Tower photographing point location generation method and device for distribution line inspection route

Abstract

The embodiment of the invention provides a tower photographing point location generation method and device for a distribution line inspection route. The method is applied to information technology. The method comprises the following steps: constructing three-dimensional environment models of various types of towers according to shooting information of obtained historical tower photos; obtaining information of a to-be-photographed tower and a preset unmanned aerial vehicle inspection route of the to-be-photographed tower; obtaining a three-dimensional environment model of the to-be-photographed tower according to the tower type in the to-be-photographed tower information; determining candidate photographing point locations according to the to-be-photographed tower information and a preset unmanned aerial vehicle inspection route and a three-dimensional environment model of the to-be-photographed tower; screening the candidate photographing point locations according to a preset constraint condition to obtain a final photographing point location; and according to the final photographing point location, the information of the to-be-photographed tower and the three-dimensional environment model of the to-be-photographed tower, determining pose information of the unmanned aerial vehicle and a camera holder, and generating an unmanned aerial vehicle inspection route in combination with the inspection task. Therefore, the inspection efficiency and precision can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of information technology, and in particular to a method and apparatus for generating tower photography locations for power distribution line inspection routes. Background Technology

[0002] A pole or tower is a pole-shaped or tower-shaped structure that supports overhead power line conductors and overhead ground wires, maintaining a certain distance between them and the ground. Power line poles and towers can be classified according to the nature of the stress, circuit, purpose, tower type, assembly method, materials, and the current and voltage levels they transmit.

[0003] As the main equipment for power transmission, power poles and towers are particularly important for power distribution line inspection. Traditional power distribution line inspection uses a manual point selection method to select suitable photo locations from laser point cloud data. This method is inefficient, has poor accuracy, and is not conducive to generating accurate inspection routes. Summary of the Invention

[0004] This disclosure provides a method, apparatus, equipment, and storage medium for generating tower photography locations for power distribution line inspection routes.

[0005] According to a first aspect of this disclosure, a method for generating tower photographic locations for power distribution line inspection routes is provided. The method includes:

[0006] Based on the shooting information of historical pole photos, a three-dimensional environment model corresponding to each type of pole is constructed; wherein, the shooting information includes pole information, UAV location information, relative position information between pole and UAV, pose information of UAV and camera gimbal, environmental information of the pole, and existing shooting points of the pole.

[0007] Obtain information about the pole to be photographed and the corresponding preset drone inspection route for the pole to be photographed;

[0008] Obtain the 3D environment model corresponding to the pole to be photographed based on the pole type in the pole information;

[0009] Based on the information of the pole to be photographed, the preset drone inspection route corresponding to the pole to be photographed, and the 3D environment model, candidate photographing points are determined;

[0010] Candidate photo locations are filtered according to preset constraints to obtain the final photo locations;

[0011] Based on the final photo location, the information of the tower to be photographed, and the corresponding 3D environment model of the tower to be photographed, the pose information of the drone and camera gimbal is determined.

[0012] Based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information, a drone inspection route is generated.

[0013] In some possible implementations of the first aspect, determining candidate photo locations based on the information of the pole to be photographed, the preset UAV inspection route corresponding to the pole to be photographed, and the three-dimensional environment model includes:

[0014] Based on the information of the tower to be photographed and the corresponding preset drone inspection route, analyze the inspection task and determine the shooting area and shooting angle.

[0015] Candidate photo points are selected from the existing photo point information in the 3D environment model corresponding to the tower to be photographed, and those that match the shooting area and shooting angle.

[0016] In some possible implementations of the first aspect, the step of analyzing the inspection task and determining the shooting area and shooting angle based on the information of the pole to be photographed and the preset UAV inspection route corresponding to the pole to be photographed includes:

[0017] Based on the information about the pole to be photographed, the structure of the pole is determined. Based on the structure of the pole and the corresponding preset drone inspection route, the inspection task is divided into multiple sub-tasks. Each sub-task corresponds to one or more detection points on the pole. The corresponding shooting area and shooting angle are determined based on the structure of the pole and each detection point.

[0018] The inspection tasks include detecting foreign objects and bird nests, insulator contamination, tower top damage, tower cracks, untied conductors, damaged insulation layers, unused insulation sleeves, damaged insulators, tilted insulators, missing insulation covers, corroded ball heads, tripped surge arresters, improperly tied conductors, and missing pins.

