UAV high-precision mapping control method, device, equipment and storage medium

Abstract

The present invention relates to the field of unmanned aerial vehicle (UAV) surveying and mapping technology, and discloses a high-precision UAV surveying and mapping control method, device, equipment, and storage medium. By querying the elevation information and weather forecast feature sequence of each location in a target area, after dividing the target area into a number of surveying and mapping sub-areas, a surveying and mapping UAV collaborative adaptive control model is constructed based on the geo-registration parameters of each surveying and mapping UAV, taking into account the overall surveying and mapping stability and accuracy of all surveying and mapping UAVs in the surveying and mapping UAV system performing surveying and mapping tasks during the corresponding surveying and mapping periods of the assigned surveying and mapping sub-areas. When the weather forecast feature sequence is updated, the surveying and mapping flight control instruction set in the surveying and mapping UAV system is adaptively adjusted to ensure that the surveying and mapping UAV system always maintains optimal surveying and mapping flight performance. Thus, a rationally designed surveying and mapping UAV collaborative adaptive control model is designed to consistently ensure that the UAV surveying and mapping system is at optimal performance, thereby improving the overall surveying and mapping accuracy of surveying and mapping tasks.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) surveying and mapping technology, and in particular to a method, device, equipment and storage medium for high-precision UAV surveying and mapping control. Background Art

[0002] Drone surveying and mapping is a technical means of using unmanned aerial vehicles as a platform, equipped with various sensors (such as optical cameras, lidar, photographic cameras, etc.) to obtain geospatial data, and generating maps, three-dimensional models and other surveying and mapping results through data processing and analysis.

[0003] Normally, the mapping devices deployed on drones will experience mapping area shifts as the drones age and are subject to vibration and impact (for example, the lidar's mapping action changes from a vertical downward direction to an oblique mapping direction with a certain angle). This will cause the position information of the mapping area to not correspond to the mapping data. Therefore, drones are usually equipped with a calibration function, which pre-inputs calibration parameters and adjusts the position information and mapping data obtained based on the calibration parameters when performing mapping, automatically outputting real data with a corresponding relationship between the two (for example, fine-tuning the calibration parameters for the corresponding mapping positions in each set of collected mapping data).

[0004] In practical applications, large-scale drone mapping of plain areas, despite the flat terrain, often involves sub-areas with varying elevations. This means that when drones maintain the same flight altitude and generate mapping data using calibration parameters, the resulting offset distances for the same tilt angle at different locations can vary. This ultimately results in inconsistent mapping data and low accuracy across the area. Furthermore, large-scale drone mapping often requires multiple drones to perform surveys in parallel to improve task efficiency. However, this data offset can occur due to the presence of different drones' deployed mapping components (i.e., different drones may have different tilt angles and calibration parameters due to age and operating conditions). When using drones with different calibration parameters to map sub-areas with varying elevations, the flight altitudes of the drones must be adjusted. This requires a well-planned sub-area allocation strategy, and the variability of meteorological characteristics at different locations and altitudes can affect the drone's attitude stability, further reducing mapping accuracy.

[0005] Therefore, how to design a reasonable collaborative adaptive control model for surveying and mapping UAVs based on the elevation information of the target area, the calibration parameters of the surveying and mapping UAVs, and the weather changes, so as to always ensure that the UAV surveying and mapping system is at its best performance and improve the overall surveying and mapping accuracy of the surveying and mapping tasks, is a technical problem that needs to be solved urgently. Summary of the Invention

[0006] The present invention provides a method, device, equipment and storage medium for high-precision mapping control of an unmanned aerial vehicle, aiming to solve at least one of the above-mentioned technical problems.

[0007] To achieve the above objectives, the present invention provides a high-precision mapping control method for an unmanned aerial vehicle, comprising the following steps:

[0008] Extract the target area in the surveying and mapping task and query the surveying and mapping control related information of the target area; wherein the surveying and mapping control related information includes elevation information and meteorological forecast feature sequence;

[0009] Determining georeferencing parameters for each mapping drone based on historical mapping correction data for each mapping drone in the mapping drone system configured for the mapping task;

[0010] Based on elevation information, weather forecast feature sequences, and georeferencing parameters, the target area is divided into several mapping sub-areas assigned to corresponding mapping UAVs. A mapping flight control instruction set is generated for each mapping UAV, and a collaborative adaptive control model for mapping UAVs is constructed.

[0011] Drive each mapping UAV to perform mapping flight control according to the mapping UAV collaborative adaptive control model, and collect the meteorological forecast feature sequence of each adaptive adjustment cycle;

[0012] The updated weather forecast feature sequence is used to drive the surveying and mapping UAV collaborative adaptive control model to adaptively adjust the surveying and mapping flight control instruction set of each surveying and mapping UAV, so that the surveying and mapping UAV system always maintains the best surveying and mapping flight performance.

