An offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning

Abstract

This invention provides an offline programming and debugging method for repairing and cutting automotive door panels based on 3D scanning, relating to the field of automotive door panel processing. The method includes 3D scanning of the door panel and importing it into a cutting scene; establishing a process simulation model of the cutting robot and the cutting scene, ensuring the simulation model corresponds to the real-world cutting scene; and connecting PLC signals with sensors on the cutting robot in the process simulation model via connection software, thereby injecting control logic consistent with the real-world cutting scene into the simulation model, and simultaneously detecting successful connection. This invention establishes a virtual model using 3D scanned door panel data and imports it into offline programming software. Cutting trajectories are planned and generated in the virtual environment, and then imported into relevant cutting equipment. Before cutting, the offline software simulates the splicing effect, adjusting the cutting trajectory in advance to ensure that the gap between the cut and the new component is less than 0.5 mm, achieving high cutting precision.

Description

Technical Field

[0001] This invention relates to the field of automotive door panel processing technology, and in particular to an offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning. Background Technology

[0002] In the repair of car doors after partial wear caused by collisions, or in the scenario of precise cutting of new car door panels, the current cutting operation for car doors mainly adopts the manual operation of hand-held cutting tools. The core principle is that the operator visually observes and locates the cutting boundary of the damaged car door or panel, and then cuts with a hand-held cutting tool. The cutting trajectory and depth rely entirely on the worker's experience and judgment, resulting in inconsistent cutting accuracy. Therefore, this invention proposes an offline programming and debugging method for the cutting path of car door panel repair based on 3D scanning to solve the problems existing in the prior art. Summary of the Invention

[0003] To address the aforementioned issues, this invention proposes an offline programming and debugging method for repairing and cutting automotive door panels based on 3D scanning. This method establishes a virtual model using 3D scanned 3D data of the automotive door and imports it into offline programming software. Cutting trajectories are planned and generated in the virtual environment and then imported into relevant cutting equipment. Before cutting, the splicing effect is simulated using offline software, and the cutting trajectory is adjusted in advance to ensure that the gap between the cut and the new component is less than 0.5 mm, achieving high cutting precision.

[0004] To achieve the objectives of this invention, the invention is implemented through the following technical solution: an offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning, comprising the following steps:

[0005] Step 1: By 3D scanning the car door panel and importing the cutting scene, a process simulation model of the cutting robot and the cutting scene is established, so that the process simulation model corresponds to the real cutting scene. At the same time, the PLC signal is associated with the sensor on the cutting robot in the process simulation model through the connection software, thereby injecting the process simulation model with the same control logic as the real cutting scene, and checking whether the connection is successful. The process simulation model also includes process parameter information for cutting simulation, and simulates the cutting process of the physical equipment in the real cutting scene in the working state, and identifies the cutting area.

[0006] Step 2: Plan the cutting trajectory of the cutting robot. In offline programming software (such as Visual Components), automatically or semi-automatically generate the cutting path based on the process simulation model. The path accuracy is controlled within ±0.1mm, and manual input adjustment is also supported.

[0007] Step 3: Perform virtual simulation verification. Simulate the movement process of the cutting equipment in the software, verify the safe distance between the trajectory and the non-working area of ​​the door, and detect whether mechanical interference, abnormal posture or path clipping occurs. At the same time, it supports multi-axis robot posture optimization and no-cutting area setting.

[0008] Step 4: Perform parameter synchronization by synchronizing the verified trajectory parameters and device motion parameters from the offline programming software to the cutting robot.

[0009] Step 5: The cutting robot performs the cutting. The equipment automatically completes the cutting based on the synchronization parameters, and provides real-time feedback on trajectory deviations and dynamically corrects them during the process.

[0010] A further improvement lies in the following steps: In step 1, the method for constructing the process simulation model includes the following steps:

[0011] S1. Three-dimensional data acquisition of the car door panel and construction of the digital car door panel are carried out. The car door panel is repeatedly scanned from multiple angles using a high-precision 3D scanner to obtain the point cloud dataset of the car door panel. The point cloud dataset is processed by using the statistical outlier removal (SOR) algorithm to remove noise points. Then, the iterative nearest point (ICP) algorithm is used to register the point cloud dataset so that the repeated points in the point cloud dataset are accurately aligned to the same coordinate system. Finally, the Poisson reconstruction algorithm is used to construct the digital car door panel model from the point cloud dataset.

