Visual network cable arrangement robot

Abstract

The invention relates to the technical field of network cable arrangement equipment, in particular to a visual network cable arrangement robot which comprises a robot body, an environment sensing module, a mechanical execution module, an energy and driving module and a communication and control module, and the environment sensing module, the mechanical execution module, the energy and driving module and the communication and control module are integrated in the robot body. The robot further comprises an independent handheld visual man-machine interaction module connected with the robot body through wireless communication. The environment sensing module collects environment data through a sensor and constructs a three-dimensional model, the mechanical execution module completes network cable laying, fixing and detecting, the visual man-machine interaction module achieves task issuing and state displaying, the energy and driving module provides electric power and moving power, and the communication and control module achieves data processing, instruction transmission and multi-machine cooperation. According to the invention, the network cable arrangement efficiency and precision can be improved, the labor cost is reduced, and the wiring safety and stability are ensured.

Description

Technical Field

[0001] This invention relates to the field of network cable laying equipment technology, specifically a visual network cable laying robot. Background Technology

[0002] In current network cabling operations, most work relies on manual labor. Workers must carry tools and navigate complex environments (such as server rooms and building wall cavities), resulting in high labor intensity and low cabling efficiency. This is especially problematic in large-area, multi-node cabling scenarios, where issues like cabling location deviations and cable damage are common. Manual cabling makes it difficult to accurately identify existing cable paths and obstacle distribution, frequently leading to cable failures due to misoperation and unnecessary economic losses. Furthermore, the inability to record cabling process data in real time makes it difficult to trace cabling information during subsequent maintenance, increasing maintenance difficulty and costs.

[0003] With the rapid development of network technology, there are numerous new, renovated, and expanded substation projects. Relying solely on manual cabling is inefficient and prone to errors, especially when laying network cables in indoor cable trenches and shafts. The internal environment is complex, with tangled cables and many areas inaccessible to personnel, making cabling impossible. Furthermore, due to their long service life, the safety of internal facilities cannot be verified, and the risk of electric shock is unknown. Poor air circulation in confined spaces can also pose risks of suffocation and poisoning, seriously impacting the safety of personnel and equipment. Currently, substation network cabling is mainly done manually, which is time-consuming and labor-intensive. The complex environment of cable trenches makes cabling very difficult, and manual cabling may damage other network cables or electrical cables. Entering old cable trenches also carries risks of electric shock, suffocation, and poisoning. Moreover, manual cabling is prone to errors, leading to rework.

[0004] In addition, traditional cabling methods lack effective visualization, interaction and collaboration mechanisms, making it impossible for operators to keep track of the overall cabling progress and robot operation status in real time. When cabling multiple areas simultaneously, work conflicts are likely to occur, further reducing the overall efficiency of cabling operations and making it difficult to meet the needs of modern high-efficiency cabling. Summary of the Invention

[0005] This invention provides a visual network cable laying robot that overcomes the shortcomings of the prior art and can effectively solve the problems of low efficiency, poor accuracy, difficult maintenance and lack of coordination mechanism of manual wiring.

[0006] The technical solution of this invention is achieved through the following measures: a visual cable laying robot, comprising a robot body, and further comprising an environmental perception module, a mechanical execution module, a visual human-machine interaction module, an energy and drive module, and a communication and control module. The environmental perception module, mechanical execution module, energy and drive module, and communication and control module are integrated inside the robot body. The visual human-machine interaction module is an independent handheld device connected to the robot body via wireless communication. The environmental perception module is used to collect spatial data and image information of the cabling environment through sensors, construct a three-dimensional digital model, and identify the direction and location of existing cables and the type and distribution of obstacles. The mechanical execution module is used to complete the cabling laying through a mechanical structure. The system includes network cable laying, positioning and fixing, and continuity detection. A visual human-machine interaction module receives wiring task parameters input by the operator, displays real-time images from the environmental perception module and the robot's operating status, and receives and parses control commands in the form of voice, gestures, or physical buttons. An energy and drive module provides power to all modules and drives the robot's movement. A communication and control module receives and analyzes the perception data from the environmental perception module to generate motion control commands, transmits these commands to the mechanical execution module and the energy and drive module, receives task commands from the visual human-machine interaction module and provides feedback on the execution status, enabling information exchange and task allocation during multi-robot collaborative operations.