[0013] Optionally, the steps of extracting the target area in the surveying and mapping task and querying the surveying and mapping control related information of the target area specifically include:

[0014] Upon receiving a surveying and mapping task for a target area, extracting the area range recorded in the surveying and mapping task and the surveying and mapping resource information configured for the surveying and mapping task; wherein the surveying and mapping resource information includes first identification information of a plurality of surveying and mapping drones and second identification information of a surveying and mapping drone control terminal;

[0015] Using the regional scope, the geographic elevation database and meteorological forecast database of the target area are queried respectively to obtain the elevation information of each position coordinate in the target area and the meteorological forecast feature sequence of each position coordinate at different heights, and to construct the surveying and mapping control association information of the target area.

[0016] Optionally, the step of determining the georeferencing parameters of each surveying and mapping drone based on the historical surveying and mapping data of each surveying and mapping drone in the surveying and mapping drone system configured for the surveying and mapping task specifically includes:

[0017] Using the first identification information and the second identification information in the surveying and mapping resource information, querying a surveying and mapping resource database to obtain a plurality of surveying and mapping drones used to construct a surveying and mapping drone system for the current surveying and mapping task and a surveying and mapping drone control terminal that is communicatively connected to the plurality of surveying and mapping drones;

[0018] Obtain historical mapping data for each mapping UAV in the mapping UAV system and determine the georeferencing parameters for each mapping UAV.

[0019] Optionally, the steps of obtaining historical surveying and calibration data for each surveying and mapping UAV in the surveying and mapping UAV system and determining georeferencing parameters for each surveying and mapping UAV include:

[0020] Acquire historical surveying and mapping correction data for each surveying and mapping UAV in the surveying and mapping UAV system; wherein the historical surveying and mapping correction data is configured as correction parameters obtained by performing surveying and mapping data position calibration for correction points with known coordinate positions after each surveying and mapping UAV performs a previous surveying and mapping mission;

[0021] According to the standard flight altitude, corrected flight position and mapping data position in the correction parameters, the mapping data position correction value and the mapping device error deflection angle of each mapping UAV are calculated, the geo-registration parameters of each mapping UAV are generated, and the geo-registration parameters are written into the mapping UAV.

[0022] Optionally, based on elevation information, weather forecast feature sequences, and georeferencing parameters, the target area is divided into a number of mapping sub-areas assigned to corresponding mapping UAVs, a mapping flight control instruction set is generated for each mapping UAV, and a collaborative adaptive control model for mapping UAVs is constructed, specifically including the following steps:

[0023] Based on the meteorological forecast feature sequence of each position coordinate at different altitudes in the target area, and in accordance with the mapping relationship between the preset meteorological features and the flight attitude stability level of the surveying and mapping UAV, the flight attitude stability level of each position coordinate at each unit analysis period at different altitudes is converted;

[0024] Based on the elevation information of each position coordinate in the target area, the target area is divided into several mapping sub-areas according to different elevation ranges, and the middle elevation value of the elevation range is assigned to the corresponding mapping sub-area in the form of a label;

[0025] Taking into account the mapping data position correction value and mapping device error deflection angle in the georeferencing parameters of each mapping UAV, several mapping sub-areas within the target area are assigned to corresponding mapping UAVs in the order of mapping execution. The mapping execution time of each mapping sub-area is determined based on the area of ​​each mapping sub-area and the mapping execution time per unit area, as well as the flight time of the mapping UAV between two adjacent mapping sub-areas. This ensures that after all mapping UAVs adjust their flight altitudes within each assigned mapping sub-area based on the mapping data position correction value and mapping device error deflection angle, the sum of the flight attitude stability levels of all mapping UAVs performing mapping within each unit analysis period is minimized.

[0026] The area range of each surveying and mapping UAV for several assigned mapping sub-areas and the mapping execution sequence of several mapping sub-areas are converted into the mapping flight control instruction set of each surveying and mapping UAV. The mapping flight control instruction set of each surveying and mapping UAV and the significant change ratio of preset meteorological characteristics are constructed into a collaborative adaptive control model for surveying and mapping UAVs.

[0027] Optionally, the flight altitude is adjusted within each assigned mapping sub-area based on the mapping data position correction value and the mapping device error deflection angle, specifically including: driving each mapping drone to adjust the flight altitude of each assigned mapping sub-area when performing mapping of the surveying sub-area, so that the adjusted flight altitude and the mapping data offset value determined by the mapping device error deflection angle of the mapping drone are within a preset error range of the mapping data position correction value.

[0028] Optionally, using the updated weather forecast feature sequence to drive the surveying and mapping UAV collaborative adaptive control model to adaptively adjust the surveying and mapping flight control instruction set of each surveying and mapping UAV so that the surveying and mapping UAV system always maintains optimal surveying and mapping flight performance steps specifically include:

[0029] After collecting the weather forecast feature sequence of each adaptive adjustment period, determine whether the difference ratio between the weather forecast feature sequence of the current adaptive adjustment period and the weather forecast feature sequence of the previously generated surveying and mapping UAV collaborative adaptive control model exceeds a preset weather feature significant change ratio;

[0030] If so, adaptively adjust and update the mapping flight control instruction set of each mapping UAV based on the meteorological forecast feature sequence collected in the current adaptive adjustment period, the elevation information of the unmapped mapping sub-area, and the georeferencing parameters of each mapping UAV, and rebuild the collaborative adaptive control model of the mapping UAVs.

