A method and system for automatically selecting tracking channels for unmanned aerial vehicle-mounted laser radar

Abstract

The present invention provides a method and system for automatically selecting tracking channels for a drone-mounted laser radar. The method includes calculating the drone's flight distance and direction based on real-time drone pose information; extracting information about all power line channels and towers in the drone's flight direction; calculating the minimum flight distance and flight angle between the drone and all power line channels based on the information about all power line channels and towers; selecting the drone's initial frame tracking channel based on the minimum flight distance and flight angle; calculating the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel based on current frame point cloud data; and calculating a score for each power line channel according to a predetermined channel scoring formula, selecting the power line channel with the highest score as the drone's current frame tracking channel. The technical solution of the present invention can solve the problems in the prior art of automatically selecting tracking channels for simulated lines and continuously tracking channels.

Description

Technical Field

[0001] The present invention relates to the field of laser radar technology, and in particular to a method and system for automatically selecting a tracking channel for a laser radar carried by an unmanned aerial vehicle. Background Art

[0002] Automated power line inspections using drone-mounted LiDAR can effectively reduce workload, improve intelligence, and facilitate stable inspections. However, a key challenge facing automated power line inspections using drone-mounted LiDAR is how to automatically select and continuously track a specific line after the drone initiates a line tracking operation, allowing for continuous flight according to the user's preferences.

[0003] In real-world scenarios, drones can be launched from above arbitrary power lines, often with multiple lines below them, and each line channel may contain multiple power lines. For example, if multiple distribution lines are adjacent to each other in a distribution network power channel, or if multiple distribution lines diverge near a bifurcation, launching a drone to track the line presents the problem of line selection. In main network scenarios, even if there is only a single line channel, identifying and tracking the lines on both sides of the channel is an inevitable problem that needs to be solved. This is especially true when there are multiple parallel lines on the main network or when the main network distribution network coexists, making it significantly more difficult to automatically and correctly select the desired line. Furthermore, after the initial line selection, how to continuously follow the current channel according to the user's flight intentions is also a problem that needs to be solved. Summary of the Invention

[0004] The present invention provides an automatic tracking channel selection solution for a UAV-mounted laser radar, aiming to solve the problem in the prior art that it is difficult to automatically and correctly select the power line channel required for UAV flight tracking.

[0005] To solve the above problem, according to a first aspect of the present invention, a method for automatically selecting a tracking channel for a UAV-mounted laser radar is proposed, comprising:

[0006] Calculate the flight distance and direction of the drone based on the real-time acquired drone posture information;

[0007] According to the flight distance and direction of the UAV, all power line channels and tower information in the UAV's flight direction are extracted from the LiDAR point cloud data;

[0008] Based on the information of all power line channels and towers, the minimum flight distance and flight angle between the drone and all power line channels are calculated respectively;

[0009] Select the initial frame tracking channel of the UAV from all power line channels according to the minimum flight distance and flight angle;

[0010] When the drone continues to fly, the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel in all power line channels in the drone's flight direction are calculated based on the current frame point cloud data;

[0011] The minimum channel distance and channel angle are used to calculate the score of each power line channel according to the predetermined channel scoring formula, and the power line channel with the highest score is selected as the current frame tracking channel of the drone.

[0012] Preferably, the above-mentioned automatic tracking channel selection method further includes, after the step of selecting the initial frame tracking channel of the drone from all power line channels: acquiring the current frame point cloud data in real time, and verifying the initial frame tracking channel based on all power line channels and tower information in the drone's flight direction extracted from the current frame point cloud data; the step of verifying the initial frame tracking channel includes:

[0013] Based on the information of all power line channels and towers, the minimum flight distance and flight angle between the drone and all power line channels are calculated respectively;

[0014] According to the minimum flight distance and flight angle, the current frame tracking channel of the UAV is selected from all power line channels for a predetermined number of times;

[0015] Determine whether the current frame tracking channel selected for a predetermined number of consecutive times is consistent with the initial frame tracking channel;

[0016] If the current frame tracking channel is consistent with the initial frame tracking channel, the drone is controlled to continue flying along the initial frame tracking channel;

[0017] If the current frame tracking channel is inconsistent with the initial frame tracking channel, the most recently selected current frame tracking channel will be used as the initial frame tracking channel to control the drone to continue flying.

[0018] Preferably, in the above-mentioned method for automatically selecting a tracking channel, the step of calculating the flight distance and flight direction of the drone based on the real-time acquired drone posture information includes:

[0019] According to the UAV's position information, obtain the first position coordinates of the UAV at the current moment;

[0020] Obtaining, based on the posture information of the drone, a second position coordinate of the drone at a first predetermined time interval;

[0021] Calculate the flight distance and flight direction of the UAV using the first position coordinate and the second position coordinate according to the flight distance calculation formula and the flight direction calculation formula respectively;

[0022] Determining whether the flight distance of the drone is greater than or equal to a predetermined distance interval threshold;

[0023] If the flight distance is greater than or equal to the predetermined distance interval threshold, the UAV is determined to be in a normal flight state;

[0024] If the flight distance is less than the predetermined distance interval threshold, the second position coordinate of the UAV is updated to the first position coordinate, and the flight distance and flight direction of the UAV are recalculated after a predetermined time interval until the flight distance of the UAV is greater than or equal to the predetermined distance interval.

[0025] Preferably, the above-mentioned method for automatically selecting a tracking channel further comprises, after the step of determining that the drone is in a normal flight state:

[0026] Obtaining a third position coordinate of the drone at a second predetermined time interval based on the posture information of the drone;

[0027] According to the flight direction calculation formula, the second position coordinate and the third position coordinate are used to calculate the flight direction of the drone respectively;

[0028] Determine whether the flight angle between the UAV's flight direction and the previous flight direction is less than a predetermined angle deviation threshold;

[0029] If the flight angle is less than a predetermined angle deviation threshold, the UAV flight is determined to be stable, and the step of extracting all power line channels and tower information in the UAV flight direction from the lidar point cloud data based on the UAV flight distance and flight direction is performed;

[0030] If the flight angle is greater than or equal to the predetermined angle deviation threshold, the drone flight is determined to be unstable, the drone's flight direction is recalculated, and it is determined whether the drone's flight angle is less than the predetermined angle deviation threshold until the drone flight is stable or the drone's current flight is terminated.

[0031] Preferably, in the above-mentioned tracking channel automatic selection method, the step of calculating the minimum flight distance and flight angle between the drone and all power line channels based on all power line channels and tower information includes:

[0032] Extract the power line channel and tower information along the UAV's flight direction, and calculate the power line equation of each power line in the power line channel based on the power line channel and tower information;

[0033] For each of all power line channels, calculate the two-dimensional and three-dimensional distances between all power lines in the power line channel and the current flight position of the UAV according to the power line straight line equation;

[0034] The minimum two-dimensional distance and the minimum three-dimensional distance are selected from the two-dimensional and three-dimensional distances between all power lines in the power line channel and the current flight position of the UAV as the minimum flight distance between the UAV and the power line channel;

[0035] According to the power line equation of each power line in the power line channel, the average direction of all power line channels is calculated;

[0036] Using the average direction of all power line channels and the flight direction of the UAV, the flight angles between the UAV and all power line channels are calculated according to the vector angle calculation formula.

