Electric power blocking robot cooperative control system and robot thereof

Abstract

The invention discloses an electric power blocking robot cooperative control system and a robot thereof, and relates to the technical field of electric power robot control. The electric power blocking robot cooperative control system comprises four robot bodies of the same structure and various sensors, according to the system, robot collaborative operation is achieved through a central control system, a remote control operation system, an accurate electrical control system and an intelligent control module, actions such as lifting, walking and pressing are accurately controlled, real-time adjustment is conducted according to feedback of a sensor, and the intelligent control module optimizes control parameters of the robot through a multi-head attention mechanism on the basis of large model analysis; the robot achieves real-time communication and coordination through the Mesh ad hoc network technology, high efficiency of collaborative operation is ensured, the terminal display and intervention module provides a three-dimensional visual interface, an operator can monitor the operation progress in real time and conduct intervention, through intelligent control and collaborative operation, the efficiency of network blocking operation is greatly improved, manual intervention is reduced, and the working efficiency is improved. And the method has self-learning and optimization capabilities.

Description

Technical Field

[0001] The present invention relates to the technical field of power robot control, and in particular to a power grid sealing robot collaborative control system and a robot thereof. Background Art

[0002] Power grid sealing operations are an indispensable part of power line construction and maintenance, involving the installation and commissioning of line equipment. Traditional power grid sealing operations mostly rely on manual operations, and operators need to work at high altitudes, facing greater safety risks, and have low operating efficiency and are prone to misoperation. With the advancement of science and technology, more and more robots are being used in power grid sealing operations, but the existing technology still has certain limitations, such as the robot's single working function, lack of efficient collaborative control, and lack of real-time feedback and adjustment of operating accuracy and stability.

[0003] Chinese invention patent application CN119297833A discloses a network sealing quality control method and system based on a network sealing robot, which uses finite element analysis to achieve stable conductor network sealing under vibration environment and temperature changes, ensuring the safety of power grid operation. This technology controls parameters such as tension and temperature to achieve adaptive regulation during network sealing operations. However, the application of this method relies on precise parameter setting and analysis, and in the collaborative operation of multiple robots, manual intervention is still required to convey instructions. It lacks a high degree of automation and intelligence, especially when faced with complex operating environments and real-time dynamic changes. It is difficult for robots to adjust their operating behaviors in a timely manner, resulting in certain limitations on operating efficiency and safety.

[0004] Chinese utility model patent CN219892806U discloses an intelligent network sealing traction machine for power lines, which has a simple structure, can reduce construction costs, and improve the safety of cross-network sealing construction and network removal. The system makes the network sealing process more stable through the cooperation of friction wheels, guide wheels and other equipment, but the equipment only provides a single traction function and lacks multi-functional comprehensive capabilities. In addition, in the collaborative operation of robots, multiple robots cannot be efficiently coordinated and controlled. In addition, the robots in the network sealing operation do not make full use of the intelligent control system, and the real-time feedback and intelligent adjustment capabilities of sensor data during the operation are weak, and the accuracy and efficiency of the network sealing process cannot be achieved. Summary of the invention

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

[0006] The object of the present invention is achieved through the following technical solutions: A power grid sealing robot collaborative control system and the robot thereof, comprising: four robot bodies with the same structure, the robot bodies are integrated with a variety of sensors for obtaining various parameters; The central control system is used to monitor and coordinate the actions of the four robots, receive remote control commands, and perform task allocation and status feedback; A remote control system, through which the operator sends instructions to the central control system; Precise electrical control system controls the lifting, walking, and pressing movements of the robot body, and makes adjustments based on sensor feedback; Intelligent control module, used to accurately control the actions of the four robots to ensure efficient and accurate network blocking operations; The intelligent control module includes: Task scheduling unit: used to assign tasks to the four robots according to the task instructions transmitted by the central control system, optimize the task allocation plan, ensure that the robots work together, and avoid resource conflicts; Sensor data acquisition and analysis unit: used to collect and process sensor data from each robot body in real time, pre-process these sensor data, and input the pre-processed data into the subsequent analysis module; Large model input and vectorization unit: used to convert preprocessed data into a sequence of high-dimensional vectors that can be processed by the large model; Large model analysis unit: A large model based on the Transformer architecture uses a multi-head attention mechanism to analyze the input high-dimensional vector; the multiple heads include absolute position head, relative position head, compression force head, and 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, so as to collaboratively complete tasks; at the same time, the communication and coordination unit processes intervention instructions from the terminal display and intervention module to adjust and correct tasks; Real-time feedback and correction unit: When it detects that the robot's current action deviates from the preset action, the real-time feedback and correction unit makes corrections and restores the robot's preset working trajectory by adjusting the control signal of the robot body; 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 network blocking 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 network blocking process in real time in three dimensions. The operator can intervene in real time at the terminal, and the terminal is connected to the large model to make unified and coordinated corrections to the robot's movements and positions.

