Intelligent construction robot for truss girder

Abstract

The invention provides an intelligent construction robot for a truss girder. The intelligent construction robot comprises a control system, a tool table, an optical sensor and a camera. The tool table comprises a conveying module, a bridge frame, a grabbing robot and a welding robot. The control system is electrically connected with the tool table and used for controlling operation of the construction robot. The conveying module is used for conveying the profiles to the lower end of the bridge; the grabbing robot and the welding robot are in sliding connection with the bridge frame; the optical sensor is mounted on the bridge frame and is used for measuring the running speed of the profile and determining the position of the profile; the camera is installed on the bridge frame and used for obtaining profile information and information of all parts of the tool table. The height of the bridge frame is adjusted based on the height-adjustable system. According to the robot, the whole process from profile conveying to welding is automatic, manual intervention is reduced, the labor intensity is lowered, and the construction efficiency and the quality stability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent robots, and particularly provides an intelligent construction robot for truss beams. Background Art

[0002] With the rapid development of the national construction industry, the status of hoisting machinery in construction is becoming increasingly crucial. Among them, the truss crane stands out with its unique advantages such as a light structure, large span, and strong load-bearing capacity. At the same time, the demand for truss beams in the construction field is increasing day by day. The traditional assembly mode relying on manual manufacturing and on-site welding can no longer meet the production rhythm of large-scale and high-efficiency. In the traditional forming process of truss beam standard sections, it mainly relies on manual or semi-automatic equipment to complete. A large number of truss forming tasks, such as handling, assembling, and welding, rely heavily on manual operations. This makes the product quality significantly affected by human factors, and it is difficult to achieve efficient coordination and close combination between production processes. Notably, in high-risk operation links such as truss welding, if the protective measures are not implemented properly during manual operation, serious safety accidents such as electric shock, fire, and even explosion are likely to occur. Generally speaking, the traditional operation method has obvious disadvantages, not only with low production efficiency, unreliable product quality, but also high labor costs, poor production flexibility and adaptability, and there are relatively large safety hazards in the working environment.

[0003] Intelligent robots can operate continuously for 24 hours, and their operation speed and accuracy are much higher than those of humans. In the link of forming truss standard sections, intelligent robots operate according to preset programs and parameters, and can quickly and accurately complete production tasks. Moreover, the production of intelligent robots greatly reduces safety risks, significantly improves the working environment, strongly promotes the standardization and large-scale production of truss beams, comprehensively improves the overall production efficiency and competitiveness of the construction industry, and helps the construction industry to accelerate its upgrade to the high-end manufacturing field. Therefore, introducing intelligent robots for the forming of truss standard sections is the development trend of the future construction industry and an important manifestation of the modernization of the construction industry.

[0004] Therefore, there is a need in this field for an intelligent construction robot for truss beams to solve the above problems. Summary of the Invention

[0005] In order to overcome the above defects, the present invention is proposed to provide a solution to solve or at least partially solve the problem that the automatic forming of truss standard sections cannot be achieved.

[0006] The present invention provides an intelligent construction robot for truss beams, comprising: a control system, a tooling table, an optical sensor, and a camera; the tooling table includes a conveying module, a bridge, a grasping robot, and a welding robot; the control system is electrically connected to the tooling table for controlling the operation of the construction robot; the conveying module is used to transport profiles to the lower end of the bridge; the grasping robot and the welding robot are slidably connected to the bridge; the optical sensor is installed on the bridge for measuring the running speed of the profiles and determining the position of the profiles; the camera is installed on the bridge for obtaining profile information and information of each component of the tooling table; the height of the bridge is adjusted based on a height adjustable system.

[0007] Advantages of the present invention: The whole process of this robot from profile transportation to welding is automated, reducing manual intervention, lowering labor intensity, and enhancing construction efficiency and quality stability. Specifically, seamless connection of multiple links such as material handling, processing, and assembly can be achieved, optimizing the entire production process; the robot has high precision, can ensure accurate dimensions of each component of the truss and precise assembly positions, and the product quality is stable and consistent; it operates strictly according to preset programs and parameters and is less affected by external factors; the reliance on a large number of human resources can be significantly reduced, and only a few workers are required to monitor and maintain an automated production line; the skill requirements for workers are relatively low, reducing the human resource training cost; the robot operation can liberate workers from dangerous environments, such as high-altitude operations, high-temperature welding, heavy object handling, etc., reducing the risk of worker injuries; this robot has a compact structure, and when combined with an automated profile storage and conveying system, a more optimized production space layout can be realized. Additionally, the adjustable height of the bridge and the sliding connection method of the robot enable it to handle profiles of different sizes and types and complex construction environments, with a wider scope of application. Moreover, through real-time monitoring by sensors and cameras, problems can be detected and processed in a timely manner to avoid accidents, and the safety warning and protection mechanisms are more perfect compared with traditional construction equipment, better ensuring the safety of personnel and equipment.

