Navigation method and system for entering equipotential path based on three-dimensional point cloud

Abstract

The invention discloses an equipotential entering path navigation method and system based on three-dimensional point cloud. The method comprises the following steps: acquiring transmission tower data; preprocessing the data of the transmission tower to construct a three-dimensional model of the transmission tower; carrying out point cloud feature analysis on the three-dimensional model and carrying out feature extraction on a field operation environment to obtain path data; setting a path constraint condition based on the path data; inputting the path data into a path planning model, and generating a path in combination with a path constraint condition; and forming a virtual point in the three-dimensional model, and moving the virtual point according to the generated path to judge the feasibility of the path. According to the method, transmission tower and environment data are acquired, a three-dimensional model is constructed, path analysis is more accurately carried out, path constraint conditions are set, the most appropriate path is generated, verification is carried out through virtual points, it is ensured that operators are always at the same potential, accidents are reduced, the operation difficulty is lowered, and the emergency processing capacity can be enhanced in combination with the VR technology.

Description

Technical Field

[0001] The present invention relates to the technical field of live transmission line operations, and in particular to a navigation method and system for entering an equipotential path based on a three-dimensional point cloud. Background Art

[0002] A notable feature of live transmission line work is the use of equipotential work, that is, the operator enters the high-voltage conductor through insulating tools and is at the same potential as the conductor. The key to equipotential work is to choose the appropriate entry path and method, and the personal safety of the operator must be ensured when entering and exiting the equipotential. This method of operation requires the operator to contact the high-voltage conductor through insulating tools (such as insulating ladders, insulating platforms, insulating hanging baskets, etc.) when entering the high-voltage conductor area, and to ensure that the operator is at the same potential as the high-voltage conductor through appropriate equipment (such as shielding clothing, insulating gloves, insulating boots, etc.). This can prevent the current from passing through the human body, thereby ensuring the safety of the operator.

[0003] However, in actual operation, when the operator enters the high-voltage conductor through the insulating tool, there is often a phenomenon that the position of the operator deviates from the designed path. This deviation may cause the operator to fail to be completely at the same potential as the high-voltage conductor, thus posing certain safety hazards. Specifically, when the position of the operator deviates from the predetermined path, the following situations may occur: 1. Potential difference is generated. If the position of the operator deviates greatly, they may not be completely in contact with the high-voltage conductor, resulting in part of the body still being at a different potential, which will cause current to pass through the human body and cause electric shock accidents. 2. Insulation failure, that is, the design of insulating tools is usually based on a specific path and position. If the position of the operator deviates, some parts of the insulating tool may fail to effectively play an insulating role, thereby increasing the risk of electric shock. 3. Difficult operation, that is, position deviation may also cause the operator to encounter difficulties during the operation, such as being unable to accurately contact the part that needs to be repaired, or requiring additional operating steps to adjust the position, which not only increases the operation time, but also may increase safety risks due to frequent position adjustments. Therefore, there is an urgent need for a safe and efficient equipotential path navigation method. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a navigation method and system for entering an equipotential path based on a three-dimensional point cloud to solve the problems that during current equipotential operations, the path may be deviated, a potential difference may be generated, insulation failure may occur, the route arrangement may not be reasonable, and operation may be difficult.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for navigating into an equipotential path based on a three-dimensional point cloud, comprising: acquiring transmission tower data;

[0008] Preprocessing the transmission tower data to construct a three-dimensional model of the transmission tower;

[0009] Performing point cloud feature analysis on the three-dimensional model and extracting features on the on-site working environment to obtain path data;

[0010] Set path constraints based on path data;

[0011] Inputting the path data into the path planning model and generating a path in combination with the path constraint conditions;

[0012] A virtual point is formed in the three-dimensional model, and the virtual point moves according to the generated path to determine the feasibility of the path.

[0013] As a preferred solution of the method for navigating into an equipotential path based on a three-dimensional point cloud according to the present invention, the three-dimensional model of a transmission tower is constructed, including:

[0014] Performing surface reconstruction based on the preprocessed data, calculating the normal direction of each point in the point cloud data, and using the Poisson reconstruction algorithm to generate a surface model of the transmission tower to obtain a first model;

[0015] The first model is optimized, including simplification, smoothing and repairing, to obtain a final three-dimensional model.