[0007] The following are further optimizations and / or improvements to the above-mentioned technical solution: The sensors in the aforementioned environmental perception module may include a lidar and an RGB-D depth camera. The lidar is used to scan the 3D spatial data of the cabling environment in 360°, and the RGB-D depth camera is used to acquire color images and object depth information of the cabling environment to assist in building a 3D model.

[0008] The aforementioned mechanical execution module may include a six-axis collaborative robotic arm and a mobile chassis. The end of the six-axis collaborative robotic arm may be equipped with a cable guide wheel assembly, a vacuum suction fixture, and a network test probe. These three components are distributed circumferentially along the rotation axis of the end of the robotic arm and can switch work positions through an electric rotary joint. The mobile chassis adopts omnidirectional wheel drive to move the robot body in the wiring environment and precisely adjust the working position.

[0009] The aforementioned environmental perception module can have a built-in material recognition model for identifying cable paths and cable tray locations based on image features.

[0010] The aforementioned lidar has an angular resolution of 0.1°, a maximum ranging distance of 50 meters, and a scanning frequency of 10Hz.

[0011] The aforementioned communication and control module may include an edge computing unit for localized processing of environmental perception data and real-time control of mechanical execution modules.

[0012] The aforementioned six-axis collaborative robotic arm may be equipped with a force sensor at its end to detect contact force during operation, with a measurement range of 0-50N.

[0013] The aforementioned energy and drive module may include a mode switching unit for switching between CPU low-power mode, high-performance mode, and deep sleep mode according to the robot's workload.

[0014] The aforementioned communication and control module may also include a storage operation unit for storing historical operation data and performing traceability queries on the stored historical operation data.

[0015] The aforementioned communication and control module may also include an alarm unit, which is used to issue an audible and visual alarm signal and transmit it synchronously to the visual interaction module when abnormal pressure of the robotic arm, excessive route deviation, or excessive bending radius of the network cable is detected.

[0016] This invention utilizes an environmental perception module to accurately capture spatial and image information of the cabling environment, construct a 3D digital model, and identify existing cables and obstacles, providing comprehensive and reliable environmental data support for cabling operations and avoiding cabling deviations caused by missing environmental information. A mechanical execution module, relying on a mechanical structure, completes network cable laying, fixing, and continuity testing, replacing traditional manual operations, reducing the uncertainty of manual operations, and improving the accuracy and efficiency of cabling operations. A visual human-machine interaction module enables efficient interaction between operators and robots, facilitating real-time distribution of task parameters, viewing of on-site images and robot operating status, ensuring operators can promptly grasp the work progress. An energy and drive module provides stable power to each module and drives robot movement, ensuring continuous robot operation during cabling. A communication and control module coordinates data interaction and command transmission among modules, generating precise control commands and enabling multi-robot collaborative operations, avoiding operational conflicts when cabling in multiple areas. Overall, this invention significantly reduces the intensity of manual labor, decreases the error rate in the cabling process, and shortens the cabling operation cycle. At the same time, it facilitates the subsequent tracing of cabling details through historical operation data, reducing maintenance difficulty and cost. It can adapt to a variety of complex cabling scenarios and effectively solves the problems of low efficiency, poor accuracy, difficult maintenance, and lack of collaboration mechanism in traditional manual cabling. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall structure of the visualization network cable laying robot according to an embodiment of the present invention.

[0018] Figure 2 This is a system block diagram of the visual network cable laying robot according to an embodiment of the present invention.

