Intelligent welding method, device and equipment, storage medium and program product

Abstract

The invention provides an intelligent welding method, device and equipment, a storage medium and a program product, and relates to the technical field of automatic welding. In some embodiments of the invention, a visual sensor is utilized to scan a to-be-welded workpiece to obtain a welding track; under the condition that the welding robot stops for one time, whether the working space of a mechanical arm of the welding robot can cover the welding track or not is judged, and a judgment result is obtained; according to the judgment result, the welding robot is autonomously controlled to conduct welding operation on the to-be-welded workpiece; based on whether the working space of the mechanical arm of the welding robot can cover the welding track or not, different welding modes are adopted, and compared with an existing welding mode of stopping while walking, the time cost is reduced, the welding efficiency is improved, and the welding quality is improved.

Description

Technical Field

[0001] This disclosure relates to the field of automatic welding technology, and in particular to an intelligent welding method, apparatus, equipment, storage medium, and program product. Background Technology

[0002] Welding automation is an important means to improve welding quality and efficiency and save labor costs. Weld seam tracking is one of the essential technologies for achieving welding automation and has been widely used in the field of high-end equipment manufacturing.

[0003] Existing track-based automated welding systems typically rely on pre-laid rigid guide rails, along which the robot moves and executes a preset welding path. These systems often use offline programming or teach-and-playback methods to set the welding torch trajectory, making them suitable for welding workpieces with regular shapes and high repetitiveness. However, for long welds, frequent movement of the welding robot is required, resulting in frequent starts and stops that waste significant time, and segmented welding leads to lap welds.

[0004] Currently, intelligent welding is time-consuming, inefficient, and produces poor welding quality. Summary of the Invention

[0005] This disclosure provides an intelligent welding method, apparatus, equipment, storage medium, and program product to at least solve the problems of high time cost, low efficiency, and poor welding quality in existing intelligent welding methods.

[0006] The technical solution disclosed herein is as follows: This disclosure provides an intelligent welding method, including: The workpiece to be welded is scanned using a vision sensor to obtain the welding trajectory; In the case of a single stop of the welding robot, determine whether the working space of the robotic arm of the welding robot can cover the welding trajectory, and obtain the judgment result; Based on the judgment result, the welding robot is controlled to perform welding operations on the workpiece to be welded.

[0007] Optionally, the step of scanning the workpiece to be welded using a vision sensor to obtain the welding trajectory includes: The process involves using a visual sensor to scan the workpiece to be welded, thereby obtaining weld point cloud data. The weld point cloud data is input into the welding trajectory generation model to obtain the welding trajectory.

[0008] Optionally, determining whether the workspace of the welding robot's robotic arm can cover the welding trajectory and obtaining a determination result includes: The welding trajectory is discretized into multiple key welding points; For each of the aforementioned key welding points, combined with the welding torch process posture constraints, the feasible region set of the robotic arm base is solved using inverse kinematics. Calculate the global common solution set based on the feasible region set; The judgment result is determined based on the global common solution set.

[0009] Optionally, determining the judgment result based on the global common solution set includes: If the global common solution set is a non-empty set, then the determination result is that the working space of the welding robot's robotic arm can cover the welding trajectory. If the global common solution set is empty, then the judgment result is determined to be that the working space of the welding robot's robotic arm cannot cover the welding trajectory.

[0010] Optionally, controlling the welding robot to perform welding operations on the workpiece to be welded based on the judgment result includes: If the determination result is that the working space of the welding robot's robotic arm can cover the welding trajectory, then the fixed-point welding mode is used to perform welding operations on the workpiece to be welded. If the determination result is that the working space of the welding robot's robotic arm cannot cover the welding trajectory, then a dynamic collaborative welding mode is adopted to perform welding operations on the workpiece to be welded.

[0011] Optionally, the welding operation on the workpiece to be welded using the fixed-point welding mode includes: Calculate the target parking position based on the average operability during the welding process, the travel distance, and the safety threshold between the welding robot and obstacles. The welding robot is controlled to move to the target parking position to perform welding operations on the workpiece to be welded.

[0012] This disclosure also provides an intelligent welding device, including: The scanning module is used to scan the workpiece to be welded using a vision sensor to obtain the welding trajectory; The judgment module is used to determine whether the working space of the robotic arm of the welding robot can cover the welding trajectory when the welding robot stops once, and obtain the judgment result. The control module is used to control the welding robot to perform welding operations on the workpiece to be welded based on the judgment result.