[0031] If not, ignore the meteorological forecast feature sequence collected in the current adaptive adjustment period.

[0032] In addition, in order to achieve the above-mentioned purpose, the present invention also provides a high-precision surveying and mapping control device for an unmanned aerial vehicle, comprising:

[0033] A query module is used to extract the target area in the surveying and mapping task and query the surveying and mapping control related information of the target area; wherein the surveying and mapping control related information includes elevation information and meteorological forecast feature sequence;

[0034] a determination module for determining georeferencing parameters of each mapping drone in the mapping drone system configured for the mapping task based on historical mapping correction data of each mapping drone;

[0035] A construction module is used to divide the target area into several mapping sub-areas assigned to corresponding mapping UAVs based on elevation information, meteorological forecast feature sequences, and georeferencing parameters, generate a mapping flight control instruction set for each mapping UAV, and build a collaborative adaptive control model for mapping UAVs;

[0036] An execution module is used to drive each surveying and mapping UAV to perform surveying and mapping flight control according to the surveying and mapping UAV collaborative adaptive control model, and collect the meteorological forecast feature sequence of each adaptive adjustment cycle;

[0037] The adjustment module is used to use the updated weather forecast feature sequence to drive the mapping UAV collaborative adaptive control model to adaptively adjust the mapping flight control instruction set of each mapping UAV, so that the mapping UAV system always maintains the best mapping flight performance.

[0038] In addition, in order to achieve the above-mentioned purpose, the present invention also provides a high-precision surveying and mapping control device for an unmanned aerial vehicle, which includes: a memory, a processor, and a high-precision surveying and mapping control program for an unmanned aerial vehicle stored on the memory and runnable on the processor. When the high-precision surveying and mapping control program for an unmanned aerial vehicle is executed by the processor, the steps of the high-precision surveying and mapping control method for an unmanned aerial vehicle as described above are implemented.

[0039] In addition, in order to achieve the above-mentioned purpose, the present invention also provides a storage medium, on which a high-precision UAV surveying and mapping control program is stored. When the high-precision UAV surveying and mapping control program is executed by the processor, the steps of the above-mentioned high-precision UAV surveying and mapping control method are implemented.

[0040] The beneficial effects of the present invention are as follows: a high-precision UAV surveying and mapping control method, device, equipment, and storage medium are proposed. By querying the elevation information and weather forecast feature sequence of each location in the target area, based on the geo-registration parameters of each surveying and mapping UAV, after dividing the target area into a number of surveying and mapping sub-areas, the overall surveying and mapping stability and surveying accuracy of all surveying and mapping UAVs in the surveying and mapping UAV system during the corresponding surveying and mapping period of the assigned surveying and mapping sub-areas are considered, a surveying and mapping flight control instruction set for each surveying and mapping UAV is generated, and a surveying and mapping UAV collaborative adaptive control model is constructed. When the weather forecast feature sequence is updated, the surveying and mapping flight control instruction set of each surveying and mapping UAV in the surveying and mapping UAV system is adaptively adjusted to ensure that the surveying and mapping UAV system always maintains optimal surveying and mapping flight performance. Thus, a rationally designed surveying and mapping UAV collaborative adaptive control model is designed to always ensure that the UAV surveying and mapping system is at its optimal performance and improve the overall surveying and mapping accuracy of the surveying and mapping task. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention;

[0042] Figure 2 This is a flow chart of an embodiment of the high-precision mapping control method for a UAV according to the present invention;

[0043] Figure 3 This is a structural block diagram of a high-precision mapping control device for an unmanned aerial vehicle in an embodiment of the present invention.

[0044] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0046] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0047] like Figure 1 As shown, Figure 1 It is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention.

[0048] like Figure 1As shown, the device may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WIFI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0049] Those skilled in the art will understand that Figure 1 The structure of the device shown in the figure does not constitute a limitation of the device, and the device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0050] like Figure 1 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a UAV high-precision mapping control program.

[0051] exist Figure 1 In the terminal shown, the network interface 1004 is mainly used to connect to the backend server and communicate data with the backend server; the user interface 1003 is mainly used to connect to the client (user end) and communicate data with the client; and the processor 1001 can be used to call the UAV high-precision mapping control program stored in the memory 1005 and perform the following operations:

[0052] Extract the target area in the surveying and mapping task and query the surveying and mapping control related information of the target area; wherein the surveying and mapping control related information includes elevation information and meteorological forecast feature sequence;

[0053] Determining georeferencing parameters for each mapping drone based on historical mapping correction data for each mapping drone in the mapping drone system configured for the mapping task;

[0054] Based on elevation information, weather forecast feature sequences, and georeferencing parameters, the target area is divided into several mapping sub-areas assigned to corresponding mapping UAVs. A mapping flight control instruction set is generated for each mapping UAV, and a collaborative adaptive control model for mapping UAVs is constructed.

[0055] Drive each mapping UAV to perform mapping flight control according to the mapping UAV collaborative adaptive control model, and collect the meteorological forecast feature sequence of each adaptive adjustment cycle;

[0056] The updated weather forecast feature sequence is used to drive the surveying and mapping UAV collaborative adaptive control model to adaptively adjust the surveying and mapping flight control instruction set of each surveying and mapping UAV, so that the surveying and mapping UAV system always maintains the best surveying and mapping flight performance.

