Power network blocking robot cooperative control system and robot thereof

Abstract

The application discloses a power network blocking robot cooperative control system and a robot thereof, and relates to the technical field of power robot control, which comprises four robot bodies with the same structure, various sensors, real-time collection of operation parameters, and a central control system, a remote control operation system, an accurate electrical control system and an intelligent control module to realize cooperative operation of the robot, accurate control of lifting, walking, pressing and other actions, real-time adjustment according to sensor feedback, intelligent control module based on large model analysis, optimization of the control parameters of the robot by using a multi-head attention mechanism, real-time communication and coordination of the robot by using Mesh ad hoc network technology to ensure the efficiency of cooperative operation, a terminal display and intervention module to provide a three-dimensional visual interface, real-time monitoring of operation progress and intervention by an operator, and the application greatly improves the efficiency of network blocking operation, reduces manual intervention, and has self-learning and optimization capabilities.

Description

Technical Field

[0001] This invention relates to the field of power robot control technology, specifically a collaborative control system for a power grid sealing robot and the robot thereof. Background Technology

[0002] Power grid closure is an indispensable part of power line construction and maintenance, involving the installation and commissioning of line equipment. Traditional power grid closure work relies heavily on manual operation, requiring operators to work at heights, which poses significant safety risks. Furthermore, the work is inefficient and prone to errors. With technological advancements, more and more robots are being used in power grid closure operations. However, existing technologies still have certain limitations, such as the limited functionality of robots, the lack of efficient collaborative control, and the absence of real-time feedback and adjustment for operational accuracy and stability.

[0003] Chinese invention patent application CN119297833A discloses a method and system for controlling the quality of wire mesh sealing based on a wire mesh sealing robot. It utilizes finite element analysis to achieve stable wire mesh sealing under vibration and temperature variations, ensuring the safety of power grid operation. This technology achieves adaptive regulation during the wire mesh sealing process by controlling parameters such as tension and temperature. However, the application of this method relies on precise parameter setting and analysis, and manual intervention is still required to transmit instructions during the collaborative operation of multiple robots. It lacks a high degree of automation and intelligence. Especially when facing complex operating environments and real-time dynamic changes, the robots struggle to adjust their behavior in a timely manner, resulting in limitations on operational efficiency and safety.

[0004] Chinese utility model patent CN219892806U discloses an intelligent power line traction machine for sealing and pulling. This machine has a simple structure, reduces construction costs, and improves the safety of crossing and removing power line barriers. The system uses friction wheels, guide wheels, and other equipment to make the sealing process more stable. However, this device only provides a single traction function and lacks multi-functional comprehensive capabilities. Furthermore, it cannot efficiently coordinate and control multiple robots in collaborative operations. In addition, the robots in the sealing operation do not fully utilize the intelligent control system, exhibiting weak real-time feedback and intelligent adjustment capabilities for sensor data during the operation, thus failing to achieve accuracy and efficiency in the sealing process. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and propose a collaborative control system for power grid sealing robots and the robot thereof to solve the above-mentioned problems.

[0006] The objective of this invention is achieved through the following technical solution: a collaborative control system for power grid sealing robots and the robot thereof, comprising: four identical robot bodies, each robot body integrating multiple sensors for acquiring various parameters;

[0007] The central control system is used to monitor and coordinate the movements of the four robot bodies, receive remote control commands, and perform task allocation and status feedback.

[0008] The remote control operating system allows operators to send commands to the central control system.

[0009] The precision electrical control system controls the robot's lifting, walking, and clamping movements, and makes adjustments based on sensor feedback.

[0010] The intelligent control module is used to precisely control the various actions of the four robots, ensuring the efficiency and accuracy of the net sealing operation;

[0011] The intelligent control module includes:

[0012] Task scheduling unit: Used to allocate tasks to the four robots according to the task instructions transmitted by the central control system, optimize the task allocation scheme, ensure that the robots work together, and avoid resource conflicts;

[0013] Sensor data acquisition and analysis unit: used to acquire and process sensor data from each robot body in real time, preprocess the sensor data, and input the preprocessed data into the subsequent analysis module;

[0014] Large Model Input and Vectorization Unit: Used to convert preprocessed data into high-dimensional vector sequences that can be processed by large models;

[0015] Large Model Analysis Unit: Based on the Transformer architecture, this unit analyzes high-dimensional input vectors using a multi-head attention mechanism. The multi-head attention mechanism includes an absolute position head, a relative position head, a pressure head, and a tension head.

[0016] Control parameter optimization and adjustment unit: used to calculate and optimize the control parameters of each robot based on the analysis results of the large model;

[0017] Communication and Coordination Unit: Responsible for handling real-time communication and coordination between robots; exchanging their respective position information, status feedback and sensor data in real time to collaboratively complete tasks; at the same time, the communication and coordination unit processes intervention commands from the terminal display and intervention module to adjust and correct tasks;

[0018] Real-time feedback and correction unit: When a deviation is detected between the robot's current action and the preset action, the real-time feedback and correction unit corrects the deviation and restores the robot's predetermined working trajectory by adjusting the robot's control signals.

[0019] Data storage and recording unit: This unit is responsible for recording all sensor data, control parameters, and important information about the robot's task progress during the sealing operation.

[0020] The communication module is used for the four robots to communicate with each other in real time during movement;

[0021] The terminal display and intervention module displays the entire sealing process in 3D in real time. Operators can intervene in real time on the terminal, which is connected to a large model to coordinate and correct the robot's movements and positions.

