Airspace data and digital base updating method and device, equipment and storage medium

Abstract

The invention provides an airspace data and digital base updating method and device, equipment and a storage medium. The method relates to the technical field of airspace data updating, and comprises the following steps: obtaining a digital base and an airspace grid corresponding to a target area; recognizing changes of components in the target area based on an image recognition algorithm and a space geometry inversion algorithm, and determining an update type of the target area; based on the update type, updating an airspace occupation state corresponding to the airspace grid to obtain a first occupation state; triggering a corresponding data acquisition task based on the first occupancy state; performing data acquisition on the target area through the data acquisition task, and updating data of components in the digital base by using the acquired data to obtain an updated digital base; and updating the first occupancy state based on the updated digital base to obtain a second occupancy state corresponding to the airspace grid, so that the updating timeliness and the updating accuracy can be improved, and the data increment updating requirement can be met.

Description

Technical Field

[0001] This application relates to the technical field of airspace data update, and particularly to a method, device, equipment and storage medium for updating airspace data and digital base. Background Art

[0002] In the current methods for updating airspace data and digital base, it relies on the pilot to manually operate the drone for periodic collection, resulting in poor update timeliness and inability to accurately define the data collection range, leading to waste of resources. Therefore, the current methods for updating airspace data and digital base have problems of poor update timeliness, low update accuracy and inability to meet the data incremental update requirements. Summary of the Invention

[0003] Embodiments of this application provide a method, device, equipment and storage medium for updating airspace data and digital base to solve one or more problems existing in the related art.

[0004] According to the first aspect of this application, there is provided a method for updating airspace data and digital base, the method comprising: obtaining the digital base and airspace grid corresponding to the target area; identifying the changes of components in the target area based on the image recognition algorithm and the spatial geometric inversion algorithm, and determining the update type of the target area; based on the update type, updating the airspace occupancy status corresponding to the airspace grid to obtain the first occupancy status; based on the first occupancy status, triggering the corresponding data collection task; performing data collection on the target area through the data collection task, and updating the data of the components in the digital base with the collected data to obtain the updated digital base; updating the first occupancy status based on the updated digital base to obtain the second occupancy status corresponding to the airspace grid; the second occupancy status is the same as or different from the first occupancy status.

[0005] According to an embodiment of this application, before obtaining the digital base and airspace grid corresponding to the target area, the method further comprises: performing data collection on the target area based on the drone to obtain the oblique photography data and orthophoto data corresponding to the target area; identifying the building projection plane of the orthophoto data based on the building recognition algorithm to obtain the building layer data; constructing the digital base corresponding to the target area based on the building layer data; dividing the airspace of the data base into grids to obtain the airspace grid corresponding to the target area; performing spatial analysis based on the airspace grid and the oblique photography data to determine the association relationship between the airspace grid and the digital base and the initial airspace occupancy status corresponding to the airspace grid.

[0006] According to an embodiment of the present application, identifying changes in components in the target area based on the image recognition algorithm and the spatial geometry inversion algorithm, and determining the update type of the target area includes: analyzing the image data collected by the drone based on the image recognition algorithm, and determining the feature information of the target component and the target time when the target component first appears when the target component first appears in the image data; determining the position information and attitude parameters of the drone corresponding to the target time; analyzing the feature information, position information, and attitude parameters based on the spatial geometry inversion algorithm to determine the spatial position information of the target component; comparing the spatial position information of the target component with the building layer data in the digital base to determine the update type of the target area.

[0007] According to an embodiment of the present application, updating the airspace occupancy status corresponding to the airspace grid based on the update type to obtain the first occupancy status includes: determining the target airspace grid from the airspace grids at different heights based on the update type; the target airspace grid represents the affected airspace range in the target area; updating the airspace occupancy status of the target airspace grid based on the update type to obtain the first occupancy status and determining the occupancy time, occupancy reason, and update time corresponding to the first occupancy status.

[0008] According to an embodiment of the present application, triggering the corresponding data collection task based on the first occupancy status includes: evaluating the first occupancy status to obtain an evaluation result; the evaluation result represents the change degree of the components in the target area and the urgency of data update; determining the corresponding drone and data collection equipment based on the evaluation result; the data collection equipment includes an oblique photography device and / or a laser point cloud data collection device; determining the data collection task plan based on the flight plan of the drone and the meteorological information of the target area; the data collection task plan at least includes: flight path planning, collection time plan, and collection type; controlling the corresponding drone based on the data collection task plan to execute the corresponding data collection task.

[0009] According to an embodiment of the present application, collecting data for the target area through the data collection task and using the collected data to update the data of the components in the digital base to obtain the updated digital base includes: obtaining the oblique photography data and / or laser point cloud data of the target area collected by the drone according to the data collection task; preprocessing the collected data based on the data processing algorithm to obtain the preprocessed data; the data processing algorithm includes data cleaning, coordinate conversion, and format conversion; updating the data of the components in the digital base with the preprocessed data based on the update type to obtain the updated digital base.

