Transmission line unmanned aerial vehicle line-imitating flight navigation control method and system
By fusing visible light and infrared images, the position of the drone and the flight speed are dynamically predicted, solving the problems of power transmission lines being outside the camera's range and complex flight path planning, thus achieving efficient power transmission line inspection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- STATE GRID INTELLIGENCE TECHNOLOGY CO LTD
- Filing Date
- 2025-07-11
- Publication Date
- 2026-07-28
AI Technical Summary
During the flight simulation, power transmission lines can easily exceed the camera's field of view. Existing technologies have complex methods for planning multiple flight paths and poor recognition results, which affect the subsequent recognition effect.
By fusing visible light and infrared images, the drone's flight control information is obtained, the drone's position is dynamically predicted, and the flight speed of the drone's coordinate system is controlled by combining the azimuth angle of the power transmission line, thus enabling autonomous control of the drone to fly and take pictures simultaneously.
It improves image recognition during drone flight, solves the problem of camera shooting range, simplifies flight path planning, and improves execution efficiency.
Smart Images
Figure CN120742930B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of UAV line simulation technology, and particularly relates to a flight navigation and control method and system for UAV line simulation of power transmission lines. Background Technology
[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.
[0003] Drones are now being used for photographic inspection of power transmission line conductors to identify defects such as broken strands, corrosion, and burns, thereby preventing problems like conductor breaks or increased resistance and overheating. Line-tracking flight differs significantly from traditional detailed inspection. Traditional detailed inspection uses waypoint flight, where the drone flies to a waypoint, adjusts its gimbal, changes its nose angle, takes photos, and then flies to the next waypoint to repeat the process. Line-tracking flight, however, requires the drone's camera to be close to the conductor, continuously photographing the entire conductor while flying. Because power transmission lines are long and have sag, directly applying the route planning methods of traditional detailed inspection to line-tracking flight would result in extremely complex route planning, significantly reducing the efficiency of line-tracking flight operations.
[0004] Currently, in the process of planning flight paths for line-following flight, a starting point and an ending point are usually planned. As the drone flies from the starting point to the ending point, it takes continuous photos with a fixed nose angle and photo interval. However, when photographing power transmission lines with sag, the power transmission lines can easily go beyond the camera's field of view. To avoid the power lines going beyond the camera's field of view, existing technologies use the method of planning multiple flight paths. However, this increases complexity and may even cause the position of the power transmission lines in the image to be inconsistent, affecting the subsequent recognition effect. Summary of the Invention
[0005] To address the technical problems mentioned above, this invention provides a method and system for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines. By fusing visible light images and infrared images, the method acquires flight control information of the UAV, thereby autonomously controlling the UAV to fly and take pictures simultaneously, and completing the inspection of power transmission lines.
[0006] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of the present invention provides a method for unmanned aerial vehicle (UAV) flight navigation and control for power transmission lines.
[0007] A method for unmanned aerial vehicle (UAV) flight navigation and control along a power transmission line, comprising: Based on the coordinates of the power transmission line to be simulated by the UAV, a baseline flight path is planned in advance; On the baseline flight path, the coordinate center position of the detection frame of the power transmission line is determined based on the infrared and visible light images of the power transmission line. Then, the position of the UAV is dynamically predicted based on the changing trend of the coordinate center position of the detection frame of the power transmission line and the changing trend of the slope of the fitted straight line of the power transmission line. The temperature gradient field characteristics within the detection frame of the transmission line are extracted, and the principal direction angle of the transmission line is calculated accordingly. Then, the direction angle of the transmission line is calculated by combining the slope of the fitted straight line of the transmission line. The flight speed of the UAV is controlled on each coordinate axis of the UAV coordinate system based on the direction angle of the power transmission line, the dynamically predicted position of the UAV, and the preset flight speed.
[0008] As one implementation method, the flight velocity value on the X-axis of the UAV coordinate system is: The preset flight speed value and the safe distance between the UAV and the reference flight path are weighted sums of the corresponding adjustment gains.