[0022] The remote control system uses 2.4G wireless communication technology, which has anti-interference capabilities and encrypted transmission functions. Operators can send various control commands, including start, stop, acceleration, deceleration and steering, to the central control system through the buttons or joystick on the handheld remote control.

[0023] The central control system shared by the four robots is built on an industrial-grade PLC and has redundancy backup function. It can decompose the net sealing task into multiple sub-tasks, such as positioning, moving, deploying, and fixing, according to the preset net sealing operation process or the instructions sent by the operator through the remote control operating system. It can also reasonably allocate tasks to each robot according to the current status and location information of each robot, while monitoring the task execution progress and status feedback of each robot in real time.

[0024] The robot receives real-time data from sensors, which is then analyzed and processed by a precision electrical control system. When a deviation is detected between the actual action and the preset action, the precision electrical control system adjusts the robot's lifting, walking, and pressing actions in real time by adjusting the motor's drive current, voltage, and the duty cycle of the control signal.

[0025] The pre-trained large model in the intelligent control module is built on the Transformer architecture and trained with a large amount of power grid sealing operation data. It can perform in-depth analysis of the high-dimensional vector of the input sequence, accurately extract key information of different parameters using a multi-head attention mechanism, and calculate the precise control parameters of each robot at different operation stages through the fully connected layers and activation functions inside the model, including moving speed, acceleration, lifting height, and clamping force, so as to achieve precise control of various robot actions.

[0026] The communication module adopts Mesh self-organizing network technology, which supports multi-hop communication. The four robots automatically build a communication network during operation, which can transmit location information, task status and sensor data to each other in real time and stably, ensuring the timeliness and reliability of data interaction.

[0027] The terminal display and intervention module is developed based on a high-performance industrial tablet PC and is equipped with a high-definition touch screen. Through 3D modeling and real-time rendering technology, it displays the entire net enclosure process in an intuitive 3D form, including the robot's position, posture, and the deployment status of the net enclosure. Operators can intervene in the robot's movements and positions in real time on the terminal by touching the screen or connecting an external keyboard and mouse, such as emergency stop and manual adjustment of task allocation. The terminal is connected to the large model in the intelligent control module through a high-speed network to achieve unified coordination and correction of the robot.

[0028] Sensors include, but are not limited to, tension sensors, pressure sensors, gyroscopes, accelerometers, and lidar. Tension sensors are used to monitor tension parameters in real time during net sealing; pressure sensors are used to acquire clamping parameters; gyroscopes and accelerometers are used to monitor the robot's posture changes; and lidar is used to acquire three-dimensional information about the surrounding environment. The sensor data is transmitted in real time to the precision electrical control system and intelligent control module via a high-speed data bus.

[0029] The power grid sealing robot body includes a frame, on which lifting rails are symmetrically fixed. Motor mounting brackets are slidably connected to the lifting rails. The motor mounting brackets are driven to lift via a lifting drive worm gear sleeve and a lifting mechanism gearbox. At least two walking motor gearboxes are fixedly connected to the motor mounting brackets. A drive wheel is fixedly connected to the power output shaft of each walking motor gearbox, and a walking drive motor is fixedly connected to its power input shaft. The lifting mechanism gearbox's power output shaft is connected to the lifting drive worm gear sleeve, and a lifting drive motor is fixedly connected to its power input shaft. A driven U-shaped wheel is rotatably connected to the frame at a position corresponding to the drive wheel. The surfaces of the driven U-shaped wheel and the drive wheel are made of non-slip, wear-resistant rubber. The lifting drive worm gear sleeve has automatic locking and overload protection functions.

[0030] Both the walking drive motor and the lifting drive motor are high-precision servo geared motors with encoder feedback. Each robot is equipped with a walking drive motor and a lifting drive motor that are electrically connected to the precision electrical control system through independent drive circuits, which can accurately control the speed, direction and torque output of the drive wheel and the driven U-shaped wheel.

[0031] The beneficial effects of this invention are:

[0032] 1. By having four robots work collaboratively, the system can achieve efficient and precise operation during power grid sealing. Through real-time task scheduling and large-scale model analysis by the intelligent control module, the system can quickly calculate the optimal task allocation and operation path for each robot. Real-time feedback from sensors and in-depth analysis of the large model enable the robots to adjust their behavior according to the environment and operation requirements, ensuring that all robots can cooperate synchronously during the operation, which significantly improves the efficiency of the sealing operation. The precise electrical control system ensures that the robots can achieve extremely high precision when performing actions such as lifting, walking, and pressing. Through fine adjustment of motor control signals, the system can accurately control the robot's actions under different working conditions, ensuring that the sealing operation achieves the predetermined goal and that the operation quality is not affected by robot movement deviation.

[0033] 2. The system exhibits exceptional flexibility and adaptability in complex environments. Through the integration of multiple sensors (such as tension sensors, pressure sensors, accelerometers, and lidar), the robot can perceive its working environment and its own status in real time. With precise real-time adjustments to the electrical control system, the robot can quickly adapt to changing operating conditions, operating stably regardless of the materials of power lines or complex terrain. The intelligent control module utilizes large-scale model analysis to not only process the robot's dynamic data but also combine external environmental information, making dynamic decisions through a multi-head attention mechanism. This optimizes various control parameters of the robot (such as speed, clamping force, and lifting height), enabling the system to adaptively adjust its operational strategies and ensure the smooth progress of the netting operation.