[0037] Preferably, in the above-mentioned automatic tracking channel selection method, the step of calculating the power line straight line equation of each power line in the power line channel according to the power line channel and tower information includes:

[0038] Extracting power line channel and tower information along the flight direction of the UAV, wherein the power line channel and tower information includes the coordinates of tower points in each power line channel among all power line channels in the flight direction;

[0039] Use the RANSAC algorithm to select the coordinates of the tower points corresponding to each power line in the power line channel;

[0040] Use the tower point coordinates to calculate the fitted center line of each power line;

[0041] The fitting center line is corrected according to the distance between the coordinates of other tower points in each power line and the fitting center line, and the power line straight line equation of each power line in the power line channel is obtained.

[0042] Preferably, the above-mentioned tracking channel automatic selection method includes the steps of selecting the initial frame tracking channel of the drone from all power line channels according to the minimum flight distance and the flight angle:

[0043] Determine whether the channel deviation angle between the minimum flight angle and the second minimum flight angle among the flight angles between the drone and all power line channels is greater than or equal to a predetermined angle threshold;

[0044] If the channel deviation angle is greater than or equal to the predetermined angle threshold, the power line channel corresponding to the minimum flight angle is selected as the initial frame tracking channel of the UAV;

[0045] If the channel deviation angle is less than the predetermined angle threshold, the weighted distance of each power line channel is calculated based on the distance weights corresponding to the minimum flight distance between the drone and all power line channels, the minimum two-dimensional distance, and the minimum three-dimensional distance of each power line channel;

[0046] The power line channel with the smallest weighted distance is selected as the initial tracking channel for the UAV.

[0047] Preferably, the above-mentioned method for automatically selecting tracking channels includes the step of calculating the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel in all power line channels in the flight direction of the drone:

[0048] Calculating an average straight line equation for each power line channel based on the straight line equations of all power lines in each power line channel;

[0049] Calculate the average straight line equation of the tracking channel of the previous frame according to the straight line equations of all power lines in the tracking channel of the previous frame;

[0050] Using the average straight line equation of each power line channel and the average straight line equation of the tracking channel of the previous frame, the channel angle between each power line channel and the tracking channel of the previous frame is calculated;

[0051] and, selecting a plurality of calculation points from each of all the power lines;

[0052] According to the power line straight line equation of each power line in the previous frame tracking channel, the point-line distances from multiple calculation points to each power line in the previous frame tracking channel are calculated;

[0053] The average distance between each power line in the power line channel and each power line in the previous frame tracking channel is calculated;

[0054] Select the shortest average distance from the average distances corresponding to each power line in the power line channel as the shortest line distance from each power line in the power line channel to the tracking channel of the previous frame;

[0055] The minimum value is selected from the shortest line distances as the minimum road distance between the power line channel and the tracking channel of the previous frame.

[0056] Preferably, the above-mentioned automatic tracking channel selection method uses the minimum channel distance and channel angle to calculate the score of each power line channel according to a predetermined channel scoring formula, and the steps of selecting the power line channel with the highest score as the current frame tracking channel of the drone include:

[0057] For all power line channels in the UAV's flight direction, sort the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel, and obtain the maximum minimum channel distance and maximum channel angle corresponding to each power line channel;

[0058] According to the predetermined channel score calculation formula:

[0059] S d =int((D max -D i) / d)*B d

[0060] S θ =int((θ max -θ i ) / d)*B θ

[0061] S total =S d +S θ

[0062] The scores of each power line channel are calculated separately, where S total is the overall score of the power line channel, S d is the minimum channel distance score, S θ Channel angle score, D max is the maximum value of the minimum channel distance, D i is the minimum channel distance, θ max is the maximum channel angle, θ i is the channel angle, d and τ are the distance step and angle step respectively, B d and B θ are the fractions corresponding to the distance step and angle step respectively;

[0063] The power line channel with the highest score is selected as the current frame tracking channel of the UAV.

[0064] According to a second aspect of the present invention, the present invention further provides a tracking channel automatic selection system for an unmanned aerial vehicle (UAV)-mounted laser radar, comprising:

[0065] A memory, a processor, and a tracking channel automatic selection program for an unmanned aerial vehicle laser radar stored in the memory and running on the processor. When the tracking channel automatic selection program is executed by the processor, the steps of the tracking channel automatic selection method described in any of the above technical solutions are implemented.

[0066] In summary, the automatic tracking channel selection scheme for the drone-mounted laser radar provided by the present invention calculates the flight distance and flight direction of the drone based on the real-time acquired drone posture information, and then extracts all power line channels and tower information in the flight direction of the drone based on the above-mentioned flight distance and flight direction of the drone. Then, based on all the above-mentioned power line channels and tower information, the minimum flight distance and flight angle between the drone and all power line channels can be calculated. The minimum flight distance reflects the distance between the drone and the power line channel. Because the flight angle reflects the deviation angle between the drone and the power line channel, the above-mentioned minimum flight distance and flight angle can be used to select the initial frame tracking channel of the drone from all power line channels, and the drone can be controlled to fly along the initial frame tracking channel to realize automatic data collection of the channel. When the UAV continues to fly, the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel in all power line channels in the UAV flight direction are calculated based on the current frame point cloud data. The minimum channel distance reflects the shortest distance between each current power line channel and the previous frame tracking channel, and the channel angle reflects the deviation angle between each current power line channel and the previous frame tracking channel. Therefore, under the premise of determining that the previous frame tracking channel is correct, the minimum channel distance and channel angle can be used to evaluate the distance and angle deviation between each power line channel in the current frame and the previous frame tracking channel. Here, a predetermined channel scoring formula is used to evaluate the above distance and angle deviation to obtain a score for each power line channel. The higher the score, the smaller the distance and angle deviation. At this time, the power line channel with the highest score is selected as the current frame tracking channel of the UAV, which can realize the automatic correct selection of the simulation line channel. The current frame tracking channel with the smallest deviation is selected according to the previous frame tracking channel, and finally the line direction is determined, thereby realizing automatic channel selection of the simulation line and automatic inspection of the channel line.

