Method and device for measuring the capacity of a ship's liquid cargo tank by using a multi-rotor drone with a camera

Abstract

This invention discloses a method and apparatus for measuring the capacity of a ship's liquid cargo tank using a multi-rotor drone equipped with a camera. The method includes: modifying the drone; establishing a flight control system and an image transmission system to achieve signal connection between the drone, server, remote controller, and mobile terminal; acquiring basic images of the cargo tank interior using an image acquisition tool to establish a realistic 3D basic model for subsequent waypoint selection and flight control; planning the drone's flight path based on the realistic 3D basic model; controlling the drone to fly inside the cargo tank and acquiring image data of the interior; and performing 3D modeling and cargo tank capacity calculation based on the image data acquired by the drone. This invention improves the accuracy and level of measurement of the contents of closed metal containers such as ship holds or large storage tanks.

Description

Technical Field

[0001] This invention relates to a method and apparatus for measuring the capacity of a ship's liquid cargo tank using a multi-rotor drone equipped with a camera. Background Technology

[0002] Currently, capacity measurement for large ship compartments or large storage tanks primarily involves using total stations or 3D laser scanners to measure the geometric features of the container, followed by calculations using appropriate mathematical models to determine the container volume. However, ship compartments or large storage tanks often have complex internal structures, with multiple vertical layers and numerous components and pipelines, creating many obstructed areas. Data collection is impossible in these areas due to obstruction, making it difficult to guarantee the accuracy and reliability of capacity measurement. Current methods involve manually constructing measurement platforms layer by layer to set up instruments, which is time-consuming, dangerous, and unable to cover all areas requiring measurement.

[0003] In recent years, drones have begun to be applied in the field of surveying. For example, patent application CN107356230A discloses a digital mapping method and system based on a real-scene 3D model. This scheme uses drone oblique photogrammetry for 3D modeling and combines it with a ground surveying robot for digital mapping. The control point coordinates obtained by the ground surveying robot can effectively control the overall accuracy of the model, and the obtained ground feature coordinates can effectively compensate for the insufficient coordinate accuracy caused by obstructions after aerial drone modeling. Patent application CN105352481A discloses a high-precision drone image mapping method and system without control points. This scheme obtains the accurate coordinates of the exposure time of the photograph by processing the data from the captured image, ground reference station and field control points, airborne GNSS receiver, and drone POS. Using the above information, image stitching is performed, reducing the need for field control points and improving the accuracy of drone aerial mapping. GNSS is the abbreviation for Global Navigation Satellite System.

[0004] While these methods can improve the accuracy of UAV aerial mapping to some extent, none of them take into account the problem of how UAVs can control their flight in enclosed indoor spaces without satellite navigation signals.

[0005] Existing technologies mainly enable UAVs to locate and perform flight mapping by receiving satellite signals using airborne GNSS receivers in the field. However, the Faraday cage effect occurs in large enclosed metal containers such as ship cabins or oil tanks, resulting in the inability to receive satellite signals and thus preventing UAVs from flying using satellite signals. Summary of the Invention

[0006] In order to overcome the above-mentioned defects in the existing technology, the present invention provides a method and apparatus for measuring the capacity of a ship's liquid cargo tank by carrying a camera on a multi-rotor UAV.

[0007] The present invention solves the above-mentioned technical problems through the following technical solution:

[0008] A method for measuring the capacity of a ship's liquid cargo tank using a multi-rotor unmanned aerial vehicle (UAV) equipped with a camera, comprising:

[0009] Step 1: Modify the drone, including mounting a wide-angle zoom camera and a camera gimbal on the drone;

[0010] Step 2: Establish the flight control system and image transmission system to realize the signal connection between the drone, server, remote controller, and mobile terminal;

[0011] Step 3: Collect basic images of the cargo hold interior using image acquisition tools to create a real-world 3D basic model for subsequent waypoint selection and flight control.

[0012] Step 4: Based on the real-world 3D model, plan the flight path of the UAV;

[0013] Step 5: Control the drone to fly inside the cabin and collect image data of the cabin interior;

[0014] Step 6: Based on the image data collected by the UAV, perform 3D modeling and cabin capacity calculation.

[0015] Furthermore, step 1 also includes installing a top infrared sensing system, a landing terrain detection system, a lighting module to improve image brightness, a multi-sensor collaborative control system, and dual inertial navigation units on the drone.

