Shallow water landform scanning method, unmanned aerial vehicle, electronic equipment and storage medium

Abstract

The invention discloses a shallow water landform scanning method, an unmanned aerial vehicle, electronic equipment and a storage medium, and the method comprises the steps: collecting first image data of a target water area through the unmanned aerial vehicle, carrying out the environment modeling based on the first image data, and obtaining a grid map of the target water area; in response to the task information instruction, marking a task target in the grid map; performing path planning by utilizing preset path planning software based on the task target to obtain a plurality of scanning paths; obtaining a route score of each scanning route according to a preset optimization demand, and taking the scanning route with the highest route score as a target route; based on the target route, controlling the unmanned aerial vehicle to perform landform scanning on the target water area to obtain scanning data; and performing data preprocessing and three-dimensional modeling on the scanning data to obtain an underwater terrain three-dimensional model of the target water area. According to the embodiment of the invention, shallow water landform scanning can be conveniently and accurately carried out, and the method can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a shallow water landform scanning method, an unmanned aerial vehicle, an electronic device and a storage medium. Background Art

[0002] Underwater topography mapping is an important basic work for marine scientific research and development and utilization. By obtaining underwater topographic data, including water depth, topographic undulations, sediment types, and underwater obstacles, and converting them into maps, three-dimensional models or other visualization forms, this process is of great significance for understanding the seabed topography, resource distribution, and environmental changes.

[0003] Shipborne sonar is a technology widely used in underwater terrain detection. This technology detects underwater targets by emitting sound waves and receiving echoes. The navigation mode of shipborne sonar can be along a predetermined route or in a grid pattern covering a specific area. During the navigation process, the shipborne sonar system collects data in real time and transmits it to the data processing system for analysis and imaging.

[0004] Sonar equipment is usually installed on the bottom of the hull or on both sides of the ship to transmit sound waves underwater and receive the reflected signals. By analyzing the time difference between the transmission and reception of the sound waves, the distance and position of obstacles can be calculated. By continuously transmitting and receiving sound waves, a three-dimensional image of the underwater environment can be constructed. Shipborne sonar can achieve ultra-wide coverage in deep water areas, significantly improve measurement efficiency, and can be combined with software to classify seabed landforms and bottom materials, thereby realizing multifunctional integrated detection.

[0005] However, shipborne sonar has the following disadvantages when scanning underwater terrain:

[0006] 1. Shallow water grounding risk: When a ship sails with excessive draft, it may lead to reduced maneuverability and the risk of loss of control. This not only destroys the natural conditions of the waterway, but may also cause local siltation, change water flow conditions, and even cause the ship to run aground. Therefore, it is not suitable for shallow water areas.

[0007] 2. Slow scanning speed: When conducting underwater topographic mapping, the ship-borne sonar system needs to sail slowly along the predetermined depth measurement line to ensure data coverage and accuracy. This process is particularly time-consuming when measuring large areas of sea. In addition, the turning and positioning of the ship between measurement points will also limit the measurement speed.

[0008] 3. Water depth limitation: In shallow water areas, sound waves are affected by more bottom reflection and scattering, resulting in signal attenuation, which significantly reduces measurement accuracy, especially in complex seabed terrain. In addition, due to the limitation of the launch device opening angle, the coverage of the sonar beam is limited, which may lead to the appearance of blind spots, thereby reducing measurement efficiency and increasing the complexity of data processing.

[0009] 4. Influence of environmental factors: The complexity of the underwater environment (such as water temperature, salinity, water flow and seabed sediment) will affect the propagation and reflection of sonar signals, thereby affecting the measurement results.

[0010] 5. Sonar signal interference: In busy waters, other ships' sonar systems, marine biological activities and seabed geological activities may generate noise and interfere with the effectiveness of sonar signals.

[0011] 6. Resolution limitations: Single-beam sonar has limited resolution and cannot clearly distinguish adjacent small underwater objects or terrain features. Although multi-beam sonar improves resolution, it may still be limited in very shallow waters or complex seafloor topography. Summary of the invention

[0012] The present invention aims to solve the problem of related technical limitations at least to a certain extent. To this end, the present invention proposes a shallow water topography scanning method, a drone, an electronic device and a storage medium, which can conveniently and accurately scan shallow water topography.

[0013] On the one hand, an embodiment of the present invention provides a shallow water topography scanning method, comprising the following steps:

[0014] Using a drone to collect first image data of the target water area, performing environmental modeling based on the first image data, and obtaining a grid map of the target water area;

[0015] In response to the mission information instruction, marking the mission target in the grid map;

[0016] Based on the mission objectives, the preset path planning software is used to plan the path and obtain multiple scanning routes;

[0017] Obtaining a route score for each scanning route according to preset optimization requirements, and taking the scanning route with the highest route score as the target route;

[0018] Based on the target route, the UAV is controlled to scan the target waters to obtain scanning data; wherein the UAV is equipped with a scanning device; the scanning device includes a camera and a laser radar; the first image data is obtained based on the camera collection; the scanning data is obtained based on the laser radar collection;

[0019] The scanned data is preprocessed and three-dimensionally modeled to obtain a three-dimensional model of the underwater terrain of the target waters.

[0020] Optionally, the first image data includes regional images of various locations of the target water area; performing environmental modeling based on the first image data to obtain a grid map of the target water area includes the following steps:

[0021] Perform image stitching on the regional images of all locations in the target water area to generate an orthophoto of the target water area;

[0022] Based on the preset data parameter format, the orthophoto is exported to a raster format to obtain a raster map of the target water area.