[0019] In some possible implementations of the first aspect, determining the pose information of the UAV and camera gimbal based on the final photo capture location, the information of the pole to be photographed, and the corresponding 3D environment model of the pole to be photographed includes:

[0020] Calculate the line-of-sight vector based on the coordinates of the final photo location in the 3D environment model corresponding to the tower to be photographed;

[0021] The relative position between the final photo-taking point and the pole to be photographed is determined based on the information of the pole to be photographed;

[0022] The pose information of the drone is calculated based on the angle between the line of sight vector and the horizontal plane, the angle between the projection of the line of sight vector on the horizontal plane and the preset drone inspection route, and the relative position between the final photo point and the tower to be photographed.

[0023] The pose information of the camera gimbal is determined based on the pose information of the drone.

[0024] In some possible implementations of the first aspect, generating the UAV inspection route based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information includes:

[0025] Using a flight path generation algorithm, the shortest flight path of the drone from the takeoff point to the final photo location, the information of the tower to be photographed, the inspection task, and the pose information of the drone and camera gimbal is calculated. The drone inspection flight path is generated by combining the drone's own flight parameters and safety requirements.

[0026] In some possible implementations of the first aspect, the preset constraints include:

[0027] Obstacle avoidance constraints, inspection route distance constraints, and inspection route curvature change rate constraints.

[0028] In some possible implementations of the first aspect, the filtering of candidate photo locations based on preset constraints includes:

[0029] Calculate the distance between each candidate photo location and the obstacle, and eliminate candidate photo locations whose distance is less than the preset obstacle avoidance distance;

[0030] Calculate the distance between each candidate photo point and its corresponding previous candidate photo point, and remove candidate photo points whose distance is not within the preset distance range;

[0031] Calculate the rate of change of curvature of the inspection route for each candidate photo point, and remove candidate photo points whose rate of change of curvature of the inspection route is greater than the preset rate of change of curvature threshold.

[0032] According to a second aspect of this disclosure, a device for generating tower photographic locations for power distribution line inspection routes is provided. The device includes:

[0033] The 3D environment model construction module is used to construct 3D environment models corresponding to various types of poles based on the shooting information of historical pole photos. The shooting information includes pole information, UAV location information, relative position information between the pole and the UAV, pose information of the UAV and camera gimbal, environmental information of the pole, and existing shooting points of the pole.

[0034] The pole information and preset inspection route acquisition module is used to acquire information about the pole to be photographed and the preset drone inspection route corresponding to the pole to be photographed.

[0035] The module for obtaining the 3D environment model of the tower to be photographed is used to obtain the 3D environment model corresponding to the tower to be photographed based on the tower type in the tower information.

[0036] The candidate photo location determination module is used to determine candidate photo locations based on the information of the tower to be photographed, the preset drone inspection route corresponding to the tower to be photographed, and the 3D environment model.

[0037] The final photo location determination module is used to filter candidate photo locations based on preset constraints and obtain the final photo location.

[0038] The pose determination module is used to determine the pose information of the drone and camera gimbal based on the final shooting point, the information of the tower to be photographed, and the 3D environment model corresponding to the tower to be photographed.

[0039] The inspection route generation module is used to generate a drone inspection route based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information.

[0040] According to a third aspect of this disclosure, an electronic device is provided. The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method described above.

[0041] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing a computer to perform the methods described above.

[0042] In this disclosure, based on the shooting information of historical pole photos, a 3D environment model corresponding to each type of pole is constructed; information about the pole to be photographed and the corresponding preset UAV inspection route are obtained; a 3D environment model corresponding to the pole to be photographed is obtained based on the pole type in the information about the pole to be photographed; candidate photographing points are determined based on the information about the pole to be photographed, the corresponding preset UAV inspection route, and the 3D environment model; candidate photographing points are filtered according to preset constraints to obtain the final photographing points; the pose information of the UAV and camera gimbal is determined based on the final photographing points, the information about the pole to be photographed, and the corresponding 3D environment model; and a UAV inspection route is generated based on the final photographing points, the information about the pole to be photographed, the inspection task, and the pose information. This method can improve inspection efficiency and accuracy.

