Airspace data and digital base update methods, apparatus, equipment and storage media

Abstract

This application provides a method, apparatus, device, and storage medium for updating airspace data and digital base; relating to the field of airspace data updating technology, including: acquiring a digital base and airspace grid corresponding to a target area; identifying changes in components in the target area based on image recognition algorithms and spatial geometric inversion algorithms to determine 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 acquisition task based on the first occupancy status; acquiring data from the target area through the data acquisition task, and using the acquired data to update the data of components in the digital base 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. This improves update timeliness and accuracy while meeting the needs of incremental data updates.

Description

Technical Field

[0001] This application relates to the field of airspace data update technology, and in particular to a method, apparatus, device and storage medium for updating airspace data and digital base. Background Technology

[0002] Current methods for updating airspace data and digital docking stations rely on pilots manually operating drones for periodic data collection. This results in poor update timeliness and an inability to precisely define the data collection range, leading to resource waste. Therefore, current airspace data and digital docking station update methods suffer from poor update timeliness, low update accuracy, and an inability to meet the needs of incremental data updates. Summary of the Invention

[0003] This application provides a method, apparatus, device, and storage medium for updating airspace data and digital docking stations to address one or more problems existing in the related technologies.

[0004] According to a first aspect of this application, a method for updating spatial data and a digital base is provided. The method includes: acquiring a digital base and a spatial grid corresponding to a target area; identifying changes in components within the target area based on an image recognition algorithm and a spatial geometric inversion algorithm, and determining an update type for the target area; updating the spatial occupancy state corresponding to the spatial grid based on the update type to obtain a first occupancy state; triggering a corresponding data acquisition task based on the first occupancy state; acquiring data from the target area through the data acquisition task, and using the acquired data to update the data of components in the digital base to obtain an updated digital base; updating the first occupancy state based on the updated digital base to obtain a second occupancy state corresponding to the spatial grid; the second occupancy state may be the same as or different from the first occupancy state.

[0005] According to one embodiment of this application, before obtaining the digital base and spatial grid corresponding to the target area, the method further includes: collecting data on the target area using a UAV to obtain oblique photogrammetry data and orthophoto data corresponding to the target area; identifying building projection surfaces in the orthophoto data using 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 spatial domain of the data base into a grid to obtain a spatial grid corresponding to the target area; and performing spatial analysis based on the spatial grid and the oblique photogrammetry data to determine the correlation between the spatial grid and the digital base and the initial spatial occupancy state corresponding to the spatial grid.

[0006] According to one embodiment of this application, the step of identifying changes in components in the target region based on image recognition algorithms and spatial geometric inversion algorithms, and determining the update type of the target region, includes: analyzing image data collected by a UAV based on the image recognition algorithm; determining the feature information of the target component and the target time of the first appearance of the target component when the target component first appears in the image data; determining the position information and attitude parameters of the UAV corresponding to the target time; analyzing the feature information, position information, and attitude parameters based on the spatial geometric inversion algorithm to determine the spatial position information of the target component; and 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 region.

[0007] According to one embodiment of this application, 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 altitudes based on the update type; the target airspace grid representing the affected airspace range in the target region; 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 one embodiment of this application, triggering a corresponding data acquisition task based on the first occupancy state includes: evaluating the first occupancy state to obtain an evaluation result; the evaluation result characterizes the degree of change of components in the target area and the urgency of data updates; based on the evaluation result, determining the corresponding UAV and data acquisition equipment; the data acquisition equipment includes oblique photography equipment and / or laser point cloud data acquisition equipment; based on the flight plan of the UAV and the meteorological information of the target area, determining a data acquisition task plan; the data acquisition task plan includes at least: flight path planning, acquisition time plan, and acquisition type; and controlling the corresponding UAV to execute the corresponding data acquisition task based on the data acquisition task plan.

[0009] According to one embodiment of this application, the step of collecting data from the target area through a data acquisition task and updating the data of the components in the digital base using the acquired data to obtain an updated digital base includes: acquiring oblique photography data and / or laser point cloud data of the target area collected by a UAV according to the data acquisition task; preprocessing 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; and updating the data of the components in the digital base using the preprocessed data based on the update type to obtain an updated digital base.

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

[0011] According to a second aspect of this application, a spatial data and digital base updating device is provided. The device includes: an acquisition module for acquiring a digital base and a spatial 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 geometric inversion algorithm, and determining an update type for the target area; a first update module for updating the spatial occupancy status corresponding to the spatial grid based on the update type, to obtain a first occupancy status; an acquisition module for triggering a corresponding data acquisition task based on the first occupancy status; a second update module for acquiring data from the target area through the data acquisition task, and using the acquired data to update the data of components in the digital base, 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 a second occupancy status corresponding to the spatial grid; wherein the second occupancy status may be the same as or different from the first occupancy status.