[0023] Optionally, in response to the task information instruction, marking the task target in the grid map comprises the following steps:

[0024] In response to the task information instruction of the target object, the task requirement of the shallow water topography scanning task is obtained, and the task target is marked in the grid map based on the task requirement.

[0025] Optionally, obtaining a route score of each scanning route according to a preset optimization requirement comprises at least one of the following steps:

[0026] An area score is determined according to a scan area of ​​each scan route, a distance score is determined according to a route distance of each scan route, a scan score is determined according to the number of scans of each scan route, and a route score corresponding to each scan route is obtained by weighted summing the area score, the distance score and the scan score based on a preset weight parameter; wherein the scan area is inversely proportional to the area score, the route distance is inversely proportional to the distance score, and the number of scans is inversely proportional to the scan score;

[0027] The route score corresponding to each scanning route is determined according to the flight parameters required by the UAV for each scanning route; wherein the flight parameters include flight speed, flight altitude and energy consumption.

[0028] Optionally, the drone is also equipped with a sensor device, which is used to collect sensory data of obstacles; the method further includes the following steps:

[0029] When the drone detects obstacles on the target route through the sensor equipment during terrain scanning;

[0030] Update and adjust the grid map based on obstacle perception data;

[0031] The target route is adjusted according to the updated and adjusted grid map, so that the UAV can fly away and avoid obstacles according to the result of the path adjustment.

[0032] Optionally, the drone is also equipped with an image transmission device, which is used to transmit the first image data collected by the camera to the remote controller; the method further includes the following steps:

[0033] Based on the second image data collected by the camera during the terrain scanning process, the remote controller uses its embedded target detection algorithm to perform personnel detection;

[0034] When a person is detected on the target route, the remote controller sends a warning to the person being operated, controls the drone to hover, and shuts down the laser radar on the drone.

[0035] Optionally, the scanning data includes laser scanning data; performing data preprocessing and three-dimensional modeling on the scanning data to obtain a three-dimensional model of underwater terrain of the target water area includes the following steps:

[0036] Import the scanned data into the preset data processing software, perform data preprocessing on the scanned data, and generate a digital elevation model;

[0037] Among them, data preprocessing includes data enhancement processing, data editing processing and verification and calibration processing; data enhancement processing includes removal of outliers, noise filtering, sound velocity profile correction and attitude correction; data editing processing includes interpolation, smoothing processing and outlier removal; verification and calibration processing includes verification and calibration of the initially generated digital elevation model based on known control point data or preset independent measurement data;

[0038] The digital elevation model is imported into the preset modeling software, and three-dimensional modeling is performed on the digital elevation model to generate a three-dimensional model of the underwater terrain of the target water area.

[0039] On the other hand, an embodiment of the present invention provides a shallow-water landform scanning UAV, which is applied to the aforementioned shallow-water landform scanning method. The UAV includes a fuselage; four symmetrical arms are arranged on both sides of the fuselage, and motors are connected to the ends of the arms. Propellers are arranged on the upper and lower sides of the motor, and multiple battery compartments are arranged above the fuselage. A visible light camera and an infrared thermal imaging camera are arranged in front of the fuselage, landing gears are arranged on both sides of the outer end below the fuselage, and connecting parts are installed on the inside. The landing gears on both sides are connected by connecting rods, and a laser radar is arranged under the connecting parts; the visible light camera, infrared thermal imaging camera and laser radar are used as scanning devices together.

[0040] On the other hand, an embodiment of the present invention provides an electronic device, including: a processor and a memory; the memory is used to store programs; the processor executes the program to implement the above-mentioned shallow water landform scanning method.

[0041] On the other hand, an embodiment of the present invention provides a computer storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to implement the above-mentioned shallow water landform scanning method.

[0042] The embodiment of the present invention collects the first image data of the target water area by using a drone, performs environmental modeling based on the first image data, and obtains a grid map of the target water area; in response to the task information instruction, marks the task target in the grid map; based on the task target, uses the preset path planning software to perform path planning to obtain multiple scanning routes; obtains the route score of each scanning route according to the preset optimization requirements, and takes the scanning route with the highest route score as the target route; based on the target route, controls the drone to perform landform scanning on the target water area to obtain scanning data; wherein, the drone is equipped with a scanning device; the scanning device includes a camera and a laser radar; the first image data is obtained based on the camera collection; the scanning data is obtained based on the laser radar collection; the scanning data is preprocessed and three-dimensionally modeled to obtain a three-dimensional model of the underwater terrain of the target water area. The embodiment of the present invention provides high-quality image and data collection through the scanning device carried by the drone, and the landform scanning using the drone is not limited by the complexity of the seabed terrain, and can be effectively scanned on different types of seabed terrain. At the same time, the laser radar can quickly capture underwater terrain data, provide efficient scanning capabilities, and the laser radar generates high-resolution three-dimensional images, which is helpful for identifying and classifying underwater targets. The embodiment of the present invention can conveniently and accurately scan shallow water landforms. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solution of the present invention and do not constitute a limitation on the technical solution of the present invention.