[0057] The specific embodiments of the present invention applied to the device are basically the same as the embodiments of the following application of the high-precision mapping control method for unmanned aerial vehicles, and will not be described in detail here.

[0058] The embodiment of the present invention provides a high-precision mapping control method for an unmanned aerial vehicle, referring to Figure 2 , Figure 2 The figure is a flow chart of an embodiment of the high-precision mapping control method for a UAV according to the present invention.

[0059] In this embodiment, a high-precision mapping control method for an unmanned aerial vehicle includes the following steps:

[0060] S100: extracting a target area in a surveying and mapping task, and querying surveying and mapping control related information of the target area; wherein the surveying and mapping control related information includes elevation information and a weather forecast feature sequence;

[0061] S200: Determining georeferencing parameters of each surveying and mapping UAV in the surveying and mapping UAV system configured for the surveying and mapping task based on historical surveying and mapping correction data of each surveying and mapping UAV;

[0062] S300: Based on the elevation information, the weather forecast feature sequence, and the geo-registration parameters, the target area is divided into a number of mapping sub-areas assigned to corresponding mapping UAVs, a mapping flight control instruction set is generated for each mapping UAV, and a collaborative adaptive control model for the mapping UAVs is constructed;

[0063] S400: driving each surveying and mapping UAV to perform surveying and mapping flight control according to the surveying and mapping UAV collaborative adaptive control model, and collecting a weather forecast feature sequence for each adaptive adjustment period;

[0064] S500: Using the updated weather forecast feature sequence to drive the surveying and mapping UAV collaborative adaptive control model to adaptively adjust the surveying and mapping flight control instruction set of each surveying and mapping UAV, so that the surveying and mapping UAV system always maintains the best surveying and mapping flight performance.

[0065] It should be noted that when it comes to large-scale UAV mapping of plain areas, despite the flat terrain, there are still sub-areas with varying elevations. This means that when drones maintain the same flight altitude for mapping and use calibration parameters to generate mapping data, the varying elevations at different locations can lead to different offset distances for the same tilt angle, ultimately resulting in inconsistent mapping data and low accuracy across the area. Furthermore, large-scale UAV mapping often requires multiple UAVs to conduct surveys in parallel to improve the efficiency of the task. However, this data offset can occur due to the mapping devices deployed by UAVs (i.e., different UAVs may have different tilt angles and calibration parameters due to age and conditions). When using UAVs with different calibration parameters to map sub-areas with varying elevations, the flight altitudes of the UAVs must be adjusted. This not only requires a well-planned sub-area allocation strategy for UAV mapping, but also the variability of meteorological characteristics at different locations and altitudes, which can affect the UAV's attitude stability to a certain extent, further reducing mapping accuracy.

[0066] To address the above issues, this embodiment queries the elevation information and weather forecast feature sequence for each location in the target area. Based on the georeferencing parameters of each mapping drone, after dividing the target area into several mapping sub-areas, the embodiment considers the overall mapping stability and accuracy of all mapping drones in the mapping drone system performing mapping tasks during the corresponding mapping periods of the assigned mapping sub-areas. This generates a mapping flight control instruction set for each mapping drone and constructs a collaborative adaptive control model for mapping drones. When the weather forecast feature sequence is updated, the mapping flight control instruction set of each mapping drone in the mapping drone system is adaptively adjusted to ensure that the mapping drone system always maintains optimal mapping flight performance. Thus, a rationally designed collaborative adaptive control model for mapping drones ensures that the drone mapping system always maintains optimal performance and improves the overall mapping accuracy of mapping tasks.

[0067] In a preferred embodiment, the steps of extracting the target area in the surveying and mapping task and querying the surveying and mapping control related information of the target area specifically include:

[0068] S110: Upon receiving a surveying and mapping task for a target area, extracting the area range recorded in the surveying and mapping task and surveying and mapping resource information configured for the surveying and mapping task; wherein the surveying and mapping resource information includes first identification information of a plurality of surveying and mapping drones and second identification information of a surveying and mapping drone control terminal;

[0069] S120: Using the regional range, query the geographic elevation database and the meteorological forecast database of the target area respectively, obtain the elevation information of each position coordinate in the target area and the meteorological forecast feature sequence of each position coordinate at different heights, and construct the surveying and mapping control association information of the target area.

[0070] In this embodiment, the surveying and mapping task records the area scope that needs to be surveyed and the configured surveying and mapping resource information. The area scope can be used to query the elevation information of each location coordinate and the meteorological forecast feature sequence of each location coordinate at different altitudes in the geographic elevation database and the meteorological forecast database. The elevation information is used for the subsequent division of the surveying and mapping sub-areas and the adjustment of the flight altitude of the surveying and mapping UAV. The meteorological forecast feature sequence is used to subsequently generate the surveying and mapping flight control instruction set of each surveying and mapping UAV and construct a collaborative adaptive control model for the surveying and mapping UAV.