[0016] As a preferred solution of the equipotential path navigation method based on three-dimensional point cloud described in the present invention, point cloud feature analysis is performed on the three-dimensional model and feature extraction is performed on the on-site working environment to obtain path data, including:

[0017] Extract the geometric features and topological relationships of transmission towers;

[0018] Extract terrain features, obstacle locations and types, and voltage distribution of the environment;

[0019] Combine the extracted data and integrate them into path data.

[0020] As a preferred solution of the equipotential path navigation method based on three-dimensional point cloud described in the present invention, path constraint conditions are set based on path data, including:

[0021] Set safety constraints, including: minimum safety distance, maximum slope, minimum turning radius, and voltage difference limit;

[0022] Set path accessibility constraints, including: maximum road load capacity and avoidable obstacles;

[0023] Set efficiency goals, including: shortest path and fewest turns.

[0024] As a preferred solution of the equipotential path navigation method based on three-dimensional point cloud described in the present invention, the path data is input into the path planning model, and the path is generated in combination with the path constraint conditions, including:

[0025] Input the path data into the A* algorithm model;

[0026] Set the path starting point and path end point, and define the heuristic function and cost function in the model;

[0027] The heuristic function is calculated by combining the minimum safe distance between the path and the dangerous area;

[0028] Combined with the maximum slope and the minimum turning radius, the voltage difference between any point on the path and the high-voltage wire is calculated. If the voltage difference does not exceed the safety threshold, the node is expanded;

[0029] Perform path search until the end of the path is found and generate the path.

[0030] As a preferred solution of the method for navigating into an equipotential path based on a three-dimensional point cloud according to the present invention, a virtual point is formed in a three-dimensional model, and the virtual point moves according to the generated path, including:

[0031] Divide the generated path into segments, with each segment serving as a moving step;

[0032] Mark the current position of the virtual point;

[0033] Determine the next target position of the virtual point, calculate the intermediate position of the virtual point at each step through linear interpolation, and obtain the moving route and status of the virtual point;

[0034] According to the speed of the virtual point, the time interval of each step is calculated to obtain the time consumed in the movement of the virtual point.

[0035] As a preferred solution of the method for navigating an equipotential path based on a three-dimensional point cloud according to the present invention, determining the feasibility of the path includes:

[0036] Based on the acquired virtual point movement route and status, determine whether the minimum safe distance to the dangerous area is reached and whether the voltage difference is within the safety threshold range;

[0037] Based on the time spent moving around the lake, determine whether the efficiency meets the target time;

[0038] If the path does not enter the dangerous area, the voltage difference is within the safety threshold range, and the target time is met, the path is determined to be feasible.

[0039] In a second aspect, the present invention provides a navigation system for entering an equipotential path based on a three-dimensional point cloud, comprising: a data acquisition module for acquiring transmission tower data;

[0040] A model building module, used for preprocessing the transmission tower data to build a three-dimensional model of the transmission tower;

[0041] A feature extraction module is used to perform point cloud feature analysis on the three-dimensional model and extract features from the on-site working environment to obtain path data;

[0042] A constraint setting module, used to set path constraint conditions based on path data;

[0043] A path generation module, used to input the path data into the path planning model and generate a path in combination with the path constraint conditions;

[0044] The judgment control module is used to form a virtual point in the three-dimensional model, and the virtual point moves according to the generated path to determine the feasibility of the path.

[0045] In a third aspect, the present invention provides a computing device, comprising:

[0046] Memory and processor;

[0047] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for entering an equipotential path navigation based on a three-dimensional point cloud are implemented.

[0048] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for navigating into an equipotential path based on a three-dimensional point cloud.

[0049] Compared with the prior art, the present invention has the following beneficial effects: the present invention obtains transmission tower and environmental data, builds a three-dimensional model, conducts path analysis more clearly and accurately, sets corresponding path constraints, and generates the most suitable and safe path based on operational requirements through real-time monitoring and calculation of the voltage difference between each point on the path and the high-voltage wire. It can also ensure that the operators are always at the same potential, greatly reducing the risk of electric shock accidents, avoiding collisions between operators and obstacles such as trees and buildings, reducing the occurrence of accidents, and reducing the difficulty of operation for operators. It can also combine VR technology to keep in touch with the ground command center, adjust operations in a timely manner, and enhance emergency handling capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0051] Figure 1 The figure is a schematic diagram of the overall process of a method for navigating into an equipotential path based on a three-dimensional point cloud according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0053] Example 1

[0054] Reference Figure 1 , as an embodiment of the present invention, provides a method for navigating into an equipotential path based on a three-dimensional point cloud, comprising:

[0055] S100: Acquire transmission tower data;

[0056] S200: pre-processing the transmission tower data to construct a three-dimensional model of the transmission tower;

[0057] S300: Perform point cloud feature analysis on the three-dimensional model and extract features on the on-site working environment to obtain path data;

[0058] S400: Setting path constraints based on path data;

[0059] S500: inputting the path data into the path planning model, and generating a path in combination with the path constraint conditions;

[0060] S600: forming a virtual point in the three-dimensional model, and moving the virtual point according to the generated path to determine the feasibility of the path.