[0008] Furthermore, the optimal solution of the truss obtained by this robot through various optimization design models not only meets the basic requirements such as the safety, stability, and reliability of the structure, but also achieves the best balance in aspects such as material cost, manufacturing process difficulty, and lightweight design, providing a highly valuable reference basis and design guidance for the actual production and application of the truss. Description of the Drawings

[0009] Referring to the accompanying drawings, the disclosure of the present invention will become more easily understandable. It is easily understood by those skilled in the art that these drawings are only for illustrative purposes and are not intended to limit the protection scope of the present invention. In addition, similar numbers in the figures are used to represent similar components, where:

[0010] Figure 1 is a schematic structural diagram of an intelligent construction robot for truss beams according to an embodiment of the present invention;

[0011] Figure 2 is the left view of the intelligent construction robot for truss beams according to an embodiment of the present invention;

[0012] Figure 3 is the top view of the intelligent construction robot for truss beams according to an embodiment of the present invention;

[0013] Figure 4 is the front view of the intelligent construction robot for truss beams according to an embodiment of the present invention;

[0014] Figure 5 is the schematic diagram of the camera of the intelligent construction robot for truss beams according to an embodiment of the present invention;

[0015] Figure 6 is the schematic diagram of the infrared sensor of the intelligent construction robot for truss beams according to an embodiment of the present invention;

[0016] Figure 7 is the schematic diagram of the ultrasonic sensor of an intelligent construction robot for truss beams proposed in the present invention;

[0017] Figure 8 is the schematic diagram of the optical sensor of an intelligent construction robot for truss beams proposed in the present invention;

[0018] Figure 9 is the schematic diagram of the absolute encoder of an intelligent construction robot for truss beams proposed in the present invention;

[0019] Figure 10 is the schematic diagram of the gravity sensor of an intelligent construction robot for truss beams proposed in the present invention;

[0020] Figure 11 is the schematic diagram of the limiter of an intelligent construction robot for truss beams proposed in the present invention;

[0021] Figure 12 is the schematic diagram of the welding robot of an intelligent construction robot for truss beams proposed in the present invention;

[0022] Figure 13 is the schematic diagram of the grasping robot of an intelligent construction robot for truss beams proposed in the present invention;

[0023] Figure 14 is the operation flow chart of the robotic arm of an intelligent construction robot for truss beams proposed in the present invention;

[0024] Figure 15 is the welding flow chart of an intelligent construction robot for truss beams proposed in the present invention;

[0025] Figure 16The optimization flowchart of an intelligent construction robot for a truss beam proposed in this invention patent.

[0026] In the figure: 1. Control system; 2. Computer; 3. Display screen; 4. Tooling table; 5. Robot arm; 6. Mechanical clamp; 7. Welding torch; 8. Conveyor line; 9. Bridge; 10. First cross beam; 11. First track; 12. Slide rail; 13. Second cross beam; 14. Column; 15. Second track; 16. Camera; 17. Infrared sensor; 18. Ultrasonic sensor; 19. Optical sensor; 20. Encoder; 21. Gravity sensor; 22. Limiter; 23. Conveyor module; 24. Gripping robot; 25. Welding robot. Detailed implementation manners

[0027] The following describes some implementation manners of the present invention with reference to the accompanying drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principle of the present invention and are not intended to limit the protection scope of the present invention.

[0028] It should be noted that in the description of the present invention, the terms indicating directions or positional relationships such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation to the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0029] In addition, it should also be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installation", "setting", "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected, or indirectly connected through an intermediate medium, and can also be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0030] In the description of the present invention, "module" and "processor" can include hardware, software, or a combination of both. A module can include a hardware circuit, various suitable sensors, communication ports, a memory, and can also include a software part, such as program code, and can also be a combination of software and hardware. The processor can be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and / or signal processing functions. The processor can be implemented in software, in hardware, or in a combination of both ways.