[0043] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0044] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of this disclosure. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0045] Figure 1 A flowchart is shown below illustrating a method for generating tower photograph locations for power distribution line inspection routes, provided by an embodiment of this disclosure.

[0046] Figure 2 This diagram shows a structural diagram of a tower photographing location generation device for power distribution line inspection routes provided in an embodiment of this disclosure;

[0047] Figure 3 A structural diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0049] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0050] To address the problems in the background technology, this disclosure provides a method, apparatus, device, and storage medium for generating pole photographing locations for power distribution line inspection routes. Specifically, based on the captured information of historical pole photographs, a three-dimensional environment model corresponding to each type of pole is constructed; information about the pole to be photographed and a preset UAV inspection route corresponding to the pole are obtained; a three-dimensional environment model corresponding to the pole to be photographed is obtained based on the pole type in the information about the pole to be photographed; candidate photographing locations are determined based on the information about the pole to be photographed, the preset UAV inspection route corresponding to the pole to be photographed, and the three-dimensional environment model; candidate photographing locations are filtered according to preset constraints to obtain the final photographing locations; the pose information of the UAV and camera gimbal is determined based on the final photographing locations, the information about the pole to be photographed, and the three-dimensional environment model corresponding to the pole to be photographed; and a UAV inspection route is generated based on the final photographing locations, the information about the pole to be photographed, the inspection task, and the pose information. This method can improve inspection efficiency and accuracy.

[0051] The following description, in conjunction with the accompanying drawings, details the method, apparatus, equipment, and storage medium for generating tower photographic locations for power distribution line inspection routes provided in this disclosure through specific embodiments.

[0052] Figure 1 This invention discloses a flowchart illustrating a method for generating tower photograph locations for power distribution line inspection routes, according to an embodiment of the present disclosure. Method 100 includes the following steps:

[0053] S110, Based on the shooting information of the acquired historical pole photos, construct a three-dimensional environment model corresponding to each type of pole; wherein, the shooting information includes pole information, drone location information, relative position information between the pole and the drone, pose information of the drone and camera gimbal, environmental information of the pole, and existing photo points of the pole.

[0054] In some embodiments, historical pole photographs are quality-compliant photographs that should have high definition and resolution, be taken under good lighting conditions with appropriate exposure to ensure that the pole and its surrounding environment are clearly visible in the photograph, and that there are no objects obscuring the pole, reflections, or shadows. There should be a certain overlap between adjacent historical pole photographs, and the photographs should contain sufficient information to construct a three-dimensional environment model, such as the drone's location, the relative position between the drone and the pole, the pose information of the drone and camera gimbal, pole information, information about the environment in which the pole is located, and information about existing photographing points on the pole.

[0055] In some embodiments, the shooting information includes:

[0056] Information includes: pole and tower information, drone location information, relative position information between the pole and drone, pose information of the drone and camera gimbal, environmental information of the pole and tower, and existing photo-taking locations on the pole and tower.

[0057] Tower information includes location coordinates, tower model, tower type, tower height, and span length. Furthermore, the line voltage can be determined based on the tower model. Tower types are classified by manufacturing materials into cement towers, steel pipe towers, and iron towers, and by purpose into straight-line towers, tension towers, angle towers, terminal towers, branch towers, and crossing towers.

[0058] The drone's location information includes its coordinates and altitude.

[0059] The relative position information between the pole and the drone includes the relative distance between the pole and the drone and the angle of the drone relative to the pole;

[0060] The attitude information of the drone and camera gimbal includes the pitch angle, yaw angle, and roll angle of the drone and the pitch angle, yaw angle, and roll angle of the camera gimbal.

[0061] The environmental information of the pole includes information such as the terrain, landforms, and vegetation around the pole.