[0061] It should be noted that a notable feature of live transmission line operations is the use of equipotential operations, that is, the operator enters the high-voltage conductor through insulating tools and is at the same potential as the conductor. The key to equipotential operations is to select a suitable entry path and method, and the personal safety of the operator must be ensured when entering and exiting the equipotential. Through the above steps S100-S600, different paths can be set based on the three-dimensional model and the operation requirements, and feasibility tests can be performed.

[0062] For example, setting the constraint conditions of potential difference to ensure the safety of the set path. Based on the safe route, you can also add route passing conditions, turning conditions or time conditions. Through the path planning model, you can realize the generation of paths with different requirements, and combine the movement of virtual points to make a second judgment on the feasibility of the path. Through detailed three-dimensional modeling and path planning, you can ensure that the designed path is accurate, doubly protect the work safety of the operators, and reduce errors caused by improper path design. It can also reduce equipment damage caused by uneven paths or collisions with obstacles, and reduce the cost of repairing and replacing equipment.

[0063] Example 2

[0064] Reference Figure 1 , which is an embodiment of the present invention, provides a navigation method for entering an equipotential path based on a three-dimensional point cloud based on the previous embodiment, comprising:

[0065] In the embodiment of the present application, the transmission tower data is acquired in step S100 by driving the laser radar scanning module to fly through the drone, and during the flight, the transmission tower is scanned by the laser radar scanning module.

[0066] In an optional implementation, the transmission tower data in step S100 may also be acquired through field measurement, including: precise measurement using a total station, GPS, or other equipment.

[0067] In another optional implementation, the transmission tower data in step S100 may also be acquired by remote sensing technology, that is, by using remote detection equipment such as drones and satellites to acquire high-resolution images or video data.

[0068] In the embodiment of the present application, the transmission tower data acquired in step S100 includes: point cloud data, structural data and electrical data. Among them: point cloud data includes three-dimensional coordinates, reflection intensity, etc.; structural data includes tower height, tower width, inclination and connection relationship, etc.; electrical data includes voltage level, current intensity, phase information and insulation performance, etc.

[0069] It should be noted that the three-dimensional coordinates in the point cloud data provide precise location information of the transmission tower and its surrounding environment; the structural data can provide detailed structural information of the transmission tower, which helps to build an accurate three-dimensional model; and the electrical data can ensure that electrical safety is taken into account when planning the path.

[0070] In an optional implementation, the transmission tower data acquired in step S100 may also include remote sensing images, elevation data, or operation tool data, etc., which are suitable for later work requirements.

[0071] In the embodiment of the present application, in step S200, the transmission tower data is preprocessed, including point cloud data obtained by means of LiDAR or the like, and denoising, filtering and other preprocessing are performed to obtain preprocessed data.

[0072] In an optional implementation, the transmission tower data is preprocessed in step S200, and descriptive statistical analysis may also be included to calculate the central trend (such as mean, median, etc.), dispersion (such as variance, standard deviation, etc.), distribution (such as histogram, box plot, etc.) and correlation of the data, so as to provide a certain data basis for the three-dimensional model.

[0073] In another optional implementation, the preprocessing of the transmission tower data in step S200 may also include inferential statistical analysis: based on the results of descriptive statistics, inferential statistical analysis, including regression analysis, variance analysis, etc., may be performed to ensure that power data such as voltage is in a normal state.

[0074] In the embodiment of the present application, constructing a three-dimensional model of a transmission tower in step S200 includes the following steps A1-A2:

[0075] In A1: surface reconstruction is performed based on the preprocessed data, the normal direction of each point in the point cloud data is calculated, and a surface model of the transmission tower is generated using a Poisson reconstruction algorithm to obtain a first model;

[0076] In an optional implementation, the surface reconstruction of the three-dimensional model of the transmission tower in step S200 may also be performed by Delaunay triangulation: connecting points in the point cloud data into a triangular mesh to approximate the surface of the original object.