[0034] 3. The system's intelligent control module possesses deep learning and self-optimization capabilities, enabling analysis and prediction based on historical operation data. Through continuous training, the large model learns various patterns and rules in netting operations, and optimizes the robot's control strategy based on feedback during real-time analysis. The data storage and recording unit after each operation provides valuable feedback for the system's self-optimization, allowing the system to automatically adjust parameters in future operations, thereby improving work efficiency and accuracy. Through a multi-head attention mechanism, the system can comprehensively consider multiple key parameters, such as the robot's absolute position, relative position, clamping force, and tension, and generate optimal control commands based on this information. This self-learning and optimization capability of the system makes the operation gradually more accurate and efficient with each execution.

[0035] 4. The robot body can operate stably at heights or in relatively confined spaces. The anti-slip and wear-resistant rubber material of the driven U-shaped wheel and the driving wheel ensures that the robot can stably clamp and move smoothly on various power lines. It can also operate stably even in complex or dangerous environments. The lifting drive worm gear sleeve has automatic locking and overload protection functions, and can automatically adjust according to the cable pressure to ensure that the cable is firmly fixed during the sealing operation. This device not only improves the operation accuracy, but also increases the safety during the operation, preventing equipment damage or cable damage caused by excessive clamping. The precise electrical control system continuously adjusts according to real-time feedback data to ensure that the robot's movements are not unstable due to external factors (such as environmental changes), thereby ensuring the stability of the operation.

[0036] 5. Operators can remotely control and intervene in the system in real time through the remote control operating system and the terminal display and intervention module. The terminal display module uses a high-performance industrial tablet PC and a high-definition touch screen to intuitively display the robot's position, posture, and netting status in a three-dimensional form during operation. Operators can manually adjust the system using devices such as a touch screen, keyboard, and mouse to quickly respond to emergencies, adjust the robot's task allocation, or stop the robot's operation. The system's remote control operating system uses 2.4G wireless communication technology, which has anti-interference capabilities and encrypted transmission functions, ensuring the stability and security of data transmission even in complex environments. Operators can flexibly control the robot, ensuring the efficiency and safety of the operation process.

[0037] 6. With the robot collaborative control system of the present invention, power grid sealing operations no longer rely on a large number of manual operations, but are carried out by robots efficiently and accurately. The system can complete large-scale grid sealing work in a very short time, which greatly improves the efficiency of the operation. Through collaborative operation and real-time adjustment, the robot can complete the most accurate operation in the shortest time, reduce human intervention, and save a lot of labor costs.

[0038] 7. The system's data storage and recording unit can record all key data during the net enclosure operation, such as sensor data, control parameters, and task execution progress. This data can not only be used for post-operation analysis and operation evaluation, but also provides a foundation for the system's self-learning and optimization. In future net enclosure operations, the system can improve and optimize based on historical data, further improving work efficiency. Attached Figure Description

[0039] Figure 1 This is a system interaction diagram of the present invention;

[0040] Figure 2 This is a diagram of the architecture of the present invention;

[0041] Figure 3This is a structural diagram of the robot body of the present invention.

[0042] Explanation of the labels in the diagram

[0043] 1. Bracket; 2. Lifting slide rail; 3. Motor mounting bracket; 4. Lifting drive worm gear sleeve; 5. Lifting mechanism gearbox; 6. Travel motor gearbox; 7. Drive wheel; 8. Travel drive motor; 9. Lifting drive motor; 10. Driven U-shaped wheel. Detailed Implementation

[0044] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0045] It should be noted that the directional concepts of "left", "right", "up", "down", "front", "back", "inner", and "outer" in the following scheme are all relative directions, and will not be listed one by one here.

[0046] Example 1:

[0047] like Figures 1 to 3 As shown, this embodiment describes a collaborative control system for power grid sealing robots and the robot itself, which aims to achieve efficient and precise power grid sealing operations. The system includes four identical robot bodies. Each robot is equipped with a U-shaped groove designed driven U-shaped wheel 10, a walking drive motor 8 driven drive wheel 7, a lifting drive worm gear sleeve 4, and various sensors to acquire various operation parameters.

[0048] The driven U-shaped wheel 10 can move stably on power lines of different materials. The lifting drive worm gear sleeve 4 is used to ensure that the cable is firmly fixed during the sealing process. The robot also integrates a variety of sensors, such as tension sensors, compression sensors, gyroscopes and lidar, to collect the robot's status information (such as position, attitude, speed, tension, compression force, etc.) in real time. This data will be used for subsequent control decisions.

[0049] The central control system is responsible for monitoring and coordinating the actions of the four robots. It receives remote control commands and assigns tasks to each robot, including positioning, moving, clamping, lifting and lowering. The central control system also receives status feedback from each robot and monitors the progress of task execution in real time to ensure the overall collaborative operation of the system.

[0050] The remote control operating system enables operators to control the robot remotely. Through input devices such as buttons and joysticks on the handheld remote control, operators can send control commands such as start, stop, accelerate, decelerate, and turn. This wireless remote control system uses 2.4G wireless communication technology, which has anti-interference capabilities and encrypted transmission functions to ensure stable communication in long-distance and complex environments.

[0051] The precision electrical control system is responsible for controlling the robot's lifting, walking, and clamping actions, and automatically adjusts based on real-time data from sensors. The system adjusts the motor's drive current, voltage, and duty cycle in real time according to the robot's operating status to ensure the accuracy and stability of the robot's actions. For example, when a change in the robot's posture is detected, the system will automatically adjust the drive signal to restore its original trajectory.