[0031] Embodiment

[0032] As shown Figures 1-16 In the figure, the present invention provides an intelligent construction robot for a truss beam, including: a control system 1, a tooling table 4, an optical sensor 19, and a camera 16; the tooling table 4 includes a conveying module 23, a bridge 9, a grasping robot 24, and a welding robot 25; the control system 1 is electrically connected to the tooling table 4 for controlling the operation of the construction robot; the conveying module 23 is used to transport profiles to the lower end of the bridge 9; the grasping robot 24 and the welding robot 25 are slidably connected to the bridge 9; the optical sensor 19 is installed on the bridge 9 for measuring the running speed of the profiles and determining the position of the profiles; the camera 16 is installed on the bridge 9 for obtaining profile information and information of each component of the tooling table 4; the bridge 9 is adjusted in height based on a height adjustable system.

[0033] Workflow: The conveying module 23 starts to work and transports profiles to the lower end of the bridge 9. During the transportation of the profiles, the optical sensor 19 installed on the bridge 9 measures the running speed of the profiles in real time and determines the position of the profiles, and feeds these data back to the control system 1. The control system 1 issues an instruction to the grasping robot 24 according to the profile position and speed information fed back by the optical sensor 19. Based on the sliding connection with the bridge 9, the grasping robot 24 moves to the position where the profiles are located, accurately grasps the profiles, and transports them to the designated processing position. During the transportation of the profiles by the grasping robot 24, the camera 16 installed on the bridge 9 obtains profile information (such as shape, size, etc.) and the running information of each component of the tooling table 4 (including the conveying module 23, the grasping robot 24, etc.), and transmits this information to the control system 1 for the operator to monitor and the control system to make adjustments according to the actual situation. When the grasping robot 24 places the profiles at the designated position, the control system 1 issues an instruction to the welding robot 25. Based on the sliding connection with the bridge 9, the welding robot 25 moves to the profiles and performs welding operations on the profiles according to the preset welding process and parameters to complete the assembly work of the truss beam. During the entire construction process, if it is necessary to adapt to different construction height requirements, the bridge 9 is adjusted in height based on its height adjustable system to meet the actual construction needs. At the same time, the optical sensor 19 and the camera 16 continuously monitor the states of the profiles and each component of the tooling table to ensure the smooth progress of the construction. After completing the operations of transporting, grasping, welding, etc. of one profile, repeat the above steps to continue processing the subsequent profiles until the entire construction task of the truss beam is completed.

[0034] Specifically, as Figure 1As shown, the control system 1 includes a computer 2, a camera display 3 and a power supply. The computer 2 and the display 3 are located on the desktop of the control system 1. The computer 2 is provided with multiple interfaces, including USB interfaces, HDMI interfaces, PWM interfaces, PCIe slots, RJ-45 network ports, etc. The USB interfaces are used to connect external devices, the HDMI interfaces are used to connect high-definition video devices, the PWM interfaces are used to control the driving operations of the robotic arm 5 and the conveying module 23, the PCIe slots are used to insert expansion cards, and the RJ-45 network ports are used to connect to the network. The camera uses an optical camera, and multiple soft light LED light sources are configured around it to eliminate the light and shadow effects of the profiles, provide stable lighting conditions, and obtain clearer profile images. The optical sensor 19 uses a photoelectric speed measurement sensor.

[0035] In one embodiment, the bridge 9 includes a support member and a track assembly. The track assembly is arranged on the support member, and the welding robot 25 and the grasping robot 24 move along the track assembly. A height adjustable system is arranged on the support member. The height adjustable system includes a height locking unit and a power driving system. The power driving system provides lifting power for the support member. After the support member completes height adjustment, it feeds back a in-place signal to the control system 1, triggering the height locking unit to start the locking process.

[0036] In this embodiment, when encountering construction requirements of different heights, the power driving system will, according to the instructions of the control system 1, drive the support member to make corresponding height adjustments to ensure that the welding robot 25 and the grasping robot 24 can work at appropriate heights. After the support member completes height adjustment under the action of the power driving system, it will feed back an in-place signal to the control system 1. After receiving this in-place signal, the control system 1 will trigger the height locking unit to start the locking process. After the height locking unit is started, it will lock the current height of the support member to prevent the height of the support member from changing due to various external force factors (such as vibrations during robot operation, etc.) during subsequent construction, thereby ensuring the stability and safety of the entire bridge 9 and devices such as the welding robot 25 and the grasping robot 24 installed thereon, and ensuring that the construction can proceed smoothly and accurately.