[0077] In another optional implementation, the surface reconstruction of the three-dimensional model of the transmission tower in step S200 can also be performed by the Alpha Shape algorithm: by defining a shape parameter α to identify the core area in the point cloud and constructing a surface model of the area. Or, the moving least squares method (MLS): by locally fitting a plane or a surface to smooth the point cloud data and construct a smoother surface model.

[0078] In A2: the first model is optimized, including simplification, smoothing and repairing, to obtain a final three-dimensional model.

[0079] Specifically, the Quadric Decimation algorithm can be used to simplify the model, reduce the number of polygons, and improve rendering efficiency; the Laplacian smoothing algorithm can be used to smooth the model surface to reduce jagged edges and irregular shapes; and the HoleFilling algorithm can be used to fill holes in the model to ensure the integrity of the model.

[0080] It should be noted that constructing a three-dimensional model of the transmission tower based on the preprocessed data can provide an intuitive visualization tool to help analyze and plan the path.

[0081] In the embodiment of the present application, step S300 performs point cloud feature analysis on the three-dimensional model and extracts features of the on-site working environment to obtain path data, including:

[0082] Extract the geometric features and topological relationships of transmission towers;

[0083] In the embodiment of the present application, the geometric features may specifically include: height, width, tilt angle, etc.; the topological relationship includes the relative position and connection relationship between transmission towers.

[0084] Extract terrain features, obstacle locations and types, and voltage distribution of the environment;

[0085] In the embodiment of the present application, terrain features include extraction of slope, slope direction, etc.; obstacle locations include power lines, trees, buildings, etc.; voltage distribution includes voltage level and phase information of each conductor.

[0086] Combine the extracted data and integrate them into path data.

[0087] It should be noted that the path data includes various data required to generate path planning, such as starting point, end point, key nodes, etc., which can provide basic information for path planning.

[0088] In the embodiment of the present application, setting the path constraint condition based on the path data in step S400 includes:

[0089] Set safety constraints, including: minimum safety distance, maximum slope, minimum turning radius, and voltage difference limit;

[0090] Specifically, the voltage difference is limited by setting a safety threshold (such as 1kV or 0.5kV, etc.);

[0091] Set path accessibility constraints, including: maximum road load capacity and avoidable obstacles;

[0092] Set efficiency goals, including: shortest path and fewest turns.

[0093] In an optional implementation, the path constraint conditions may also include meteorological conditions such as wind speed limit and temperature limit, and load capacity of the operating equipment;

[0094] In an optional implementation, the path constraint may also include backup paths to cope with emergencies, such as equipment failure, weather changes, etc., or multi-task coordination to avoid conflicts and duplication of work.

[0095] In the embodiment of the present application, in step S500, the path data is input into the path planning model, and the path is generated in combination with the path constraint conditions, including:

[0096] Input the path data into the A* algorithm model;

[0097] Set the path starting point and path end point, and define the heuristic function h(n) and cost function g(n) in the model;

[0098] The heuristic function is calculated by combining the minimum safe distance between the path and the dangerous area;

[0099] Combined with the maximum slope and the minimum turning radius, the voltage difference between any point on the path and the high-voltage wire is calculated. If the voltage difference does not exceed the safety threshold, the node is expanded.

[0100] Perform path search until the end of the path is found and generate the path.

[0101] Specifically, select the node n with the smallest f(n)=g(n)+h(n) from the open list;

[0102] Move n from the open list to the closed list;

[0103] Expand n's neighbor nodes and calculate their g and h values;

[0104] If the neighbor node is not in the open list, add it to the open list; if it is already in the open list, update its g and f values;

[0105] Repeat the above steps until the end point is found or the open list is empty.

[0106] It should be noted that the A* algorithm is a heuristic search algorithm suitable for finding the shortest path. It can consider multiple safety constraints in path planning and optimize multiple goals, such as the shortest path, the minimum number of turns, the minimum voltage difference, etc., to ensure that the generated path is optimal in multiple aspects. It can also support dynamic adjustment, and can update the path in real time during the path planning process to adapt to environmental changes. For example, if new obstacles or environmental changes are found, the path can be replanned.

[0107] In an optional implementation, the path planning model in step S500 may also be generated by a Dijkstra algorithm, which is applicable to the shortest path without negative-weighted edges.