[0012] According to a third aspect of this application, an electronic device is provided, comprising:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in this application.

[0016] According to a fourth aspect of this application, a non-transitory computer-readable storage medium is provided storing computer instructions for causing the computer to perform the methods described in this application.

[0017] The method of this application embodiment obtains a digital base and a spatial grid corresponding to a target area; identifies changes in components in the target area based on image recognition algorithms and spatial geometric inversion algorithms to determine the update type of the target area; updates the spatial occupancy state corresponding to the spatial grid based on the update type to obtain a first occupancy state; triggers a corresponding data acquisition task based on the first occupancy state; collects data from the target area through the data acquisition task, and uses the collected data to update the data of the components in the digital base to obtain an updated digital base; updates the first occupancy state based on the updated digital base to obtain a second occupancy state corresponding to the spatial grid; the second occupancy state may be the same as or different from the first occupancy state. This improves update timeliness and accuracy while meeting the needs of incremental data updates.

[0018] It should be understood that the teachings of this application are not required to achieve all the beneficial effects described above, but rather that a specific technical solution can achieve a specific technical effect, and other embodiments of this application can also achieve beneficial effects not mentioned above. Attached Figure Description

[0019] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of this application are illustrated in the drawings by way of example and not limitation, wherein:

[0020] In the drawings, the same or corresponding reference numerals denote the same or corresponding parts.

[0021] Figure 1 This illustration shows a flowchart of the airspace data and digital baseboard update method provided in an embodiment of this application. Figure 1 ;

[0022] Figure 2 This illustration shows a flowchart of the airspace data and digital baseboard update method provided in an embodiment of this application. Figure 2 ;

[0023] Figure 3 This illustration shows an optional schematic diagram of the airspace data and digital base station update device provided in an embodiment of this application;

[0024] Figure 4 A schematic diagram of the composition structure of the electronic device provided in the embodiments of this application is shown. Detailed Implementation

[0025] To make the objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0027] In the following description, the terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first" and "second" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0029] The processing flow of the airspace data and digital baseboard update method provided in the embodiments of this application is described below. See also Figure 1 , Figure 1 This is a schematic diagram of the processing flow of the airspace data and digital baseboard update method provided in the embodiments of this application. Figure 1 , will combine Figure 1 Steps S101-S106 shown will be explained.

[0030] Step S101: Obtain the digital base and spatial grid corresponding to the target area.

[0031] In some embodiments, low-altitude airspace specifically refers to the near-ground space area with an altitude below 150 meters, excluding areas such as buildings and no-fly zones, which are areas suitable for aircraft to fly. The digital base may include: a digital mirror of the physical world composed of GIS (Geographic Information System) data such as terrain, orthophotos, oblique projections, and laser point clouds, and modeling model data such as 3Dmax and BIM (Building Information Modeling). The airspace grid may include: multiple regular or irregular grid units that divide the low-altitude airspace according to spatial dimensions based on defined rules.

[0032] Step S102: Based on image recognition algorithm and spatial geometric inversion algorithm, identify the changes of components in the target area and determine the update type of the target area.

[0033] In some embodiments, image recognition algorithms can be used to identify the characteristics and changes of components such as buildings and construction equipment in a target area. Spatial geometric inversion algorithms can include methods that use spatial geometric principles and mathematical models to infer the spatial location, height, shape, and other geometric features of target components from known observation data. Spatial geometric inversion algorithms can be used to determine the three-dimensional spatial information of components in a target area by combining data such as the position and attitude of a UAV. Update types can include the classification of changes occurring in the target area. Specific update types can include: growth updates, reduction updates, and complete reduction updates.

[0034] Step S103: Based on the update type, update the airspace occupancy status corresponding to the airspace grid to obtain the first occupancy status.

[0035] In some embodiments, airspace occupancy status can include: long-term occupancy, short-term occupancy, temporary occupancy, and conflict occupancy. Airspace occupied by buildings and other near-ground ancillary facilities that only grow in the future is considered long-term occupancy; areas occupied by tower cranes, long-arm cranes, construction safety protection facilities, etc., which are dismantled and the airspace released after the work is completed, are considered short-term occupancy; airspace unavailable due to satellite signals or weather factors is considered temporary occupancy; areas temporarily occupied by drones during their flight path missions, requiring other drones to avoid them during the same time period, are considered conflict occupancy.