[0010] According to an embodiment of the present application, updating the first occupancy status based on the updated digital base to obtain the second occupancy status corresponding to the airspace grid includes: performing spatial analysis on the airspace grid corresponding to the first occupancy status using the updated digital base to obtain the spatial occupancy characteristics of each airspace grid; and updating the first occupancy status based on the spatial occupancy characteristics to obtain the second occupancy status.

[0011] According to a second aspect of the present application, there is provided an airspace data and digital base update device, the device including: an acquisition module for acquiring the digital base and airspace grid corresponding to a target area; an identification module for identifying changes in components in the target area based on an image recognition algorithm and a spatial geometry inversion algorithm to determine the update type of the target area; a first update module for updating the airspace occupancy status corresponding to the airspace grid based on the update type to obtain a first occupancy status; a collection module for triggering a corresponding data collection task based on the first occupancy status; a second update module for performing data collection on the target area through the data collection task and updating the data of the components in the digital base using the collected data to obtain an updated digital base; and a third update module for updating the first occupancy status based on the updated digital base to obtain the second occupancy status corresponding to the airspace grid; the second occupancy status being the same as or different from the first occupancy status.

[0012] According to a third aspect of the present application, there is provided an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method of the present application.

[0013] According to a fourth aspect of the present application, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method of the present application.

[0014] The method of the embodiment of the present application includes: obtaining a digital base and an airspace grid corresponding to a target area; identifying changes in components in the target area based on an image recognition algorithm and a spatial geometry inversion algorithm, and determining the update type of the target area; updating the airspace occupancy status corresponding to the airspace grid based on the update type to obtain a first occupancy status; triggering a corresponding data collection task based on the first occupancy status; performing data collection on the target area through the data collection task, and updating the data of the components in the digital base using the collected data to obtain an updated digital base; updating the first occupancy status based on the updated digital base to obtain a second occupancy status corresponding to the airspace grid; the second occupancy status may be the same as or different from the first occupancy status. In this way, the update timeliness and update accuracy can be improved, and the data incremental update requirement can be met.

[0015] It should be understood that the teachings of the present application do not require achieving all the beneficial effects described above. Instead, specific technical solutions can achieve specific technical effects, and other embodiments of the present application can also achieve beneficial effects not mentioned above. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present application will become readily understood. In the drawings, several embodiments of the present application are shown in an exemplary rather than restrictive manner, where: In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0017] Figure 1 shows a schematic processing flow of the airspace data and digital base update method provided by the embodiment of the present application Figure 1 ; Figure 2 shows a schematic processing flow of the airspace data and digital base update method provided by the embodiment of the present application Figure 2 ; Figure 3 shows an optional schematic diagram of the airspace data and digital base update device provided by the embodiment of the present application; Figure 4 shows a schematic composition structure diagram of an electronic device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, features, and advantages of this application more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0020] In the following description, the terms "first / second" are only used to distinguish similar objects and do not represent a specific order for the objects. It can be understood that "first / second" can be interchanged in a specific order or sequence when allowed, so that the embodiments of this application described here can be implemented in an order other than that illustrated or described here.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0022] The processing flow in the airspace data and digital base update method provided by the embodiments of this application will be described. Refer to Figure 1 , Figure 1 is the schematic diagram of the processing flow of the airspace data and digital base update method provided by the embodiments of this application Figure 1 , and will be described in conjunction with Figure 1 the steps S101-S106 shown.

[0023] Step S101, obtain the digital base and airspace grid corresponding to the target area.

[0024] In some embodiments, the low-altitude airspace specifically refers to the near-ground space area with a height lower than 150 meters in this solution, which is the area available for aircraft to fly excluding areas such as buildings and no-fly zones. The digital base can include: a digital mirror of the physical world jointly composed of GIS (Geographic Information System) data such as terrain, orthophoto, oblique, and laser point cloud, and modeling model data such as 3Dmax and BIM (Building Information Modeling). The airspace grid can include: a plurality of regular or irregular grid cells obtained by dividing the low-altitude airspace according to spatial dimensions based on set rules.

[0025] Step S102: Identify the changes of components in the target area based on the image recognition algorithm and the spatial geometry inversion algorithm, and determine the update type of the target area.

[0026] In some embodiments, the image recognition algorithm can be used to identify the characteristics and changes of components such as buildings and construction devices in the target area. The spatial geometry inversion algorithm can include: a method of using spatial geometry principles and mathematical models to inversely deduce the geometric feature information such as the spatial position, height, and shape of the target component according to known observation data. The spatial geometry inversion algorithm can be used to determine the three-dimensional spatial information of components in the target area in combination with data such as the position and attitude of the unmanned aerial vehicle. The update type can include: classification of the changes occurring in the target area. Specific update types can include: growth-type update, reduction-type update, and complete reduction-type update.