[0012] S2. Obtain the accurate 3D CAD model and kinematic parameter file of the cutting robot from the cutting robot manufacturer, import it into the offline programming software, and correctly define the length and torsion angle of each link of the cutting robot, as well as the type (rotation / translation) and range of motion of each joint of the cutting robot according to the robot's DH parameters. At the same time, set the position and direction of the cutting tool relative to the end flange of the cutting robot, thereby constructing the motion model of the cutting robot.

[0013] S3. Establish the spatial relationship between the motion model of the cutting robot and the digital door panel model. In reality, measure the 3D coordinates of three non-collinear feature points of the door panel in the base coordinate system of the cutting robot. At the same time, in the offline programming software, establish corresponding "virtual marker points" at these 3D coordinates. Using the least squares method, calculate an optimal rigid body transformation matrix (rotation matrix R and translation vector T) to minimize the error between the marker points on the virtual door model and the measured 3D coordinate points in reality. Finally, apply this transformation matrix to the entire digital door panel model to accurately "place" it in the correct position within the workspace of the cutting robot motion model. At this point, the coordinates of the tool center point of the robot motion model in the offline programming software moving to a certain point on the digital door panel model will be completely consistent with the coordinates of the cutting robot moving to that point on the door panel in reality.

[0014] A further improvement lies in the following steps: In step 1, the method for injecting control logic into the process simulation model includes the following steps:

[0015] A1. In the connection software, configure the correspondence between the input / output signal addresses of the physical PLC and the virtual sensors and virtual actuators in the process simulation model;

[0016] A2. Establish a virtual-physical link between the process simulation model and the physical PLC through the OPC UA industrial communication protocol to ensure that the physical PLC can drive virtual sensors in real time and that virtual control instructions can be safely written into the physical PLC for logic testing.

[0017] A3. Employ a multi-layered handshake protocol, including network connectivity testing, protocol session verification, and data echo testing, to comprehensively determine whether the virtual and physical links have been successfully established and meet synchronization accuracy requirements.

[0018] A further improvement is made in step 2, where the method for automatically generating the cutting trajectory includes the following steps:

[0019] B1. Based on the digital door panel model, the cutting boundary curve is automatically extracted through the edge detection algorithm. For the damage repair scenario, the region growth algorithm is used to expand from the damage point to the geometric discontinuity boundary.

[0020] B2. Adaptive arc length discretization is performed on the boundary curve, and the sampling density is increased in areas with large curvature to ensure contour accuracy.

[0021] B3. For each path point, the surface normal vector is calculated through local surface fitting. Combined with the cutting direction, the optimal posture of the tool coordinate system (TCP) is automatically determined to ensure that the cutting head is always perpendicular to the workpiece surface.

[0022] B4. Under multiple conditions such as accessibility, joint constraints, velocity / acceleration constraints, and collision avoidance of the cutting robot, B-spline interpolation and time-optimal algorithm are used to generate smooth and efficient trajectories.

[0023] B5. Establish a material-thickness-process parameter database, and adjust parameters such as cutting power, cutting speed, and focal point position in real time according to the material properties of the cutting position to achieve adaptive cutting;

[0024] B6. Using a dedicated processor, the optimized trajectory is converted into executable code for the cutting robot control system and integrated with process control instructions.

[0025] Further improvements are made in step 2, where operators can write scripts based on actual needs and past experience, and use these scripts to define the logic and behavior of the cutting robot's motion model in offline programming software, binding the planned cutting path (a series of spatial points) with the tool center point motion trajectory of the cutting robot.

[0026] Further improvements are made in step 3 by using a continuous collision detection (CCD) algorithm to calculate the minimum distance between objects in real time, predict possible interference, and verify the cutting effect.

[0027] Further improvements are made in step 5, where, in a real cutting scenario, the operator records the motion posture of the sensors on the cutting robot and each axis of the cutting robot, and monitors whether there are any discrepancies between the cutting speed, cutting power, cutting path, focal position, and entry / exit points and the simulation data. If the data difference is too large, the operator will start troubleshooting from step 1, optimize the trajectory, and run the test again. If the data difference is within the allowable range, the robot will run according to the original trajectory.