[0019] The codes in the attached diagram are as follows: 1 represents the environmental perception module, 2 represents the mechanical execution module, 3 represents the energy and drive module, and 4 represents the mobile chassis. Detailed Implementation

[0020] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0021] The present invention will be further described below with reference to embodiments: Example 1: As Figure 1 , Figure 2 As shown, this embodiment provides a visual cable laying robot, including a robot body, an environmental perception module, a mechanical execution module, a visual human-machine interaction module, an energy and drive module, and a communication and control module. The environmental perception module, mechanical execution module, energy and drive module, and communication and control module are integrated inside the robot body. The visual human-machine interaction module is an independent handheld device connected to the robot body via wireless communication. The environmental perception module is used to collect spatial data and image information of the cabling environment through sensors, construct a three-dimensional digital model, and identify the direction and location of existing cables and the type and distribution of obstacles. The mechanical execution module is used to complete the laying of the cable through a mechanical structure. The system includes positioning and fixing, and line continuity detection. The visual human-machine interaction module receives wiring task parameters input by the operator, displays real-time images of the environment acquired by the environmental perception module and the robot's operating status, and receives and parses control commands in the form of voice, gestures, or physical buttons. The energy and drive module provides power to all modules and drives the robot's movement. The communication and control module receives and analyzes the perception data from the environmental perception module to generate motion control commands, transmits these commands to the mechanical execution module and the energy and drive module, receives task commands from the visual human-machine interaction module and provides feedback on the execution status, enabling information exchange and task allocation during multi-robot collaborative operations. This allows for clear division of labor and collaborative work among modules, replacing manual labor in complex wiring operations, avoiding the limitations of manual operation, improving overall wiring efficiency and accuracy, and enabling multi-robot collaborative functionality to adapt to large-area wiring needs while reducing operational conflicts.

[0022] In this embodiment, the environmental perception module's sensors include a LiDAR and an RGB-D depth camera. The LiDAR is used to scan the 3D spatial data of the cabling environment in 360°, while the RGB-D depth camera is used to acquire color images and object depth information of the cabling environment to assist in constructing a 3D model. The LiDAR can acquire environmental spatial data from all directions, ensuring no scanning blind spots, while the RGB-D depth camera can supplement the color images and depth information. The combination of the two makes the constructed 3D digital model more accurate, providing reliable data for subsequent cabling route planning and avoiding cabling deviations caused by missing environmental information. This improves the comprehensiveness and accuracy of environmental perception, laying a solid data foundation for cabling operations.

[0023] In this embodiment, the mechanical execution module includes a six-axis collaborative robotic arm and a mobile chassis. The end effector of the six-axis collaborative robotic arm is equipped with cable guide wheels, a vacuum suction gripper, and a network test probe, all distributed circumferentially along the rotation axis of the end effector. Workstation switching is achieved via an electrically operated rotary joint. The mobile chassis employs omnidirectional wheel drive to move the robot body within the wiring environment and precisely adjust its working position. The six-axis collaborative robotic arm possesses multi-degree-of-freedom motion capabilities, flexibly adapting to different wiring angles and positional requirements. Different end effector components achieve integrated wiring, fixing, and testing operations through workstation switching, eliminating the need for additional tool changes and improving work efficiency. The omnidirectional wheel-driven mobile chassis allows the robot to move flexibly in confined spaces, precisely reaching the work point. This automates and integrates wiring operations, reducing operational steps and improving wiring accuracy and mobility.

[0024] In this embodiment, the environmental perception module has a built-in material recognition model for identifying cable paths and cable tray locations based on image features. The material recognition model can distinguish between different cables and cable trays through image features, avoiding misidentification of existing cables and accurately locating cable tray positions to ensure network cables are accurately laid to designated locations. This further improves the targeting of environmental recognition, reduces interference with existing facilities during cabling, and ensures cabling accuracy.

[0025] In this embodiment, the lidar has an angular resolution of 0.1°, a maximum ranging distance of 50 meters, and a scanning frequency of 10Hz. The high angular resolution ensures the precision of spatial data acquisition, the long ranging distance is suitable for large-space cabling scenarios, and the high scanning frequency allows for real-time updates of environmental data, avoiding cabling errors caused by data lag. This allows the lidar to adapt to cabling environments of different scales, continuously providing accurate real-time spatial data.