[0009] As one implementation method, the flight velocity value on the Y-axis of the UAV coordinate system is: ; in, This represents the flight speed value on the Y-axis of the UAV's coordinate system. This represents the lateral deviation of the transmission line in the image. This represents the left and right translation components of the direction angle; , , , These are the proportional gain reference, deviation adaptive coefficient, direction angle compensation coefficient, and differential gain on the Y-axis, respectively.
[0010] As one implementation method, the flight speed value on the Z-axis of the UAV coordinate system is: ; in, This represents the flight speed value on the Z-axis of the UAV's coordinate system. This represents the longitudinal deviation of the transmission line in the image; This represents the vertical translation component of the direction angle; , , , These are the proportional gain reference, deviation adaptive coefficient, orientation angle compensation coefficient, and differential gain on the Z-axis, respectively.
[0011] As one implementation method, the process of determining the coordinate center position of the detection frame of the transmission line is as follows: Both infrared and visible light images of transmission lines are decomposed into corresponding base layer images and detail layer images; The base layer fused image is obtained by fusing the infrared and visible light images of the transmission line using base layer weights. The detail layer images of the infrared and visible light images of the transmission line are fused using detail layer weights to obtain a fused detail layer image. The base layer fused image and the detail layer fused image are directly added together to obtain the fused image; The fused image is processed using a pre-trained target recognition model to obtain the coordinate center position of the detection box of the transmission line and its confidence level.
[0012] In one implementation, the weight of the base layer is determined by the lighting conditions.
[0013] As one implementation method, the detail layer images of the infrared and visible light images of the transmission line are fused based on a detail layer weighting and weighted averaging strategy. The detail layer weights of the infrared and visible light images of the transmission line are as follows:
[0014]
[0015]
[0016] in, i =1,2; For intermediate parameters; Mean filtering; Median filtering; For the detail layer weights of the infrared image of the transmission line; The detail layer weights for the visible light image of the transmission line; These are the pixel coordinates in the image.
[0017] A second aspect of the present invention provides a power transmission line unmanned aerial vehicle (UAV) flight navigation and control system.
[0018] A power transmission line unmanned aerial vehicle (UAV) flight navigation and control system includes: The baseline flight path planning module is used to pre-plan the baseline flight path based on the coordinates of the power transmission line to be imitated by the UAV. The UAV position dynamic prediction module is used to determine the coordinate center position of the detection box of the power transmission line on the reference flight path based on the infrared and visible light images of the power transmission line, and then dynamically predict the UAV position based on the changing trend of the coordinate center position of the detection box of the power transmission line and the changing trend of the slope of the fitted straight line of the power transmission line. The transmission line orientation angle calculation module is used to extract the temperature gradient field characteristics within the detection frame of the transmission line, calculate the main orientation angle of the transmission line accordingly, and then combine it with the slope of the fitted straight line of the transmission line to calculate the orientation angle of the transmission line. The flight speed control module is used to control the flight speed on each coordinate axis of the UAV coordinate system based on the direction angle of the power transmission line, the dynamically predicted position of the UAV, and the preset flight speed.
[0019] A third aspect of the present invention provides a computer-readable storage medium.
[0020] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines.
[0021] A fourth aspect of the present invention provides an unmanned aerial vehicle (UAV).
[0022] A drone includes a drone body, a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the above-described method for controlling the flight navigation of a power transmission line drone.
[0023] Compared with the prior art, the beneficial effects of the present invention are: This invention innovatively proposes a coupling technology for image fusion and UAV flight navigation control along power transmission lines. It solves the problems of power transmission lines easily exceeding the camera's shooting range and poor recognition results when planning multiple flight paths during current line-following flight. Based on a pre-planned baseline flight path, it fuses infrared and visible light images of the power transmission line to determine the coordinate center position of the detection box and dynamically predict the UAV's position. Furthermore, it combines the direction angle of the power transmission line to control the flight speed on each coordinate axis of the UAV's coordinate system, realizing autonomous control of the UAV to take pictures while flying, thus improving the image recognition effect during UAV line-following flight.