[0036] Step S104: Based on the first occupancy state, trigger the corresponding data acquisition task.

[0037] Step S105: Data is collected from the target area through a data acquisition task, and the collected data is used to update the data of the components in the digital base to obtain the updated digital base.

[0038] Step S106: Update the first occupancy state based on the updated digital base to obtain the second occupancy state corresponding to the spatial grid; the second occupancy state may be the same as or different from the first occupancy state.

[0039] In some embodiments, the data acquisition task may include: a task performed by a UAV and data acquisition equipment to acquire relevant data about the target area, determined according to a first occupancy status. The data acquisition task may be used to collect various types of data to update the digital base and airspace occupancy status, such as oblique photogrammetry data and / or laser point cloud data. The first occupancy status may include: the occupancy status of the airspace grid after the initial update based on the update type. Data on components in the digital base may include: information on various basic elements constituting the digital base. Specific component data may include: the shape, size, and location of buildings; the type, height, and coordinates of construction devices, etc. Component data can be used to describe the physical entity characteristics within the target area. The second occupancy status may include: the airspace grid occupancy status obtained by reassessing 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 can be used to reflect the occupancy status of low-altitude airspace, ensuring the accuracy of the airspace grid.

[0040] The method in this application, by actively triggering data update and collection tasks using a drone swarm, effectively solves the problems of long update cycles and poor real-time performance of digital base and airspace status during large-scale engineering construction phases, and can accurately restore the current status of low-altitude areas. Simultaneously, by meticulously dividing the grid and combining real-time and deterministic update methods, rapid local updates of the digital base are achieved under various conditions, including long-term, short-term, and temporary occupancy, meeting the needs of incremental data updates and ensuring the accuracy and overall rationality of the updates. Furthermore, the use of AI recognition of gimbal-acquired images and flight path change monitoring improves the drone's ability to perceive and identify obstacles and accurately respond to changes in the digital base. Automatic triggering of different types of drone tasks and plans through event classification improves the timeliness and accuracy of data collection. Finally, a two-way dynamic update mechanism is formed by driving data base collection and updates through airspace grid occupancy updates, and by verifying updates after base updates, ensuring both data accuracy and improved update efficiency.

[0041] In some embodiments, the processing flow of the spatial data and digital base update method is illustrated. Figure 2 ,like Figure 2 As shown, before obtaining the digital base and spatial grid corresponding to the target area in step S101, the spatial data and digital base update method may further include:

[0042] Step S201: Data collection is performed on the target area using a drone to obtain oblique photography data and orthophoto data corresponding to the target area.

[0043] Step S202: Based on the building recognition algorithm, identify the building projection surface of the orthophoto data to obtain building layer data.

[0044] Step S203: Construct a digital base corresponding to the target area based on the building layer data.

[0045] Step S204: Divide the spatial domain of the data base into a grid to obtain the spatial grid corresponding to the target area.

[0046] Step S205: Based on the spatial grid and oblique photogrammetry data, perform spatial analysis to determine the correlation between the spatial grid and the digital base and the initial spatial occupancy status corresponding to the spatial grid.

[0047] In this embodiment, oblique photogrammetry data may include: image data containing three-dimensional information of components in the target area, acquired through oblique photogrammetry technology. Orthophoto data can be used as the base map of the digital base. Building projection surfaces may include: surface features formed by the orthographic projection of the top of a building onto the orthophoto data. Building projection surfaces can be used to determine the horizontal position of a building. Building layer data may include: geospatial layer data formed by integrating the projection surfaces of various buildings and their related attribute information. Spatial analysis may include: the process of analyzing data using technologies such as geographic information systems. Spatial analysis can be used to determine the relationship between the spatial grid and the digital base, and the initial spatial occupancy status corresponding to the spatial grid. The initial spatial occupancy status may include: after the digital base is constructed and the spatial grid is divided, the initial occupancy status, determined based on the initial data, whether the spatial grid is occupied and by what kind of object.

