Climbing robot system for controlling operation process of angle steel tower of power transmission line

Abstract

The invention discloses a climbing robot system for controlling the operation process of an angle steel tower of a power transmission line, and relates to the field of robots, machine vision and electric power safety monitoring. The system comprises a climbing robot body, a remote control and data acquisition unit and an intelligent identification and management and control platform. The climbing robot body adopts a crawler-type magnetic adsorption structure and is equipped with an elastic self-adaptive obstacle crossing mechanism, so that the climbing robot body can realize reliable adsorption and autonomous movement of crossing obstacles on the complex and uneven surface of the angle steel tower. The system is integrated with a high-definition visual acquisition module, and carries out real-time monitoring and normative judgment on key behaviors such as safety belt hanging and construction operation processes of high-altitude operation personnel based on a deep learning algorithm through an intelligent identification and management and control platform. Meanwhile, the system adopts a three-dimensional dynamic path planning technology to guide the robot to efficiently inspect on the tower material. The system has the advantages of low high-altitude operation risk, high detection precision, high automation degree and the like.

Description

Technical Field

[0001] This invention relates to the fields of robotics, computer vision, and power safety production monitoring technology, and in particular to a climbing robot system for controlling the operation process of angle steel towers for power transmission lines. Background Technology

[0002] The tower erection and line stringing of transmission lines is a core component of power engineering construction and operation. However, its operational scenarios are characterized by significant uniqueness and high risk. Traditional operating methods and existing technologies are insufficient to meet the stringent safety management requirements. Specific issues are as follows: Traditional methods of tower erection and line stringing for power transmission lines present significant challenges to safety risk management. These operations are typically high-altitude and fieldwork, often conducted in or near-energized environments, with the work primarily involving complex geometric structures such as angle steel towers. The harsh working environment not only significantly increases the difficulty of the work but also exposes workers to extremely high personal safety risks. Traditional safety management methods rely mainly on manual on-site supervision and random checks, which have inherent flaws: firstly, they struggle to achieve real-time, continuous monitoring of the entire operational process, easily creating blind spots and regulatory loopholes; secondly, monitoring critical safety aspects such as the proper installation of safety belts and compliance with work procedures is not only inefficient but also heavily influenced by subjective human judgment, failing to ensure strict and consistent adherence to safety management requirements and making it difficult to fundamentally mitigate safety risks.

[0003] To address these challenges, specialized robot technology is increasingly being applied in related fields. However, existing specialized robot technologies still have many limitations and cannot effectively adapt to the operational scenarios of power transmission angle steel towers. In terms of mobility and adhesion, existing high-altitude operation or inspection robots on the market, using suction cups, wheels, or simple magnetic adhesion, are only suitable for smooth planes or cylindrical surfaces. Power transmission angle steel towers, however, consist of numerous angle steel members, inclined members, and connecting plates, forming a complex non-planar structure. Existing robots not only struggle to meet the adhesion requirements of such complex structures but also lack the ability to overcome obstacles during operation, often resulting in restricted movement or unstable adhesion, severely impacting operational reliability. Regarding intelligent control capabilities, most existing inspection robots can only achieve basic data collection and video transmission functions, lacking core capabilities based on advanced technologies such as artificial intelligence and deep learning. They cannot perform key control actions such as intelligent recognition of operational procedures, analysis of personnel behavior, and real-time early warning of safety risks. They cannot automatically assess and intervene in the safety compliance of high-altitude operations and cannot replace manual labor for effective safety control.

[0004] In summary, a prominent technical contradiction exists in the industry: the rigid demand for safety management in high-altitude power transmission line tower erection operations clashes with the inefficiency of traditional manual supervision methods, the insufficient adaptability of existing specialized robot technologies, and their low level of intelligence. Against this backdrop, there is an urgent need to develop a novel climbing robot system. This system must integrate reliable climbing mechanisms, precise path planning technology, and high-precision intelligent recognition technology to overcome the technical challenges of achieving automated, intelligent, and real-time comprehensive management of operations on high-altitude, complex-structured power transmission angle steel towers. This would fill existing technological gaps and ensure the safe and efficient operation of power transmission lines. Summary of the Invention

[0005] In order to overcome the defects in the prior art, the present invention provides a climbing robot system for the operation and control of angle steel towers for power transmission lines. This system solves the technical problems of high safety hazards and low efficiency in the traditional manual supervision mode during the tower erection and line stringing operations of existing power transmission lines, as well as the poor adaptability of existing climbing robots to complex angle steel tower structures and the lack of intelligent control capabilities.