[0037] In an alternative embodiment, as Figure 1As shown in the figure, the support member is composed of 3 second crossbeams 13 and 6 columns 14 and is erected on the ground to form the main frame structure of the bridge frame 9; the first crossbeam 10 is located between the second crossbeams 13, and the first track 11 and the second track 15 are laid between the 6 columns 14; a slide rail 12 is installed on the first crossbeam 10, and the welding robot 25 is installed on the slide rail 12 to achieve multi-functional and all-round welding, and each robot is controlled by the control system 1. The gripping robots 24 are located on both sides of the conveying module 23, and at the same time, the gripping robots 24 are slidably connected to the second track 15, so that the gripping robots 24 can move along the direction of the conveying profile. A height adjustment system is provided on the column 14. The height locking unit can be a limit groove, and the power drive system can be a hydraulic system. The limit groove is arranged inside the column 14, and the height adjustment is realized through the hydraulic system, and the height of the support rod is fixed through the limit groove to adapt to different working environments.

[0038] Alternatively, in an alternative embodiment, the height locking unit can be an electromagnetic locking mechanism: an electromagnetic coil and a magnetic adsorption component are installed on the column. When locking is required, the electromagnetic coil is energized to generate a magnetic field, so that the magnetic adsorption component tightly adsorbs at the corresponding position, thereby fixing the height of the column. The height locking unit can also be a ratchet and pawl mechanism: a ratchet with ratchet teeth and a retractable pawl are arranged on the column. When the column rises or falls to the appropriate height, the pawl is inserted into the tooth groove of the ratchet under the action of a spring or other driving force to prevent the column from moving and achieve height locking. The height locking unit can also be a wedge locking device: a wedge is arranged on the column, and the wedge is wedged tightly by a mechanical or hydraulic device, and the friction force between the wedge and the column is used to lock the height. The height locking unit is not limited to the above structures, as long as the height locking can be completed.

[0039] The power drive system can be an electric lead screw drive system, a pneumatic drive system, etc. The power drive system is not limited to the above structures, as long as it can provide lifting power for the support member.

[0040] In an alternative embodiment, the optical sensor 19 is installed on the column in the middle of the bridge frame 9 for measuring the running speed of the profile and determining the position of the profile. The camera 16 is installed on the first crossbeam 10 for collecting profile information and real-time monitoring of the forming process of the truss standard section. When a problem occurs during the operation of the robot, it can be promptly fed back to the computer control terminal, and then a warning sound is emitted for alarm. Once the alarm information appears, the tooling table will immediately brake to avoid major accidents.

[0041] In this embodiment, the optical sensor 19 has two main functions. First, it measures the running speed of the profile. By monitoring the movement process of the profile, the running speed of the profile is calculated. For example, the control system can accurately control when the gripping robot 24 grabs the profile according to the speed of the profile to ensure the accuracy and timeliness of gripping. Second, it determines the position of the profile. Knowing exactly the specific position of the profile during operation helps the robot to accurately operate on the profile, such as gripping and placing. The camera 16 can take images of the profile and collect relevant information about the profile, such as the shape, size, and surface condition of the profile, through the analysis of these images. In addition, during the forming process of the truss standard section, the camera 16 takes real-time pictures of the whole process so that the operator can understand the progress and quality of the forming in real time. When the robot has problems during operation, the camera 16 can capture these abnormal situations and promptly feedback the information to the computer control terminal. After receiving the abnormal information, the computer control terminal will emit a warning sound for alarm. At the same time, once the alarm information appears, the tooling table will immediately brake.

[0042] In one embodiment, the height adjustable system further includes a status feedback and confirmation module, and the status feedback and confirmation module is configured to determine whether the height adjustable system is in a stable state after receiving a locking success signal.

[0043] In this embodiment, preset condition 1: The displacement change of the support component is monitored in real time through the built-in sensor group to confirm that it is in a static state; preset condition 2: Data verification is performed on the locking pressure or biting state of the height locking unit to ensure that the locking structure is in an effective working state; preset condition 3: The current system state is compared and analyzed with a preset stable threshold.

[0044] One or more of the above preset conditions can be set. If the preset conditions are met, the status feedback and confirmation module will send a "system stable" instruction to the control system 1, indicating that the height adjustment process is completed and allowing the subsequent equipment to operate normally; if the preset conditions are not met, the status feedback and confirmation module will send an "abnormal alarm" to the control system 1, and at the same time, the power drive system and the height locking unit will be linked to enter the safety protection mode to prevent safety accidents caused by system instability.

