Unmanned aerial vehicle route planning method and related device

Abstract

The embodiment of the invention provides an unmanned aerial vehicle route planning method and a related device. The method comprises the following steps: acquiring target area inspection equipment data and a target area preset inspection route; splitting the target area preset inspection route into k sub target area preset inspection routes; calculating the total action resultant force of the unmanned aerial vehicle in the preset inspection route of the sub-target area by adopting an artificial potential field algorithm; determining a sub unmanned aerial vehicle route according to the total action resultant force and a corresponding sub target area preset inspection route; repeating the above steps until all sub unmanned aerial vehicle routes of the preset inspection routes of the k sub target areas are determined; and integrating all sub unmanned aerial vehicle routes to obtain an unmanned aerial vehicle route. According to the invention, the preset inspection route is divided into the plurality of sub inspection routes, the total action resultant force is calculated by using the artificial potential field algorithm, the optimal inspection route of the unmanned aerial vehicle is determined, the calculation amount is small, and the inspection route planning efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of unmanned aerial vehicle equipment, and in particular to a method for planning a route for an unmanned aerial vehicle and related devices. Background Art

[0002] With the rapid development of drone technology, drones are being used more and more widely in various fields. Especially in inspection operations, drones have become an indispensable tool due to their high efficiency and flexibility.

[0003] However, traditional UAV route planning methods require processing a large amount of spatial data and obstacle information when calculating complex terrain and fine areas, which results in extremely large amounts of calculations, resulting in low planning efficiency and inability to meet the needs of real-time inspections. Summary of the invention

[0004] The embodiments of the present application provide a method and related devices for planning a route for a UAV, which can determine the optimal inspection route for the UAV by splitting the preset inspection route of a target area into multiple preset inspection routes of sub-target areas, and using an artificial potential field algorithm to calculate the total combined force of the UAV in each sub-area, with a small amount of calculation, thereby improving the efficiency of UAV route planning for fine inspection areas.

[0005] A first aspect of an embodiment of the present application provides a method for planning a route for a drone, the method comprising:

[0006] Obtain inspection equipment data and preset inspection routes for the target area;

[0007] According to the inspection equipment data of the target area, the preset inspection route of the target area is split into k preset inspection routes of sub-target areas;

[0008] According to the inspection route preset in the sub-target area, an artificial potential field algorithm is used to calculate the total combined force of the drone in the inspection route preset in the sub-target area;

[0009] Preset inspection routes based on the total combined force and the corresponding sub-target areas, and determine the sub-UAV route;

[0010] Repeat the steps of calculating the total combined force of the drones in the preset inspection routes of the sub-target areas by using an artificial potential field algorithm according to the preset inspection routes of the sub-target areas, and determining the routes of the sub-drones according to the moving distances of the sub-drones until all the routes of the sub-drones of the preset inspection routes of the k sub-target areas are determined;

[0011] Integrate all sub-UAV routes to obtain the UAV route.

[0012] Furthermore, the method of calculating the total combined force of the drones in the preset inspection route of the sub-target area by using an artificial potential field algorithm according to the preset inspection route of the sub-target area includes:

[0013] Calculate a first force according to the preset inspection route of the sub-target area, wherein the first force is the gravitational force of the end point of the preset inspection route of the sub-target area on the drone;

[0014] Calculate a second force according to the preset inspection route of the sub-target area, wherein the second force is a repulsive force of an obstacle point in the preset inspection route of the sub-target area on the drone;

[0015] The first acting force and the second acting force are combined to obtain a total acting force.

[0016] Furthermore, the calculation formula of the first acting force is as follows:

[0017]

[0018] Among them, U att (q) is the first force, η is the gravitational coefficient, ρ(q,q g ) is the position of the drone q and the position of the target point q g The distance between.

[0019] Furthermore, the preset inspection route according to the total combined force and the corresponding sub-target area to determine the sub-UAV route includes:

[0020] According to the total combined force, the single movement distance of the UAV is calculated;

[0021] Generate a single series of track point data according to the preset inspection route of the sub-target area and the single movement distance of the drone;

[0022] The single series of track point data are integrated to determine the route of the sub-UAV.