[0071] In a preferred embodiment, the step of determining the georeferencing parameters of each surveying and mapping drone based on the historical surveying and mapping data of each surveying and mapping drone in the surveying and mapping drone system configured for the surveying and mapping task specifically includes:

[0072] S210: Using the first identification information and the second identification information in the surveying and mapping resource information, querying a surveying and mapping resource database to obtain a plurality of surveying and mapping drones used to construct a surveying and mapping drone system for the current surveying and mapping task and a surveying and mapping drone control terminal that is communicatively connected to the plurality of surveying and mapping drones;

[0073] S220: Acquire historical surveying data of each surveying UAV in the surveying UAV system, and determine the geo-registration parameters of each surveying UAV.

[0074] On this basis, the historical surveying and calibration data of each surveying and mapping UAV in the surveying and mapping UAV system is obtained, and the georeferencing parameter steps of each surveying and mapping UAV are determined, including:

[0075] S221: Acquire historical surveying and mapping correction data for each surveying and mapping UAV in the surveying and mapping UAV system; wherein the historical surveying and mapping correction data is configured as correction parameters obtained by performing surveying and mapping data position calibration on a correction point with a known coordinate position after each surveying and mapping UAV performs a previous surveying and mapping task;

[0076] S222: Calculate the surveying data position correction value and the surveying device error deflection angle of each surveying UAV based on the standard flight altitude, corrected flight position, and surveying data position in the correction parameters, generate the geo-registration parameters of each surveying UAV, and write the geo-registration parameters into the surveying UAV.

[0077] In this embodiment, after obtaining the configured surveying and mapping resource information during a surveying and mapping task, the surveying and mapping resource database is queried using the first and second identification information in the surveying and mapping resource information to obtain a number of surveying and mapping drones and drone control terminals to construct a surveying and mapping drone system. The drone control terminal is used to store the surveying and mapping flight control instruction set for each surveying and mapping drone after constructing a surveying and mapping drone collaborative adaptive control model. The surveying and mapping drone is used to execute the corresponding surveying and mapping flight actions according to the surveying and mapping flight control instructions issued by the drone control terminal. Subsequently, the calibration parameters obtained by performing calibration on the surveying and mapping data position for correction points with known coordinates after each surveying and mapping drone completed the previous surveying and mapping task are obtained. The calibration values ​​for the surveying and mapping data position and the deviation angle of the surveying and mapping device error are calculated and written into the surveying and mapping drone as georeferencing parameters for correction of the collected surveying and mapping data.

[0078] In a preferred embodiment, based on elevation information, weather forecast feature sequences, and geo-referenced parameters, the target area is divided into a number of mapping sub-areas assigned to corresponding mapping drones, a mapping flight control instruction set is generated for each mapping drone, and a collaborative adaptive control model for mapping drones is constructed. The steps specifically include:

[0079] S310: Based on the meteorological forecast feature sequence at different altitudes for each position coordinate within the target area, and according to a preset mapping relationship between the meteorological features and the flight attitude stability level of the surveying and mapping UAV, convert and obtain the flight attitude stability level of each position coordinate within each unit analysis period at different altitudes;

[0080] S320: Based on the elevation information of each position coordinate in the target area, the target area is divided into a plurality of surveying and mapping sub-areas according to different elevation ranges, and the elevation median value of the elevation range is assigned to the corresponding surveying and mapping sub-area in the form of a label;

[0081] S330: Considering the mapping data position correction value and the mapping device error deflection angle in the georeferencing parameters of each mapping UAV, a plurality of mapping sub-areas within the target area are allocated to corresponding mapping UAVs in a surveying execution order, and determining a mapping execution period for each mapping sub-area for each mapping UAV based on the area of ​​each mapping sub-area and the time consumption per unit area for surveying execution, as well as the flight time of the mapping UAV between two adjacent mapping sub-areas, so that the sum of the flight attitude stability levels of all mapping UAVs performing surveying in each mapping sub-area within each assigned mapping sub-area is minimized after adjusting their flight altitudes based on the mapping data position correction value and the mapping device error deflection angle.

[0082] S340: Convert the area range of each surveying and mapping UAV for the several surveying and mapping sub-areas assigned to it and the surveying execution sequence of the several surveying and mapping sub-areas into a surveying and mapping flight control instruction set of each surveying and mapping UAV, and construct the surveying and mapping flight control instruction set of each surveying and mapping UAV and the ratio of significant changes in preset meteorological characteristics into a collaborative adaptive control model for surveying and mapping UAVs.

[0083] Furthermore, the flight altitude is adjusted within each assigned mapping sub-area based on the mapping data position correction value and the mapping device error deflection angle, specifically including: driving each mapping drone to adjust the flight altitude of each assigned mapping sub-area when performing mapping of the surveying sub-area, so that the adjusted flight altitude and the mapping data offset value determined by the mapping device error deflection angle of the mapping drone are within the preset error range of the mapping data position correction value.