[0027] Step S103: Update the airspace occupancy status corresponding to the airspace grid based on the update type to obtain the first occupancy status.

[0028] In some embodiments, the airspace occupancy status can include: long-term occupancy, short-term occupancy, temporary occupancy, and conflict occupancy. The airspace occupied by buildings and other near-ground auxiliary facilities that only grow positively belongs to long-term occupancy; the areas occupied by tower cranes, long-arm cranes, construction safety protection facilities, etc., which are demolished and the airspace is released after the operation is completed, belong to short-term occupancy; the unavailable airspace caused by satellite signals and meteorological factors belongs to temporary occupancy; during the execution of the unmanned aerial vehicle route task, when a certain area is temporarily occupied and other unmanned aerial vehicles need to avoid it during the same time period, it belongs to conflict occupancy.

[0029] Step S104: Trigger the corresponding data collection task based on the first occupancy status.

[0030] Step S105: Collect data on the target area through the data collection task, and update the data of the components in the digital base using the collected data to obtain the updated digital base.

[0031] Step S106: Update the first occupancy status based on the updated digital base to obtain the second occupancy status corresponding to the airspace grid; the second occupancy status may be the same as or different from the first occupancy status.

[0032] In some embodiments, the data collection task may include: a task of acquiring data related to the target area performed by the unmanned aerial vehicle and the data collection device determined according to the first occupancy status. The data collection task may be used to collect various types of data for updating the digital base and the airspace occupancy status, such as oblique photography data and / or lidar point cloud data. The first occupancy status may include: the occupancy of the airspace grid after the initial update based on the update type. The data of the components in the digital base may include: information on various basic elements constituting the digital base. The specific data of the components may include: data such as the shape, size, and position of the building, and the type, height, and coordinates of the construction device. The data of the components may be used to describe the physical entity characteristics in the target area. The second occupancy status may include: the occupancy of the airspace grid re-evaluated based on the updated digital base. The second occupancy status may be a confirmation, correction, or supplement to the first occupancy status. The second occupancy status may be used to reflect the occupancy status of the low-altitude airspace and ensure the accuracy of the airspace grid.

[0033] The method of the embodiment of the present application effectively solves the problems of long update cycle and poor real-time performance of the digital base and the airspace status during the large-scale engineering construction stage by using the unmanned aerial vehicle cluster to actively trigger the data update and collection task, and can accurately restore the current situation of the low-altitude area. At the same time, the grid is carefully divided, and combined with the immediate update and deterministic update methods, rapid local update of the digital base in various situations such as long-term, short-term, and temporary occupancy is realized, which can meet the data incremental update requirements and ensure the accuracy and overall rationality of the update. In addition, by using the AI recognition of the images collected by the pan-tilt head and the monitoring means of the flight path change, the perception and recognition ability of the unmanned aerial vehicle to obstacles and the accurate feedback on the changes of the digital base are improved. By automatically triggering different types of unmanned aerial vehicle tasks and plans through event classification and discrimination, the timeliness and accuracy of data collection are improved. Finally, through the update of the airspace grid occupancy to drive the data base collection and update, and the verification update after the base update, a two-way dynamic update mechanism is formed, which not only ensures the accuracy of the data but also improves the update efficiency.

[0034] In some embodiments, a schematic diagram of the processing flow of the airspace data and digital base update method Figure 2 is as Figure 2 shown. Before step S101 of obtaining the digital base and the airspace grid corresponding to the target area, the airspace data and digital base update method may further include: Step S201: Perform data collection on the target area based on the unmanned aerial vehicle to obtain the oblique photography data and the orthophoto image data corresponding to the target area.

[0035] Step S202: Identify the building projection planes from the orthophoto image data based on the building recognition algorithm to obtain the building layer data.

[0036] Step S203: Construct the digital base corresponding to the target area based on the building layer data.

[0037] Step S204: Divide the airspace of the data base into grids to obtain the airspace grids corresponding to the target area.

[0038] Step S205: Conduct spatial analysis based on the airspace grids and the oblique photography data to determine the association relationship between the airspace grids and the digital base and the initial airspace occupancy status corresponding to the airspace grids.

[0039] In this embodiment, the oblique photography data may include: image data containing the three-dimensional information of the components in the target area obtained through the oblique photography technology. The orthophoto image data can be used as the basic base map of the digital base. The building projection plane may include: the surface element formed by the orthographic projection of the top of the building on the orthophoto image data. The building projection plane can be used to determine the position of the building in the horizontal direction. The building layer data may include: the geographical space layer data formed by integrating the projection planes of various buildings and their related attribute information. The spatial analysis may include: the process of analyzing the data through technologies such as geographic information systems. The spatial analysis can be used to determine the association relationship between the airspace grids and the digital base and the initial airspace occupancy status corresponding to the airspace grids. The initial airspace occupancy status may include: after the construction of the digital base and the division of the airspace grids are completed, the initial occupancy situation of whether the airspace grids are occupied and by what objects according to the initial data.