[0048] As an example, the digital foundation and spatial grid of the engineering construction area are established, and the implementation method is as follows:

[0049] 1. Conduct a full-area aerial data collection of the construction area to obtain oblique photogrammetry data and orthophoto data; 2. Using the orthophoto data as the data source, use an aerial building recognition algorithm to identify the building projection surface, and save the projection surface of each individual building, continuous building cluster or work equipment as a vector surface feature, and output it as layer A. Layer A contains fields such as "Code", "Type", and "Vertex Height". Each individual feature has a unique code, such as 00001. 3. Using the maximum boundary of the construction area as the horizontal boundary, and the lowest elevation within the current horizontal boundary up to an elevation of 200 meters, the area is divided according to the BeiDou grid location code principle, using the eighth level horizontally and the eighth level vertically, forming a grid approximately 0.97m × 0.97m × 0.97m in size. 4. The grid is encoded based on a 16-bit horizontal code + a 10-bit vertical code, such as N50J47539B8255340000001120 representing longitude: 116.0°18.0' 45.370000" E, latitude: 39.0°59.0' 35.380000" N, Altitude: A unique code at 200.000000, where the coding rule for the grid based on latitude, longitude, and altitude is the "BeiDou Grid Location Code" (GB / T39409-2020); 5. Store the grid's corresponding code in the spatial database, and add fields such as "Update Time," "Status," "Occupation Category," and "Building Affiliation" to form grid set B. The initial values ​​of the attribute fields such as "Update Time," "Status," "Occupation Category," and "Building Affiliation" in grid set B are all empty. The "Building Affiliation" field can be used to associate with the single-element unique code in step 2; 6. Use the oblique photogrammetry data collected in step 1 and the grids in grid set B to perform spatial analysis. When a grid intersects with the oblique photogrammetry data, update the "Status" field to "Occupied," the category to "Long-term Occupied," and the "Update Time" to the current spatial analysis time. 7. Mark the remaining grids in grid set B as unoccupied in the "Status" field; 8. Filter out the grids in grid set B whose "Status" field is occupied, and perform horizontal projection intersection analysis with the vector surface features in layer A in step 2. Assign the unique code in layer A to the building (equipment) in grid set B to obtain the association between the spatial grid and the digital base; 9. Slice the oblique photogrammetry data according to the grid and store it. The data of each area can use the Beidou grid location code as the index code; 10. Perform overlay analysis on layer A and oblique photogrammetry, extract the height of the building in the oblique photogrammetry, and store it under the highest point height attribute of the corresponding feature in layer A.

[0050] In some embodiments, the airspace data and digital base update method may further include: building a perception analysis module. The purpose of building the perception analysis module is to form a cloud computing service module that receives and analyzes information such as drone images, positions, and events in all flight states. The implementation method is as follows: 1. Create a video server platform to access the real-time live stream of the drone-mounted gimbal and process it into a data format for image recognition output; 2. Create a position and status recording module to acquire the real-time position of the drone and the status of the drone's mounted equipment twice per second. The real-time position includes latitude, longitude, and altitude, and the status of the drone's mounted equipment includes parameters such as the gimbal's orientation and pitch angle; 3. Create an event recording module to record events such as temporary route changes, automatic obstacle avoidance, and forced hovering and return during drone flight; 4. Create an AI image recognition service module based on video data to receive data sources provided by the video server and perform image recognition of components such as buildings and construction equipment.

[0051] In some embodiments, the airspace data and digital base update method may further include: establishing 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 issue it to the corresponding UAV for execution. The implementation method is as follows: 1. Receive real-time data such as meteorological grid points, band radar, ground stations, etc., and real-time data such as communication signals and electromagnetic data, and divide 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" occupancy category is "temporary occupancy"; 3. Obtain the flight path tasks of each UAV in the current flight plan task, and update the occupancy status of the airspace grid intersecting with the flight path according to the waypoint and transit time of the flight path, such as "unavailable" category is "conflict occupancy"; 4. Receive data acquisition tasks, complete the selection of UAVs and data acquisition equipment, and control the corresponding UAVs to execute data acquisition tasks in combination with the airspace situation.

[0052] In some embodiments, step S102 may include: analyzing image data collected by the UAV based on an image recognition algorithm; determining the feature information of the target component and the target time when the target component first appears in the image data; determining the position information and attitude parameters of the UAV at 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; and 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.

[0053] In this embodiment, the image data acquired by the UAV may include: image data from the image data sequence acquired by the UAV. Feature information may include: shape features, color features, and texture features of the target component, etc. Target time may include the timestamp of the first appearance of the target component in the image data sequence. Location information may include: the geographic coordinates of the UAV when acquiring the image. Attitude parameters may include: parameters such as the heading angle, pitch angle, and roll angle of the UAV when acquiring the image. Spatial location information may include: the coordinate position and height range of the target component in three-dimensional geographic space, etc. Building layer data may include: vector data corresponding to the spatial location information in the digital pedestal.

