Fine mapping method, device and equipment based on unmanned aerial vehicle group and storage medium

Abstract

The application discloses a fine mapping method and device based on a UAV group, equipment and a storage medium, relates to the technical field of unmanned aerial vehicle mapping, and aims to solve the problem of insufficient mapping accuracy of a fixed-point area. The method comprises the following steps: constructing a master-slave UAV group, the master-slave UAV group comprising a master and at least one slave, the master being a UAV serving as a reference station, and the slave being a UAV working cooperatively with the master; the slave keeps synchronization with the master to form an accuracy reference network through positioning technology; the master and the at least one slave are controlled to shoot the fixed-point area from different angles respectively, and multi-angle images are acquired; the fixed-point area is a specific area that needs to be finely mapped; the multi-angle images are fused to obtain a fused image; and the fixed-point area is finely mapped based on the fused image to obtain a regional mapping diagram.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) mapping technology, and in particular to a refined mapping method, apparatus, equipment and storage medium based on UAV swarms. Background Technology

[0002] In the field of surveying and mapping technology, drones have become an important technical means for tasks such as regional topographic surveying and resource monitoring due to their advantages of flexible deployment and efficient operation.

[0003] Traditional UAV mapping solutions typically employ a single UAV for mission execution or rely on simple formations for basic coordination. Their operational mode depends on single-view data acquisition and absolute positioning technology. Since the positioning accuracy of a single viewpoint is significantly affected by satellite navigation system errors and environmental interference, and the data acquisition mode of a single UAV or simple formation depends on a fixed flight path, it is susceptible to interference from terrain obstruction and changes in weather conditions. This results in incomplete image coverage and loss of feature details, leading to insufficient mapping accuracy for a specific point area. Summary of the Invention

[0004] The purpose of this application is to provide a refined surveying method, apparatus, equipment, and storage medium based on UAV swarms, aiming to solve the problem of insufficient surveying accuracy for fixed-point areas.

[0005] To achieve the above objectives, this application adopts the following technical solution: This application provides a method for refined mapping based on a drone swarm. The method includes: constructing a master-slave drone swarm, which includes a master drone and at least one slave drone. The master drone serves as a reference station, and the slave drones operate collaboratively with the master drone. The slave drones maintain synchronization with the master drone through positioning technology to form a precision reference network; controlling the master drone and at least one slave drone to take pictures of a fixed area from different angles to obtain multi-angle images, where the fixed area is a specific area requiring refined mapping; fusing the multi-angle images to obtain a fused image; and performing refined mapping of the fixed area based on the fused image to obtain a regional mapping map.

[0006] The refined mapping method based on UAV swarms provided in this application constructs a master-slave UAV swarm with the host as the base station. This allows the slave UAVs to maintain positioning synchronization with the host, forming a precision reference network. This effectively overcomes the problem of large absolute positioning errors of single UAVs and improves the relative positioning accuracy of the UAV swarm itself. Furthermore, the host and slave UAVs collaboratively photograph a fixed area from different angles, acquiring multi-angle images. This overcomes the limitations of single-angle photography, which is susceptible to interference from terrain and weather factors, ensuring the integrity of image information and multi-view coverage. Subsequently, the acquired multi-angle images are fused, effectively integrating complementary information, eliminating blind spots in single-view images, and enhancing image detail, providing a high-quality data foundation for subsequent mapping. Finally, refined mapping is performed based on this high-precision fused image, optimizing the detail reproduction and spatial accuracy of the mapping results, thereby effectively improving the mapping accuracy of the fixed area.

[0007] In some embodiments, the positioning technology described above is differential positioning technology. The slave device maintains synchronization with the master device through the positioning technology, including: controlling the slave device to receive reference positioning data sent by the master device; controlling the slave device to perform differential calculation based on its own collected positioning data and the reference positioning data to obtain a relative position deviation; and controlling the slave device to adjust its own position according to the relative position deviation to maintain synchronization with the master device.

[0008] Based on this, this application provides reference positioning data through the host, and the slave performs differential calculations and adjusts its position in real time, effectively eliminating common errors (such as atmospheric delay and satellite clock error) and improving the synchronization accuracy of the slave relative to the host.

[0009] In some embodiments, the formation of the aforementioned precision reference network includes: the control host obtaining its own reference position through a global navigation satellite system (GNSS); the control slave constructing a relative positioning relationship with the host based on the reference position and its own real-time positioning information; and forming a master-slave unmanned aerial vehicle (UAV) swarm precision reference network based on the relative positioning relationship.

[0010] Based on this, this application uses the host to obtain a reference position by receiving GNSS as the core of the network, and the slaves construct a precise relative positioning relationship based on the reference position to ensure the spatial coordinate system of the entire UAV swarm is unified.

[0011] In some embodiments, the control host and at least one slave device respectively capture images of a fixed area from different angles to obtain multi-angle images, including: acquiring terrain contour information of the fixed area; planning the shooting height and shooting azimuth of the host and at least one slave device based on the terrain contour information; and capturing images of the control host and at least one slave device according to the shooting height and shooting azimuth to obtain multi-angle images; wherein, the shooting height and shooting azimuth are different for different drones.