[0040] As an example, to establish the digital base and airspace grids of the project construction area, the implementation method is as follows: 1. Conduct an aerial flight data collection over the entire project construction area to obtain oblique photography data and orthophoto image data. 2. Using the orthophoto image data as the data source, identify the building projection surfaces using an aerial photography-based building recognition algorithm. Save each monomerized building, continuous building cluster, or operation equipment projection surface as a vector surface element and output it as Layer A. Layer A contains fields such as "code", "type", "vertex height", etc. Each individual element has a unique code, such as 00001. 3. Take the maximum range boundary of the project construction area as the horizontal boundary, and the height range from the lowest elevation within the current horizontal boundary to an elevation of 200 meters. According to the principle of the Beidou grid position code dissection, dissect it at the eighth level horizontally and the eighth level vertically to form grids approximately equal to 0.97m × 0.97m × 0.97m. 4. Encode the grids based on a 16-bit horizontal code + 10-bit vertical code. For example, N50J47539B8255340000001120 represents the unique code at longitude: 116.0°18.0' 45.370000" E, latitude: 39.0°59.0' 35.380000" N, and height: 200.000000. Among them, the encoding rule for the grids according to longitude, latitude, and height is the "Beidou Grid Position Code" (GB / T39409-2020). 5. Store the codes corresponding to the grids in the spatial database, and add additional fields such as "update time", "status", "occupation category", "building belonging to", etc. to form Grid Set B. The initial values of the attributes of the fields such as "update time", "status", "occupation category", "building belonging to" in Grid Set B are all empty. The "building belonging to" field can be used to associate with the unique code of the single element in Step 2. 6. Use the oblique photography data collected in Step 1 and the grids in Grid Set B for spatial analysis. When there is a spatial intersection between a certain grid and the oblique photography data, update the "status" field to occupied, the category to long-term occupation, and the "update time" to the current time of spatial analysis. Mark the "status" fields of the remaining grids in Grid Set B as unoccupied. 7. Screen out the grids in Grid Set B with the "status" field being occupied, and conduct an intersection analysis of horizontal projection with the vector surface elements in Layer A in Step 2. Assign the unique code in Layer A to the building (equipment) belonging to in Grid Set B to obtain the association relationship between the airspace grids and the digital base. 8. Slice and store the oblique photography data according to the grids, and the data of each area can use the Beidou grid position code as the index code. 9. Conduct an overlay analysis of Layer A and the oblique photography, extract the height of the buildings in the oblique photography, and store it under the highest point height attribute of the corresponding elements in Layer A.

[0041] In some embodiments, the airspace data and digital base update method may further include: building a perception and analysis module. The purpose of building the perception and analysis module is to form a cloud computing service module, which receives information such as drone images, positions, and events in all flight states for unified analysis. The implementation method is as follows: 1. Create a middle platform for a video server to access the real-time live stream of the gimbal carried by the drone and process it into a data format for image recognition and output; 2. Create a position and status recording module to obtain the real-time position of the drone and the status of the equipment mounted on the drone at a frequency of twice per second. The real-time position includes longitude, latitude, and altitude, and the status of the equipment mounted on the drone includes parameters such as the orientation and pitch angle of the gimbal; 3. Create an event recording module to record events such as temporary route changes, automatic avoidance, and forced hovering and returning during the flight of the drone; 4. Create an AI image recognition service module based on video data to receive the data source provided by the video server and perform image recognition of components such as buildings and construction devices.

[0042] In some embodiments, the airspace data and digital base update method may further include: building a data update task scheduling module; the main function of the data update task scheduling module is to analyze various factors after updating the airspace occupancy status corresponding to the airspace grid, form a reasonable flight plan, and send it to the corresponding drone for execution. The implementation method is as follows: 1. Receive real-time data such as meteorological grid points, band radars, and ground stations, as well as real-time data such as communication signals and electromagnetism, and slice these data according to the airspace grid to obtain the result of whether the airspace grid is available airspace; 2. Synchronize the change result of the airspace grid to the status of the airspace grid, such as "unavailable" and the occupancy category is "temporary occupancy"; 3. Obtain the route tasks of each drone in the current flight plan task, and update the occupancy status of the airspace grid intersecting the route according to the waypoints and passing times of the route, such as "unavailable" and the category is "conflict occupancy"; 4. Receive the data collection task, complete the selection of the drone and the data collection device, and control the corresponding drone to perform the data collection task in combination with the airspace situation.

[0043] In some embodiments, step S102 may include: analyzing the image data collected by the drone based on an image recognition algorithm, and when the target component first appears in the image data, determining the feature information of the target component and the target time when the target component first appears; determining the position information and attitude parameters of the drone corresponding to the target time; analyzing the feature information, position information, and attitude parameters based on a spatial geometric inversion algorithm to determine the spatial position information of the target component; comparing the spatial position information of the target component with the building layer data in the digital base to determine the update type of the target area.