[0026] In this embodiment, the communication and control module includes an edge computing unit for localized processing of environmental perception data and real-time control of the mechanical execution module. The edge computing unit can quickly process environmental perception data locally on the robot, reducing the latency of data transmission to a remote server and ensuring that control commands to the mechanical execution module are issued in real time, avoiding wiring deviations caused by command delays. This improves the timeliness of data processing and command transmission, ensuring the real-time performance and accuracy of wiring operations.

[0027] In this embodiment, a force sensor is installed at the end of the six-axis collaborative robotic arm to detect contact forces during operation, with a measurement range of 0-50N. The force sensor can monitor the contact forces between the robotic arm and cables or obstacles in real time. When the contact force exceeds a safety threshold, it can promptly feed back to the communication and control module to adjust the robotic arm's movements, preventing cable damage or robotic arm malfunction due to excessive force. This protects the cables and robotic arm, reducing equipment wear and wiring failures.

[0028] In this embodiment, the energy and drive module includes a mode switching unit, used to switch between CPU low-power mode, high-performance mode, and deep sleep mode according to the robot's workload. When the robot is in standby or light-load state, it switches to low-power or deep sleep mode to reduce energy consumption; when in high-load wiring state, it switches to high-performance mode to ensure efficient operation of each module; in this way, energy can be rationally allocated, the robot's endurance can be extended, and it can adapt to different workload requirements.

[0029] In this embodiment, the communication and control module also includes a storage operation unit for storing historical operation data and performing traceability queries on this data. The storage operation unit can record information such as task parameters, robot operating status, and environmental data during the cabling process. During subsequent maintenance, staff can query historical data through a visual human-machine interaction module to quickly locate fault points or understand cabling details. This provides data support for subsequent maintenance, reducing maintenance difficulty and costs.

[0030] In this embodiment, the communication and control module also includes an alarm unit, which issues an audible and visual alarm signal and simultaneously transmits it to the visual interaction module when abnormal robotic arm pressure, excessive route deviation, or excessively small network cable bending radius is detected. When an abnormality occurs, the alarm unit can promptly alert the operator and transmit the abnormal information to the visual human-machine interaction module, allowing the operator to quickly understand the type of abnormality and take countermeasures, preventing the abnormality from escalating into wiring failures or equipment damage. This allows for timely detection and handling of abnormalities during the wiring process, ensuring the safety and stability of the wiring operation.

[0031] This invention combines multi-sensor fusion and edge computing technologies, utilizing AI algorithms and modular design to formulate cabling schemes. It collects environmental information in real time and obtains scene information through a human-machine interface, relying on a robotic arm to automatically lay and fix network cables. This achieves automatic network cable laying functionality in different scenarios, making network cable deployment safer, simpler, and more reliable. Its main structure includes an environmental perception module, a mechanical execution module, a visual human-machine interaction module, an energy and drive module, and a communication and control module. The environmental perception module includes 3D spatial scanning, obstacle recognition, and cable feature detection functions. 3D spatial scanning utilizes a LiDAR (360° scanning, angular resolution 0.1°, maximum range 50 meters) and an RGB-D depth camera (global shutter, depth accuracy ±1mm) to construct a high-precision digital twin model. Obstacle recognition distinguishes between fixed obstacles (walls, pipes) and dynamic obstacles (personnel, equipment). Cable feature detection uses a material recognition model to identify existing cable paths and cable tray positions. The mechanical execution module employs a six-axis collaborative robotic arm (with a force sensor at the end, capable of switching between cabling, fixing, and detection functions). The robot features a multi-modal interface (MTI) with an omnidirectional wheel-driven chassis and a step-crossing mechanism to overcome obstacles. The visual human-machine interface module is a handheld terminal supporting multi-modal input (voice, gestures, physical buttons), capable of issuing tasks, displaying environmental information, monitoring operating conditions, and sending alarms. Its platinum resistance temperature sensor offers superior linearity compared to thermocouples and thermistors. The energy and drive module is powered by a drive motor (peak torque > 15 Nm, IP67 protection rating) and a 48V 20Ah lithium battery (supporting fast charging). A mode switching unit allows for intelligent power saving by switching between three CPU operating modes. The communication and control module, relying on an edge computing unit and control center, controls robot movements and enables historical data tracing and multi-robot collaborative scheduling (topology diagram shown in figure). Figure 2 (As shown).