[0045] In one embodiment, the grasping robot 24 includes a robotic arm 5, a mechanical gripper 6, an ultrasonic sensor 18, and an encoder 20. Among them, the mechanical gripper 6 is installed at the end of the robotic arm 5, and its main function is to grasp profiles. The robotic arm 5 can move flexibly, bringing the mechanical gripper 6 to the position where the profile is located to achieve the grasping and handling of the profile. The encoder 20 is installed on the base of the robotic arm 5, and obtains the real-time position of the grasping robot 24 through real-time high-speed pulse feedback, which enables the control system to accurately know the position of the robotic arm 5, thereby accurately controlling the actions of the grasping robot 24 and ensuring the accuracy and stability of the grasping operation. The ultrasonic sensor 18 is installed on the mechanical gripper 6 and is used to measure the distance between the profile and the mechanical gripper 6. Through this distance measurement, the mechanical gripper 6 can accurately adjust its position when approaching the profile to ensure that the profile can be smoothly grasped and avoid collisions or grasping failures.

[0046] The welding robot 25 includes a robotic arm 5, a welding torch 7, and an infrared sensor 17. Among them, the infrared sensor 17 is installed at the part where the welding torch 7 is connected to the welding wire and is used to measure the welding temperature and the thermal imaging during the welding process. By measuring the welding temperature, the operator can monitor whether the welding process is carried out within a suitable temperature range to ensure the welding quality. The thermal imaging function can help observe the heat distribution in the welding area and timely detect possible welding defects or abnormal conditions.

[0047] The conveying module 23 includes a conveyor line 8, a gravity sensor 21, and a stopper 22. Among them, the stopper 22 is used to identify the profile when it reaches this position and control the conveyor line 8 to stop to prevent collisions between the robot and the column. The gravity sensor 21 is used to continuously monitor the weight on the conveyor line 8 after all the profiles have been transported. If it detects that the weight on the conveyor line 8 is lower than a pre-set threshold, it triggers a signal to restart the conveyor line 8 to continue with the subsequent profile conveying task.

[0048] In this embodiment, the three-dimensional spatial relative positions of the grasping robot 24 and the welding robot 25 are obtained by the camera 16 and transmitted to the computer 2. The infrared sensor 17 uses an infrared temperature sensor and an infrared thermal imaging sensor; the ultrasonic sensor 18 uses an ultrasonic ranging sensor; the encoder 20 uses an absolute encoder; the stopper 22 uses an electronic stopper. The robotic arm host, the mechanical gripper host, and the welding head host all communicate with the master control system terminal using the TCR protocol. The communication content includes control instructions, the real-time path coordinates of the robotic arm 5, and the postures of the mechanical gripper 6 and the welding head.

[0049] Furthermore, electric rollers are assembled at the bottom of the base of the grasping robot 24. With the coordinated cooperation of the electric rollers and the track, the grasping robot 24 can move flexibly back and forth between the columns, greatly expanding its working space. Electric rollers are installed at both ends of the bottom of the crossbeam of the welding robot 25. By installing the electric rollers of the crossbeam of the welding robot 25 on the track, the welding robot 25 can move back and forth between the crossbeams to achieve all-round welding. The optical sensor 19 is installed on the column in the middle of the bridge 9 and is used to measure the running speed of the profile and determine the position of the profile. The conveying module 23 is installed in the middle of the bridge 9 and is responsible for transporting the profile.

[0050] In an optional embodiment, the conveying module 23 is a roller conveyor. Specifically, the required profile is placed on the roller conveyor, and the motor provides power. The power is transmitted to the rollers through a reduction device to make the rollers rotate to convey the profile. The profile passes through the front end of the bridge 9 and is positioned and speed-measured by the optical sensor 19 and identified by the camera 16. The positioner 22 monitors the position information of the conveyor in real time and transmits the data to the microprocessor. The microprocessor analyzes and judges the data transmitted by the sensor according to the preset limit position parameters. When the conveyor runs to the preset position at the lower end of the bridge 9, it stops.

[0051] In one embodiment, the control system 1 includes: a truss structure optimization module, which is used to determine the basic parameters of the truss design and the set values of the section parameters according to the user requirements, establish a mathematical model with the cross-section of the truss member as the design variable, optimize the initial parameters, obtain the optimal feasible solution of the parameters, and then output the optimal parameters of the truss member and give the standard section structure and profile model of the truss; a profile identification module, which is used for the acquisition, processing and feature matching numbering of profile data; the control system 1 generates a sorting instruction, and the grasping robot 24 grabs and transports the profile based on the sorting instruction until all the profiles on the conveying module 23 are transported; an intelligent welding module, which is used for welding, collecting image data during the welding process and processing the image data; an obstacle avoidance and safety module, which is used for profile detection and identification, combined with camera ranging and real-time high-speed pulse feedback of the absolute encoder to obtain the real-time position of the robot for obstacle avoidance and system emergency stop and restart.

