, the insulation resistance detection data, and the loop resistance detection data in the detection data:

[0080] Minimize the deformation of the target device after the collision;

[0081] Candidate drones corresponding to normal insulation resistance test data;

[0082] Candidate drones corresponding to normal loop resistance test data;

[0083] The parameter data determining unit is used to determine the parameter data of the target UAV based on at least one of the model information, material information and preset flight parameters of the candidate UAV.

[0084] Optionally, the device further includes:

[0085] A flight image acquisition module, configured to acquire flight images of the candidate UAV during flight through at least one image collector arranged in the flight route of the candidate UAV;

[0086] an actual flight parameter determination module, configured to determine the actual flight parameters of the candidate UAV based on the flight image;

[0087] The correction control module is used to correct and control the flight process of the candidate UAV according to the real-time flight parameters and the preset flight parameters.

[0088] Optionally, the detection data acquisition module 320 includes:

[0089] an image acquisition unit, configured to acquire, through at least one image collector disposed in a flight path of the candidate UAV, an image of a surface of the target device when the candidate UAV collides with the target device;

[0090] The detection data determining unit is configured to determine, based on an image of a surface of the target device, detection data of the target device after being collided with by a candidate drone.

[0091] Optionally, the device further includes:

[0092] an acquisition module configured to acquire, for each part of the target device, information related to the attention level of each part; wherein the information related to the attention level includes at least one of information on the damage susceptibility of each part, information on the probability of each part appearing in a route with preset flight parameters, and information on the impact of damage on the operation of the target device;

[0093] an attention ranking module, configured to determine an attention matrix of each part of the target device according to the attention association information, and to sort the attention of each part according to the attention matrix;

[0094] The target part determination module is used to determine the target part on the target device according to the attention ranking.

[0095] Furthermore, the drone control module 310 includes:

[0096] The UAV control unit is used to control the candidate UAV to fly toward the target part of the target device according to preset flight parameters, and collide with the target part of the target device.

[0097] The drone control device provided in the third embodiment of the present invention can be used to execute the drone control method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0098] Example 4

[0099] Figure 6 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device 10 can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, user equipment, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0100] like Figure 6As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0101] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks and wireless networks.

[0102] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the drone control method.

[0103] In some embodiments, the drone control method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the drone control method in any other suitable manner (e.g., via firmware).

[0104] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a load programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0105] Computer programs used to implement the processes of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a standalone software package and partially on a remote machine or entirely on a remote machine or server.

[0106] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0107] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device 10 having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device 10. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0108] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0109] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0110] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0111] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A drone control method, characterized in that: The method comprises: Controlling the candidate UAV to fly towards the target device according to preset flight parameters to collide with the target device; Acquire detection data obtained by detecting the target device after the candidate UAV collides; Determining parameter data of a target UAV for patrolling based on the detection data, selecting a target UAV based on the parameter data and controlling the target UAV to patrol; The method further comprises: Obtaining, for each part of the target device, information related to the degree of attention of each part; wherein the information related to the degree of attention includes at least one of information on the susceptibility of each part to damage, information on the probability of each part appearing in a route with preset flight parameters, and information on the degree of impact of damage on the operation of the target device; Determining an attention matrix for each part of the target device according to the attention association information, and ranking the parts according to the attention matrix; determining a target part on the target device according to the attention ranking; The controlling the candidate UAV to fly toward the target device according to preset flight parameters to collide with the target device includes: The candidate UAV is controlled to fly toward the target part of the target device according to preset flight parameters, and collides with the target part of the target device.

2. The method according to claim 1, characterized in that The preset flight parameters include at least one preset route, at least one preset speed, and at least one flight distance, wherein the flight distance is the distance between the candidate UAV flight starting point and the target device.

3. The method according to claim 2, characterized in that Determine parameter data of the target UAV for patrol based on the detection data, including: Determine, based on at least one of the deformation data, the insulation resistance detection data, and the loop resistance detection data in the detection data, a candidate drone that satisfies at least one of the following: Minimize the deformation of the target device after the collision; Candidate drones corresponding to normal insulation resistance test data; Candidate drones corresponding to normal loop resistance test data; Parameter data of the target UAV is determined based on at least one of the model information, material information, and preset flight parameters of the candidate UAV.

4. The method according to claim 3, characterized in that Obtain detection data after the target device is collided with the candidate drone, including: Acquiring, by means of at least one image collector disposed in a flight path of the candidate UAV, an image of a surface of the target device when the candidate UAV collides with the target device; Determine deformation data of the target device after being collided with by the candidate drone based on the image of the target device surface.

5. The method according to claim 1, wherein The method further comprises: Capturing flight images of the candidate UAV during flight by at least one image collector disposed in the flight path of the candidate UAV; determining actual flight parameters of the candidate UAV based on the flight image; The flight process of the candidate UAV is corrected and controlled according to the actual flight parameters and the preset flight parameters.

6. A drone control device, characterized in that: The device comprises: The UAV control module is used to control the candidate UAV to fly towards the target device according to preset flight parameters to collide with the target device; A detection data acquisition module is used to obtain detection data obtained by detecting the target device after the candidate drone collides; a parameter data determination module, configured to determine parameter data of a target UAV for patrolling based on the detection data, so as to select a target UAV based on the parameter data and control the target UAV to patrol; The device further comprises: an acquisition module configured to acquire, for each part of the target device, information related to the attention level of each part; wherein the information related to the attention level includes at least one of information on the damage susceptibility of each part, information on the probability of each part appearing in a route with preset flight parameters, and information on the impact of damage on the operation of the target device; an attention ranking module, configured to determine an attention matrix of each part of the target device according to the attention association information, and to sort the attention of each part according to the attention matrix; A target part determination module, configured to determine a target part on a target device according to the attention ranking; The drone control module includes: The UAV control unit is used to control the candidate UAV to fly toward the target part of the target device according to preset flight parameters, and collide with the target part of the target device.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the drone control method according to 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 a processor, the drone control method according to any one of claims 1 to 5 is implemented.

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