An unmanned aerial vehicle flight route planning method and device based on spatial grid value and a medium
By using a UAV flight path planning method based on airspace grid cost, which comprehensively considers the safety and distance between the UAV's starting grid and destination grid, the problem of insufficient consideration of both safety and distance in traditional methods is solved, and flight path planning with high safety and short distance is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- THE SECOND RES INST OF CIVIL AVIATION ADMINISTRATION OF CHINA
- Filing Date
- 2024-11-22
- Publication Date
- 2026-06-26
AI Technical Summary
Traditional drone flight path planning methods cannot simultaneously balance short flight distances and airspace safety, resulting in insufficient drone flight safety.
A UAV flight path planning method based on airspace grid cost value is adopted. By calculating the cumulative cost value and critical cost value of each target grid, the flight path with the lowest cost value is determined, taking into account the overall safety and distance between the UAV's starting grid and the destination grid.
This improves the safety of drone flights and reduces the total flight distance, ensuring safe and efficient drone flight in complex airspace environments.
Smart Images
Figure CN119245659B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of unmanned aerial vehicles (UAVs), and in particular to a method, device, and medium for UAV flight path planning based on airspace grid cost values. Background Technology
[0002] With the booming development of the drone industry, the number of drone flights is constantly increasing, and the vast majority of drones operate at low altitudes. This increasing density of low-altitude flights has led to a growing number of low-altitude safety issues. Therefore, it is necessary to plan drone flight routes more scientifically and rationally to improve the safety level of low-altitude operations.
[0003] Traditional flight path planning methods, such as the A* algorithm, are based on heuristic search algorithms and are suitable for quickly finding the shortest flight path. However, since the total flight distance of a UAV and the safety of the airspace it flies in are more important when flying in the airspace, it is necessary to comprehensively consider the cost of the entire flight path. Traditional flight path planning methods only perform local processing on the cost of the map grid corresponding to each airspace and other map grids adjacent to that grid. This results in the UAV's flight path not being able to simultaneously possess the characteristics of high safety and short total flight distance. Therefore, traditional flight path planning algorithms cannot meet the requirements of both total flight distance length and airspace safety. Summary of the Invention
[0004] To address the aforementioned technical problems, the technical solution adopted by this invention is as follows:
[0005] According to one aspect of this application, a method for planning UAV flight routes based on airspace grid cost values is provided and applied to a flight route planning system. The flight route planning system includes a target grid map corresponding to the target space. The target grid map includes a number of target grids and a grid coordinate system. Each target grid has grid coordinates in the grid coordinate system.
[0006] The UAV flight path planning method based on airspace grid cost values includes the following steps:
[0007] Step S100: In response to receiving a flight path planning request from the target UAV, obtain the starting grid coordinates of the starting grid and the destination grid coordinates of the destination grid included in the flight path planning request; the starting grid is the target grid in the target grid map where the starting position point of the target UAV is located; the destination grid is the target grid in the target grid map where the destination position point of the target UAV is located.
[0008] Step S200: Determine several initial flight paths from the starting grid to the destination grid based on the starting grid coordinates and the destination grid coordinates;
[0009] Step S300: Determine the cost of each target grid on each initial flight path based on the starting grid coordinates, the target grid coordinates, and the corresponding grid coordinates on each initial flight path.
[0010] Step S400: Determine the total value corresponding to each initial flight path based on the value of several target grids on each initial flight path.
[0011] Step S500: Determine the target flight route from several initial flight routes based on the total agency value corresponding to each initial flight route.
[0012] In one exemplary embodiment of this application, step S200 includes:
[0013] Step S210: The grid coordinates are (x... a ,y a ), (x a ,y b ), (x b ,y a ) and (x b ,y b The area composed of the target grid is defined as the target flight area; where x a The x-coordinate of the starting raster coordinates; y a The ordinate of the starting raster coordinates; x b y is the x-coordinate of the target raster coordinates; b The ordinate of the target raster coordinates;
[0014] Step S220: According to the preset flight path planning algorithm, starting from the starting grid, traverse each target grid in the target flight area until the destination grid is reached, so as to determine several initial flight paths.
[0015] In one exemplary embodiment of this application, step S300 includes:
[0016] Step S310: Based on the starting grid coordinates, the destination grid coordinates, and the corresponding grid coordinates on each initial flight path, determine the cumulative cost value from the starting grid to the target grid and the critical cost value from the target grid to the destination grid.