[0044] Figure 1 This is a schematic diagram of an implementation environment for shallow water topography scanning provided by an embodiment of the present invention;

[0045] Figure 2 It is a schematic flow chart of a shallow water landform scanning method provided by an embodiment of the present invention;

[0046] Figure 3 A schematic diagram of the expansion process of environment modeling provided by an embodiment of the present invention;

[0047] Figure 4 A schematic diagram of an expanded flow chart of obtaining a route score for each scanning route provided by an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of an extended process of shallow water topography scanning provided by an embodiment of the present invention;

[0049] Figure 6 A schematic diagram of another extended process of shallow water topography scanning provided by an embodiment of the present invention;

[0050] Figure 7A schematic diagram of the expanded flow of step S600 provided in an embodiment of the present invention;

[0051] Figure 8 A schematic diagram of the structure of a shallow water topography scanning drone provided by an embodiment of the present invention;

[0052] Fig. 9 A schematic diagram of the structure of a remote controller of a shallow water topography scanning drone provided by an embodiment of the present invention;

[0053] Fig.10 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 used to limit the present invention.

[0055] It should be noted that, although the functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first / S100", "second / S200", etc. in the specification, claims and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0056] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0057] It is understandable that the shallow water landform scanning method provided in the embodiment of the present invention can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal is a smart phone, tablet computer, laptop computer, desktop computer, etc., but is not limited to this.

[0058] To facilitate the understanding of the technical solution of the present invention, the technical feature terms that may appear in the embodiments of the present invention are first explained:

[0059] like Figure 1 FIG. 1 is a schematic diagram of an implementation environment provided by an embodiment of the invention. Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected to a network wirelessly or wired to complete data transmission and exchange.

[0060] Server 101 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), as well as big data and artificial intelligence platforms.

[0061] In addition, the server 101 can also be a node server in the blockchain network. Blockchain is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm.

[0062] The terminal 102 may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto. The terminal 102 and the server 101 may be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present invention.

[0063] Based on the example Figure 1In the implementation environment shown, an embodiment of the present invention provides a shallow water topography scanning method. The following is explained using the shallow water topography scanning method applied in the server 101 as an example. It can be understood that the shallow water topography scanning method can also be applied in the terminal 102.

[0064] Reference Figure 2 , Figure 2 The flowchart of the shallow water topography scanning method applied to the server provided in the embodiment of the present invention, the execution subject of the shallow water topography scanning method can be any of the aforementioned computer devices (including servers or terminals). Figure 2 , the method comprises the following steps:

[0065] S100, using a drone to collect first image data of a target water area, performing environmental modeling based on the first image data, and obtaining a grid map of the target water area;

[0066] It should be noted that the first image data includes regional images of various locations in the target water area; in some embodiments, such as Figure 3 As shown, environmental modeling is performed based on the first image data to obtain a raster map of the target water area, which may include the following steps: S101, image stitching of regional images of all locations of the target water area to generate an orthophoto of the target water area; S102, based on a preset data parameter format, exporting the orthophoto to a raster format to obtain a raster map of the target water area.

[0067] Exemplarily, in some specific implementations, environmental modeling is first performed, which can be specifically implemented as follows: Start the drone and use the built-in GPS system to locate the target waters. The images taken by the drone are stitched using Photoscan software to generate accurate orthophotos. The orthophotos are exported to a raster format, and the raster map represents the spatial area in the form of a grid, where each grid cell represents a location (obstacle or free space). The resolution or size of the raster map is determined according to the flight altitude and mission requirements of the drone to ensure that the data accuracy meets the planning requirements. After the raster map is generated, aerial data is obtained from the remote sensing intelligent monitoring platform through the drone online service to provide a detailed geographical basis for subsequent path planning.

[0068] S200, in response to the task information instruction, marking the task target in the grid map;

[0069] It should be noted that in some embodiments, in response to the task information instruction, marking the task target in the grid map may include the following steps: in response to the task information instruction of the target object, obtaining the task requirements of the shallow water topography scanning task, marking the task target in the grid map based on the task requirements

[0070] For example, in some specific implementations, the target setting is performed for the shallow water topography scanning task set for the operation object or the management object, which can be specifically implemented as follows: according to the shallow water topography scanning task, the target is set in the raster map, including the starting point, the end point, the obstacle point and the necessary intermediate waypoints. The selection of the target is based on factors including task requirements, regional characteristics and obstacle locations, and is usually determined using experience-based standards and preset algorithms. In addition, the drone has the ability to dynamically adjust, can monitor environmental changes in real time during flight, and automatically update waypoints based on new perception data to ensure the smooth completion of the task.

[0071] S300, performing path planning based on the task target using preset path planning software to obtain multiple scanning routes;

[0072] Exemplarily, in some specific implementations, path planning can be implemented as follows: the UAV flight planning software intelligently plans all feasible flight routes based on the grids that need to be scanned in the map and the scanning accuracy and coverage required by the lidar system to ensure efficient coverage of the target area.

[0073] S400, obtaining a route score of each scanning route according to a preset optimization requirement, and taking the scanning route with the highest route score as the target route;

[0074] It should be noted that in some embodiments, Figure 4 As shown, obtaining the route score of each scanning route according to the preset optimization requirements may include at least one of the following steps:

[0075] S401, determining an area score according to a scan area of ​​each scan route, determining a distance score according to a route distance of each scan route, determining a scan score according to the number of scans of each scan route, and performing a weighted summation of the area score, the distance score and the scan score based on a preset weight parameter to obtain a route score corresponding to each scan route; wherein the scan area is inversely proportional to the area score, the route distance is inversely proportional to the distance score, and the number of scans is inversely proportional to the scan score;

[0076] Exemplarily, in some specific implementations, the path optimization selection can be optimized based on the calculated minimum scanning area "fA", where "fA" represents the optimization goal set based on minimizing the scanning area, and can be calculated based on the firefly algorithm or other optimization algorithms. Specifically, the laser radar scanning angle resolution θ (the ground angle range covered by each scan) is set and adjusted, and the flight altitude of the drone is set to R above the water surface. This height R is the vertical distance from the ground when the laser radar scans. At a height of R, the scanning range of the laser radar forms a conical area on the ground with the drone as the vertex, so the covered length is 2R*θ, and the area A covered by a single scan is: A=R^2*θ. The drone carries a laser radar to scan at a certain scanning frequency f, and each scan covers an area A. After arriving at the end point according to the planned flight route, the total area scanned by the laser radar is fA.