[0084] In this embodiment, based on the geo-registration parameters of each surveying and mapping UAV, after dividing the target area into several surveying and mapping sub-areas, the overall surveying and mapping stability and surveying accuracy of all surveying and mapping UAVs in the surveying and mapping UAV system in performing surveying and mapping tasks in the corresponding surveying and mapping time periods of the assigned surveying and mapping sub-areas are considered, and a surveying and mapping UAV collaborative adaptive control model is generated for each surveying and mapping UAV. The surveying and mapping flight control instruction set of each surveying and mapping UAV stored in the surveying and mapping UAV collaborative adaptive control model is the optimal control logic for the surveying and mapping UAV system to perform all surveying and mapping actions of the entire target area under the currently obtained meteorological forecast feature sequence.

[0085] In a preferred embodiment, the updated weather forecast feature sequence is used to drive the surveying and mapping UAV collaborative adaptive control model to adaptively adjust the surveying and mapping flight control instruction set of each surveying and mapping UAV so that the surveying and mapping UAV system always maintains the best surveying and mapping flight performance. The steps specifically include:

[0086] S510: After collecting the weather forecast feature sequence of each adaptive adjustment period, determining whether the difference ratio between the weather forecast feature sequence of the current adaptive adjustment period and the weather forecast feature sequence of the previously generated surveying and mapping UAV collaborative adaptive control model exceeds a preset weather feature significant change ratio;

[0087] S520: If yes, adaptively adjust and update the mapping flight control instruction set of each mapping UAV based on the meteorological forecast feature sequence collected in the current adaptive adjustment period, the elevation information of the unmapped mapping sub-area, and the geo-referenced parameters of each mapping UAV, and rebuild the collaborative adaptive control model of the mapping UAVs.

[0088] S530: If not, ignore the meteorological forecast feature sequence collected in the current adaptive adjustment period.

[0089] In this embodiment, when the weather forecast feature sequence is updated, the mapping flight control instruction set of each mapping drone in the mapping drone system is adaptively adjusted to ensure that the mapping drone system always maintains optimal mapping flight performance. Thus, a well-designed collaborative adaptive control model for mapping drones ensures that the drone mapping system always maintains optimal performance, improving the overall mapping accuracy of the mapping task.

[0090] Reference Figure 3 , Figure 3 This is a structural block diagram of an embodiment of the high-precision mapping control device for unmanned aerial vehicles of the present invention.

[0091] like Figure 3 As shown, the high-precision mapping control device for a UAV proposed in an embodiment of the present invention includes:

[0092] The query module 10 is used to extract the target area in the surveying and mapping task and query the surveying and mapping control related information of the target area; wherein the surveying and mapping control related information includes elevation information and meteorological forecast feature sequence;

[0093] a determination module 20 for determining a geo-registration parameter of each surveying and mapping UAV in the surveying and mapping UAV system configured for the surveying and mapping task based on historical surveying and calibration data of each surveying and mapping UAV;

[0094] A construction module 30 is configured to divide the target area into a number of mapping sub-areas assigned to corresponding mapping UAVs based on elevation information, weather forecast feature sequences, and geo-registration parameters, generate a mapping flight control instruction set for each mapping UAV, and construct a collaborative adaptive control model for mapping UAVs;

[0095] An execution module 40 is used to drive each surveying and mapping UAV to perform surveying and mapping flight control according to the surveying and mapping UAV collaborative adaptive control model, and collect a weather forecast feature sequence for each adaptive adjustment period;

[0096] The adjustment module 50 is used to use the updated weather forecast feature sequence to drive the mapping UAV collaborative adaptive control model to adaptively adjust the mapping flight control instruction set of each mapping UAV, so that the mapping UAV system always maintains the best mapping flight performance.

[0097] Other embodiments or specific implementations of the high-precision mapping control device for the unmanned aerial vehicle of the present invention can refer to the above-mentioned method embodiments and will not be described in detail here.

[0098] In addition, the present invention also proposes a high-precision surveying and mapping control device for an unmanned aerial vehicle, which includes: a memory, a processor, and a high-precision surveying and mapping control program for an unmanned aerial vehicle stored on the memory and runnable on the processor. When the high-precision surveying and mapping control program for an unmanned aerial vehicle is executed by the processor, the steps of the high-precision surveying and mapping control method for an unmanned aerial vehicle as described above are implemented.

[0099] The specific implementation of the high-precision mapping control device for unmanned aerial vehicles of the present application is basically the same as the embodiments of the high-precision mapping control method for unmanned aerial vehicles described above, and will not be repeated here.

[0100] In addition, the present invention also proposes a readable storage medium, which includes a computer readable storage medium on which a high-precision mapping control program for a UAV is stored. The readable storage medium may be Figure 1 The memory 1005 in the terminal may also be at least one of a ROM (Read-Only Memory) / RAM (Random Access Memory), a magnetic disk, and an optical disk. The readable storage medium includes a number of instructions for enabling a high-precision mapping control device for an unmanned aerial vehicle with a processor to execute the high-precision mapping control method for an unmanned aerial vehicle described in various embodiments of the present invention.

[0101] The specific implementation methods in the readable storage medium of this application are basically the same as the embodiments of the above-mentioned high-precision mapping control method for unmanned aerial vehicles, and will not be repeated here.

[0102] It should be understood that, in the description of this specification, reference to terms such as "one embodiment," "another embodiment," "other embodiments," or "first to Nth embodiments" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in any one or more embodiments or examples.

