Robot teaching-free welding positioning system based on vision
The robot-based teach-free welding positioning system, which utilizes visual recognition and intelligent path planning, automatically identifies welding points and plans routes. This solves the problem of existing systems requiring extensive debugging and manual adjustments, enabling efficient and flexible welding production and improving welding quality and production efficiency.
Patent Information
- Application Number
- CN202511824261.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-05
- Publication Date
- 2026-03-13
AI Technical Summary
Existing robot-based welding positioning systems require extensive debugging and calibration before being put into use. Furthermore, they require manual resetting and adjustment when dealing with products of different specifications and shapes, resulting in low production efficiency, high skill requirements for operators, and difficulty in meeting the demands for high-precision and high-quality welding.
A vision-based robot teaching-free welding positioning system is adopted. It uses a high-definition camera, image processing unit and route planning module combined with intelligent path planning algorithm to automatically identify welding points and plan routes. The control unit precisely controls the movement of the traveling trolley and welding robot, reducing the reliance on manual operation.
It improves the automation and flexibility of welding production, reduces production preparation time, reduces reliance on manual operation, ensures the stability and consistency of welding quality, and meets the high precision requirements of different products.
Smart Images
Figure CN121649666A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of robot teaching-free technology, and in particular to a vision-based robot teaching-free welding positioning system. Background Technology
[0002] Welding, a crucial processing technology in modern manufacturing, is widely used in numerous fields such as automobile manufacturing, aerospace, and shipbuilding. Precise positioning is a key factor in ensuring weld quality, directly affecting weld formation, weld strength, and the overall performance of the product. The main function of a welding positioning system is to provide precise positional information for the welding operation, guiding the welding equipment accurately to the predetermined welding position, thereby ensuring the stability and consistency of the welding process and meeting the high precision and quality requirements of various industrial products.
[0003] With the continuous development of industrial automation technology, robots are increasingly being widely used in the welding field, and many existing welding positioning systems employ robots to perform welding tasks. Robots offer advantages such as high precision, strong repeatability, and adaptability to harsh working environments, improving welding production efficiency and quality to a certain extent. However, existing robot-based welding positioning systems still face numerous challenges in practical applications. These systems require extensive debugging and calibration before deployment, including robot motion trajectory planning and welding parameter settings. These operations often require significant time and effort from specialized technicians. Furthermore, manual readjustment and adjustments are necessary when dealing with products of different specifications and shapes, increasing production preparation time and placing higher demands on operator skills, thus limiting production efficiency. Summary of the Invention
[0004] In order to at least solve one of the above-mentioned technical problems, the present invention aims to provide a vision-based robot teach-free welding positioning system, which further improves the automation and flexibility of welding production, reduces reliance on manual operation, and improves production efficiency and quality stability.
[0005] To achieve the above objectives, the present invention provides the following technical solution:
[0006] A vision-based robot teach-free welding positioning system includes a traveling trolley with an electric turntable for multi-degree-of-freedom adjustment; a welding robot is fixedly mounted on the moving part of the electric turntable; a high-definition camera is mounted on one side of the welding head of the welding robot; the high-definition camera is electrically connected to an image processing unit; the image processing unit is connected to a route planning module; and the route planning module is connected to a control unit, which controls the traveling trolley to move straight, turn, accelerate, and decelerate, and communicates with the welding robot and the electric turntable.
[0007] Preferably, a ring-shaped fill light strip is provided on one side of the high-definition camera, and the high-definition camera has an autofocus function.
[0008] Preferably, the image processing unit has built-in image recognition algorithms and deep learning models, which are used to preprocess the welding workpiece images captured by the high-definition camera, identify workpiece feature points, and analyze the overall shape and structure of the workpiece to find the welding points.
[0009] Preferably, the route planning module plans the welding route based on the welding point location information provided by the image processing unit, combined with the motion parameters of the traveling trolley and the welding robot, using an intelligent path planning algorithm.