[0012] Based on this, this application proactively plans the flight altitude and azimuth of each UAV based on terrain contour information to ensure optimal shooting angle coverage, effectively avoid terrain obstruction and weather interference, maximize the acquisition of complementary, blind-spot-free multi-angle image information, and improve the quality and integrity of the raw data.

[0013] In some embodiments, the control host and at least one slave device take pictures according to the shooting height and shooting azimuth angle to obtain multi-angle images, including: the control host flying to a first height and vertically shooting a fixed area to obtain a main image; controlling at least one slave device to fly to its respective corresponding second height and shoot a fixed area according to its respective corresponding azimuth angle to obtain at least one secondary image; wherein, the shooting height includes the first height and at least one second height, and the multi-angle image includes the main image and at least one secondary image.

[0014] Based on this, this application uses a host camera to capture vertical images to provide a reference orthophoto, and a slave camera to capture images from multiple heights and angles to supplement side and detail information, forming an image combination with clear primary and secondary elements and complementary perspectives. This provides a clear and information-rich basic data for subsequent fusion, thus optimizing the fusion effect.

[0015] In some embodiments, the above-described fusion processing of multi-angle images to obtain a fused image includes: preprocessing the multi-angle images to remove noise information from the images; extracting feature points from the preprocessed multi-angle images to obtain a feature point set; and matching and fusing the feature point set to obtain a fused image.

[0016] Based on this, this application improves image quality through preprocessing and noise reduction, and then achieves accurate image alignment and fusion through feature point extraction and matching. It effectively integrates the complementary advantages of multi-source information, eliminates the defects of single images, and generates a fused image with richer details and more complete information.

[0017] In some embodiments, the above-mentioned detailed mapping of a fixed area based on the fused image to obtain a regional mapping map includes: extracting the terrain detail features of the fixed area from the fused image; constructing a mapping model based on the terrain detail features; and generating a regional mapping map of the fixed area based on the mapping model.

[0018] Based on this, this application extracts key terrain detail features from high-precision fused images and constructs a targeted mapping model accordingly, ensuring that the final generated regional mapping map can more realistically and meticulously reflect the actual landform and features of the designated area.

[0019] This application provides a high-resolution mapping device based on a drone swarm. The device includes: a construction unit for constructing a master-slave drone swarm, the master-slave drone swarm including a master drone and at least one slave drone, the master drone serving as a reference station, and the slave drones operating collaboratively with the master drone, the slave drones maintaining synchronization with the master drone through positioning technology to form a precision reference network; an imaging unit for controlling the master drone and at least one slave drone to respectively capture images of a fixed-point area from different angles to obtain multi-angle images, the fixed-point area being a specific area requiring high-resolution mapping; a fusion unit for fusing the multi-angle images to obtain a fused image; and a mapping unit for performing high-resolution mapping of the fixed-point area based on the fused image to obtain a regional mapping map.

[0020] In some embodiments, the positioning technology described above is differential positioning technology, and the aforementioned building unit is specifically used for: controlling the slave device to receive reference positioning data sent by the host; controlling the slave device to perform differential calculations based on its own collected positioning data and the reference positioning data to obtain the relative position deviation; and controlling the slave device to adjust its own position according to the relative position deviation to maintain synchronization with the host.

[0021] In some embodiments, the above-mentioned building unit is specifically used for: controlling the host to obtain its own reference position through the Global Navigation Satellite System; controlling the slave to construct a relative positioning relationship with the host based on the reference position and its own real-time positioning information; and forming a precision reference network for the master-slave UAV swarm based on the relative positioning relationship.

[0022] In some embodiments, the above-mentioned shooting unit is specifically used for: acquiring terrain contour information of a fixed area; planning the shooting height and shooting azimuth of the host and at least one slave device based on the terrain contour information; controlling the host and at least one slave device to shoot according to the shooting height and shooting azimuth to obtain multi-angle images; wherein, the shooting height and shooting azimuth are different for different drones.

[0023] In some embodiments, the above-mentioned shooting unit is specifically used to: control the host to fly to a first altitude and vertically shoot a fixed area to obtain a main image; control at least one slave to fly to its corresponding second altitude and shoot the fixed area according to its corresponding azimuth angle to obtain at least one secondary image; wherein the shooting altitude includes the first altitude and at least one second altitude, and the multi-angle image includes the main image and at least one secondary image.

[0024] In some embodiments, the fusion unit is specifically used to: preprocess the multi-angle image to remove noise information from the image; extract feature points from the preprocessed multi-angle image to obtain a feature point set; and match and fuse the feature point set to obtain a fused image.

[0025] In some embodiments, the above-mentioned surveying unit is specifically used for: extracting terrain detail features of a fixed area from the fused image; constructing a surveying model based on the terrain detail features; and generating a regional surveying map of the fixed area based on the surveying model.

[0026] This application provides an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute instructions to implement the above-described method for detailed mapping based on UAV swarms.

[0027] This application provides a computer-readable storage medium storing instructions that, when executed on a terminal, cause the terminal to perform the above-described method for detailed mapping based on UAV swarms.

[0028] This application provides a computer program product containing instructions that, when executed by a computer, cause the computer to perform the above-described high-resolution mapping method based on unmanned aerial vehicle (UAV) swarms.