[0077] Specifically, the logical principle of path optimization includes evaluating the coverage efficiency and flight distance of each possible path to select the path with the shortest total flight distance and the least number of scans, thereby improving the utilization efficiency of resources.

[0078] S402, determining a route score corresponding to each scanning route according to the flight parameters required by the drone for each scanning route;

[0079] Among them, flight parameters include flight speed, flight altitude and energy consumption.

[0080] For example, in some specific implementations, factors such as the flight speed, altitude, and energy consumption of the drone can also be comprehensively considered during the path planning process. For example, the flight altitude directly affects the coverage and resolution of the lidar, the flight speed affects the timeliness of data collection, and the energy consumption is related to the endurance of the drone. Through a comprehensive analysis of these factors, it is ensured that the optimized path is both efficient and safe. Specifically, the route score is determined based on the flight parameters, and the sub-scores corresponding to each flight parameter in the flight speed, flight altitude, and energy consumption can be integrated and counted based on a mapping relationship table between preset parameter values ​​and score values ​​to obtain a route score corresponding to the final total.

[0081] In some preferred implementations, the final route score may also be determined by weighted summing the scores of the two score statistics in steps S401 and S402 to obtain the final score statistics.

[0082] S500, based on the target route, controlling the UAV to scan the target waters to obtain scanning data;

[0083] The UAV is equipped with a scanning device; the scanning device includes a camera and a laser radar; the first image data is acquired based on the camera; the scanning data is acquired based on the laser radar;

[0084] It should be noted that the drone is also equipped with a sensor device, which is used to collect sensor data of obstacles; in some embodiments, such as Figure 5 As shown, the method may also include the following steps: T100, when the drone detects the existence of an obstacle on the target route through the sensor equipment during the terrain scanning process; T200, updating and adjusting the grid map based on the perception data of the obstacle; T300, adjusting the path of the target route according to the updated and adjusted grid map, so that the drone can fly away and avoid the obstacle according to the result of the path adjustment.

[0085] For example, in some specific implementations, a remote controller can be used to control a drone to start a flight mission. The drone flies according to a preset route, and the laser radar, visible light camera, and infrared thermal imaging camera carried by the drone sense the surrounding environment in real time. The drone processes the sensed data through built-in sensors (such as ultrasonic sensors and laser rangefinders) and obstacle detection algorithms to dynamically adjust the flight path and adjust its pitch, roll, and yaw attitude in real time to avoid obstacles.

[0086] It should be noted that in some specific application scenarios, if the drone encounters emergency situations such as strong winds or insufficient power during flight, the drone will automatically activate the emergency response mechanism, switch to safety mode, find the nearest safe place to land, or enable the backup power supply to ensure a safe return.

[0087] It should also be noted that the drone is also equipped with an image transmission device, which is used to transmit the first image data collected by the camera to the remote controller; in some embodiments, such as Figure 6 As shown, the method may also include the following steps: T300, based on the second image data collected by the camera during the terrain scanning process, personnel detection is performed by using the remote control using its embedded target detection algorithm; T400, when a human object is detected on the target route, a warning is issued to the operating object through the remote control, the drone is controlled to perform a hovering operation, and the laser radar carried by the drone is turned off.

[0088] For example, in some specific implementations, the drone can also transmit images to the remote control in real time. The remote control can use the embedded YOLO target detection algorithm to detect whether there are people in the image. Once a person is detected, the remote control will issue a warning, hover the drone, and turn off the lidar to prevent the lidar from causing damage to human eyes and improve operational safety.

[0089] S600: Perform data preprocessing and three-dimensional modeling on the scanned data to obtain a three-dimensional model of the underwater terrain of the target water area.

[0090] It should be noted that the scanning data includes laser scanning data; in some embodiments, such as Figure 7 As shown, data preprocessing and three-dimensional modeling are performed on the scan data to obtain a three-dimensional model of the underwater terrain of the target water area, which can include the following steps: S601, importing the scan data into a preset data processing software, performing data preprocessing on the scan data, and generating a digital elevation model; wherein the data preprocessing includes data enhancement processing, data editing processing, and verification and calibration processing; the data enhancement processing includes removing outliers, noise filtering, sound velocity profile correction, and attitude correction; the data editing processing includes interpolation, smoothing processing, and outlier removal; the verification and calibration processing includes verifying and calibrating the initially generated digital elevation model based on known control point data or preset independent measurement data; S602, importing the digital elevation model into a preset modeling software, performing three-dimensional modeling on the digital elevation model, and generating a three-dimensional model of the underwater terrain of the target water area.