[0007] The remote control system uses 2.4G wireless communication technology, which has anti-interference ability and encrypted transmission function. The operator sends various control instructions including start, stop, acceleration, deceleration and steering to the central control system through the buttons on the handheld remote control or the joystick input device.

[0008] The central control system shared by the four robots is built based on an industrial-grade PLC and has a redundant backup function. It can decompose the network blocking task into multiple subtasks, such as positioning, moving, deploying, and fixing, according to the preset network blocking operation process or the instructions sent by the operator through the remote control operating system. It can also reasonably allocate tasks to each robot based on the current status and position information of each robot, and monitor the task execution progress and status feedback of each robot in real time.

[0009] The real-time data fed back by the robot through the sensors is analyzed and processed by the precise electrical control system. When a deviation is detected between the actual action and the preset action, the precise electrical control system adjusts the robot's lifting, walking, and pressing actions in real time by adjusting the motor's driving current, voltage, and duty cycle of the control signal.

[0010] The pre-trained large model in the intelligent control module is built based on the Transformer architecture. After being trained with a large amount of power grid closure operation data, it can perform in-depth analysis on the input sequence high-dimensional vectors, and use the multi-head attention mechanism to accurately extract the key information of different parameters. Through the fully connected layer and activation function within the model, the precise control parameters of each robot in different operation stages are calculated, including moving speed, acceleration, lifting height, and clamping force, to achieve precise control of the robot's various actions.

[0011] The communication module adopts Mesh self-organizing network technology and supports multi-hop communication. The four robots automatically build a communication network during the operation process, and 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.

[0012] The terminal display and intervention module is developed based on a high-performance industrial tablet computer and is equipped with a high-definition touch screen. Through 3D modeling and real-time rendering technology, it displays the entire network blocking process in an intuitive 3D form, including the robot's position, posture, and the deployment status of the network blocking. The operator can intervene in the robot's movements and positions in real time at the terminal by touching the screen and using 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 and coordinated correction of the robot.

[0013] The sensors include but are not limited to tension sensors, pressure sensors, gyroscopes, accelerometers and lidars. The tension sensors are used to monitor the tension parameters during net sealing in real time; the pressure sensors are used to obtain the clamping parameters; the gyroscopes and accelerometers are used to monitor the posture changes of the robot body; the lidars are used to obtain three-dimensional information of the surrounding environment. The sensor data is transmitted in real time to the precise electrical control system and intelligent control module via a high-speed data bus.

[0014] The main body of the electric power grid sealing robot includes a bracket, on which a lifting slide rail is symmetrically fixedly connected, and a motor mounting bracket is slidably connected to the lifting slide rail. The motor mounting bracket drives the lifting and lowering through a lifting drive worm sleeve and a lifting mechanism gear box. At least two travel motor gear boxes are fixedly connected to the motor mounting bracket, and a driving wheel is fixedly connected to the power output shaft of the travel motor gear box. A travel drive motor is fixedly connected to the power input shaft of the travel motor gear box. The power output shaft of the lifting mechanism gear box is connected to the lifting drive worm sleeve, and the lifting drive motor is fixedly connected to the power input shaft of the lifting mechanism gear box. A driven U-shaped wheel is rotatably connected to the corresponding position of the driving wheel on the bracket. The surfaces of the driven U-shaped wheel and the driving wheel are made of anti-slip and wear-resistant rubber material, and the lifting drive worm sleeve has automatic locking and overload protection functions.

[0015] Both the walking drive motor and the lifting drive motor are high-precision servo reduction motors with encoder feedback function. The walking drive motor and lifting drive motor equipped on each robot are electrically connected to the precise electrical control system through independent drive circuits, which can accurately control the speed, steering and torque output of the driving wheel and the driven U-shaped wheel.

[0016] The beneficial effects of the present invention are: 1. Through the collaborative work of four robots, efficient and accurate operations can be achieved during the power grid sealing operation. The system can quickly calculate the optimal task allocation and operation path of each robot through real-time task scheduling and large-scale model analysis of the intelligent control module. The real-time feedback of the sensor and the in-depth analysis of the large model enable the robot to adjust its behavior according to the environment and operation requirements, ensuring that each robot can collaborate synchronously during the operation, which significantly improves the efficiency of the grid sealing operation. The precise electrical control system ensures that the robot can achieve extremely high precision when performing lifting, walking, pressing and other actions. Through fine motor control signal adjustment, the system can accurately control the robot's actions under different working conditions, ensuring that the grid sealing operation achieves the predetermined goal and will not affect the operation quality due to robot motion deviation.

[0017] 2. The system shows strong flexibility and adaptability in complex environments. Through the integration of multiple sensors (such as tension sensors, pressure sensors, accelerometers, lidars, etc.), the robot can perceive the working environment and its own status in real time. Through real-time adjustment of the precise electrical control system, the robot can quickly adapt to changing operating conditions. Whether it is on different materials of power lines or in complex terrain, it can operate stably. The intelligent control module uses large model analysis to not only process the dynamic data of the robot itself, but also combine external environmental information to make dynamic decisions through a multi-head attention mechanism, thereby optimizing the robot's various control parameters (such as speed, clamping force, lifting height, etc.), so that the system can adaptively adjust the operation strategy to ensure the smooth progress of the network sealing operation process.