[0024] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.
[0026] Figure 1 This is a flowchart of a method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines according to an embodiment of the present invention; Figure 2This is a diagram illustrating the flight navigation and control process of a UAV for power transmission lines according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of a power transmission line unmanned aerial vehicle (UAV) flight navigation control system according to an embodiment of the present invention. Detailed Implementation
[0027] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0028] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0029] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.
[0030] Currently, there are two main methods for power line simulation flights on the market: purely visual and those equipped with lidar. Purely visual flight uses only the drone's visible light camera, utilizing zoom and acquired video frame data, combined with visible light image recognition, to determine the relative position of the power line and the drone, ensuring the power line is centered in the captured image and controlling the drone to fly along the power line. However, this method has significant drawbacks: power lines are mostly silver-gray or black, blending into the ground in the field, and their thinness makes them difficult to identify, especially at night. While lidar-equipped solutions can solve the problem of difficult power line identification, they suffer from high costs, require drones with a certain payload capacity (which is difficult for small, lightweight drones to handle), and significantly reduce flight time, resulting in poor economic efficiency.
[0031] Example 1 Combination Figure 1 and Figure 2 This invention provides a method for unmanned aerial vehicle (UAV) flight navigation and control along power transmission lines, comprising: S101: Based on the coordinates of the power transmission line to be simulated by the UAV, a baseline flight path is planned in advance.
[0032] Pre-planning a baseline flight path ensures that the drone will not deviate from the flight path or collide with obstacles during flight. In well-lit conditions, binocular ranging can be used to measure distances and calculate spatial coordinates. In poorly lit conditions, the beginning and end positions of the flight path need to be manually determined.
[0033] Under sufficient lighting conditions, the drone photographs and identifies the attachment point at the end of the guide wire. Then, the drone retreats a distance of L meters and photographs and identifies the attachment point again. The position coordinates of the captured images are combined with the identification results to establish three-dimensional spatial coordinates. Finally, the attachment point on the other side of the guide wire is photographed and identified, ultimately determining the spatial coordinates of both sides of the guide wire. Finally, a certain displacement is added to the spatial coordinates of the attachment points at the guide wire ends to determine the drone's initial and final flight positions.
[0034] In cases of insufficient light, manual positioning is used to manually set the drone's flight position.
[0035] Let the points where the conductor is attached be A(x1,y1,z1) and B(x2,y2,z2); Let the Z-axis of the three-dimensional coordinate system be vertically upward and positive, and the X-axis and Y-axis be coordinate axes that are perpendicular to each other and parallel to the ground.
[0036] The equation of the parabola in the local coordinate system of the traverse is: , ; in, For horizontal spacing, ; For the elevation difference, ; It is a sag; Global coordinate transformation: Local coordinates ->Global Coordinates The global coordinate formula is:
[0037] It should be noted that the local coordinate system is a temporary coordinate system constructed at point A, and its XZ plane exactly contains the traverse path. The global coordinate system is a three-dimensional coordinate system constructed based on the earth.
[0038] S102: On the reference flight path, the coordinate center position of the detection frame of the power transmission line is determined based on the infrared and visible light images of the power transmission line. Then, the position of the UAV is dynamically predicted based on the changing trend of the coordinate center position of the detection frame of the power transmission line and the changing trend of the slope of the fitted straight line of the power transmission line.
[0039] During line-following flight, the image captured is only a fraction of the length of the conductor. Therefore, the conductor can be approximated as being flush with the branch line in the image, and a straight-line equation can be used. Perform a fitting operation and take the midpoint of the fitted line segment. This serves as a reference point for comparison with the actual flight position of the drone. The direction of the drone's flight is determined by the change in the k (slope) value.