[0108] In another optional implementation, the path planning model in step S500 may also be generated by an RRT algorithm.

[0109] In the embodiment of the present application, in step S600, a virtual point is formed in the three-dimensional model, and the virtual point moves according to the generated path, including:

[0110] Divide the generated path into segments, with each segment serving as a moving step;

[0111] Mark the current position of the virtual point;

[0112] Determine the next target position of the virtual point, calculate the intermediate position of the virtual point at each step through linear interpolation, and obtain the moving route and status of the virtual point;

[0113] According to the speed of the virtual point, the time interval of each step is calculated to obtain the time consumed in the movement of the virtual point.

[0114] In an optional embodiment, the movement of the virtual point according to the generated path in step S600 can also be achieved through spline interpolation. Spline interpolation (such as B-spline or cubic spline) is used to smooth the path and calculate the middle position of the virtual point at each step. This can generate a smooth path, reduce sudden changes in the path, and improve the smoothness of the movement of the virtual point.

[0115] In another optional implementation, the movement of the virtual point according to the generated path in step S600 can also be achieved through a dynamic window method. The dynamic window method (DWA) is used to calculate the motion trajectory of the virtual point in real time to ensure that the virtual point avoids obstacles and maintains a safe distance during movement. The motion trajectory of the virtual point can be adjusted in real time to adapt to environmental changes.

[0116] In the embodiment of the present application, determining the path feasibility in step S600 includes:

[0117] Based on the acquired virtual point movement route and status, determine whether the minimum safe distance to the dangerous area is reached and whether the voltage difference is within the safety threshold range;

[0118] Based on the time spent moving around the lake, determine whether the efficiency meets the target time;

[0119] If the path does not enter the dangerous area, the voltage difference is within the safety threshold range, and the target time is met, the path is determined to be feasible.

[0120] In an optional implementation, the feasibility of the path in step S600 may also be determined through Monte Carlo simulation, that is, the movement process of virtual points is simulated through a large number of random samples to evaluate the feasibility and safety of the path.

[0121] In another optional implementation, the determination of path feasibility in step S600 may also be performed through path evaluation based on machine learning.

[0122] It should be noted that based on the above scheme, after determining that the path is feasible in step S600, VR glasses can be worn on the person's head. Thereafter, the designed path can be displayed through the VR glasses. After the display, the person can enter according to the designed path. During the entry process, the position of the VR glasses will be located through the positioning module and displayed in the three-dimensional model. In addition, the intercom module will enable the personnel to communicate so as to guide the personnel.

[0123] Example 3

[0124] The above is a schematic scheme of a method for navigating into an equipotential path based on a three-dimensional point cloud in this embodiment. It should be noted that the technical scheme of the system for navigating into an equipotential path based on a three-dimensional point cloud and the technical scheme of the method for navigating into an equipotential path based on a three-dimensional point cloud belong to the same concept. For details not described in detail in the technical scheme of the system for navigating into an equipotential path based on a three-dimensional point cloud in this embodiment, please refer to the description of the technical scheme of the method for navigating into an equipotential path based on a three-dimensional point cloud.

[0125] This embodiment also provides a system for a navigation method for entering an equipotential path based on a three-dimensional point cloud, comprising: a data acquisition module for acquiring transmission tower data;

[0126] A model building module, used for preprocessing transmission tower data and building a three-dimensional model of the transmission tower;

[0127] Feature extraction module, used to perform point cloud feature analysis on the 3D model and feature extraction on the on-site working environment to obtain path data;

[0128] A constraint setting module, used to set path constraint conditions based on path data;

[0129] A path generation module is used to input the path data into the path planning model and generate a path in combination with path constraints;

[0130] The judgment control module is used to form virtual points in the three-dimensional model, and the virtual points move according to the generated path to determine the feasibility of the path.

[0131] This embodiment also provides a computing device, which is suitable for the situation of entering an equipotential path navigation based on a three-dimensional point cloud, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the method of entering an equipotential path navigation based on a three-dimensional point cloud as proposed in the above embodiment.

[0132] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for navigating into an equipotential path based on a three-dimensional point cloud as proposed in the above embodiment is implemented.

[0133] The storage medium proposed in this embodiment and the method for implementing navigation into an equipotential path based on a three-dimensional point cloud proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0134] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by means of software and necessary general-purpose hardware, and of course can also be implemented by hardware.