[0010] Preferably, the control unit uses a high-performance microprocessor to receive route instructions sent by the route planning module and convert them into specific control signals to precisely control the motor speed and steering of the traveling trolley.
[0011] Preferably, it also includes a human-machine interface, which adopts a touch screen design, allowing operators to view images of the welding workpiece, welding point locations, planned route information, and set and adjust system parameters.
[0012] The present invention has the following beneficial effects:
[0013] I. Enhancing Welding Automation and Flexibility: This system captures images of the workpiece for welding using a high-definition camera. The image processing unit utilizes image recognition algorithms and deep learning models to preprocess the images, identify workpiece feature points, and analyze the overall shape and structure to locate the welding points. The route planning module plans the welding route based on this location information and the motion parameters of the traveling carriage and welding robot. The control unit precisely controls the traveling carriage and welding robot to execute the welding task. The entire process requires no complex manual teaching operations; the robot can automatically complete welding positioning and route planning based on visual information, greatly improving the automation level of welding production. Furthermore, the system can quickly adapt to and accurately locate welding points and plan suitable welding routes for products of different specifications and shapes, enhancing the flexibility of welding production.
[0014] Second, reduced reliance on manual operation: Traditional robot-based welding positioning systems require extensive debugging and calibration work by professional technicians before deployment, including robot motion trajectory planning and welding parameter settings. Furthermore, manual readjustment is necessary for different products, demanding high operator skills. In contrast, this system utilizes vision technology, with an image processing unit and route planning module automatically identifying welding points and planning routes. The control unit precisely controls equipment operation. Operators only need to view relevant information and make simple parameter adjustments through the human-machine interface, eliminating the need for advanced professional skills. This reduces reliance on manual operation and decreases production preparation time and labor costs.
[0015] III. Improved Production Efficiency and Quality Stability: This system achieves rapid and accurate welding positioning and route planning. The traveling trolley and welding robot can quickly reach the predetermined position and perform welding according to the planned route, reducing the time wasted due to manual debugging and setup, and improving production efficiency. Simultaneously, visual positioning and intelligent path planning ensure the accuracy of the welding position and the consistency of the welding route, avoiding errors that may occur during manual operation, guaranteeing the stability and consistency of the welding process, thereby improving welding quality stability and meeting the high requirements of different industrial products for welding precision and quality.
[0016] IV. Vision and Multi-device Collaboration: High-definition cameras work collaboratively with traveling carts, welding robots, and electric turntables. The image information captured by the high-definition cameras is processed to provide a basis for route planning. The control unit precisely controls the movements of the traveling cart and welding robot according to the planned route. The electric turntable achieves multi-degree-of-freedom adjustment, enabling the welding robot to weld in the optimal posture. This combination achieves efficient conversion of visual information into equipment movements, fully leverages the advantages of each device, and improves overall welding positioning and operational capabilities.
[0017] V. Combination of Intelligent Algorithms and Hardware Equipment: The image processing unit's built-in image recognition algorithm and deep learning model are combined with the intelligent path planning algorithm of the route planning module, along with a high-performance microprocessor control unit and hardware equipment such as a high-definition camera with autofocus and a ring-shaped fill light strip. The intelligent algorithm performs precise processing and analysis of images to plan the optimal welding route, while the hardware equipment ensures the clarity of image acquisition and the precision of control execution. The cooperation between software and hardware improves the system's intelligence level and the accuracy of welding positioning.
[0018] VI. Human-Computer Interaction and System Operation Integration: The human-computer interaction interface adopts a touchscreen design, allowing operators to easily view images of the welding workpiece, welding point locations, and planned route information, as well as set and adjust system parameters. This human-computer interaction method, combined with automatic system operation, ensures that the system can automatically complete most of the welding positioning and planning work based on visual information, while also allowing operators to intervene and adjust as necessary, thus improving the system's operability and adaptability. Attached Figure Description
[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a schematic diagram of the structure of an embodiment of the present invention.