[0067] In summary, this solution uses drone lidar technology to inspect power lines. The drone's position and orientation within the scene are determined based on the direction and position of the flight at startup. Point cloud data from the drone's onboard lidar is used to extract information about power line channels and towers. This information is then comprehensively compared with the direction and position of the lines below the drone. A score is calculated for each channel, and the channel with the highest score is selected. In this calculation, the channel with the smallest angle to the flight direction and closest position has the highest score, while the channel with the lowest score has the lowest score. Finally, the selected channel is verified, and the final direction is determined after selecting the same line direction twice in a row. This process ultimately enables automatic channel selection and line inspection based on line simulation. Furthermore, based on the drone's flight status and the user's flight intent, the corresponding channel is selected for automated inspection and continuous tracking. No human interaction is required during flight, enhancing the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0069] Figure 1 This is a flow chart of a method for automatically selecting a tracking channel for a UAV-mounted laser radar provided by an embodiment of the present invention;

[0070] Figure 2 yes Figure 1 The illustrated embodiment provides a flow chart of a method for calculating the flight distance and flight direction of a UAV;

[0071] Figure 3 yes Figure 2 A schematic flow chart of a method for determining the flight distance of a UAV provided in the illustrated embodiment;

[0072] Figure 4 yes Figure 1 The illustrated embodiment provides a flow chart of a method for calculating the minimum flight distance and flight angle of a UAV;

[0073] Figure 5 yes Figure 4 A schematic flow chart of a method for calculating a power line equation of a power line provided by the illustrated embodiment;

[0074] Figure 6 yes Figure 1 A flowchart of a method for selecting an initial frame tracking channel for a drone provided by the illustrated embodiment;

[0075] Figure 7 1 is a flow chart of a method for verifying an initial frame tracking channel provided by an embodiment of the present invention;

[0076] Figure 8 yes Figure 1 A schematic flow chart of a method for calculating a minimum channel distance and a channel angle provided by the illustrated embodiment;

[0077] Figure 9 yes Figure 1 The illustrated embodiment provides a flow chart of a method for selecting a current frame tracking channel of a drone;

[0078] Figure 10 This is a structural diagram of an automatic tracking channel selection system for an unmanned aerial vehicle (UAV)-mounted laser radar provided by an embodiment of the present invention.

[0079] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0080] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0081] The main technical problems solved by the embodiments of the present invention are:

[0082] Drones can be launched above any power line, often with multiple power lines below them. Each power line may contain multiple power lines. For example, if multiple power lines are adjacent to each other within a distribution network power line channel, or if multiple power lines diverge near a power line bifurcation, launching a drone to track the line poses a problem. In main network scenarios, even with a single power line channel, identifying and tracking the lines on both sides of the channel is an unavoidable challenge.

[0083] To address the aforementioned issues, the following embodiment of the present invention provides a solution for automatically selecting tracking channels for drone-mounted laser radar (LiDAR). This solution utilizes drone-mounted LiDAR technology to inspect power lines. The drone's position and orientation within the channel inspection scenario are determined based on the drone's flight direction and position at startup. After extracting power line channel and tower information from the drone's LiDAR point cloud data, a comprehensive comparison of direction and position with the underlying lines is performed. A score is calculated for each power line channel, and the channel with the highest score is selected. In the score calculation process for all power line channels in the flight direction, the channel with the smallest angle to the drone's flight direction and closest position receives the highest score; conversely, the channel with the smallest angle to the drone's flight direction receives the lowest score. Finally, the selected power line channel is verified, and the final direction is determined after the same line direction is selected twice in a row. This process achieves the goal of automatic channel selection and line inspection based on line simulation. This allows the drone to select the appropriate channel for automated inspection and continuous tracking based on the drone's flight status and the user's flight intent. Furthermore, no human interaction is required during unmanned flight, significantly improving the user experience.

[0084] To achieve the above purpose, see Figure 1 , Figure 1 The following is a flow chart of a method for automatically selecting a tracking channel for a drone-mounted laser radar provided by an embodiment of the present invention. Figure 1 As shown, the automatic tracking channel selection method of the UAV-mounted laser radar includes:

[0085] S110: Calculate the flight distance and direction of the drone based on the real-time acquired drone pose information. Drones are typically equipped with a POS system (Position and Orientation System) that can acquire pose information (inertial navigation pose and GNS position). This pose information, i.e., the drone's pose and GNS position, can be used to calculate the drone's flight distance and direction. This pose information is acquired in real time upon startup.

[0086] Specifically, as a preferred embodiment, Figure 2 As shown, the above step S110: the step of calculating the flight distance and flight direction of the drone based on the real-time acquired drone posture information includes:

[0087] S111: Obtain the first position coordinates of the drone at the current moment based on the drone's posture information. Utilize the POS system carried by the drone to obtain the drone's position P1 at the current moment. The first position coordinates of the drone are set to (X1, Y1, Z1).

[0088] S112: Based on the UAV's position information, obtain the second position coordinates of the UAV at a first predetermined time interval. Set the first predetermined time interval dt, and after the interval dt, obtain the second position coordinates P2 (X2, Y2, Z2) of the UAV at the current moment.

[0089] S113: Calculate the flight distance and flight direction of the UAV using the first position coordinates and the second position coordinates according to the flight distance calculation formula and the flight direction calculation formula.

[0090] Taking the first position coordinate (X1, Y1, Z1) and the second position coordinate P2 (X2, Y2, Z2) as an example, calculate the flight distance and flight direction of the drone after the interval dt. The flight distance s and flight direction The calculation formula is as follows:

[0091]

[0092]

[0093] S114: Determine whether the flight distance of the UAV is greater than or equal to a predetermined distance interval threshold.

[0094] S115: If the flight distance is greater than or equal to the predetermined distance interval threshold, it is determined that the UAV is in a normal flight state.

[0095] S116: If the flight distance is less than the predetermined distance interval threshold, the second position coordinate of the UAV is updated to the first position coordinate, and the process returns to step S112. The flight distance and flight direction of the UAV are then recalculated after a predetermined time interval until the flight distance of the UAV is greater than or equal to the predetermined distance interval.

[0096] Set a predetermined interval distance threshold δ. When the flight distance s of the UAV is greater than or equal to δ, if the interval distance is large enough, it indicates that the UAV is in a normal flight state. At this time, the flight direction of the UAV is calculated more accurately (i.e. The calculation is accurate), and there will be no large fluctuations due to a small flight distance; on the contrary, it means that the drone is not in a suitable flight state at this time (for example, flying too slowly or in a hovering state), and it is not suitable to calculate the flight direction at this time, so the current position P2 is updated to P1, that is, the current second position coordinate is used as the initial first position coordinate P1, and the above steps of calculating the drone's flight distance and flight direction are repeated after a predetermined time interval to determine whether the drone's flight distance is greater than or equal to the predetermined distance interval threshold, until the drone's flight distance meets the requirements and the final flight direction is calculated.

[0097] After calculating the drone's flight distance and direction and confirming it's in normal flight, it's necessary to verify its flight stability. If the drone is stable, it's controlled to continue flying, extracting information about all power line channels and towers in its flight direction. If the drone fails to achieve a stable flight for an extended period of time, such as duration T, the flight direction estimation is considered a failure, and the flight is terminated.

