Urban basic model-based unmanned aerial vehicle scheduling method and system

Abstract

The invention relates to the technical field of unmanned aerial vehicle scheduling, and provides an unmanned aerial vehicle scheduling method and system based on a city basic model, and the method comprises the steps: building an unmanned aerial vehicle schedulable region which can accommodate the hovering of an unmanned aerial vehicle between a source signal node and a target signal node through the city basic model, and then traversing a relay signal point setting scheme by using a shortest path without signal shielding in the region, identifying a scheme in which the number of set relay signal points is minimum and the obstacle thickness between adjacent relay signal points is less than a preset thickness threshold, and scheduling the unmanned aerial vehicle by using the coordinates of the relay signal point with the minimum total thickness. The established wireless ad hoc network can have the best communication signal quality, the number of the unmanned aerial vehicles needing to serve as the relay nodes is minimum, and the networking cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle dispatching, and in particular to a method and system for dispatching unmanned aerial vehicles based on a city basic model. Background Art

[0002] In urban areas with densely populated high-rise buildings, direct communication will be restricted due to the shielding and weakening of signals by buildings, and signal communication will be poor. Therefore, when users need to establish wireless ad hoc network communications, they will choose to use drones as relay nodes to forward signals and transmit signals from source nodes to target nodes, thereby solving communication problems. However, the coordinates of the dispatching position of the drone are difficult to determine. Summary of the invention

[0003] The present invention provides a method for dispatching unmanned aerial vehicles (UAVs) based on a city basic model, which is used to solve the problem of determining the dispatching coordinates of UAV relay points for establishing a wireless ad hoc network in a city in the prior art.

[0004] The first aspect of the present invention provides a method for dispatching unmanned aerial vehicles based on a city basic model, comprising: Obtain the source signal node coordinates and the target signal node coordinates; obtain the city basic model, identify the obstacle building area according to the source signal node coordinates and the target signal node coordinates, and establish the drone dispatchable area according to the obstacle building area; According to the coordinates of the source signal node and the target signal node, the shortest path without signal obstruction is identified in the dispatchable area of ​​the UAV; all relay signal point setting schemes are generated according to the number of inflection points on the shortest path without signal obstruction; the positions of the relay signal points are moved and traversed in each relay signal point setting scheme, the obstacle thickness between adjacent relay signal points is calculated, and the minimum value of the total obstacle thickness is identified when the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than a preset thickness threshold; Among the relay signal point setting schemes that satisfy the requirement that the thickness of all obstacles is greater than a preset thickness threshold, the scheme with the least number of relay signal points is selected, and the coordinates of the relay signal points corresponding to the minimum total thickness in the scheme are sent to the UAV for scheduling.

[0005] Optionally, the positions of the relay signal points are moved and traversed in each relay signal point setting scheme to calculate the obstacle thickness between adjacent relay signal points, specifically: In the process of moving and traversing the positions of relay signal points in each relay signal point setting plan, the types of obstacle buildings between adjacent relay signal points are identified, the signal shielding coefficients corresponding to the obstacle building types are identified according to the urban basic model, the obstacle thickness between adjacent relay signal points is calculated and corrected with the signal shielding coefficients.

[0006] Optionally, the establishment of a drone dispatchable area according to the obstacle building area is specifically as follows: The signal transmission space is established with the coordinates of the source signal node and the target signal node. The spatial obstacle building area is corrected with the preset UAV size. The intersection space of the spatial obstacle building area and the signal transmission space is identified to obtain the non-scheduled area. The non-scheduled area is eliminated in the signal transmission space to obtain the UAV dispatchable area.