[0052] The intelligent control module comprises multiple functional units to ensure that the robot can complete efficient and precise netting operations in complex environments. The key functional units of the intelligent control module are as follows:

[0053] Task scheduling unit: Based on the task instructions, it assigns tasks to the four robots, ensuring that tasks are reasonably distributed among the four robots and avoiding resource conflicts.

[0054] Sensor data acquisition and analysis unit: Collects and preprocesses sensor data from the robot body in real time, removes noise, and ensures that the data input to subsequent analysis modules is accurate and reliable.

[0055] Large Model Input and Vectorization Unit: Converts sensor data into high-dimensional vectors that can be processed by large models, facilitating the analysis and optimization of large models.

[0056] Large Model Analysis Unit: Based on the Transformer architecture, the large model analyzes the input high-dimensional vector through a multi-head attention mechanism to generate control commands for the robot and control its actions.

[0057] Control parameter optimization and adjustment unit: Based on the analysis results of the large model, optimize the robot's control parameters to ensure the accuracy of the robot's movements.

[0058] Communication and Coordination Unit: Handles real-time communication between the four robots, ensuring that the robots can coordinate with each other when performing tasks.

[0059] Real-time feedback and correction unit: When the robot's movements deviate from the predetermined target, the system will make real-time corrections and adjust the control signals to ensure stable operation of the robot.

[0060] The data storage and recording unit is responsible for recording all sensor data, control parameters, robot task progress and other important information during the sealing operation. The data storage is used for subsequent analysis and system optimization to improve the efficiency and accuracy of subsequent sealing operations.

[0061] The terminal display and intervention module uses a high-performance industrial tablet PC and a high-definition touch screen to display the entire sealing process in three dimensions in real time. Operators can intervene in the robot's actions in real time through the touch screen, such as emergency stop and manual adjustment of task allocation.

[0062] Working principle

[0063] The power grid sealing robot collaborative control system of the present invention uses four robots to work together to ensure the efficiency, stability and accuracy of the power grid sealing operation during the power line sealing operation. This is achieved through precise sensor data acquisition, intelligent control module analysis and processing and real-time feedback correction.

[0064] Task allocation and execution

[0065] The task scheduling unit allocates different tasks (such as positioning, movement, lifting, etc.) to each robot according to the task instructions sent by the central control system. During this process, the robots can exchange position information and task status in real time to ensure that the four robots work together to complete the task and avoid conflicts.

[0066] During task scheduling, a weighted allocation algorithm can be used to assign tasks to robots to ensure efficient task execution. Specific scheduling can be improved by optimizing algorithms (such as genetic algorithms or particle swarm optimization) to enhance the efficiency and accuracy of task allocation.

[0067] Weighted task allocation algorithm formula:

[0068]

[0069] The task scheduling unit can select the most suitable robot for task allocation based on these weights.

[0070] Data collection and analysis

[0071] Sensors on the robot body collect environmental data and robot status information in real time, including tension, clamping force, posture, speed, etc. After data collection, the sensor data acquisition and analysis unit performs data preprocessing and transmits the data to the intelligent control module, converting it into the format required by the model.

[0072] Large Model Analysis and Instruction Generation

[0073] The intelligent control module performs deep learning on various data through the analysis of a large model, and uses a multi-head attention mechanism to analyze the correlation between different parameters to generate control commands for the robot (such as movement speed, acceleration, lifting and lowering height). This analysis is based on preset task requirements to ensure that every action of the robot meets the task objectives.

[0074] In the intelligent control module, when using deep learning models for big data analysis, a multi-head attention mechanism is used to analyze high-dimensional vector data and generate optimized control commands.

[0075] Multi-head attention mechanism formula:

[0076]

[0077] The analysis of large models is based on this attention mechanism, which is used to capture multi-dimensional dependencies, such as absolute position, relative position, compressive force, tensile force, etc.

[0078] Motion control and feedback adjustment

[0079] When the robot performs actual actions, the precision electrical control system adjusts the robot's control signals (such as motor drive current and voltage) in real time based on sensor feedback to ensure that it performs precise lifting, walking, clamping and other actions.

[0080] Real-time intervention and correction

[0081] Operators can monitor the entire sealing process through the terminal display and intervention module. If any deviation is detected, they can intervene in the robot's task execution in real time, adjust its actions, and ensure the smooth completion of the sealing operation.

[0082] With four robots working together, the central control system and intelligent control module can coordinate the tasks of each robot in real time, reducing operation time and improving the efficiency of net enclosure.

[0083] The precision electrical control system, combined with sensor feedback and large-scale model analysis, ensures the robot's accurate operation in complex environments, reduces errors, and guarantees the accuracy of the netting operation.

[0084] The system can monitor and correct robot motion deviations in real time, and ensure the stability of robot operation through a feedback mechanism to avoid network sealing failures caused by improper operation.

[0085] The remote control operating system allows operators to control the robot remotely, providing a flexible operating method. The real-time feedback and correction unit can promptly correct deviations in the robot's movements, improving operational safety.

[0086] The data storage and recording unit enables the system to record data for each job, providing data support for the optimization of subsequent jobs and further improving the overall performance of the system.

[0087] The power grid sealing robot collaborative control system in this embodiment can not only complete the power grid sealing operation efficiently and stably, but also has intelligent scheduling, precise control and real-time intervention functions, which greatly improves the operation efficiency and reliability of the robot system.