[0028] The beneficial effects of this invention are as follows: This invention establishes a virtual model by scanning the three-dimensional data of the car door using 3D scanning and imports it into offline programming software. The cutting trajectory is planned and generated in the virtual environment and then imported into the relevant cutting equipment. Before cutting, the splicing effect is simulated through offline software, and the cutting trajectory is adjusted in advance to ensure that the gap between the cut and the new part after cutting is less than 0.5 mm. The cutting accuracy is high, and there is no need for repeated debugging, saving time and cost. Non-working areas of the car door can be set in the offline programming. When the cutting equipment approaches the forbidden cutting boundary, the system triggers a stop command to prevent accidental cutting. At the same time, simulation can be performed in the software to eliminate the risk of collision in advance. Attached Figure Description

[0029] Figure 1 This is a flowchart of the present invention; Figure 2 This is a flowchart of the cutting trajectory generation process of the present invention. Detailed Implementation

[0030] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0031] according to Figures 1-2 As shown, this embodiment proposes an offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning, including the following steps:

[0032] Step 1: By 3D scanning the car door panel and importing the cutting scene, a process simulation model of the cutting robot and the cutting scene is established, so that the process simulation model corresponds to the real cutting scene. At the same time, the PLC signal is associated with the sensor on the cutting robot in the process simulation model through the connection software, thereby injecting the process simulation model with the same control logic as the real cutting scene, and checking whether the connection is successful. The process simulation model also includes process parameter information for cutting simulation, and simulates the cutting process of the physical equipment in the real cutting scene in the working state, and identifies the cutting area.

[0033] Step 2: Plan the cutting trajectory of the cutting robot. In offline programming software (such as Visual Components), automatically or semi-automatically generate the cutting path based on the process simulation model. The path accuracy is controlled within ±0.1mm, and manual input adjustment is also supported.

[0034] Step 3: Perform virtual simulation verification. Simulate the movement process of the cutting equipment in the software, verify the safe distance between the trajectory and the non-working area of ​​the door, and detect whether mechanical interference, abnormal posture or path clipping occurs. At the same time, it supports multi-axis robot posture optimization and no-cutting area setting.

[0035] Step 4: Perform parameter synchronization by synchronizing the verified trajectory parameters and device motion parameters from the offline programming software to the cutting robot.

[0036] Step 5: The cutting robot performs the cutting. The equipment automatically completes the cutting based on the synchronization parameters, and provides real-time feedback on trajectory deviations and dynamically corrects them during the process.

[0037] In step 1, the method for constructing the process simulation model includes the following steps:

[0038] S1. Three-dimensional data acquisition of the car door panel and construction of the digital car door panel are carried out. The car door panel is repeatedly scanned from multiple angles using a high-precision 3D scanner to obtain the point cloud dataset of the car door panel. The point cloud dataset is processed by using the statistical outlier removal (SOR) algorithm to remove noise points. Then, the iterative nearest point (ICP) algorithm is used to register the point cloud dataset so that the repeated points in the point cloud dataset are accurately aligned to the same coordinate system. Finally, the Poisson reconstruction algorithm is used to construct the digital car door panel model from the point cloud dataset.

[0039] S2. Obtain the accurate 3D CAD model and kinematic parameter file of the cutting robot from the cutting robot manufacturer, import it into the offline programming software, and correctly define the length and torsion angle of each link of the cutting robot, as well as the type (rotation / translation) and range of motion of each joint of the cutting robot according to the robot's DH parameters. At the same time, set the position and direction of the cutting tool relative to the end flange of the cutting robot, thereby constructing the motion model of the cutting robot.

[0040] S3. Establish the spatial relationship between the motion model of the cutting robot and the digital door panel model. In reality, measure the 3D coordinates of three non-collinear feature points of the door panel in the base coordinate system of the cutting robot. At the same time, in the offline programming software, establish corresponding "virtual marker points" at these 3D coordinates. Using the least squares method, calculate an optimal rigid body transformation matrix (rotation matrix R and translation vector T) to minimize the error between the marker points on the virtual door model and the measured 3D coordinate points in reality. Finally, apply this transformation matrix to the entire digital door panel model to accurately "place" it in the correct position within the workspace of the cutting robot motion model. At this point, the coordinates of the tool center point of the robot motion model in the offline programming software moving to a certain point on the digital door panel model will be completely consistent with the coordinates of the cutting robot moving to that point on the door panel in reality.

[0041] In step 1, the method of injecting control logic into the process simulation model includes the following steps:

[0042] A1. In the connection software, configure the correspondence between the input / output signal addresses of the physical PLC and the virtual sensors and virtual actuators in the process simulation model;

[0043] A2. Establish a virtual-physical link between the process simulation model and the physical PLC through the OPC UA industrial communication protocol to ensure that the physical PLC can drive virtual sensors in real time and that virtual control instructions can be safely written into the physical PLC for logic testing.