[0007] The second aspect of the present application provides a drone dispatching system based on a city basic model, including: The dispatchable area construction module is used to obtain the source signal node coordinates and the target signal node coordinates; obtain the city basic model, identify the obstacle building area according to the source signal node coordinates and the target signal node coordinates, and establish the drone dispatchable area according to the obstacle building area; The signal point setting scheme generation module is used to identify the shortest path without signal obstruction in the UAV dispatchable area according to the source signal node coordinates and the target signal node coordinates; generate all relay signal point setting schemes according to the number of inflection points on the shortest path without signal obstruction; move and traverse the positions of the relay signal points in each relay signal point setting scheme, calculate the obstacle thickness between adjacent relay signal points, and identify the minimum value of the total obstacle thickness when the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than a preset thickness threshold; The drone scheduling module is used to select the scheme with the least number of relay signal points among the relay signal point setting schemes that meet the requirements of all obstacles with thickness greater than a preset thickness threshold, and send the coordinates of the relay signal points corresponding to the minimum total thickness in the scheme to the drone for scheduling.

[0008] Optionally, in the signal point setting scheme generating module, the positions of the relay signal points in each relay signal point setting scheme are moved and traversed to calculate the obstacle thickness between adjacent relay signal points, specifically: In the process of moving and traversing the positions of relay signal points in each relay signal point setting plan, the types of obstacle buildings between adjacent relay signal points are identified, the signal shielding coefficients corresponding to the obstacle building types are identified according to the urban basic model, the obstacle thickness between adjacent relay signal points is calculated and corrected with the signal shielding coefficients.

[0009] Optionally, in the dispatchable area construction module, a drone dispatchable area is established according to the obstacle building area, specifically: The signal transmission space is established with the coordinates of the source signal node and the target signal node. The spatial obstacle building area is corrected with the preset UAV size. The intersection space of the spatial obstacle building area and the signal transmission space is identified to obtain the non-scheduled area. The non-scheduled area is eliminated in the signal transmission space to obtain the UAV dispatchable area.

[0010] The third aspect of the present application provides a method and device for dispatching a drone based on a city basic model, the device comprising a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute a drone scheduling method based on a city basic model as described in any one of the first aspects of the present invention according to the instructions in the program code.

[0011] The fourth aspect of the present application provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute a drone scheduling method based on an urban basic model as described in any one of the first aspects of the present invention.

[0012] It can be seen from the above technical scheme that the present invention has the following advantages: a drone dispatchable area that can accommodate drone hovering is established between the source signal node and the target signal node through the city basic model, and then the relay signal point setting scheme is traversed with the shortest path without signal obstruction in the area, and the scheme with the least number of relay signal points and the obstacle thickness between each adjacent relay signal point is identified to be less than the preset thickness threshold. The drone is dispatched according to the relay signal point coordinates with the minimum total thickness, so that the established wireless self-organizing network can have the best communication signal quality, and the number of drones required as relay nodes is minimized, thereby reducing the networking cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0014] Figure 1 It is a flowchart of a UAV dispatching method based on the city basic model; Figure 2 This is a structural diagram of a drone dispatching system based on a city-based model. DETAILED DESCRIPTION

[0015] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions 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 embodiments described below 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 are within the scope of protection of the present invention.

[0016] The present invention provides a method for dispatching unmanned aerial vehicles (UAVs) based on a city basic model, which is used to solve the problem of determining the dispatching coordinates of UAV relay points for establishing a wireless ad hoc network in a city in the prior art.

[0017] See also Figure 1 , Figure 1 The present invention provides a first flowchart of a method for dispatching unmanned aerial vehicles based on a city basic model in an embodiment of the present invention.