[0088] Example 2:

[0089] like Figures 1 to 3 As shown, this embodiment further describes in detail the specific working principle of the collaborative control system for power grid sealing robots based on embodiment 1, such as sensor types and installation, large-scale model analysis of intelligent control modules, and characteristics of Mesh self-organizing network communication modules.

[0090] The four robots have identical structures, including a support frame 1. A lifting slide rail 2 is symmetrically fixedly connected to the support frame 1. A motor mounting bracket 3 is slidably connected to the lifting slide rail 2. The motor mounting bracket 3 is driven to lift via a lifting drive worm gear sleeve 4 and a lifting mechanism gearbox 5. At least two walking motor gearboxes 6 are fixedly connected to the motor mounting bracket 3. A drive wheel 7 is fixedly connected to the power output shaft of the walking motor gearbox 6. A walking drive motor 8 is fixedly connected to the power input shaft of the walking motor gearbox 6. The power output shaft of the lifting mechanism gearbox 5 is connected to the lifting drive worm gear sleeve 4. A lifting drive motor 9 is fixedly connected to the power input shaft of the lifting mechanism gearbox 5. A driven U-shaped wheel 10 is rotatably connected to the support frame 1 at a position corresponding to the drive wheel 7. The surfaces of the driven U-shaped wheel 10 and the drive wheel 7 are made of non-slip, wear-resistant rubber material. The lifting drive worm gear sleeve 4 has automatic locking and overload protection functions.

[0091] Both the walking drive motor 8 and the lifting drive motor 9 are high-precision servo geared motors with encoder feedback function. Each robot is equipped with a walking drive motor 8 and a lifting drive motor 9, which are connected to the precision electrical control system through independent drive circuits, enabling precise control of the speed, direction and torque output of the drive wheel 7 and the driven U-shaped wheel 10.

[0092] The lifting drive motor 9 drives the lifting drive worm sleeve 4 to rotate. The lifting drive worm sleeve 4 moves up and down with the lifting slide rail 2 and the motor mounting bracket 3. Then, the active wheel 7 and the driven U-shaped wheel 10 are used to press the wire. The walking drive motor 8 drives the active wheel 7 to rotate through the walking motor gearbox 6. The active wheel 7 and the driven U-shaped wheel 10 drive the robot body to move along the wire through friction with the wire.

[0093] The robot integrates multiple sensors for real-time data collection, including:

[0094] Tension sensor: It adopts the strain gauge principle and is installed at the contact point between the drive wheel 7 and the wire to monitor the tension during net sealing.

[0095] Pressure sensor: It adopts the capacitive principle and is installed at the contact point between the drive wheel 7 and the wire to obtain the clamping parameters.

[0096] Gyroscopes and accelerometers: monitor changes in the robot's posture to ensure stability during operation.

[0097] LiDAR: Acquires three-dimensional information about the surrounding environment, ensuring that the robot can identify obstacles or changes in its surroundings, and assists in localization and obstacle avoidance.

[0098] The central control system is built with an industrial-grade PLC and has redundant backup functions. It can decompose the net sealing task into multiple sub-tasks, such as positioning, moving, unfolding, and fixing, according to the preset net sealing operation process or the instructions sent by the operator through the remote control operating system. It can allocate tasks to each robot in real time and monitor the task execution progress of each robot through a task feedback mechanism.

[0099] Operators send start, stop, acceleration, deceleration, and steering commands to the central control system via a handheld remote control. The remote control operating system uses 2.4G wireless communication technology, which has anti-interference capabilities and encrypted transmission functions to ensure data security and stability in the working environment.

[0100] The precision electrical control system automatically adjusts the robot's lifting, walking, and clamping actions by monitoring sensor data in real time. The system can ensure that the robot can perform net sealing operations stably and efficiently in complex terrains and environments by adjusting the motor control signals.

[0101] The intelligent control module achieves precise control of the four robots through a multi-functional unit. The following are some of the functional units not mentioned in detail in Example 1:

[0102] Sensor data acquisition and analysis unit: Collects and processes sensor data from each robot body, including tension, clamping force, acceleration, attitude, etc. After noise filtering, these data are converted into standardized parameters and input into subsequent analysis modules.

[0103] Large Model Analysis Unit: Based on the Transformer architecture, the large model analyzes high-dimensional parameter data through a multi-head attention mechanism. The task instructions for each robot are generated based on these analysis results. During the analysis process, the model dynamically adjusts the control parameters of various operations, such as movement speed, acceleration, lifting height, and clamping force.

[0104] The real-time communication between the robots adopts Mesh self-organizing network technology, which supports multi-hop communication and ensures that the four robots can exchange data in real time and stably during the netting operation, including location information, task status and sensor data. Mesh self-organizing network technology can effectively improve the communication reliability of the system, especially in complex environments, the communication bandwidth can reach [X] Mbps and the packet loss rate is less than [X]%.

[0105] This system includes a data storage unit for recording all sensor data, control parameters, and robot task execution progress during the net sealing operation. The stored data can be used for subsequent analysis, performance optimization, and system self-learning to improve the system's execution efficiency in future operations.

[0106] Operators can monitor the barricade operation in real time through the terminal display and intervention module. This module uses 3D modeling and real-time rendering technology to intuitively display the progress of the barricade operation, the robot's position and posture changes. Operators can intervene in the robot's actions through the terminal, such as emergency stop and task reassignment.