[0054] As an example, the method for identifying the occupancy growth of buildings in a target area is as follows: 1. First, deduplicate the building and other building results identified by the image recognition module to obtain the feature information of the target component when the target building first appears in the image data; 2. Based on the target time when the target building is identified, obtain the UAV position and the state parameters (focal length, attitude angle) of the data acquisition equipment at that time; 3. Using a spatial geometric inversion algorithm, calculate the top height H1 and planar coordinate position coor1 of the target building; 4. Perform overlay analysis based on the planar coordinate position coor1 and the building layer data in the digital base to obtain the unique code code1 and the highest point height attribute H2 of the target building. If the result of H1-H2 is greater than 1 meter, the update type of the target area can be determined to be a growth update; 5. For target areas with a growth update type, record the number of growth updates and the time.

[0055] In some embodiments, step S103 may include: determining 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 region; updating the airspace occupancy status of the target airspace grid based on the update type to obtain a first occupancy status and determining the occupancy time, occupancy reason and update time corresponding to the first occupancy status.

[0056] In this embodiment, the airspace grids at different heights may include multiple layers of airspace grids divided at certain height intervals, each grid having a different height range. Airspace grids at different heights can be used to represent the airspace occupancy status of a target area in the vertical direction. The target airspace grid may include airspace grids affected in the target area, determined according to the update type. The occupancy time may include the specific time range or point in time when the target airspace grid is occupied. The occupancy reason may include the specific reason causing the target airspace grid to be occupied, such as building construction, temporary event setup, etc. The update time may include the time when the airspace occupancy status of the target airspace grid is updated.

[0057] As an example, the implementation method for real-time updates of airspace occupancy status is as follows: When the update type is an incremental update, the grid set C directly above the code1 face, the grid set D at height H2, and the grid set E at heights H1-H2 are spatially retrieved. The airspace grids in grid set E are identified as the target airspace grids, and only the occupancy status of grid set E is updated; the "belonging building" field is not updated. If no existing building face is found in layer A at the identified coordinates, the airspace grids within the height range of 0-H2 directly above code1 are identified as the target airspace grids, the airspace occupancy status is updated, and the height field in layer A is updated. When a short-term occupancy reduction update is identified, the number of times the target area has been identified as reduction within 24 hours is determined from the face building layer data. The airspace occupancy status of the airspace grids is only updated when the number reaches three. For partial reduction updates, the grids in grid set B with heights between H1 and H2 are identified as target airspace grids by using the building code1, and the airspace occupancy status is updated to unoccupied. For complete reduction updates, the target airspace grids for the vertical region are calculated based on the coor1 coordinates of the face, the airspace occupancy status is updated to unoccupied, and the associated building layers are deleted.

[0058] As an example, real-time updates to airspace occupancy status can also include: The event log in the perception and analysis module collects events during UAV flight, such as hovering and automatic obstacle avoidance, that deviate from the predetermined flight path, and filters out events caused by sensors (LiDAR) identifying hazards. Based on the UAV's coordinates at the time of the event and the direction and distance of the obstacle identified by the LiDAR, the spatial location information of the obstacle is calculated. This spatial location information 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 grid where the obstacle is located is determined from airspace grids at different altitudes. Based on the update type, the airspace occupancy status of the airspace grid where the obstacle is located is updated to obtain the first occupancy status, and the corresponding occupancy time, occupancy reason, and update time are determined.

[0059] In some embodiments, step S104 may include: assessing the first occupancy state to obtain an assessment result; the assessment result characterizes the degree of change of components in the target area and the urgency of data updates; based on the assessment result, determining the corresponding UAV and data acquisition equipment; the data acquisition equipment includes oblique photography equipment and / or laser point cloud data acquisition equipment; based on the flight plan of the UAV and the meteorological information of the target area, determining a data acquisition task plan; the data acquisition task plan includes at least: flight path planning, acquisition time plan, and acquisition type; controlling the corresponding UAV based on the data acquisition task plan to execute the corresponding data acquisition task.

[0060] In this embodiment, the evaluation results may include: the degree of component change and the urgency of data updates in the target area obtained after analyzing the first occupancy state. Data acquisition equipment may include: oblique photography equipment and / or laser point cloud data acquisition equipment. Oblique photography equipment may include: a multi-angle camera mounted on the UAV, capable of acquiring image data of the target area from vertical and multiple oblique angles. Laser point cloud data acquisition equipment may include: a lidar device that emits laser pulses and receives reflected signals. Flight plans may include: a pre-set flight mission schedule for the UAV. The flight plan may specifically include information such as flight area, flight altitude, flight speed, and takeoff and landing time. Meteorological information may include: weather condition information of the target area. The meteorological information may specifically include wind speed, wind direction, visibility, and precipitation.