[0018] S100, obtaining source signal node coordinates and target signal node coordinates; obtaining a basic city model, identifying an obstacle building area according to the source signal node coordinates and the target signal node coordinates, and establishing a UAV dispatchable area according to the obstacle building area; It should be noted that, in the wireless ad hoc network to be built, a spatial coordinate system can be first established, and the corresponding source signal node coordinates can be obtained according to the source signal sending position, and the target signal node coordinates can be obtained at the receiving terminal of the wireless ad hoc network; in the urban area, there will be dense buildings between the source signal node coordinates and the target signal node coordinates to hinder signal transmission, and the horizontal, vertical and high coordinate differences between the source signal node coordinates and the target signal node coordinates can be used as the length, width and height of the rectangular parallelepiped to obtain a signal transmission space; and the urban basic model has a comprehensive description of buildings and roads, including detailed three-dimensional information, and the appearance and parameter data of the buildings can be obtained in the three-dimensional information. The space occupied by the urban basic model in the spatial coordinate system can establish an obstacle building area, that is, the obstacle building area is full of buildings, and the signal propagation through the concrete of the building will cause the signal to attenuate, which will bring obstacles to wireless communication; By identifying the intersection of the signal transmission space of the source signal node coordinates and the target signal node coordinates and the obstacle building areas corresponding to each building, it can be identified which buildings have invaded the signal transmission space, that is, these buildings will hinder the source signal from being sent to the target signal. After all the buildings that will hinder the signal are identified, the obstacle building area can be established; the drone needs to fly and hover in an open area and will not be inside a building. There will be gaps between obstacle buildings. This gap area can be used as the drone's dispatchable area. The drone's dispatchable area is obtained by subtracting the signal transmission space from the signal transmission space obstacle building area.

[0019] S200, identifying the shortest path without signal obstruction in the dispatchable area of ​​the UAV according to the coordinates of the source signal node and the target signal node; generating all relay signal point setting schemes according to the number of inflection points on the shortest path without signal obstruction; moving and traversing the positions of the relay signal points in each relay signal point setting scheme, calculating the obstacle thickness between adjacent relay signal points, and identifying the minimum value of the total obstacle thickness when the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than a preset thickness threshold; It should be noted that the drone dispatchable area is an irregular channel. The source signal node coordinates and the target signal node coordinates are used as the starting and ending points of the path respectively, and the shortest path is identified. The shortest path will form a broken line with multiple inflection points in the drone dispatchable area; a drone relay point is set at each inflection point in the shortest path to form a wireless ad hoc network without signal obstruction, but this is the solution that requires the largest number of drones and has a high cost. Therefore, it is necessary to set up relay nodes by traversing a solution with a smaller number of drones; there will be straight line paths between the inflection points in the shortest path without signal obstruction, between the inflection points and the source signal nodes, and between the inflection points and the target signal nodes. The number of straight line paths is the number of inflection points plus one, and the number of relay signal point setting solutions is , is the number of straight line paths, is the number of relay signal points, and less than the number of inflection points; each relay signal point moves on a straight line path, and the distance between two relay signal points is calculated. The Euclidean distance can be calculated by the spatial coordinates of the relay signal points. While calculating the Euclidean distance, the straight line expression between the two relay signal points can be obtained. The obstacle thickness between adjacent signal points can be obtained by the overlap length of the straight line expression and the obstacle building area; the obstacle thickness that the signal can pass through is related to its frequency. The thicker the wall, the faster the wireless signal will attenuate, affecting the communication quality of the ad hoc network. Therefore, a thickness threshold that will not affect the signal attenuation or has a low attenuation degree can be obtained according to the signal frequency of the source signal node and the drone as a relay node. When the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than the preset thickness threshold, it reflects that the position of the relay signal node after the move in the scheme is feasible, and the signal of the wireless ad hoc network is not hindered. The total obstacle thickness can be obtained by accumulating each obstacle thickness. When the total obstacle thickness is at the minimum value in the relay signal point setting scheme, the corresponding position of each relay signal point is optimal, and the degree of signal loss is the lowest.

[0020] When the drone acts as a relay node, the signal processing of the drone relay communication mainly includes signal reception, demodulation, encoding and modulation. During the signal reception process, the drone relay node needs to receive the signal sent from the previous signal node through the antenna, and then convert the signal into original information through processing methods such as demodulation and decoding. The drone relay node then sends the signal to the next signal node through modulation technology until the target node receives the signal.

[0021] S300, among the relay signal point setting schemes that satisfy all obstacle thicknesses greater than a preset thickness threshold, select the scheme with the least number of relay signal points, and send the relay signal point coordinates corresponding to the minimum total thickness in the scheme to the drone for scheduling.

