CN112783196A - Distribution network line unmanned aerial vehicle autonomous flight path planning method and system - Google Patents
Distribution network line unmanned aerial vehicle autonomous flight path planning method and system Download PDFInfo
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Abstract
The invention provides a method and a system for planning an autonomous flight path of a distribution network line unmanned aerial vehicle, and relates to the technical field of distribution networks. The invention obtains the image data of the distribution network line. And constructing a three-dimensional model of the distribution network line under a typical scene based on the image data of the distribution network line. And generating an initial path image based on the three-dimensional model of the distribution network line, and carrying out hidden danger calibration and correction on the initial path image to generate an unmanned aerial vehicle path supporting routing inspection of key components of the distribution network. According to the unmanned aerial vehicle route detection method, the initial route image is generated based on the three-dimensional model of the distribution network line, the hidden danger calibration correction is carried out on the initial route image, the unmanned aerial vehicle route supporting the routing inspection of key parts of the distribution network is generated, the unmanned aerial vehicle initial route image is calibrated through the hidden danger, the obstacle avoidance under the complex power line environment is realized, the safety factor of the unmanned aerial vehicle routing inspection is improved, and the routing inspection risk is reduced.
Description
Technical Field
The invention relates to the technical field of distribution networks, in particular to a method and a system for planning an autonomous flight path of a distribution network line unmanned aerial vehicle.
Background
Through practice and application in recent years, the service area of the unmanned aerial vehicle power inspection service is further expanded, and the services mainly developed by the small unmanned helicopter include daily inspection operation, line acceptance, line maintenance safety supervision, capital construction inspection and reinspection after comprehensive maintenance; the main services developed by the fixed-wing unmanned aerial vehicle include channel patrol, mountain fire prevention special patrol, pole tower icing special patrol, capital construction patrol, disaster general survey and the like. The deployment and the wide application of the intelligent inspection of the unmanned aerial vehicle have solid practical foundation and basis.
Autonomous flight path planning is carried out on a routing inspection path of the unmanned aerial vehicle, and the autonomous flight path planning method is a main research direction for routing inspection of the unmanned aerial vehicle at present.
The method for planning the autonomous flight path of the unmanned aerial vehicle of the distribution network line in the prior art is generally used for realizing higher inspection risk in a complex power line environment aiming at a simple power environment.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a method and a system for planning the autonomous flight path of a distribution network line unmanned aerial vehicle, which solve the technical problem that the autonomous flight path planning method of the distribution network line unmanned aerial vehicle in the prior art is applied to realize higher inspection risk in a complex power line environment.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention provides a distribution network line unmanned aerial vehicle autonomous flight path planning method, which comprises the following steps:
acquiring image data of a distribution network line;
constructing a three-dimensional model of the distribution network line under a typical scene based on the image data of the distribution network line;
and generating an initial path image based on the three-dimensional model of the distribution network line, and carrying out hidden danger calibration and correction on the initial path image to generate an unmanned aerial vehicle path supporting routing inspection of key components of the distribution network.
Preferably, the method for constructing a three-dimensional model of the distribution network line in a typical scene based on the image data of the distribution network line includes:
constructing an environmental three-dimensional model based on the image data;
constructing a tower three-dimensional model based on the image data;
constructing a three-dimensional model of the key component based on the image data;
and inputting component information.
Preferably, the constructing an environmental three-dimensional model based on the image data includes:
and automatically generating a three-dimensional environment model file by adopting image identification, multi-side texture extraction and automatic characteristic ground object extraction, and manufacturing an environment three-dimensional model according to image data acquired by unmanned aerial vehicle inspection.
Preferably, the three-dimensional model of the environment includes: a terrain model and a ground object model;
wherein:
the terrain model construction method comprises the following steps:
on the basis of a high-precision digital earth surface model DSM, extracting three-dimensional information of the ground object by adopting contour extraction, surface patch fitting and roof reconstruction through an image identification technology, and simultaneously carrying out image segmentation, edge extraction and texture clustering on a multi-view image to obtain all-directional texture information of the ground object; and establishing a corresponding relation between geometric information and texture information of the ground features, and simultaneously performing integral uniform light and color carding to realize orthographic processing of multi-view images and construct a terrain model.