[0044] In this embodiment, the image data collected by the drone may include: the image data in the image data sequence collected by the drone. The feature information may include: the shape feature, color feature, texture feature, etc. of the target component. The target time may include the time stamp when the target component first appears in the image data sequence. The position information may include: the geographical coordinates where the drone is located when collecting the image. The attitude parameters may include: parameters such as the heading angle, pitch angle, roll angle, etc. of the drone when collecting the image. The spatial position information may include: information such as the coordinate position and height range of the target component in the three-dimensional geographical space. The building layer data may include: the vector data corresponding to the spatial position information in the digital base.

[0045] As an example, for the recognition of the occupancy growth change of the buildings in the target area, the implementation method is as follows: 1. First, de-duplicate the building results such as buildings recognized by the image recognition module to obtain the feature information of the target component in the case where the target building first appears in the image data; 2. According to the target time when the target building is recognized, obtain the position of the drone and the state parameters (focal length, attitude angle) of the data acquisition device at the target time; 3. Use the spatial geometric inversion algorithm to calculate the top height H1 and the planar coordinate position coor1 of the target building; 4. Perform superposition analysis according to the planar coordinate position coor1 and the building layer data in the digital base to obtain the unique code code1 of the target building and the highest point height attribute H2. If the result of H1 - H2 is greater than 1 meter, it can be determined that the update type of the target area is growth-type update; 5. For the target area with the update type of growth-type update, record the number and time of the growth-type update.

[0046] In some embodiments, step S103 may include: determining the target airspace grid from the airspace grids at different heights based on the update type; the target airspace grid represents the affected airspace range in the target area; based on the update type, update the airspace occupancy status of the target airspace grid to obtain the first occupancy status and determine the occupancy time, occupancy reason, and update time corresponding to the first occupancy status.

[0047] In this embodiment, the airspace grids at different heights may include: multiple levels of airspace grids divided at a certain height interval, and each grid has a different height range. The airspace grids at different heights can be used to represent the airspace occupancy of the target area in the vertical direction. The target airspace grid may include: the airspace grid affected in the target area determined according to the update type. The occupancy time may include: the specific time range or time point when the target airspace grid is occupied. The occupancy reason may include: the specific reason for causing the target airspace grid to be occupied, such as building construction, temporary activity setup, etc. The update time may include: the time when the airspace occupancy status of the target airspace grid is updated.

[0048] As an example, the immediate update of the airspace occupancy status is implemented as follows: When the update type is an incremental update, for the grid sets C directly above the spatial retrieval code1 plane, D at the H2 height, and E at the H1 - H2 height, the airspace grids in grid set E are determined as the target airspace grids, and only the occupancy status of grid set E is updated, without updating the "belonging building" field. If no existing building plane is retrieved in layer A for the identified coordinates, the airspace grids within the height range of 0 - H2 directly above coor1 are determined as the target airspace grids, the airspace occupancy status is updated, and the height field in layer A is updated. When an incremental update of short-term occupancy is identified, the number of times the target area is identified as reduced within 24 hours is determined from the building layer data of the plane. Only when it reaches three times is the airspace occupancy status of the airspace grids updated. For a partial reduction incremental update, the grids in grid set B with a height between H1 and H2 are determined as the target airspace grids through the belonging building code1, and the airspace occupancy status is updated to the released state; for a complete reduction incremental update, the target airspace grids of the vertical area are calculated based on the coor1 coordinates of the plane, and the airspace occupancy status is updated to the released state and the associated building layer is deleted.

[0049] As an example, the immediate update of the airspace occupancy status may further include: The event record in the perception analysis module collects events such as hovering and automatic avoidance during the flight of the UAV that change the established flight path, and filters out the events caused by the sensor (lidar) identifying hazards. Based on the UAV coordinate position at the time of the event and the direction and distance of the obstacle identified by the lidar, the spatial position information of the obstacle is calculated inversely, and the spatial position information of the obstacle is compared with the building layer data in the digital base to determine the update type of the target area. Based on the update type, the airspace grids where the obstacle is located are determined from the airspace grids at different heights; based on the update type, the airspace occupancy status of the airspace grids where the obstacle is located is updated to obtain the first occupancy status and determine the occupancy time, occupancy reason, and update time corresponding to the first occupancy status.

[0050] In some embodiments, step S104 may include: evaluating the first occupancy status to obtain an evaluation result; the evaluation result represents the degree of change of components and the urgency of data update in the target area; based on the evaluation result, the corresponding UAV and data acquisition equipment are determined; the data acquisition equipment includes an oblique photography device and / or a laser point cloud data acquisition device; based on the flight plan of the UAV and the meteorological information of the target area, a data acquisition task plan is determined; the data acquisition task plan at least includes: flight path planning, acquisition time plan, and acquisition type; the corresponding UAV is controlled based on the data acquisition task plan to execute the corresponding data acquisition task.