[0029] This application provides a chip including a processor and a communication interface, the communication interface and the processor being coupled together. The processor is used to run computer programs or instructions to implement the above-described high-resolution mapping method based on UAV swarms.

[0030] Specifically, the chip provided in this application embodiment also includes a memory for storing computer programs or instructions. Attached Figure Description

[0031] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 An architecture diagram of an unmanned aerial vehicle (UAV) swarm mapping system provided in this application embodiment; Figure 2 A flowchart illustrating a refined mapping method based on an unmanned aerial vehicle (UAV) swarm, provided as an embodiment of this application; Figure 3 A structural diagram of a high-resolution mapping device based on an unmanned aerial vehicle (UAV) swarm, provided for an embodiment of this application; Figure 4This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0033] The technical solutions of 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.

[0034] In the description of this application, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or relative positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and for simplification, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Unless otherwise specified, the above-mentioned orientational descriptions can be flexibly set in practical applications, provided that the relative positional relationships shown in the accompanying drawings are satisfied.

[0035] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0036] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "communication" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a direct connection or an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0037] In some embodiments, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0038] In some embodiments, the words "exemplary" or "for example" are used to indicate that something is an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0039] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0040] As surveying scenarios become more refined and complex, traditional methods are gradually revealing their technical limitations in surveying fixed areas or locations.

[0041] The core shortcomings of existing UAV mapping technology are reflected in two aspects: First, the absolute positioning accuracy is affected by factors such as satellite navigation system errors and environmental interference, resulting in cumulative deviations in the spatial benchmark of the surveying and mapping results.

[0042] Secondly, the data acquisition mode of a single drone or a simple formation relies on a fixed flight path and a single perspective, which is easily affected by terrain obstruction, changes in weather conditions, etc., resulting in incomplete image information coverage and loss of feature details.

[0043] Specifically, in complex terrains such as mountains and building complexes, single-angle shooting makes it difficult to obtain three-dimensional information of hidden areas or vertical surfaces, while meteorological factors (such as strong winds and fog) may further reduce image clarity, resulting in insufficient mapping accuracy for fixed-point areas.

[0044] Against this backdrop, to address the issue of insufficient mapping accuracy for fixed-point areas in related technologies, this application provides a refined mapping method, apparatus, equipment, and storage medium based on a drone swarm. By constructing a precision reference network using a master-slave drone swarm (with the master drone serving as the base station and slave drones synchronizing via positioning), the swarm collaboratively captures images of the fixed-point area from different angles. Multi-angle image fusion processing enhances detail integrity, ultimately achieving refined mapping and improving the mapping accuracy of the fixed-point area.

[0045] Figure 1 This is an architectural diagram of an unmanned aerial vehicle (UAV) swarm mapping system provided in an embodiment of this application. The UAV swarm mapping system 100 includes a host 110, a first slave 120, a second slave 130, a third slave 140, and a fourth slave 150.

[0046] In this embodiment of the application, the host 110, the first slave 120, the second slave 130, the third slave 140 and the fourth slave 150 communicate with each other via a wireless link to jointly map the fixed area A.

[0047] For example, the host 110 may be equipped with a real-time kinematic (RTK) positioning module and an inertial measurement unit (IMU). The RTK positioning module is used to receive GNSS signals and generate reference positioning data, while the IMU is used to monitor its own attitude (such as pitch angle, roll angle, and heading angle) in real time, so as to realize the scheduling and data distribution of the slave units.

[0048] For example, when the host 110 is deployed over a fixed area in a mountainous region, the RTK positioning module can send reference data containing latitude, longitude, elevation and timestamp to each slave device once per second, and compensate for minor attitude deviations (such as pitch angle fluctuations caused by gusts of wind) in real time through the IMU.

[0049] For example, the first slave device 120 may be equipped with a wide-angle camera with high dynamic range (HDR) mode and a LiDAR (light detection and ranging) obstacle avoidance module. The wide-angle camera is used to capture terrain details of a fixed area from a side and lower angle. In backlit scenes, the HDR mode preserves details of shadow areas (such as the bottom of a valley) and highlight areas (such as rocks on a mountaintop). The LiDAR obstacle avoidance module can detect surrounding obstacles (such as trees and power transmission towers) in real time and feed them back to the master device 110.

[0050] For example, when shooting a steep slope area, the first slave device 120 can shoot under the control of the host device 110. At the same time, the LiDAR generates point cloud data according to a preset cycle. When a boulder is detected at the top of the slope, it immediately sends an obstacle avoidance signal to the host device 110. The host device 110 then adjusts its flight trajectory to make the shooting path deviate from the obstacle.

[0051] For example, the second slave device 130 may be equipped with a five-lens (including one vertical lens and four tilt lenses) tilt photography camera, which can acquire multi-directional images of a fixed area through time synchronization triggering.

[0052] For example, when shooting a fixed area in an urban village, the vertical lens can capture the roof plan layout, and the four tilting lenses can capture the east, south, west and north facades of the building respectively, clearly presenting details such as balconies, windows, and air conditioner outdoor units, supplementing the building side information that the 110 vertical shooting of the main unit cannot cover, and providing sufficient matching features for subsequent stitching.