[0091] Exemplarily, in some specific implementations, after the flight mission is completed, the collected data can be imported into the professional software Pix4Dmapper for data preprocessing, and the steps include removing outliers, noise filtering, sound velocity profile correction and attitude correction to improve data quality. The preprocessed data is edited, including interpolation, smoothing and outlier removal to generate a more continuous and complete terrain data set. A digital elevation model (DEM) is generated using the edited data, and the digital elevation model is three-dimensionally modeled using professional software TerraSolid to generate a more intuitive three-dimensional model of underwater terrain. Finally, the generated digital elevation model is verified and calibrated by comparing with known control point data or other independently measured data to ensure the accuracy of the data.

[0092] On the other hand, an embodiment of the present invention provides a shallow-water landform scanning UAV, which is applied to any of the aforementioned shallow-water landform scanning methods. The UAV may include a fuselage; four symmetrical arms are arranged on both sides of the fuselage, and motors are connected to the ends of the arms. Propellers are arranged on the upper and lower sides of the motor, and multiple battery compartments are arranged above the fuselage (at least two battery compartments can be arranged, and excellent battery life is guaranteed by multiple battery compartments), a visible light camera and an infrared thermal imaging camera are arranged in front of the fuselage, landing gears are arranged on both sides of the outer end below the fuselage, and connecting parts are installed on the inside, the landing gears on both sides are connected by connecting rods, and a laser radar is arranged under the connecting parts; the visible light camera, infrared thermal imaging camera and laser radar are used as scanning devices together.

[0093] Among them, the drone is controlled by a remote control, which is equipped with a power button, a laser radar power button and a battery indicator light. A touch screen is set in the middle of the remote control, and lifting control joysticks and horizontal movement joysticks are set on both sides of the touch screen. A left turn button and a right turn button are set on the front left side of the remote control, and a camera rotation control button is set on the front right side.

[0094] For example, in some specific embodiments, the shallow-water topography scanning drone includes a fuselage, four symmetrical arms are arranged on both sides of the fuselage, motors are connected to the ends of the arms, propellers are arranged on the upper and lower sides of the motors, two battery compartments are arranged on the top of the fuselage, a visible light camera and an infrared thermal imaging camera are arranged in front of the fuselage, a landing gear is arranged on the outer end of the lower part of the fuselage, a connecting piece is installed on the inner side, the landing gears on both sides are connected by a connecting rod, and a laser radar (such as a small sea and land detection laser radar) is arranged under the connecting piece. The scanning drone is controlled by a remote controller, and the remote controller is provided with a power button, a laser radar power button and a battery indicator light, a touch screen in the middle, a menu button, an emergency stop button, and a lifting control joystick and a horizontal movement joystick are arranged on both sides of the touch screen, a left turn button and a right turn button are arranged on the left front side of the remote controller, and a camera rotation control button is arranged on the right front side.

[0095] The contents of the method embodiments of the present invention are all applicable to the drone device embodiments. The functions specifically implemented by the drone device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0096] In order to explain the principle of the technical solution of the present invention in detail, the overall process of the present invention is described below in combination with some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and cannot be regarded as a limitation of the present invention.

[0097] First of all, it should be noted that in view of the shortcomings of the prior art, the present invention provides a method for mapping landforms using a drone equipped with a laser radar, which is specifically implemented as follows:

[0098] According to the needs of terrain mapping, the flight route of the UAV is planned, and the flight altitude, speed and heading are determined to ensure that the lidar can effectively cover the target area. The drone equipped with lidar flies along the predetermined optimal route to reduce the amount of data and improve processing efficiency.

[0099] LiDAR measures distance by emitting laser pulses and receiving light waves reflected from the underwater surface. It can generate high-resolution three-dimensional terrain data. Unlike sonar, LiDAR uses light waves, which have limited penetration in water and are suitable for clear shallow water environments. When used underwater, LiDAR needs to use lasers of specific wavelengths that have good absorption and scattering properties on water to improve penetration and measurement accuracy. LiDAR systems can quickly scan large areas and are suitable for rapid topographic mapping of wide areas in a short period of time. LiDAR is not affected by the complexity of underwater terrain and can effectively detect on changing terrain. The convenience of battery replacement of drones enables long endurance, enabling them to efficiently perform LiDAR tasks, extend operating time and expand coverage. This flexibility and maneuverability enable drones to quickly respond to diverse reconnaissance and mapping needs, thereby significantly improving operational efficiency.

[0100] The technical solution of the present invention integrates an advanced flight control system (FCS), an intelligent path planning algorithm, precise GPS navigation technology, and an intuitive user interface through a remote control. The user can clearly see the scanning area on the remote control, and use the path planning algorithm to automatically calculate the best flight path based on the data of the scanning area. This automated path planning not only ensures the high efficiency of the scanning operation, but also generates very high-quality scans, greatly reducing the dependence on professionals. Even non-professionals can easily operate the drone through a simple and easy-to-use interface to perform complex terrain or underwater landform scanning tasks, thereby lowering the technical threshold and improving the safety and convenience of the operation.

[0101] The system of drones equipped with visible light cameras, infrared thermal imaging cameras and lidar provides an efficient monitoring solution: the visible light camera and infrared thermal imaging camera use multispectral target detection technology to capture real-time images, while the lidar is used for precise measurement and terrain scanning. In order to ensure the safety of operation, the system has an embedded target detection function based on the YOLO algorithm, which can automatically identify people in the image. Once a person is detected, the system will automatically turn off the lidar to avoid potential damage to the human eye, and record the location to make the drone hover. This automated response mechanism improves the safety of operation, reduces dependence on manual judgment, and ensures timely and accurate response, especially in rapidly changing or limited vision environments.