[0040] In practice, the infrared and visible light images of the transmission lines are directly captured by a dual-light camera mounted on a drone, acquiring video image frame data directly through the video stream. In the infrared image, the conductor appears as a continuous bright line due to heating from the current, while the ambient background (sky / vegetation) appears dark due to its lower temperature. The visible light image is used for subsequent identification and spatial coordinate calculation.
[0041] After acquiring infrared and visible light images of the transmission line, preprocessing operations are performed, including dynamic temperature normalization, normalization calculation, and mask-guided CLAHE enhancement.
[0042] The dynamic temperature normalization process is as follows: During flight, the first frame is processed by using the Otsu thresholding method to initially segment the conductor region and obtain the temperature range of the transmission line.
[0043] Dynamic extraction formula: , T wire This is a collection of pixel temperatures for the power transmission line area; the temperature range is updated every 5 frames to adapt to environmental changes.
[0044] Normalized calculation: The transmission line temperature is linearly mapped to the [0,1] interval, and the background region is compressed to a low value.
[0045] The mask-guided CLAHE enhancement process is as follows: Generate binary masks based on the transmission line region for infrared and visible light images. Limit contrast adaptive histogram equalization is applied only within the masked area.
[0046] In the specific implementation process, the process of determining the coordinate center position of the detection frame of the transmission line is as follows: Step a: Decompose both the infrared and visible light images of the transmission line into corresponding base layer images and detail layer images.
[0047] Preprocessed infrared images and visible light images The mean filter is used to decompose the layers into base and detail layers.
[0048]
[0049]
[0050] , Base layer image, This is the formula for calculating the mean filter. After obtaining the base layer, the detail layer image is obtained by comparing the original image with the base layer image.
[0051]
[0052]
[0053] , This is a detail layer image.
[0054] Step b: Use base layer weights to fuse the infrared image and the visible light image of the transmission line into a base layer fused image.
[0055] ; The weights of the base layer are related to the lighting conditions.
[0056] Here, `clamp()` is a general function whose meaning is: , It is a weight that will be used later to determine the proportion of infrared and visible light base layers; It is the average value of the lighting conditions. and These represent conditions with ample sunlight and conditions at night.
[0057] Step c: Use detail layer weights to fuse the detail layer images of the infrared image and the visible light image of the transmission line to obtain the fused detail layer image.
[0058] Among them, the detail layer images of infrared and visible light images of transmission lines are fused based on detail layer weights and a weighted average strategy. The detail layer weights of the infrared and visible light images of the transmission lines are as follows:
[0059]
[0060]
[0061] in, i =1,2; For intermediate parameters; Mean filtering; Median filtering; For the detail layer weights of the infrared image of the transmission line; The detail layer weights for the visible light image of the transmission line; These are the pixel coordinates in the image.
[0062] ; Step d: Directly add the base layer fused image and the detail layer fused image to obtain the fused image; .
[0063] Step e: Process the fused image using a pre-trained target recognition model to obtain the coordinate center position of the detection box of the transmission line and its confidence level.
[0064] For example, using YOLOv8n for lightweight recognition, the coordinate center position of the wire detection box is output. And confidence level.
[0065] S103: Extract the temperature gradient field features within the detection frame of the transmission line, calculate the main direction angle of the transmission line accordingly, and then combine the slope of the fitted straight line of the transmission line to calculate the direction angle of the transmission line.
[0066] Calculate the temperature gradient field within the detection frame: , .
[0067] Calculation of the principal direction angle of the conductor: ; The temperature is highest at the center of the conductor and decreases radially towards the edges.
[0068] S104: Control the flight speed on each coordinate axis of the UAV coordinate system based on the direction angle of the power transmission line, the dynamically predicted position of the UAV, and the preset flight speed.
[0069] Table 1. Definition of UAV coordinate system:
[0070] The average of the guide direction angles of the identified infrared image and the fused image is taken: This yields a real-time changing conductor direction angle. .