[0021] Figure 2 This is a schematic diagram of the connection relationship in an embodiment of the present invention.
[0022] In the diagram: 1. Moving trolley; 2. Electric turntable; 3. Welding robot; 4. High-definition camera; 5. Control unit; 6. Ring-shaped supplementary lighting strip; 7. Human-machine interface. Detailed Implementation
[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0024] like Figures 1 to 2 As shown, a vision-based robot teach-free welding positioning system includes a traveling trolley 1, an electric turntable 2 mounted on the traveling trolley 1 for multi-degree-of-freedom adjustment; a welding robot 3 fixedly mounted on the movable part of the electric turntable 2; a high-definition camera 4 mounted on one side of the welding head of the welding robot 3; the high-definition camera 4 electrically connected to an image processing unit; the image processing unit connected to a route planning module; and a control unit 5 connected to the route planning module, which controls the traveling trolley 1 to move straight, turn, accelerate, and decelerate, and communicates with the welding robot 3 and the electric turntable 2.
[0025] like Figures 1 to 2As shown, a high-definition camera 4 is installed on one side of the welding head of the welding robot 3. During operation, it captures images of the workpiece and transmits these image data as electrical signals to the image processing unit electrically connected to it. After receiving the image data from the high-definition camera 4, the image processing unit uses built-in image recognition algorithms and deep learning models to preprocess the images, such as removing noise and enhancing contrast, to improve image quality. It then identifies feature points of the workpiece, such as edges and corners, and further analyzes the overall shape and structure of the workpiece to determine the welding locations. After obtaining the welding point location information provided by the image processing unit, the route planning module combines the motion parameters of the traveling carriage 1 and the welding robot 3, such as the maximum speed and acceleration of the traveling carriage 1, and the joint range of motion and movement speed of the welding robot 3, and uses intelligent path planning algorithms, such as the A* algorithm and Dijkstra's algorithm, to plan the optimal welding route from the current position to each welding point.
[0026] The control unit 5 employs a high-performance microprocessor. It receives route instructions from the route planning module and transforms these abstract instructions into specific control signals. For the traveling trolley 1, the control signals precisely control the speed and direction of its motor, thereby enabling actions such as straight-line movement, turning, acceleration, and deceleration. Simultaneously, the control unit 5 is also communicatively connected to the welding robot 3 and the electric turntable 2. It sends welding action instructions to the welding robot 3, controlling the movement of its welding head and welding parameters, and sends rotation instructions to the electric turntable 2, achieving multi-degree-of-freedom adjustment so that the welding robot 3 can reach the welding position in a suitable posture to perform welding operations.
[0027] like Figures 1 to 2 As shown, the ring-shaped fill light strip 6 on one side of the high-definition camera 4 provides uniform and sufficient light to the shooting area, eliminating problems such as image blurring and shadows caused by insufficient or uneven lighting. Simultaneously, the high-definition camera 4's autofocus function automatically adjusts the lens focal length according to the distance between the welding workpiece and the camera, ensuring that the captured image remains clear at all times, thus providing high-quality raw data for subsequent image processing.
[0028] like Figures 1 to 2 As shown, the ring-shaped fill light strip 6 on one side of the high-definition camera 4 provides uniform and sufficient light to the shooting area, eliminating problems such as image blurring and shadows caused by insufficient or uneven lighting. Simultaneously, the high-definition camera 4's autofocus function automatically adjusts the lens focal length according to the distance between the welding workpiece and the camera, ensuring that the captured image remains clear at all times, thus providing high-quality raw data for subsequent image processing.