[0053] For example, the third slave device 140 may be equipped with an infrared thermal imaging camera and a weather sensor. The infrared thermal imaging camera can capture terrain contours in cloud or low light conditions, and the weather sensor can detect temperature, humidity, air pressure and visibility, and feed back environmental parameters to the host device 110 in real time.

[0054] For example, when a thin fog in a fixed area causes visible light photography to be blurry, the third slave unit 140 can automatically switch to infrared mode to distinguish the temperature difference between water and land, and use thermal imaging data to help identify the heat source of a building (such as an unextinguished fire), providing multi-dimensional information for subsequent terrain recognition.

[0055] For example, the fourth slave device 150 can be configured with the same backup RTK positioning module and dual GNSS antennas as the master device 110, serving as a backup master device. The fourth slave device 150 is used to synchronously back up the raw data (such as images, positioning information, attitude data) of the master device 110 and other slave devices.

[0056] For example, when the RTK signal of the host 110 is interrupted due to sudden electromagnetic interference (such as signal interference from a nearby radar station), the fourth slave 150 can take over the data aggregation task through a preset master-slave switching mechanism, and the backup RTK module can re-establish the base station to ensure that the surveying process is not interrupted.

[0057] It should be noted that the UAV swarm mapping system provided in this application embodiment is illustrated using an example comprising one master and four slave devices. In actual scenarios, there may be more or fewer master and slave devices, and the specific number can be adjusted according to the actual scenario. This application does not impose a specific limitation on this.

[0058] Thus, the UAV swarm mapping system in this application provides benchmark positioning through the host, collects multiple types of data (visible light, infrared, and oblique images) through the slave devices, and achieves real-time communication and collaborative scheduling between the devices, forming a three-dimensional mapping capability that covers multiple perspectives and adapts to complex environments, thereby improving the mapping accuracy from a hardware perspective.

[0059] The following is a reference. Figure 2 The refined mapping method based on UAV swarms provided in the embodiments of this application is described.

[0060] Figure 2 This is a flowchart of a method for a refined mapping method based on an unmanned aerial vehicle (UAV) swarm provided in an embodiment of this application. The entity executing this method can be... Figure 1 The UAV swarm mapping system 100 shown can also be any of the devices / modules in the UAV swarm mapping system 100, such as integrated circuits or chips. This application embodiment does not specifically limit this.

[0061] For example, such as Figure 2As shown, the refined mapping method based on UAV swarms provided in this application embodiment may include the following steps S201 to S204: S201. Construct a master-slave drone swarm.

[0062] In this embodiment of the application, the master-slave drone swarm includes a master drone and at least one slave drone.

[0063] The host drone is the drone that serves as the base station, and the slave drones are drones that work in conjunction with the host drone.

[0064] It should be noted that a detailed description of drones can be found above. Figure 1 To avoid repetition, the relevant descriptions will not be repeated here.

[0065] In this embodiment, the slave device can maintain synchronization with the master device through positioning technology to form a precision reference network.

[0066] For example, the positioning technology can be differential positioning technology.

[0067] In some embodiments, the slave and master devices can be synchronized by controlling the slave device to receive the reference positioning data sent by the master device, and performing differential calculations based on the positioning data it collects and the reference positioning data to obtain the relative position deviation.

[0068] For example, if the reference positioning data sent by the host is (30°25′12.3″N, 114°30′05.8″E, elevation 52.5 meters), and the positioning data collected by the first slave device is (30°25′13.1″N, 114°30′06.6″E, elevation 50.3 meters), then the relative position deviation can be calculated to be 1.2 meters eastward, 0.8 meters northward, and -2.2 meters in elevation through differential operation.

[0069] Furthermore, the slave device can be controlled to adjust its own position according to the relative position deviation to keep synchronized with the master device.

[0070] For example, the first slave device can adjust its motor speed to fly 1.5 meters northwest and gain 2.2 meters in altitude based on the calculated relative position deviation of 1.2 meters to the north, 0.8 meters to the north, and -2.2 meters in elevation, thus ensuring spatial synchronization with the host device.

[0071] Thus, this application provides reference positioning data through the host, and the slave performs differential calculations and adjusts its position in real time, effectively eliminating common errors (such as atmospheric delay and satellite clock error) and improving the synchronization accuracy of the slave relative to the host.

[0072] Optionally, the formation of the accuracy reference network includes: the control host obtaining its own reference position through a global navigation satellite system.

[0073] For example, if the host computer hovers above the top of a reservoir dam (e.g., 10 meters), it can be calibrated by using GNSS static observation for a period of time (e.g., 15 minutes) and combining this with known control points on the top of the reservoir dam (e.g., coordinates 32°18′00.0″N, 113°45′00.0″E, elevation 450.0 meters). The final coordinates of the host computer are: coordinates 32°18′00.0″N, 113°45′00.0″E, elevation 460.0 meters.

[0074] Furthermore, the slave drones, based on their reference positions and their own real-time positioning information, construct a relative positioning relationship with the master drone, and based on this relative positioning relationship, form a precision reference network for the master-slave drone swarm.