[0016] Furthermore, in step 2, wireless signals are used to connect the remote controller and the drone, the remote controller and the server, and the mobile terminal and the server; a wired connection is used between the remote controller and the mobile terminal; the flight control system can control the drone to fly autonomously according to the flight route designed in the flight mission and complete image acquisition according to the designed waypoint positions and shooting modes; the flight control system includes flight control software, establishes a real-time connection between the flight control software, the camera gimbal and the drone, transmits images back during the drone image acquisition process, and realizes real-time transmission and download of photos and videos.

[0017] Furthermore, in step 3, the image acquisition tools include a total station, a digital camera, and photogrammetric markers; or, the image acquisition tools include a handheld camera with freely adjustable shooting angles.

[0018] Furthermore, in step 4, the UAV's route planning includes single waypoint design, route segment design, modification of route or waypoint, connecting waypoints, displaying the aircraft's photography range, route roaming, and obstacle judgment on the route.

[0019] Single waypoint design includes: selecting a point on the ground in the real-world 3D basic model to determine the planar position of the waypoint; setting the flight altitude of the waypoint, the pitch angle of the camera when taking pictures, the nose turn angle of the aircraft, and whether other actions need to be performed after taking a picture of an image;

[0020] The flight path design includes: selecting two waypoints on the real-world 3D base model, and setting a flight path between the two waypoints; multiple waypoints need to be inserted within a flight path to ensure the overlap of the images; when the distance between them is too far, more waypoints need to be placed in the flight path between the two waypoints to meet the photography requirements.

[0021] Modifying routes or waypoints includes: after selecting and setting all waypoints and routes, modifying the routes that have been set according to actual needs;

[0022] Connecting waypoints involves linking all waypoints according to their positions and logical order. When encountering modified waypoints or added waypoints or flight segments, waypoints are linked based on proximity and altitude from low to high.

[0023] The display of the aircraft's photographic range includes: calculating the visible range of a single image on the model based on the location of waypoints and the parameters of the photographic design, and displaying it on the model;

[0024] Flight route roaming includes: roaming the flight route through the designed shooting angles of each waypoint, previewing the shooting range of each waypoint, and determining the overlap between two adjacent images using this method;

[0025] Obstacle detection on the flight path includes: determining whether there are obstacles on the flight path by judging whether there is an intersection between the flight path and the model; if there are obstacles, feedback is given to the user.

[0026] Furthermore, in step 5, the image transmission control system receives the flight path plan, issues and monitors the UAV flight mission, and controls the UAV to fly according to the designed flight path to collect image data at fixed points through the flight control system; the UAV's flight position and attitude information is calculated in real time by adaptively matching four or more pairs of three-dimensional points on the real scene three-dimensional basic model and two-dimensional points on the image, and performing single-image space resection calculation to determine the attitude and position at the time of image capture, and to determine whether the flight position and attitude have reached the preset position.

[0027] Furthermore, visual pose estimation includes: establishing a relationship between the image to be solved and known scene information, matching feature points of the scene's 3D model with feature points of the 2D image; and using spatial resection to solve for the exterior orientation elements of the image based on the correspondence between the 3D and 2D feature points, thereby obtaining the pose of the UAV.

[0028] Furthermore, in step 6, after obtaining the image data, the cabin 3D model is reconstructed by solving the image exterior orientation elements, generating dense matching point clouds, constructing triangulation networks, and adaptive data repair; the image exterior orientation elements are obtained by joint adjustment of multi-source data such as flight control information, indoor pose parameters, and camera parameters under various constraints, and local updates are achieved through automatic registration of multi-temporal acquisition data.

[0029] Furthermore, step 6 also includes:

[0030] By searching for corresponding points of the stereo image pair along the epipolar line constraint relationship, a disparity map of the stereo image pair can be obtained. Then, a large number of corresponding points of the stereo image pair can be calculated from the disparity map, and spatial forward intersection of the corresponding point pairs can be performed to obtain the three-dimensional point cloud of the ship's cabin.

[0031] After obtaining the point cloud, surface reconstruction is used to estimate the surface indicator function of the model and extract the corresponding isosurface to form a three-dimensional solid model composed of seamless triangular facets from the discrete point cloud.

