Unmanned aerial vehicle urban management scene patrol inspection system and method based on geographic information

Abstract

The invention discloses an unmanned aerial vehicle urban management scene patrol inspection system and method based on geographic information, and the system comprises an event processing module, a task management module, a route planning module, an unmanned aerial vehicle flying module and a three-dimensional modeling module, and achieves the intelligent planning of an unmanned aerial vehicle urban management patrol inspection task in combination with the geographic information. Through fusion of urban management inspection business process, task multi-mode issuing, route self-defined planning of a three-dimensional map and task scene management, high fusion of unmanned aerial vehicle operation and business management is realized, a whole-process closed loop is formed, the unmanned aerial vehicle is ensured to complete tasks in an optimal state in different scenes, and the working efficiency of the unmanned aerial vehicle is improved. And the flexibility and adaptability of task issuing are greatly enhanced. Through the spatial geographic information of the three-dimensional map, the attitude perception capability of obstacles in route planning is enhanced, the flight risk is reduced, the safety risk in the flight process of the unmanned aerial vehicle is greatly reduced, and the patrol inspection effect can be further optimized.

Description

Technical Field

[0001] The present invention relates to an inspection and patrol system and method for an unmanned aerial vehicle (UAV) in an urban management scenario, specifically to an inspection and patrol system and method for an unmanned aerial vehicle in an urban management scenario based on geographic information; it belongs to the technical field related to UAV applications. Background Art

[0002] With the continuous expansion of the urban scale and the increasing complexity of urban management, UAVs, relying on their advantages such as strong mobility, high flexibility, and the ability to obtain high-resolution images, have gradually become one of the important forces in urban management. However, there are still many limitations in the combination of UAVs and business applications at present: (1) At the task management level, the issuance of management tasks overly relies on the personal experience of operators, lacking a systematic and intelligent task scheduling mechanism. Most traditional task issuance methods are limited to simple immediate flight instructions and are difficult to flexibly adjust parameters such as task priorities and execution times according to actual situations. Moreover, in the face of sudden emergencies, due to the cumbersome manual processing process and the delay in information transmission, it is impossible to ensure that the UAV can quickly respond and fly to the target area for disposal. That is to say, the existing systems and methods lack a business closed-loop. Most of them still stay in the stage of offline docking with UAVs for task processing, without a direct online association with events, and the videos or images taken by the UAV after flight cannot be shared in a timely manner, resulting in the inability to form a closed-loop for the overall business process and requiring manual tracking and processing.

[0003] (2) In terms of inspection area planning, most existing technologies operate based on two-dimensional maps. Although they can provide certain geographic information, their ability to express the complex three-dimensional urban space environment is limited, and they cannot accurately reflect key geographic features such as terrain undulations and building heights. As a result, it is difficult to fully consider the impact of these factors on UAV flight safety and inspection effects when planning inspection areas and flight routes. For example, there may be unreasonable division of inspection areas, insufficient inspection frequencies in some key areas or high-risk areas, while excessive inspections in some non-critical areas. It is impossible to formulate differentiated inspection strategies according to factors such as the geographic features and functional uses of different areas, resulting in unsatisfactory inspection effects and resource waste.

[0004] (3) In terms of flight path planning, current UAV flight paths mainly focus on flight path planning algorithms. For example, the shortest path algorithm or greedy algorithm is used to determine the flight route of the UAV from the starting point to the target point, which can improve the flight efficiency of the UAV to a certain extent. However, in the inspection area and flight path planning, although attempts have been made to introduce geographical information, most of them simply overlay geographical information data on a 2D map without truly delving into the 3D spatial characteristics of geographical information. For mountainous areas or urban areas with high-rise buildings, planning flight paths based solely on coordinate information on a 2D map cannot effectively avoid the three-dimensional spatial range of obstacles such as mountains and buildings, threatening flight safety. Therefore, in the actual UAV flight path planning process, not only geometric parameters of the flight path need to be considered, such as flight altitude, heading overlap rate, side overlap degree, etc., but also flight environment parameters, flight performance parameters, camera parameters, etc. All of these highly rely on human experience.

[0005] It can be seen that there are many problems with the existing UAV-based urban management scene inspection and patrol system and method, including: the overall business process loop is closed, the task handling efficiency is low, the flight path planning has poor awareness of the surrounding environment situation, and the flight path planning highly relies on human experience, etc. These problems restrict the efficiency and feasibility of using UAVs for urban management. Summary of the Invention

[0006] To solve the deficiencies of the existing technology, the purpose of the present invention is to provide a UAV urban management scene inspection and patrol system and method, which combines geographical information and an automatic UAV flight path planning algorithm based on the actual business process of urban management to achieve intelligent task inspection of UAV urban management.