[0032] In practice, the network cable laying task is first created and issued through the human-machine interface, clarifying the cabling scope. Then, the environmental perception module collects and analyzes the environmental data of the work scene, and formulates the cabling route and plan in combination with AI intelligent algorithms. The network cable to be laid is then fixed on the robot. The robot automatically lays the cable according to the predetermined plan. The operator can monitor the robot's position and dynamics in real time through the human-machine interface. The operator can fix the cable at the fixed point through control commands and calculate the bending rate at the bending point to prevent the cable from being damaged. During the cabling process, the system will classify and store the raw data, calculation results, and verification analysis data according to time sequence and equipment identification, and establish a data management system to ensure data security, integrity and traceability. At the same time, the system monitors the working condition in real time. If abnormal pressure on the robotic arm, excessive route deviation, or excessively small bending radius of the cable are detected, the system will automatically diagnose and analyze the situation and issue an audible and visual alarm, and simultaneously transmit the alarm information to the maintenance personnel. In long-term use, it is necessary to conduct in-depth analysis of the accumulated cabling data, uncover potential patterns, and propose targeted measures to generate monitoring reports that include operational status assessments, fault warnings, and cabling recommendations. At the same time, sensors and instruments should be calibrated and maintained regularly to ensure the accuracy and reliability of the detection data. Furthermore, the system hardware and software should be upgraded and optimized to adapt to different cabling needs and technological advancements.

[0033] In this invention, the "RGB-D depth camera" refers to a camera that simultaneously possesses color image acquisition and depth information measurement functions. It captures the three-dimensional coordinate information of an object's surface through an infrared projector and image sensor, and can simultaneously acquire color images of the environment and distance data between objects, providing accurate spatial dimension information for constructing a three-dimensional digital model of the cabling environment. The "six-axis collaborative robotic arm" refers to a robotic arm structure with six freely rotating joints, each joint corresponding to one degree of freedom of motion, enabling flexible movement in multiple directions and angles. It can adjust the posture and position of the end effector according to cabling requirements, adapting to different scenarios for cable laying and fixing operations. The "edge computing unit" refers to a computing processing unit deployed locally on the robot, capable of completing data analysis and processing without transmitting data to a remote server. The system can quickly respond to environmental perception data and generate control commands, reducing data transmission latency and ensuring the real-time operation of mechanical execution modules. The "mode switching unit" refers to the control component integrated into the energy and drive module. It can automatically or manually switch the CPU's operating mode according to the robot's current workload. It switches to a low-power mode to save energy under light load and switches to a high-performance mode to ensure efficient operation of each module under high load, balancing the robot's endurance and work efficiency. The "material recognition model" refers to a data analysis model built based on image recognition algorithms. By learning and matching the image features of cables and cable trays collected by the environmental perception module, it can distinguish cables of different materials and different types of cable trays, accurately identify cable paths and cable tray positions, and avoid misoperation of existing cables during the wiring process.

[0034] During operation, the operator inputs wiring task parameters and issues wiring instructions through the visual human-machine interaction module. After receiving the instructions, the communication and control module controls the power and drive module to start, driving the robot to move to the wiring starting position. Simultaneously, the environmental perception module collects spatial data and image information of the wiring environment through LiDAR and RGB-D depth camera, constructs a 3D digital model, identifies existing cable paths and obstacle distribution, and transmits the data to the communication and control module. The communication and control module processes the environmental data through the edge computing unit, plans the wiring route, and generates control instructions that are transmitted to the mechanical execution module. The mobile chassis of the mechanical execution module drives the robot to move along the planned route. The six-axis collaborative robotic arm guides the network cable through the end-effector guide wheel set and lays the cable according to the route. During the laying process, the network cable is fixed to the cable tray by a vacuum suction clamp. After fixing, the network test probe is switched to detect the continuity of the line. Force sensors monitor the contact force of the robotic arm in real time, and the alarm unit monitors abnormal conditions and alarms in time if an abnormality occurs. The storage operation unit records the wiring process data synchronously. After the wiring is completed, the communication and control module feeds back the work results to the visual human-machine interaction module, and the operator can view the wiring report. Overall, this embodiment automates, visualizes, and coordinates network cable routing, significantly improving cabling efficiency and accuracy, reducing labor costs and operational risks, and has good practical value.