[0032] The capacity of the complex closed three-dimensional region is calculated by intersecting the waterline surface with the surface of the three-dimensional model. The final capacity is obtained by considering the calculation of internal components and the tilt correction of the ship under different floating states.

[0033] A device for measuring the capacity of a ship's liquid cargo tank using a multi-rotor unmanned aerial vehicle (UAV) equipped with a camera, comprising:

[0034] The drone is equipped with a wide-angle zoom camera and a camera gimbal.

[0035] The flight control and image transmission module is used to establish the flight control system and the image transmission system, and to realize the signal connection between the UAV, server, remote controller and mobile terminal;

[0036] The ground acquisition and basic model generation module is used to acquire basic images of the cargo hold interior using image acquisition tools, and to build a real-scene 3D basic model for subsequent waypoint selection and flight control.

[0037] The drone flight path planning module is used to plan the flight path of drones based on a real-world 3D model.

[0038] The cabin capacity calculation module is used to perform 3D modeling and cabin capacity calculation based on image data collected by UAVs.

[0039] The beneficial effects of this invention are as follows: This invention solves the problem that drones cannot receive satellite signals and cannot locate or fly autonomously inside closed metal containers such as ship cabins or large storage tanks, and solves the problem of lacking effective capacity measurement methods when there is severe obstruction inside the cabin, thereby improving the accuracy and measurement level of capacity measurement in such special scenarios. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of a device according to a preferred embodiment of the present invention. Detailed Implementation

[0041] The present invention will be described more clearly and completely below with reference to a preferred embodiment and the accompanying drawings.

[0042] This embodiment provides a method for measuring the capacity of a ship's liquid cargo tank using a multi-rotor UAV equipped with a camera, which includes:

[0043] Step 1: Modify the drone, including mounting a wide-angle zoom camera and a camera gimbal on the drone;

[0044] Step 2: Establish the flight control system and image transmission system to realize the signal connection between the drone, server, remote controller, and mobile terminal;

[0045] Step 3: Collect basic images of the cargo hold interior using image acquisition tools to create a real-world 3D basic model for subsequent waypoint selection and flight control.

[0046] Step 4: Based on the real-world 3D model, plan the flight path of the UAV;

[0047] Step 5: Control the drone to fly inside the cabin and collect image data of the cabin interior;

[0048] Step 6: Based on the image data collected by the UAV, perform 3D modeling and cabin capacity calculation.

[0049] This invention modifies a drone to establish a flight control system and an image transmission system, creates a real-scene 3D basic model, performs fine-grained flight path planning based on the real-scene 3D basic model, controls the drone's flight and collects images, and performs 3D modeling and capacity calculation.

[0050] The specific steps are as follows:

[0051] 1. Drone modification.

[0052] Modify the drone. The drone will be a multi-rotor drone.

[0053] By mounting multiple wide-angle zoom cameras on a multi-rotor drone and configuring a camera gimbal with high degrees of freedom, images inside the ship's cabin can be acquired.

[0054] Equipping drones with depth sensors can acquire the coordinates of the hull, which can then be used in the initial calculation of the camera position.

[0055] Installing a top-mounted infrared sensing system on the drone can provide upper-body protection during flight, preventing the drone from crashing due to excessive altitude.

[0056] Install a landing terrain detection system on the drone to determine the flight altitude using ultrasound, and an obstacle perception system to avoid obstacles.

[0057] Install lighting modules on drones to improve image brightness; install multi-sensor collaborative control systems and dual inertial navigation units on drones to enable precise control and high-precision data acquisition during mission execution.

[0058] The camera system and its selected lens mounted on the drone can be the Zenmuse X7 camera, Zenmuse X7 DL 35mm lens, or Zenmuse X7 DL 24mm lens.

[0059] 2. Establish flight control system and image transmission system.

[0060] Establish a flight control system and an image transmission system to achieve signal connection between the drone, server, remote controller, and mobile terminal. The mobile terminal can be a mobile phone. The server is located on a laptop computer.

[0061] The hardware of the ship's in-cabin drone flight control and image transmission system mainly consists of the drone, server, mobile phone, and remote controller. The mobile phone connects to the server via Wi-Fi; the remote controller connects to the drone via antenna frequency pairing, and the mobile phone connects to the remote controller via a Type-C interface. The mobile phone controls the drone through the remote controller, and its upload interface uploads drone data to the server, ensuring seamless connectivity between the mobile phone, drone, and server. The flight control system includes flight control software. This software is a mobile flight control app developed based on the DJI Mobile SDK. It controls the drone to fly autonomously according to the designed flight path and takes fixed-point photos at the designed waypoints and shooting modes to complete image acquisition. The flight control software allows users to view camera shooting status and transmit image data in real time.