[0018] 3. The intelligent control module of the system has deep learning and self-optimization capabilities, and can analyze and predict based on historical operation data. The large model learns various patterns and rules in network blocking operations through continuous training, and can optimize the robot's control strategy based on feedback results during real-time analysis. The data storage and recording unit after each operation provides valuable feedback for system self-optimization, allowing the system to automatically adjust parameters in future operations, thereby improving work efficiency and accuracy. Through the multi-head attention mechanism, the system can comprehensively consider multiple key parameters, such as the robot's absolute position, relative position, clamping force, pulling force, etc., and generate optimal control instructions based on this information. The system's self-learning and optimization capabilities enable operations to become more precise and efficient with each execution.

[0019] 4. The robot body can operate stably in high-altitude operations or relatively narrow spaces. The anti-slip and wear-resistant rubber materials of the driven U-shaped wheel and the driving wheel ensure that the robot can stably clamp and drive smoothly on various power lines. It can also operate stably even in complex or dangerous environments. The lifting drive worm sleeve has automatic locking and overload protection functions. It can automatically adjust according to the pressure of the cable and ensure that the cable is firmly fixed during the network 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 compression. The precise electrical control system continuously adjusts according to real-time feedback data to ensure that the robot will not be unstable due to external factors (such as environmental changes), thereby ensuring the stability of the operation.

[0020] 5. The operator 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 computer and a high-definition touch screen to intuitively display the robot's position, posture, network blocking status, etc. during the operation in three dimensions. The operator can make manual adjustments through touch screens, keyboards, mice and other devices 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, and can ensure the stability and security of data transmission even in complex environments. The operator can flexibly control the robot to ensure the efficiency and safety of the operation process.

[0021] 6. Through the robot collaborative control system of the present invention, the power grid sealing operation no longer relies on a large amount of manual operation, but the robot performs the task efficiently and accurately. The system can complete a large range of grid sealing work in a very short time, greatly improving the operation efficiency. The robot can complete the most accurate operation in the shortest time through collaborative operation and real-time adjustment, reducing manual intervention and saving a lot of labor costs.

[0022] 7. The system's data storage and recording unit can record all key data during the network blocking operation, such as sensor data, control parameters, task execution progress, etc. These data can not only be used for post-analysis and operation evaluation, but also provide a basis for the system's self-learning and optimization. In future network blocking operations, the system can be improved and optimized based on historical data to further improve work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a system interaction diagram of the present invention; Figure 2 is a structural diagram of the present invention; Figure 3 This is a structural diagram of the robot body of the present invention.

[0024] Description of the symbols in the figure 1. Bracket; 2. Lifting slide rail; 3. Motor mounting bracket; 4. Lifting drive worm sleeve; 5. Lifting mechanism gearbox; 6. Travel motor gearbox; 7. Driving wheel; 8. Travel drive motor; 9. Lifting drive motor; 10. Driven U-shaped wheel. DETAILED DESCRIPTION

[0025] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0026] It is to be noted that the concepts of directions “left”, “right”, “up”, “down”, “front”, “back”, “inside” and “outside” in the following schemes are all relative directions and will not be listed one by one here.

[0027] Embodiment 1: like Figures 1 to 3 As shown, this embodiment describes a power grid sealing robot collaborative control system and its robot, which aims to achieve efficient and accurate power grid sealing operations. The system includes four robot bodies with the same structure. Each robot is equipped with a driven U-shaped wheel 10 with a U-shaped groove design, a driving wheel 7 driven by a walking drive motor 8, a lifting drive worm sleeve 4 and a variety of sensors for obtaining various operation parameters.

[0028] The driven U-shaped wheel 10 can stably walk on power lines of different materials and lift the worm sleeve 4 to ensure that the cable is firmly fixed during the network sealing process. The robot also integrates a variety of sensors, such as tension sensors, compression sensors, gyroscopes and lidars, which are used to collect real-time status information of the robot body (such as position, posture, speed, tension, compression force, etc.). These data will be used for subsequent control decisions.

[0029] The central control system is responsible for monitoring and coordinating the actions of the four robots. It receives remote control instructions and assigns tasks to each robot. The tasks include positioning, moving, pressing, lifting and other operations. The central control system also receives status feedback from each robot body, monitors the progress of task execution in real time, and ensures the overall collaborative operation of the system.

[0030] The remote control operating system enables the operator to remotely control the robot. Through input devices such as buttons and joysticks on the handheld remote control, the operator can send control commands such as start, stop, accelerate, decelerate, and turn. This wireless remote control system uses 2.4G wireless communication technology, has anti-interference capabilities and encrypted transmission functions, ensuring stable communication over long distances and in complex environments.