[0052] In this embodiment, a single-chip microcomputer circuit board and a main control board are internally connected to the computer 2. The single-chip microcomputer circuit board integrates a single-chip microcomputer. First, the computer 2 can determine the basic parameters of the truss design according to the user's needs, determine the set value of the truss section parameters, and establish a mathematical model with the truss member section as the design variable. The initial parameters are input into the optimization software, and the software iterates and compares through various algorithm models to obtain the optimal feasible solution and output the optimal parameters of the truss members, and gives the standard section structure of the truss and the profile model. Secondly, the camera and various sensors collect data on the profiles. The computer 2 preprocesses the data, and the ViT vision system extracts features to fuse the features of multi-source data. Through the pre-established numbering rules and arrangement strategies, feature matching and number matching of the profiles are carried out. The computer 2 generates a sorting instruction and sends a 5G signal to the stm32 development board of the grasping robot, and the grasping robot 24 accurately grasps and transports the profiles. After all the profiles on the conveying module 23 are transported, they are grasped and fixed according to the previous numbering of the profiles. Using the intelligent optimization algorithm, according to the shape, size and welding process requirements of the profiles, the welding path is optimized. The computer master control terminal sends a 5G signal again to transmit the optimized welding path and related instructions to the welding robot 25. After receiving the signal, the welding robot 25 quickly starts the welding equipment and welds the profiles according to the preset path and parameters. During the welding process, the robot can monitor the welding quality and progress in real time, adjust and optimize according to the actual situation to ensure that each welding point is firm and reliable, and finally complete the welding task of the profiles. At the same time, the infrared sensor 17 monitors the welding temperature in real time and transmits it to the computer 2. The camera 16 monitors the entire working process, reports the health status of the tooling table 4 in real time, and sends the results to the computer 2 for the administrator to monitor in real time.

[0053] In an optional embodiment, the truss structure optimization module includes parameter definition, and the objective function F(x) = minM(x), where M(x) is the total mass of the truss. The constraint conditions meet the requirements of 3S (stiffness, strength, stability) and welding process requirements. For example: the maximum stress of the material does not exceed the yield strength maxσ ≤ [σ], the yield safety factor λ ≥ 2.5, the optimization process is displayed in real time, the effects of various intelligent optimization algorithms are compared, and the result evaluation and output function.

[0054] In an optional embodiment, the intelligent truss forming robot has powerful data processing and analysis capabilities and can deeply analyze various truss information collected manually according to a pre-set program. This information covers detailed data in many aspects such as the material properties, size specifications, load types and magnitudes borne by the truss, and application environment conditions. The intelligent truss forming robot can call a variety of rigorously verified and optimized optimization models.

[0055] These models include finite element analysis optimization models, topology optimization models, structural dynamics optimization models, etc., which carry out optimization design work on the truss structure from different dimensions and perspectives. In the finite element analysis optimization model, computer 2 can accurately simulate the mechanical behavior of the truss under various working conditions, such as stress distribution, deformation conditions, strain magnitudes, etc., and based on this, make targeted improvements to the structure; the topology optimization model can help explore the optimal material distribution method of the truss structure, realizing the rational utilization of materials and effective control of costs while ensuring the structural performance; the structural dynamics optimization model enables computer 2 to fully consider the response characteristics of the truss in a dynamic environment, ensuring that it can still operate stably under the influence of wind loads and other adverse loads. Through calculation and analysis, among numerous possible design schemes, computer 2 performs step-by-step iteration to finally obtain the optimal solution for the truss structure.

[0056] In one embodiment, the profile recognition module includes: an image acquisition subsystem for acquiring a three-dimensional spatial image of the profile; a calculation module for generating three-dimensional image coordinates of the profile based on the three-dimensional spatial image of the profile; a feature extraction and fusion module for performing feature extraction based on the ViT vision model, fusing the extracted multi-source data features, and then performing feature matching and number matching on the profile according to the pre-established numbering rules and arrangement strategies.