[0022] It should be noted that, in the process of the relay node moving and traversing on the straight path under each relay signal point setting scheme in the aforementioned steps, the thickness of the obstacle that the signal transmission path between adjacent relay signal nodes needs to penetrate will also change. There are some relay signal point setting schemes with too few relay signal points. No matter how the movement, traversal and adjustment are made, there will be a certain section of the signal that is severely attenuated due to the excessive thickness of the building obstacle, resulting in poor communication quality. In this case, the corresponding relay signal point setting scheme is not feasible. Since the cost of drones as relay nodes is high, it is necessary to select the relay signal point setting scheme that satisfies all obstacles with a thickness greater than the preset thickness threshold. The scheme that requires the least number of drones as relay nodes is required. In the corresponding scheme, the position of the relay signal point can be further adjusted to further reduce the attenuation of the communication signal while satisfying the signal transmission quality, that is, find the relay signal point coordinates under the minimum total thickness in the scheme, send the relay signal point coordinates to the drone for scheduling, and generate scheduling instructions with the coordinates as the drone flight destination. The drone will generate a flight route based on the relay signal point coordinates. After the drone arrives at the designated location, it can forward the self-organizing network signal to build a wireless self-organizing network in the city.

[0023] In this embodiment, a drone dispatchable area that can accommodate drones to hover is established between the source signal node and the target signal node through the city basic model, and then the relay signal point setting plan is traversed along the shortest path without signal obstruction in the area, and the plan with the least number of relay signal points and the obstacle thickness between each adjacent relay signal point is identified to be less than a preset thickness threshold. The drones are dispatched according to the relay signal point coordinates with the minimum total thickness, so that the established wireless ad hoc network can have the best communication signal quality and the number of drones required as relay nodes is minimized, thereby reducing the networking cost.

[0024] The above is a detailed description of the first embodiment of a drone scheduling method based on a city basic model provided by the present application. The following is a detailed description of the second embodiment of a drone scheduling method based on a city basic model provided by the present application.

[0025] In this embodiment, a method for dispatching a drone based on a city basic model is further provided. In the aforementioned step S200, the positions of the relay signal points are moved and traversed in each relay signal point setting scheme, and the obstacle thickness between adjacent relay signal points is calculated. Specifically, in the process of moving and traversing the positions of the relay signal points in each relay signal point setting scheme, the types of obstacle buildings between adjacent relay signal points are identified, and the signal shielding coefficients corresponding to the obstacle building types are identified according to the city basic model, and the obstacle thickness between adjacent relay signal points is calculated and corrected by the signal shielding coefficients; It should be noted that, in addition to the thickness of the building walls, the factors that affect the ability of wireless signals to penetrate walls also include the type of materials. Different building types use different building materials, and walls of different materials have different degrees of attenuation of wireless signals. For example, concrete walls have a greater attenuation of wireless signals, while walls of materials such as wood or glass have a smaller attenuation of wireless signals. The straight line expression between the two relay signal points passes through the obstacle building and its building material is identified. According to the preset material and signal shielding coefficient, the actual obstacle thickness is corrected. For example, when the exterior wall of the building is glass, the obstacle thickness is corrected with the signal shielding coefficient corresponding to the building material. Because the signal of the exterior wall of the glass building is easier to penetrate, the obstacle thickness is corrected to a smaller value for comparison with the preset thickness coefficient in subsequent steps. This can further increase the accuracy of the relay signal point setting position and improve the signal quality.