[0023] Furthermore, the single movement distance of the drone is calculated based on the total resultant force, including: multiplying the total resultant force by a preset step coefficient to obtain the single movement distance of the drone.

[0024] In this example, the preset inspection route of the target area is split into multiple preset inspection routes of sub-target areas, and the artificial potential field algorithm is used to calculate the total resultant force of the drone in each sub-area. By simulating the concept of potential field in physics, the target point is regarded as the source of gravity and the obstacle is regarded as the source of repulsion. The movement of the drone in the potential field is determined by the combined force of gravity and repulsion, and the sub-drone route is calculated by the combined force. Finally, all the sub-drone routes are integrated to determine the total drone route, with a small amount of calculation, thereby improving the efficiency of drone route planning for fine inspection areas.

[0025] A second aspect of an embodiment of the present application provides a drone route planning device, the device comprising:

[0026] An acquisition unit, used to acquire inspection equipment data of a target area and a preset inspection route of the target area;

[0027] A first processing unit is used to make a difference value decision of the power equipment in the target inspection area according to the first inspection equipment data and the second inspection equipment data, and obtain a regional inspection precision decision result;

[0028] A second processing unit is used to calculate the total combined force of the drone in the preset inspection route of the sub-target area using an artificial potential field algorithm according to the preset inspection route of the sub-target area;

[0029] A third processing unit is used to preset an inspection route according to the total combined force and the corresponding sub-target area, and determine the sub-UAV route;

[0030] The summary unit is used to integrate all sub-UAV routes to obtain the detailed route of UAV inspection.

[0031] Further, in the aspect of calculating the total combined force of the drone in the preset inspection route of the sub-target area by using an artificial potential field algorithm according to the preset inspection route of the sub-target area, the second processing unit is used to:

[0032] Calculate a first force according to the preset inspection route of the sub-target area, wherein the first force is the gravitational force of the end point of the preset inspection route of the sub-target area on the drone;

[0033] Calculate a second force according to the preset inspection route of the sub-target area, wherein the second force is a repulsive force of an obstacle point in the preset inspection route of the sub-target area on the drone;

[0034] The first acting force and the second acting force are combined to obtain a total acting force.

[0035] Further, in the aspect of calculating the first force according to the preset inspection route of the sub-target area, the calculation formula of the first force in the second processing unit is as follows:

[0036]

[0037] Among them, U att (q) is the first force, η is the gravitational coefficient, ρ(q,q g ) is the position of the drone q and the position of the target point q g The distance between.

[0038] Further, in terms of presetting the inspection route according to the total combined force and the corresponding sub-target area to determine the route of the sub-UAV, the third processing unit is used to:

[0039] According to the total combined force, the single movement distance of the UAV is calculated;

[0040] Generate a single series of track point data according to the preset inspection route of the sub-target area and the single movement distance of the drone;

[0041] The single series of track point data are integrated to determine the route of the sub-UAV.

[0042] A third aspect of an embodiment of the present application provides a terminal, comprising a processor, an input device, an output device and a memory, wherein the processor, input device, output device and memory are interconnected, wherein the memory is used to store a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the step instructions of the drone route planning method in the first aspect of the embodiment of the present application.

[0043] The fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the above-mentioned computer-readable storage medium stores a computer program for electronic data exchange, wherein the above-mentioned computer program enables the computer to execute part or all of the steps described in the drone route planning method in the first aspect of the embodiment of the present application.