[0061] As an example, the data collection task is triggered as follows: 1. When the assessment result is a positive growth event for the building, and this event has been triggered a total of 5 times since the last base update, then find the nearest drone with oblique photogrammetry data collection capability based on the location of the target area; 2. When the assessment result is a short-term occupancy positive growth event, and this event has been triggered a total of 3 times since the last base update. 1. If the target area is located, find the nearest drone with laser point cloud data acquisition capability. 2. If the assessment result is a short-term obstacle reduction event, and the trigger count reaches 3 times, find the nearest drone with oblique photography data acquisition capability. 3. Based on the drone's flight plan and the recently acquired meteorological information of the target area, plan the flight path and execution time of the data acquisition task plan. The priority of the data acquisition task plan is lower than other inspection tasks. 4. If the same drone is found to need to perform multiple data acquisition tasks on the same day, and the acquisition type is the same, the task acquisition target points in the multiple data acquisition task plans need to be replanned to reduce the drone's flight consumption and enable the drone to complete the data update of multiple target areas in one flight.

[0062] In some embodiments, step S105 may include: acquiring oblique photography data and / or laser point cloud data of the target area collected by the UAV according to the data acquisition task; preprocessing the collected data based on the data processing algorithm to obtain preprocessed data; the data processing algorithm includes data cleaning, coordinate transformation and format conversion; and updating the data of the components in the digital base using the preprocessed data based on the update type to obtain the updated digital base.

[0063] As an example, the following method is used to update the data of components in the digital base: 1. After the data acquisition task is completed, use mapping tools to process the oblique photogrammetry data and / or laser point cloud data of the target area to obtain the 3D data model corresponding to each acquisition point in the data acquisition task; 2. Update the data of components in the digital base according to update types such as "forward growth of the original model", "initial addition of model growth", and "complete reduction"; 3. When the data of components in the digital base needs to be updated by forward growth of the original model, match the building face code xxxx1 corresponding to the target area in layer A, and then filter out the grids in grid B when the digital base was built that match the building code xxxx1, and update the data of the components contained in the grids to the data of the newly acquired 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, the original occupied face of the components in layer A is deleted; 5. When it is an initial addition of model growth, it is necessary to first obtain the face data and model height according to the vertical projection range of the newly added components, update layer A, and then update the model according to the grid dimension based on the occupied grid.

[0064] In some embodiments, step S106 may include: performing spatial analysis on the spatial grid corresponding to the first occupancy state using the updated digital base to obtain the spatial occupancy characteristics of each spatial grid; and updating the first occupancy state based on the spatial occupancy characteristics to obtain the second occupancy state.

[0065] As an example, spatial analysis is performed on the updated digital base and the spatial grid corresponding to the first occupancy state. Using GIS software, the 3D data of buildings, construction equipment, and other components in the digital base are overlaid and analyzed with the spatial grid. The spatial relationship between each spatial grid and these components is calculated, and the spatial occupancy characteristics of each spatial grid are obtained. For example, it is determined which spatial grids are penetrated by the top of buildings, which grids completely contain construction equipment, and which grids are close to obstacles but not occupied. Then, based on these spatial occupancy characteristics, the first occupancy state is updated. If the spatial occupancy characteristics show that the actual height occupied by a building in a spatial grid exceeds the previous record, the first occupancy state of that grid (e.g., initially recorded as unoccupied) is updated to the second occupancy state (long-term occupancy), and the occupancy height range and building information are recorded. If the analysis finds that a grid was previously misjudged as being occupied by a temporary obstacle due to data errors, but the obstacle has actually been removed, the occupancy state of that grid is updated from the first occupancy state (temporary occupancy) to the second occupancy state (unoccupied).

[0066] The following continues to describe the exemplary structure of the software modules included in the airspace data and digital base station update device 90 provided in the embodiments of this application. In some embodiments, such as Figure 3As shown, the airspace data and digital base update device 90 may include: an acquisition module 901, used to acquire the digital base and airspace grid corresponding to the target area;

[0067] The identification module 902 is used to identify changes in components in the target area based on image recognition algorithms and spatial geometric inversion algorithms, and to determine the update type of the target area;

[0068] The first update module 903 is used to update the airspace occupancy status corresponding to the airspace grid based on the update type, so as to obtain the first occupancy status;

[0069] The acquisition module 904 is used to trigger the corresponding data acquisition task based on the first occupancy state;

[0070] The second update module 905 is used to collect data from the target area through a data acquisition task, and to update the data of the components in the digital base using the collected data, so as to obtain the updated digital base.