[0075] For example, if the second slave unit measures a straight-line distance of 90 meters to the host unit on the top of the reservoir dam using an ultra-wideband (UWB) module, it can calculate its coordinates relative to the host unit as (63.6 meters, 63.6 meters, 1 meter) by combining its own IMU's heading angle (e.g., 45°). Ultimately, the four slave units and the host unit form a cross-shaped symmetrical network centered on the host unit.

[0076] Thus, this application uses the host to obtain a reference position via GNSS as the core of the network, and the slave devices construct precise relative positioning relationships based on the reference position, ensuring the spatial coordinate system consistency of the entire fleet.

[0077] S202, the control host and at least one slave device take pictures of the fixed area from different angles to obtain multi-angle images.

[0078] Among them, the designated area is a specific area that requires detailed surveying. For example, the designated area could be a highway slope area, which has steep slopes and multiple potential rockfall hazards, requiring detailed surveying to assess safety risks.

[0079] In some embodiments, terrain contour information of a fixed area can be obtained first, and then the shooting height and shooting azimuth of the host and at least one slave device can be planned based on the terrain contour information.

[0080] For example, taking a highway slope area as a fixed location, the digital elevation model (DEM) data of the slope area can be obtained in advance by aerial photography at a set scale (e.g., 1:2000), and the terrain contour information (e.g., altitude range of 350-420 meters, slope of 38°, a 5-meter-wide patrol road at the top of the slope, and a 1-meter-wide and 0.8-meter-deep drainage ditch at the bottom of the slope) can be extracted. Then, the shooting height and shooting azimuth angle can be planned based on the terrain contour information.

[0081] It should be noted that different drones have different shooting altitudes and shooting azimuths.

[0082] For example, the shooting height can be: the main camera shooting height is 10 meters from the top of the slope, the first slave camera shooting height is 8 meters from the top of the slope, the second slave camera shooting height is 9 meters from the top of the slope, the third slave camera shooting height is 6 meters from the top of the slope, and the fourth slave camera shooting height is 7 meters from the top of the slope; the shooting azimuth can be: the main camera is located vertically above the slope, the first slave camera is located due east of the slope, the second slave camera is located due south of the slope, the third slave camera is located due west of the slope, and the fourth slave camera is located due north of the slope.

[0083] Furthermore, the host and at least one slave device can be controlled to take pictures according to the shooting height and shooting azimuth angle to obtain multi-angle images.

[0084] For example, consider at least one slave camera, including a first slave camera and a second slave camera. The master camera is positioned at a height of 430 meters (10 meters above the top of the slope) and takes vertical shots at a 0° tilt angle, covering the entire slope area; the first slave camera is positioned at a height of 400 meters (20 meters below the top of the slope) and takes shots from the east side of the slope at a 30° tilt angle, covering the rockfall area; the second slave camera is positioned at a height of 390 meters and takes shots from the west side of the slope at a 45° tilt angle, covering the area with dense cracks.

[0085] In addition, the shooting is triggered by the host's time synchronization signal (such as the pulses per second (PPS) signal generated by the GNSS receiver or the precise timestamp broadcast by wireless communication) to ensure that the three drones shoot at the same time and avoid image misalignment caused by slight deformation of the slope.

[0086] Thus, this application proactively plans the flight altitude and azimuth of each UAV based on terrain contour information to ensure optimal shooting angle coverage, effectively avoid terrain obstruction and weather interference, maximize the acquisition of complementary, blind-spot-free multi-angle image information, and improve the quality and integrity of the raw data.

[0087] In this embodiment of the application, the shooting height includes a first height and at least one second height, and the multi-angle image includes a main image and at least one secondary image.

[0088] In some embodiments, the host computer can be controlled to fly to a first altitude and vertically capture a fixed area to obtain the main image.

[0089] For example, the host can be controlled to take a vertical shot at a first height of 430 meters to obtain a main image that clearly shows the planar distribution of the slope: the projection position of the fallen rocks on the plane, the direction of the cracks, the positional relationship between the patrol road and the drainage ditch, etc.

[0090] In some embodiments, at least one slave aircraft can be controlled to fly to its corresponding second altitude and take pictures of a fixed area according to its corresponding azimuth angle to obtain at least one secondary image.

[0091] For example, taking at least one secondary image including a first image and a second image as an example, the first slave camera can be controlled to shoot at a second height of 400 meters with a 30° tilt angle (i.e., the angle between the lens optical axis and the vertical direction) to obtain the first image, which clearly shows the side shape of the falling rock; the second slave camera can be controlled to shoot at a second height of 390 meters with a 45° tilt angle to obtain the second image, which shows the three-dimensional direction of the crack, thus compensating for the height measurement error of the main camera shooting vertically.

[0092] Thus, this application uses a host camera to capture a vertical image to provide a reference orthophoto, while the slave camera captures images from multiple heights and angles to supplement side and detail information, forming an image combination with clear primary and secondary elements and complementary perspectives. This provides a clear and information-rich foundation of data for subsequent fusion, thereby optimizing the fusion effect.

[0093] S203. Perform fusion processing on the multi-angle images to obtain a fused image.

[0094] In some embodiments, multi-angle images can be preprocessed to remove noise information from the images.