[0013] This disclosure also provides an electronic device, including: processor; Memory used to store processor-executable instructions; The processor is configured to execute instructions to implement the steps in the above method.

[0014] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0015] This disclosure also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the method described above.

[0016] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects: In some embodiments of this disclosure, a visual sensor is used to scan the workpiece to be welded to obtain the welding trajectory; when the welding robot stops once, it is determined whether the working space of the welding robot's robotic arm can cover the welding trajectory, and a judgment result is obtained; based on the judgment result, the welding robot is autonomously controlled to perform welding operations on the workpiece to be welded; this disclosure adopts different welding methods based on whether the working space of the welding robot's robotic arm can cover the welding trajectory, which reduces time costs, improves welding efficiency, and improves welding quality compared to the existing welding method of moving and stopping.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0019] Figure 1 A schematic flowchart of an intelligent welding method provided for an exemplary embodiment of this disclosure; Figure 2 A schematic diagram of the structure of an intelligent welding device provided for an exemplary embodiment of this disclosure; Figure 3 A schematic diagram of the structure of an electronic device provided for an exemplary embodiment of this disclosure. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0021] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure.

[0022] It should be noted that the user information involved in this disclosure includes, but is not limited to, user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0023] To address the aforementioned technical problems, in some embodiments of this disclosure, a visual sensor is used to scan the workpiece to be welded to obtain the welding trajectory; when the welding robot stops once, it is determined whether the working space of the welding robot's robotic arm can cover the welding trajectory, and a judgment result is obtained; based on the judgment result, the welding robot is autonomously controlled to perform welding operations on the workpiece to be welded; this disclosure adopts different welding methods based on whether the working space of the welding robot's robotic arm can cover the welding trajectory, which reduces time costs, improves welding efficiency, and improves welding quality compared to the existing welding method of moving and stopping simultaneously.

[0024] The technical solutions provided by the embodiments of this disclosure are described in detail below with reference to the accompanying drawings.

[0025] Figure 1 This is a schematic flowchart illustrating an exemplary embodiment of the present disclosure of a smart welding method. Figure 1 As shown, the method includes: S101: Use a vision sensor to scan the workpiece to be welded to obtain the welding trajectory; S102: In the case of a single stop of the welding robot, determine whether the working space of the welding robot's robotic arm can cover the welding trajectory, and obtain the judgment result; S103: Based on the judgment result, control the welding robot to perform welding operations on the workpiece to be welded.

[0026] In this embodiment, the entity executing the above method can be a terminal device or a server.

[0027] The terminal device includes, but is not limited to, mobile stations (MS), mobile terminals, mobile phones, handsets, and portable equipment. This terminal device can communicate with one or more core networks via a radio access network (RAN). For example, the terminal device can be a mobile phone (or "cellular" phone), a computer with wireless communication capabilities, a computer with wireless transceiver capabilities, a virtual reality (VR) terminal device, an AR terminal device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical care, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc. The operating systems installed on the terminal device include, but are not limited to, iOS, Android, Windows, Linux, and Mac OS. In different networks, terminals may be called by different names, such as: user equipment, mobile station, user unit, station, cellular phone, personal digital assistant, wireless modem, wireless communication device, handheld device, laptop, cordless phone, wireless local loop station, television, etc. For ease of description, this embodiment will simply refer to it as terminal device.

[0028] In this embodiment, the implementation form of the server is not limited. For example, the server can be a conventional server, a cloud server, a cloud host, a virtual center, or other server devices. The server mainly consists of a processor, hard disk, memory, system bus, and other common computer architecture types.

[0029] In this embodiment, a vision sensor is used to scan the workpiece to be welded to obtain the welding trajectory. When the welding robot stops once, it is determined whether the working space of the welding robot's robotic arm can cover the welding trajectory, and a judgment result is obtained. Based on the judgment result, the welding robot is autonomously controlled to perform welding operations on the workpiece to be welded. This disclosure adopts different welding methods based on whether the working space of the welding robot's robotic arm can cover the welding trajectory. Compared with the existing welding method of moving and stopping, it reduces time costs, improves welding efficiency, and improves welding quality.