[0071] The third update module 906 is used to update the first occupancy state based on the updated digital base to obtain the second occupancy state corresponding to the spatial grid; the second occupancy state may be the same as or different from the first occupancy state.

[0072] In some embodiments, the airspace data and digital base update device 90 further includes a construction module, which is used to: collect data on the target area based on the UAV to obtain oblique photogrammetry data and orthophoto data corresponding to the target area; identify the building projection surface of the orthophoto data based on the building recognition algorithm to obtain building layer data; construct a digital base corresponding to the target area based on the building layer data; divide the airspace of the data base into a grid to obtain the airspace grid corresponding to the target area; and perform spatial analysis based on the airspace grid and oblique photogrammetry data to determine the correlation between the airspace grid and the digital base and the initial airspace occupancy state corresponding to the airspace grid.

[0073] In some embodiments, the identification module 902 is used to: analyze image data collected by the UAV based on an image recognition algorithm; determine the feature information of the target component and the target time when the target component first appears in the image data; determine the position information and attitude parameters of the UAV at the target time; analyze 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; and 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.

[0074] In some embodiments, the first update module 903 is used 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 region; 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.

[0075] In some embodiments, the acquisition module 904 is configured to: assess a first occupancy state to obtain an assessment result; the assessment result characterizes the degree of change of components in the target area and the urgency of data updates; based on the assessment result, determine the corresponding UAV and data acquisition equipment; the data acquisition equipment includes oblique photography equipment and / or laser point cloud data acquisition equipment; based on the flight plan of the UAV and the meteorological information of the target area, determine a data acquisition task plan; the data acquisition task plan includes at least: flight path planning, acquisition time plan and acquisition type; and control the corresponding UAV to perform the corresponding data acquisition task based on the data acquisition task plan.

[0076] In some embodiments, the second updating module 905 is used to: acquire oblique photography data and / or laser point cloud data of the target area collected by the UAV according to the data acquisition task; preprocess the collected data based on the data processing algorithm to obtain preprocessed data; the data processing algorithm includes data cleaning, coordinate transformation and format conversion; and update the data of the components in the digital base using the preprocessed data based on the update type to obtain the updated digital base.

[0077] In some embodiments, the third update module 906 is used to: perform spatial analysis on the spatial grid corresponding to the first occupancy state using the updated digital base to obtain the spatial occupancy characteristics of each spatial grid; and update the first occupancy state based on the spatial occupancy characteristics to obtain the second occupancy state.

[0078] It should be noted that the description of the apparatus in this application embodiment is similar to the description of the method embodiment above, and has similar beneficial effects as the method embodiment, therefore it will not be repeated. For any technical details not covered in the airspace data and digital base station update apparatus provided in this application embodiment, please refer to... Figures 1 to 2 The meaning is understood in accordance with the description of any of the accompanying drawings.

[0079] According to embodiments of this application, this application also provides an electronic device and a non-transitory computer-readable storage medium.

[0080] Figure 4A schematic block diagram of an example electronic device 800 that can be used to implement embodiments of this application is shown. The electronic device is intended to represent various forms of digital computers, such as 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 personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0081] like Figure 4 As shown, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes based on 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. The RAM 803 may also store various programs and data required for the operation of the electronic device 800. The computing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0082] Multiple components in electronic device 800 are connected to I / O interface 805, including: input unit 806, such as keyboard, mouse, etc.; output unit 807, such as various types of displays, speakers, etc.; storage unit 808, such as disk, optical disk, etc.; and communication unit 809, such as network card, modem, wireless transceiver, etc. Communication unit 809 allows electronic device 800 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0083] The computing unit 801 can be a variety of 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 special-purpose 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 performs the various methods and processes described above, such as the spatial data and digital docking update method. For example, in some embodiments, the spatial data and digital docking update method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 800 via ROM 802 and / or communication unit 809. When the computer program is loaded into RAM 803 and executed by the computing unit 801, one or more steps of the spatial data and digital docking update method described above can be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the airspace data and digital base update method by any other suitable means (e.g., by means of firmware).

[0084] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0085] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0086] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction 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. Machine-readable media can be, 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 machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0087] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, 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 sound input, voice input, or tactile input).