Preferably, the constructing a tower three-dimensional model based on the image data includes:
carrying out external operation scanning on different types of towers in a typical scene to generate point cloud data;
performing rough model line drawing and feature point extraction on point cloud data through internal operation processing to generate a rough three-dimensional model of the tower;
and processing and generating refined models of all types of towers by drawing a toughened structure and rendering the models.
Preferably, the building of the three-dimensional model of the key component based on the image data includes:
obtaining a high-quality three-dimensional model library of key components of the distribution network line by adopting an analysis method and an operation mode of high-precision acquisition, component measurement and fine modification;
performing digital differential correction by using the generated digital elevation model through regional color correction to generate a photo digital orthophoto image;
and inspecting the quality of the digital ortho-image of the photo, and processing the problems and phenomena of image blurring, dislocation, distortion, deformation and leak to obtain a three-dimensional model of the key component.
Preferably, the generating of the initial path image based on the three-dimensional model of the distribution network line, the performing of hidden danger calibration and correction on the initial path image, and the generating of the unmanned aerial vehicle path supporting the routing inspection of the key components of the distribution network includes:
an initial path image of the unmanned aerial vehicle is rapidly generated through a GIS platform, hidden danger calibration and correction are carried out on the initial path image, and corrected track points are input into a three-dimensional model of a distribution network line;
and generating an unmanned aerial vehicle path supporting distribution network key component inspection by taking the maximum path as a target based on the waypoints in the three-dimensional model of the distribution network line.
The invention also provides a system for planning the autonomous flight path of the unmanned aerial vehicle on the distribution network line, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the steps of the method are realized when the processor executes the computer program.
(III) advantageous effects
The invention provides a method and a system for planning an autonomous flight path of a distribution network line unmanned aerial vehicle. Compared with the prior art, the method has the following beneficial effects:
according to the unmanned aerial vehicle route detection method, the initial route image is generated based on the three-dimensional model of the distribution network line, the hidden danger calibration correction is carried out on the initial route image, the unmanned aerial vehicle route supporting the routing inspection of key parts of the distribution network is generated, the unmanned aerial vehicle initial route image is calibrated through the hidden danger, the obstacle avoidance under the complex power line environment is realized, the safety factor of the unmanned aerial vehicle routing inspection is improved, and the routing inspection risk is reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a block diagram of a method for planning an autonomous flight path of a distribution network line unmanned aerial vehicle according to an embodiment of the present invention;
FIG. 2 is a diagram of an example terrain model;
FIG. 3 is a schematic diagram of a rough three-dimensional model of a tower;
FIG. 4 is a schematic diagram of a refined model of a tower;
FIG. 5 is a schematic diagram of a three-dimensional model of a key component.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The distribution network line unmanned aerial vehicle autonomous flight path planning method solves the technical problem that the distribution network line unmanned aerial vehicle autonomous flight path planning method in the prior art is applied to the realization of high inspection risk in a complex power line environment, realizes obstacle avoidance in the complex power line environment, improves the safety factor of unmanned aerial vehicle inspection, and reduces inspection risk.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the unmanned aerial vehicle autonomous flight path planning technology comprises two technologies, one technology is that a flight path of the unmanned aerial vehicle during power transmission line inspection is accurately recorded by using Beidou high-precision positioning service, the path is used as a prior path to carry out path point design, and the other technology is that accurate three-dimensional modeling is carried out on a power transmission tower and a corridor, and path design is carried out in a three-dimensional model and a scene. Utilize unmanned aerial vehicle to become more meticulous to patrol and examine and acquire waypoint and need carry on the high accuracy positioner based on RTK difference technique on unmanned aerial vehicle, can make unmanned aerial vehicle platform possess higher positioning accuracy and course precision under the complex environment under the device's assistance, combine the cloud platform control mechanism of high accuracy for the camera can obtain better orientation precision. The scheme for designing the three-dimensional scene auxiliary flight route is that an automatic or semi-automatic path planning algorithm is applied in a three-dimensional scene, limiting factors needing to be considered for unmanned aerial vehicle inspection are input into the algorithm in a conditional mode, and then a computer is used for designing an inspection route in an auxiliary mode by matching with the three-dimensional scene. According to the scheme, three-dimensional modeling needs to be carried out on the transmission line channel, and the modeling content comprises modeling of a tower, acquisition of a tower coordinate position, modeling of surrounding environments such as trees and houses and creation of a transmission line terrain DEM. The embodiment of the invention performs the autonomous flight path planning of the unmanned aerial vehicle of the distribution network line based on the second method.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
The embodiment of the invention provides a method for planning an autonomous flight path of a distribution network line unmanned aerial vehicle, which comprises the steps of S1-S3 as shown in figure 1.