[0026] Further, in the aforementioned step S100, the establishment of a UAV dispatchable area according to the obstacle building area is specifically as follows: a signal transmission space is established with source signal node coordinates and target signal node coordinates, the spatial obstacle building area is corrected with a preset UAV size, and the intersection space of the spatial obstacle building area and the signal transmission space is identified to obtain a non-dispatching area; the non-dispatching area is eliminated in the signal transmission space to obtain a UAV dispatchable area; it should be noted that the UAV cannot be hovered and dispatched in the spatial obstacle building area. At the same time, it should be considered that the UAV is not a particle, and the volume of the UAV needs to be considered. Therefore, a UAV size can be set according to the actual UAV model for the self-organizing network. The UAV size needs to consider the maximum motor wheelbase and rotor length of the UAV, so that the hovering position of the UAV can be at a safe distance from the obstacle building, and the edge coordinates of the spatial obstacle building area are then extended vertically to the building facade by the preset UAV size. In this way, the intersection space of the spatial obstacle building area and the signal transmission space identified under correction can be a safe non-dispatching area, and the UAV dispatchable area obtained subsequently can fully guarantee the flight safety of the UAV in the process of dispatching the UAV.

[0027] The above is a detailed description of a drone scheduling method based on a city basic model provided in the first aspect of the present application. The following is a detailed description of an embodiment of a drone scheduling system based on a city basic model provided in the second aspect of the present application.

[0028] See also Figure 2 , Figure 2 This embodiment provides a UAV dispatching system based on a city basic model, including: The dispatchable area construction module 10 is used to obtain the source signal node coordinates and the target signal node coordinates; obtain the city basic model, identify the obstacle building area according to the source signal node coordinates and the target signal node coordinates, and establish the drone dispatchable area according to the obstacle building area; The signal point setting scheme generating module 20 is used to identify the shortest path without signal obstruction in the dispatchable area of ​​the UAV according to the source signal node coordinates and the target signal node coordinates; generate all relay signal point setting schemes according to the number of inflection points on the shortest path without signal obstruction; move and traverse the positions of the relay signal points in each relay signal point setting scheme, calculate the obstacle thickness between adjacent relay signal points, and identify the minimum value of the total obstacle thickness when the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than a preset thickness threshold; The drone scheduling module 30 is used to select the scheme with the least number of relay signal points among the relay signal point setting schemes that satisfy all obstacle thicknesses greater than a preset thickness threshold, and send the relay signal point coordinates corresponding to the minimum total thickness in the scheme to the drone for scheduling.

[0029] Furthermore, in the signal point setting scheme generating module 20, the positions of the relay signal points in each relay signal point setting scheme are moved and traversed to calculate the obstacle thickness between adjacent relay signal points, specifically: In the process of moving and traversing the positions of relay signal points in each relay signal point setting plan, the types of obstacle buildings between adjacent relay signal points are identified, the signal shielding coefficients corresponding to the obstacle building types are identified according to the urban basic model, the obstacle thickness between adjacent relay signal points is calculated and corrected with the signal shielding coefficients.

[0030] Furthermore, in the dispatchable area construction module 10, a drone dispatchable area is established according to the obstacle building area, specifically: The signal transmission space is established with the coordinates of the source signal node and the target signal node. The spatial obstacle building area is corrected with the preset UAV size. The intersection space of the spatial obstacle building area and the signal transmission space is identified to obtain the non-scheduled area. The non-scheduled area is eliminated in the signal transmission space to obtain the UAV dispatchable area.

[0031] The third aspect of the present application also provides a drone scheduling method device based on a city basic model, including a processor and a memory: the memory is used to store program code and transfer the program code to the processor; the processor is used to execute the above-mentioned drone scheduling method based on a city basic model according to the instructions in the program code.

[0032] The fourth aspect of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium is used to store program code, and the program code is used to execute the above-mentioned drone scheduling method based on the urban basic model.

[0033] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0034] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0035] 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.

[0036] 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.

[0037] 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, in essence, 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. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0038] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A UAV dispatching method based on a city basic model, characterized in that include: Obtain source signal node coordinates and target signal node coordinates; Obtain the basic city model, identify the obstacle building area according to the source signal node coordinates and the target signal node coordinates, and establish the drone dispatchable area according to the obstacle building area; According to the source signal node coordinates and the target signal node coordinates, the shortest path without signal obstruction is identified in the dispatchable area of ​​the UAV; Generate all relay signal point setting schemes based on the number of inflection points on the shortest path without signal obstruction; move and traverse the positions of relay signal points in each relay signal point setting scheme, calculate the obstacle thickness between adjacent relay signal points, and identify the minimum value of the total obstacle thickness when the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than a preset thickness threshold; Among the relay signal point setting schemes that satisfy the requirement that the thickness of all obstacles is greater than a preset thickness threshold, the scheme with the least number of relay signal points is selected, and the coordinates of the relay signal points corresponding to the minimum total thickness in the scheme are sent to the UAV for scheduling.