[0102] Specifically, Figure 8 and Fig. 9As shown, the shallow-water landform scanning UAV based on the small sea and land detection laser radar includes a fuselage 4, four symmetrical arms 3 are arranged on both sides of the fuselage, the ends of the arms are connected to motors 2, propellers 1 are arranged on the upper and lower sides of the motor, two battery compartments 5 are arranged on the top of the fuselage, a visible light camera 6 and an infrared thermal imaging camera 22 are arranged in front of the fuselage, a landing gear 7 is arranged at the outer end below the fuselage, a connecting piece 9 is installed on the inner side, the landing gears on both sides are connected by a connecting rod 8, and a small sea and land detection laser radar 10 is arranged under the connecting piece. The scanning UAV is controlled by a remote controller, and the remote controller is provided with a power button 11, a laser radar power button 21 and a power indicator 12, a touch screen 13 is in the middle, a menu button 14, an emergency stop button 15, and a lifting control joystick 16 and a horizontal movement joystick 17 are arranged on both sides of the touch screen, a left turn button 18 and a right turn button 19 are arranged on the left side of the front side of the remote controller, and a camera rotation control button 20 is arranged on the right side of the front side.

[0103] The fuselage of the drone is supported by the landing gear, and the connecting rods in the landing gear ensure the stability of the landing gear.

[0104] The laser radar is firmly connected to the fuselage through four connecting parts, and its bottom is higher than the landing gear.

[0105] Press the power button once and then long press it to turn on the remote control. The battery indicator shows the battery level of the remote control.

[0106] Two battery compartments ensure the drone's endurance, and the battery level is displayed on the remote control touch screen.

[0107] Select the genetic algorithm generation path in the remote control touch screen interface through the menu key.

[0108] Start the drone, the motor drives the propeller to rotate, and the drone is driven by the arm to start the flight mission.

[0109] Use the lidar power button to turn on the small sea and land detection lidar for data collection.

[0110] The drone can dynamically adjust its flight path based on real-time perception data, and can also be manually controlled to collect data through the emergency stop button, lift control joystick, horizontal movement joystick, left turn button, right turn button, and camera rotation control button.

[0111] The images captured by the visible light camera and infrared thermal imaging camera are transmitted to the remote control in real time. When the YOLO target detection algorithm embedded in the remote control detects the presence of a person in the image, the remote control will sound an alarm, hover the drone, and turn off the lidar.

[0112] In some specific application scenarios, in landform mapping, in order to enable lidar scanning to achieve large-scale three-dimensional terrain, underwater and vegetation scanning in a short time, it is necessary to optimize the path planning of drones equipped with lidar for lake landform scanning, so as to improve scanning efficiency and save energy:

[0113] 1. Obtain aerial data: The images taken by the drone are stitched together to generate orthophotos through software such as photoscan, and the orthophotos are exported into raster format;

[0114] 2. Generate a topographic map: Each grid of the grid map represents a location (obstacle or free space). The grid is a square with a side length of a. The area to be scanned is b = a^2*n, and the total number of grids is n.

[0115] 3. Path planning: The UAV flight planning software plans all feasible flight routes based on the grids that need to be scanned in the map and the scanning accuracy and coverage required by the lidar system;

[0116] 4. Scanning coverage area: Set and adjust the laser radar scanning angle resolution θ (the ground angle range covered by each scan), set the drone's flight altitude to R above the water surface. This height R is the vertical distance from the ground when the laser radar scans. At the height R, the laser radar's scanning range forms a conical area on the ground with the drone as the vertex, so the coverage length is 2R*θ. The area A covered by a single scan is: A=R^2*θ. The drone carries a laser radar to scan at a certain scanning frequency f. Each scan covers an area A. After arriving at the end point according to the planned flight route, the total area scanned by the laser radar is fA;

[0117] 5. Optimal path: After completing the mission scan, when fA is the smallest, the total distance flown by the drone is the shortest and the number of lidar scans is the least.

[0118] The scanning process of a shallow water topography scanning drone based on a small sea and land detection lidar can include the following steps:

[0119] Step 1, environmental modeling: Start the drone and use the built-in GPS system to locate the target waters. The images taken by the drone are stitched through the Photoscan software to generate accurate orthophotos. The orthophotos are exported to raster format. The raster map represents the spatial area in the form of a grid, where each grid cell represents a location (obstacle or free space). The resolution or size of the raster map is determined according to the flight altitude and mission requirements of the drone to ensure that the data accuracy meets the planning requirements. After the raster map is generated, the aerial data is obtained from the remote sensing intelligent monitoring platform through the drone online service to provide a detailed geographical basis for subsequent path planning.

[0120] Step 2: Target setting: According to the shallow water topography scanning mission, set the target in the grid map, including the starting point, end point, obstacle point and necessary intermediate waypoints. The selection of the target is based on factors such as mission requirements, regional characteristics and obstacle locations, and is usually determined using experience-based standards and preset algorithms. In addition, the drone has the ability to dynamically adjust, monitor environmental changes in real time during flight, and automatically update waypoints based on new perception data to ensure the smooth completion of the mission.

[0121] Step 3: Path planning: The UAV flight planning software intelligently plans all feasible flight routes based on the grids that need to be scanned in the map and the scanning accuracy and coverage required by the lidar system to ensure efficient coverage of the target area.