[0062] In some embodiments, based on the shooting information of acquired historical tower photographs, a three-dimensional environment model corresponding to each type of tower is constructed, including:

[0063] Based on historical pole photos taken by drones at different heights and angles, this study obtains information about the poles, drone positions, relative positions of the poles and drones, pose information of the drones and camera gimbals, environmental information of the poles, and existing photo-taking points on the poles. Using this information, initial 3D environmental models are constructed for each type of pole. The pose information of the drones and camera gimbals in each historical pole photo is analyzed. Using this pose information, the coordinates of each pixel in the historical pole photos are calculated in 3D space using photogrammetry principles. The images are mapped to the initial 3D environment model corresponding to the same type of pole in the historical pole photos to ensure that the images in the historical pole photos and the images in the initial 3D environment model corresponding to the same type of pole in the historical pole photos are aligned. The historical pole photos taken by the UAV at different heights and angles are analyzed based on the UAV's position information and relative position information. Based on the analysis results, holes or missing parts in the initial 3D environment model corresponding to the same type of pole in the historical pole photos are identified and filled to improve the integrity and accuracy of the model, resulting in the constructed 3D models corresponding to each type of pole.

[0064] Furthermore, historical pole photos and image processing techniques (interpolation, texture synthesis, etc.) are used to fill and repair holes or missing parts in the initial 3D environment model corresponding to poles of the same type as those in the historical pole photos.

[0065] S120 acquires information about the pole to be photographed and the corresponding preset drone inspection route.

[0066] In some embodiments, information about the tower to be photographed is obtained using tools such as GPS locators, rangefinders, and inclinometers, or from a basic database of circuit lines or a GIS system.

[0067] In some embodiments, an undirected graph is created based on the information of the pole to be photographed. An intelligent algorithm is used to calculate the shortest path for the UAV to traverse and inspect the pole on the undirected graph. A preset UAV inspection route is then generated by combining this route with the UAV's own flight parameters.

[0068] Intelligent algorithms include breadth-first search and depth-first search.

[0069] Flight parameters include flight speed, range, and obstacle avoidance capabilities.

[0070] S130: Obtain the 3D environment model corresponding to the pole to be photographed based on the pole type in the pole information.

[0071] In some embodiments, the three-dimensional environment model corresponding to the pole to be photographed is selected from the three-dimensional environment models corresponding to each type of pole in the constructed three-dimensional environment model, based on the pole type in the pole information to be photographed.

[0072] S140 determines candidate photo locations based on the information of the pole to be photographed, the preset drone inspection route corresponding to the pole to be photographed, and the three-dimensional environment model.

[0073] In some embodiments, candidate photo locations are determined based on the information of the pole to be photographed, the preset UAV inspection route corresponding to the pole, and the 3D environment model, including:

[0074] Based on the information of the tower to be photographed and the corresponding preset drone inspection route, analyze the inspection task and determine the shooting area and shooting angle.

[0075] Candidate photo points are selected from the existing photo point information in the 3D environment model corresponding to the tower to be photographed, and those that match the shooting area and shooting angle.

[0076] In some embodiments, based on the information of the pole to be photographed and the preset drone inspection route corresponding to the pole, the inspection task is analyzed and the shooting area and shooting angle are determined, including:

[0077] The structure of the pole to be photographed is determined based on the information of the pole to be photographed. Based on the structure of the pole to be photographed and the preset drone inspection route corresponding to the pole to be photographed, the inspection task is divided into multiple sub-tasks. Each sub-task corresponds to one or more detection points on the pole to be photographed. The corresponding shooting area and shooting angle are determined based on the structure of the pole to be photographed and each detection point.

[0078] Furthermore, based on a load-balanced clustering algorithm, and considering various constraints such as the drone's flight range, inspection tasks are evenly distributed according to the different types of inspection tasks, ensuring that the drone can independently complete all inspection tasks within the maximum vector similarity space; among which,

[0079] The inspection tasks include detecting defects such as foreign objects and bird nests, insulator contamination, tower top damage, tower cracks, untied conductors, damaged insulation layers, unused insulation sleeves, damaged insulators, tilted insulators, missing insulation covers, corroded ball heads, tripped surge arresters, improperly tied conductors, and missing pins.

[0080] For example, when the inspection task is to detect cracks in the tower, the gimbal is used to take pictures from a level view. When the inspection task is to detect damage to the top of the tower and the tower to be photographed is a cement tower, the gimbal angle is generally set to 45 degrees. When taking pictures of the top of the tower, the drone is aimed at the top of the tower from top to bottom along the downward direction at four counterclockwise angles, with the shooting directions being the small side, right side, left side, and large side in that order. Generally, the vertical height of the drone from the top of the tower is 4 meters. When the inspection task is to detect damage to the top of the tower and the tower to be photographed is a steel tower, the gimbal angle is generally set to 65 to 70 degrees. If the tower to be photographed contains pole-mounted equipment such as transformers, disconnectors, pole-mounted switches, surge arresters, and platforms, when photographing these pole-mounted equipment, the vertical height of the drone from the top of the tower is 1 to 2 meters, the gimbal angle is set to 60 to 70 degrees, and the pole-mounted switches, disconnectors, and surge arresters are photographed from the equipment side, while the platforms are photographed from both sides.