[0098] Specifically, as a preferred embodiment, Figure 3 As shown, after determining that the drone is in a normal flight state, the following steps are also included:

[0099] S1141: Acquire the third position coordinates of the drone within a second predetermined time interval based on the posture information of the drone.

[0100] S1142: Calculate the flight direction of the UAV using the second position coordinate and the third position coordinate according to the flight direction calculation formula.

[0101] S1143: Determine whether the flight angle between the UAV's flight direction and the previous flight direction is less than a predetermined angle deviation threshold.

[0102] S1144: If the flight angle is less than the predetermined angle deviation threshold, the UAV flight is determined to be stable, and the step of extracting all power line channels and tower information in the UAV flight direction from the lidar point cloud data according to the UAV flight distance and flight direction is executed.

[0103] S1145: If the flight angle is greater than or equal to the predetermined angle deviation threshold, the UAV flight is determined to be unstable, the flight direction of the UAV is recalculated, and it is determined whether the flight angle of the UAV is less than the predetermined angle deviation threshold until the UAV flight is stable or the UAV flight is terminated.

[0104] In the technical solution provided by the embodiments of the present invention, upon determining that the drone is in normal flight, the drone's flight stability is verified. Specifically, a new third position coordinate, P3, and other positions are calculated based on the drone's position information to determine whether the drone is stable. After determining the second position coordinate, P2, the drone continues flight, starting from P2. After an interval time dt, the current third position coordinate, P3, is obtained, and the drone's flight direction is calculated using the formula in the above steps. A predetermined angle deviation threshold α is set for the drone's flight direction. If the angle between the drone's flight direction and the previously estimated direction is less than the predetermined angle deviation threshold α, the drone's flight direction is essentially stable, and the current result can be adopted. Otherwise, the drone's flight is unstable, possibly indicating that the pilot is performing a turn or other maneuver, making it unsuitable for route selection. The above steps of calculating the drone's position coordinates and determining whether the flight distance is greater than or equal to the predetermined distance interval threshold and whether the flight angle is less than the predetermined angle deviation are repeated until the drone's flight is stable. The maximum time allowed for the above direction estimation process is set to T. If the drone still cannot fly stably after the duration T reaches T, the direction estimation is determined to have failed, the next step is discontinued, and the drone's flight is terminated.

[0105] After confirming that the UAV is in normal and stable flight state, it is necessary to extract the power line channel and tower information along the flight direction of the UAV calculated in step S110, and then select the initial frame line channel. Figure 1 The technical solution provided in the illustrated embodiment further includes the following steps after calculating the flight distance and flight direction of the drone:

[0106] S120: According to the flight distance and flight direction of the UAV, extract all power line channels and tower information in the UAV flight direction from the point cloud data of the lidar.

[0107] By extracting information about all power line channels and towers in the drone's flight direction from the LiDAR point cloud data, the power line channel equation and tower point cloud are obtained. Each power line channel may have multiple power lines depending on the line scenario; for example, a 10kV distribution network typically has three power lines. After obtaining information about all power line channels and towers, specifically the power line equations for each power line in the channel, the minimum flight distance and angle between the drone and each power line channel are calculated based on this information. This determines the power line channel closest to the drone with the smallest directional deviation, allowing for the selection of the initial frame tracking channel.

[0108] S130: Based on the information of all power line channels and towers, the minimum flight distance and flight angle between the drone and all power line channels are calculated. The minimum flight distance is the minimum distance between the drone and all power line lines in each power line channel, which reflects the distance between the drone and the power line channel. The flight angle is the angle between the drone and each power line channel, which reflects the deviation angle between the drone and the power line channel. Therefore, by calculating the minimum flight distance and flight angle between the drone and each power line channel, the initial frame tracking channel of the drone can be selected from all power line channels within the current flight direction and flight distance range of the drone.

[0109] Specifically, as a preferred embodiment, Figure 4 As shown, the steps of calculating the minimum flight distance and flight angle between the UAV and all power line channels based on all power line channels and tower information include:

[0110] S131: Extract power line channel and tower information along the UAV's flight direction, and calculate the power line equation for each power line in the power line channel based on the power line channel and tower information. Typically, within a certain distance range and direction, a power line channel appears as a straight line. Therefore, assuming that each power line channel and power line is a straight line, the power line equation for each power line in the power line channel can be calculated. This power line equation can typically be estimated by fitting a point cloud using the RANSAC method, facilitating line extraction.

[0111] S132: For each of all power line channels, calculate the two-dimensional and three-dimensional distances between all power lines in the channel and the UAV's current flight position based on the power line equations. Specifically, select a power line channel and traverse all power lines in the channel. Calculate the 2D and 3D distances from the current UAV's position P to the power line equations calculated for each power line. The 2D distance is the horizontal distance, while the 3D distance is the distance in three dimensions, including both horizontal and vertical distances.

[0112] S133: Selecting a minimum two-dimensional distance and a minimum three-dimensional distance from the two-dimensional and three-dimensional distances between all power lines in the power line channel and the current flight position of the UAV as the minimum flight distance between the UAV and the power line channel.

[0113] Specifically, a power line channel is selected and all power lines in the power line channel are traversed. The 2D distance and 3D distance from the current UAV's position coordinate P to the power line straight line equation of each power line calculated above are calculated, and the minimum value of all 2D and 3D distances are calculated respectively. The minimum flight distance between the UAV and the power line channel can be obtained. The minimum flight distance includes the minimum two-dimensional distance d1 and the minimum three-dimensional distance d2. Among them, the 2D distance is the horizontal distance, and the 3D distance is the three-dimensional distance, including calculations in the horizontal and vertical directions. The equation of the power line mentioned above is a straight line equation, which is a mathematical expression of the actual line. Here, the power line straight line equation can be used to determine the distance relationship between the UAV and the line position, so that the pilot can stay close to the initially tracked line channel and stay away from other interfering line channels during the initial tracking.

[0114] S134: Calculate the average direction of all power line channels based on the power line equation of each power line in the power line channel. For each power line channel, average the power line equations of all power lines in the power line channel to obtain the average direction of each power line channel.

[0115] S135: Using the average direction of all power line channels and the flight direction of the drone, the flight angles between the drone and all power line channels are calculated according to the vector angle calculation formula. Because the equations of all power line lines in the power line channels are directional, the flight angle between the average direction of the power line channels and the flight direction of the drone can be calculated using the vector angle calculation formula.

[0116] The technical solution provided by the embodiment of the present invention selects a power line channel and traverses all power lines in the power line channel to calculate the 2D distance and 3D distance from the current position coordinate P of the drone to the equation of each power line line, and calculates the minimum value of all 2D distances and 3D distances respectively, so as to obtain the above-mentioned minimum two-dimensional distance d1 and minimum three-dimensional distance d2 respectively. In addition, the flight angle between all power line channels and the current flight direction is calculated. By selecting a power line channel as the current channel, the average direction of all power lines in the current channel can be calculated, and then all power line channels in the flight direction of the drone are traversed (usually all power line channels within a predetermined angle range of the straight line in which the drone's flight direction is located are selected), and the flight angle between each power line channel and the current flight direction of the drone is calculated. In real scenarios, especially in distribution network environments, the power lines in the same power line channel may have a certain angle deviation and are not strictly parallel. Therefore, calculating the average direction of the line channel is useful to improve stability and thus unify the line direction.