[0007] To achieve the above objectives, the present invention adopts the following technical solutions: The present invention first discloses a UAV urban management scene inspection and patrol system based on geographical information, including: Event processing module: used to receive reported events, conduct preliminary processing and judgment on the events, determine whether UAV participation in handling is required, and transmit the processing results to the task management module; Task management module: responsible for managing UAV tasks, making task plans according to the instructions of the event processing module, and interacting with the flight path planning module to determine the specific parameters of the UAV flight task; Flight path planning module: uses camera parameters and geographical information to calculate a safe and efficient UAV flight path and send it to the UAV flight execution module; UAV flight execution module: executes the UAV flight task, conducts flight operations according to the flight path determined by the flight path planning module, collects relevant result information and associates it with the task or event, and notifies the system of the task completion situation; 3D Modeling Module: Conduct 3D modeling on the target area to construct a 3D map, providing geographical information data support for the system.

[0008] Preferably, in the aforementioned task management module, the specific parameters of the flight mission include: the flight altitude of the UAV, speed, camera parameters, and payload device information.

[0009] More preferably, the results collected by the aforementioned UAV flight module are photos or videos.

[0010] Even more preferably, the aforementioned task management system supports at least three task distribution modes: immediate distribution, scheduled distribution, and periodic distribution.

[0011] The present invention also discloses an inspection and patrol method based on the aforementioned UAV urban management scene inspection and patrol system, which specifically includes the following steps: (1) Event reporting: Start the system, and relevant personnel report the event to the event processing module. (2) Event processing: The system issues the event and determines whether a UAV is required. (3) Task planning: Select the task mode, determine whether to select an existing flight route, select the task scene, preview and submit after determining the task, complete task approval, and enter the UAV flight operation. (4) Flight route planning: Automatically calculate the camera parameters in the task scene or define the height, heading angle, and side overlap rate for sampling, and automatically generate the UAV flight route. (5) UAV flight: The approved task is sent to the system to notify the UAV to take off, and the result information such as photos / videos is automatically associated with the task or time, and the system is notified to complete the flight inspection.

[0012] Preferably, during the aforementioned event processing, if it is determined that a UAV is required to participate in the disposal, the information is transmitted to the task management module to add a UAV flight task; if not, the processing result is feedback to the system to complete the event closed-loop.

[0013] More preferably, during the aforementioned task planning, if an existing flight route is selected, the system automatically recommends the flight altitude and speed of the UAV, the camera parameters of the UAV, and the payload device information according to the selected scene; if an existing flight route is not selected, the flight route planning program is entered.

[0014] Even further preferably, the aforementioned flight route planning is realized based on the 3D map constructed by the 3D modeling module.

[0015] Even more preferably, the specific implementation steps of the aforementioned flight route planning are as follows: a) Calculate or define the accuracy, height, flight route angle, and side overlap rate for sampling according to the camera parameters. b) Add polygon boundary points on the 3D map. These points are on the 3D surface of the earth and need to be converted into a 2D coordinate system using tools to become a plane; c) Obtain a planar polygon according to b). Then, determine the takeoff point of the unmanned aerial vehicle based on the hangar position, and define the point with the shortest distance from the takeoff point to the polygon as the starting point of the flight route, which is also the point with the minimum distance from the aircraft to the flight route; d) Calculate the longest distance S between two waypoints according to the side overlap rate and sampling accuracy in a), and calculate the slope of the boundary line based on the planar polygon obtained in b); e) A ray is formed along the slope direction from the waypoint of the starting point, and then this ray is translated by the vertical distance S. According to the longest distance S between two waypoints and the slope obtained in d), obtain and record the intersection point, which becomes a waypoint H1 on the flight route; f) If the ray is parallel to the line segment or there is no intersection point within the vertical distance S, it is considered that the flight of this side has been completed, and a new boundary needs to be obtained as the line segment for the next cycle; g) Then, continue to move this ray by the vertical distance S and the line segment of the polygon, continuously obtain intersection points, and finally judge the entire polygon until the line segment of the polygon becomes the first line segment, and the loop stops; h) After obtaining all 2N intersection points on the polygon in the previous step, find the corresponding first point from the initial point in the opposite direction according to the slope and record it as the second waypoint (the vertical distance corresponding to the waypoint movement is S). Continuously loop forward, one in one direction and the other in the opposite direction, and connect them in pairs to form a flight route; i) Finally, convert all points into longitude and latitude through coordinates and display them on the 3D map to form parallel flight routes.