[0017] Step S320: Determine the cumulative cost coefficient and critical cost coefficient corresponding to any target grid based on the cumulative cost value and critical cost value corresponding to that target grid.
[0018] Step S330: Determine the target value of any target grid based on its cumulative cost value, critical cost value, cumulative cost coefficient, and critical cost coefficient.
[0019] In one exemplary embodiment of this application, step S310 includes:
[0020] Step S311: Obtain the grid coordinates of several target grids located between the starting grid and the destination grid on each initial flight path, and obtain the initial flight path coordinate list set E = (E1, E2, ..., E i ,...,E n ); where i = 1, 2, ..., n; n is the number of initial flight paths; E i This is a list of initial flight path coordinates corresponding to the i-th initial flight path;
[0021] E i =(E i1 E i2 ,...,E ig ,...,E if(i) ); g = 1, 2, ..., f(i); f(i) is the number of target grids located between the starting grid and the destination grid on the i-th initial flight path; E ig Let g be the grid coordinates of the g-th target grid located between the starting grid and the target grid on the i-th initial flight path;
[0022] E ig =(E ig1 E ig2 ); E ig1 For E ig The x-coordinate; E ig2 For E ig The ordinate;
[0023] Step S312: Determine the path from the starting grid to E along the i-th initial flight path. ig The cumulative cost H at the corresponding target grid ig =|E ig1 -x a |+|E ig2 -y a |;
[0024] Step S313: Determine the initial flight path from E along the i-th initial flight path. ig The corresponding critical value M from the target grid to the destination grid ig =((E) ig1 -x b ) 2 +(E ig2 -y b ) 2 ) 1 / 2 .
[0025] In one exemplary embodiment of this application, step S320 includes:
[0026] Step S321, if H ig ≤M ig Then determine E ig The position coefficient T at the corresponding target grid ig =M ig / H ig Otherwise, determine E. ig The position coefficient T at the corresponding target grid ig =H ig / M ig ;
[0027] Step S322, Determine E ig The cumulative cost coefficient of the corresponding target raster Where e is the natural constant;
[0028] Step S323, Determine E ig The corresponding key cost coefficient W of the target grid ig =1-U ig .
[0029] In one exemplary embodiment of this application, step S330 includes:
[0030] Step S331, according to U ig and W ig Determine E ig The target value Z of the corresponding target grid ig =U ig ×H ig +W ig ×M ig .
[0031] In one exemplary embodiment of this application, step S400 includes:
[0032] Step S410: Determine the total value B corresponding to the i-th initial flight path based on the target value of each target grid on the i-th initial flight path. i =∑ f(i) g＝1 Z ig .
[0033] In one exemplary embodiment of this application, step S500 includes:
[0034] Step S510: Set MIN(B1,B2,...,B) to... i ,...,B n The initial flight path corresponding to ) is determined as the target flight path; where MIN() is a preset minimum value determination function.
[0035] According to one aspect of this application, a non-transitory computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored in the storage medium, the at least one instruction or the at least one program being loaded and executed by a processor to implement the aforementioned UAV flight path planning method based on airspace grid cost value.
[0036] According to one aspect of this application, an electronic device is provided, including a processor and the aforementioned non-transitory computer-readable storage medium.
[0037] The present invention has at least the following beneficial effects:
[0038] The UAV flight path planning method based on airspace grid cost value of the present invention determines several initial flight paths from the starting grid to the destination grid based on the starting grid coordinates and the destination grid coordinates of the target UAV. Then, based on the starting grid coordinates, the destination grid coordinates, and the corresponding grid coordinates of each initial flight path, the cost value of each target grid on each initial flight path is determined. Based on the cost values of the several target grids on each initial flight path, the total cost value corresponding to each initial flight path is determined. Based on the total cost value corresponding to each initial flight path, the target flight path is determined from the several initial flight paths. By performing overall cost value calculation on each initial flight path, the cost value of the finally determined target flight path is minimized. Furthermore, the determined target flight path satisfies both the requirements of high safety and short total flight distance, thereby improving the safety of UAVs flying according to the target flight path. Attached Figure Description
[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0040] Figure 1 A flowchart of a UAV flight path planning method based on airspace grid cost value provided in an embodiment of the present invention. Detailed Implementation
[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0042] With the increasing number of drones in flight, flight management is necessary for flight safety, which involves flight path planning to ensure each drone flies according to its designated route. The ultra-low altitude airspace environment in which drones operate is becoming increasingly complex and variable with the development of the drone industry. Therefore, to ensure the safety of drones during flight, reasonable and safe flight path planning is required. This invention proposes a drone flight path planning method based on airspace grid cost values.
