Method and device for determining navigation route of unmanned aerial vehicle, electronic equipment and storage medium

Abstract

The invention discloses an unmanned aerial vehicle navigation route determination method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a first natural feature set of a plurality of inspection objects, the first natural feature set comprising a plurality of initial natural features of the inspection objects; controlling the target unmanned aerial vehicle to execute inspection operation on the plurality of inspection objects to obtain a second natural feature set; comparing the first natural feature set with the second natural feature set to obtain a comparison result; and determining a target navigation route of the target unmanned aerial vehicle according to a comparison result. The technical problems that in the prior art, transformer substation inspection consumes much manpower, and the indoor inspection density is low are solved.

Description

Technical Field

[0001] The present invention relates to the field of automation technology, and in particular to a method, device, electronic device and storage medium for determining a navigation route of an unmanned aerial vehicle. Background Art

[0002] Substation inspection refers to the regular inspection, measurement, testing and maintenance of substation equipment. The purpose of the inspection is to ensure the normal operation of the equipment, improve the reliability and safety of the equipment, and avoid the occurrence of failures and accidents. The inspection content includes but is not limited to: 1. Check the operation of substation equipment, including transformers, switchgear, cables, insulators, etc. 2. Measure the voltage, current, temperature and other parameters of the equipment to ensure that the equipment operates within the normal range. 3. Conduct equipment tests, such as insulation resistance testing, partial discharge detection, etc., to ensure the normal operation of the equipment. 4. Check the environmental sanitation and safety facilities of the substation, such as fire-fighting equipment, lightning protection equipment, etc. 5. Check the operation records and maintenance records of the substation to ensure that the maintenance of the equipment is carried out in a timely and effective manner.

[0003] During the inspection process, equipment failures and problems can be discovered in time, and corresponding measures can be taken to repair and maintain them. The frequency of inspections is generally determined by the importance of the equipment and the operating environment, and is generally conducted once a month or quarterly. Through regular inspections, the safe and stable operation of substation equipment can be ensured, the service life of the equipment can be extended, and the normal operation of the power grid can be guaranteed.

[0004] In the existing technology, autonomous flight of indoor drones usually relies on the fusion of lidar and visible light data. In order to improve the positioning and navigation accuracy of drones, it is usually necessary to add markers to them during flight, which increases the workload of construction and maintenance.

[0005] There is currently no corresponding solution to the above problems. Summary of the invention

[0006] The embodiments of the present invention provide a method, device, electronic device and storage medium for determining a navigation route of an unmanned aerial vehicle, so as to at least solve the technical problems in the prior art that substation inspection consumes a lot of manpower and has a low indoor inspection density.

[0007] According to one embodiment of the present invention, there is provided a method for determining a navigation route of an unmanned aerial vehicle, comprising: obtaining a first natural feature set of multiple inspection objects, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects; controlling a target unmanned aerial vehicle to perform inspection operations on the multiple inspection objects to obtain a second natural feature set; comparing the first natural feature set and the second natural feature set to obtain a comparison result; and determining a target navigation route of the target unmanned aerial vehicle based on the comparison result.

[0008] Optionally, the method for determining the navigation route of the unmanned aerial vehicle also includes: obtaining multiple target positions of multiple inspection objects; and determining multiple initial natural features based on the multiple target positions.

[0009] Optionally, the method for determining the navigation route of the UAV also includes: obtaining inspection channel information of the target UAV; determining the initial navigation route of the target UAV based on multiple target positions and inspection channel information; and controlling the target UAV to perform inspection operations on multiple inspection objects based on the initial navigation route.

[0010] Optionally, the method for determining the drone navigation route also includes: in response to the target drone inspecting multiple inspection objects, acquiring multiple target natural features of the multiple inspection objects based on a monocular vision algorithm.

[0011] Optionally, the method for determining the navigation route of the unmanned aerial vehicle further includes: in response to the comparison result being that the first natural feature set and the second natural feature set are consistent, determining the initial navigation route as the target navigation route.