[0006] To achieve the above objectives, the present invention adopts the following technical solution, including: A climbing robot system for controlling the operation of angle steel towers for power transmission lines includes: a climbing robot body, a remote control and communication unit, and an intelligent identification and control platform; The robot is controlled to move and adjust its posture on the surface of the angle steel tower of the power transmission line, and to collect data. The collected data includes video streams of high-altitude operations, images of key parts of the power transmission facility, as well as the robot's posture and environmental parameters. The remote control and communication unit communicates wirelessly with the climbing robot body in two directions to achieve remote control and data transmission; The intelligent identification and control platform receives data streams transmitted back from the climbing robot and performs high-altitude operation standardization inspections and power transmission facility defect detection based on the transmitted data streams. The intelligent identification and control platform also performs path planning and navigation for the climbing robot based on the transmitted data streams and sends motion control command sequences to the climbing robot for execution through the remote control and communication unit.

[0007] Preferably, the specific process of route planning and navigation is as follows: An environmental map is constructed based on the three-dimensional geometric model of the angle steel tower, and real-time positioning is achieved by combining the IMU data and lidar data of the climbing robot itself. The RRT algorithm is used to calculate the optimal three-dimensional dynamic climbing path that meets the structural constraints of the tower. The optimal climbing path is converted into a sequence of motion control commands and sent to the climbing robot for execution.

[0008] Preferably, the specific process for high-altitude operation compliance inspection is as follows: Convolutional neural networks are used to perform real-time detection on the video stream transmitted back by the climbing robot, and to detect and output the bounding boxes and confidence scores of key targets such as workers, safety helmets, safety belt hooks, and attachment points. Based on the detection results, analyze the geometric relationship and temporal motion state between key targets to determine whether the worker's safety belt is physically anchored or whether there is any violation of operating procedures, and whether the safety helmet is worn or whether there is any violation of operating procedures. When a violation is determined to be non-compliant or illegal, an audible and visual warning will be triggered within a set time.

[0009] Preferably, the specific process for detecting defects in power transmission facilities is as follows: The climbing robot moves to a key part of the power transmission facility and collects corresponding images; By employing a defect detection algorithm and introducing context coding and saliency analysis mechanisms, the ability to extract subtle global and local features of images is enhanced, enabling accurate location and classification of defects in key parts of power transmission facilities. These defects include missing bolts, component damage, and corrosion on the tower surface.

[0010] Preferably, the climbing robot body includes: Tracked magnetic adsorption walking mechanism: used to provide adsorption force and walking driving force; Elastic adaptive obstacle crossing mechanism: used to assist the body in crossing tower material obstacles and automatically adjust the climbing posture; Information acquisition module: integrates a camera, inertial measurement unit and lidar, used to acquire images, videos, as well as body attitude and environmental parameters.

[0011] Preferably, the tracked magnetic adsorption walking mechanism is as follows: At least two sets of brushless DC motors are used as drive units to independently drive the tracks on both sides to achieve walking and steering; The permanent magnet array used to provide adsorption force is arranged in a matrix, in the form of a Halbach array, to increase the effective adsorption force on the angle steel tower material.

[0012] Preferably, the elastic adaptive obstacle-crossing mechanism is as follows: Composed of a linkage and joint mechanical structure, it is used to connect the walking mechanism to the main body; when the main body moves to the obstacle of the angle steel tower, it automatically or remotely adjusts the relative height and angle between the walking mechanism and the main body.

[0013] Preferably, the remote control and communication unit adopts spread spectrum communication or 5G / 4G technology.

[0014] The present invention also provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it realizes the high-altitude operation standardization detection, power transmission facility defect detection, path planning and navigation of the intelligent identification and control platform.

[0015] The present invention also provides a computer program product, which includes a computer program / instruction that, when executed by a processor, enables the high-altitude operation standardization detection, power transmission facility defect detection, path planning and navigation of the intelligent identification and control platform.