[0103] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0104] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0105] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0106] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A high-precision mapping control method for an unmanned aerial vehicle, characterized in that: The following steps are involved: Extract the target area in the surveying and mapping task and query the surveying and mapping control related information of the target area; the surveying and mapping control related information includes elevation information and meteorological forecast feature sequence; specifically, it includes: Upon receiving a surveying and mapping task for a target area, extracting the area range recorded in the surveying and mapping task and the surveying and mapping resource information configured for the surveying and mapping task; wherein the surveying and mapping resource information includes first identification information of a plurality of surveying and mapping drones and second identification information of a surveying and mapping drone control terminal; Using the regional range, query the geographic elevation database and the weather forecast database of the target area respectively, obtain the elevation information of each position coordinate in the target area and the weather forecast feature sequence of each position coordinate at different heights, and construct the surveying and mapping control association information of the target area; Determine the georeferencing parameters of each mapping drone based on the historical mapping correction data of each mapping drone in the mapping drone system configured for the mapping task; specifically, include: Using the first identification information and the second identification information in the surveying and mapping resource information, querying a surveying and mapping resource database to obtain a plurality of surveying and mapping drones used to construct a surveying and mapping drone system for the current surveying and mapping task and a surveying and mapping drone control terminal that is communicatively connected to the plurality of surveying and mapping drones; Acquire historical surveying and mapping correction data for each surveying and mapping UAV in the surveying and mapping UAV system; wherein the historical surveying and mapping correction data is configured as correction parameters obtained by performing surveying and mapping data position calibration for correction points with known coordinate positions after each surveying and mapping UAV performs a previous surveying and mapping mission; Calculate the mapping data position correction value and mapping device error deflection angle of each mapping UAV based on the standard flight altitude, corrected flight position, and mapping data position in the correction parameters, generate georeferencing parameters for each mapping UAV, and write the georeferencing parameters into the mapping UAV; Based on elevation information, weather forecast feature sequences, and georeferencing parameters, the target area is divided into several mapping sub-areas assigned to corresponding mapping UAVs. A mapping flight control instruction set is generated for each mapping UAV, and a collaborative adaptive control model for mapping UAVs is constructed. This includes: Based on the meteorological forecast feature sequence of each position coordinate at different altitudes in the target area, and in accordance with the mapping relationship between the preset meteorological features and the flight attitude stability level of the surveying and mapping UAV, the flight attitude stability level of each position coordinate at each unit analysis period at different altitudes is converted; Based on the elevation information of each position coordinate in the target area, the target area is divided into several mapping sub-areas according to different elevation ranges, and the middle elevation value of the elevation range is assigned to the corresponding mapping sub-area in the form of a label; Taking into account the mapping data position correction value and mapping device error deflection angle in the georeferencing parameters of each mapping UAV, several mapping sub-areas within the target area are assigned to corresponding mapping UAVs in the order of mapping execution. The mapping execution time of each mapping sub-area is determined based on the area of ​​each mapping sub-area and the mapping execution time per unit area, as well as the flight time of the mapping UAV between two adjacent mapping sub-areas. This ensures that after all mapping UAVs adjust their flight altitudes within each assigned mapping sub-area based on the mapping data position correction value and mapping device error deflection angle, the sum of the flight attitude stability levels of all mapping UAVs performing mapping within each unit analysis period is minimized. The area range of each mapping UAV assigned to several mapping sub-areas and the mapping execution sequence of the several mapping sub-areas are converted into a mapping flight control instruction set for each mapping UAV. The mapping flight control instruction set of each mapping UAV and the ratio of significant changes in preset meteorological characteristics are used to construct a collaborative adaptive control model for mapping UAVs. Drive each mapping UAV to perform mapping flight control according to the mapping UAV collaborative adaptive control model, and collect the meteorological forecast feature sequence of each adaptive adjustment cycle; The updated weather forecast feature sequence is used to drive the surveying and mapping UAV collaborative adaptive control model to adaptively adjust the surveying and mapping flight control instruction set of each surveying and mapping UAV, so that the surveying and mapping UAV system always maintains the best surveying and mapping flight performance.

2. The high-precision mapping control method for an unmanned aerial vehicle according to claim 1, wherein: Adjusting the flight altitude within each assigned mapping sub-area based on the mapping data position correction value and the mapping device error deflection angle specifically includes: driving each mapping drone to adjust the flight altitude of each assigned mapping sub-area when performing mapping of the surveying sub-area, so that the mapping data offset value determined by the adjusted flight altitude and the mapping device error deflection angle of the mapping drone is within a preset error range of the mapping data position correction value.

3. The high-precision mapping control method for an unmanned aerial vehicle according to claim 1, wherein: The updated weather forecast feature sequence is used to drive the mapping UAV collaborative adaptive control model to adaptively adjust the mapping flight control instruction set of each mapping UAV so that the mapping UAV system always maintains the best mapping flight performance. The steps specifically include: After collecting the weather forecast feature sequence of each adaptive adjustment period, determine whether the difference ratio between the weather forecast feature sequence of the current adaptive adjustment period and the weather forecast feature sequence of the previously generated surveying and mapping UAV collaborative adaptive control model exceeds a preset weather feature significant change ratio; If so, adaptively adjust and update the mapping flight control instruction set of each mapping UAV based on the meteorological forecast feature sequence collected in the current adaptive adjustment period, the elevation information of the unmapped mapping sub-area, and the georeferencing parameters of each mapping UAV, and rebuild the collaborative adaptive control model of the mapping UAVs. If not, ignore the meteorological forecast feature sequence collected in the current adaptive adjustment period.