[0012] Optionally, the method for determining the navigation route of the unmanned aerial vehicle also includes: in response to the comparison result that the first natural feature set and the second natural feature set are inconsistent, performing an update operation on the initial navigation route based on the second natural feature set to obtain an updated navigation route; and determining the updated navigation route as the target navigation route.

[0013] Optionally, the method for determining the navigation route of the unmanned aerial vehicle also includes: performing a matching operation on the first natural feature set and the second natural feature set to obtain a matching result; in response to the matching result being that the first natural feature set and the second natural feature set are inconsistent, determining the target natural feature; obtaining the target inspection object corresponding to the target natural feature; and performing an update operation on multiple inspection objects based on the target inspection object.

[0014] According to one embodiment of the present invention, there is also provided a device for determining a navigation route of a UAV, comprising: a first acquisition module, used to acquire a first natural feature set of multiple inspection objects, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects; a first execution module, used to control a target UAV to perform inspection operations on the multiple inspection objects to obtain a second natural feature set; a comparison module, used to compare the first natural feature set and the second natural feature set to obtain a comparison result; and a first determination module, used to determine a target navigation route of the target UAV based on the comparison result.

[0015] Optionally, the first acquisition module includes: a first acquisition unit, used to acquire multiple target positions of multiple inspection objects; and a first determination unit, used to determine multiple initial natural features according to the multiple target positions.

[0016] Optionally, the first execution module includes: a second acquisition unit, used to acquire inspection channel information of the target UAV; a second determination unit, used to determine the initial navigation route of the target UAV based on multiple target positions and inspection channel information; and a first execution unit, used to control the target UAV to perform inspection operations on multiple inspection objects based on the initial navigation route.

[0017] Optionally, the first execution module also includes: a third acquisition unit, used to acquire multiple target natural features of the multiple inspection objects based on a monocular vision algorithm in response to the target drone inspecting multiple inspection objects.

[0018] Optionally, the first determination module includes: a third determination unit, configured to determine the initial navigation route as the target navigation route in response to a comparison result showing that the first natural feature set and the second natural feature set are consistent.

[0019] Optionally, the first determination module also includes: a second execution unit, used to perform an update operation on the initial navigation route based on the second natural feature set in response to the comparison result being inconsistent between the first natural feature set and the second natural feature set, to obtain an updated navigation route; and a fourth determination unit, used to determine that the updated navigation route is the target navigation route.

[0020] Optionally, the device for determining the navigation route of the unmanned aerial vehicle also includes: a second execution module, used to perform a matching operation on the first natural feature set and the second natural feature set to obtain a matching result; a second determination module, used to determine the target natural feature in response to the matching result being that the first natural feature set and the second natural feature set are inconsistent; a second acquisition module, used to acquire the target inspection object corresponding to the target natural feature; and a third execution module, used to perform an update operation on multiple inspection objects based on the target inspection object.

[0021] According to one embodiment of the present invention, there is also provided an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute any of the above methods for determining a navigation route of a drone.

[0022] According to one embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, wherein the computer program is configured to execute any of the above-mentioned methods for determining a navigation route of a drone when running.

[0023] In an embodiment of the present invention, a first natural feature set of multiple inspection objects is obtained, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects, and a target UAV is controlled to perform inspection operations on the multiple inspection objects to obtain a second natural feature set. This achieves the purpose of comparing the first natural feature set and the second natural feature set to obtain a comparison result, and achieves the technical effect of determining the target navigation route of the target UAV based on the comparison result, thereby solving the technical problems in the prior art that substation inspection consumes a lot of manpower and has a low indoor inspection density. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0025] Figure 1 is a flow chart of a method for determining a navigation route of a drone according to one embodiment of the present invention;

[0026] Figure 2 is a structural block diagram of a drone according to one embodiment of the present invention;