[0043] A method for planning UAV flight routes based on airspace grid cost values is applied to a flight route planning system. The flight route planning system includes a target grid map corresponding to the target space. The target grid map includes several target grids and has a corresponding grid coordinate system. Each target grid has corresponding grid coordinates in the grid coordinate system.
[0044] like Figure 1 As shown, the UAV flight path planning method based on airspace grid cost value described in this application includes the following steps:
[0045] Step S100: In response to receiving the flight path planning request from the target UAV, obtain the starting grid coordinates of the starting grid and the destination grid coordinates of the destination grid included in the flight path planning request.
[0046] The starting grid is the target grid in the target grid map where the starting position of the target UAV is located, and the destination grid is the target grid in the target grid map where the destination position of the target UAV is located.
[0047] Step S200: Determine several initial flight paths from the starting grid to the destination grid based on the starting grid coordinates and the destination grid coordinates;
[0048] Furthermore, step S200 includes steps S210-S220:
[0049] Step S210: The grid coordinates are (x... a ,y a ), (x a ,y b ), (x b ,y a ) and (x b ,y b The area composed of the target grid is defined as the target flight area; where x a The x-coordinate of the starting raster coordinates; y a The ordinate of the starting raster coordinates; x b y is the x-coordinate of the target raster coordinates; bThe ordinate of the target raster coordinates;
[0050] Step S220: According to the preset flight path planning algorithm, starting from the starting grid, traverse each target grid in the target flight area until the destination grid is reached, so as to determine several initial flight paths.
[0051] The preset flight route planning algorithm can adopt existing path planning algorithms, such as the A* algorithm.
[0052] Step S300: Determine the cost of each target grid on each initial flight path based on the starting grid coordinates, the target grid coordinates, and the corresponding grid coordinates on each initial flight path.
[0053] In one exemplary embodiment of this application, step S300 includes:
[0054] Step S310: Based on the starting grid coordinates, the destination grid coordinates, and the corresponding grid coordinates on each initial flight path, determine the cumulative cost value from the starting grid to the target grid and the critical cost value from the target grid to the destination grid.
[0055] Step S310 includes steps S311-S313:
[0056] Step S311: Obtain the grid coordinates of several target grids located between the starting grid and the destination grid on each initial flight path, and obtain the initial flight path coordinate list set E = (E1, E2, ..., E i ,...,E n ); where i = 1, 2, ..., n; n is the number of initial flight paths; E i This is a list of initial flight path coordinates corresponding to the i-th initial flight path;
[0057] E i =(E i1 E i2 ,...,E ig ,...,E if(i) ); g = 1, 2, ..., f(i); f(i) is the number of target grids located between the starting grid and the destination grid on the i-th initial flight path; E ig Let g be the grid coordinates of the g-th target grid located between the starting grid and the target grid on the i-th initial flight path;
[0058] E ig =(E ig1 E ig2 ); E ig1 For E ig The x-coordinate; E ig2 For Eig The ordinate;
[0059] Step S312: Determine the path from the starting grid to E along the i-th initial flight path. ig The cumulative cost H at the corresponding target grid ig =|E ig1 -x a |+|E ig2 -y a |;
[0060] Step S313: Determine the initial flight path from E along the i-th initial flight path. ig The corresponding critical value M from the target grid to the destination grid ig =((E) ig1 -x b ) 2 +(E ig2 -y b ) 2 ) 1 / 2 .
[0061] Step S320: Determine the cumulative cost coefficient and critical cost coefficient corresponding to any target grid based on the cumulative cost value and critical cost value corresponding to that target grid.
[0062] Step S320 includes steps S321-S323:
[0063] Step S321, if H ig ≤M ig Then determine E ig The position coefficient T at the corresponding target grid ig =M ig / H ig Otherwise, determine E. ig The position coefficient T at the corresponding target grid ig =H ig / M ig ;
[0064] Step S322, Determine E ig The cumulative cost coefficient of the corresponding target raster Where e is the natural constant;
[0065] Step S323, Determine E ig The corresponding key cost coefficient W of the target grid ig =1-U ig .