[0044] A3. Employ a multi-layered handshake protocol, including network connectivity testing, protocol session verification, and data echo testing, to comprehensively determine whether the virtual and physical links have been successfully established and meet synchronization accuracy requirements.

[0045] In step 2, the method for automatically generating the cutting trajectory includes the following steps:

[0046] B1. Based on the digital door panel model, the cutting boundary curve is automatically extracted through the edge detection algorithm. For the damage repair scenario, the region growth algorithm is used to expand from the damage point to the geometric discontinuity boundary.

[0047] B2. Adaptive arc length discretization is performed on the boundary curve, and the sampling density is increased in areas with large curvature to ensure contour accuracy.

[0048] B3. For each path point, the surface normal vector is calculated through local surface fitting. Combined with the cutting direction, the optimal posture of the tool coordinate system (TCP) is automatically determined to ensure that the cutting head is always perpendicular to the workpiece surface.

[0049] B4. Under multiple conditions such as accessibility, joint constraints, velocity / acceleration constraints, and collision avoidance of the cutting robot, B-spline interpolation and time-optimal algorithm are used to generate smooth and efficient trajectories.

[0050] B5. Establish a material-thickness-process parameter database, and adjust parameters such as cutting power, cutting speed, and focal point position in real time according to the material properties of the cutting position to achieve adaptive cutting;

[0051] B6. Using a dedicated processor, the optimized trajectory is converted into executable code for the cutting robot control system and integrated with process control instructions.

[0052] In step 2, the operator can also write a script based on actual needs and past experience, and use the script to define the logic and behavior of the cutting robot motion model in the offline programming software, and bind the planned cutting path (a series of spatial points) to the motion trajectory of the cutting robot's tool center point.

[0053] In step 3, the minimum distance between objects is calculated in real time using the continuous collision detection (CCD) algorithm to predict possible interference and verify the cutting effect.

[0054] In step 5, under the actual cutting scenario, the operator records the motion posture of the sensors on the cutting robot and each axis of the cutting robot. At the same time, the operator monitors whether there are any discrepancies between the cutting speed, cutting power, cutting path, focal position, and entry and exit points and the simulation data. If the data difference is too large, the operator will start troubleshooting from step 1, optimize the trajectory, and run the operation again. If the data difference is within the allowable range, the operator will run the operation according to the original trajectory.

[0055] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for offline programming and debugging of cutting paths for repairing automotive door panels based on 3D scanning, characterized in that: Includes the following steps: Step 1: Scan the car door panel with 3D and import the cutting scene to establish a process simulation model of the cutting robot and the cutting scene, so that the process simulation model corresponds to the real cutting scene. At the same time, the PLC signal is associated with the virtual sensors and virtual actuators on the virtual cutting robot in the process simulation model through the connection software, so as to inject the control logic consistent with the real cutting scene into the process simulation model, and at the same time check whether the connection is successful. The process simulation model also includes process parameter information for cutting simulation, and simulates the cutting process of the physical equipment in the real cutting scene in the working state, and identifies the cutting area. Step 2: Plan the cutting trajectory of the cutting robot. In offline programming software (such as Visual Components), automatically or semi-automatically generate the cutting path based on the process simulation model. The path accuracy is controlled within ±0.1mm, and manual input adjustment is also supported. Step 3: Perform virtual simulation verification. Simulate the movement process of the cutting equipment in the software, verify the safe distance between the trajectory and the non-working area of ​​the door, and detect whether mechanical interference, abnormal posture or path clipping occurs. At the same time, it supports multi-axis robot posture optimization and no-cutting area setting. Step 4: Perform parameter synchronization by synchronizing the verified trajectory parameters and device motion parameters from the offline programming software to the cutting robot. Step 5: The cutting robot performs the cutting. The equipment automatically completes the cutting based on the synchronization parameters, and provides real-time feedback on trajectory deviations and dynamically corrects them during the process.