[0027] Figure 3 4 is a structural block diagram of a device for determining a navigation route of a drone according to one embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] According to an embodiment of the present invention, an embodiment of a method for determining a navigation route of an unmanned aerial vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system comprising at least one set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] The method embodiment may also be performed in an electronic device, a similar control device or an electronic device including a memory and a processor. Taking an electronic device as an example, the electronic device may include one or more processors and a memory for storing data. Optionally, the electronic device may also include a communication device and a display device for communication functions. It will be understood by those skilled in the art that the above structural description is only illustrative and does not limit the structure of the above electronic device. For example, the electronic device may also include more or fewer components than the above structural description, or have a configuration different from the above structural description.

[0032] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microcontroller unit (MCU), a field-programmable gate array (FPGA), a neural-network processing unit (NPU), a tensor processing unit (TPU), an artificial intelligence (AI) type processor, and other processing devices. Among them, different processing units may be independent components or integrated into one or more processors. In some instances, the electronic device may also include one or more processors.

[0033] The memory can be used to store computer programs, such as storing a computer program corresponding to the method for determining the navigation route of the unmanned aerial vehicle in the embodiment of the present invention. The processor implements the above-mentioned method for determining the navigation route of the unmanned aerial vehicle by running the computer program stored in the memory. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the electronic device via a grid. Examples of the above-mentioned grid include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0034] The communication device is used to receive or send data via a grid. The specific examples of the above-mentioned grid may include a wireless grid provided by a communication provider of the mobile terminal. In one example, the communication device includes a grid adapter (network interface controller, NIC), which can be connected to other grid devices through a base station so as to communicate with the Internet. In one example, the communication device can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly. In some embodiments of the present solution, the communication device is used to connect to mobile devices such as mobile phones and tablets, and instructions can be sent to the vehicle-mounted terminal through the mobile device.

[0035] The display device may be a touch screen type liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or "touch display screen"). The liquid crystal display may enable a user to interact with a user interface of the vehicle-mounted terminal. In some embodiments, the vehicle-mounted terminal has a graphical user interface (GUI), and a user may interact with the GUI by finger contact and / or gestures on a touch-sensitive surface. The human-computer interaction function here may include a vehicle gear shifting function, and executable instructions for executing the human-computer interaction function are configured / stored in a computer program product or a readable storage medium executable by one or more processors.

[0036] Figure 1 is a flow chart of a method for determining a navigation route of a drone according to one embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0037] Step S102: Acquire a first natural feature set of multiple inspection objects, wherein the first natural feature set includes a plurality of initial natural features of the multiple inspection objects.

[0038] Optionally, the execution subject of this embodiment is a navigation route determination system. It should be noted that other electronic devices and processors can also serve as execution subjects, and no further limitations are given here.

[0039] In the technical solution provided in the above step S102 of the present invention, the navigation route determination system obtains a first natural feature set of multiple inspection objects in the substation, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects.

[0040] Specifically, each inspection object corresponds to an initial natural feature.

[0041] Specifically, Figure 2 As shown, the UAV includes a laser radar, a camera, a flight control system and an edge computing terminal. Furthermore, the edge computing terminal can be integrated into the UAV nest, which includes a work ticket analysis part, a marker navigation analysis part, a marker generation and management part and a natural marker database part.

[0042] Specifically, the substation is densely populated with equipment. In order to improve flight accuracy, drones need landmarks to fly with reference to camera and lidar data. Since the functions of each room in the substation are clear and the equipment is highly standardized, indoor equipment can be selected to extract its natural features as navigation landmarks to assist drones in precise positioning.

[0043] Step S104: Control the target UAV to perform inspection operations on multiple inspection objects to obtain a second natural feature set.

[0044] In the technical solution provided in the above step S104 of the present invention, the navigation route determination system needs to control the flight of the target UAV to perform inspection operations on the above multiple inspection objects, so that the second natural feature set can be collected during the flight.