[0107] Working principle

[0108] Data Acquisition and Preprocessing

[0109] Each robot collects real-time data on its working environment and robot status through installed sensors. This data includes tension, clamping force, acceleration, and posture, and is transmitted in real-time to the precision electrical control system and intelligent control module via a high-speed data bus. After preprocessing and noise reduction, the sensor data is analyzed and processed by the intelligent control module.

[0110] To ensure data accuracy, sensor data acquisition and preprocessing can utilize filtering algorithms to remove noise and perform standardization.

[0111] Data standardization formula:

[0112]

[0113] Data standardization helps ensure stability during subsequent processing and allows data from different types of sensors to be processed uniformly.

[0114] Intelligent control module analysis and decision making

[0115] The large model analysis unit in the intelligent control module performs deep analysis based on the pre-trained Transformer architecture. It extracts key information from different angles through a multi-head attention mechanism. The analysis results determine parameters such as the robot's movement speed, lifting height, and clamping force to ensure that the robot can perform tasks according to the predetermined goals.

[0116] Task allocation and coordination

[0117] The task scheduling unit assigns tasks to the four robots according to the instructions of the central control system. The robots share location information, status information and sensor data in real time through Mesh self-organizing network technology to ensure collaborative work. Each robot optimizes its task execution path according to its current status and task execution progress to avoid conflicts or duplicate work.

[0118] Real-time feedback and correction

[0119] During execution, if the robot detects a deviation between its current action and the preset action, the real-time feedback and correction unit will make corrections. By adjusting control signals such as motor drive current, voltage, and duty cycle, the robot will return to the predetermined working trajectory, ensuring the accuracy and stability of the net sealing operation.

[0120] Based on the real-time data fed back from the sensors, the precision electrical control system uses control algorithms to calculate and adjust parameters (such as motor current and voltage) to correct the robot's movements.

[0121] PID control algorithm formula:

[0122]

[0123] When adjusting robot movements based on real-time feedback, an adaptive control algorithm can also be used to optimize robot movements by adjusting based on real-time feedback data and errors.

[0124] Adaptive control algorithm formula:

[0125]

[0126] This algorithm can continuously adjust itself during the robot's task execution to ensure the accuracy and stability of the operation.

[0127] Terminal intervention and optimization

[0128] Operators can monitor the progress of the net enclosure operation in real time through the terminal display and intervention module, and can intervene, such as pausing the operation, reassigning tasks, or adjusting the robot's operating path, in order to deal with emergencies.

[0129] The system enables the rapid and precise completion of the net enclosure operation through the collaborative operation of four robots, precise task allocation, and intelligent control. Real-time optimization through sensor feedback and large-scale model analysis ensures that every robot action meets the preset requirements.

[0130] Mesh self-organizing network technology ensures stable communication between the four robots in complex environments. The system can exchange task data and status information in real time during operation, avoiding communication interruption or data loss.

[0131] The large model analysis unit, through deep learning and multi-head attention mechanisms, can perform in-depth analysis of the data in each task and optimize itself, enabling the system to continuously improve the robot's work efficiency and accuracy.

[0132] Operators can flexibly control the robot through the remote operating system, and the terminal intervention module enables any abnormalities during the operation to be corrected in a timely manner, ensuring operational safety.

[0133] Through the above embodiments, the present invention provides a highly efficient, accurate, reliable and intelligent collaborative control system for power grid sealing robots, which not only optimizes the traditional grid sealing operation process, but also greatly improves operation efficiency and safety.

[0134] Example 3:

[0135] like Figures 1 to 3 As shown in the previous embodiments, this embodiment will further describe in detail the parts of the power grid sealing robot collaborative control system that were not mentioned in the previous embodiments, such as the precision electrical control system, the terminal display and intervention module, and the hardware design of the robot body, based on Embodiments 1 and 2. It will focus on how to ensure the stability and accuracy of the grid sealing operation by using real-time data feedback and precise adjustment of robot movements, and how to improve operability and operational safety through the terminal display and intervention module.

[0136] In the collaborative control system of power grid sealing robots, the robot uses sensors to provide real-time feedback of various parameter data, such as position information, posture changes, tension, and clamping force. The precision electrical control system is responsible for analyzing this real-time data and evaluating whether the robot's current actions meet the preset goals. If a deviation is found between the robot's actions and the predetermined actions, the precision electrical control system will adjust the robot in real time by adjusting the motor's drive current, voltage, and the duty cycle of the control signal to restore its working trajectory and ensure that the robot accurately performs tasks such as lifting, walking, and clamping.

[0137] The key function of this control system is:

[0138] Real-time data analysis: Data from sensors is acquired in real time and filtered and processed to ensure the accuracy of the input control data.

[0139] Deviation detection and correction: If a deviation is detected during the robot's task execution, the system will compensate for the deviation by adjusting motor parameters (such as current, voltage, etc.) to ensure that the robot can always maintain the predetermined trajectory.

[0140] High-efficiency feedback mechanism: The precision electrical control system utilizes a high-efficiency feedback mechanism to quickly respond to changes in the robot's state, adjust the robot's operating status, optimize robot behavior, and ensure efficient operation of the sealing operation.

[0141] The terminal display and intervention module provides a visual monitoring interface for net enclosure operations through a high-performance industrial tablet PC and a high-definition touch screen, combined with 3D modeling and real-time rendering technology. Operators can use this module to monitor the position, attitude, net enclosure deployment status, etc. of the four robots in real time, ensuring coordinated operations from a global perspective.