[0016] The advantages of this invention are: (1) This invention provides a climbing robot system for the operation and control of angle steel towers of transmission lines. It aims to solve the technical problems of high safety hazards and low efficiency of traditional manual supervision mode in the existing tower erection and line stringing operations of transmission lines, as well as the poor adaptability of existing climbing robots to complex angle steel tower structures and lack of intelligent control capabilities. The system of this invention integrates a reliable climbing structure, a precise path planning method and a high-precision intelligent recognition technology, and realizes automated, intelligent and full-coverage monitoring of the entire process of high-altitude operations.

[0017] (2) This invention enables continuous and real-time monitoring of the entire process of tower erection and line stringing, making up for the shortcomings of traditional manual supervision.

[0018] (3) Based on two professional identification algorithms of deep learning, this invention realizes automated, high-precision judgment and real-time early warning of work specifications and facility defects.

[0019] (4) This invention significantly reduces the safety risks of high-altitude operations and improves the efficiency and quality of safety monitoring and defect inspection, and has significant engineering application value.

[0020] (5) This invention combines the elastic adaptive obstacle crossing mechanism and the tracked magnetic adsorption mechanism, which solves the technical problem of unstable movement and adsorption of climbing robots on the complex structure of angle steel tower. Attached Figure Description

[0021] Figure 1 This is an architectural diagram of a climbing robot system for controlling the operation of angle steel towers for power transmission lines, according to the present invention.

[0022] Figure 2 This is a structural diagram of the climbing robot.

[0023] Figure 3 This is a picture of the actual climbing robot. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] This invention relates to the fields of robotics, computer vision, and power safety production monitoring technology. Specifically, it provides a climbing robot system that integrates tracked magnetic adsorption climbing technology, deep learning intelligent recognition technology, and three-dimensional dynamic path planning technology for the control of the operation process of angle steel towers for transmission lines. This system is used to achieve automated and intelligent control of the tower erection and line stringing operation process of angle steel towers for transmission lines.

[0026] Depend on Figure 1 As shown, the system of the present invention includes: a climbing robot body, a remote control and communication unit, and an intelligent identification and management platform.

[0027] Climbing robot body: Used for adsorption, movement, attitude adjustment, and data acquisition on the surface of the angle steel tower of the power transmission line. The climbing robot body includes: Tracked magnetic adsorption walking mechanism: used to provide adsorption force and walking driving force; Elastic adaptive obstacle crossing mechanism: used to assist the body in crossing tower material obstacles and automatically adjust the climbing posture; Information acquisition module: used to acquire high-resolution images of key parts of power transmission facilities, video streams of high-altitude operations, as well as the posture of the power transmission facility and environmental parameters.

[0028] Remote control and communication unit: used for two-way wireless communication with the main body to realize remote control and data transmission.

[0029] Intelligent identification and control platform: Used to receive data streams transmitted from the robot itself and perform intelligent decision-making, path planning, and early warning. Specifically, it includes: high-altitude operation compliance inspection, power transmission facility defect detection, and path planning and navigation for the climbing robot itself.

[0030] Furthermore, by Figure 2 and Figure 3 As shown, the present invention provides a climbing robot body adapted to the complex structure of an angle steel tower, comprising: Tracked magnetic adsorption walking mechanism: The tracked design provides a larger contact area and friction; the adsorption structure uses a permanent magnet array to provide a stable and reliable adsorption force, ensuring the robot walks stably on the vertical surface of the tower.

[0031] Elastic Adaptive Obstacle-Crossing Mechanism: A uniquely designed linkage and joint structure enables the robot to adapt flexibly. This mechanism automatically adjusts the robot's posture and chassis height to maintain a tight fit with the adhesion surface when traversing complex obstacles such as inclined members, connecting plates, and bolt heads on angle steel towers.

[0032] Multifunctional information acquisition module: It integrates a high-resolution visible light camera, as well as sensors such as an inertial measurement unit (IMU) and lidar (LiDAR) to realize multi-dimensional acquisition of images, attitude and environmental data at the work site.