[0044] A fifth aspect of the embodiments of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the method for planning a route for a drone in the first aspect of the embodiments of the present application. The computer program product may be a software installation package. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A schematic diagram of the overall process of a method for planning a route for a drone is provided for an embodiment of the present application;

[0047] Figure 2 A specific flow chart of determining the sub-drone routes of a drone route planning method is provided for an embodiment of the present application;

[0048] Figure 3 A schematic diagram of a drone avoiding obstacles on an inspection route planned in a method for fine inspection route planning is provided for an embodiment of the present application;

[0049] Figure 4 A structural schematic diagram of a patrol inspection fine route planning device is provided for an embodiment of the present application;

[0050] Figure 5 A schematic diagram of the structure of a terminal provided in an embodiment of the present application;

[0051] Reference numerals:

[0052] Acquisition unit-1, first processing unit-2, second processing unit-3, third processing unit-4, summary unit-5. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0054] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. 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 limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0055] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0056] In order to better understand the UAV route planning method provided in the embodiment of the present application, the following first briefly introduces the scenario in which the UAV route planning method is applied. In the process of planning the inspection flight route of the UAV for the fine inspection area, since the fine area to be inspected by the UAV often contains complex geographical features and various obstacles, such as high-rise buildings, telephone poles, trees, etc., these elements must be fully considered in the route planning process to avoid the UAV from colliding or deviating from the predetermined route. When dealing with such complex environments, traditional route planning algorithms need to traverse all possible paths and calculate the feasibility of each path, which is time-consuming and easily affected by computing resource limitations, and the efficiency of route planning is low.

[0057] The UAV route planning method is applied to the Cesium 3D earth visualization platform. Figure 1 The overall process diagram of a UAV route planning method is shown in FIG. Figure 1 As shown, including:

[0058] S1. Obtain inspection equipment data of the target area and preset inspection routes of the target area.

[0059] S2. According to the inspection equipment data of the target area, the preset inspection route of the target area is split into k preset inspection routes of sub-target areas. In this embodiment, preferably, the waypoint flight order planned by the ant colony algorithm is used to split the entire route into simple obstacle avoidance planning tasks from one target point to the next target point, and k preset inspection routes of sub-target areas are obtained. The point cloud data between two points is intercepted by a plane of preset thickness as an obstacle point, so as to reduce the amount of calculation.

[0060] S3. According to the preset inspection route of the sub-target area, the artificial potential field algorithm is used to calculate the total combined force of the drone in the preset inspection route of the sub-target area. The initial position of the drone is placed at the starting point, and the gravitational force of the end point on the drone and the repulsive force of the obstacle point on the drone are calculated respectively, as well as the combined force of all forces, specifically including:

[0061] S301. Calculate a first force according to a preset inspection route of the sub-target area, wherein the first force is the gravitational force of an end point in the preset inspection route of the sub-target area on the drone.

[0062] In this example, the calculation formula for the first force is as follows:

[0063]

[0064] Among them, U att (q) is the first force, η is the gravitational coefficient, ρ(q,q g ) is the position of the drone q and the position of the target point q g The distance between.

[0065] S302, calculating a second force according to the preset inspection route of the sub-target area, wherein the second force is the repulsive force of the obstacle point in the preset inspection route of the sub-target area on the drone. In this example, the calculation formula of the second force is as follows:

[0066]

[0067] Where k is the repulsion coefficient, ρ(q,q 0 ) is the position q of the drone and the obstacle q 0 The distance between.

[0068] S303: Combine the first acting force and the second acting force to obtain a total acting force. The total acting force is the vector sum of the attraction and repulsion at a certain position. In this example, the calculation formula of the total acting force is as follows:

[0069] U total =U att +U rep

[0070] Among them, U total is the total force, U att is the first force, U rep The UAV moves according to this synthetic force field, eventually tending to the target position and avoiding obstacles.

[0071] S4. Preset an inspection route based on the total combined force and the corresponding sub-target area to determine the sub-UAV route. Figure 2 The specific process diagram of determining the sub-drone route of a drone route planning method is shown. Figure 2 As shown, including:

[0072] S401, calculating the single movement distance of the drone according to the total resultant force, specifically including: moving the drone in the direction of the total resultant force on the preset inspection route of the sub-target area, and calculating the total resultant force by multiplying the preset step coefficient.

[0073] S402. Generate a single series of track point data based on the preset inspection route of the sub-target area and the single movement distance of the drone. When the distance between the position of the drone and the target point in the preset inspection route of the sub-target area is less than a given threshold, stop generating the single series of track point data and use the currently generated series of track point data as the single series of track point data.