[0029] like Figures 1 to 2The route planning module, after obtaining the welding point location information provided by the image processing unit, combines the motion parameters of the traveling vehicle 1 and the welding robot 3, such as the maximum travel speed, acceleration, and minimum turning radius of the traveling vehicle 1, and the joint range of motion and movement speed of the welding robot 3, and applies intelligent path planning algorithms, such as genetic algorithms, ant colony algorithms, or A* algorithms. Taking the genetic algorithm as an example, it transforms the welding route planning problem into an optimization problem, treating different welding routes as individuals, and continuously iterating and optimizing through operations such as selection, crossover, and mutation, ultimately finding an optimal or near-optimal welding route from the starting position to each welding point, and sending this route information to the control unit 5.
[0030] like Figures 1 to 2 As shown, the control unit 5 employs a high-performance microprocessor. After receiving route instructions from the route planning module, it transforms these abstract route instructions into specific control signals. For the traveling vehicle 1, the control signals precisely control the speed and direction of its motors. For example, the motor speed is controlled by adjusting the duty cycle of the PWM (Pulse Width Modulation) signal, and the direction is achieved by controlling the forward and reverse rotation of the motor, thus enabling the traveling vehicle 1 to travel accurately along the planned route. Simultaneously, the control unit 5 also communicates with the welding robot 3, controlling the joint movements of the welding robot 3 so that its welding head can accurately reach the welding point for welding operations.
[0031] like Figures 1 to 2 As shown, the human-machine interface 7 adopts a touch screen design, allowing operators to intuitively view images of the workpiece being welded, the specific locations of the welding points, and the planned welding route information. If the welding route is found to be unreasonable or system parameters need to be adjusted, operators can directly operate on the touch screen to set and adjust system parameters such as the brightness of the supplementary lighting strip, the parameters of the image processing algorithm, and the weights of the route planning algorithm to meet the needs of different welding tasks.
[0032] The above are merely specific embodiments of the present invention, but the technical features of the present invention are not limited thereto. Any simple changes, equivalent substitutions, or modifications made based on the present invention to solve essentially the same technical problems and achieve essentially the same technical effects are all covered within the protection scope of the present invention.
Claims
1. A vision-based robot teach-free welding positioning system, characterized in that, The system includes a traveling trolley (1), on which an electric turntable (2) is installed. The electric turntable (2) is used for multi-degree-of-freedom adjustment. A welding robot (3) is fixedly installed on the movable part of the electric turntable (2). A high-definition camera (4) is installed on one side of the welding head of the welding robot (3). The high-definition camera (4) is electrically connected to an image processing unit. The image processing unit is connected to a route planning module. The route planning module is connected to a control unit (5). The control unit (5) is used to control the traveling trolley (1) to go straight, turn, accelerate, and decelerate, and is communicatively connected to the welding robot (3) and the electric turntable (2).
2. The vision-based robot teach-free welding positioning system according to claim 1, characterized in that, The high-definition camera (4) has a ring-shaped fill light strip on one side and has an autofocus function.
3. The vision-based robot teach-free welding positioning system according to claim 2, characterized in that, The image processing unit has built-in image recognition algorithms and deep learning models, which are used to preprocess the welding workpiece images captured by the high-definition camera (4), identify workpiece feature points, and analyze the overall shape and structure of the workpiece to find the welding points.
4. The vision-based robot teach-free welding positioning system according to claim 3, characterized in that, The route planning module plans the welding route based on the welding point location information provided by the image processing unit, combined with the motion parameters of the traveling trolley (1) and the welding robot (3), using an intelligent path planning algorithm.
5. A vision-based robot teach-free welding positioning system according to claim 4, characterized in that, The control unit (5) uses a high-performance microprocessor to receive route instructions sent by the route planning module and convert them into specific control signals to precisely control the motor speed and direction of the traveling trolley (1).
6. The vision-based robot teach-free welding positioning system according to claim 5, characterized in that, It also includes a human-machine interface (7), which is designed with a touch screen. Operators can use it to view images of the welding workpiece, welding point positions, and planned route information, and set and adjust system parameters.