[0030] In some embodiments of this disclosure, a vision sensor is used to scan the workpiece to be welded to obtain the welding trajectory. One possible approach is to use a vision sensor to scan the workpiece to be welded to obtain weld point cloud data; the weld point cloud data is then input into a welding trajectory generation model to obtain the welding trajectory. Specifically, after the welding robot enters the workstation, it uses its onboard 3D laser profilometer to perform a coarse scan of a section of the workpiece to be welded; the collected weld point cloud data is then input into the welding trajectory generation model to obtain the welding trajectory. Based on the welding trajectory, the weld length and the normal vectors of each point on the welding trajectory are further calculated.

[0031] It should be noted that this disclosure does not limit the type of visual sensor or the type of welding trajectory generation model, and adjustments can be made according to the actual situation. The visual sensor can be any one of a 3D laser profilometer, a stereo vision sensor, and a structured light vision sensor. The welding trajectory generation model can be an Encoder-Decoder model or a Transformer-Based model.

[0032] This disclosure does not limit the type of workpiece to be welded, and can be adapted according to the structural form, material, and application scenario. For example, plate workpieces, pipe and cylinder workpieces, box frame structures (such as H-beams), curved irregular-shaped workpieces, and assembly components.

[0033] In some embodiments of this disclosure, when the welding robot stops for a single time, it is determined whether the workspace of the welding robot's arm can cover the welding trajectory, and a judgment result is obtained. One possible approach is to discretize the welding trajectory into multiple welding key points; for each welding key point, combined with the welding torch process posture constraints, the feasible region set of the robot arm base is solved using inverse kinematics; based on the feasible region set, a global common solution set is calculated; and based on the global common solution set, the judgment result is determined. This disclosure discretizes the welding trajectory into multiple welding key points, and for each key point, combined with the welding torch process posture constraints (such as tilt angle, extension length, and travel direction), uses inverse kinematics to solve the feasible region set of the robot arm base, and then calculates the global common solution set of the feasible regions of all key points. Based on the global common solution set, it is possible to accurately determine whether the workspace of the welding robot's arm can cover the welding trajectory.

[0034] In the above embodiments, the judgment result is determined based on the global common solution set. One possible approach is that if the global common solution set is not empty, the judgment result is determined to be that the working space of the welding robot's robotic arm can cover the welding trajectory; if the global common solution set is empty, the judgment result is determined to be that the working space of the welding robot's robotic arm cannot cover the welding trajectory.

[0035] For example, discretizing the welding trajectory into a set of key points. For each point, combining the welding torch's process posture constraints, the feasible region set of the robotic arm base is solved using inverse kinematics. .

[0036] Calculate the global common solution set based on the feasible region set. .

[0037] Decision branch: If If (not empty), then the judgment result indicates that the working space of the welding robot's robotic arm can cover the welding trajectory, and it will subsequently enter the fixed-point welding mode, prioritizing welding stability. If (Empty set, indicating that the weld is too long to reach), enter dynamic collaborative welding mode, and prioritize ensuring welding continuity.

[0038] In some embodiments of this disclosure, the welding robot is controlled to perform welding operations on the workpiece based on the judgment result. One possible approach is that if the judgment result indicates that the working space of the welding robot's robotic arm can cover the welding trajectory, then a fixed-point welding mode is used to weld the workpiece; if the judgment result indicates that the working space of the welding robot's robotic arm cannot cover the welding trajectory, then a dynamic collaborative welding mode is used to weld the workpiece. This disclosure employs different welding methods for different workpieces depending on the judgment result regarding whether the working space of the welding robot's robotic arm can cover the welding trajectory, thereby improving the welding robot's autonomous judgment capability and enhancing the intelligence level of the welding process.

[0039] In one exemplary embodiment, a fixed-point welding mode is used to perform welding operations on the workpiece to be welded. One possible approach is to calculate a target stopping position based on the average operability during the welding process, the travel distance, and the safety threshold between the welding robot and obstacles; then control the welding robot to move to the target stopping position to perform the welding operation on the workpiece. This disclosure automatically calculates the optimal stopping position, reducing reliance on manual operation.

[0040] Specifically, in the global common solution set In this process, a cost function is constructed based on the average operability, travel distance, and safety threshold of the welding robot and obstacles during the welding process. :

[0041] in, This refers to the average operability (dexterity) during the welding process. For the distance traveled, The safety threshold for welding robots and obstacles. , and These are the weighting coefficients.