[0074] S403: Integrate the single series of track point data to determine the route of the sub-UAV.

[0075] Repeat step S3 to step S4 until all sub-UAV routes of the preset inspection routes of the k sub-target areas are determined. In the preferred embodiment, during the iteration process, it may fall into a local minimum and fail to reach the target. This usually occurs when an obstacle is close to the target point, and the second force as a repulsive force may be greater than the first force as an attractive force, causing the UAV to be unable to continue flying to the target point. The algorithm determines that if the magnitude of the second force is greater than the set threshold, the current state is trapped in a local minimum. At this time, the second force in the Z-axis direction is temporarily ignored, and a two-dimensional obstacle avoidance planning is performed on the horizontal plane to enable the UAV to jump out of the local minimum.

[0076] S5. Integrate all sub-drone routes to obtain the drone route. In this example, the simulation results are as follows: Figure 3 As shown, Figure 3 A schematic diagram of a drone avoiding obstacles in a planned inspection route in a drone route planning method is shown. After completing the detailed area drone inspection route planning, the planned drone inspection route can avoid obstacles.

[0077] In this example, the preset inspection route of the target area is split into multiple preset inspection routes of sub-target areas, and the artificial potential field algorithm is used to calculate the total resultant force of the drone in each sub-area. By simulating the concept of potential field in physics, the target point is regarded as the source of gravity and the obstacle is regarded as the source of repulsion. The movement of the drone in the potential field is determined by the combined force of gravity and repulsion, and the sub-drone route is calculated by the combined force. Finally, all the sub-drone routes are integrated to determine the total drone route, with a small amount of calculation, thereby improving the efficiency of drone route planning for fine inspection areas.

[0078] In line with the above, see Figure 4 , Figure 4 A schematic diagram of the structure of a drone route planning is provided for the embodiment of the present application. Figure 4 As shown, the device comprises:

[0079] An acquisition unit, used to acquire inspection equipment data of a target area and a preset inspection route of the target area;

[0080] A first processing unit is used to make a difference value decision of the power equipment in the target inspection area according to the first inspection equipment data and the second inspection equipment data, and obtain a regional inspection precision decision result;

[0081] A second processing unit is used to calculate the total combined force of the drone in the preset inspection route of the sub-target area using an artificial potential field algorithm according to the preset inspection route of the sub-target area;

[0082] A third processing unit is used to preset an inspection route according to the total combined force and the corresponding sub-target area, and determine the sub-UAV route;

[0083] The summary unit is used to integrate all sub-UAV routes to obtain the detailed route of UAV inspection.

[0084] In a possible implementation, in the aspect of calculating the total resultant force of the drone in the preset inspection route of the sub-target area by using an artificial potential field algorithm according to the preset inspection route of the sub-target area, the second processing unit is used to:

[0085] Calculate a first force according to the preset inspection route of the sub-target area, wherein the first force is the gravitational force of the end point of the preset inspection route of the sub-target area on the drone;

[0086] Calculate a second force according to the preset inspection route of the sub-target area, wherein the second force is a repulsive force of an obstacle point in the preset inspection route of the sub-target area on the drone;

[0087] The first acting force and the second acting force are combined to obtain a total acting force.

[0088] In a possible implementation, in the aspect of calculating the first force according to the inspection route preset in the sub-target area, the calculation formula of the first force in the second processing unit is as follows:

[0089]

[0090] Among them, U att (q) is the first force, η is the gravitational coefficient, ρ(q,q g ) is the position of the drone q and the position of the target point q g The distance between.

[0091] In a possible implementation, in terms of presetting the inspection route according to the total combined force and the corresponding sub-target area and determining the route of the sub-UAV, the third processing unit is used to:

[0092] According to the total combined force, the single movement distance of the UAV is calculated;

[0093] Generate a single series of track point data according to the preset inspection route of the sub-target area and the single movement distance of the drone;

[0094] The single series of track point data are integrated to determine the route of the sub-UAV.