[0045] Specifically, when the drone flies to a designated inspection object on the line, it can use a monocular vision method to extract the natural feature data of the inspection object and send it to the edge computing server.

[0046] Optionally, after inspecting multiple designated objects in the line, the target drone extracts the natural feature data (i.e., the second natural features) of the above multiple objects in sequence and sends them to the edge computing server, thereby forming a second natural feature set of multiple inspected objects.

[0047] Step S106: compare the first natural feature set and the second natural feature set to obtain a comparison result.

[0048] In the technical solution provided in the above step S106 of the present invention, further, the navigation route determination system compares the initial first natural feature set with the second natural feature set acquired by the target UAV during the flight to obtain a comparison result.

[0049] Specifically, when the landmark navigation analysis part of the edge computing server matches the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set), if the database data (i.e., the first natural feature set) does not match the collected data (i.e., the second natural feature set), it is determined that the inspection object has changed (such as: equipment has been adjusted), and the collected data is saved in the database for manual identification by the background (the registration process is executed after identification), and at the same time, the target drone is controlled to inspect the next inspection object according to the inspection plan.

[0050] Specifically, when the landmark navigation analysis part of the edge computing server matches the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set), if the database data (i.e., the first natural feature set) matches the collected data (i.e., the second natural feature set), it indicates that the inspection object has not changed, so no other operations are required. At the same time, the target drone is controlled to inspect the next inspection object according to the inspection plan.

[0051] Step S108, determining the target navigation route of the target UAV according to the comparison result.

[0052] In the technical solution provided in the above step S108 of the present invention, the navigation route determination system determines the target navigation route of the target UAV according to the comparison result of the first natural feature set and the second natural feature set.

[0053] Optionally, the landmark navigation analysis part of the edge computing server compares the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set). If the above comparison results are inconsistent, the flight control system of the target UAV will adjust its own position according to the flight route deviation, and determine the adjusted navigation route as the target navigation route.

[0054] Optionally, the landmark navigation analysis part of the edge computing server compares the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set). If the above comparison results are consistent, the flight control system of the target UAV will conduct inspections based on the original flight route as the target navigation route.

[0055] From the above steps S102 to S108, it can be known that in the present invention, a first natural feature set of multiple inspection objects is obtained, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects, and the target UAV is controlled to perform inspection operations on the multiple inspection objects to obtain a second natural feature set, thereby achieving the purpose of comparing the first natural feature set and the second natural feature set to obtain a comparison result, and achieving the technical effect of determining the target navigation route of the target UAV according to the comparison result, thereby solving the technical problems in the prior art that substation inspection consumes a lot of manpower and has a low indoor inspection density.

[0056] The purpose of the present invention is to provide an indoor unmanned aerial vehicle natural marker navigation method, specifically involving unmanned aerial vehicles and edge computing terminals. The unmanned aerial vehicle includes a laser radar, a camera and a flight control system. The edge computing terminal can be integrated into the unmanned aerial vehicle nest, including a work ticket analysis part, a marker navigation analysis part, a marker generation and management part and a natural marker database part. The inspection object is extracted according to the work ticket, and then the natural marker is automatically analyzed and optimized for the inspection object, so as to realize the safe flight of the indoor unmanned aerial vehicle, improve the indoor inspection density of the substation, and effectively replace the manual inspection.

[0057] Furthermore, the present invention provides a natural marker navigation method for indoor drones, which extracts the content of the inspection work ticket and uses the inspection object as a natural marker for drone navigation reference. This can provide a basis for navigation when the indoor drone is flying, improve the accuracy and safety of the drone flight, and achieve the generation and optimization of natural markers without human intervention, thereby reducing the equipment risk and personal risk of indoor drone inspections.

[0058] The above method of this embodiment is further described in detail below.

[0059] As an optional implementation, obtaining a first natural feature set of multiple inspection objects includes: obtaining multiple target positions of the multiple inspection objects; and determining multiple initial natural features according to the multiple target positions.