[0095] For example, consider a case where the main image captured by the host device is overexposed, and the secondary image captured by the slave device has Gaussian blur. First, Gaussian filtering can be used to remove high-frequency noise from the secondary image, smoothing the image while preserving edges. Then, piecewise linear grayscale correction can be performed on the overexposed and underexposed areas of the main image, while maintaining the original parameters for the intermediate areas, ultimately achieving grayscale balance between the main and secondary images.

[0096] Furthermore, feature points are extracted from the preprocessed multi-angle images to obtain a feature point set, and the feature point set is matched and fused to obtain a fused image.

[0097] For example, the scale-invariant feature transform (SIFT) algorithm can be used to extract feature points from the main image and the sub-image respectively. Then, the sub-image feature points can be matched to the homography transformation matrix required by the main image using the random sample consensus (RANSAC) algorithm, and the sub-image can be aligned to the coordinate system of the main image to obtain the fused image.

[0098] Specifically, the SIFT algorithm described above, which extracts feature points from the main image and the sub-image respectively, may include the following steps: 1) Construct a scale space (such as an 8-layer Gaussian pyramid with 4 levels per layer) and detect extreme points.

[0099] 2) Calculate the orientation of feature points (e.g., based on the gradient histogram, the main orientation ±15°).

[0100] 3) Generate 128-dimensional feature descriptor vectors (e.g., 4×4 sub-regions, each sub-region has 8 directions).

[0101] For example, when surveying the slope area of ​​a highway, about 6,000 feature points (such as slope inflection points, rockfall edges, and crack endpoints) are extracted from the main image, and about 4,000 feature points are extracted from each sub-image. The nearest neighbor ratio method is used to screen matching pairs and remove mismatched point pairs caused by patrol road edges, crack endpoints, and drainage ditch edges. Finally, 3,200 pairs of valid points are matched between the main image and the first slave sub-image, and 2,800 pairs of valid points are matched between the main image and the second slave sub-image.

[0102] The fused image contains both the planar layout of the main image and the three-dimensional information of the sub-image, such as the depth of the side cracks and the height of the falling rocks.

[0103] Thus, this application improves image quality through preprocessing and noise reduction, and then achieves accurate image alignment and fusion through feature point extraction and matching, effectively integrating the complementary advantages of multi-source information, eliminating single-image defects, and generating a fused image with richer details and more complete information.

[0104] S204. Based on the fused image, perform detailed mapping of the fixed-point area to obtain the area mapping map.

[0105] In some embodiments, terrain detail features of a specific region can be extracted from the fused image.

[0106] For example, the terrain can be segmented into units such as slopes, platforms, and gullies according to the elevation change boundary using the watershed algorithm. Feature points are extracted from the segmentation boundary and the interior of the unit, and the parameter information of the feature points is estimated by combining the fused image to form a discrete three-dimensional point set.

[0107] For example, when surveying the slope area of ​​a highway, the slope protection surface, the main road, and the material stockpile area can be divided. The slope of the slope protection surface is measured to be 25°, the length-to-width ratio of the main road is 5, and the curvature of the material stockpile area is 0.01m⁻¹.

[0108] Furthermore, a mapping model is constructed based on the detailed features of the terrain, and a regional mapping map of the fixed-point area is generated based on the mapping model.

[0109] For example, an initial three-dimensional model can be generated using a triangulated irregular network (TIN), and then the slope, aspect, and curvature of each unit can be calculated to establish a terrain parameter matrix. The parameter information can then be embedded as attribute data into the initial three-dimensional model to obtain a mapping model. Finally, the mapping model outputs a regional mapping map at a preset scale (e.g., 1:500).

[0110] For example, using the slope protection surface, main road, and material stockpile area as fixed points, a three-dimensional model is generated using TIN. Then, the slope, aspect, and curvature are mapped as attribute data to the three-dimensional model to obtain the survey model. Finally, a 1:500 survey map of the highway slope area is output.

[0111] Thus, this application extracts key terrain detail features from high-precision fused images and constructs a targeted mapping model accordingly, ensuring that the final generated regional mapping map can more realistically and meticulously reflect the actual landforms and features of the designated area.

[0112] In the refined mapping method based on UAV swarms provided in this application embodiment, a master-slave UAV swarm is constructed with the host as the base station. This enables the slave UAVs to maintain positioning synchronization with the host, forming a precision reference network. This effectively overcomes the problem of large absolute positioning errors of single UAVs and improves the relative positioning accuracy of the UAV swarm itself. On this basis, the host and slave UAVs work together to take pictures of the fixed area from different angles, acquiring multi-angle images. This overcomes the limitations of single-angle shooting, which is easily affected by terrain and weather factors, ensuring the integrity of image information and multi-view coverage. Subsequently, the acquired multi-angle images are fused to effectively integrate complementary information, eliminate single-view blind spots, and enhance the image detail, providing a high-quality data foundation for subsequent mapping. Finally, refined mapping is performed based on this high-precision fused image, optimizing the detail reproduction and spatial accuracy of the mapping results, thereby effectively improving the mapping accuracy of the fixed area.