[0095] For the above embodiments, please refer to Figure 5 , Figure 5 A schematic diagram of the structure of a terminal provided in an embodiment of the present application, as shown in the figure, includes a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the program includes instructions for executing the following steps;

[0096] Obtain inspection equipment data and preset inspection routes for the target area;

[0097] According to the inspection equipment data of the target area, the preset inspection route of the target area is split into k preset inspection routes of sub-target areas;

[0098] According to the inspection route preset in the sub-target area, an artificial potential field algorithm is used to calculate the total combined force of the drone in the inspection route preset in the sub-target area;

[0099] Preset inspection routes based on the total combined force and the corresponding sub-target areas, and determine the sub-UAV route;

[0100] Repeat the steps of calculating the total combined force of the drones in the preset inspection routes of the sub-target areas by using an artificial potential field algorithm according to the preset inspection routes of the sub-target areas, and determining the routes of the sub-drones according to the moving distances of the sub-drones until all the routes of the sub-drones of the preset inspection routes of the k sub-target areas are determined;

[0101] Integrate all sub-UAV routes to obtain the UAV route.

[0102] In this example, the preset inspection route of the target area is split into multiple preset inspection routes of sub-target areas, and the artificial potential field algorithm is used to calculate the total resultant force of the drone in each sub-area. By simulating the concept of potential field in physics, the target point is regarded as the source of gravity and the obstacle is regarded as the source of repulsion. The movement of the drone in the potential field is determined by the combined force of gravity and repulsion, and the sub-drone route is calculated by the combined force. Finally, all the sub-drone routes are integrated to determine the total drone route, with a small amount of calculation, thereby improving the efficiency of drone route planning for fine inspection areas.

[0103] In addition, this embodiment provides specific route strategy solutions for different scenarios in drone power grid inspection, targeting different scenarios of power transmission and distribution, specifically including:

[0104] Power transmission scenario:

[0105] Fine Mode / Infrared:

[0106] According to the inspection target towers A, B, C, ....N, etc., a safe and efficient complete route between the airport, the tower, and the airport is intelligently planned. The safety strategies include: safety strategy for airport arrival at the tower and safety strategy for transfer between towers.

[0107] Airport-tower safety strategy: Based on the intelligent algorithm strategy mentioned above, from the airport to the first tower, fly in a straight line along a fixed height from the ground to the target location, intelligently crossing dangerous situations such as high objects and mountains along the way; similarly, from the last tower to the airport, fly in a straight line back to the airport.

[0108] Tower-to-tower safety strategy: For two adjacent towers, fly directly from the last waypoint of the first tower to the first waypoint of the second tower; for two non-adjacent towers, fly from the last waypoint of the first tower to the top of the next tower, pass the tops of the towers along the line until reaching the top of the second tower, and then execute the first waypoint of the second tower.

[0109] According to the refined route of the tower, the complete route is automatically spliced ​​to ensure flight safety and improve inspection efficiency.

[0110] 1.2 Channel Mode:

[0111] According to the inspection target towers A, B, C, ....N, etc., a safe and efficient complete route between the airport, the tower, and the airport is intelligently planned. The safety strategies include: safety strategy for airport arrival at the tower and safety strategy for transfer between towers.

[0112] Airport-tower safety strategy: Based on the intelligent algorithm strategy mentioned above, from the airport to the first tower, the aircraft flies in a straight line at a fixed height from the ground to the target location, intelligently crossing dangerous situations such as high objects and mountains along the way; similarly, from the last tower to the airport, the aircraft also flies in a straight line back to the airport based on the intelligent algorithm.

[0113] Tower-to-tower intelligent algorithm strategy: The aircraft flies from tower A to tower N directly above the tower. The flight strategy takes photos at regular intervals to generate channel inspection photos.

[0114] 2. Power distribution

[0115] 2.1 Refined mode:

[0116] According to the inspection target towers A, B, C, ....N, etc., a safe and efficient complete route between the airport, the tower, and the airport is intelligently planned. The safety strategies include: safety strategy for airport arrival at the tower and safety strategy for transfer between towers.