[0081] In some embodiments, to ensure the continuity and integrity of the shooting, a certain overlap area is set between adjacent candidate shooting points.

[0082] S150: Based on preset constraints, candidate photo locations are filtered to obtain the final photo locations.

[0083] In some embodiments, the preset constraints include obstacle avoidance constraints, inspection route distance constraints, and inspection route curvature change rate constraints.

[0084] In some embodiments, candidate photo locations are filtered according to preset constraints, including:

[0085] Calculate the distance between each candidate photo location and the obstacle, and eliminate candidate photo locations whose distance is less than the preset obstacle avoidance distance;

[0086] Calculate the distance between each candidate photo point and its corresponding previous candidate photo point, and remove candidate photo points whose distance is not within the preset distance range;

[0087] Calculate the rate of change of curvature of the inspection route for each candidate photo point, and remove candidate photo points whose rate of change of curvature of the inspection route is greater than the preset rate of change of curvature threshold.

[0088] S160 determines the pose information of the drone and camera gimbal based on the final photo location, the information of the tower to be photographed, and the corresponding 3D environment model of the tower to be photographed.

[0089] In some embodiments, the pose information of the drone and camera gimbal is determined based on the final photo capture location, the information of the pole to be photographed, and the 3D environment model corresponding to the pole to be photographed, including:

[0090] Calculate the line-of-sight vector based on the coordinates of the final photo location in the 3D environment model corresponding to the tower to be photographed;

[0091] The relative position between the final photo-taking point and the pole to be photographed is determined based on the information of the pole to be photographed;

[0092] The pose information of the drone is calculated based on the angle between the line of sight vector and the horizontal plane, the angle between the projection of the line of sight vector on the horizontal plane and the preset drone inspection route, and the relative position between the final photo point and the tower to be photographed.

[0093] The pose information of the camera gimbal is determined based on the pose information of the drone.

[0094] Furthermore, by determining the coordinates of the final photo-taking point and the shooting area in the 3D environment model corresponding to the tower to be photographed, the line-of-sight direction vector is calculated. The direction of this line-of-sight direction vector is from the final photo-taking point to the shooting area.

[0095] In the 3D environment model corresponding to the pole to be photographed, the pitch angle of the drone is calculated based on the angle between the line-of-sight vector and the horizontal plane; the yaw angle of the drone is calculated based on the angle between the projection of the line-of-sight vector on the horizontal plane and the preset drone inspection route; based on the relative position between the final shooting point and the pole to be photographed, it is determined whether there are obstacles obstructing the pole to be photographed. If there are obstacles obstructing the pole to be photographed, the calculated pitch and yaw angles are adjusted to ensure that the camera on the drone can avoid these obstacles and take pictures to obtain clear images; under normal circumstances, the roll angle of the drone is set to 0 degrees or close to 0 degrees. For some shooting areas that require close-up shots, the roll angle of the drone is calculated based on the relative position between the final shooting point and the pole to be photographed and the corresponding shooting requirements;

[0096] Based on the position of the camera gimbal in the drone, the pose information of the drone is converted into the pose information of the gimbal using an attitude calculation algorithm.

[0097] S170 generates a drone inspection route based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information.

[0098] In some embodiments, a drone inspection route is generated based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information, including:

[0099] Using a flight path generation algorithm, based on the final photo location, information about the pole to be photographed, the inspection task, and the pose information of the drone and camera gimbal, the shortest flight path of the drone from the takeoff point to the final photo location and then to the landing point is calculated. This path is then combined with the drone's own flight parameters and safety requirements to generate the drone inspection flight path.