[0033] The climbing robot adopts a tracked magnetic adsorption structure and is equipped with an elastic adaptive obstacle-crossing mechanism, enabling it to reliably adsorb and autonomously move across obstacles on the complex and uneven surface of the angle steel tower.

[0034] Furthermore, the intelligent identification and control platform of this invention employs advanced path planning technology to enable the robot to move autonomously and efficiently on complex angle steel tower structures, as follows: Based on the three-dimensional geometric model of the angle steel tower, an accurate environmental map is constructed, and real-time positioning is achieved by combining the on-body IMU and LiDAR data. The Rapidly-exploring Random Tree (RRT) algorithm or its improved version is used to calculate the three-dimensional dynamic optimal climbing path from the starting point to the task point that meets the structural constraints of the tower material, thereby improving inspection efficiency and avoiding collisions. The optimal path is converted into a sequence of motion control commands and sent to the host for execution via a remote control and communication unit.

[0035] Furthermore, this invention achieves intelligent monitoring of the work process through a deep learning model deployed on an intelligent identification and control platform, as follows: Based on machine vision detection algorithms, a convolutional neural network (CNN) is used to perform real-time detection on the video stream returned by the ontology information acquisition module, and to detect and output the bounding boxes and confidence scores of key targets such as workers, safety helmets, safety belt hooks, and attachment points. Based on the detection results, the geometric relationship and temporal motion status between key targets are analyzed to determine whether the safety belt of the operator is physically anchored or whether there is any violation of the operation, and whether the safety helmet is worn or whether there is any violation of the operation, so as to realize the automated judgment of the operation compliance. When a violation is detected, an audible and visual warning will be triggered within a set time (1 second).

[0036] Furthermore, this invention achieves defect detection of power transmission facilities through a defect detection algorithm deployed on an intelligent identification and control platform, as follows: The climbing robot moves to key parts of the facility and collects high-resolution image data of key parts of the power transmission facility; The defect detection algorithm enhances the ability to extract subtle global and local features of images by introducing context encoding and saliency analysis mechanisms, enabling accurate location and classification of defects in key parts of power transmission facilities, such as missing bolts, component damage, and corrosion of tower materials.

[0037] This system integrates a high-definition visual acquisition module and, through an intelligent recognition and control platform, uses deep learning algorithms to monitor and standardize key behaviors of high-altitude workers, such as safety belt installation and construction procedures. Simultaneously, the system employs 3D dynamic path planning technology to guide robots in efficient inspection of tower materials. This system boasts advantages such as low risk of high-altitude operations, high detection accuracy, and a high degree of automation, effectively solving the problems of high safety risks, low efficiency, and difficulty in achieving real-time monitoring throughout the entire process associated with traditional manual operations. It can significantly improve the safety and intelligence level of transmission line tower erection operations.

[0038] Furthermore, the remote control and communication unit of the present invention employs spread spectrum communication or 5G / 4G technology to achieve long-distance high-bandwidth data transmission of more than 100 meters.

[0039] Example 1: Implementation of the Climbing Robot's Body Structure and Performance This embodiment describes the hardware structure and performance parameter design of the climbing robot body, aiming to ensure that it can adapt to the complex working environment of the angle steel tower.

[0040] Body structure and parameter design: The robot's overall weight is designed to not exceed 14 kg.

[0041] The maximum external dimensions are controlled within 1200mm×320mm×280mm.

[0042] Mobility performance target: Climbing speed requirement is not less than 1m / min.

[0043] Battery life: Built-in high-energy-density lithium battery pack ensures continuous operation time of no less than 8 hours in energy-saving mode.

[0044] Implementation of a tracked magnetic adsorption walking mechanism: A dual-track structure is adopted to increase the contact area with the tower material and improve driving stability.

[0045] Adsorption unit: A permanent magnet array is adopted, preferably arranged in a Halbach array to effectively concentrate the magnetic field, enhance the adsorption force, and reduce the interference of the external magnetic field.

[0046] Drive unit: A brushless DC motor is selected, which drives the tracks through a gearbox to provide stable and sufficient torque driving force.

[0047] Implementation of a flexible adaptive obstacle-crossing mechanism: Structural composition: It adopts a mechanical design based on linkages and joints, which connects the walking mechanism and the main body.