[0117] Among them, as a preferred embodiment, Figure 5 As shown, the above step S131: the step of calculating the power line straight line equation of each power line in the power line channel according to the power line channel and tower information includes:

[0118] S1311: Extracting power line channel and tower information along the flight direction of the UAV, wherein the power line channel and tower information includes the coordinates of tower points in each power line channel in all power line channels in the flight direction.

[0119] S1312: Use the RANSAC algorithm to select the tower point coordinates corresponding to each power line in the power line channel.

[0120] S1313: Calculate the fitting center line of each power line using the tower point coordinates;

[0121] S1314: Correcting the fitted center line according to the distances between the coordinates of other tower points in each power line and the fitted center line, and obtaining a power line straight line equation for each power line in the power line channel.

[0122] The RANSAC algorithm is an optimal algorithm for fitting straight lines, because there are a large number of pole tower point coordinates in each power line channel, and these pole tower point coordinates belong to multiple power lines. In this way, each power line will have its own pole tower point. In this way, the RANSAC algorithm is used to select the pole tower point coordinates corresponding to each power line from the pole tower point coordinates of each power line. The center line of the power line can be fitted using the above-mentioned pole tower point coordinates. When the distance between the coordinates of other pole tower points on the power line and the fitted center line reaches the minimum, it can be determined that there are a large number of pole tower point coordinates of the power line on the fitted center line, that is, the power line straight line equation of the power line is obtained by fitting. In this way, the power line straight line equations of all power lines in the current power line channel can be obtained, and then the power line straight line equations of all power line channels can be obtained.

[0123] Figure 1 The technical solution provided by the embodiment shown, after respectively calculating the minimum flight distance and flight angle between the drone and all power line channels, it is also necessary to select the line channel closest to the drone according to the above minimum flight distance and flight angle as the drone's tracking channel. Specifically, Figure 1 The technical solution provided by the illustrated embodiment also includes:

[0124] S140: Select the initial frame tracking channel of the UAV from all power line channels based on the minimum flight distance and flight angle; this application requires selecting the power line channel with the smallest angle or the closest distance from all power line channels in the current flight direction of the UAV as the initial frame tracking channel of the UAV.

[0125] Specifically, as a preferred embodiment, Figure 6 As shown, the steps of selecting the initial frame tracking channel of the UAV from all power line channels according to the minimum flight distance and the flight angle include:

[0126] S141: Determine whether the channel deviation angle between the minimum flight angle and the second smallest flight angle among the flight angles between the UAV and all power line channels is greater than or equal to a predetermined angle threshold. The present invention calculates the corresponding flight angle and flight distance for each line channel and sorts them, so as to give priority to the channel with the smallest angle. By using a predetermined angle threshold (usually selected based on an empirical value, usually set at around 10-15 degrees), it is determined whether the channel deviation angle between the minimum flight angle and the second smallest flight angle is greater than or equal to the predetermined angle threshold, so as to determine whether the current power line channel is the initial tracking channel of the UAV.

[0127] S142: If the channel deviation angle is greater than or equal to a predetermined angle threshold, the power line channel corresponding to the minimum flight angle is selected as the initial frame tracking channel for the UAV. If the channel deviation angle between the minimum flight angle and the next smallest flight angle exceeds the predetermined angle threshold, the currently selected minimum angle channel is deemed to be significantly distinguishable from the other channels and is directly selected as the initial frame tracking channel for the UAV.

[0128] Conversely, if the minimum angle difference between the drone's flight angles and multiple powerline channels is within the angle threshold, the channels are considered approximately parallel. In this case, the powerline channels cannot be selected based solely on the flight angle; distance must be considered for differentiation. For example, if the flight direction is 30 degrees, channel A is 40 degrees, and channel B is 43 degrees, it is impossible to determine whether to select A or B. Although channel A is closer at 40 degrees, B may be the correct choice.

[0129] When the power line channels have equal selection weights, the channel with the current minimum angle does not have significant discrimination ability. At this time, the weighted distance of each power line channel is calculated based on the distance weight of the minimum flight distance between the UAV and the power line channel, thereby screening the initial tracking channel for the UAV.

[0130] S143: If the channel deviation angle is less than the predetermined angle threshold, the weighted distance of each power line channel is calculated according to the distance weights corresponding to the minimum flight distance between the UAV and all power line channels, the minimum two-dimensional distance, and the minimum three-dimensional distance of each power line channel.

[0131] S144: Select the power line channel with the smallest weighted distance as the initial tracking channel for the UAV.

[0132] In the technical solution provided by the embodiment of the present invention, the flight angle and minimum flight distance calculated for each line channel are sorted, and the power line channel with the smallest flight angle is preferentially selected. An angle threshold β is set. If the angle threshold β is exceeded, the power line channel corresponding to the smallest angle is selected. This allows the remaining power line channels to be significantly distinguished. If the channel deviation angle between the smallest flight angle and the channel with the next smallest flight angle exceeds the predetermined angle threshold β, the power line channel corresponding to the currently selected lowest flight angle is considered to be able to significantly distinguish the remaining channels and is directly selected as the initial frame tracking channel.

[0133] On the contrary, if there are multiple power line channels whose flight angles are within the predetermined angle threshold from the channel deviation angle of the minimum flight angle, then these channels are considered to have equal selection weights, and the channel with the current minimum angle does not have significant distinguishing ability. At this time, the weighted distance is calculated using the distance from the channel to the drone (including the above-mentioned minimum two-dimensional distance and minimum three-dimensional distance), and these channels with equal selection weights are further distinguished. Set the weight of the 2D distance to ω1 and the weight of the 3D distance to ω2, and both satisfy ω1+ω2=1. Calculate the weighted distance of each power line channel and select the power line channel with the smallest weighted distance as the current frame tracking channel.

[0134] After obtaining the current frame tracking channel, the tracking channel needs to be verified to determine whether the tracking process of the current frame tracking channel is sustainable. Specifically, the above steps are performed to obtain the initial frame tracking channel. Repeating these steps, if the same tracking channel is selected again, the currently selected tracking channel is considered sustainable and meets the user's flight intention. Otherwise, the newly selected channel is used as the initial channel, and channel verification continues until the channel verification is successful. If the verification is repeated K times and still fails, the channel selection fails and the user is notified.