[0100] Route generation algorithms include graph search algorithms, genetic algorithms, particle swarm optimization algorithms, dynamic programming algorithms, RRT algorithms, and greedy algorithms;

[0101] Safety requirements include safe distance limits between the drone and the pole to be photographed, as well as obstacles; drone flight altitude limits; and emergency plans. Generally, the safe distance between the drone and the pole to be photographed is set at 8 meters.

[0102] Furthermore, the inspection interval of the pole to be photographed is used as a weight, and the goal is to maximize the sum of the weights of the poles inspected by the drone. The inspection route of the drone is optimized. Based on the traditional genetic algorithm, the Metropolis criterion of the SA algorithm is introduced to improve the local search capability of the genetic algorithm and obtain the optimal inspection route within the reasonable operating time of the drone. Among them, the larger the weight, the longer the inspection interval of the pole to be photographed, and the higher the priority of the pole to be photographed.

[0103] When using a greedy algorithm to generate UAV inspection routes, all inspection tasks are first traversed. Then, the take-off and landing strategies corresponding to different types of inspection tasks are combined to generate the inspection route with the minimum total inspection mileage and total inspection time, while ensuring that the UAV can take off safely. This inspection route is then used as the final UAV inspection route.

[0104] According to embodiments of this disclosure, based on the captured information from historical pole photos, a 3D environment model corresponding to each type of pole is constructed; information about the pole to be photographed and a preset UAV inspection route corresponding to the pole are obtained; a 3D environment model corresponding to the pole to be photographed is obtained based on the pole type in the information about the pole to be photographed; candidate photographing points are determined based on the information about the pole to be photographed, the preset UAV inspection route corresponding to the pole to be photographed, and the 3D environment model; candidate photographing points are filtered according to preset constraints to obtain the final photographing points; the pose information of the UAV and camera gimbal is determined based on the final photographing points, the information about the pole to be photographed, and the 3D environment model corresponding to the pole to be photographed; and a UAV inspection route is generated based on the final photographing points, the information about the pole to be photographed, the inspection task, and the pose information. This method can improve inspection efficiency and accuracy.

[0105] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this disclosure is not limited to the described order of actions, because according to this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this disclosure.

[0106] The above is an introduction to the method embodiments. The following describes the solution described in this disclosure further through device embodiments.

[0107] Figure 2 This diagram illustrates a structural representation of a device for generating tower photographic locations along a power distribution line inspection route, according to an embodiment of this disclosure. The device 200 includes:

[0108] The 3D environment model construction module 210 is used to construct 3D environment models corresponding to various types of poles based on the shooting information of historical pole photos; wherein, the shooting information includes pole information, UAV location information, relative position information between pole and UAV, pose information of UAV and camera gimbal, environmental information of the pole, and existing shooting point information of the pole.

[0109] The pole information and preset inspection route acquisition module 220 is used to acquire the pole information to be photographed and the preset UAV inspection route corresponding to the pole.

[0110] The three-dimensional environment model acquisition module 230 for the tower to be photographed is used to acquire the three-dimensional environment model corresponding to the tower to be photographed based on the tower type in the tower information.

[0111] The candidate photo location determination module 240 is used to determine candidate photo locations based on the information of the tower to be photographed, the preset UAV inspection route corresponding to the tower to be photographed, and the three-dimensional environment model.

[0112] In some embodiments, the candidate photo location determination module 240 is specifically used for:

[0113] Based on the information of the pole to be photographed, the corresponding preset drone inspection route, and the 3D environment model, candidate photographing locations are determined, including:

[0114] Based on the information of the tower to be photographed and the corresponding preset drone inspection route, analyze the inspection task and determine the shooting area and shooting angle.

[0115] Candidate photo points are selected from the existing photo point information in the 3D environment model corresponding to the tower to be photographed, and those that match the shooting area and shooting angle.

[0116] In some embodiments, the candidate photo location determination module 240 is further configured to:

[0117] Based on the information of the pole to be photographed and the corresponding preset drone inspection route, the inspection task is analyzed and the shooting area and shooting angle are determined, including:

[0118] Based on the information about the pole to be photographed, the structure of the pole is determined. Based on the structure of the pole and the corresponding preset drone inspection route, the inspection task is divided into multiple sub-tasks. Each sub-task corresponds to one or more detection points on the pole. The corresponding shooting area and shooting angle are determined based on the structure of the pole and each detection point.