[0117] Airport-tower safety strategy: Based on the intelligent algorithm strategy mentioned above, from the airport to the first tower, the aircraft flies in a straight line at a fixed height from the ground to the target location, intelligently crossing dangerous situations such as high objects and mountains along the way; similarly, from the last tower to the airport, the aircraft also flies in a straight line back to the airport based on the intelligent algorithm.

[0118] Tower-to-tower intelligent algorithm strategy: The aircraft flies from tower A to tower N directly above the tower. The flight strategy takes fixed photos of each tower to generate detailed inspection photos.

[0119] Right angle: Take 3 fixed inspection photos.

[0120] First photo: A shot of the passage directly in front of the tower.

[0121] The second photo: A photo of the tower taken from the front.

[0122] The third photo: A photo of the tower taken vertically downward from the top of the tower.

[0123] Tension resistance: 6 fixed inspection photos are taken.

[0124] First photo: A shot of the passage directly in front of the tower.

[0125] Second photo: A photo of the tower taken from the front.

[0126] The third photo: A photo of the tower taken vertically downward from the top of the tower.

[0127] The fourth photo: A photo of the tower taken from the left side.

[0128] Fifth photo: A photo of the tower taken from the right side.

[0129] The sixth photo: A photo of the tower taken from the back.

[0130] 2.2 Channel Mode:

[0131] According to the inspection target towers A, B, C, ....N, etc., a safe and efficient complete route between the airport, the tower, and the airport is intelligently planned. The safety strategies include: safety strategy for airport arrival at the tower and safety strategy for transfer between towers.

[0132] Airport-tower safety strategy: Based on the intelligent algorithm strategy mentioned above, from the airport to the first tower, the aircraft flies in a straight line at a fixed height from the ground to the target location, intelligently crossing dangerous situations such as high objects and mountains along the way; similarly, from the last tower to the airport, the aircraft also flies in a straight line back to the airport based on the intelligent algorithm.

[0133] Tower-to-tower intelligent algorithm strategy: The aircraft flies from tower A to tower N directly above the tower. The flight strategy takes photos at regular intervals to generate channel inspection photos.

[0134] 2.3 Infrared:

[0135] According to the inspection target towers A, B, C, ....N, etc., a safe and efficient complete route between the airport, the tower, and the airport is intelligently planned. The safety strategies include: safety strategy for airport arrival at the tower and safety strategy for transfer between towers.

[0136] Airport-tower safety strategy: Based on the intelligent algorithm strategy mentioned above, from the airport to the first tower, the aircraft flies in a straight line at a fixed height from the ground to the target location, intelligently crossing dangerous situations such as high objects and mountains along the way; similarly, from the last tower to the airport, the aircraft also flies in a straight line back to the airport based on the intelligent algorithm.

[0137] Tower-to-tower safety strategy: For two adjacent towers, fly directly from the last waypoint of the first tower to the first waypoint of the second tower; for two non-adjacent towers, fly from the last waypoint of the first tower to the top of the next tower, pass the tops of the towers along the line until reaching the top of the second tower, and then execute the first waypoint of the second tower.

[0138] According to the refined route of the tower, the complete route is automatically spliced ​​to ensure flight safety and improve inspection efficiency.

[0139] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that in order to realize the above functions, the terminal includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0140] The embodiment of the present application can divide the terminal into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0141] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the drone route planning methods recorded in the above method embodiments.

[0142] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program enables a computer to execute part or all of the steps of any one of the drone route planning methods recorded in the above method embodiments.

[0143] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0144] In the above embodiments, 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.

[0145] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as 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, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0146] 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 on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0147] In addition, the functional units in the various embodiments of the application 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 units may be implemented in the form of hardware or in the form of software program modules.

[0148] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially 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, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program codes.

[0149] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which can include: a flash drive, a read-only memory, a random access memory, a magnetic disk or an optical disk, etc.