And S1, acquiring the image data of the distribution network line.
And S2, constructing a three-dimensional model of the distribution network line in a typical scene based on the image data of the distribution network line.
S3, generating an initial path image based on the three-dimensional model of the distribution network line, carrying out hidden danger calibration and correction on the initial path image, and generating the unmanned aerial vehicle path supporting routing inspection of the key components of the distribution network.
According to the method and the device, the initial path image is generated based on the three-dimensional model of the distribution network line, the hidden danger calibration correction is carried out on the initial path image, the unmanned aerial vehicle path supporting the routing inspection of the key parts of the distribution network is generated, the initial path image of the unmanned aerial vehicle is calibrated through the hidden danger, the obstacle avoidance under the complex power line environment is realized, the safety factor of the unmanned aerial vehicle routing inspection is improved, and the routing inspection risk is reduced.
In one embodiment, S1, the image data of the distribution network route is obtained. The method specifically comprises the following steps:
in the embodiment of the invention, in order to realize autonomous intelligent inspection of the unmanned aerial vehicle, firstly, image data of a distribution network line is required to be acquired, basic information of the distribution network line is acquired from the image data, and a three-dimensional fine model of the distribution line under three typical application scenes of the distribution network line of an urban and rural junction, the distribution network line of a hilly area around the city and a plain area and the distribution network line is constructed by using a nonparametric three-dimensional modeling method and the basic information. The characteristics of different scenes are different and need to be analyzed separately. Wherein: the environment of the urban and rural junction is relatively complex, and various environmental factors such as green belts, road construction, vehicle and road environment and the like need to be considered when modeling the distribution network line; the terrain of hilly lands in the peri-urban mountain areas is uneven, and terrain features need to be considered and reflected when the distribution network lines are modeled; the environment of plain areas is relatively simple compared with the former two scenes, and only the environmental factors such as tree obstacles need to be considered when the distribution network line is modeled.
And S2, constructing a three-dimensional model of the distribution network line in a typical scene based on the image data of the distribution network line. The specific implementation process is as follows:
the distribution network line mainly comprises distribution equipment such as an overhead line, a pole tower, a cable, a distribution transformer and the like and accessory facilities, so that when the three-dimensional abstract modeling of the distribution line is carried out, all parts of the distribution line are decomposed according to the construction standard based on a non-parametric modeling method, the functional relationship among all parts is utilized for combination, the flexible three-dimensional reconstruction of the three-dimensional pole tower and the accessory parts of the distribution line is realized, and the construction of the three-dimensional model of the distribution network line can be divided into the following four steps:
s201, constructing an environment model, specifically:
the three-dimensional environment model file is automatically generated by adopting the technologies of image identification, multi-side texture extraction, automatic characteristic ground object extraction and the like, and the three-dimensional environment model containing the real scene of the terrain ground object is quickly manufactured according to the image data acquired by the unmanned aerial vehicle inspection. The terrain, ground object and scene three-dimensional modeling is that three-dimensional information of ground objects is extracted by adopting methods of contour extraction, surface patch fitting, roof reconstruction and the like on the basis of a high-precision digital ground model DSM through an image recognition technology, and meanwhile, omnibearing texture information of the ground objects is obtained by carrying out methods of image segmentation, edge extraction, texture clustering and the like on multi-view images. And finally, establishing a corresponding relation between geometric information and texture information of the ground features, and simultaneously performing integral uniform light and color carding to realize the orthographic processing of the multi-view image. The environment model comprises a terrain model and a ground feature model, and an example of the terrain model is shown in figure 2.
According to three typical application scenarios of the distribution line, buildings which may exist in all scenarios are analyzed and classified into the following five categories: urban public buildings, residential buildings, educational/sports/cultural buildings, industrial buildings, traffic hubs.