[0062] The image transmission system integrates the data link between the image acquisition terminal, mobile terminal, and server, enabling rapid processing of the on-site environment. It establishes a real-time connection between the flight control software, camera gimbal, and drone, transmitting high-definition images during drone image acquisition and enabling real-time transmission and download of photos and videos. The system primarily operates within a local area network environment, enabling the mobile flight control software to receive flight missions; the client to create flight missions; and the server to monitor flight mission status and view flight mission image results.

[0063] 3. Establish a basic model of the ship's cabin.

[0064] Using a total station, digital camera, and photogrammetric markers, basic images of the cargo hold interior were acquired. A realistic 3D model was then established for subsequent waypoint selection and flight control. DP-Smart was used for image data processing and 3D reconstruction to generate the 3D realistic model for use in subsequent waypoint selection and flight control.

[0065] A handheld camera (Canon 5DMK4) with freely adjustable shooting angles was used to capture basic images of the ship's cabin. A ground-based shooting tripod was used to take photos from multiple angles. During this process, it was necessary to ensure the overlap of the images. After acquiring the images, an exhaustive matching method was used to estimate whether there were any missed areas by analyzing the relationships between the images and the range of the images captured.

[0066] 4. Detailed route planning based on real-world 3D scenery.

[0067] Fine-grained flight path planning based on a realistic 3D model refers to interactive flight path planning. Operators can intuitively select waypoints, set the angle of the shooting gimbal, preview the shooting range, and make deletions and edits to improve the quality of indoor image acquisition. In addition, by performing spatial calculations on the flight path formed by connecting waypoints and the 3D model, conflicts between the flight path and obstacles can be detected, improving flight safety in complex indoor environments.

[0068] Indoor flight path planning based on real-world 3D scenery mainly includes the following:

[0069] (1) Single waypoint design: Select a point on the ground in the real-world 3D basic model to determine the planar position of the waypoint. Set the flight altitude of the waypoint, the pitch angle of the camera when shooting, the nose turn angle of the aircraft, and whether other actions need to be performed after taking a picture of one image (taking multiple pictures at a certain waypoint according to different shooting angles).

[0070] (2) Flight line segment design: Select two waypoints on the real scene 3D basic model and set a flight line segment between the two waypoints; multiple waypoints need to be inserted in a flight line segment to ensure the overlap of the images. When the distance is too far, more waypoints need to be set up in the flight line segment between the two waypoints to meet the photography requirements.

[0071] (3) Modify routes or waypoints: After selecting and setting all waypoints and routes, modify the routes that have been set according to actual needs, that is, add or delete routes.

[0072] (4) Connecting waypoints: Connect all waypoints according to their positions and logical order. When encountering modified waypoints or added waypoints or route segments, connect waypoints according to the principle of proximity and from low to high altitude.

[0073] (5) Display the aircraft's photographic range: Calculate the visible range of a single image on the model based on the location of the waypoint and the parameters of the photographic design (parameters include flight altitude, pitch angle, nose turn angle, etc.), and display it on the model.

[0074] (6) Route roaming: Route roaming is performed by taking pictures at each waypoint through the designed route and previewing the range of each waypoint. The overlap between two adjacent images is determined by this method.

[0075] (7) Obstacle detection on the flight path: By judging whether there is an intersection between the flight path and the model, it is determined whether there is an obstacle on the flight path. If there is an obstacle, it is fed back to the user.

[0076] 5. Control the drone's flight and collect images

[0077] A multi-rotor UAV autonomously acquires images with the assistance of a realistic 3D model. An indoor 3D flight path is designed based on the realistic 3D model of the cabin. An image transmission system receives the designed 3D flight path, issues and monitors the UAV's flight mission, and the UAV flight control software controls the UAV to fly along the designed flight path to collect image data at designated points. This data is then combined with indoor signage to improve the accuracy of subsequent calculations.