[0135] Based on this understanding, the technical solution of the present invention can essentially or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of the various embodiments of the present invention.

[0136] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A navigation method for entering an equipotential path based on a three-dimensional point cloud, characterized in that: include: Obtain transmission tower data; Preprocessing the transmission tower data to construct a three-dimensional model of the transmission tower; Performing point cloud feature analysis on the three-dimensional model and extracting features on the on-site working environment to obtain path data; Set path constraints based on path data; Inputting the path data into the path planning model and generating a path in combination with the path constraint conditions; A virtual point is formed in the three-dimensional model, and the virtual point moves according to the generated path to determine the feasibility of the path.

2. The method for navigating into an equipotential path based on a three-dimensional point cloud as claimed in claim 1, characterized in that: Construct a 3D model of a transmission tower, including: Performing surface reconstruction based on the preprocessed data, calculating the normal direction of each point in the point cloud data, and using the Poisson reconstruction algorithm to generate a surface model of the transmission tower to obtain a first model; The first model is optimized, including simplification, smoothing and repairing, to obtain a final three-dimensional model.

3. The method for navigating into an equipotential path based on a three-dimensional point cloud as claimed in claim 1 or 2, characterized in that: Performing point cloud feature analysis on the three-dimensional model and extracting features on the on-site working environment to obtain path data includes: Extract the geometric features and topological relationships of transmission towers; Extract terrain features, obstacle locations and types, and voltage distribution of the environment; Combine the extracted data and integrate them into path data.

4. The method for navigating into an equipotential path based on a three-dimensional point cloud as claimed in claim 3, characterized in that: Based on the path data, set path constraints, including: Set safety constraints, including: minimum safety distance, maximum slope, minimum turning radius, and voltage difference limit; Set path accessibility constraints, including: maximum road load capacity and avoidable obstacles; Set efficiency goals, including: shortest path and fewest turns.

5. The method for navigating into an equipotential path based on a three-dimensional point cloud as claimed in claim 4, characterized in that: Inputting the path data into the path planning model and generating a path in combination with the path constraint conditions includes: Input the path data into the A* algorithm model; Set the path starting point and path end point, and define the heuristic function and cost function in the model; The heuristic function is calculated by combining the minimum safe distance between the path and the dangerous area; Combined with the maximum slope and the minimum turning radius, the voltage difference between any point on the path and the high-voltage wire is calculated. If the voltage difference does not exceed the safety threshold, the node is expanded; Perform path search until the end of the path is found and generate the path.

6. The method for navigating into an equipotential path based on a three-dimensional point cloud as claimed in claim 5, characterized in that: A virtual point is formed in the 3D model, and the virtual point moves according to the generated path, including: Divide the generated path into segments, with each segment serving as a moving step; Mark the current position of the virtual point; Determine the next target position of the virtual point, calculate the intermediate position of the virtual point at each step through linear interpolation, and obtain the moving route and status of the virtual point; According to the speed of the virtual point, the time interval of each step is calculated to obtain the time consumed in the movement of the virtual point.

7. The method for navigating into an equipotential path based on a three-dimensional point cloud as claimed in claim 6, characterized in that: Determining the feasibility of the path includes: Based on the acquired virtual point movement route and status, determine whether the minimum safe distance to the dangerous area is reached and whether the voltage difference is within the safety threshold range; Based on the time spent moving around the lake, determine whether the efficiency meets the target time; If the path does not enter the dangerous area, the voltage difference is within the safety threshold range, and the target time is met, the path is determined to be feasible.

8. A system applied to the method for navigating into an equipotential path based on a three-dimensional point cloud as described in any one of claims 1 to 7, characterized in that: include: A data acquisition module, used to acquire transmission tower data; A model building module, used for preprocessing the transmission tower data to build a three-dimensional model of the transmission tower; A feature extraction module is used to perform point cloud feature analysis on the three-dimensional model and extract features from the on-site working environment to obtain path data; A constraint setting module, used to set path constraint conditions based on path data; A path generation module, used to input the path data into the path planning model and generate a path in combination with the path constraint conditions; The judgment control module is used to form a virtual point in the three-dimensional model, and the virtual point moves according to the generated path to determine the feasibility of the path.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for entering an equipotential path navigation based on a three-dimensional point cloud as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for navigating into an equipotential path based on a three-dimensional point cloud as described in any one of claims 1 to 7.

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