The urban public building comprises: urban complex, office building/office building, special building, hotel and other model types.
The residential area building comprises: high-rise buildings, low-rise buildings, commercial and residential buildings, shops, kindergartens, primary and secondary schools, hospitals, administrative offices and the like.
③ education/sports/culture building comprising: model types such as experimental buildings, libraries, stadiums, gymnasiums, student apartments and playgrounds.
The industrial building comprises: model types such as factory buildings, warehouses, scientific research buildings, industrial parks and the like.
The crossing hinge comprises: model types of airports, train stations, bus stations, etc.
S202, constructing a tower model, specifically:
firstly, carrying out external operation scanning on different types of towers in a typical scene to generate point cloud data, secondly, carrying out rough model line drawing and characteristic point extraction on the point cloud data through internal operation processing to further generate a rough three-dimensional model of the towers as shown in fig. 3, and finally, processing and generating refined models of all types of towers through drawing a toughened structure, model rendering and the like as shown in fig. 4.
S203, constructing a key component model, specifically:
the key parts of the distribution network line comprise an insulation hanging point, an iron tower mark, a flange plate bolt, a wire clamp, a lightning rod, a vibration damper and the like. By adopting advanced analysis methods and operation modes such as high-precision acquisition, component measurement, fine modification and the like, a high-quality three-dimensional model library of key components of the distribution network line can be obtained, and the accuracy of mapping results can reach centimeter level. And finally, performing digital differential correction by using the generated digital elevation model through regional color correction to generate a photo digital ortho-image map (DOM). After the production of the fast jigsaw is completed, the quality of the digital ortho-image of the picture is checked, and the problems and phenomena of image blurring, dislocation, distortion, deformation, loophole and the like are processed to obtain a key component model, as shown in fig. 5.
S204, component information entry, specifically:
the SQLite database is adopted to store information such as types, positions, sizes and numbers of distribution network towers, information such as types, lengths and brands of all key components, and database files support display and information updating of a PC end and a mobile end at the same time.
It should be noted that, in the above process, an environment model is first constructed, then a tower model is constructed on the basis of the environment model, a key component model is superimposed on the environment model and the tower model, and then component information is entered, that is, the next step in the above steps S201 to S204 is performed on the basis of the previous step.
The method for constructing the model in steps S201 to S203 mainly includes: the method comprises a three-dimensional modeling method of an object based on triangular texture mapping and a three-dimensional real-time modeling method based on auxiliary marks.
(1) The object three-dimensional modeling method based on the triangular texture mapping is mainly divided into five parts:
firstly, scanning an object placed on a turntable by using a Kinect v2, and rotating the turntable for one circle to obtain 30 frames of color point clouds;
secondly, the object is divided from the turntable and preprocessed, and abnormal values and noise are eliminated;
thirdly, aiming at the characteristic of partial overlap between adjacent point clouds, firstly, carrying out primary registration on the preprocessed adjacent frame point clouds by using a point-to-surface ICP algorithm, and deleting the misaligned parts for fine registration again;
fourthly, global optimization is carried out to eliminate accumulated errors, and a color three-dimensional point cloud model of the object is obtained after smooth filtering is carried out;
and finally, forming a grid by using a greedy triangulation algorithm, establishing a grid model of the object, and mapping the RGB texture of the object onto the surface of the object model to obtain a final model.
(2) A three-dimensional real-time modeling method based on auxiliary marks mainly comprises five steps:
firstly, scanning an object placed on a turntable by using a Kinect v2, and collecting point clouds once every 2 seconds for processing;
secondly, the object is divided from the turntable and preprocessed, and abnormal values and noise are eliminated;
and thirdly, extracting the mark points on the flat plate, dividing each mark point once, calculating the circle center coordinate of each mark point, and classifying the mark points to form a rigid body. In order to solve the problem that the calculation of the center coordinates is inaccurate due to uneven density of point clouds of the mark points, the center coordinates are more accurately calculated by a partition compensation method of a three-dimensional real-time modeling method based on auxiliary marks;
and fourthly, registering the rigid bodies constructed in the third step. Aiming at the registration problem of a rigid body formed by three points, a coordinate system algorithm is provided for calculating a rotation translation matrix;
and fifthly, fusing the object point clouds after each pretreatment into the global point clouds, and repeating the steps from the first step to the fourth step until the turntable is rotated for a circle, so as to generate a final object three-dimensional model.