[0060] In this embodiment, the navigation route determination system obtains the first natural feature set of multiple inspection objects, including the following steps: the navigation route determination system first obtains multiple optimal observation positions of multiple inspection objects in the substation, and then further determines multiple initial natural features of the multiple inspection objects based on the multiple target positions of the above-mentioned multiple inspection objects.

[0061] Specifically, the substation is densely populated with equipment. In order to improve flight accuracy, the drone also needs landmarks to fly with reference to camera and lidar data. Since the functions of each room in the substation are clear and the equipment is highly standardized, indoor equipment can be selected to extract its natural features as navigation landmarks to assist the drone in precise positioning. As an optional implementation, controlling the target drone to perform inspection operations on multiple inspection objects to obtain the second natural feature set includes: obtaining the inspection channel information of the target drone; determining the initial navigation route of the target drone based on multiple target locations and inspection channel information; and controlling the target drone to perform inspection operations on multiple inspection objects based on the initial navigation route.

[0062] In this embodiment, the navigation route determination system controls the target UAV to perform inspection operations on multiple inspection objects in the substation, and obtains the second natural feature set during the inspection process, including the following steps: the navigation route determination system can obtain the channel information required for inspection of the target UAV, and then determine the initial navigation route of the target UAV according to the multiple target positions of the multiple inspection objects and the inspection channel information of the target UAV, and control the target UAV to first perform inspection operations on the multiple inspection objects based on the initial navigation route of the UAV.

[0063] Specifically, the edge computing server automatically plans the optimal inspection route based on the best observation positions of the above-mentioned multiple inspection objects and the inspectable channel data.

[0064] Optionally, the navigation route determination system compares the initial natural features extracted from the substation inspection equipment based on the video data from the drone inspection camera with the standard tracking data after registration to determine the precise location of the drone flight, and sends the location to the flight control system as the initial inspection route for inspection operations.

[0065] As an optional embodiment, the second natural feature set includes multiple target natural features, wherein the method further includes: in response to the target drone inspecting multiple inspection objects, acquiring multiple target natural features of the multiple inspection objects based on a monocular vision algorithm.

[0066] In this embodiment, the above method also includes: when the target drone performs a flight operation to inspect multiple inspection objects, the navigation route determination system can obtain multiple target natural features of the multiple inspection objects during the inspection process based on a monocular vision algorithm, that is, the above multiple target natural features constitute a second natural feature collection.

[0067] Optionally, a set of systems can be used to extract the natural feature marker features of multiple inspection objects in a variety of different indoor equipment environments, so there is no need to adjust and configure parameters, saving a lot of manpower costs.

[0068] As an optional implementation, determining the target navigation route of the target UAV according to the comparison result includes: in response to the comparison result being that the first natural feature set and the second natural feature set are consistent, determining the initial navigation route as the target navigation route.

[0069] In this embodiment, the navigation route determination system determines the target navigation route of the target drone based on the comparison result between the database data (i.e., the first natural feature set) and the collected data (i.e., the second natural feature set), including the following steps: when the above comparison result is that the first natural feature set and the second natural feature set are consistent, the navigation route determination system can determine that the initially set navigation route is the target navigation route.

[0070] Specifically, the landmark navigation analysis part of the edge computing server compares the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set). If the above comparison results are consistent, the flight control system of the target UAV will conduct inspections based on the original flight route as the target navigation route.

[0071] As an optional implementation, the method also includes: in response to the comparison result that the first natural feature set and the second natural feature set are inconsistent, performing an update operation on the initial navigation route based on the second natural feature set to obtain an updated navigation route, and determining that the updated navigation route is the target navigation route.

[0072] In this embodiment, the navigation route determination system determines the target navigation route of the target UAV based on the comparison result between the database data (i.e., the first natural feature set) and the collected data (i.e., the second natural feature set), and includes the following steps: when the above comparison result is that the first natural feature set and the second natural feature set are inconsistent, the navigation route determination system performs an update operation on the initial navigation route based on multiple target natural features of multiple inspection objects to obtain an updated navigation route, and then controls the target UAV to perform the inspection operation according to the updated navigation route (i.e., the target navigation route).