[0031] The precise electrical control system is responsible for controlling the robot's lifting, walking, pressing and other actions, and automatically adjusts according to the real-time data feedback from the sensor. 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 movements. 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.

[0032] The intelligent control module includes multiple functional units to ensure that the robot can complete efficient and accurate network blocking operations in complex environments. The key functional units of the intelligent control module are as follows: Task scheduling unit: According to the task instructions, the tasks are assigned to the four robots to ensure that the tasks are reasonably distributed among the four robots to avoid resource conflicts.

[0033] Sensor data acquisition and analysis unit: collects and preprocesses the robot's sensor data in real time, removes noise, and ensures that the data input into the subsequent analysis module is accurate and reliable.

[0034] Large model input and vectorization unit: converts sensor data into high-dimensional vectors that can be processed by the large model, facilitating the analysis and optimization of the large model.

[0035] Large model analysis unit: A large model based on the Transformer architecture analyzes the input high-dimensional vector through a multi-head attention mechanism, generates robot control instructions, and controls the robot's actions.

[0036] Control parameter optimization and adjustment unit: According to the analysis results of the large model, the control parameters of the robot are optimized to ensure the accuracy of the robot's movements.

[0037] Communication and coordination unit: handles real-time communication between the four robots, ensuring that the robots can coordinate with each other when performing tasks.

[0038] Real-time feedback and correction unit: When the robot's action deviates from the predetermined target, the system will make real-time corrections and adjust the control signal to ensure stable operation of the robot.

[0039] The data storage and recording unit is responsible for recording all sensor data, control parameters, robot task progress and other important information during the network blocking operation. The data storage is used for subsequent analysis and system optimization to improve the efficiency and accuracy of subsequent network blocking operations.

[0040] The terminal display and intervention module uses a high-performance industrial tablet computer and a high-definition touch screen to display the entire network blocking process in real time in three dimensions. The operator can intervene in the robot's actions in real time through the touch screen, such as emergency stop, manual adjustment of task allocation, etc.

[0041] How it works The electric power grid sealing robot collaborative control system of the present invention uses four robots working in collaboration to ensure efficient, stable and accurate grid sealing operations during power line grid sealing operations through precise sensor data collection, analysis and processing by intelligent control modules, and real-time feedback correction.

[0042] Task allocation and execution The task scheduling unit reasonably allocates different tasks (such as positioning, moving, 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 complete the task in coordination and avoid conflicts.

[0043] In the task scheduling process, a weighted allocation algorithm can be used to assign tasks to robots to ensure efficient execution of tasks. The specific scheduling can be improved through optimization algorithms (such as genetic algorithms or particle swarm optimization) to improve the efficiency and accuracy of task allocation.

[0044] Weighted task allocation algorithm formula: The task scheduling unit can select the most suitable robot for task allocation based on these weights.

[0045] Data collection and analysis The sensors on the robot body collect environmental data and robot status information in real time, including tension, compression 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 to convert it into the format required by the model.

[0046] Large model analysis and instruction generation The intelligent control module conducts deep learning on various data through large model analysis, uses a multi-head attention mechanism to analyze the relationship between different parameters, and generates control instructions for the robot (such as moving speed, acceleration, lifting height, etc.). This analysis is based on preset work requirements to ensure that each action of the robot meets the work objectives.

[0047] 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 instructions.

[0048] Multi-head attention mechanism formula: 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, compression force, tension, etc.

[0049] Motion control and feedback adjustment When the robot performs actual actions, the precise electrical control system will adjust the robot's control signals (such as motor drive current, voltage, etc.) in real time according to sensor feedback to ensure that it performs precise lifting, walking, pressing and other actions.

[0050] Real-time intervention and correction The operator monitors the entire network blocking process through the terminal display and intervention module. If any deviation is found, the operator can intervene in the robot's task execution in real time and adjust its actions to ensure the smooth completion of the network blocking operation.

[0051] Through the collaborative work of four robots, the central control system and intelligent control module can coordinate the tasks of each robot in real time, reduce operation time and improve network blocking efficiency.

[0052] The precise electrical control system combines sensor feedback and large model analysis to ensure the robot's precise operation in complex environments, reduce errors, and ensure the accuracy of network sealing operations.

[0053] The system can monitor and correct the robot's motion deviations in real time, ensure the stability of the robot's operation through a feedback mechanism, and avoid network blocking failures caused by improper operation.

[0054] The remote control operating system allows the operator to remotely control the robot, providing a flexible operating method. The real-time feedback and correction unit can make timely corrections when the robot's movements deviate, thereby improving operational safety.

[0055] The data storage and recording unit enables the system to record the data of each operation, provide data support for the optimization of subsequent operations, and further improve the overall performance of the system.

[0056] The power grid sealing robot collaborative control system of 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 operating efficiency and reliability of the robot system.

[0057] Embodiment 2: like Figures 1 to 3 As shown, this embodiment further describes in detail the specific working principles of the power grid sealing robot collaborative control system on the basis of Embodiment 1, such as sensor types and installation, large model analysis of intelligent control modules, Mesh self-organizing network communication modules and other characteristics.