[0142] This module includes the following functions:

[0143] 3D real-time display: Operators can intuitively view the robot's current position, working posture, and netting progress through a 3D view. Through real-time rendering technology, operators can clearly see every step of the netting operation and make corresponding adjustments to the robot's actions.

[0144] Real-time intervention and adjustment: Operators can intervene in the robot's movements and positions in real time through input devices such as touch screens, external keyboards or mice, such as emergency stops and manual adjustments to task assignments, to ensure rapid response and adjustment of operations during operation.

[0145] Connecting to the intelligent control module: The terminal display and intervention module is connected to the large model in the intelligent control module through a high-speed network, which can coordinate the robot's movements and positions in real time. If a problem is found during the robot's execution, the operator can adjust the robot's task, modify the control parameters, or perform emergency intervention through the terminal module.

[0146] The robot body is made of high-strength aluminum alloy, which is lightweight and highly rigid. The use of aluminum alloy not only ensures the structural strength of the robot, but also effectively reduces the weight of the robot, making it convenient for transportation, installation and maintenance. Its overall structural design conforms to ergonomic principles, making it easy for operators to install and maintain the robot equipment on site.

[0147] The robot is equipped with a U-shaped wheel 10 with a U-shaped groove design and uses non-slip and wear-resistant rubber material to ensure that the robot can stably grip the power line and move smoothly on power lines of different materials. The U-shaped groove design helps to improve the robot's friction, especially in complex power line environments, and can maintain the robot's stability.

[0148] The robot's lifting drive worm gear sleeve 4 has automatic locking and overload protection functions to ensure that the cable can be stably fixed during the netting operation and to avoid accidents caused by excessive pressure or other factors. The automatic locking function can automatically adjust the clamping force when fixing the cable, while the overload protection function can monitor the applied pressure in real time to prevent excessive clamping of the cable and ensure the safety of the netting operation.

[0149] Working principle

[0150] In the sealing operation, the robot uses sensors installed on its body to provide real-time feedback of various parameter data. The precision electrical control system continuously receives and analyzes this data and compares it with the preset operation target. When a deviation is detected in the robot during lifting, walking, or pressing, the control system will immediately make adjustments by changing the motor control signal to correct the robot's movements. This process ensures the high precision and stability of the robot's operation and prevents misoperation or deviation from affecting the operation.

[0151] Intelligent terminal intervention and operation: Through the terminal display and intervention module, the operator can monitor the working status of four robots in real time. The system uses 3D rendering technology to display the real-time position and work progress of the robots. The operator can clearly see the working trajectory of the robots and make adjustments as needed. For example, the operator can adjust the task allocation of the robots through the touch screen, or manually stop the robots in an emergency to make necessary interventions.

[0152] The robustness of the robot body and hardware structure: The design of the robot body ensures stability and safety during operation. The robot, made of high-strength aluminum alloy, not only has high rigidity and strength and can withstand the pressure in complex environments, but also ensures the robot's portability when working on power lines. The driven U-shaped wheel 10 with U-shaped groove design and anti-slip and wear-resistant rubber material enable the robot to move stably in various power line environments, while the automatic locking and overload protection functions of the lifting drive worm gear sleeve 4 provide a guarantee for the safety of operation.

[0153] The precision electrical control system ensures the high accuracy of the robot when performing actions such as lifting, walking, and clamping. When the robot deviates from the preset trajectory, the system can detect it in real time and correct the robot's actions by adjusting the motor control signals, thus ensuring the accuracy and stability of the operation.

[0154] The terminal display and intervention module uses 3D visualization to enable operators to monitor the work progress in real time and intervene in the robot. Especially in case of abnormal situations, operators can quickly intervene manually to ensure the flexibility and safety of the work process.

[0155] The robot body is made of high-strength aluminum alloy, which makes the robot lightweight and highly rigid, making it easy to perform tasks in complex environments. At the same time, the automatic locking and overload protection functions of the driven U-shaped wheel 10 with U-shaped groove design and the lifting drive worm gear sleeve 4 further improve the stability of the robot and the safety of the operation process.

[0156] The system enables efficient operation of the net sealing process through real-time feedback and correction mechanisms, avoiding operation failures caused by robot deviations. At the same time, the intelligent control system has self-optimization capabilities, which can continuously improve the accuracy and efficiency of robot operations based on historical operation data.

[0157] Through this embodiment, the collaborative control system of the power grid sealing robot demonstrates high precision, high efficiency and high safety during operation, effectively solving many challenges faced in grid sealing operations.