[0073] Specifically, the landmark navigation analysis part of the edge computing server compares the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set). If the comparison results are consistent, the flight control system of the target UAV will perform an inspection based on the original flight route as the target navigation route. As an optional implementation, the method also includes: performing a matching operation on the first natural feature set and the second natural feature set to obtain a matching result; in response to the matching result that the first natural feature set and the second natural feature set are inconsistent, determining the target natural feature; obtaining the target inspection object corresponding to the target natural feature; and performing an update operation on multiple inspection objects based on the target inspection object.

[0074] In this embodiment, the method for determining the navigation route of the target UAV also includes the following steps: after the target UAV performs an inspection operation to obtain multiple target natural features of multiple inspection objects, a matching operation is performed on the initial first natural feature set and the second natural feature set to obtain a matching result between the two. If the above matching result is that the first natural feature set and the second natural feature set are inconsistent, it is necessary to determine the different natural features between the first natural feature set and the second natural feature set as the target natural features, and then obtain the target inspection objects corresponding to the above target natural features, and perform an update operation on the multiple inspection objects based on the above target inspection objects.

[0075] Specifically, when the landmark navigation analysis part of the edge computing server matches the database data (i.e., the first natural feature set) with the collected data (i.e., the second natural feature set), if the database data (i.e., the first natural feature set) does not match the collected data (i.e., the second natural feature set), it is determined that the inspection object has changed (such as: equipment has been adjusted), and the collected data is saved in the database for manual identification by the background (the registration process is executed after identification), and at the same time, the target drone is controlled to inspect the next inspection object according to the inspection plan.

[0076] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, 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, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a grid device, etc.) to execute the methods of various embodiments of the present invention.

[0077] In this embodiment, a device for determining a drone navigation route is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0078] Figure 3 is a structural block diagram of a device 300 for determining a navigation route of a drone according to one embodiment of the present invention. Figure 3 As shown, the device includes: a first acquisition module 301, a first execution module 302, a comparison module 303 and a first determination module 304.

[0079] A first acquisition module 301 is used to acquire a first natural feature set of multiple inspection objects, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects;

[0080] The first execution module 302 is used to control the target UAV to perform inspection operations on multiple inspection objects to obtain a second natural feature set;

[0081] A comparison module 303, used to compare the first natural feature set and the second natural feature set to obtain a comparison result;

[0082] The first determination module 304 is used to determine the target navigation route of the target UAV according to the comparison result.

[0083] Optionally, the first acquisition module 301 includes: a first acquisition unit, used to acquire multiple target positions of multiple inspection objects; and a first determination unit, used to determine multiple initial natural features according to the multiple target positions.

[0084] Optionally, the first execution module 302 includes: a second acquisition unit, used to acquire the inspection channel information of the target UAV; a second determination unit, used to determine the initial navigation route of the target UAV based on multiple target positions and inspection channel information; and a first execution unit, used to control the target UAV to perform inspection operations on multiple inspection objects based on the initial navigation route.

[0085] Optionally, the first execution module 302 further includes: a third acquisition unit, configured to acquire multiple target natural features of the multiple inspection objects based on a monocular vision algorithm in response to the target drone inspecting multiple inspection objects.

[0086] Optionally, the first determination module 304 includes: a third determination unit, configured to determine the initial navigation route as the target navigation route in response to the comparison result being that the first natural feature set and the second natural feature set are consistent.

[0087] Optionally, the first determination module 304 also includes: a second execution unit, used to perform an update operation on the initial navigation route based on the second natural feature set in response to the comparison result being inconsistent between the first natural feature set and the second natural feature set, to obtain an updated navigation route; and a fourth determination unit, used to determine that the updated navigation route is the target navigation route.