[0057] In this embodiment, the numbering rules can be established in advance according to the properties of the profile such as type, size, and use: large category - type - size - material - shape - additional attribute, where the large category identifier: T (truss-specific identifier), type: MJ (main chord), XG (diagonal web member), SG (vertical web member), LJ (connector), etc., the size is in the format of "length × width × height" or "diameter × wall thickness", the material: Q235, Q355, etc., the shape: H (H-beam), L (angle steel), P (round pipe), B (square pipe), etc., the additional attribute: Z (hot-dip galvanized), D (electro-galvanized), P (painted), W (untreated), etc. For example, T-XG-120×80×5-Q235-H-P represents the diagonal web member of the truss standard section, H-beam, size 120×80×5mm, material Q235, painted, and the total control terminal performs fixed feature matching and number assignment on different profiles according to the numbering rules; then, a sorting algorithm is used to arrange the numbered profiles.

[0058] The robot grabs profiles with different numbers to the welding position, and the camera 16, infrared sensor 17, and ultrasonic sensor 18 extract information. After normalizing different information, it is input into the ViT model. The model extracts key feature points to generate a comprehensive feature map through global correlation analysis of each feature. The specific profiles are grabbed and fixed according to the previous numbering and sorting of the profiles. Further, the welding path planning and the selection of welding methods are to optimize the welding path using the genetic algorithm and the ViT vision model according to the shape, size of the profiles, and the requirements of the welding process.

[0059] To optimize the welding path using the genetic algorithm, the goal needs to be clarified first: find the priority access order of the welding points. Specifically:

[0060] Set of welding points: Q = {q1, q2, …, q n}, a total of N points to be welded.

[0061] Representation of the welding path: The priority access order of the welding points A = {a1, a2, …, a N}, where A i ∈ {1, 2, …, N} and there are no repetitions.

[0062] Establish an objective function for the target problem:

[0063] F(x) = min T(x) + min L(x), P(x) = 0,

[0064] where T(x) represents the welding time, L(x) represents the welding path, and P(x) represents the number of obstacles;

[0065] Represent the welding path as a chromosome, and use integer encoding for the encoding method. Each gene represents the number of a welding point. The camera collects obstacle information and uses polygons or circles to describe the size and position of the obstacles, and models the obstacles and profiles. For the position information of a circular obstacle, it is expressed as (x0, y0, r), where (x0, y0) represents the center coordinates and r represents the radius; the position information of a rectangular obstacle is expressed as (x min , y min , x max , y maxare the coordinates of the lower left and upper right corners of the rectangle, respectively, clearly expressing the positional relationship between the profile and the obstacle. Then, initialize the chromosome population and randomly generate a number of chromosomes (initial welding paths). Then, check whether the welding path collides with the obstacle. For each segment of the path (the line connecting adjacent welding points), determine whether it intersects with the obstacle. If it intersects, a corresponding penalty value P is given according to the severity of the intersection. For example, the more intersections and the longer the intersection part, the greater the penalty value. Among them, to judge whether a circular obstacle (x0, y0, r) intersects with a line segment, given the two endpoints (x1, y1) and (x2, y2) of the line segment, calculate the distance d from the center of the circle to the line segment. If (d ≤ r), the line segment intersects with the circle. The formula for calculating d is:

[0066] The number of the welding point, and the order of the chromosome represents the visiting order of the welding points.

[0067] For a rectangular obstacle (x min , y min , x max , y max ) It can be determined whether it intersects by judging whether the two endpoints of the line segment are on different sides of the rectangle or whether the line segment intersects with a certain side of the rectangle.

[0068] Design a fitness function, which can transform the objective function into a fitness value: Fitness = 1 / (L + T + αP), where L represents the length of the welding path, T represents the time of the welding path, P represents the penalty value, and α is a weight coefficient

[0069] The fitness function is used to evaluate the quality of each chromosome. Then, according to the obtained fitness values, use roulette wheel selection Select a certain number of chromosomes from the current population as the parents of the next generation population. Use partially mapped crossover (PMX): Randomly select two crossover points k1, k2, and then exchange the subsequences a A , a B subsequence a A k1：k2 and a B k1：k2 , and finally solve the conflict through the mapping relationship. Generate new offspring chromosomes. Use the random mutation method, randomly select two positions i, j, and exchange a i and a j , a new = (a1,…, a j ,…, a i ,…, a N ​) Perform mutation operations on the offspring chromosomes to introduce new genes. Finally, repeat the selection, crossover, and mutation operations to generate a new population. The fitness value of each generation of the population will gradually increase until the fitness value no longer increases. After stopping the iteration, output the chromosome with the highest fitness as the optimal welding path to achieve the optimization of the welding path. Using this genetic algorithm, the system can update the welding path in real time, avoid the influence of obstacles on the welding process, and improve the welding efficiency.