2. The method for dispatching unmanned aerial vehicles based on a city basic model according to claim 1, characterized in that: The positions of the relay signal points are moved and traversed in each relay signal point setting scheme to calculate the obstacle thickness between adjacent relay signal points, specifically: In the process of moving and traversing the positions of relay signal points in each relay signal point setting plan, the types of obstacle buildings between adjacent relay signal points are identified, the signal shielding coefficients corresponding to the obstacle building types are identified according to the urban basic model, the obstacle thickness between adjacent relay signal points is calculated and corrected with the signal shielding coefficients.

3. The method for dispatching unmanned aerial vehicles based on a city basic model according to claim 1, characterized in that: The establishment of a drone dispatchable area based on the obstacle building area is specifically as follows: The signal transmission space is established with the coordinates of the source signal node and the target signal node. The spatial obstacle building area is corrected with the preset UAV size. The intersection space of the spatial obstacle building area and the signal transmission space is identified to obtain the non-scheduled area. The non-scheduled area is eliminated in the signal transmission space to obtain the UAV dispatchable area.

4. A drone dispatching system based on a city-based model, characterized in that: include: A schedulable region construction module is used to obtain the source signal node coordinates and the target signal node coordinates; Obtain the basic city model, identify the obstacle building area according to the source signal node coordinates and the target signal node coordinates, and establish the drone dispatchable area according to the obstacle building area; A signal point setting scheme generation module is used to identify the shortest path without signal obstruction in the UAV dispatchable area according to the source signal node coordinates and the target signal node coordinates; Generate all relay signal point setting schemes based on the number of inflection points on the shortest path without signal obstruction; move and traverse the positions of relay signal points in each relay signal point setting scheme, calculate the obstacle thickness between adjacent relay signal points, and identify the minimum value of the total obstacle thickness when the obstacle thickness between all adjacent relay signal points in the relay signal point setting scheme is less than a preset thickness threshold; The drone scheduling module is used to select the scheme with the least number of relay signal points among the relay signal point setting schemes that meet the requirements of all obstacles with thickness greater than a preset thickness threshold, and send the coordinates of the relay signal points corresponding to the minimum total thickness in the scheme to the drone for scheduling.

5. The UAV dispatching system based on the city basic model according to claim 4 is characterized in that: In the signal point setting scheme generating module, the positions of the relay signal points in each relay signal point setting scheme are moved and traversed to calculate the obstacle thickness between adjacent relay signal points, specifically: In the process of moving and traversing the positions of relay signal points in each relay signal point setting plan, the types of obstacle buildings between adjacent relay signal points are identified, the signal shielding coefficients corresponding to the obstacle building types are identified according to the urban basic model, the obstacle thickness between adjacent relay signal points is calculated and corrected with the signal shielding coefficients.

6. The UAV dispatching system based on the city basic model according to claim 4 is characterized in that: In the dispatchable area construction module, the dispatchable area of ​​the drone is established according to the obstacle building area, specifically: The signal transmission space is established with the coordinates of the source signal node and the target signal node. The spatial obstacle building area is corrected with the preset UAV size. The intersection space of the spatial obstacle building area and the signal transmission space is identified to obtain the non-scheduled area. The non-scheduled area is eliminated in the signal transmission space to obtain the UAV dispatchable area.

7. A drone dispatching device based on a city basic model, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute a drone scheduling method based on a city basic model as described in any one of claims 1-3 according to the instructions in the program code.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program code, and the program code is used to execute the drone scheduling method based on the urban basic model described in any one of claims 1-3.

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