[0088] Optionally, the device 300 for determining the drone navigation route also includes: a second execution module, used to perform a matching operation on the first natural feature set and the second natural feature set to obtain a matching result; a second determination module, used to determine the target natural feature in response to the matching result being that the first natural feature set and the second natural feature set are inconsistent; a second acquisition module, used to acquire the target inspection object corresponding to the target natural feature; and a third execution module, used to perform an update operation on multiple inspection objects based on the target inspection object.

[0089] An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the above-mentioned method for determining the navigation route of the unmanned aerial vehicle.

[0090] Optionally, in this embodiment, the electronic device may be configured to store a computer program for performing the following steps:

[0091] Step S102, obtaining a first natural feature set of multiple inspection objects, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects;

[0092] Step S104, controlling the target UAV to perform inspection operations on multiple inspection objects to obtain a second natural feature set;

[0093] Step S106, comparing the first natural feature set and the second natural feature set to obtain a comparison result;

[0094] Step S108, determining the target navigation route of the target UAV according to the comparison result.

[0095] Optionally, when the processor executes the program, the following steps are further implemented: obtaining multiple target positions of multiple inspection objects; and determining multiple initial natural features according to the multiple target positions.

[0096] Optionally, when the processor executes the program, the following steps are also implemented: obtaining inspection channel information of the target UAV; determining an initial navigation route of the target UAV based on multiple target positions and inspection channel information; and controlling the target UAV to perform inspection operations on multiple inspection objects based on the initial navigation route.

[0097] Optionally, when the processor executes the program, the following steps are also implemented: in response to the target drone inspecting multiple inspection objects, multiple target natural features of the multiple inspection objects are acquired based on a monocular vision algorithm.

[0098] Optionally, when executing the program, the processor further implements the following steps: in response to the comparison result being that the first natural feature set and the second natural feature set are consistent, determining the initial navigation route as the target navigation route.

[0099] Optionally, the processor further implements the following steps when executing the program: in response to the comparison result that the first natural feature set and the second natural feature set are inconsistent, performing an update operation on the initial navigation route based on the second natural feature set to obtain an updated navigation route; and determining that the updated navigation route is the target navigation route.

[0100] Optionally, when the processor executes the program, the following steps are also implemented: performing a matching operation on the first natural feature set and the second natural feature set to obtain a matching result; in response to the matching result being that the first natural feature set and the second natural feature set are inconsistent, determining a target natural feature; obtaining a target inspection object corresponding to the target natural feature; and performing an update operation on multiple inspection objects based on the target inspection object.

[0101] An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned substation environment analysis method when running on a computer or a processor.

[0102] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0103] Step S102, obtaining a first natural feature set of multiple inspection objects, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects;

[0104] Step S104, controlling the target UAV to perform inspection operations on multiple inspection objects to obtain a second natural feature set;

[0105] Step S106, comparing the first natural feature set and the second natural feature set to obtain a comparison result;

[0106] Step S108, determining the target navigation route of the target UAV according to the comparison result.

[0107] Optionally, the storage medium is configured to store program codes for executing the following steps: acquiring multiple target positions of multiple inspection objects; and determining multiple initial natural features according to the multiple target positions.

[0108] Optionally, the storage medium is configured to store program code for executing the following steps: obtaining inspection channel information of the target UAV; determining an initial navigation route of the target UAV based on multiple target locations and inspection channel information; and controlling the target UAV to perform inspection operations on multiple inspection objects based on the initial navigation route.

[0109] Optionally, the storage medium is configured to store program code for executing the following steps: in response to the target drone inspecting multiple inspection objects, acquiring multiple target natural features of the multiple inspection objects based on a monocular vision algorithm.

[0110] Optionally, the storage medium is configured to store program code for executing the following steps: in response to the comparison result being that the first natural feature set and the second natural feature set are consistent, determining the initial navigation route as the target navigation route.