S3, generating an initial path image based on the three-dimensional model of the distribution network line, and carrying out hidden danger calibration and correction on the initial path image; and generating an unmanned aerial vehicle path supporting the routing inspection of the key components of the distribution network based on the corrected initial path image. The specific implementation process is as follows:
s301, an initial path image of the unmanned aerial vehicle is generated rapidly through the GIS platform, hidden danger calibration and correction are conducted on the initial path image, and corrected track points are input into a three-dimensional model of the distribution network line.
In the embodiment of the invention, the initial path image of the unmanned aerial vehicle is quickly generated by virtue of the distribution network GIS platform in Shanxi province and stored as the KML file which can be read by the unmanned aerial vehicle flight control system, the trend of the line corridor, the position of the tower and the altitude information are recorded in the KML file, and the longitude and latitude, the sea wave height, the terrain capture time and the visual angle altitude of the line corridor and the tower can be truly reflected. However, the KML file generated rapidly by the distribution network GIS platform inevitably has the phenomena of inaccurate line position information or height deviation and the like, hidden danger calibration and correction are required to be carried out on track points of the unmanned aerial vehicle executing the inspection task, and the accuracy of the air route in flight operation and the effectiveness of an oblique photography result are ensured. And finally, inputting the corrected track point into a three-dimensional model of the distribution network line.
S302, generating an unmanned aerial vehicle path supporting routing inspection of key components of the distribution network by taking the most path as a target based on the track points in the three-dimensional model of the distribution network line. The method specifically comprises the following steps:
the unmanned aerial vehicle autonomously finishes the routing inspection operation, firstly, a flight path needs to be reasonably planned, the flight path is composed of a series of track points in a three-dimensional space, the track points comprise aerial points needing to be hovered and path points which must be passed through in order to safely reach the aerial points, and the unmanned aerial vehicle path supporting routing inspection of the key components of the distribution network is obtained through an A-star algorithm.
It should be noted that, in the embodiment of the present invention, when the unmanned aerial vehicle performs autonomous inspection operation, data collected by sensing equipment carried by the unmanned aerial vehicle, including pole towers, insulating hanging points, flange bolts, wire clamps, lightning rods, vibration dampers, and other key components of power distribution equipment, is transmitted back in real time. Before data processing work is carried out, integrity check and correctness check are carried out on data, whether the inspection work on the same day is completely finished or not is checked according to an inspection plan, whether omission exists or not is checked, whether pictures collected by the unmanned aerial vehicle are correct or not is checked, whether the inspection tower is correct or not is checked, whether a channel inspection path is correct or not is checked, and the like. In addition, image decompression, photo distortion correction, image enhancement and the like of flight shooting are needed, processed photos are clear, contrast is high, and high-quality data are provided for subsequent defect identification work and next unmanned aerial vehicle autonomous flight path planning.
And (3) performing adjustment aerial triangulation on the processed inspection operation data by adopting a light beam method local area network, simultaneously introducing a vertical image and an inclined image into the space-three calculation, introducing the inclined image and POS data, performing operation processing through the steps of extracting characteristic points, extracting homonymy image pairs, relative orientation, matching connection points, area network adjustment and the like, establishing a self-checking area network adjustment equation of element connection points, connection lines, control point coordinates and cradle head auxiliary data, obtaining a space-three result through joint calculation after the area network adjustment is qualified, and finally obtaining the result of aerial triangulation of the image in the shooting area.
The embodiment of the invention also provides a system for planning the autonomous flight path of the unmanned aerial vehicle on the distribution network line, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the steps of the method are realized when the processor executes the computer program.