[0066] Step S330: Determine the target value of any target grid based on its cumulative cost value, critical cost value, cumulative cost coefficient, and critical cost coefficient.
[0067] Step S330 includes step S331:
[0068] Step S331, according to U ig and W ig Determine E ig The target value Z of the corresponding target grid ig =U ig ×H ig +W ig ×M ig .
[0069] Step S400: Determine the total value corresponding to each initial flight path based on the value of several target grids on each initial flight path.
[0070] Furthermore, step S400 includes step S410:
[0071] Step S410: Determine the total value B corresponding to the i-th initial flight path based on the target value of each target grid on the i-th initial flight path. i =∑ f(i) g＝1 Z ig .
[0072] The total agency value represents an index corresponding to the flight safety of the initial flight route. The higher the total agency value, the lower the safety of the initial flight route, and vice versa.
[0073] Step S500: Determine the target flight route from several initial flight routes based on the total agency value corresponding to each initial flight route.
[0074] Furthermore, step S500 includes step S510:
[0075] Step S510: Set MIN(B1,B2,...,B) to... i ,...,B n The initial flight path corresponding to ) is determined as the target flight path; where MIN() is a preset minimum value determination function.
[0076] The initial flight route with the lowest overall value has the highest safety; therefore, the corresponding initial flight route is determined as the target flight route.
[0077] The UAV flight path planning method based on airspace grid cost value of the present invention determines several initial flight paths from the starting grid to the destination grid based on the starting grid coordinates and the destination grid coordinates of the target UAV. Then, based on the starting grid coordinates, the destination grid coordinates, and the corresponding grid coordinates on each initial flight path, the cost value of each target grid on each initial flight path is determined. Based on the cost values of the several target grids on each initial flight path, the total cost value corresponding to each initial flight path is determined. Finally, based on the total cost value corresponding to each initial flight path, the target flight path is determined from the several initial flight paths. By calculating the cost value of each initial flight path, the cost value of the finally determined target flight path is minimized, thus improving its safety.
[0078] Embodiments of the present invention also provide a computer program product including program code, which, when the program product is run on an electronic device, causes the electronic device to perform the steps of the methods described above in various exemplary embodiments of the present invention.
[0079] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.
[0080] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.
[0081] In an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.
[0082] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: entirely hardware implementations, entirely software implementations (including firmware, microcode, etc.), or implementations combining hardware and software aspects, collectively referred to herein as “circuits,” “modules,” or “systems.”
[0083] An electronic device according to this embodiment of the invention. The electronic device is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the invention.
[0084] Electronic devices are manifested in the form of general-purpose computing devices. Components of an electronic device may include, but are not limited to: at least one processor, at least one memory, and buses connecting different system components (including memory and processor).
[0085] The storage device stores program code that can be executed by the processor to perform the steps described in the "Exemplary Methods" section above, according to various exemplary embodiments of the present invention.
[0086] The storage may include readable media in the form of volatile storage, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).
[0087] The storage may also include programs / utilities having a set (at least one) of program modules, including but not limited to: an operating system, one or more applications, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.
[0088] A bus can represent one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus that uses any of the various bus architectures.
[0089] Electronic devices can also communicate with one or more external devices (such as keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable users to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (such as routers, modems, etc.). This communication can be performed through input / output (I / O) interfaces. Furthermore, electronic devices can also communicate with one or more networks (such as local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapters.
[0090] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.
[0091] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the invention described in the "Exemplary Methods" section of this specification.
[0092] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.
[0093] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.
[0094] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.
[0095] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java and C++, and conventional procedural programming languages such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).
[0096] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.
[0097] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.