[0042] By solving the cost function, the optimal target parking position is obtained. .

[0043] Next, control the welding robot to move to the target parking position, lock the chassis, and perform welding operations on the workpiece to be welded until the welding is completed.

[0044] In another exemplary embodiment, a dynamic collaborative welding mode is employed to perform welding operations on the workpiece. This disclosure eliminates the influence of the moving chassis motion on weld formation through a dynamic collaborative speed compensation mechanism. Specifically, firstly, chassis path planning: a Frenet coordinate system (along the weld curve coordinate system) is established on one side of the weld, and the chassis path is planned to ensure it always remains at the center of the robot arm's highly operable area. Secondly, velocity vector synthesis and disturbance compensation are performed, establishing a velocity coupling model:

[0045] in, For the constant welding speed required by the process (e.g.) ); The actual speed of the chassis (including vibrations and slippage caused by uneven ground). The angular velocity of the robotic arm joints; The current posture of the robotic arm. It is the velocity of the robotic arm's end effector in the robotic arm's coordinate system. .

[0046] During the welding process, the speed of the robotic arm joints is adjusted in real time. Even if the chassis shakes, the robotic arm will move in the opposite direction to counteract the shaking, ensuring that the absolute speed of the welding torch tip is constant in the world coordinate system.

[0047] Figure 2 This is a schematic diagram of the structure of an intelligent welding device 20 provided for an exemplary embodiment of this disclosure. (See diagram below.) Figure 2 As shown, the intelligent welding device 20 includes: a scanning module 21, a judgment module 22, and a control module 23.

[0048] The scanning module 21 is used to scan the workpiece to be welded using a vision sensor to obtain the welding trajectory. The judgment module 22 is used to determine whether the working space of the welding robot's robotic arm can cover the welding trajectory in the case of a single stop of the welding robot, and obtain the judgment result. The control module 23 is used to control the welding robot to perform welding operations on the workpiece to be welded based on the judgment result.

[0049] Optionally, when scanning the workpiece to be welded using a vision sensor to obtain the welding trajectory, the scanning module 21 is used for: A visual sensor is used to scan the workpiece to be welded to obtain weld point cloud data; The weld seam point cloud data is input into the welding trajectory generation model to obtain the welding trajectory.

[0050] Optionally, when determining whether the workspace of the welding robot's robotic arm can cover the welding trajectory and obtaining the determination result, the judgment module 22 is used for: The welding trajectory is discretized into multiple key welding points; For each key welding point, combined with the welding torch process posture constraints, the feasible region set of the robot arm base is solved using inverse kinematics; Calculate the global common solution set based on the feasible region set; The judgment result is determined based on the global common solution set.

[0051] Optionally, when determining the judgment result based on the global common solution set, the judgment module 22 is used to: If the global common solution set is non-empty, then the judgment result is determined to be that the working space of the welding robot's robotic arm can cover the welding trajectory. If the global common solution set is empty, then the judgment result is that the working space of the welding robot's robotic arm cannot cover the welding trajectory.

[0052] Optionally, when the control module 23 controls the welding robot to perform welding operations on the workpiece to be welded based on the judgment result, it is used to: If the result indicates that the working space of the welding robot's arm can cover the welding trajectory, then the fixed-point welding mode is used to perform the welding operation on the workpiece to be welded. If the result indicates that the working space of the welding robot's robotic arm cannot cover the welding trajectory, then a dynamic collaborative welding mode is adopted to perform welding operations on the workpiece to be welded.

[0053] Optionally, when the control module 23 performs welding operations on the workpiece to be welded using the spot welding mode, it is used to: Calculate the target parking position based on the average operability during the welding process, the travel distance, and the safety threshold between the welding robot and obstacles. Control the welding robot to move to the target parking position to perform welding operations on the workpiece to be welded.

[0054] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0055] Figure 3This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of the present disclosure. For example... Figure 3 As shown, the electronic device includes a memory 31 and a processor 32. Additionally, the electronic device also includes a power supply component 33 and a communication component 34.

[0056] Memory 31 is used to store computer programs and can be configured to store various other data to support operation on the electronic device. Examples of this data include instructions for any application or method used to operate on the electronic device.

[0057] The memory 31 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0058] Communication component 34 is used for data transmission with other devices.