[0135] Specifically, as a preferred embodiment, Figure 7 As shown, the automatic tracking channel selection method provided by the embodiment of the present invention, after the above-mentioned step S140: the step of selecting the initial frame tracking channel of the drone from all power line channels, the method further includes: acquiring the current frame point cloud data in real time, and verifying the initial frame tracking channel based on all power line channels and tower information in the drone's flight direction extracted from the current frame point cloud data;

[0136] The step of verifying the initial frame tracking channel based on all power line channels and tower information in the UAV flight direction extracted from the current frame point cloud data includes:

[0137] S211: Based on the information of all power line channels and towers, the minimum flight distance and flight angle between the UAV and all power line channels are calculated respectively.

[0138] S212: Selecting a current frame tracking channel of the UAV from all power line channels for a predetermined number of consecutive times according to the minimum flight distance and the flight angle.

[0139] S213: Determine whether the current frame tracking channel selected for a predetermined number of consecutive times is consistent with the initial frame tracking channel.

[0140] S214: If the current frame tracking channel is consistent with the initial frame tracking channel, the UAV is controlled to continue flying along the initial frame tracking channel.

[0141] S215: If the current frame tracking channel is inconsistent with the initial frame tracking channel, the most recently selected current frame tracking channel is used as the initial frame tracking channel to control the drone to continue flying.

[0142] The technical solution provided by the embodiment of the present invention calculates the minimum flight distance and flight angle between the drone and all power line channels through all the above-mentioned power line channels and tower information, and then selects the current frame tracking channel for a predetermined number of consecutive times based on the minimum flight distance and flight angle. If the current frame tracking channel selected for the predetermined number of consecutive times is consistent with the initial frame tracking channel, it means that the power line channel selected for tracking is the channel corresponding to the flight direction of the drone, and the drone can be controlled to fly continuously along the initial frame tracking channel. If the current frame tracking channel is inconsistent with the initial frame tracking channel, the most recently selected current frame tracking channel is used as the initial frame tracking channel, and the drone is controlled to fly continuously for a period of time, and the channel verification is continued. The verification process is as above until the verification is successful. If the channel verification is repeated K times and still unsuccessful, it is determined that the channel selection has failed and the user is prompted.

[0143] Through the above verification process, it is possible to determine whether the initial frame tracking channel selected during the continuous flight of the UAV is correct. When the selected initial frame tracking channel is correct, the initial frame tracking channel is used as the previous frame tracking channel to control the continuous flight of the UAV. At this time, it is necessary to compare the distance and direction of the power line channel in the flight direction of the UAV with the above previous frame tracking channel during the continuous flight of the UAV, select the current frame tracking channel during the flight of the UAV, and realize the tracking of continuous multiple frames of power line channels during the flight.

[0144] Specifically, Figure 1 The technical solution provided by the illustrated embodiment further includes, after the initial frame tracking channel verification of the drone is successful:

[0145] S150: While the drone is in continuous flight, the minimum channel distance and angle between each power line channel and the previous frame's tracking channel are calculated based on the current frame's point cloud data. If the initial frame tracking channel selection method is still used during the drone's continuous flight, unstable flight status may affect the drone's flight status verification, resulting in tracking channel selection failure. In this case, using the successfully verified or followed previous frame tracking channel to constrain the current frame tracking channel can effectively improve the drone's flight stability, eliminating the impact of the aircraft's flight status.

[0146] As a preferred embodiment, Figure 8As shown, in the automatic tracking channel selection method provided in the above embodiment, the original step S150: calculating the minimum channel distance and channel angle between each power line channel and the tracking channel of the previous frame in all power line channels in the flight direction of the drone, includes:

[0147] S151: Calculating an average straight line equation of each power line channel based on the power line straight line equations of all power lines in each power line channel.

[0148] S152: Calculate the average straight line equation of the tracking channel in the previous frame according to the straight line equations of the power lines of all the power lines in the tracking channel in the previous frame.

[0149] S153: using the average straight line equation of each power line channel and the average straight line equation of the tracking channel of the previous frame, calculate the channel angle between each power line channel and the tracking channel of the previous frame.

[0150] as well as,

[0151] S154: Select multiple calculation points from each of all power lines.

[0152] S155: The power line equation of each power line in the tracking channel is calculated to obtain the point-line distances from multiple calculation points to each power line in the tracking channel of the previous frame.

[0153] S156: averaging the point-line distances to obtain an average distance from each power line in the power line channel to each power line in the previous frame tracking channel.

[0154] S157: Selecting the shortest average distance from the average distances corresponding to each power line in the power line channel as the shortest line distance from each power line in the power line channel to the tracking channel of the previous frame.

[0155] S158: Select a minimum value from the shortest line distances as the minimum channel distance between the power line channel and the tracking channel of the previous frame.

[0156] Regarding the calculation of the channel angle: the power line straight line equations of all power lines in the tracking channel of the previous frame are used to calculate the average straight line equation of the tracking channel of the previous frame, and then the power line straight line equations of each power line in all power line channels of the current frame are used to calculate the average straight line equation of each power line channel in all power line channels of the current frame. Finally, the channel angle between the average straight line equation of each power line channel in the current frame and the average straight line equation of the tracking channel of the previous frame is calculated.

[0157] Regarding the calculation of the minimum channel distance: select the two endpoints and the midpoint of the straight segment of each power line in a power line channel of the current frame as calculation points, calculate the point-line distances from these three calculation points to a power line straight line in the power line channel of the previous frame respectively, and then average the three point-line distances to obtain the average distance from each power line in the power line channel of the current frame to each power line in the tracking channel of the previous frame. The above method can realize the distance calculation from the above straight line equation to the straight line equation. Because multiple average distances can be calculated through a power line straight line of a power line channel of the current frame and all power line straight line equations of the tracking channel of the previous frame, the shortest average distance among the above multiple average distances can be taken as the shortest line distance from the straight line equation to the channel selected in the previous frame. Since there are multiple line equations in the current frame channel, the minimum value is selected from the shortest line distances from each line to the channel selected in the previous frame as the minimum channel distance from the power line channel of the current frame to the tracking channel of the previous frame.

[0158] Figure 1 The technical solution provided by the illustrated embodiment further includes the following steps after calculating the minimum channel distance and channel angle from the power line channel to the previous frame tracking channel:

[0159] S160: Using the minimum channel distance and channel angle, calculate the score of each power line channel according to a predetermined channel scoring formula, and select the power line channel with the highest score as the current frame tracking channel of the drone.

[0160] Traverse all the line channels of the current frame and execute the above steps to obtain the minimum channel distance and channel angle between each power line channel and the tracking channel of the previous frame. Then sort the minimum channel distance and channel angle of all power line channels respectively. Using the sorted results, the minimum and maximum values ​​of the angle and distance can be obtained respectively; among which, the maximum angle value of the above channel angle is recorded as θ max , the maximum distance of the above minimum channel distance is recorded as D max ,Through the predetermined channel score calculation formula, the power line channel with the highest ,score among all the power line channels in the current frame can be calculated and ,used as the current frame tracking channel of the UAV.