4. A high-precision mapping control device for an unmanned aerial vehicle, characterized in that: include: The query module is used to extract the target area in the surveying and mapping task and query the surveying and mapping control related information of the target area; wherein the surveying and mapping control related information includes elevation information and meteorological forecast feature sequence; specifically, it includes: Upon receiving a surveying and mapping task for a target area, extracting the area range recorded in the surveying and mapping task and the surveying and mapping resource information configured for the surveying and mapping task; wherein the surveying and mapping resource information includes first identification information of a plurality of surveying and mapping drones and second identification information of a surveying and mapping drone control terminal; Using the regional range, query the geographic elevation database and the weather forecast database of the target area respectively, obtain the elevation information of each position coordinate in the target area and the weather forecast feature sequence of each position coordinate at different heights, and construct the surveying and mapping control association information of the target area; A determination module is configured to determine the georeferencing parameters of each mapping UAV in the mapping UAV system configured for the mapping task based on the historical mapping correction data of each mapping UAV; specifically comprising: Using the first identification information and the second identification information in the surveying and mapping resource information, querying a surveying and mapping resource database to obtain a plurality of surveying and mapping drones used to construct a surveying and mapping drone system for the current surveying and mapping task and a surveying and mapping drone control terminal that is communicatively connected to the plurality of surveying and mapping drones; Acquire historical surveying and mapping correction data for each surveying and mapping UAV in the surveying and mapping UAV system; wherein the historical surveying and mapping correction data is configured as correction parameters obtained by performing surveying and mapping data position calibration for correction points with known coordinate positions after each surveying and mapping UAV performs a previous surveying and mapping mission; Calculate the mapping data position correction value and mapping device error deflection angle of each mapping UAV based on the standard flight altitude, corrected flight position, and mapping data position in the correction parameters, generate georeferencing parameters for each mapping UAV, and write the georeferencing parameters into the mapping UAV; The construction module is used to divide the target area into several mapping sub-areas assigned to corresponding mapping UAVs based on elevation information, meteorological forecast feature sequences, and georeferencing parameters, generate a mapping flight control instruction set for each mapping UAV, and build a collaborative adaptive control model for mapping UAVs. Specifically, it includes: Based on the meteorological forecast feature sequence of each position coordinate at different altitudes in the target area, and in accordance with the mapping relationship between the preset meteorological features and the flight attitude stability level of the surveying and mapping UAV, the flight attitude stability level of each position coordinate at each unit analysis period at different altitudes is converted; Based on the elevation information of each position coordinate in the target area, the target area is divided into several mapping sub-areas according to different elevation ranges, and the middle elevation value of the elevation range is assigned to the corresponding mapping sub-area in the form of a label; Taking into account the mapping data position correction value and mapping device error deflection angle in the georeferencing parameters of each mapping UAV, several mapping sub-areas within the target area are assigned to corresponding mapping UAVs in the order of mapping execution. The mapping execution time of each mapping sub-area is determined based on the area of ​​each mapping sub-area and the mapping execution time per unit area, as well as the flight time of the mapping UAV between two adjacent mapping sub-areas. This ensures that after all mapping UAVs adjust their flight altitudes within each assigned mapping sub-area based on the mapping data position correction value and mapping device error deflection angle, the sum of the flight attitude stability levels of all mapping UAVs performing mapping within each unit analysis period is minimized. The area range of each mapping UAV assigned to several mapping sub-areas and the mapping execution sequence of the several mapping sub-areas are converted into a mapping flight control instruction set for each mapping UAV. The mapping flight control instruction set of each mapping UAV and the ratio of significant changes in preset meteorological characteristics are used to construct a collaborative adaptive control model for mapping UAVs. An execution module is used to drive each surveying and mapping UAV to perform surveying and mapping flight control according to the surveying and mapping UAV collaborative adaptive control model, and collect the meteorological forecast feature sequence of each adaptive adjustment cycle; The adjustment module is used to use the updated weather forecast feature sequence to drive the mapping UAV collaborative adaptive control model to adaptively adjust the mapping flight control instruction set of each mapping UAV, so that the mapping UAV system always maintains the best mapping flight performance.

5. A high-precision mapping control device for unmanned aerial vehicles, characterized in that: The UAV high-precision surveying and mapping control device includes: a memory, a processor, and a UAV high-precision surveying and mapping control program stored in the memory and runnable on the processor. When the UAV high-precision surveying and mapping control program is executed by the processor, the steps of the UAV high-precision surveying and mapping control method described in any one of claims 1 to 3 are implemented.

6. A storage medium, characterized in that The storage medium stores a high-precision UAV surveying and mapping control program, which, when executed by the processor, implements the steps of the high-precision UAV surveying and mapping control method according to any one of claims 1 to 3.

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