[0058] The structures of the four robot bodies are exactly the same, including a bracket 1, on which a lifting slide rail 2 is symmetrically fixedly connected, and a motor mounting bracket 3 is slidably connected to the lifting slide rail 2. The motor mounting bracket 3 is driven to lift and lower through a lifting drive worm sleeve 4 and a lifting mechanism gear box 5. At least two walking motor gear boxes 6 are fixedly connected to the motor mounting bracket 3, and a driving wheel 7 is fixedly connected to the power output shaft of the walking motor gear box 6. A walking drive motor 8 is fixedly connected to the power input shaft of the walking motor gear box 6. The power output shaft of the lifting mechanism gear box 5 is connected to the lifting drive worm sleeve 4, and a lifting drive motor 9 is fixedly connected to the power input shaft of the lifting mechanism gear box 5. A driven U-shaped wheel 10 is rotatably connected to the corresponding position of the driving wheel 7 on the bracket 1. The surfaces of the driven U-shaped wheel 10 and the driving wheel 7 are made of anti-slip and wear-resistant rubber material, and the lifting drive worm sleeve 4 has automatic locking and overload protection functions.

[0059] The walking drive motor 8 and the lifting drive motor 9 are both high-precision servo reduction motors with encoder feedback function. The walking drive motor 8 and the lifting drive motor 9 equipped on each robot are connected to the precise electrical control system through independent drive circuits, which can accurately control the speed, steering and torque output of the driving wheel 7 and the driven U-shaped wheel 10.

[0060] The lifting drive motor 9 drives the lifting drive worm sleeve 4 to rotate, and the lifting drive worm sleeve 4 drives the motor mounting bracket 3 to move up and down through the lifting slide rail 2, and then the wire is pressed through the driving wheel 7 and the driven U-shaped wheel 10. The travel drive motor 8 drives the driving wheel 7 to rotate through the travel motor gear box 6, and the driving wheel 7 and the driven U-shaped wheel 10 drive the robot body to move along the wire through friction with the wire; The robot body integrates multiple sensors for real-time collection of operation data, including: Tension sensor: It adopts the strain gauge principle and is installed at the contact point between the driving wheel 7 and the wire to monitor the tension during net sealing.

[0061] Pressure sensor: It adopts the capacitive principle and is installed at the contact point between the driving wheel 7 and the wire to obtain the clamping parameters.

[0062] Gyroscope and accelerometer: monitor the posture changes of the robot body to ensure the stability of the robot during operation.

[0063] LiDAR: Obtains three-dimensional information of the surrounding environment to ensure that the robot can identify surrounding obstacles or changes, and assists in positioning and obstacle avoidance.

[0064] The central control system is built with industrial-grade PLC and has redundant backup function. It can decompose the network blocking task into multiple sub-tasks, such as positioning, moving, deploying, fixing, etc., according to the preset network blocking operation process or the instructions sent by the operator through the remote control operating system, and assign tasks to each robot in real time, and monitor the task execution progress of each robot through the task feedback mechanism.

[0065] The operator sends start, stop, acceleration, deceleration, steering and other instructions to the central control system through a handheld remote control. The remote control operating system uses 2.4G wireless communication technology, has anti-interference capabilities and encrypted transmission functions, ensuring data security and stability in the working environment.

[0066] The precise electrical control system automatically adjusts the robot's lifting, walking, pressing and other actions by monitoring sensor data in real time. The system can ensure that the robot can perform network sealing operations stably and efficiently in complex terrain and environments by adjusting the motor control signals.

[0067] The intelligent control module realizes precise control of the four robots through multifunctional units. The following are several functional units not mentioned in detail in Example 1: Sensor data acquisition and analysis unit: collects and processes sensor data from each robot body, including tension, compression, acceleration, posture, etc. After noise filtering, these data are converted into standardized parameters and input into the subsequent analysis module.

[0068] Large model analysis unit: A large model based on the Transformer architecture analyzes high-dimensional parameter data through a multi-head attention mechanism. The task instructions of each robot are generated according to these analysis results. During the analysis process, the model will dynamically adjust the control parameters of each operation, such as moving speed, acceleration, lifting height, and clamping force.

[0069] The real-time communication between robots adopts Mesh self-organizing network technology and supports multi-hop communication, ensuring that the four robots can exchange data in real time and stably during the network blocking 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]%.

[0070] The system includes a data storage unit for recording all sensor data, control parameters and the robot's task execution progress during the network blocking 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.

[0071] The operator monitors the network blocking process in real time through the terminal display and intervention module. The module uses 3D modeling and real-time rendering technology to intuitively display the network blocking progress, robot position and posture changes. The operator can intervene in the robot's actions through the terminal, such as emergency stop, task reallocation, etc.