[0048] Functionality: When obstacles such as inclined members, connecting plates, and protruding bolt heads are detected on the angle steel tower, this mechanism can adaptively adjust the relative angle and height between the robot body and the walking mechanism to ensure close contact between the magnetic adsorption surface of the track and the tower material during obstacle crossing, and maintain the continuity of the adsorption force.

[0049] Example 2: Implementation Method of Three-Dimensional Dynamic Path Planning This embodiment describes the specific algorithm and steps of the path planning module in the intelligent identification and control platform: S21, Angle Steel Tower 3D Model Construction and Positioning: Based on the design drawings or point cloud data of the angle steel tower, a high-precision 3D geometric model is constructed within the control platform, serving as a map of the robot's working environment. The robot body determines its real-time position and attitude in the 3D model by fusing positioning data from IMU and LiDAR sensors.

[0050] S22, Selection and application of path planning algorithms: The RRT (Rapidly-exploring Random Tree) algorithm or its improved algorithm suitable for complex spaces is selected as the core planner.

[0051] S23, Dynamic Optimal Path Generation: The RRT algorithm takes the robot's current position, the task target point, the tower material's geometric constraints, and the obstacle distribution as inputs to calculate and generate a three-dimensional dynamic optimal climbing path that avoids collisions and minimizes energy consumption.

[0052] S24, Path Execution and Feedback Control: The planned path is sent to the robot body in the form of a series of motion control commands. When the robot body executes the commands, it receives real-time feedback through the IMU and vision sensors, and the motion controller of the robot body performs closed-loop correction to ensure accurate adherence to the planned path.

[0053] Example 3: Intelligent Recognition Method for High-Altitude Operation Specifications This embodiment describes a machine vision-based detection algorithm for real-time control of the work process, as shown below: S31, Real-time video stream acquisition: The climbing robot body acquires a real-time video stream for the operator through its high-resolution visible light camera and transmits it back to the management platform via a remote control and communication unit (such as spread spectrum communication).

[0054] S32, Deployment of the target detection model: Deploy a high-altitude worker target detection model based on a convolutional neural network (CNN) on the control platform. After training, this model can accurately identify key targets in the image, such as workers, safety helmets, safety belt hooks, and attachment points.

[0055] S33, Real-time determination of work specifications: based on the bounding box and confidence level output by the model: Determining the seatbelt's attachment status: Analyze the spatial relationship (overlap) and relative motion state (such as relative speed being zero) between the hook and the attachment point to distinguish between visual overlap and physical anchoring.

[0056] Determining violations: Identifying whether personnel are in a pre-defined violation state such as climbing without protection, standing in a dangerous position, or having both feet off the ground.

[0057] S34, Real-time Early Warning and Recording: If the judgment result is non-compliant or illegal, the intelligent identification and control platform will issue an audible and visual warning to the on-site and remote operation terminals within 1 second, and at the same time record the spatiotemporal data and image evidence of the violation.

[0058] Example 4: Intelligent Detection Method for Defects in Power Transmission Facilities This embodiment describes a defect detection algorithm based on context encoding and salient context for implementing facility defect inspection, as shown below: S41, High-precision image acquisition: The robot moves to the preset key inspection points (such as bolt connections and welds) and acquires clear images of the facility components through a high-resolution camera.

[0059] S42, Defect Detection Model Deployment: Deploy a deep learning model based on context encoding and salient context on the management platform.

[0060] S43, Precise Defect Localization and Classification: This model enhances the understanding of global image information by introducing context encoding and improves the focus on small defect targets through a salient context mechanism. The algorithm outputs the defect type (e.g., missing bolt, surface corrosion, crack) and the corresponding bounding box coordinates.

[0061] S44, Report Generation: The management platform binds the detected defect information with the robot's positioning data (GPS or relative coordinates) and automatically generates a defect inspection report to assist maintenance personnel in subsequent processing.