[0113] The above primarily describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the high-precision mapping device or electronic device based on UAV swarms includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] This application embodiment can, based on the above method, exemplarily divide a high-resolution mapping device or electronic device based on a UAV swarm into functional modules. For example, the high-resolution mapping device or electronic device based on a UAV swarm may include functional modules corresponding to each functional division, or two or more functions may be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0115] Figure 3 This is a structural diagram of a high-resolution mapping device based on a drone swarm, provided in an embodiment of this application. The high-resolution mapping device 300 based on a drone swarm includes: a construction unit 301, an image capture unit 302, a fusion unit 303, and a mapping unit 304.

[0116] The system comprises: a construction unit 301 for constructing a master-slave drone swarm, which includes a master drone and at least one slave drone. The master drone serves as a reference station, and the slave drones operate collaboratively with the master drone. The slave drones maintain synchronization with the master drone through positioning technology to form a precision reference network; an imaging unit 302 for controlling the master drone and at least one slave drone to capture images of a fixed area from different angles to obtain multi-angle images. The fixed area is a specific region that requires detailed mapping; a fusion unit 303 for fusing the multi-angle images to obtain a fused image; and a mapping unit 304 for performing detailed mapping of the fixed area based on the fused image to obtain a region mapping map.

[0117] In some embodiments, the above-mentioned positioning technology is differential positioning technology, and the above-mentioned construction unit 301 is specifically used to: control the slave device to receive the reference positioning data sent by the host; control the slave device to perform differential operation based on its own collected positioning data and the reference positioning data to obtain the relative position deviation; and control the slave device to adjust its own position according to the relative position deviation to keep synchronized with the host.

[0118] In some embodiments, the above-mentioned construction unit 301 is specifically used for: controlling the host to obtain its own reference position through the global navigation satellite system; controlling the slave to construct a relative positioning relationship with the host based on the reference position and its own real-time positioning information; and forming a precision reference network for the master-slave unmanned aerial vehicle swarm based on the relative positioning relationship.

[0119] In some embodiments, the above-mentioned shooting unit 302 is specifically used for: acquiring terrain contour information of a fixed area; planning the shooting height and shooting azimuth of the host and at least one slave device according to the terrain contour information; controlling the host and at least one slave device to shoot according to the shooting height and shooting azimuth to obtain multi-angle images; wherein, the shooting height and shooting azimuth are different for different drones.

[0120] In some embodiments, the above-mentioned shooting unit 302 is specifically used to: control the host to fly to a first altitude and vertically shoot a fixed area to obtain a main image; control at least one slave to fly to its corresponding second altitude and shoot the fixed area according to its corresponding azimuth angle to obtain at least one secondary image; wherein, the shooting altitude includes the first altitude and at least one second altitude, and the multi-angle image includes the main image and at least one secondary image.

[0121] In some embodiments, the fusion unit 303 is specifically used to: preprocess the multi-angle image to remove noise information from the image; extract feature points from the preprocessed multi-angle image to obtain a feature point set; and match and fuse the feature point set to obtain a fused image.

[0122] In some embodiments, the mapping unit 304 is specifically used to: extract terrain detail features of a fixed area from the fused image; construct a mapping model based on the terrain detail features; and generate a regional mapping map of the fixed area based on the mapping model.

[0123] In the high-precision mapping device based on UAV swarm provided in this application embodiment, a master-slave UAV swarm is constructed with the host as the base station. This enables the slave UAVs to maintain positioning synchronization with the host, forming a precision reference network. This effectively overcomes the problem of large absolute positioning errors of single UAVs and improves the relative positioning accuracy of the UAV swarm itself. On this basis, the host and slave UAVs work together to take pictures of the fixed area from different angles, acquiring multi-angle images. This overcomes the limitations of single-angle shooting, which is easily affected by terrain and weather factors, ensuring the integrity of image information and multi-view coverage. Subsequently, the acquired multi-angle images are fused to effectively integrate complementary information, eliminate single-view blind spots, and enhance the image detail, providing a high-quality data foundation for subsequent mapping. Finally, high-precision mapping is performed based on this high-precision fused image, optimizing the detail reproduction and spatial accuracy of the mapping results, thereby effectively improving the mapping accuracy of the fixed area.

[0124] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0125] Figure 4 This is a structural diagram of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 400 includes, but is not limited to, a processor 401 and a memory 402.

[0126] The aforementioned memory 402 is used to store the executable instructions of the aforementioned processor 401. It is understood that the aforementioned processor 401 is configured to execute instructions to implement the UAV swarm-based refined mapping method in the above embodiments.

[0127] It should be noted that those skilled in the art will understand that Figure 4 The electronic device structure shown does not constitute a limitation on the electronic device; the electronic device may include, but is not limited to, other electronic devices. Figure 4 This may indicate more or fewer components, or combinations of certain components, or different component arrangements.

[0128] Processor 401 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 402, and by calling data stored in memory 402, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Processor 401 may include one or more processing units. Optionally, processor 401 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 401.

[0129] The memory 402 can be used to store software programs and various data. The memory 402 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required by at least one functional module (such as a determination unit, processing unit, etc.), etc. Furthermore, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0130] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 402 including instructions, which can be executed by a processor 401 of an electronic device 400 to implement the UAV swarm-based fine mapping method in the above embodiments.