2. The offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning as described in claim 1, characterized in that: In step 1, the method for constructing the process simulation model includes the following steps: S1. Three-dimensional data acquisition of the car door panel and construction of the digital car door panel are carried out. The car door panel is repeatedly scanned from multiple angles using a high-precision 3D scanner to obtain the point cloud dataset of the car door panel. The point cloud dataset is processed by using the statistical outlier removal (SOR) algorithm to remove noise points. Then, the iterative nearest point (ICP) algorithm is used to register the point cloud dataset so that the repeated points in the point cloud dataset are accurately aligned to the same coordinate system. Finally, the Poisson reconstruction algorithm is used to construct the digital car door panel model from the point cloud dataset. S2. Obtain the accurate 3D CAD model and kinematic parameter file of the cutting robot from the cutting robot manufacturer, import it into the offline programming software, and correctly define the length and torsion angle of each link of the cutting robot, as well as the type (rotation / translation) and range of motion of each joint of the cutting robot according to the robot's DH parameters. At the same time, set the position and direction of the cutting tool relative to the end flange of the cutting robot, thereby constructing the motion model of the cutting robot. S3. Establish the spatial relationship between the motion model of the cutting robot and the digital door panel model. In reality, measure the 3D coordinates of three non-collinear feature points of the door panel in the base coordinate system of the cutting robot. At the same time, in the offline programming software, establish corresponding "virtual marker points" at these 3D coordinates. Using the least squares method, calculate an optimal rigid body transformation matrix (rotation matrix R and translation vector T) to minimize the error between the marker points on the virtual door model and the measured 3D coordinate points in reality. Finally, apply this transformation matrix to the entire digital door panel model to accurately "place" it in the correct position within the workspace of the cutting robot motion model. At this point, the coordinates of the tool center point of the robot motion model in the offline programming software moving to a certain point on the digital door panel model will be completely consistent with the coordinates of the cutting robot moving to that point on the door panel in reality.

3. The offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning as described in claim 2, characterized in that: In step 1, the method of injecting control logic into the process simulation model includes the following steps: A1. In the connection software, configure the correspondence between the input / output signal addresses of the physical PLC and the virtual sensors and virtual actuators on the virtual cutting robot in the process simulation model; A2. Establish a virtual-physical link between the process simulation model and the physical PLC through the OPC UA industrial communication protocol to ensure that the physical PLC can drive virtual sensors in real time and that virtual control instructions can be safely written into the physical PLC for logic testing. A3. Employ a multi-layered handshake protocol, including network connectivity testing, protocol session verification, and data echo testing, to comprehensively determine whether the virtual and physical links have been successfully established and meet synchronization accuracy requirements.

4. The offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning, as described in claim 3, is characterized in that: In step 2, the method for automatically generating the cutting trajectory includes the following steps: B1. Based on the digital door panel model, the cutting boundary curve is automatically extracted through the edge detection algorithm. For the damage repair scenario, the region growth algorithm is used to expand from the damage point to the geometric discontinuity boundary. B2. Adaptive arc length discretization is performed on the boundary curve, and the sampling density is increased in areas with large curvature to ensure contour accuracy. B3. For each path point, the surface normal vector is calculated through local surface fitting. Combined with the cutting direction, the optimal posture of the tool coordinate system (TCP) is automatically determined to ensure that the cutting head is always perpendicular to the workpiece surface. B4. Under multiple conditions such as accessibility, joint constraints, velocity / acceleration constraints, and collision avoidance of the cutting robot, B-spline interpolation and time-optimal algorithm are used to generate smooth and efficient trajectories. B5. Establish a material-thickness-process parameter database, and adjust parameters such as cutting power, cutting speed, and focal point position in real time according to the material properties of the cutting position to achieve adaptive cutting; B6. Using a dedicated processor, the optimized trajectory is converted into executable code for the cutting robot control system and integrated with process control instructions.

5. The offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning according to claim 4, characterized in that: In step 2, the operator can also write a script based on actual needs and past experience, and use the script to define the logic and behavior of the cutting robot motion model in the offline programming software, and bind the planned cutting path (a series of spatial points) to the motion trajectory of the cutting robot's tool center point.

6. The offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning according to claim 5, characterized in that: In step 3, the minimum distance between objects is calculated in real time using the continuous collision detection (CCD) algorithm to predict possible interference and verify the cutting effect.

7. The offline programming and debugging method for repairing and cutting paths of automotive door panels based on 3D scanning as described in claim 6, characterized in that: In step 5, under the actual cutting scenario, the operator records the motion posture of the sensors on the cutting robot and each axis of the cutting robot. At the same time, the operator monitors whether there are any discrepancies between the cutting speed, cutting power, cutting path, focal position, and entry and exit points and the simulation data. If the data difference is too large, the operator will start troubleshooting from step 1, optimize the trajectory, and run the operation again. If the data difference is within the allowable range, the operator will run the operation according to the original trajectory.

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