[0059] The processor 32 can execute computer instructions stored in the memory 31 to: scan the workpiece to be welded using a vision sensor to obtain a welding trajectory; determine whether the working space of the welding robot's robotic arm can cover the welding trajectory in the event of a single stop of the welding robot, and obtain a judgment result; and control the welding robot to perform welding operations on the workpiece to be welded based on the judgment result.

[0060] Accordingly, embodiments of this disclosure also provide a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores a computer program, and the computer program is executed by one or more processors, it causes one or more processors to perform... Figure 1 Each step in the method embodiment.

[0061] Accordingly, embodiments of this disclosure also provide a computer program product, which includes a computer program / instructions that are executed by a processor. Figure 1 Each step in the method embodiment.

[0062] The above Figure 3The communication component is configured to facilitate wired or wireless communication between the device containing the communication component and other devices. The device containing the communication component can access wireless networks based on communication standards, such as WiFi, 2G, 3G, 4G / LTE, 5G, or combinations thereof. In one exemplary embodiment, the communication component receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component also includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID), Infrared Data Association (IrDA) technology, Ultra-Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0063] The above Figure 3 The power supply component provides power to the various components of the device in which it resides. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which it resides.

[0064] The aforementioned electronic devices also include a display screen and audio components.

[0065] The display includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can sense not only the boundaries of touch or swipe actions, but also the duration and pressure associated with the touch or swipe operation.

[0066] An audio component may be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC) configured to receive external audio signals when the device containing the audio component is in an operating mode, such as call mode, recording mode, or voice recognition mode. The received audio signals may be further stored in memory or transmitted via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0067] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0068] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0069] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0070] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0071] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0072] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0073] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0074] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0075] The above are merely specific embodiments of this disclosure, enabling those skilled in the art to understand or implement this disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent welding method, characterized in that, include: The workpiece to be welded is scanned using a vision sensor to obtain the welding trajectory; In the case of a single stop of the welding robot, determine whether the working space of the robotic arm of the welding robot can cover the welding trajectory, and obtain the judgment result; Based on the judgment result, the welding robot is controlled to perform welding operations on the workpiece to be welded.

2. The method according to claim 1, characterized in that, The step of using a vision sensor to scan the workpiece to be welded and obtain the welding trajectory includes: A visual sensor is used to scan the workpiece to be welded to obtain weld point cloud data; The weld point cloud data is input into the welding trajectory generation model to obtain the welding trajectory.

3. The method according to claim 1, characterized in that, The step of determining whether the workspace of the welding robot's robotic arm can cover the welding trajectory and obtaining the determination result includes: The welding trajectory is discretized into multiple key welding points; For each of the aforementioned key welding points, combined with the welding torch process posture constraints, the feasible region set of the robotic arm base is solved using inverse kinematics. Calculate the global common solution set based on the feasible region set; The judgment result is determined based on the global common solution set.

4. The method according to claim 3, characterized in that, The determination of the judgment result based on the global common solution set includes: If the global common solution set is a non-empty set, then the determination result is that the working space of the welding robot's robotic arm can cover the welding trajectory. If the global common solution set is empty, then the judgment result is determined to be that the working space of the welding robot's robotic arm cannot cover the welding trajectory.

5. The method according to claim 1, characterized in that, The step of controlling the welding robot to perform welding operations on the workpiece to be welded based on the judgment result includes: If the determination result is that the working space of the welding robot's robotic arm can cover the welding trajectory, then the fixed-point welding mode is used to perform welding operations on the workpiece to be welded. If the determination result is that the working space of the welding robot's robotic arm cannot cover the welding trajectory, then a dynamic collaborative welding mode is adopted to perform welding operations on the workpiece to be welded.

6. The method according to claim 5, characterized in that, The welding operation on the workpiece to be welded using the fixed-point welding mode includes: Calculate the target parking position based on the average operability during the welding process, the travel distance, and the safety threshold between the welding robot and obstacles. The welding robot is controlled to move to the target parking position to perform welding operations on the workpiece to be welded.

7. An intelligent welding device, characterized in that, include: The scanning module is used to scan the workpiece to be welded using a vision sensor to obtain the welding trajectory; The judgment module is used to determine whether the working space of the robotic arm of the welding robot can cover the welding trajectory when the welding robot stops once, and obtain the judgment result. The control module is used to control the welding robot to perform welding operations on the workpiece to be welded based on the judgment result.

8. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to execute instructions to implement the steps of the method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-6.

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