[0161] As a preferred embodiment, Figure 9 As shown, the above-mentioned automatic tracking channel selection method, step S160: using the minimum channel distance and channel angle, respectively calculating the score of each power line channel according to a predetermined channel scoring formula, and selecting the power line channel with the highest score as the current frame tracking channel of the drone includes the following steps:

[0162] S161: Sort the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel in all power line channels in the flight direction of the UAV, and obtain the maximum value of the minimum channel distance and the maximum value of the channel angle corresponding to each power line channel.

[0163] S162: Calculate the channel score according to the predetermined formula:

[0164] S d =int((D max -D i ) / d)*B d

[0165] S θ =int((θ max -θ i ) / d)*B θ

[0166] S total =S d +S θ

[0167] The scores of each power line channel are calculated separately, where S total is the overall score of the power line channel, S d is the minimum channel distance score, S θ Channel angle score, D max is the maximum value of the minimum channel distance, D i is the minimum channel distance, θ max is the maximum channel angle, θ i is the channel angle, d and τ are the distance step and angle step respectively, B d and B θ are fractions corresponding to the distance step and the angle step respectively;

[0168] S163: Selecting the power line channel with the highest score as the UAV's tracking channel for the current frame. The higher the score of the power line channel, the shorter the distance between the power line channel and the tracking channel of the previous frame, and the smaller the angle between the power line channel and the tracking channel of the previous frame. Selecting the power line channel with the highest score can maintain the continuity of the tracking channel during the UAV's flight.

[0169] In summary, the automatic tracking channel selection method of the drone-mounted laser radar provided by the present invention calculates the flight distance and flight direction of the drone based on the real-time acquired drone posture information, and then extracts all power line channels and tower information in the flight direction of the drone based on the above-mentioned flight distance and flight direction of the drone. Then, based on all the above-mentioned power line channels and tower information, the minimum flight distance and flight angle between the drone and all power line channels can be calculated. The minimum flight distance reflects the distance between the drone and the power line channel. Because the flight angle reflects the deviation angle between the drone and the power line channel, the above-mentioned minimum flight distance and flight angle can be used to select the initial frame tracking channel of the drone from all power line channels, and the drone can be controlled to fly along the initial frame tracking channel to realize automatic data collection of the channel. When the UAV continues to fly, the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel in all power line channels in the UAV flight direction are calculated based on the current frame point cloud data. The minimum channel distance reflects the shortest distance between each current power line channel and the previous frame tracking channel, and the channel angle reflects the deviation angle between each current power line channel and the previous frame tracking channel. Therefore, under the premise of determining that the previous frame tracking channel is correct, the minimum channel distance and channel angle can be used to evaluate the distance and angle deviation between each power line channel in the current frame and the previous frame tracking channel. Here, a predetermined channel scoring formula is used to evaluate the above distance and angle deviation to obtain a score for each power line channel. The higher the score, the smaller the distance and angle deviation. At this time, the power line channel with the highest score is selected as the current frame tracking channel of the UAV, which can realize the automatic correct selection of the simulation line channel. The current frame tracking channel with the smallest deviation is selected according to the previous frame tracking channel, and finally the line direction is determined, thereby realizing automatic channel selection of the simulation line and automatic inspection of the channel line.

[0170] In summary, this solution uses drone-mounted LiDAR technology to inspect power lines. The drone's position and orientation within the scene are determined based on its flight direction and position at startup. Point cloud data from the drone's onboard LiDAR is used to extract information about power line channels and towers. This information is then comprehensively compared with the direction and position of the lines below the drone. A score is calculated for each channel, and the highest-scoring channel is selected. The channel with the smallest angle to the flight direction and closest position receives the highest score, while the lowest score is the lowest. Finally, the selected channel is verified, and the final direction is determined after the same direction is selected twice in a row. This process ultimately enables automated channel selection and line inspection.

[0171] Also, see Figure 10 , Figure 10 This is a schematic diagram of the structure of an automatic tracking channel selection system for a drone-mounted laser radar provided by an embodiment of the present invention. Figure 10As shown in FIG, the automatic tracking channel selection system of the UAV-mounted laser radar includes:

[0172] Communication line 1002, communication module 1003, memory 1004, processor 1001 and a tracking channel automatic selection program for an unmanned aerial vehicle laser radar stored in memory 1004 and executable on processor 1001. When the tracking channel automatic selection program for an unmanned aerial vehicle laser radar is executed by processor 1001, the steps of the tracking channel automatic selection method for an unmanned aerial vehicle laser radar provided in any one of the above embodiments are implemented.

[0173] In summary, the automatic tracking channel selection scheme for the drone-mounted laser radar provided in the above embodiment of the present application uses drone laser radar technology to inspect power lines, and determines the position and direction of the drone in the scene based on the flight direction and position at startup. After extracting the power line channel and tower information using the drone laser radar point cloud, a comprehensive comparison of the direction and position is made with the line below, the score of each line channel is calculated, and the line channel with the highest score is selected. In the calculation, the line channel with the smallest angle to the flight direction and the closest position has the highest score, and vice versa. Finally, the selected channel is verified, and the line direction is finally determined after selecting the same line direction twice in a row. The above process finally realizes the automatic channel selection and line inspection of the line by imitation line. This solution can automatically select the line channel according to the flight status of the drone and continuously follow the channel without manual interaction, with a high level of intelligence and a good user experience.

[0174] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0175] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts 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, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0176] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0178] It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third etc. does not indicate any order. These words may be interpreted as names.

[0179] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0180] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for automatically selecting a tracking channel for a UAV-mounted laser radar, characterized in that: include: Calculate the flight distance and direction of the drone based on the real-time acquired drone position information; Extracting all power line channels and tower information in the flight direction of the drone from the laser radar point cloud data according to the flight distance and flight direction of the drone; Calculate the minimum flight distance and flight angle between the UAV and all power line channels based on the information of all power line channels and towers; Selecting an initial frame tracking channel for the UAV from all the power line channels according to the minimum flight distance and the flight angle; When the UAV continues to fly, the minimum channel distance and channel angle between each power line channel and the tracking channel of the previous frame are calculated based on the point cloud data of the current frame in all power line channels in the flight direction of the UAV; Using the minimum channel distance and channel angle, respectively calculating a score for each power line channel according to a predetermined channel scoring formula, and selecting the power line channel with the highest score as the current frame tracking channel for the UAV; The step of calculating the minimum flight distance and flight angle between the drone and all power line channels based on the information of all power line channels and towers includes: Extracting the power line channel and tower information along the flight direction of the UAV, and calculating the power line straight line equation of each power line in the power line channel based on the power line channel and tower information; For each of all the power line channels, calculating, according to a power line equation, two-dimensional and three-dimensional distances between all power lines in the power line channel and the current flight position of the UAV; Selecting the minimum two-dimensional distance and the minimum three-dimensional distance from the two-dimensional and three-dimensional distances between all power lines in the power line channel and the current flight position of the UAV as the minimum flight distance between the UAV and the power line channel; calculating an average direction of all the power line channels according to a power line equation of each power line in the power line channel; The average direction of all the power line channels and the flight direction of the UAV are used, and the flight angles between the UAV and all the power line channels are calculated according to a vector angle calculation formula.