[0016] The advantages of the present invention are as follows: (1) The unmanned aerial vehicle urban management scene inspection and patrol system of the present invention combines geographical information to realize the intelligent planning of unmanned aerial vehicle urban management inspection tasks. Through the integration of urban management inspection business processes, multi-mode task distribution, custom flight route planning on 3D maps, and task scene management, the high integration of unmanned aerial vehicle operations and business management is achieved, forming a full-process closed loop, ensuring timely, efficient, and accurate processing of urban management events, complete information transmission and feedback, and improving the overall management efficiency.

[0017] (2) In the present invention, diversified task modes are also adopted to support various scenarios, and parameters are automatically recommended to reduce dependence on human experience, thereby improving the scientificity and flexibility of task execution. Various scenarios of actual task handling are grouped together. The system supports different delivery modes such as immediate delivery, scheduled delivery, and periodic delivery, which can cover all business scenarios in the process of urban management. At the same time, in order to reduce dependence on human experience, the task scenario can be selected in the task planning stage. The system can automatically recommend the altitude and speed of the drone, the camera parameters of the drone, and the payload equipment information according to the selected scenario content, which can minimize dependence on human experience, not only reducing the complexity and uncertainty of human operation, but also improving the scientificity and standardization of task execution, ensuring that the drone can complete the task in the best state in different scenarios, and greatly enhancing the flexibility and adaptability of task delivery.

[0018] (3) In the present invention, a three-dimensional map is constructed by means of surveying and modeling, and it supports directly defining the cruising area on the three-dimensional map. Through the spatial geographic information of the three-dimensional map, the ability to perceive the situation of obstacles in route planning is enhanced, the flight risk is reduced, and the safety risk of the drone during flight is greatly reduced. It can also further optimize the patrol and inspection effect.

[0019] (4) In traditional route planning, coordinates are manually selected one by one on a two-dimensional map and the order of the coordinates is clearly defined. The present invention, however, uses a route generation algorithm based on the map polygon boundary points and utilizes an automatic route generation mechanism to ensure regional coverage, thereby improving image acquisition quality, route planning efficiency and accuracy, and reducing human errors, greatly enhancing the intelligence level and practicality of drone urban management inspection tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a business architecture diagram of the UAV urban management scene inspection and patrol system based on geographic information of the present invention; Figure 2 It is a business flow chart of the method for urban management scene inspection by unmanned aerial vehicle based on geographic information of the present invention; Figure 3 It is a flow chart of route generation in the method for urban management scene inspection and patrol by unmanned aerial vehicles based on geographic information of the present invention; Figure 4 This is an example map of routes generated in the method for urban management scene inspection using unmanned aerial vehicles based on geographic information of the present invention. DETAILED DESCRIPTION

[0021] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Example 1

[0023] This embodiment discloses a drone urban management scene inspection and patrol system based on geographic information. See Figure 1 , which includes: an event processing module, a task management module, a flight route planning module, a drone flight execution module, and a 3D modeling module. These modules form a tight connection through information transmission and feedback, jointly constituting an efficient and intelligent drone urban management scene inspection and patrol system.

[0024] (1) Event processing module: Receives event reporting information from field personnel, preliminarily processes and judges the event to determine whether drones need to participate in the disposal. If so, it transmits the information to the task management module to add a drone flight execution task; if not, it directly feeds back the processing result to the system to complete the event closed-loop.

[0025] (2) Task management module: Responsible for managing drone tasks, including functions such as task mode selection (such as immediate issuance, scheduled issuance, periodic issuance), task scene selection, and task approval. It conducts task planning according to the requirements of the event processing module or user instructions, and interacts with the flight route planning module to determine the specific parameters of the drone flight task.

[0026] The specific process is as follows: Receives the event information that requires drone disposal transmitted by the event processing module and enters the task planning process; 2) Selects the task mode and task scene according to user operations, and the system automatically recommends relevant parameters (such as drone flight altitude, speed, camera parameters, payload device information, etc.); 3) After completing the task approval, transmits the task information to the flight route planning module, and at the same time receives the result information (photos / videos) transmitted by the drone flight execution module after the task is completed, and automatically associates it with the task / event to achieve information closed-loop.