[0051] In this embodiment, the evaluation result may include: the degree of component change and the urgency of data update in the target area obtained after analyzing the first occupancy state. The data acquisition device may include: an oblique photography device and / or a lidar data acquisition device. The oblique photography device may include: a multi-angle camera installed on a drone, capable of obtaining image data of the target area from vertical and multiple oblique angles. The lidar data acquisition device may include: devices such as lidar that emit laser pulses and receive reflected signals. The flight plan may include: the flight task arrangement preset for the drone. Specifically, the flight plan may include information such as the flight area, flight altitude, flight speed, takeoff and landing time, etc. The meteorological information may include: the weather condition information of the target area. Specifically, the meteorological information may include wind speed, wind direction, visibility, and precipitation.

[0052] As an example, to trigger the data acquisition task, the implementation method is as follows: 1. When the evaluation result is a positive growth event of a building, and this event has been cumulatively triggered 5 times after the last base update time. Then, find the drone with the closest distance and having the ability to collect oblique photography data around according to the location of the target area; 2. When the evaluation result is a positive growth event of short-term occupancy type, and this event has been cumulatively triggered 3 times after the last base update time. Then, find the drone with the closest distance and having the ability to collect lidar data around according to the location of the target area; 3. When the evaluation result is a complete reduction event of short-term obstacles and the trigger times reach 3 times, then find the drone with the closest distance and having the ability to collect oblique photography data around according to the location of the target area; 4. According to the flight plan of the drone and the meteorological information of the target area obtained recently, plan the flight path and execution time of the data acquisition task plan, and the priority of the data acquisition task plan is lower than that of other inspection tasks; 5. If it is found on the same day that the same drone needs to execute multiple data acquisition tasks and the acquisition types are the same; then re-plan the task acquisition target points in multiple data acquisition task plans to reduce the flight consumption of the drone and achieve the data update of multiple target areas in one flight of the drone.

[0053] In some embodiments, step S105 may include: obtaining the oblique photography data and / or lidar data of the target area collected by the drone according to the data acquisition task; preprocessing the collected data based on a data processing algorithm to obtain preprocessed data; the data processing algorithm includes data cleaning, coordinate transformation, and format transformation; based on the update type, using the preprocessed data to update the data of the components in the digital base to obtain an updated digital base.

[0054] As an example, the data of components in the digital base is updated, and the implementation method is as follows: 1. After the data collection task is completed, use mapping tools to process the oblique photography data and / or laser point cloud data of the target area to obtain a three-dimensional data model corresponding to each collection point in the data collection task; 2. Update the data of components in the digital base according to update types such as "original model positive growth", "initial addition model growth", and "complete reduction"; 3. When the data of components in the digital base needs to be updated with the original model positive growth, match the building surface code xxxx1 corresponding to the target area in layer A, and then screen out the grids in grid B when the digital base is built whose affiliated building matches the code xxxx1, and update the data of the components contained in the grids to the data of the newly collected components; 4. Similarly, when the update is a complete reduction, the data of the components is also updated by grid. After the update is completed, delete the original occupied surface of the components in layer A; 5. When it is the initial addition model growth, first obtain the surface data and model height according to the vertical projection range of the newly added components, and update layer A, and then update the model in terms of grid dimension according to the occupied grids. In some embodiments, step S106 may include: performing spatial analysis on the airspace grids corresponding to the first occupancy state using the updated digital base to obtain the spatial occupancy characteristics of each airspace grid; based on the spatial occupancy characteristics, updating the first occupancy state to obtain a second occupancy state.

[0055] As an example, perform spatial analysis on the updated digital base and the airspace grids corresponding to the first occupancy state. Using GIS software, overlay and analyze the three-dimensional data of components such as buildings and construction devices in the digital base with the airspace grids, calculate the spatial relationship between each airspace grid and these components, and obtain the spatial occupancy characteristics of each airspace grid. For example, determine which airspace grids are penetrated by the tops of buildings, which grids completely contain construction devices, and which grids are close to obstacles but not occupied, etc. Then, based on these spatial occupancy characteristics, update the first occupancy state. If the spatial occupancy characteristics show that the actual occupied height of a certain airspace grid by a building exceeds the previous record, update the first occupancy state of this grid (such as the initial record is unoccupied) to the second occupancy state (long-term occupancy), and record the occupancy height range and building information; if the analysis finds that a certain grid was misjudged as being temporarily occupied by an obstacle due to data errors, and in fact the obstacle has been removed, update the occupancy state of this grid from the first occupancy state (temporary occupancy) to the second occupancy state (unoccupied).