[0071] The left and right translation components of the direction angle are: ; The vertical translation components of the orientation angle are: ; In step S104, the flight speed value on the X-axis of the UAV coordinate system is: The preset flight speed value and the safe distance between the UAV and the reference flight path are weighted sums of the corresponding adjustment gains.
[0072] For example, X-axis control (forward and backward movement): ; in, The preset flight speed; The safe distance between the drone and the planned baseline flight path; , Adjustment gain for speed and distance.
[0073] Y-axis control (left and right translation): The flight speed value on the Y-axis of the UAV coordinate system is: ; in, This represents the flight speed value on the Y-axis of the UAV's coordinate system. This represents the lateral deviation of the transmission line in the image. This represents the left and right translation components of the direction angle; , , , These are the proportional gain reference, deviation adaptive coefficient, direction angle compensation coefficient, and differential gain on the Y-axis, respectively.
[0074] Z-axis control (vertical translation): The flight speed value on the Z-axis of the UAV coordinate system is: ; in, This represents the flight speed value on the Z-axis of the UAV's coordinate system. This refers to the longitudinal deviation of the transmission line on the image, i.e.: ; This represents the vertical translation component of the direction angle; , , , These are the proportional gain reference, deviation adaptive coefficient, orientation angle compensation coefficient, and differential gain on the Z-axis, respectively.
[0075] In this embodiment, X-axis control relies on a preset path and real-time positioning to ensure a safe distance between the drone and the tower; YZ-axis control of the drone uses the image center deviation as the main control quantity, with the guide wire direction angle providing auxiliary correction.
[0076] Example 2 like Figure 3 As shown, this embodiment provides a power transmission line unmanned aerial vehicle (UAV) flight navigation and control system, including: The reference flight path planning module 301 is used to pre-plan the reference flight path based on the coordinates of the power transmission line to be imitated by the UAV. The UAV position dynamic prediction module 302 is used to determine the coordinate center position of the detection frame of the power transmission line on the reference flight path based on the infrared and visible light images of the power transmission line, and then dynamically predict the UAV position based on the changing trend of the coordinate center position of the detection frame of the power transmission line and the changing trend of the slope of the fitted straight line of the power transmission line. The transmission line orientation angle calculation module 303 is used to extract the temperature gradient field characteristics within the detection frame of the transmission line, calculate the main orientation angle of the transmission line accordingly, and then combine the slope of the fitted straight line of the transmission line to calculate the orientation angle of the transmission line. The flight speed control module 304 is used to control the flight speed on each coordinate axis of the UAV coordinate system based on the direction angle of the power transmission line, the dynamically predicted position of the UAV, and the preset flight speed.
[0077] It should be noted that each module in this embodiment corresponds one-to-one with each step in Embodiment 1, and their specific implementation processes are the same, so they will not be repeated here.
[0078] Example 3 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the above-described method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines.
[0079] Example 4 This invention provides a drone, including a drone body, a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the above-described method for drone flight navigation and control of power transmission lines.