2. The method for automatically selecting a tracking channel according to claim 1, wherein: After the step of selecting the initial frame tracking channel of the UAV from all the power line channels, the method further includes: acquiring current frame point cloud data in real time, and verifying the initial frame tracking channel based on all power line channels and tower information in the UAV flight direction extracted from the current frame point cloud data; the step of verifying the initial frame tracking channel includes: Calculate the minimum flight distance and flight angle between the UAV and all power line channels based on the information of all power line channels and towers; selecting a current frame tracking channel of the UAV from all the power line channels for a predetermined number of consecutive times according to the minimum flight distance and the flight angle; Determining whether the current frame tracking channel selected a predetermined number of times consecutively is consistent with the initial frame tracking channel; If the current frame tracking channel is consistent with the initial frame tracking channel, controlling the UAV to continue flying along the initial frame tracking channel; If the current frame tracking channel is inconsistent with the initial frame tracking channel, the most recently selected current frame tracking channel is used as the initial frame tracking channel to control the drone to continue flying.

3. The automatic tracking channel selection method according to claim 1, characterized in that: The step of calculating the flight distance and flight direction of the drone based on the real-time acquired drone posture information includes: Obtaining the first position coordinates of the drone at the current moment according to the posture information of the drone; Acquire a second position coordinate of the drone at a first predetermined time interval according to the posture information of the drone; Calculate the flight distance and flight direction of the UAV using the first position coordinates and the second position coordinates according to a flight distance calculation formula and a flight direction calculation formula, respectively; Determining whether the flight distance of the UAV is greater than or equal to a predetermined distance interval threshold; If the flight distance is greater than or equal to a predetermined distance interval threshold, it is determined that the UAV is in a normal flight state; If the flight distance is less than the predetermined distance interval threshold, the second position coordinate of the UAV is updated to the first position coordinate, and the flight distance and flight direction of the UAV are recalculated after the predetermined time interval until the flight distance of the UAV is greater than or equal to the predetermined distance interval.

4. The automatic tracking channel selection method according to claim 3, characterized in that: After the step of determining that the drone is in a normal flight state, the method further includes: Acquire a third position coordinate of the UAV at a second predetermined time interval according to the posture information of the UAV; Calculate the flight direction of the UAV using the second position coordinates and the third position coordinates according to the flight direction calculation formula; Determining whether a flight angle between the flight direction of the UAV and the previous flight direction is less than a predetermined angle deviation threshold; If the flight angle is less than a predetermined angle deviation threshold, the UAV is determined to be in stable flight, and the step of extracting information of all power line channels and towers in the UAV's flight direction from the laser radar point cloud data is performed based on the UAV's flight distance and flight direction; If the flight angle is greater than or equal to a predetermined angle deviation threshold, the UAV flight is determined to be unstable, the flight direction of the UAV is recalculated, and it is determined whether the flight angle of the UAV is less than a predetermined angle deviation threshold until the UAV flight is stabilized or the current flight of the UAV is terminated.

5. The automatic tracking channel selection method according to claim 4, characterized in that: The step of calculating the power line straight line equation of each power line in the power line channel according to the power line channel and tower information includes: Extracting the power line channel and tower information along the flight direction of the UAV, wherein the power line channel and tower information includes the coordinates of tower points in each power line channel of all power line channels in the flight direction; Use the RANSAC algorithm to select the tower point coordinates corresponding to each power line in the power line channel; Calculating a fitting center line of each power line using the tower point coordinates; The fitting center line is corrected according to the distance between the coordinates of other tower points in each power line and the fitting center line, so as to obtain the power line straight line equation of each power line in the power line channel.

6. The automatic tracking channel selection method according to claim 1 or 5, characterized in that: The step of selecting the initial frame tracking channel of the UAV from all the power line channels according to the minimum channel distance and the flight angle includes: Determine whether a channel deviation angle between a minimum flight angle and a second minimum flight angle among the flight angles between the UAV and all the power line channels is greater than or equal to a predetermined angle threshold; If the channel deviation angle is greater than or equal to a predetermined angle threshold, selecting the power line channel corresponding to the minimum flight angle as the initial frame tracking channel of the UAV; If the channel deviation angle is less than a predetermined angle threshold, calculating the weighted distance of each power line channel according to the distance weights corresponding to the minimum two-dimensional distance and the minimum three-dimensional distance of each power line channel in the minimum flight distance between the UAV and all power line channels; The power line channel with the smallest weighted distance is selected as the initial tracking channel of the UAV.

7. The method for automatically selecting a tracking channel according to claim 1, wherein: The step of calculating the minimum channel distance and channel angle between each power line channel and the previous frame tracking channel in all power line channels in the flight direction of the drone includes: Calculating an average straight line equation of each power line channel according to the straight line equations of all power lines in each power line channel; Calculating an average straight line equation of the tracking channel of the previous frame according to the straight line equations of the power lines of all the power lines in the tracking channel of the previous frame; Using the average straight line equation of each power line channel and the average straight line equation of the tracking channel of the previous frame, calculate the channel angle between each power line channel and the tracking channel of the previous frame; and, selecting a plurality of calculation points from each of said power lines; Calculating the point-to-line distances from the plurality of calculation points to each power line in the tracking channel of the previous frame according to the power line straight line equation of each power line in the tracking channel of the previous frame; averaging the point-line distances to obtain an average distance from each power line in the power line channel to each power line in the previous frame tracking channel; Selecting the shortest average distance from the average distances corresponding to each power line in the power line channel as the shortest line distance from each power line in the power line channel to the tracking channel of the previous frame; A minimum value is selected from the shortest line distances as the minimum road distance between the power line channel and the tracking channel of the previous frame.

8. The method for automatically selecting a tracking channel according to claim 1, wherein: The step of using the minimum channel distance and channel angle to calculate the score of each power line channel according to a predetermined channel scoring formula, and selecting the power line channel with the highest score as the current frame tracking channel of the drone includes: For all power line channels in the flight direction of the UAV, sort the minimum channel distance and channel angle between each power line channel and the tracking channel of the previous frame, and obtain the maximum value of the minimum channel distance and the maximum value of the channel angle corresponding to each power line channel; According to the predetermined channel score calculation formula: ； ； ； The scores of each power line channel are calculated separately, where: is the overall score of the power line channel, is the minimum channel distance score, Channel angle score, is the maximum value of the minimum channel distance, is the minimum channel distance, is the maximum value of the channel angle, is the channel angle, d and τ are the distance step and angle step respectively, and are fractions corresponding to the distance step and the angle step respectively; The power line channel with the highest score is selected as the current frame tracking channel of the UAV.

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