[0070] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the original technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An intelligent construction robot for truss beams, characterized in that, Including: Control system, tooling table, optical sensor, camera; The tooling table includes a conveying module, a bridge, a grasping robot, and a welding robot; The control system is electrically connected to the tooling table and is used to control the operation of the construction robot; The conveying module is used to transport profiles to the lower end of the bridge; The grasping robot and the welding robot are slidably connected to the bridge; The optical sensor is installed on the bridge and is used to measure the running speed of the profile and determine the position of the profile; The camera is installed on the bridge and is used to obtain profile information and information of each component of the tooling table; The height of the bridge is adjusted based on a height adjustable system.

2. The intelligent construction robot for truss beams according to claim 1, wherein The bridge includes a support component and a track assembly. The track assembly is arranged on the support component, and the welding robot and the grasping robot move along the track assembly; A height adjustable system is arranged on the support component. The height adjustable system includes a height locking unit and a power driving system. The power driving system provides lifting power for the support component. After the support component completes height adjustment, it feeds back a in-place signal to the control system to trigger the height locking unit to start the locking process.

3. The intelligent construction robot for truss beams according to claim 2, characterized in that, The height adjustable system further includes a status feedback and confirmation module, and the status feedback and confirmation module is used to determine whether the height adjustable system is in a stable state after receiving a locking success signal.

4. The intelligent construction robot for truss beams according to claim 2, wherein, The grasping robot includes a robotic arm, a mechanical gripper, an ultrasonic sensor, and an encoder; wherein, the mechanical gripper is installed at the end of the robotic arm, the encoder is installed on the robotic arm, and the real-time position of the grasping robot is obtained through real-time high-speed pulse feedback; the ultrasonic sensor is installed on the mechanical gripper and is used to measure the distance between the profile and the mechanical gripper.

5. The intelligent construction robot for truss beams according to claim 2, wherein The welding robot includes a robotic arm, a welding torch, and an infrared sensor; wherein, the infrared sensor is installed at the part where the welding torch is connected to the welding wire and is used to measure the welding temperature and the thermal imaging during the welding process.

6. The intelligent construction robot for truss beams according to claim 2, wherein The conveying module includes a conveyor line, a gravity sensor, and a stopper. The stopper is used to identify the profile when the profile reaches this position and control the conveyor line to stop; the gravity sensor is used to continuously monitor the weight on the conveyor line after all the profiles are transported. If it detects that the weight on the conveyor line is lower than a preset threshold, it triggers a signal to restart the operation of the conveyor line and continue to execute the subsequent profile conveying task.

7. The intelligent construction robot for truss beams according to claim 1, wherein The control system includes: A truss structure optimization module, which is used to determine the basic parameters of the truss design and the set values of the cross-section parameters according to user requirements, establish a mathematical model with the cross-section of the truss member as the design variable, optimize the initial parameters, obtain the optimal feasible solution of the parameters, and then output the optimal parameters of the truss member and give the truss standard section structure and profile model; A profile identification module, which is used for the acquisition, processing, and feature matching and numbering of profile data; The control system generates a sorting instruction, and the grasping robot grabs and transports the profiles based on the sorting instruction until all the profiles on the conveying module are transported. An intelligent welding module, which is used for welding, collecting image data during the welding process and processing the image data; An obstacle avoidance and safety module, which is used for profile detection and recognition, combined with camera ranging and real-time high-speed pulse feedback of an absolute encoder to obtain the real-time position of the robot for obstacle avoidance and system emergency stop and restart.

8. The intelligent construction robot for truss beams according to claim 7, wherein, The profile recognition module includes: An image acquisition subsystem, which is used to obtain the three-dimensional space image of the profile; A calculation module, which generates the three-dimensional image coordinates of the profile based on the three-dimensional space image of the profile; A feature extraction and fusion module, which is used to perform feature extraction based on the ViT vision model, fuse the multi-source data features after extraction, and then perform feature matching and number matching on the profile according to the pre-established numbering rules and arrangement strategies.

9. The intelligent construction robot for truss beams according to claim 7, wherein The intelligent welding module includes: A welding path optimization module, which is used to optimize the welding path by using an intelligent optimization algorithm according to the shape, size of the profile and the requirements of the welding process; A welding robot, which is used to receive the optimized welding path and relevant instructions issued by the control system, and weld the profile according to the preset path and parameters.

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