[0080] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0081] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for unmanned aerial vehicle (UAV) flight navigation and control along a power transmission line, characterized in that, include: Based on the coordinates of the power transmission line to be simulated by the UAV, a baseline flight path is planned in advance; On the baseline flight path, the coordinate center position of the detection frame of the power transmission line is determined based on the infrared and visible light images of the power transmission line. Then, the position of the UAV is dynamically predicted based on the changing trend of the coordinate center position of the detection frame of the power transmission line and the changing trend of the slope of the fitted straight line of the power transmission line. The temperature gradient field characteristics within the detection frame of the transmission line are extracted, and the principal orientation angle of the transmission line is calculated accordingly. Then, combined with the slope of the fitted straight line of the transmission line, the orientation angle of the transmission line is calculated. The orientation angle of the transmission line includes the left and right translation components. and the vertical translation components of the direction angle ; ; ; The conductor orientation angle is the real-time changing angle, which is the average of the conductor orientation angles of the infrared image and the fused image; the conductor orientation angle of the infrared image is the ratio of the temperature gradient field within the detection box in the Y-axis direction to the temperature gradient field within the detection box in the X-axis direction; the conductor orientation angle of the fused image is the arctangent function value of the slope of the fitted straight line of the transmission line. The flight speed on each coordinate axis of the UAV coordinate system is controlled based on the direction angle of the power transmission line, the dynamically predicted position of the UAV, and the preset flight speed. The flight speed value on the X-axis of the UAV coordinate system is: the weighted sum of the preset flight speed value and the safe distance between the UAV and the reference flight path, respectively, and the corresponding adjustment gain; The flight velocity value on the Y-axis of the UAV coordinate system is: ； in, This represents the flight speed value on the Y-axis of the UAV's coordinate system. This represents the lateral deviation of the transmission line in the image. , , , These are the proportional gain reference, deviation adaptive coefficient, orientation angle compensation coefficient, and differential gain on the Y-axis, respectively. The flight speed value on the Z-axis of the UAV coordinate system is: ； in, This represents the flight speed value on the Z-axis of the UAV's coordinate system. This represents the longitudinal deviation of the transmission line in the image; , , , These are the proportional gain reference, deviation adaptive coefficient, orientation angle compensation coefficient, and differential gain on the Z-axis, respectively.
2. The method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines as described in claim 1, characterized in that, The process of determining the coordinate center position of the detection frame for a transmission line is as follows: Both infrared and visible light images of transmission lines are decomposed into corresponding base layer images and detail layer images; The base layer fused image is obtained by fusing the infrared and visible light images of the transmission line using base layer weights. The detail layer images of the infrared and visible light images of the transmission line are fused using detail layer weights to obtain a fused detail layer image. The base layer fused image and the detail layer fused image are directly added together to obtain the fused image; The fused image is processed using a pre-trained target recognition model to obtain the coordinate center position of the detection box of the transmission line and its confidence level.
3. The method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines as described in claim 2, characterized in that, The weights of the base layer are determined by the lighting conditions.
4. The method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines as described in claim 2, characterized in that, The detail layer images of the transmission line are fused based on a detail layer weighting and weighted averaging strategy. The detail layer weights of the infrared and visible light images of the transmission line are as follows: in, i =1,2; For intermediate parameters; Mean filtering; Median filtering; For the detail layer weights of the infrared image of the transmission line; The detail layer weights for the visible light image of the transmission line; These are the pixel coordinates in the image.
5. A power transmission line unmanned aerial vehicle (UAV) flight navigation and control system, characterized in that, The method for unmanned aerial vehicle (UAV) flight navigation and control of power transmission lines as described in any one of claims 1-4 includes: The baseline flight path planning module is used to pre-plan the baseline flight path based on the coordinates of the power transmission line to be imitated by the UAV. The UAV position dynamic prediction module is used to determine the coordinate center position of the detection box of the power transmission line on the reference flight path based on the infrared and visible light images of the power transmission line, and then dynamically predict the UAV position based on the changing trend of the coordinate center position of the detection box of the power transmission line and the changing trend of the slope of the fitted straight line of the power transmission line. The transmission line orientation angle calculation module is used to extract the temperature gradient field characteristics within the detection frame of the transmission line, calculate the main orientation angle of the transmission line accordingly, and then combine it with the slope of the fitted straight line of the transmission line to calculate the orientation angle of the transmission line. The flight speed control module is used to control the flight speed on each coordinate axis of the UAV coordinate system based on the direction angle of the power transmission line, the dynamically predicted position of the UAV, and the preset flight speed.
6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the transmission line UAV line-following flight navigation control method as described in any one of claims 1-4.
7. A drone, comprising a drone body, a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the transmission line UAV line-following flight navigation control method as described in any one of claims 1-4.