[0078] In indoor flight, the drone is placed at the waypoint launch point. The drone's flight control software receives the flight mission, and the drone flies vertically to the waypoint to take pictures. Based on the drone's position and the inertial navigation unit (IMU), the drone is controlled for autonomous flight. Upon reaching the next waypoint, the drone's position and attitude information is calculated in real time, compared with the designed waypoint position, and the drone's position is calibrated.

[0079] The drone's flight position and attitude information is calculated in real time by adaptively matching four or more pairs of points, including three-dimensional points on the real-world three-dimensional basic model and two-dimensional points on the image, and performing single-image space resection calculation to determine the attitude and position at the time of image capture, and to determine whether the flight position and attitude have reached the preset position.

[0080] Visual pose estimation involves two key steps: first, establishing a relationship between the image to be solved and known scene information, that is, matching the feature points of the real-world 3D model with the feature points of the 2D image; second, based on the correspondence between the 3D and 2D feature points, using the spatial resection method to solve for the exterior orientation elements of the image, thereby obtaining the pose of the UAV.

[0081] 6. 3D modeling and capacity calculation

[0082] After acquiring cabin imagery data, the cabin's 3D model is reconstructed through image exterior orientation element calculation, dense matching point cloud generation, triangulation construction, and adaptive data repair. Multi-source data, including flight control information, indoor pose parameters, and camera parameters, are combined under various constraints to obtain image exterior orientation elements, which are then updated locally through automatic registration of multi-temporal acquired data.

[0083] By searching for corresponding points of the stereo image pair along the epipolar line constraint relationship, a disparity map of the stereo image pair can be obtained. Then, a large number of corresponding points of the stereo image pair can be calculated from the disparity map, and spatial forward intersection of the corresponding point pairs can be performed to obtain the three-dimensional point cloud of the ship's cabin.

[0084] After obtaining the point cloud, surface reconstruction based on the Poisson equation is used to estimate the surface indicator function of the model and extract the corresponding isosurfaces to form a three-dimensional solid model composed of seamless triangular facets from the discrete point cloud.

[0085] The capacity of the complex closed three-dimensional region is calculated by intersecting the waterline surface with the surface of the three-dimensional model. The final capacity is obtained by considering the calculation of internal components and the tilt correction of the ship under different floating states.

[0086] This embodiment describes a method for measuring the capacity of a ship's liquid cargo tank using a multi-rotor UAV equipped with a camera. The method involves modifying the multi-rotor UAV to carry a wide-angle zoom camera and configuring a camera gimbal with high degrees of freedom to acquire images within the ship's liquid cargo tank area. By collecting images of the tank interior using a ground camera, total station, and coded markers, a realistic 3D model of the tank is quickly established, providing a base map for UAV flight path design. Flight control software controls the UAV's flight and image acquisition, and image processing, 3D reconstruction, and capacity calculation are used to measure the ship's tank capacity.

[0087] In practical measurements, the measurement using imaging equipment requires that the relative flight altitude, ground resolution, and physical pixel size meet the trigonometric ratio. To form a 3D model, the lateral overlap of the flight path design needs to reach 66%, and the forward overlap also needs to reach 66%. These requirements cannot be met by manually controlling the UAV; a flight control system must be used to enable the UAV to fly autonomously according to the flight path document. The Faraday cage effect inside ship cabins or oil tanks prevents the UAV from flying using satellite signals. To address this problem, this invention proposes a multi-rotor UAV flight method based on a real-scene 3D model. A certain number of identifiable coded markers are deployed on the ground and elevations. The coordinates of the center point of each coded marker are measured using a total station or other instruments. Images are acquired using a handheld camera, control points are marked on the images, and 3D reconstruction is performed to obtain a real-scene 3D basic model. Secondly, in the precision flight phase, using the real-scene 3D basic model and based on the actual project's image resolution requirements, UAV flight safety and accessibility, and the requirement to comprehensively acquire images of various indoor areas, a certain number of waypoints are selected. The flight altitude and shooting angle are designed according to the pre-designed overlap, and a flight mission is designed and sent to the UAV. The UAV flies according to the preset flight path and acquires images. Finally, by calculating the coverage area of ​​the images acquired during the precise flight phase, it is determined whether the images are comprehensive enough and whether the resolution of the images meets the requirements. If not, supplementary flights are required based on the actual situation.