[0122] Step 4, path optimization: Path optimization is performed based on the calculated minimum scanning area "fA", where "fA" represents the optimization goal set based on minimizing the scanning area, which may be calculated based on the firefly algorithm or other optimization algorithms. The logical principle of path optimization includes evaluating the coverage efficiency and flight distance of each possible path to select the path with the shortest total flight distance and the least number of scans, thereby improving the efficiency of resource utilization. In the path planning process, factors such as the flight speed, altitude and energy consumption of the drone can also be considered comprehensively. For example, the flight altitude directly affects the coverage and resolution of the lidar, the flight speed affects the timeliness of data collection, and the energy consumption is related to the endurance of the drone. Through a comprehensive analysis of these factors, it is ensured that the optimized path is both efficient and safe.

[0123] Step 5, data collection: Use the remote control to start the flight mission. The drone flies according to the preset route. The laser radar, visible light camera and infrared thermal imaging camera on board perceive the surrounding environment in real time. The drone processes the perception data through built-in sensors (such as ultrasonic sensors and laser rangefinders) and obstacle detection algorithms to dynamically adjust the flight path and adjust its pitch, roll and yaw attitude in real time to avoid obstacles. If there is an emergency such as strong wind or low battery during flight, the drone will automatically start the emergency response mechanism, switch to safety mode, find the nearest safe place to land, or enable the backup power supply to ensure safe return.

[0124] Step 6: The drone transmits images to the remote controller in real time. The remote controller uses the built-in YOLO target detection algorithm to detect whether there are people in the image. Once a person is detected, the remote controller issues a warning, hovers the drone, and turns off the lidar to prevent the lidar from causing damage to human eyes and improve operational safety.

[0125] Step 7, data post-processing: After the flight mission is completed, the collected data is imported into the professional software Pix4Dmapper for data preprocessing, including outlier removal, noise filtering, sound velocity profile correction and attitude correction to improve data quality. The preprocessed data is edited, including interpolation, smoothing and outlier removal, to generate a more continuous and complete terrain data set. The edited data is used to generate a digital elevation model (DEM), and the professional software TerraSolid is used to perform three-dimensional modeling on the digital elevation model to generate a more intuitive three-dimensional model of the underwater terrain. Finally, the generated digital elevation model is verified and calibrated by comparing with known control point data or other independently measured data to ensure the accuracy of the data.

[0126] In summary, the advantages achieved by the technical solution of the present invention are as follows:

[0127] 1. Long endurance: Carrier-based aircraft have a long endurance so that they can perform long-term missions far away from the ship.

[0128] 2. Fast scanning: LiDAR can quickly capture underwater terrain data and provide efficient scanning capabilities.

[0129] 3. Terrain independence: The system is not limited by the complexity of the seabed terrain and can effectively scan on different types of seabed terrain.

[0130] 4. High-resolution imaging: LiDAR generates high-resolution three-dimensional images that help identify and classify underwater targets.

[0131] 5. Automatic target detection: Use target detection algorithms such as YOLO to automatically detect people or other important targets in the image.

[0132] 6. Safety mechanism: When a person is detected, the system automatically turns off the lidar and records the location to ensure the safety of the person.

[0133] 7. Hovering function: When a key point or area that needs protection is detected, the drone can automatically hover and wait for further instructions.

[0134] 8. Reduce manual dependence: Automated detection and response reduce reliance on manual judgment and improve the timeliness and accuracy of operations.

[0135] 9. Path planning: The intelligent path planning algorithm automatically designs the optimal flight path based on the geographic information of the scanned area, ensuring that the drone can efficiently cover the entire area.

[0136] 10. High-quality scanning: The sensors carried by drones provide high-quality images and data collection.

[0137] 11. Real-time data processing: The system can process data in real time and quickly feedback scanning results.

[0138] Compared with the prior art, the present invention has at least the following beneficial effects:

[0139] 1. Suitable for clear shallow water environment;

[0140] 2. Fast scanning speed;

[0141] 3. Less affected by complex terrain;

[0142] 4. The drone has long endurance and can perform tasks for longer periods of time when equipped with laser radar;

[0143] 5. Automatic path planning reduces dependence on professionals;

[0144] 6. Ensure personnel safety based on YOLO target detection.

[0145] On the other hand, an embodiment of the present invention further provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above shallow water landform scanning method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0146] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0147] like Fig.10 As shown, Fig.10 The hardware structure of an electronic device 1000 of another embodiment is illustrated. The electronic device 1000 includes:

[0148] The processor 1001 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (application-specific integrated circuit, aSIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention;

[0149] The memory 1002 may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1002 may store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1002, and the processor 1001 calls and executes the network node population optimization method of the embodiment of the present invention;

[0150] Input / output interface 1003, used to implement information input and output;

[0151] The communication interface 1004 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0152] A bus 1005 , which transmits information between various components of the device (e.g., the processor 1001 , the memory 1002 , the input / output interface 1003 , and the communication interface 1004 );

[0153] The processor 1001 , the memory 1002 , the input / output interface 1003 and the communication interface 1004 are connected to each other in communication within the device via the bus 1005 .

[0154] The electronic device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0155] The contents of the method embodiments of the present invention are all applicable to the electronic device embodiments. The functions specifically implemented by the electronic device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0156] Another aspect of an embodiment of the present invention further provides a computer-readable storage medium, the storage medium stores a program, and the program is executed by a processor to implement the above method.

[0157] It should be noted that the computer-readable medium shown in the embodiment of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read to Only Memory, CD to ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer readable signal media may also be any computer readable medium other than computer readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0158] The contents of the method embodiments of the present invention are all applicable to the computer-readable storage medium embodiments. The functions specifically implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0159] The embodiment of the present invention also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the above method.