[0098] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A method for planning UAV flight routes based on airspace grid cost values, characterized in that, The system is applied to a flight path planning system, which includes a target grid map corresponding to a target space. The target grid map includes several target grids and corresponds to a grid coordinate system. Each target grid corresponds to grid coordinates in the grid coordinate system. The method includes the following steps: Step S100: In response to receiving a flight path planning request from the target UAV, obtain the starting grid coordinates of the starting grid and the destination grid coordinates of the destination grid included in the flight path planning request; the starting grid is the target grid of the starting position point of the target UAV in the target grid map; the destination grid is the target grid of the destination position point of the target UAV in the target grid map. Step S200: Determine several initial flight paths from the starting grid to the destination grid based on the starting grid coordinates and the destination grid coordinates; Step S300: Determine the cost of each target grid on each initial flight path based on the starting grid coordinates, the target grid coordinates, and the corresponding grid coordinates on each initial flight path. Step S400: Determine the total cost value corresponding to each initial flight path based on the cost value of the target grids on each initial flight path. Step S500: Determine the target flight route from the initial flight routes based on the total agency value corresponding to each initial flight route. Wherein, step S300 includes steps S310-S330: Step S310: Based on the starting grid coordinates, the destination grid coordinates, and each grid coordinate corresponding to each initial flight path, determine the cumulative cost value from the starting grid to the target grid and the critical cost value from the target grid to the destination grid; Step S320: Determine the cumulative cost coefficient and critical cost coefficient corresponding to any of the target grids based on the cumulative cost value and critical cost value corresponding to the target grid. Step S330: Determine the target value of the target grid based on the cumulative cost value, critical cost value, cumulative cost coefficient, and critical cost coefficient corresponding to any of the target grids; Wherein, step S310 includes steps S311-S313: Step S311: Obtain the grid coordinates corresponding to several target grids located between the starting grid and the destination grid on each initial flight path, to obtain the initial flight path coordinate list set E=(E1,E2,...,E...). i ,...,E n ); where i = 1, 2, ..., n; n is the number of the initial flight paths; E i This is a list of initial flight path coordinates corresponding to the i-th initial flight path; E i =(E i1 E i2 ,...,E ig ,...,E if(i) ); g=1,2,...,f(i); f(i) is the number of target grids located between the starting grid and the destination grid on the i-th initial flight path; E ig The grid coordinates are the grid coordinates of the g-th target grid located between the starting grid and the target grid on the i-th initial flight path; E ig =(E ig1 E ig2 ); E ig1 For E ig The x-coordinate; E ig2 For E ig The ordinate; Step S312: Determine the distance from the starting grid to E along the i-th initial flight path. ig The cumulative cost H at the corresponding target grid ig =|E ig1 -x a |+|E ig2 -y a |; Step S313: Determine the initial flight path along the i-th path from E ig The critical cost M from the corresponding target grid to the destination grid ig =((E ig1 -x b ) 2 +(E ig2 -y b ) 2 ) 1 / 2 ; Wherein, step S320 includes steps S321-S323: Step S321, if H ig ≤M ig Then determine E ig The position coefficient T at the corresponding target grid ig =M ig / H ig Otherwise, determine E. ig The position coefficient T at the corresponding target grid ig =H ig / M ig ; Step S322, Determine E ig The cumulative cost coefficient of the corresponding target raster Where e is the natural constant; Step S323, Determine E ig The corresponding key cost coefficient W of the target grid ig =1-U ig .
2. The method according to claim 1, characterized in that, Step S200 includes: Step S210: The grid coordinates are (x... a ,y a ), (x a ,y b ), (x b ,y a ) and (x b ,y b The area composed of the target grid is defined as the target flight area; where x a y is the x-coordinate of the starting grid coordinates; a x is the ordinate of the starting grid coordinates; b y is the x-coordinate of the target raster coordinates; b The ordinate of the target raster coordinates; Step S220: According to the preset flight path planning algorithm, starting from the starting grid, traverse each target grid in the target flight area until the destination grid is reached, so as to determine several initial flight paths.
3. The method according to claim 1, characterized in that, Step S330 includes: Step S331, according to U ig and W ig Determine E ig The target value Z of the corresponding target grid ig =U ig ×H ig +W ig ×M ig .
4. The method according to claim 3, characterized in that, Step S400 includes: Step S410: Determine the total value B corresponding to the i-th initial flight path based on the target value of each target grid on the i-th initial flight path. i =∑ f(i) g=1 Z ig .
5. The method according to claim 4, characterized in that, Step S500 includes: Step S510: Set MIN(B1,B2,...,B) to... i ,...,B n The initial flight path corresponding to ) is determined as the target flight path; where MIN() is a preset minimum value determination function.
6. A non-transitory computer-readable storage medium, wherein the storage medium stores at least one instruction or at least one program segment, characterized in that, The at least one instruction or the at least one program segment is loaded and executed by the processor to implement the UAV flight path planning method based on airspace grid cost value as described in any one of claims 1-5.
7. An electronic device, characterized in that, Includes a processor and the non-transitory computer-readable storage medium as described in claim 6.