[0088] The present invention relates to a method for measuring the capacity of a ship's liquid cargo tank using a multi-rotor UAV equipped with a camera. By establishing a realistic 3D basic model, designing flight routes, and implementing a UAV flight control system, the method enables the UAV to locate itself and autonomously fly to collect images. This solves the problem that UAVs cannot receive satellite signals and thus cannot locate themselves or fly autonomously inside enclosed metal containers such as ship cabins or large storage tanks. It also addresses the lack of effective capacity measurement methods in situations with severe obstruction inside the cabin, thereby improving the accuracy and level of capacity measurement in such special scenarios.

[0089] like Figure 1 As shown, this embodiment provides a device for measuring the capacity of a ship's liquid cargo tank using a multi-rotor UAV equipped with a camera, which includes:

[0090] The drone 11 is equipped with a wide-angle zoom camera and a camera gimbal.

[0091] The flight control and image transmission module 12 is used to establish the flight control system and the image transmission system, and realize the signal connection between the UAV, server, remote controller and mobile terminal;

[0092] Ground acquisition and basic model generation module 13 is used to acquire basic images of the cargo hold interior through image acquisition tools and establish a real-scene 3D basic model for subsequent waypoint selection and flight control.

[0093] The UAV flight path planning module 14 is used to plan the flight path of the UAV based on the real-scene 3D basic model.

[0094] The cabin capacity calculation module 15 is used to perform 3D modeling and cabin capacity calculation based on image data collected by UAV.

[0095] The device for measuring the capacity of a ship's liquid cargo tank using a multi-rotor UAV equipped with a camera in this embodiment adopts the aforementioned method for measuring the capacity of a ship's liquid cargo tank using a multi-rotor UAV equipped with a camera.

[0096] This embodiment uses a multi-rotor UAV equipped with a camera to measure the capacity of a ship's liquid cargo tank. First, a ground-based data acquisition and basic model generation module collects and establishes a realistic 3D basic model. Then, 3D flight path UAV flight control software is designed and generated on the model to control the UAV to fly according to waypoint coordinates and control the camera to acquire images. The UAV image transmission system monitors the UAV's flight mission, controlling the UAV based on its position and inertial navigation unit (IMU) to achieve autonomous flight and photography. Motion reconstruction technology is used to accurately recover the exterior orientation elements of each image. A large number of corresponding points of the stereo image pairs are calculated and spatial forward intersection is performed to obtain a 3D point cloud. Finally, a 3D model of the ship's cargo hold is established through mesh reconstruction and fine modeling to calculate the corresponding capacity.

[0097] The device for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV in this embodiment has the same technical features as the aforementioned method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV, and can solve the same technical problems and achieve the same technical effects. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above device can be referred to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0098] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A method for measuring the capacity of a ship's liquid cargo tank using a multi-rotor unmanned aerial vehicle equipped with a camera, characterized in that, It includes: Step 1: Modify the drone, including mounting a wide-angle zoom camera and a camera gimbal on the drone; Step 2: Establish the flight control system and image transmission system to realize the signal connection between the drone, server, remote controller, and mobile terminal; Step 3: Collect basic images of the cargo hold interior using image acquisition tools to create a real-world 3D basic model for subsequent waypoint selection and flight control. Step 4: Based on the real-world 3D model, plan the flight path of the UAV; Step 5: Control the drone to fly inside the cabin and collect image data of the cabin interior; Step 6: Based on the image data collected by the UAV, perform 3D modeling and cabin capacity calculation.

2. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 1, characterized in that, Step 1 also includes installing a top infrared sensing system, a landing terrain detection system, a lighting module to improve image brightness, a multi-sensor collaborative control system, and dual inertial navigation units on the drone.

3. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 1, characterized in that... In step 2, wireless signals are used to connect the remote controller and the drone, the remote controller and the server, and the mobile terminal and the server; a wired connection is used between the remote controller and the mobile terminal; the flight control system can control the drone to fly autonomously according to the flight route designed in the flight mission and complete image acquisition according to the designed waypoint position and shooting mode; the flight control system includes flight control software, establishes a real-time connection between the flight control software, camera gimbal and drone, transmits images back during the drone image acquisition process, and realizes real-time transmission and download of photos and videos.

4. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 1, characterized in that... In step 3, the image acquisition tools include a total station, a digital camera, and photogrammetric markers; or, the image acquisition tools include a handheld camera with freely adjustable shooting angles.

5. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 1, characterized in that... In step 4, the UAV's route planning includes single waypoint design, route segment design, modification of route or waypoint, connecting waypoints, displaying the aircraft's photography range, route roaming, and obstacle judgment on the route. Single waypoint design includes: selecting a point on the ground in the real-world 3D basic model to determine the planar position of the waypoint; setting the flight altitude of the waypoint, the pitch angle of the camera when taking pictures, the nose turn angle of the aircraft, and whether other actions need to be performed after taking a picture of an image; The flight path design includes: selecting two waypoints on the real-world 3D base model, and setting a flight path between the two waypoints; multiple waypoints need to be inserted within a flight path to ensure the overlap of the images; when the distance between them is too far, more waypoints need to be placed in the flight path between the two waypoints to meet the photography requirements. Modifying routes or waypoints includes: after selecting and setting all waypoints and routes, modifying the routes that have been set according to actual needs; Connecting waypoints involves linking all waypoints according to their positions and logical order. When encountering modified waypoints or added waypoints or flight segments, waypoints are linked based on proximity and altitude from low to high. The display of the aircraft's photographic range includes: calculating the visible range of a single image on the model based on the location of waypoints and the parameters of the photographic design, and displaying it on the model; Flight route roaming includes: roaming the flight route through the designed shooting angles of each waypoint, previewing the shooting range of each waypoint, and determining the overlap between two adjacent images using this method; Obstacle detection on the flight path includes: determining whether there are obstacles on the flight path by judging whether there is an intersection between the flight path and the model; if there are obstacles, feedback is given to the user.

6. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 1, characterized in that... In step 5, the image transmission control system receives the flight path plan, issues and monitors the UAV flight mission, and controls the UAV to fly according to the designed flight path to collect image data at fixed points through the flight control system. The UAV's flight position and attitude information is calculated in real time by adaptively matching four or more pairs of three-dimensional points on the real scene three-dimensional basic model and two-dimensional points on the image, and performing single-image space resection calculation to determine the attitude and position at the time of image capture, and to determine whether the flight position and attitude have reached the preset position.

7. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 6, characterized in that... Visual pose estimation includes: establishing a relationship between the image to be solved and known scene information, matching feature points of the scene's 3D model with feature points of the 2D image; and using spatial resection to solve for the exterior orientation elements of the image based on the correspondence between the 3D and 2D feature points, thereby obtaining the pose of the UAV.

8. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 1, characterized in that, In step 6, after obtaining the image data, the cabin 3D model is reconstructed by solving the image exterior orientation elements, generating dense matching point clouds, constructing triangulation networks, and adaptive data repair. The image exterior orientation elements are obtained by joint adjustment of multi-source data such as flight control information, indoor pose parameters, and camera parameters under various constraints, and local updates are achieved through automatic registration of multi-temporal acquisition data.

9. The method for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor UAV as described in claim 8, characterized in that, Step 6 also includes: By searching for corresponding points of the stereo image pair along the epipolar line constraint relationship, a disparity map of the stereo image pair can be obtained. Then, a large number of corresponding points of the stereo image pair can be calculated from the disparity map, and spatial forward intersection of the corresponding point pairs can be performed to obtain the three-dimensional point cloud of the ship's cabin. After obtaining the point cloud, surface reconstruction is used to estimate the surface indicator function of the model and extract the corresponding isosurface to form a three-dimensional solid model composed of seamless triangular facets from the discrete point cloud. The capacity of the complex closed three-dimensional region is calculated by intersecting the waterline surface with the surface of the three-dimensional model. The final capacity is obtained by considering the calculation of internal components and the tilt correction of the ship under different floating states.

10. A device for measuring the capacity of a ship's liquid cargo tank using a camera mounted on a multi-rotor unmanned aerial vehicle (UAV), characterized in that, It includes: The drone is equipped with a wide-angle zoom camera and a camera gimbal. The flight control and image transmission module is used to establish the flight control system and the image transmission system, and to realize the signal connection between the UAV, server, remote controller and mobile terminal; The ground acquisition and basic model generation module is used to acquire basic images of the cargo hold interior using image acquisition tools, and to build a real-scene 3D basic model for subsequent waypoint selection and flight control. The drone flight path planning module is used to plan the flight path of drones based on a real-world 3D model. The cabin capacity calculation module is used to perform 3D modeling and cabin capacity calculation based on image data collected by UAVs.

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