[0056] Next, continue to describe the exemplary structure of the software modules included in the airspace data and digital base update device 90 provided in the embodiments of the present application. In some embodiments, such as Figure 3As shown, the airspace data and digital base update device 90 may include: an acquisition module 901, configured to acquire the digital base and airspace grid corresponding to the target area; an identification module 902, configured to identify changes in components in the target area based on an image recognition algorithm and a spatial geometry inversion algorithm, and determine the update type of the target area; a first update module 903, configured to update the airspace occupancy status corresponding to the airspace grid based on the update type to obtain a first occupancy status; a collection module 904, configured to trigger corresponding data collection tasks based on the first occupancy status; a second update module 905, configured to perform data collection on the target area through the data collection task, and update the data of the components in the digital base with the collected data to obtain an updated digital base; a third update module 906, configured to update the first occupancy status based on the updated digital base to obtain a second occupancy status corresponding to the airspace grid; the second occupancy status may be the same as or different from the first occupancy status.

[0057] In some embodiments, the airspace data and digital base update device 90 further includes a construction module, and the construction module is configured to: perform data collection on the target area based on a drone to obtain the oblique photography data and orthophoto data corresponding to the target area; identify the building projection plane of the orthophoto data based on a building recognition algorithm to obtain building layer data; construct the digital base corresponding to the target area based on the building layer data; perform grid division on the airspace of the data base to obtain the airspace grid corresponding to the target area; perform spatial analysis based on the airspace grid and the oblique photography data to determine the association relationship between the airspace grid and the digital base and the initial airspace occupancy status corresponding to the airspace grid.

[0058] In some embodiments, the identification module 902 is configured to: analyze the image data collected by the drone based on an image recognition algorithm, and determine the feature information of the target component and the target time when the target component first appears in the case where the target component first appears in the image data; determine the position information and attitude parameters of the drone corresponding to the target time; analyze the feature information, position information, and attitude parameters based on a spatial geometry inversion algorithm to determine the spatial position information of the target component; compare the spatial position information of the target component with the building layer data in the digital base to determine the update type of the target area.

[0059] In some embodiments, the first update module 903 is configured to: determine a target airspace grid from airspace grids at different altitudes based on the update type; the target airspace grid represents the affected airspace range in the target area; update the airspace occupancy status of the target airspace grid based on the update type to obtain a first occupancy status and determine the occupancy time, occupancy reason, and update time corresponding to the first occupancy status.

[0060] In some embodiments, the acquisition module 904 is configured to: evaluate the first occupancy status to obtain an evaluation result; the evaluation result represents the degree of change of components and the urgency of data update in the target area; determine corresponding unmanned aerial vehicles (UAVs) and data acquisition devices based on the evaluation result; the data acquisition devices include oblique photography devices and / or laser point cloud data acquisition devices; determine a data acquisition task plan based on the flight plan of the UAV and the meteorological information of the target area; the data acquisition task plan at least includes: flight path planning, acquisition time plan, and acquisition type; control the corresponding UAV based on the data acquisition task plan to perform the corresponding data acquisition task.

[0061] In some embodiments, the second update module 905 is configured to: obtain the oblique photography data and / or laser point cloud data of the target area acquired by the UAV according to the data acquisition task; preprocess the acquired data based on a data processing algorithm to obtain preprocessed data; the data processing algorithm includes data cleaning, coordinate transformation, and format transformation; update the data of the components in the digital base using the preprocessed data based on the update type to obtain an updated digital base.

[0062] In some embodiments, the third update module 906 is configured to: perform a spatial analysis on the airspace grid corresponding to the first occupancy status using the updated digital base to obtain the spatial occupancy characteristics of each airspace grid; update the first occupancy status based on the spatial occupancy characteristics to obtain a second occupancy status.

[0063] It should be noted that the description of the device in the embodiments of the present application is similar to the description of the above method embodiments and has similar beneficial effects as the method embodiments, so details will not be repeated here. For the technical details not covered in the airspace data and digital base update device provided in the embodiments of the present application, they can be understood according to the description of any one of the Figures 1 to 2 accompanying drawings.

[0064] According to the embodiments of the present application, the present application also provides an electronic device and a non-transitory computer-readable storage medium.

[0065] Figure 4FIG. 0 shows a schematic block diagram of an exemplary electronic device 800 that can be used to implement embodiments of the present application. The electronic device is intended to represent various forms of digital computers, such as, for example, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as, for example, personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present application described and / or claimed herein.

[0066] As Figure 4 shown, the electronic device 800 includes a computing unit 801 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the electronic device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0067] A plurality of components in the electronic device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the electronic device 800 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0068] The computing unit 801 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 executes the various methods and processes described above, such as the airspace data and digital base update methods. For example, in some embodiments, the airspace data and digital base update methods can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the airspace data and digital base update methods described above can be executed. Alternatively, in other embodiments, the computing unit 801 can be configured to execute the airspace data and digital base update methods in any other suitable manner (e.g., by means of firmware).

[0069] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0070] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0071] In the context of this application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0072] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0073] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0074] A computer system can include a client and a server. The client and the server are generally far apart from each other and typically interact through a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, can also be a server of a distributed system, or a server incorporating a blockchain.

[0075] It should be understood that the various forms of processes shown above can be used, with steps reordered, added or deleted. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in this application can be achieved, and no limitations are imposed herein.