It can be understood that the system for planning the autonomous flight path of the distribution network line unmanned aerial vehicle provided by the embodiment of the invention corresponds to the method for planning the autonomous flight path of the distribution network line unmanned aerial vehicle, and the explanation, the example, the beneficial effects and the like of the relevant contents can refer to the corresponding contents in the method for planning the autonomous flight path of the distribution network line unmanned aerial vehicle, and the details are not repeated here
In summary, compared with the prior art, the method has the following beneficial effects:
according to the method and the device, the initial path image is generated based on the three-dimensional model of the distribution network line, the hidden danger calibration correction is carried out on the initial path image, the unmanned aerial vehicle path supporting the routing inspection of the key parts of the distribution network is generated, the initial path image of the unmanned aerial vehicle is calibrated through the hidden danger, the obstacle avoidance under the complex power line environment is realized, the safety factor of the unmanned aerial vehicle routing inspection is improved, and the routing inspection risk is reduced.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A distribution network line unmanned aerial vehicle autonomous flight path planning method is characterized by comprising the following steps:
acquiring image data of a distribution network line;
constructing a three-dimensional model of the distribution network line under a typical scene based on the image data of the distribution network line;
and generating an initial path image based on the three-dimensional model of the distribution network line, and carrying out hidden danger calibration and correction on the initial path image to generate an unmanned aerial vehicle path supporting routing inspection of key components of the distribution network.
2. The method for planning the autonomous flight path of the distribution network line unmanned aerial vehicle of claim 1, wherein the constructing of the three-dimensional model of the distribution network line in a typical scene based on the image data of the distribution network line comprises:
constructing an environmental three-dimensional model based on the image data;
constructing a tower three-dimensional model based on the image data;
constructing a three-dimensional model of the key component based on the image data;
and inputting component information.
3. The method for planning the autonomous flight path of the unmanned aerial vehicle with the network distribution line according to claim 2, wherein the constructing the three-dimensional model of the environment based on the image data comprises:
and automatically generating a three-dimensional environment model file by adopting image identification, multi-side texture extraction and automatic characteristic ground object extraction, and manufacturing an environment three-dimensional model according to image data acquired by unmanned aerial vehicle inspection.
4. The method of claim 3, wherein the three-dimensional model of the environment comprises: a terrain model and a ground object model;
wherein:
the terrain model construction method comprises the following steps:
on the basis of a high-precision digital earth surface model DSM, extracting three-dimensional information of the ground object by adopting contour extraction, surface patch fitting and roof reconstruction through an image identification technology, and simultaneously carrying out image segmentation, edge extraction and texture clustering on a multi-view image to obtain all-directional texture information of the ground object; and establishing a corresponding relation between geometric information and texture information of the ground features, and simultaneously performing integral uniform light and color carding to realize orthographic processing of multi-view images and construct a terrain model.
5. The method for planning the autonomous flight path of the unmanned aerial vehicle with the network distribution line according to claim 2, wherein the constructing a tower three-dimensional model based on the image data comprises:
carrying out external operation scanning on different types of towers in a typical scene to generate point cloud data;
performing rough model line drawing and feature point extraction on point cloud data through internal operation processing to generate a rough three-dimensional model of the tower;
and processing and generating refined models of all types of towers by drawing a toughened structure and rendering the models.
6. The method for planning the autonomous flight path of the unmanned aerial vehicle with the network distribution line according to claim 2, wherein the constructing a three-dimensional model of the key component based on the image data comprises:
obtaining a high-quality three-dimensional model library of key components of the distribution network line by adopting an analysis method and an operation mode of high-precision acquisition, component measurement and fine modification;
performing digital differential correction by using the generated digital elevation model through regional color correction to generate a photo digital orthophoto image;
and inspecting the quality of the digital ortho-image of the photo, and processing the problems and phenomena of image blurring, dislocation, distortion, deformation and leak to obtain a three-dimensional model of the key component.
7. The method for planning the autonomous flight path of the distribution network line unmanned aerial vehicle according to claim 1, wherein the generating of the initial path image based on the distribution network line three-dimensional model, the performing of hidden danger calibration and correction on the initial path image, and the generating of the unmanned aerial vehicle path supporting routing inspection of the distribution network key components comprises:
an initial path image of the unmanned aerial vehicle is rapidly generated through a GIS platform, hidden danger calibration and correction are carried out on the initial path image, and corrected track points are input into a three-dimensional model of a distribution network line;
and generating an unmanned aerial vehicle path supporting distribution network key component inspection by taking the maximum path as a target based on the waypoints in the three-dimensional model of the distribution network line.
8. A system for planning an autonomous flight path of a distribution network line unmanned aerial vehicle, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.
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