[0160] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0161] It should be noted that, although several modules of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0162] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD to ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation of the present invention.

[0163] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0164] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0165] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0166] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution device, apparatus or device (such as a computer-based device, a device including a processor, or other device that can fetch instructions from an instruction execution device, apparatus or device and execute the instructions), or in conjunction with such instruction execution device, apparatus or device. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution device, apparatus or device, or in conjunction with such instruction execution device, apparatus or device.

[0167] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0168] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution device. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0169] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the 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 one or more embodiments or examples in a suitable manner.

[0170] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0171] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. A shallow water landform scanning method, characterized in that: The following steps are involved: Using a drone to collect first image data of a target water area, performing environmental modeling based on the first image data, and obtaining a grid map of the target water area; In response to the mission information instruction, marking the mission target in the grid map; Based on the task objectives, a preset path planning software is used to perform path planning to obtain multiple scanning routes; Obtaining a route score of each of the scanning routes according to a preset optimization requirement, and taking the scanning route with the highest route score as a target route; Based on the target route, the drone is controlled to scan the target waters to obtain scanning data; wherein the drone is equipped with a scanning device; the scanning device includes a camera and a laser radar; the first image data is obtained based on the camera; and the scanning data is obtained based on the laser radar; The scanned data is subjected to data preprocessing and three-dimensional modeling to obtain a three-dimensional model of the underwater terrain of the target water area.

2. The shallow water topography scanning method according to claim 1, characterized in that: The first image data includes regional images of various locations of the target water area; performing environmental modeling based on the first image data to obtain a grid map of the target water area includes the following steps: Performing image stitching on the regional images of all locations of the target water area to generate an orthophoto of the target water area; Based on a preset data parameter format, the orthophoto is exported into a raster format to obtain the raster map of the target water area.

3. The shallow water topography scanning method according to claim 1, characterized in that: The step of marking the task target in the grid map in response to the task information instruction comprises the following steps: In response to the task information instruction of the target object, a task requirement of the shallow water topography scanning task is obtained, and the task target is marked in the grid map based on the task requirement.

4. The shallow water topography scanning method according to claim 1, characterized in that: The step of obtaining a route score of each scanning route according to a preset optimization requirement comprises at least one of the following steps: An area score is determined according to a scan area of ​​each of the scan routes, a distance score is determined according to a route distance of each of the scan routes, a scan score is determined according to the number of scans of each of the scan routes, and a weighted sum is performed on the area score, the distance score and the scan score based on a preset weight parameter to obtain the route score corresponding to each of the scan routes; wherein the scan area is inversely proportional to the area score, the route distance is inversely proportional to the distance score, and the number of scans is inversely proportional to the scan score; The route score corresponding to each scanning route is determined according to the flight parameters required by the drone for each scanning route; wherein the flight parameters include flight speed, flight altitude and energy consumption.

5. The shallow water topography scanning method according to claim 1, characterized in that: The drone is also equipped with a sensor device, which is used to collect sensory data of obstacles; the method further includes the following steps: When the drone detects the existence of obstacles on the target route through the sensor device during the terrain scanning process; Updating and adjusting the grid map based on the perception data of the obstacle; The target route is adjusted according to the updated and adjusted grid map, so that the UAV flies away from the obstacle according to the result of the path adjustment.

6. The shallow water topography scanning method according to claim 1, characterized in that: The drone is also equipped with an image transmission device, which is used to transmit the image data collected by the camera to the remote controller; the method further includes the following steps: Based on the second image data collected by the camera during the terrain scanning process, the remote controller uses an embedded target detection algorithm to perform personnel detection; When a human object is detected on the target route, a warning is issued to the operating object through the remote controller, the drone is controlled to perform a hovering operation, the position of the human object is recorded, and the laser radar carried by the drone is turned off.

7. The shallow water topography scanning method according to claim 1, characterized in that: The scanning data includes laser scanning data; the data preprocessing and three-dimensional modeling of the scanning data to obtain the three-dimensional model of the underwater terrain of the target water area includes the following steps: Importing the scanned data into a preset data processing software, performing data preprocessing on the scanned data, and generating a digital elevation model; The data preprocessing includes data enhancement processing, data editing processing and verification and calibration processing; the data enhancement processing includes outlier removal, noise filtering, sound velocity profile correction and attitude correction; the data editing processing includes interpolation, smoothing and outlier removal; the verification and calibration processing includes verification and calibration of the initially generated digital elevation model based on known control point data or preset independent measurement data; The digital elevation model is imported into a preset modeling software, and three-dimensional modeling is performed on the digital elevation model to generate a three-dimensional model of the underwater terrain of the target water area.

8. A shallow water topography scanning drone, characterized in that: The shallow water topography scanning method applied to any one of claims 1 to 7, wherein the UAV includes a fuselage; four symmetrical arms are arranged on both sides of the fuselage, motors are connected to the ends of the arms, propellers are arranged on the upper and lower sides of the motor, a plurality of battery compartments are arranged above the fuselage, a visible light camera and an infrared thermal imaging camera are arranged in front of the fuselage, landing gears are arranged on both sides of the outer end below the fuselage, and connecting parts are installed on the inner side, the landing gears on both sides are connected by connecting rods, and a laser radar is arranged below the connecting part; the visible light camera, the infrared thermal imaging camera and the laser radar are collectively used as scanning equipment.

9. An electronic device, characterized in that: including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method according to any one of claims 1 to 7.

10. A computer storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

Images