[0158] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be modified within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A collaborative control system for a power grid sealing robot, characterized in that, include: Four identical robot bodies, each integrating multiple sensors to acquire various parameters; The central control system is used to monitor and coordinate the movements of the four robot bodies, receive remote control commands, and perform task allocation and status feedback. The remote control operating system allows operators to send commands to the central control system. The precision electrical control system controls the robot's lifting, walking, and clamping movements, and makes adjustments based on sensor feedback. The intelligent control module is used to precisely control the various actions of the four robots, ensuring the efficiency and accuracy of the net sealing operation; The intelligent control module includes: Task scheduling unit: Used to allocate tasks to the four robots according to the task instructions transmitted by the central control system, optimize the task allocation scheme, ensure that the robots work together, and avoid resource conflicts; Sensor data acquisition and analysis unit: used to acquire and process sensor data from each robot body in real time, preprocess the sensor data, and input the preprocessed data into the subsequent analysis module; Large Model Input and Vectorization Unit: Used to convert preprocessed data into high-dimensional vector sequences that can be processed by large models; Large Model Analysis Unit: Based on the Transformer architecture, this unit analyzes high-dimensional input vectors using a multi-head attention mechanism. The multi-head attention mechanism includes an absolute position head, a relative position head, a pressure head, and a tension head. Control parameter optimization and adjustment unit: used to calculate and optimize the control parameters of each robot based on the analysis results of the large model; Communication and Coordination Unit: Responsible for handling real-time communication and coordination between robots; exchanging their respective position information, status feedback and sensor data in real time to collaboratively complete tasks; at the same time, the communication and coordination unit processes intervention commands from the terminal display and intervention module to adjust and correct tasks; Real-time feedback and correction unit: When a deviation is detected between the robot's current action and the preset action, the real-time feedback and correction unit corrects the deviation and restores the robot's predetermined working trajectory by adjusting the robot's control signals. Data storage and recording unit: This unit is responsible for recording all sensor data, control parameters, and important information about the robot's task progress during the sealing operation. The communication module is used for the four robots to communicate with each other in real time during movement; The terminal display and intervention module displays the entire sealing process in 3D in real time. Operators can intervene in real time on the terminal, which is connected to a large model to coordinate and correct the robot's movements and positions.

2. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The remote control operating system adopts 2.4G wireless communication technology, which has anti-interference capabilities and encrypted transmission functions. Operators can send various control commands, including start, stop, acceleration, deceleration and steering, to the central control system through the input devices on the handheld remote control.

3. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The central control system shared by the four robots is built on an industrial-grade PLC and has redundancy backup function. It can decompose the net sealing task into multiple sub-tasks according to the preset net sealing operation process or the instructions sent by the operator through the remote control operating system, and reasonably allocate them to each robot according to the current status and location information of each robot. At the same time, it can monitor the task execution progress and status feedback of each robot in real time.

4. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The robot receives real-time data from sensors, which is analyzed and processed by a precision electrical control system. When a deviation between the actual action and the preset action is detected, the precision electrical control system adjusts the robot's lifting, walking, and pressing actions in real time by adjusting the drive current and voltage of the motor and the duty cycle of the control signal.

5. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The pre-trained large model in the intelligent control module is built on the Transformer architecture and trained with a large amount of power grid sealing operation data. It can perform in-depth analysis of the high-dimensional vector of the input sequence, accurately extract key information of different parameters using a multi-head attention mechanism, and calculate the precise control parameters of each robot at different operation stages through the fully connected layers and activation functions inside the model, including moving speed, acceleration, lifting height, and clamping force, so as to achieve precise control of various robot actions.

6. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The communication module adopts Mesh self-organizing network technology, supports multi-hop communication, and the four robots automatically build a communication network during operation, which can transmit location information, task status and sensor data to each other in real time and stably, ensuring the timeliness and reliability of data interaction.

7. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The terminal display and intervention module is developed based on a high-performance industrial tablet PC and is equipped with a high-definition touch screen. Through 3D modeling and real-time rendering technology, it displays the entire net sealing process in an intuitive 3D form, including the robot's position, posture, and the deployment status of the net. Operators can intervene in the robot's movements and position in real time on the terminal by touching the screen or connecting an external keyboard and mouse. The terminal is connected to a large model in the intelligent control module through a high-speed network to achieve unified coordination and correction of the robot.

8. The collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The sensors include a tension sensor, a pressure sensor, a gyroscope, an accelerometer, and a lidar. The tension sensor is used to monitor the tension parameters during net sealing in real time; the pressure sensor is used to obtain the clamping parameters; the gyroscope and accelerometer are used to monitor the posture changes of the robot body; and the lidar is used to obtain three-dimensional information of the surrounding environment. The data from the sensors are transmitted in real time to the precision electrical control system and intelligent control module via a high-speed data bus.

9. A collaborative control system for a power grid sealing robot according to claim 1, characterized in that: The power grid sealing robot body includes a bracket (1), on which lifting slide rails (2) are symmetrically fixedly connected. A motor mounting bracket (3) is slidably connected to the lifting slide rails (2). The motor mounting bracket (3) is driven to lift via a lifting drive worm gear sleeve (4) and a lifting mechanism gearbox (5). At least two walking motor gearboxes (6) are fixedly connected to the motor mounting bracket (3). A drive wheel (7) is fixedly connected to the power output shaft of each walking motor gearbox (6). 6) A walking drive motor (8) is fixedly connected to the power input shaft. The power output shaft of the lifting mechanism gearbox (5) is connected to the lifting drive worm sleeve (4). A lifting drive motor (9) is fixedly connected to the power input shaft of the lifting mechanism gearbox (5). A driven U-shaped wheel (10) is rotatably connected to the bracket (1) at the corresponding position of the drive wheel (7). The surfaces of the driven U-shaped wheel (10) and the drive wheel (7) are made of anti-slip and wear-resistant rubber material. The lifting drive worm sleeve (4) has automatic locking and overload protection functions.

10. A collaborative control system for a power grid sealing robot according to claim 9, characterized in that: The walking drive motor (8) and the lifting drive motor (9) are both high-precision servo geared motors with encoder feedback function. Each robot is equipped with a walking drive motor (8) and a lifting drive motor (9) which are electrically connected to the precision electrical control system through independent drive circuits. This system can precisely control the speed, direction and torque output of the drive wheel (7) and the driven U-shaped wheel (10).

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