[0027] (3) Flight route planning module: Customizes the inspection area and automatically generates flight routes based on the 3D map. Using camera parameters and geographic information, it calculates a safe and efficient drone flight route to ensure effective coverage of the target area, enhance the perception ability of obstacles, and reduce flight risks.

[0028] The specific process is as follows: Receives the task information sent by the task management module, and automatically calculates or defines key data such as sampling altitude, heading angle, and side overlap rate according to the camera parameters in the task scene; Supports operations on the 3D map, including adding polygon boundary points (converted into a planar polygon in the two-dimensional coordinate system through tools), determining the starting point of the flight route (based on the principle of the shortest distance from the hangar position to the polygon), calculating the longest distance between waypoints and the slope of the parallel line of the flight route angle, and generating the flight route (obtained through a series of complex calculations and intersection processes); Will be based on Figure 3 The route information generated by the dimension model is synchronized to the task management module for users to confirm and adjust; After the mission is confirmed, the route information is synchronized to the drone flight module, allowing the drone to fly according to the preset route.

[0029] (4) Drone flight module Execute UAV flight missions, perform flight operations according to the route determined by the route planning module, collect results information such as photos / videos, and automatically associate the results information with tasks or events to notify the system of task completion status.

[0030] The specific process is as follows: Receive the task notification after approval sent by the task management module, and take off to execute the task according to the route information provided by the route planning module; During the flight, photos / videos and other achievement information are collected. After the mission is completed, the achievement information is automatically associated with the task or event, and the system is notified to complete the information feedback of the entire business process, so that the system can record and subsequently process the mission execution status.

[0031] (5) 3D modeling module By directly calling on drones to survey and map the target scene or receiving uploaded third-party image information of the target scene, the target area is three-dimensionally modeled to construct a three-dimensional map that can accurately reflect key geographical features such as terrain undulations and building heights, providing accurate geographic information data support for subsequent inspection area customization and route planning.

[0032] The specific process is as follows: It is connected to the route planning module and provides it with 3D map data. When the route planning module performs operations based on the 3D map (such as adding polygon boundary points, determining the route starting point, calculating the relationship between waypoints, etc.), it relies on the geographic information contained in the 3D map built by the 3D modeling module to enhance the ability to perceive the situation of obstacles and achieve safer and more efficient route planning.

[0033] It can receive external instructions or trigger signals. When it is necessary to conduct refined management of a specific area or update geographic information, it can start the mapping task of the target scene, obtain the latest geographic data and update the 3D map model to ensure that the geographic information used by the system always maintains accuracy and timeliness. At the same time, it also provides basic data support for other functions in the system involving geographic information display and analysis (such as more accurate calibration of event coordinates when reporting events, etc.).

[0034] Example 2

[0035] This embodiment discloses an inspection method based on the aforementioned inspection and patrol system. This method closely combines the business processes of urban management with the route planning of unmanned aerial vehicles (UAVs) to form a full-process closed loop, as Figure 2 shown. It can be seen from the flowchart that a full-process closed loop is formed from event reporting, task planning, route customization, to result information synchronization. In the flowchart, starting from "event reporting", through links such as "event handling", "task planning", "automatic route planning", and "UAV takeoff", finally, result information (photos / videos) is generated and automatically associated with tasks / events. This not only realizes the seamless connection between event processing and UAV operation but also forms a complete closed loop, ensuring that every event can be effectively processed and feedback, improving the efficiency and accuracy of urban management.

[0036] In this method, first, polygon boundary points are added on the map, and these points on the three-dimensional surface are converted into a planar polygon in the two-dimensional coordinate system through a special tool. Then, the point with the shortest distance from the UAV takeoff point to the polygon is determined as the starting point of the route. Next, the longest distance between waypoints and the slope of the parallel line of the route angle are calculated according to the side overlap rate and sampling accuracy. Rays are formed along the slope direction through the starting point waypoints and translated to obtain the intersection points with the polygon line segments. After traversing the entire polygon to obtain all intersection points, they are connected pairwise to form the route. Finally, the route point coordinates are converted into longitude and latitude and displayed on the three-dimensional map. The generated parallel routes can ensure the comprehensive coverage of the polygon area, improving the integrity and accuracy of the inspection. This complex and intelligent route generation process realizes the automatic conversion from task requirements to the actual flight route, improving the efficiency and accuracy of route planning, and at the same time reducing the introduction of human errors.