[0150] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for planning a route for an unmanned aerial vehicle, characterized in that: Applied to Cesium 3D Earth visualization platform, including: Obtain inspection equipment data and preset inspection routes for the target area; According to the inspection equipment data of the target area, the preset inspection route of the target area is split into k preset inspection routes of sub-target areas; According to the inspection route preset in the sub-target area, an artificial potential field algorithm is used to calculate the total combined force of the drone in the inspection route preset in the sub-target area; Preset inspection routes based on the total combined force and the corresponding sub-target areas, and determine the sub-UAV route; Repeat the steps of calculating the total combined force of the drones in the preset inspection routes of the sub-target areas by using an artificial potential field algorithm according to the preset inspection routes of the sub-target areas, and determining the routes of the sub-drones according to the moving distances of the sub-drones until all the routes of the sub-drones of the preset inspection routes of the k sub-target areas are determined; Integrate all sub-UAV routes to obtain the UAV route.

2. The method for planning a UAV route according to claim 1, characterized in that: The method of calculating the total combined force of the drones in the preset inspection route of the sub-target area by using an artificial potential field algorithm according to the preset inspection route of the sub-target area includes: Calculate a first force according to the preset inspection route of the sub-target area, wherein the first force is the gravitational force of the end point of the preset inspection route of the sub-target area on the drone; Calculate a second force according to the preset inspection route of the sub-target area, wherein the second force is a repulsive force of an obstacle point in the preset inspection route of the sub-target area on the drone; The first acting force and the second acting force are combined to obtain a total acting force.

3. The method for planning a UAV route according to claim 2, characterized in that: The calculation formula of the first force is as follows: Among them, U att (q) is the first force, η is the gravitational coefficient, ρ(q,q g ) is the position of the drone q and the position of the target point q g The distance between.

4. The method for planning a UAV route according to claim 1, characterized in that: The presetting of the inspection route according to the total combined force and the corresponding sub-target area to determine the sub-UAV route includes: According to the total combined force, the single movement distance of the UAV is calculated; Generate a single series of track point data according to the preset inspection route of the sub-target area and the single movement distance of the drone; The single series of track point data are integrated to determine the route of the sub-UAV.

5. The method for planning a UAV route according to claim 4, characterized in that: The calculating the single movement distance of the drone according to the total resultant force includes: multiplying the total resultant force by a preset step length coefficient to obtain the single movement distance of the drone.

6. A drone route planning device, characterized in that: The device comprises: An acquisition unit, used to acquire inspection equipment data of a target area and a preset inspection route of the target area; A first processing unit is used to make a difference value decision of the power equipment in the target inspection area according to the first inspection equipment data and the second inspection equipment data, and obtain a regional inspection precision decision result; A second processing unit is used to calculate the total combined force of the drone in the preset inspection route of the sub-target area using an artificial potential field algorithm according to the preset inspection route of the sub-target area; A third processing unit is used to preset an inspection route according to the total combined force and the corresponding sub-target area, and determine the sub-UAV route; The summary unit is used to integrate all sub-UAV routes to obtain the detailed route of UAV inspection.

7. The unmanned aerial vehicle route planning device according to claim 6, characterized in that: In the aspect of calculating the total combined force of the drone in the preset inspection route of the sub-target area by using an artificial potential field algorithm according to the preset inspection route of the sub-target area, the second processing unit is used to: Calculate a first force according to the preset inspection route of the sub-target area, wherein the first force is the gravitational force of the end point of the preset inspection route of the sub-target area on the drone; Calculate a second force according to the preset inspection route of the sub-target area, wherein the second force is a repulsive force of an obstacle point in the preset inspection route of the sub-target area on the drone; The first acting force and the second acting force are combined to obtain a total acting force.

8. The UAV route planning device according to claim 6, characterized in that: In terms of presetting the inspection route according to the total combined force and the corresponding sub-target area to determine the route of the sub-UAV, the third processing unit is used to: According to the total combined force, the single movement distance of the UAV is calculated; Generate a single series of track point data according to the preset inspection route of the sub-target area and the single movement distance of the drone; The single series of track point data are integrated to determine the route of the sub-UAV.

9. A terminal, characterized in that: The method comprises a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the UAV route planning method as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the processor executes the drone route planning method as described in any one of claims 1 to 5.

Images