[0111] Optionally, the storage medium is configured to store program code for executing the following steps: in response to a comparison result that the first natural feature set and the second natural feature set are inconsistent, performing an update operation on the initial navigation route based on the second natural feature set to obtain an updated navigation route; and determining that the updated navigation route is the target navigation route.

[0112] Optionally, the storage medium is configured to store program code for executing the following steps: performing a matching operation on a first natural feature set and a second natural feature set to obtain a matching result; in response to the matching result being that the first natural feature set and the second natural feature set are inconsistent, determining a target natural feature; obtaining a target inspection object corresponding to the target natural feature; and performing an update operation on multiple inspection objects based on the target inspection object.

[0113] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0114] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] In some embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0116] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0117] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a grid device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc., which can store program codes.

[0119] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining a navigation route of an unmanned aerial vehicle, characterized in that: include: Acquire a first natural feature set of multiple inspection objects, wherein the first natural feature set includes multiple initial natural features of the multiple inspection objects; Controlling the target UAV to perform inspection operations on the multiple inspection objects to obtain a second natural feature set; Comparing the first natural feature set with the second natural feature set to obtain a comparison result; The target navigation route of the target UAV is determined according to the comparison result.

2. The method for determining the navigation route of an unmanned aerial vehicle according to claim 1, characterized in that: Acquiring the first natural feature set of the multiple inspection objects includes: Acquire multiple target positions of the multiple inspection objects; The plurality of initial natural features are determined according to the plurality of target locations.

3. The method for determining the navigation route of an unmanned aerial vehicle according to claim 2, characterized in that: Controlling the target UAV to perform the inspection operation on the multiple inspection objects to obtain the second natural feature set includes: Obtaining inspection channel information of the target UAV; Determining an initial navigation route of the target UAV according to the multiple target locations and the inspection channel information; The target UAV is controlled to perform inspection operations on the multiple inspection objects based on the initial navigation route.

4. The method for determining the navigation route of an unmanned aerial vehicle according to claim 3, characterized in that: The second natural feature set includes a plurality of target natural features, wherein the method further includes: In response to the target drone inspecting the multiple inspection objects, multiple target natural features of the multiple inspection objects are acquired based on a monocular vision algorithm.

5. The method for determining the navigation route of an unmanned aerial vehicle according to claim 3, characterized in that: Determining the target navigation route of the target UAV according to the comparison result includes: In response to the comparison result being that the first natural feature set and the second natural feature set are consistent, the initial navigation route is determined to be the target navigation route.

6. The method for determining the navigation route of an unmanned aerial vehicle according to claim 5, characterized in that: The method further comprises: In response to the comparison result being that the first natural feature set and the second natural feature set are inconsistent, performing an update operation on the initial navigation route based on the second natural feature set to obtain an updated navigation route; The updated navigation route is determined to be the target navigation route.

7. The method for determining the navigation route of an unmanned aerial vehicle according to claim 1, characterized in that: The method further comprises: Performing a matching operation on the first natural feature set and the second natural feature set to obtain a matching result; In response to the matching result being that the first natural feature set and the second natural feature set are inconsistent, determining a target natural feature; Obtaining a target inspection object corresponding to the target natural feature; An update operation is performed on the plurality of inspection objects based on the target inspection object.

8. A device for determining a navigation route of an unmanned aerial vehicle, characterized in that: include: A first acquisition module, configured to acquire a first natural feature set of a plurality of inspection objects, wherein the first natural feature set includes a plurality of initial natural features of the plurality of inspection objects; A first execution module is used to control the target UAV to perform an inspection operation on the multiple inspection objects to obtain a second natural feature set; A comparison module, used for comparing the first natural feature set with the second natural feature set to obtain a comparison result; The first determination module is used to determine a target navigation route of the target UAV according to the comparison result.

9. An electronic device, comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the method for determining the navigation route of the drone as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the method for determining the navigation route of the unmanned aerial vehicle as described in any one of claims 1 to 7 when running on a computer or a processor.

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