[0072] How it works Data collection and preprocessing Each robot collects real-time data on the working environment and the robot's status through installed sensors. These data include tension, compression, acceleration, posture, etc., and are transmitted in real time to the precise electrical control system and intelligent control module through a high-speed data bus. After preprocessing and denoising, the sensor data is analyzed and processed by the intelligent control module.

[0073] Sensor data collection and preprocessing To ensure the accuracy of the data, filtering algorithms can be used to remove noise and perform standardization.

[0074] Data normalization formula: Data standardization helps ensure stability during subsequent processing and enables different types of sensor data to be processed uniformly.

[0075] Intelligent control module analysis and decision making The large model analysis unit in the intelligent control module performs in-depth analysis based on the pre-trained Transformer architecture and extracts key information from different angles through a multi-head attention mechanism. The analysis results determine parameters such as the moving speed, lifting height, and clamping force of each robot to ensure that the robot can perform tasks according to predetermined goals.

[0076] Task allocation and coordination The task scheduling unit assigns tasks to 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 own task execution path according to its current status and task execution progress to avoid conflicts or duplication of work.

[0077] Real-time feedback and correction During the execution process, if the robot finds that there is a deviation between the current action and the preset action, the real-time feedback and correction unit will make corrections. By adjusting the control signals such as the motor drive current, voltage and duty cycle, the robot will return to the predetermined working trajectory to ensure the accuracy and stability of the network blocking operation.

[0078] Based on the real-time data fed back by the sensors, the precise electrical control system uses control algorithms to calculate adjustment parameters (such as motor current, voltage, etc.) to correct the robot's movements.

[0079] PID control algorithm formula: When adjusting the robot's movements with real-time feedback, an adaptive control algorithm can also be used to make adjustments based on real-time feedback data and errors to optimize the robot's movements.

[0080] Adaptive control algorithm formula: This algorithm can continuously adjust while the robot is performing tasks to ensure the accuracy and stability of the operation.

[0081] Terminal intervention and optimization The operator can observe the progress of the network blocking operation in real time through the terminal display and intervention module, and can intervene, such as pausing the operation, reallocating tasks, or adjusting the robot's operation path, in order to deal with emergencies.

[0082] The system uses four robots working together, precise task allocation and intelligent control to complete network blocking operations quickly and accurately. Real-time optimization of sensor feedback and large-scale model analysis ensures that every action of the robot meets preset requirements.

[0083] Mesh self-organizing network technology ensures stable communication between the four robots in a complex environment. The system can exchange task data and status information in real time during operation to avoid communication interruption or data loss.

[0084] The large model analysis unit uses deep learning and multi-head attention mechanisms to conduct in-depth analysis and self-optimization of the data in each operation. The system can continuously improve the robot's operating efficiency and accuracy.

[0085] The operator can flexibly control the robot through the remote control system, and the terminal intervention module ensures that any abnormalities in the operation process can be corrected in time to ensure operation safety.

[0086] Through the above embodiments, the present invention provides an efficient, accurate, reliable and intelligent power grid sealing robot collaborative control system, which not only optimizes the traditional grid sealing operation process, but also greatly improves the operation efficiency and safety.

[0087] Embodiment 3: like Figures 1 to 3As shown, this embodiment will further describe in detail the parts not mentioned in the previous embodiments, such as the precise electrical control system, terminal display and intervention module, and hardware design of the robot body in the power grid sealing robot collaborative control system on the basis of Embodiment 1 and Embodiment 2, and focus on how to ensure the stability and accuracy of the grid sealing operation through real-time data feedback and precise adjustment of the robot's movements, as well as improve controllability and operational safety through the terminal display and intervention module.

[0088] In the collaborative control system of the power grid sealing robot, the robot uses sensors to provide real-time feedback of various parameter data, such as position information, posture changes, pulling force, pressing force, etc. The precise electrical control system is responsible for analyzing these real-time data and evaluating whether the current action performed by the robot meets the preset goals. If it is found that the robot's action deviates from the predetermined action, the precise electrical control system will adjust the robot in real time by adjusting the motor's driving current, voltage, and duty cycle of the control signal, restore its working trajectory, and ensure that the robot accurately performs lifting, walking, pressing and other tasks.

[0089] The key functions of the control system are: Real-time data analysis: Collect data from sensors in real time, filter and process it to ensure that the input control data is accurate.

[0090] Deviation detection and correction: When the robot is performing a task, if a movement deviation is detected, the system will compensate for the deviation by adjusting the motor parameters (such as current, voltage, etc.) to ensure that the robot can always maintain the predetermined trajectory.

[0091] High-efficiency feedback mechanism: The precise electrical control system uses an efficient feedback mechanism to quickly respond to changes in the robot's state, adjust the robot's operating state, optimize the robot's behavior, and ensure efficient network blocking operations.

[0092] The terminal display and intervention module uses a high-performance industrial tablet computer and a high-definition touch screen, combined with 3D modeling and real-time rendering technology, to provide a visual network blocking operation monitoring interface. The operator can use this module to monitor the position, posture, network blocking deployment status, etc. of the four robots in real time, ensuring operation coordination from a global perspective.