[0076] As described above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims

1. A method for updating airspace data and digital base, characterized in that, The method includes: Obtaining a digital base and an airspace grid corresponding to the target area; Identifying changes in components in the target area based on an image recognition algorithm and a spatial geometry inversion algorithm, and determining the update type of the target area; Updating the airspace occupancy status corresponding to the airspace grid based on the update type to obtain a first occupancy status; Triggering a corresponding data collection task based on the first occupancy status; Performing data collection on the target area through the data collection task, and updating the data of the components in the digital base with the collected data to obtain an updated digital base; Updating the first occupancy status based on the updated digital base to obtain a second occupancy status corresponding to the airspace grid; the second occupancy status is the same as or different from the first occupancy status.

2. The method according to claim 1, wherein Before obtaining the digital base and the airspace grid corresponding to the target area, the method further includes: Performing data collection on the target area based on a drone to obtain oblique photography data and orthophoto data corresponding to the target area; Identifying the building projection plane of the orthophoto data based on a building recognition algorithm to obtain building layer data; Constructing a digital base corresponding to the target area based on the building layer data; Dividing the airspace of the data base into grids to obtain an airspace grid corresponding to the target area; Performing spatial analysis based on the airspace grid and the oblique photography data to determine the association relationship between the airspace grid and the digital base and the initial airspace occupancy status corresponding to the airspace grid.

3. The method according to claim 1, wherein The identifying changes in components in the target area based on an image recognition algorithm and a spatial geometry inversion algorithm, and determining the update type of the target area includes: Analyzing the image data collected by the drone based on the image recognition algorithm, and determining the feature information of the target component and the target time when the target component first appears in the case where the target component first appears in the image data; Determining the position information and attitude parameters of the drone corresponding to the target time; Analyzing the feature information, position information, and attitude parameters based on the spatial geometry inversion algorithm to determine the spatial position information of the target component; Comparing the spatial position information of the target component with the building layer data in the digital base to determine the update type of the target area.

4. The method according to claim 1, wherein The updating the airspace occupancy status corresponding to the airspace grid based on the update type to obtain a first occupancy status includes: Determining a target airspace grid from airspace grids at different heights based on the update type; the target airspace grid represents the affected airspace range in the target area; Updating the airspace occupancy status of the target airspace grid based on the update type to obtain the first occupancy status and determining the occupancy time, occupancy reason, and update time corresponding to the first occupancy status.

5. The method according to claim 1, characterized in that, The triggering a corresponding data collection task based on the first occupancy status includes: Evaluating the first occupancy status to obtain an evaluation result; the evaluation result represents the change degree of components in the target area and the urgency of data update; Based on the evaluation results, determine the corresponding unmanned aerial vehicle (UAV) and data acquisition device; the data acquisition device includes an oblique photography device and / or a laser point cloud data acquisition device; Based on the flight plan of the UAV and the meteorological information of the target area, determine the data acquisition task plan; the data acquisition task plan at least includes: flight path planning, acquisition time plan, and acquisition type; Control the corresponding UAV based on the data acquisition task plan to perform the corresponding data acquisition task.

6. The method according to claim 1, wherein The data acquisition of the target area through the data acquisition task and the update of the data of the components in the digital base using the acquired data to obtain the updated digital base includes: Obtain the oblique photography data and / or laser point cloud data of the target area acquired by the UAV according to the data acquisition task; Perform preprocessing on the acquired data based on a data processing algorithm to obtain preprocessed data; the data processing algorithm includes data cleaning, coordinate transformation, and format conversion; Based on the update type, update the data of the components in the digital base using the preprocessed data to obtain the updated digital base.

7. The method according to claim 1, characterized in that, The update of the first occupancy status based on the updated digital base to obtain the second occupancy status corresponding to the airspace grid includes: Perform spatial analysis on the airspace grid corresponding to the first occupancy status using the updated digital base to obtain the spatial occupancy characteristics of each airspace grid; Based on the spatial occupancy characteristics, update the first occupancy status to obtain the second occupancy status.

8. An airspace data and digital base update device, characterized in that The device includes: An acquisition module, configured to acquire the digital base and the airspace grid corresponding to the target area; An identification module, configured to identify the changes of the components in the target area based on an image recognition algorithm and a spatial geometric inversion algorithm, and determine the update type of the target area; A first update module, configured to update the airspace occupancy status corresponding to the airspace grid based on the update type to obtain the first occupancy status; An acquisition module, configured to trigger the corresponding data acquisition task based on the first occupancy status; A second update module, configured to perform data acquisition on the target area through the data acquisition task and update the data of the components in the digital base using the acquired data to obtain the updated digital base; A third update module, configured to update the first occupancy status based on the updated digital base to obtain the second occupancy status corresponding to the airspace grid; the second occupancy status is the same as or different from the first occupancy status.

9. An electronic device, characterized in that, Includes: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause a computer to execute the method according to any one of claims 1-7.

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