[0037] The specific method steps are as follows: (1) Event reporting: Start the system, and relevant personnel can report events to the event processing module through the system event reporting function; (2) Event handling: The system issues the event and determines whether a UAV is needed. If a UAV is needed, enter the UAV flight operation; if a UAV is not needed, directly feedback the result to the system.

[0038] The system of the present invention supports different issuing modes such as immediate issuing, scheduled issuing, and periodic issuing, which can cover all business scenarios in the process of urban management. At the same time, in order to reduce the dependence on human experience.

[0039] (3) Task planning: Select the task method, determine whether to select an existing route, select the task scenario, preview and submit after determining the task, complete the task approval, and enter the UAV flight operation.

[0040] In the present invention, various scenarios of actual task handling are grouped together. In this step, the grouped task scenarios can be directly selected. The system automatically recommends the altitude and speed of the drone, the camera parameters of the drone, and the payload equipment information according to the selected scenario, which can minimize the dependence on human experience.

[0041] If you do not select an existing route, enter the route planning procedure described below.

[0042] (4) Route planning: In traditional route planning, coordinates are manually selected one by one on a two-dimensional map and the order of the coordinates is clearly defined. However, the present invention automatically calculates or defines the camera parameters in the mission scene, such as the height, heading angle, and lateral overlap rate that need to be sampled, and then automatically generates the UAV route. This is also an important innovation of the present invention.

[0043] A three-dimensional map is constructed through the three-dimensional modeling module, and it supports directly defining the cruising area on the three-dimensional map. Through the spatial geographic information of the three-dimensional map, the ability to perceive the situation of obstacles in route planning is enhanced, the flight risk is shifted to the left, and the safety risk during the drone flight is greatly reduced.

[0044] like Figure 3 As shown in the figure, the specific implementation steps of route planning are as follows: a) Calculate or define the accuracy, altitude, flight angle and lateral overlap rate required for sampling based on camera parameters; b) Add polygon boundary points to the 3D map. These points are 3D surfaces on the earth and need to be converted into a 2D coordinate system using tools to become a plane; c) A plane polygon is obtained according to b), and then the take-off point of the UAV is determined by the hangar position, and the point with the shortest distance from the take-off point to the polygon is defined as the starting point of the route, which is also the point with the shortest distance from the aircraft to the route; d) According to the lateral overlap rate and sampling accuracy in a), calculate the longest distance S between two waypoints, and calculate the slope of the boundary line according to the plane polygon obtained in b). e) The waypoint of the starting point forms a ray along the slope direction, and then the ray is translated vertically by a distance S. According to the longest distance S between the two waypoints obtained in d) and the slope, the intersection is obtained and recorded, which becomes a waypoint H1 on the route; f) If the ray is parallel to the line segment or has no intersection within the vertical distance S, the flight of the edge is considered to be completed, and a new boundary needs to be obtained as the line segment of the next cycle; g) Then, continue to move this ray perpendicular to the distance S and the line segment of the polygon, continuously obtain the intersection point, and finally judge the entire polygon once. When the line segment of the polygon becomes the first line segment, stop the loop; h) After obtaining all the intersection points on the polygon in the previous step (the number of intersection points is 2N), find the corresponding first point from the initial point in the reverse direction according to the slope and mark it as the second waypoint (the vertical moving distance corresponding to the waypoint is S). Continuously loop forward, with the other moving backward, and connect them pairwise to form a flight path. i) Finally, convert all points to longitude and latitude through coordinates. What is shown on the 3D map are parallel flight paths. An example diagram of the flight path is as Figure 4 shown.

[0045] (5) UAV flight: The approved task is sent to the system to notify the UAV to take off, and the result information such as photos / videos is automatically associated with the task or time, and the system is notified to complete the patrol flight.

[0046] In summary, the present invention realizes the intelligent planning of the UAV urban management scene inspection and patrol tasks based on geographic information. By integrating the urban management inspection business process, multi-mode task distribution, custom flight path planning on a 3D map, and task scenario management, it realizes the high integration of UAV operation and business management, the diversification and timeliness of task handling, improves the situation awareness ability of flight path planning and the knowledge management of flight path planning, reduces the business threshold of flight path planning, and improves the inspection and patrol efficiency and safety.

[0047] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any form. Any technical solutions obtained by using equivalent replacement or equivalent transformation fall within the protection scope of the present invention.