[0035] The above technical features constitute the embodiments of the present invention, which have strong adaptability and implementation effect. Unnecessary technical features can be added or removed according to actual needs to meet the needs of different situations.

Claims

1. A visual network cable laying robot, comprising a robot body, characterized in that, It also includes an environmental perception module, a mechanical execution module, a visual human-computer interaction module, an energy and drive module, and a communication and control module. The environmental perception module, mechanical execution module, energy and drive module, and communication and control module are integrated inside the robot body, while the visual human-computer interaction module is an independent handheld device that is connected to the robot body via wireless communication. Among them, the environmental perception module is used to collect spatial data and image information of the cabling environment through sensors, construct a three-dimensional digital model, and identify the direction and location of existing cables as well as the type and distribution of obstacles. Among them, the mechanical execution module is used to complete the laying, positioning and fixing of network cables and the detection of line continuity through mechanical structure; Among them, the visual human-computer interaction module is used to receive wiring task parameters input by the operator, display the on-site scene and robot running status obtained by the environmental perception module in real time, and receive and parse control commands in the form of voice, gesture or physical button. The energy and drive module provides power to all modules and drives the robot to move. The communication and control module receives and analyzes the sensing data from the environmental perception module to generate motion control commands, transmits the control commands to the mechanical execution module and the energy and drive module, receives task commands from the visual human-machine interaction module and provides feedback on the execution status, and realizes information interaction and task allocation in the process of multi-robot collaborative operation.

2. The visual network cable laying robot according to claim 1, characterized in that, The environmental perception module's sensors include a LiDAR and an RGB-D depth camera. The LiDAR is used to scan the 3D spatial data of the cabling environment in 360°, while the RGB-D depth camera is used to acquire color images of the cabling environment and object depth information to assist in building a 3D model.

3. The visual network cable laying robot according to claim 1, characterized in that, The mechanical execution module includes a six-axis collaborative robotic arm and a mobile chassis. The end of the six-axis collaborative robotic arm is equipped with a cable guide wheel assembly, a vacuum suction fixture, and a network test probe. These three components are distributed circumferentially along the rotation axis of the end of the robotic arm and can switch work positions through an electric rotary joint. The mobile chassis adopts omnidirectional wheel drive to move the robot body in the wiring environment and accurately adjust the working position.

4. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The environmental perception module has a built-in material recognition model, which is used to identify cable paths and cable tray locations based on image features.

5. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The lidar has an angular resolution of 0.1°, a maximum ranging distance of 50 meters, and a scanning frequency of 10Hz.

6. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The communication and control module includes an edge computing unit, which is used to realize the localized processing of environmental perception data and the real-time control of mechanical execution modules.

7. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The six-axis collaborative robotic arm is equipped with a force sensor at its end to detect the contact force during operation, with a measurement range of 0-50N.

8. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The energy and drive module includes a mode switching unit for switching between CPU low-power mode, high-performance mode, and deep sleep mode according to the robot's workload.

9. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The communication and control module also includes a storage operation unit, which is used to store historical operation data and perform traceability queries on the stored historical operation data.

10. The visual network cable laying robot according to claim 1, 2, or 3, characterized in that, The communication and control module also includes an alarm unit, which is used to issue audible and visual alarm signals and transmit them synchronously to the visualization interaction module when abnormal pressure of the robotic arm, excessive route deviation, or excessive bending radius of the network cable is detected.

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