[0088] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0089] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0090] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0091] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for updating spatial data and digital base, characterized in that, The method includes: Obtain the digital base and spatial grid corresponding to the target area; Based on image recognition algorithms and spatial geometric inversion algorithms, changes in components within the target region are identified, and the update type of the target region is determined. Based on the update type, update the airspace occupancy status corresponding to the airspace grid to obtain the first occupancy status; Based on the first occupancy state, the corresponding data acquisition task is triggered; Data is collected from the target area through a data acquisition task, and the collected data is used to update the data of the components in the digital base to obtain the updated digital base. The first occupancy state is updated based on the updated digital base to obtain the second occupancy state corresponding to the spatial grid; the second occupancy state may be the same as or different from the first occupancy state.

2. The method according to claim 1, characterized in that, Before obtaining the digital base and spatial grid corresponding to the target area, the method further includes: Based on the data collection of the target area by the UAV, oblique photography data and orthophoto data corresponding to the target area are obtained; The building projection surfaces are identified based on the building recognition algorithm to obtain building layer data from the orthophoto data; Construct a digital base corresponding to the target area based on the architectural layer data; The spatial domain of the data base is divided into grids to obtain the spatial grid corresponding to the target area; Spatial analysis is performed based on the spatial grid and the oblique photogrammetry data to determine the correlation between the spatial grid and the digital base and the initial spatial occupancy status corresponding to the spatial grid.

3. The method according to claim 1, characterized in that, The method of identifying changes in components within the target region based on image recognition algorithms and spatial geometric inversion algorithms, and determining the update type of the target region, includes: Based on the image recognition algorithm, the image data collected by the UAV is analyzed, and when the target component first appears in the image data, the feature information of the target component and the target time of the first appearance of the target component are determined. Determine the position information and attitude parameters of the UAV at the target time; Based on the spatial geometric inversion algorithm, the feature information, position information and attitude parameters are analyzed to determine the spatial position information of the target component; The spatial location information of the target component is compared 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, characterized in that, The step of updating the spatial occupancy status corresponding to the spatial grid based on the update type to obtain the first occupancy status includes: Based on the update type, a target airspace grid is determined from airspace grids at different altitudes; the target airspace grid represents the affected airspace range in the target region. Based on the update type, the airspace occupancy status of the target airspace grid is updated to obtain the first occupancy status and determine the occupancy time, occupancy reason and update time corresponding to the first occupancy status.

5. The method according to claim 1, wherein The step of triggering a corresponding data acquisition task based on the first occupancy state includes: The first occupancy state is evaluated to obtain an evaluation result; the evaluation result characterizes the degree of change of components in the target area and the urgency of data updates; Based on the evaluation results, the corresponding UAV and data acquisition equipment are determined; the data acquisition equipment includes oblique photography equipment and / or laser point cloud data acquisition equipment. Based on the UAV's flight plan and the meteorological information of the target area, a data acquisition task plan is determined; the data acquisition task plan includes at least: flight path planning, acquisition time plan, and acquisition type; Based on the data acquisition task plan, control the corresponding drone to execute the corresponding data acquisition task.

6. The method according to claim 1, characterized in that, The process of collecting data from the target area via a data acquisition task and updating the data of the components in the digital base using the collected data to obtain an updated digital base includes: Acquire oblique photography data and / or laser point cloud data of the target area collected by the UAV in accordance with the data acquisition task; The collected data is preprocessed based on data processing algorithms to obtain preprocessed data; the data processing algorithms include data cleaning, coordinate transformation and format conversion. Based on the update type, the data of the components in the digital base are updated using the preprocessed data to obtain the updated digital base.

7. The method according to claim 1, characterized in that, The step of updating the first occupancy state based on the updated digital base to obtain the second occupancy state corresponding to the spatial grid includes: The updated digital base is used to perform spatial analysis on the spatial grid corresponding to the first occupancy state to obtain the spatial occupancy characteristics of each spatial grid. Based on the space occupancy characteristics, the first occupancy state is updated to obtain the second occupancy state.

8. A spatial data and digital base update device, characterized in that, The device includes: The acquisition module is used to acquire the digital base and spatial grid corresponding to the target area; The identification module is used to identify changes in components in the target region based on image recognition algorithms and spatial geometric inversion algorithms, and to determine the update type of the target region; The first update module is used to update the airspace occupancy status corresponding to the airspace grid based on the update type, so as to obtain the first occupancy status; The acquisition module is used to trigger a corresponding data acquisition task based on the first occupancy state; The second update module is used to collect data from the target area through a data acquisition task, and use the collected data to update the data of the components in the digital base to obtain the updated digital base. The third update module is used to update the first occupancy state based on the updated digital base to obtain the second occupancy state corresponding to the spatial grid; the second occupancy state may be the same as or different from the first occupancy state.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of 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 the computer to perform the method according to any one of claims 1-7.

Images