Claims

1. Here, the UAV urban management scene inspection system based on geographic information is characterized by: include: Event processing module: used to receive reported events, perform preliminary processing and judgment on the events, determine whether drones are needed to deal with them, and pass the processing results to the task management module; Mission management module: responsible for managing drone missions, planning missions according to the instructions of the event processing module, and interacting with the route planning module to determine the specific parameters of the drone flight mission; Route planning module: uses camera parameters and geographic information to calculate a safe and efficient drone flight route and sends it to the drone flight module; Drone flight module: executes drone flight missions, performs flight operations according to the route determined by the route planning module, collects relevant results information and associates it with tasks or events, and notifies the system of task completion status; 3D modeling module: perform 3D modeling of the target area, construct a 3D map, and provide geographic information data support for the system.

2. According to the geographic information-based UAV urban management scene inspection and patrol system according to claim 1, it is characterized in that: In the mission management module, the specific parameters of the flight mission include: UAV flight altitude, speed, camera parameters and payload equipment information.

3. According to the geographic information-based UAV urban management scene inspection and patrol system according to claim 1, it is characterized in that: The results collected by the drone flight module are photos or videos.

4. According to the geographic information-based UAV urban management scene inspection and patrol system according to claim 1, it is characterized in that: The task management system supports at least three task delivery modes: immediate delivery, scheduled delivery and periodic delivery.

5. The inspection method of the unmanned aerial vehicle urban management scene inspection system and the urban management scene inspection system according to any one of claims 1 to 4 is characterized in that: The steps include: (1) Event reporting: Start the system, and relevant personnel report the event to the event processing module; (2) Event processing: The system sends an event to determine whether a drone is needed; (3) Mission planning: select the mission mode, determine whether to select an existing route, select the mission scenario, preview and submit the mission after confirming it, complete the mission approval, and enter the drone flight operation; (4) Route planning: Automatically calculate the camera parameters in the mission scene or define the height, heading angle, and side overlap rate that need to be sampled, and automatically generate the UAV route; (5) Drone flight: The approved mission is sent to the system to notify the drone to take off, and the results information such as photos / videos are automatically associated with the mission or time, notifying the system to complete the flight.

6. The inspection method according to claim 5, characterized in that: If a drone is required to handle the situation, the information will be passed to the task management module and a new drone mission will be added; if not required, the processing results will be fed back to the system to complete the event loop.

7. The inspection method according to claim 5, characterized in that: When planning a mission, if you select an existing route, the system will automatically recommend the altitude and speed of the drone, the camera parameters of the drone, and the payload equipment information according to the selected scenario; If you do not select an existing route, you will enter the route planning program.

8. The inspection method according to claim 5, characterized in that: The route planning is implemented based on a three-dimensional map constructed by a three-dimensional modeling module.

9. The inspection method according to claim 5, characterized in that: The specific implementation steps of the route planning are as follows: a) Calculate or define the accuracy, altitude, flight angle and lateral overlap rate required for sampling based on camera parameters; b) Add polygonal boundary points to the 3D map and use tools to convert it into a 2D coordinate system to form a plane; c) According to b), a plane polygon is obtained, and then the take-off point of the UAV is determined by the hangar position, and the point with the shortest distance from the take-off point to the polygon is defined as the starting point of the route, which is also the point with the shortest distance from the aircraft to the route; d) Calculate the longest distance S between two waypoints based on the lateral overlap rate and sampling accuracy in a), and calculate the slope of the boundary line based on the plane polygon obtained in b); e) The waypoint of the starting point forms a ray along the slope direction, and then the ray is translated vertically by a distance S. According to the longest distance S between the two waypoints obtained in d) and the slope, the intersection point is obtained and recorded, which becomes a waypoint H1 on the route; f) If the ray is parallel to the line segment or has no intersection within the vertical distance S, the flight of the edge is considered to be completed, and a new boundary needs to be obtained as the line segment of the next cycle; Then, continue to move this ray perpendicular to the distance S and the line segment of the polygon, continuously obtain the intersection point, and finally judge the entire polygon again until the line segment of the polygon becomes the first line segment, and stop the loop; h) After obtaining all 2N intersection points on the polygon through the previous step, find the corresponding first point from the initial point in the opposite direction according to the slope and record it as the second waypoint. Keep looping forward and the other backward, connecting them in pairs to form a route; i) Finally, all points are converted into longitude and latitude through coordinates and displayed on a three-dimensional map to form parallel routes.

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