[0062] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A climbing robot system for controlling the operation of angle steel towers for power transmission lines, characterized in that, include: The climbing robot body, remote control and communication unit, and intelligent identification and management platform; The robot is controlled to move and adjust its posture on the surface of the angle steel tower of the power transmission line, and to collect data. The collected data includes video streams of high-altitude operations, images of key parts of the power transmission facility, as well as the robot's posture and environmental parameters. The remote control and communication unit communicates wirelessly with the climbing robot body in two directions to achieve remote control and data transmission; The intelligent identification and control platform receives data streams transmitted back from the climbing robot and performs high-altitude operation standardization inspections and power transmission facility defect detection based on the transmitted data streams. The intelligent identification and control platform also performs path planning and navigation for the climbing robot based on the transmitted data streams and sends motion control command sequences to the climbing robot for execution through the remote control and communication unit.

2. The climbing robot system for controlling the operation of angle steel towers for transmission lines according to claim 1, characterized in that, The specific process of route planning and navigation is as follows: An environmental map is constructed based on the three-dimensional geometric model of the angle steel tower, and real-time positioning is achieved by combining the IMU data and lidar data of the climbing robot itself. The RRT algorithm is used to calculate the optimal three-dimensional dynamic climbing path that meets the structural constraints of the tower. The optimal climbing path is converted into a sequence of motion control commands and sent to the climbing robot for execution.

3. The climbing robot system for controlling the operation of angle steel towers for power transmission lines according to claim 1, characterized in that, The specific process for the high-altitude operation compliance inspection is as follows: Convolutional neural networks are used to perform real-time detection on the video stream transmitted back by the climbing robot, and to detect and output the bounding boxes and confidence scores of key targets such as workers, safety helmets, safety belt hooks, and attachment points. Based on the detection results, analyze the geometric relationship and temporal motion state between key targets to determine whether the worker's safety belt is physically anchored or whether there is any violation of operating procedures, and whether the safety helmet is worn or whether there is any violation of operating procedures. When a violation is determined to be non-compliant or illegal, an audible and visual warning will be triggered within a set time.

4. A climbing robot system for controlling the operation of angle steel towers for transmission lines according to claim 1, characterized in that, The specific process for detecting defects in power transmission facilities is as follows: The climbing robot moves to a key part of the power transmission facility and collects corresponding images; By employing a defect detection algorithm and introducing context coding and saliency analysis mechanisms, the ability to extract subtle global and local features of images is enhanced, enabling accurate location and classification of defects in key parts of power transmission facilities. These defects include missing bolts, component damage, and corrosion on the tower surface.

5. A climbing robot system for controlling the operation of angle steel towers for transmission lines according to claim 1, characterized in that, The climbing robot body includes: Tracked magnetic adsorption walking mechanism: used to provide adsorption force and walking driving force; Elastic adaptive obstacle crossing mechanism: used to assist the body in crossing tower material obstacles and automatically adjust the climbing posture; Information acquisition module: integrates a camera, inertial measurement unit and lidar, used to acquire images, videos, as well as body attitude and environmental parameters.

6. A climbing robot system for controlling the operation of angle steel towers for transmission lines according to claim 5, characterized in that, The tracked magnetic adsorption walking mechanism is as follows: At least two sets of brushless DC motors are used as drive units to independently drive the tracks on both sides to achieve walking and steering; The permanent magnet array used to provide adsorption force is arranged in a matrix, in the form of a Halbach array, to increase the effective adsorption force on the angle steel tower material.

7. A climbing robot system for controlling the operation of angle steel towers for transmission lines according to claim 2, characterized in that, The elastic adaptive obstacle-crossing mechanism is as follows: Composed of a linkage and joint mechanical structure, it is used to connect the walking mechanism to the main body; when the main body moves to the obstacle of the angle steel tower, it automatically or remotely adjusts the relative height and angle between the walking mechanism and the main body.

8. A climbing robot system for controlling the operation of angle steel towers for transmission lines according to any one of claims 1-7, characterized in that, The remote control and communication unit adopts spread spectrum communication or 5G / 4G technology.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the high-altitude operation standardization detection, power transmission facility defect detection, path planning and navigation of the intelligent identification and control platform according to any one of claims 1 to 4.

10. A computer program product, characterized in that, It includes a computer program / instruction that, when executed by a processor, implements the high-altitude operation standardization detection, power transmission facility defect detection, path planning and navigation of the intelligent identification and control platform as described in any one of claims 1 to 4.

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