[0119] The inspection tasks include detecting foreign objects and bird nests, insulator contamination, tower top damage, tower cracks, untied conductors, damaged insulation layers, unused insulation sleeves, damaged insulators, tilted insulators, missing insulation covers, corroded ball heads, tripped surge arresters, improperly tied conductors, and missing pins.

[0120] The final photo location determination module 250 is used to filter candidate photo locations according to preset constraints and obtain the final photo location.

[0121] In some embodiments, the final photo location determination module 250 is specifically used for:

[0122] The preset constraints include obstacle avoidance constraints, inspection route distance constraints, and inspection route curvature change rate constraints.

[0123] In some embodiments, the final photo location determination module 250 is further configured to:

[0124] Candidate photo locations are filtered based on preset constraints, including:

[0125] Calculate the distance between each candidate photo location and the obstacle, and eliminate candidate photo locations whose distance is less than the preset obstacle avoidance distance;

[0126] Calculate the distance between each candidate photo point and its corresponding previous candidate photo point, and remove candidate photo points whose distance is not within the preset distance range;

[0127] Calculate the rate of change of curvature of the inspection route for each candidate photo point, and remove candidate photo points whose rate of change of curvature of the inspection route is greater than the preset rate of change of curvature threshold.

[0128] The pose determination module 260 is used to determine the pose information of the drone and camera gimbal based on the final shooting point, the information of the tower to be photographed, and the three-dimensional environment model corresponding to the tower to be photographed.

[0129] In some embodiments, the pose determination module 260 is specifically used for:

[0130] Based on the final photo location, the information of the pole to be photographed, and the corresponding 3D environment model of the pole, the pose information of the drone and camera gimbal is determined, including:

[0131] Calculate the line-of-sight vector based on the coordinates of the final photo location in the 3D environment model corresponding to the tower to be photographed;

[0132] The relative position between the final photo-taking point and the pole to be photographed is determined based on the information of the pole to be photographed;

[0133] The pose information of the drone is calculated based on the angle between the line of sight vector and the horizontal plane, the angle between the projection of the line of sight vector on the horizontal plane and the preset drone inspection route, and the relative position between the final photo point and the tower to be photographed.

[0134] The pose information of the camera gimbal is determined based on the pose information of the drone.

[0135] The inspection route generation module 270 is used to generate a drone inspection route based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information.

[0136] In some embodiments, the inspection route generation module 270 is specifically used for:

[0137] Based on the final photo location, the information of the tower to be photographed, the inspection task, and the aforementioned pose information, a drone inspection route is generated, including:

[0138] Using a flight path generation algorithm, the shortest flight path of the drone from the takeoff point to the final photo location, the information of the tower to be photographed, the inspection task, and the pose information of the drone and camera gimbal is calculated. The drone inspection flight path is generated by combining the drone's own flight parameters and safety requirements.

[0139] Understandable Figure 2 Each module / unit in the apparatus 200 shown has the function of implementing each step in the method 100 provided in the embodiments of this disclosure, and can achieve its corresponding technical effect. For the sake of brevity, it will not be described in detail here.

[0140] Figure 3 A structural diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. Electronic device 300 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic device 300 may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0141] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0142] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0143] The computing unit 301 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as method 100. For example, in some embodiments, method 100 may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform method 100 by any other suitable means (e.g., by means of firmware).

[0144] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0146] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0147] It should be noted that this disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute method 100 and achieve the corresponding technical effects achieved by executing the method in the embodiments of this disclosure. For the sake of brevity, they will not be described in detail here.

[0148] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including voice input, speech input, or tactile input).

[0149] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0150] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0151] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0152] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for generating a tower photographing point of a power distribution line inspection route, characterized in that, include: Based on the shooting information of the historical tower photos, construct three-dimensional environment models corresponding to each type of tower; Obtain information about the pole to be photographed and the corresponding preset drone inspection route for the pole to be photographed; Obtain the 3D environment model corresponding to the pole to be photographed based on the pole type in the pole information; determine the candidate photographing points based on the pole information, the preset UAV inspection route corresponding to the pole, and the 3D environment model. Candidate photo locations are filtered according to preset constraints to obtain the final photo locations; Based on the final photo location, the information of the tower to be photographed, and the corresponding 3D environment model of the tower to be photographed, the pose information of the drone and camera gimbal is determined. Based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information, a drone inspection route is generated.