[0093] This module includes the following functions: 3D real-time display: The operator can intuitively view the robot's current position, working posture and network blocking progress through the 3D view. Through real-time rendering technology, the operator can clearly see every link of the network blocking operation and make corresponding adjustments to the robot's actions.

[0094] Real-time intervention and adjustment: The operator can intervene in the robot's movement and position in real time through input devices such as touch screen, external keyboard or mouse, such as emergency stop, manual adjustment of task allocation, etc., to ensure rapid response and adjustment of operations during operation.

[0095] 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 problems are found during the robot's execution, the operator can adjust the robot's tasks, modify control parameters or perform emergency intervention through the terminal module.

[0096] 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 robot equipment on site.

[0097] The robot is equipped with a driven U-shaped wheel 10 with a U-shaped groove design and uses anti-slip and wear-resistant rubber material to ensure that the robot can stably clamp the power line and travel smoothly on power lines of different materials. The U-shaped groove design helps to improve the friction of the robot, especially in the environment of complex power lines, and can maintain the stability of the robot.

[0098] The robot's lifting drive worm sleeve 4 has automatic locking and overload protection functions, which ensure that the cable can be stably fixed during the network sealing operation and avoid accidents caused by excessive pressure or other factors. The automatic locking function can automatically adjust the clamping force when fixing the cable, and the overload protection function can monitor the applied pressure in real time to prevent excessive compression of the cable and ensure the safety of the network sealing operation.

[0099] How it works Real-time motion detection and adjustment During the network sealing operation, the robot uses sensors installed on the robot body to provide real-time feedback of various parameter data. The precise electrical control system continuously receives and analyzes this data and compares it with the preset operation goals. When it detects that the robot has deviations during lifting, walking or pressing, the control system will immediately adjust it to correct the robot's movements through changes in the motor control signal. This process ensures the high precision and stability of the robot's operation and prevents the operation from being affected by misoperation or deviations.

[0100] Intelligent terminal intervention and operation Through the terminal display and intervention module, the operator can monitor the working status of the four robots in real time. The system uses 3D rendering technology to display the real-time position and operation progress of the robots. The operator can clearly see the robot's operation trajectory and adjust it as needed. For example, the operator can adjust the robot's task allocation through the touch screen, or manually stop the robot in an emergency and perform necessary intervention.

[0101] Stability 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 material not only has high rigidity and strength, and can withstand pressure in complex environments, but also ensures the portability of the robot when operating on power lines. The U-groove designed driven U-shaped wheel 10 and the anti-slip and wear-resistant rubber material enable the robot to travel stably in various power line environments, while the automatic locking and overload protection functions of the lifting drive worm sleeve 4 provide guarantees for the safety of the operation.

[0102] The precise electrical control system ensures the robot's high accuracy when performing actions such as lifting, walking, and pressing. When the robot deviates from the preset trajectory, the system can detect it in real time and correct the robot's action by adjusting the motor control signal to ensure the accuracy and stability of the operation.

[0103] The terminal display and intervention module uses three-dimensional visualization to enable the operator to monitor the progress of the operation in real time and intervene in the robot. Especially when encountering abnormal situations, the operator can quickly intervene manually to ensure the flexibility and safety of the operation process.

[0104] 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 a U-shaped groove design and the lifting drive worm sleeve 4 further enhance the stability of the robot and the safety of the operation process.

[0105] The system uses real-time feedback and correction mechanisms to enable the network blocking operation process to be carried out efficiently and avoid operation failures due to robot deviations. At the same time, the intelligent control system has self-optimization capabilities and can continuously improve the accuracy and efficiency of robot operations based on historical operation data.

[0106] Through this embodiment, the collaborative control system of the power grid sealing robot demonstrates high precision, high efficiency and high safety during the operation process, effectively solving many challenges faced in the grid sealing operation.

[0107] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein and should not be regarded 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 the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not depart from the spirit and scope of the present invention, and should all be within the scope of protection of the claims attached to the present invention.

Claims

1. A power grid sealing robot collaborative control system, characterized in that: include: Four robot bodies with the same structure, each robot body integrating multiple sensors for obtaining various parameters; A central control system, used to monitor and coordinate the actions of the four robot bodies, receive remote control instructions and perform task allocation and status feedback; A remote control system, through which the operator sends instructions to the central control system; Precise electrical control system controls the lifting, walking, and pressing actions of the robot body, and makes adjustments based on sensor feedback; Intelligent control module, used to accurately control the actions of the four robots to ensure efficient and accurate network blocking operations; The intelligent control module comprises: Task scheduling unit: used to assign tasks to the four robots according to the task instructions transmitted by the central control system, optimize the task allocation plan, ensure that the robots work together, and avoid resource conflicts; Sensor data acquisition and analysis unit: used to collect and process sensor data from each robot body in real time, pre-process these sensor data, and input the pre-processed data into the subsequent analysis module; Large model input and vectorization unit: used to convert preprocessed data into a sequence of high-dimensional vectors that can be processed by the large model; Large model analysis unit: A large model based on the Transformer architecture uses a multi-head attention mechanism to analyze the input high-dimensional vector; the multiple heads include absolute position head, relative position head, compression force head, and 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, so as to collaboratively complete tasks; at the same time, the communication and coordination unit processes intervention instructions from the terminal display and intervention module to adjust and correct tasks; Real-time feedback and correction unit: When it detects that the robot's current action deviates from the preset action, the real-time feedback and correction unit makes corrections and restores the robot's preset working trajectory by adjusting the control signal of the robot body; 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 network blocking 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 network blocking process in real time in three dimensions. The operator can intervene in real time at the terminal, and the terminal is connected to the large model to make unified and coordinated corrections to the robot's movements and positions.