[0131] In actual implementation, Figure 3 The steps performed by the construction unit 301, the shooting unit 302, the fusion unit 303, and the surveying unit 304 can all be performed by... Figure 4The processor 401 calls the computer program stored in the memory 402 to implement the process. The specific execution process can be found in the description of the method section in the previous embodiment, and will not be repeated here.

[0132] Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0133] In an exemplary embodiment, this application also provides a computer program product including one or more instructions, which can be executed by a processor 401 of an electronic device to complete the high-resolution mapping method based on UAV swarms in the above embodiments.

[0134] It should be noted that when one or more instructions in the computer-readable storage medium or computer program product are executed by the processor of an electronic device, they implement the various processes of the above method embodiments and achieve the same technical effect as the above method. To avoid repetition, they will not be described again here.

[0135] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0137] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the classified units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0138] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0139] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, essentially, or the part that contributes to the prior art, or a complete or partial classification of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0140] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A refined mapping method based on unmanned aerial vehicle (UAV) swarms, characterized in that, The method includes: Construct a master-slave drone swarm, which includes a master drone and at least one slave drone. The master drone is a drone that serves as a reference station, and the slave drone is a drone that works in cooperation with the master drone. The slave drone maintains synchronization with the master drone through positioning technology to form a precision reference network. The host and at least one slave device are controlled to take pictures of the fixed area from different angles to obtain multi-angle images. The fixed area is a specific area that needs to be mapped in detail. The multi-angle images are fused to obtain a fused image; Based on the fused image, a detailed mapping of the fixed-point area is performed to obtain a regional mapping map.

2. The method for refined mapping of UAV swarms according to claim 1, characterized in that, The positioning technology is differential positioning technology, and the slave device maintains synchronization with the master device through the positioning technology, including: Control the slave device to receive the reference positioning data sent by the master device; The slave device is controlled to perform a differential operation based on its own collected positioning data and the reference positioning data to obtain the relative position deviation; The slave device is controlled to adjust its own position according to the relative position deviation in order to keep synchronized with the master device.

3. The method for refined mapping of UAV swarms according to claim 1 or 2, characterized in that, The formation of the accuracy reference network includes: The host computer is controlled to obtain its own reference position through the Global Navigation Satellite System; The slave device is controlled to construct a relative positioning relationship with the master device based on the reference position and its own real-time positioning information; Based on the relative positioning relationship, a precision reference network is formed for the master-slave drone swarm.

4. The method for refined mapping of UAV swarms according to claim 1, characterized in that, The control of the host and at least one slave device to take pictures of the fixed area from different angles to obtain multi-angle images includes: Obtain the terrain contour information of the fixed-point area; The shooting height and shooting azimuth angle of the host and at least one slave device are planned based on the terrain contour information; The host and at least one slave device are controlled to take pictures according to the shooting height and the shooting azimuth angle to obtain the multi-angle images; Different drones require different shooting altitudes and shooting azimuths.

5. The method for refined mapping of UAV swarms according to claim 4, characterized in that, The control of the host and at least one slave device to take pictures according to the shooting height and the shooting azimuth angle to obtain the multi-angle image includes: The host computer is controlled to fly to a first altitude and vertically photograph the fixed area to obtain the main image; Control at least one of the slave aircraft to fly to its respective second altitude and take pictures of the fixed-point area according to its respective azimuth angle to obtain at least one secondary image; The shooting height includes the first height and at least one second height, and the multi-angle image includes the main image and at least one of the sub-images.

6. The method for refined mapping of unmanned aerial vehicle (UAV) swarms according to claim 1, characterized in that, The process of fusing the multi-angle images to obtain a fused image includes: The multi-angle images are preprocessed to remove noise information from the images; Feature points are extracted from the preprocessed multi-angle images to obtain a feature point set; The feature point set is matched and fused to obtain the fused image.

7. The method for refined mapping of UAV swarms according to claim 1, characterized in that, The step of performing refined mapping of the fixed-point region based on the fused image to obtain a region mapping map includes: Extract terrain detail features of the fixed-point region from the fused image; A mapping model is constructed based on the described terrain details; The regional survey map of the fixed-point area is generated based on the survey model.

8. A refined mapping device based on unmanned aerial vehicle (UAV) swarms, characterized in that, The device includes: A construction unit is used to construct a master-slave drone swarm, which includes a master drone and at least one slave drone. The master drone is a drone that serves as a reference station, and the slave drone is a drone that works in cooperation with the master drone. The slave drone maintains synchronization with the master drone through positioning technology to form a precision reference network. The shooting unit is used to control the host and at least one slave device to take pictures of the fixed area from different angles to obtain multi-angle images. The fixed area is a specific area that needs to be finely surveyed. The fusion unit is used to fuse the multi-angle images to obtain a fused image; The surveying unit is used to perform fine surveying of the fixed-point area based on the fused image to obtain a regional surveying map.

9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the refined mapping method for unmanned aerial vehicle swarms as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing instructions, characterized in that, When the computer executes the instruction, the computer performs the refined mapping method for the UAV swarm as described in any one of claims 1 to 7.

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