2. The method according to claim 1, characterized in that, The process of determining candidate photo locations based on the information of the pole to be photographed, the preset UAV inspection route corresponding to the pole, and the 3D environment model includes: Based on the information of the tower to be photographed and the corresponding preset drone inspection route, analyze the inspection task and determine the shooting area and shooting angle. Candidate photo points are selected from the existing photo point information in the 3D environment model corresponding to the tower to be photographed, and those that match the shooting area and shooting angle.

3. The method according to claim 2, characterized in that, The process of analyzing the inspection task and determining the shooting area and shooting angle based on the information of the tower to be photographed and the corresponding preset drone inspection route includes: Based on the information about the pole to be photographed, the structure of the pole is determined. Based on the structure of the pole and the corresponding preset drone inspection route, the inspection task is divided into multiple sub-tasks. Each sub-task corresponds to one or more detection points on the pole. The corresponding shooting area and shooting angle are determined based on the structure of the pole and each detection point. The inspection tasks include detecting foreign objects and bird nests, insulator contamination, tower top damage, tower cracks, untied conductors, damaged insulation layers, unused insulation sleeves, damaged insulators, tilted insulators, missing insulation covers, corroded ball heads, tripped surge arresters, improperly tied conductors, and missing pins.

4. The method according to claim 1, characterized in that, The process of determining the pose information of the drone and camera gimbal based on the final photo location, the information of the tower to be photographed, and the corresponding 3D environment model of the tower to be photographed includes: Calculate the line-of-sight vector based on the coordinates of the final photo location in the 3D environment model corresponding to the tower to be photographed; The relative position between the final photo-taking point and the pole to be photographed is determined based on the information of the pole to be photographed; The pose information of the drone is calculated based on the angle between the line of sight vector and the horizontal plane, the angle between the projection of the line of sight vector on the horizontal plane and the preset drone inspection route, and the relative position between the final photo point and the tower to be photographed. The pose information of the camera gimbal is determined based on the pose information of the drone.

5. The method according to claim 1, characterized in that, The step of generating a drone inspection route based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information includes: Using a flight path generation algorithm, the shortest flight path of the drone from the takeoff point to the final photo location, the information of the tower to be photographed, the inspection task, and the pose information of the drone and camera gimbal is calculated. The drone inspection flight path is generated by combining the drone's own flight parameters and safety requirements.

6. The method according to claim 1, characterized in that, The preset constraints include: Obstacle avoidance constraints, inspection route distance constraints, and inspection route curvature change rate constraints.

7. The method according to claim 6, characterized in that, The process of filtering candidate photo locations based on preset constraints includes: Calculate the distance between each candidate photo location and the obstacle, and eliminate candidate photo locations whose distance is less than the preset obstacle avoidance distance; Calculate the distance between each candidate photo point and its corresponding previous candidate photo point, and remove candidate photo points whose distance is not within the preset distance range; Calculate the rate of change of curvature of the inspection route for each candidate photo point, and remove candidate photo points whose rate of change of curvature of the inspection route is greater than the preset rate of change of curvature threshold.

8. A device for generating tower photographic locations for power distribution line inspection routes, characterized in that, include: The 3D environment model building module is used to build 3D environment models corresponding to various types of poles based on the shooting information of the acquired historical pole photos. The pole information and preset inspection route acquisition module is used to acquire information about the pole to be photographed and the preset drone inspection route corresponding to the pole to be photographed. The module for obtaining the 3D environment model of the tower to be photographed is used to obtain the 3D environment model corresponding to the tower to be photographed based on the tower type in the tower information. The candidate photo location determination module is used to determine candidate photo locations based on the information of the tower to be photographed, the preset drone inspection route corresponding to the tower to be photographed, and the 3D environment model. The final photo location determination module is used to filter candidate photo locations based on preset constraints and obtain the final photo location. The pose determination module is used to determine the pose information of the drone and camera gimbal based on the final shooting point, the information of the tower to be photographed, and the 3D environment model corresponding to the tower to be photographed. The inspection route generation module is used to generate a drone inspection route based on the final photo location, the information of the tower to be photographed, the inspection task, and the pose information.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-7.

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