2. The power grid sealing robot collaborative control system according to claim 1 is characterized by: The remote control system adopts 2.4G wireless communication technology, has anti-interference ability and encrypted transmission function. The operator sends various control instructions including start, stop, acceleration, deceleration and steering to the central control system through the buttons on the handheld remote control or the joystick input device.

3. The power grid sealing robot collaborative control system according to claim 1 is characterized by: The central control system shared by the four robots is built based on industrial-grade PLC and has redundant backup function. It can decompose the network blocking task into multiple subtasks, such as positioning, moving, deploying, and fixing, according to the preset network blocking 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 position information of each robot, and monitor the task execution progress and status feedback of each robot in real time.

4. The power grid sealing robot collaborative control system according to claim 1 is characterized by: The real-time data fed back by the robot through the sensor is analyzed and processed by the precise electrical control system. When a deviation is detected between the actual action and the preset action, the precise electrical control system adjusts the robot's lifting, walking and pressing actions in real time by adjusting the motor's driving current, voltage and the duty cycle of the control signal.

5. The power grid sealing robot collaborative control system according to claim 1 is characterized by: The pre-trained large model in the intelligent control module is built based on the Transformer architecture. After being trained with a large amount of power grid closure operation data, it can perform in-depth analysis on the input sequence high-dimensional vectors, and use the multi-head attention mechanism to accurately extract the key information of different parameters. Through the fully connected layer and activation function within the model, the precise control parameters of each robot in different operation stages are calculated, including moving speed, acceleration, lifting height, and clamping force, to achieve precise control of the robot's various actions.

6. The power grid sealing robot collaborative control system according to claim 1 is characterized by: The communication module adopts Mesh self-organizing network technology and supports multi-hop communication. The four robots automatically build a communication network during the operation process, and 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 power grid sealing robot collaborative control system according to claim 1, characterized in that: The terminal display and intervention module is developed based on a high-performance industrial tablet computer and is equipped with a high-definition touch screen. Through three-dimensional modeling and real-time rendering technology, it displays the entire network blocking process in an intuitive three-dimensional form, including the robot's position, posture, and the deployment status of the network blocking. The operator can intervene in the robot's movements and positions in real time at the terminal by touching the screen and using 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 and coordinated correction of the robot.

8. The power grid sealing robot collaborative control system according to claim 1 is characterized by: The sensors include but are not limited to tension sensors, pressure sensors, gyroscopes, accelerometers and laser radars. 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 gyroscopes and accelerometers are used to monitor the posture changes of the robot body, and the laser radar is used to obtain three-dimensional information of the surrounding environment. The data of the sensors are transmitted in real time to the precise electrical control system and the intelligent control module via a high-speed data bus.

9. A power grid sealing robot, characterized in that: The power grid sealing robot body comprises a bracket (1), the bracket (1) is symmetrically fixedly connected to a lifting slide rail (2), the lifting slide rail (2) is slidably connected to a motor mounting bracket (3), the motor mounting bracket (3) is driven to rise and fall through a lifting drive worm sleeve (4) and a lifting mechanism gear box (5), the motor mounting bracket (3) is fixedly connected to at least two travel motor gear boxes (6), the power output shaft of the travel motor gear box (6) is fixedly connected to a driving wheel (7), and the travel motor gear box ( 6) A travel drive motor (8) is fixedly connected to the power input shaft, the power output shaft of the lifting mechanism gear box (5) is connected to the lifting drive worm sleeve (4), the power input shaft of the lifting mechanism gear box (5) is fixedly connected to the lifting drive motor (9), a driven U-shaped wheel (10) is rotatably connected to a position corresponding to the driving wheel (7) on the bracket (1), the surfaces of the driven U-shaped wheel (10) and the driving wheel (7) are made of anti-slip and wear-resistant rubber material, and the lifting drive worm sleeve (4) has automatic locking and overload protection functions.

10. The 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 reduction motors with encoder feedback function. The walking drive motor (8) and the lifting drive motor (9) equipped with each robot are electrically connected to a precise electrical control system through independent drive circuits, respectively, and can accurately control the rotation speed, steering, and torque output of the driving wheel (7) and the driven U-shaped wheel (10).

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