Vehicle gluing positioning method and device, electronic equipment and storage medium

Abstract

The invention discloses a vehicle gluing positioning method which comprises the following steps: when a vehicle body to be glued moves to a gluing station, determining a preset identification feature and a preset identification feature image coordinate; obtaining a vehicle body current image of the vehicle body to be glued; identifying the current image of each vehicle body, and determining the current identification feature and the current identification feature image coordinate of the current image of each vehicle body; judging whether the current identification feature is matched with a preset identification feature or not; if yes, whether the current identification feature image coordinates are the same as the preset identification feature image coordinates of the matched preset identification features or not is judged; and if not, the offset of the mechanical arm is determined according to the current image identification feature coordinates. The mechanical arm is ensured to be accurately positioned during gluing, so that the gluing accuracy and consistency are greatly improved. The invention further discloses a device for implementing the method, electronic equipment and a computer readable storage medium.

Description

Technical Field

[0001] The present invention relates to the field of industrial control technology, and in particular to a vehicle gluing positioning method, device, electronic equipment and storage medium. Background Art

[0002] During the automobile production process, the car body is automatically transported on the production line through a skid; when the car body reaches the gluing station, the robot will automatically apply glue to it. Due to the error of the transmission system, the car body cannot stop at the same position every time, but the working position of the robot arm is unchanged. Therefore, the gluing position may be inaccurate when the robot arm is working. Summary of the invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a vehicle gluing positioning method, device, electronic device and storage medium. The technical problem to be solved by the present invention is achieved through the following technical solutions: A first aspect of an embodiment of the present invention provides a vehicle gluing positioning method, comprising the following steps: When the car body to be glued moves to the gluing station, the current car model and current process are obtained; Determining a preset identification feature and a corresponding preset identification feature image coordinate according to the current vehicle model and the current process; Acquire current images of at least three parts of the vehicle body to be coated with glue, respectively captured by at least three industrial cameras; Identify each of the current images of the vehicle body, and determine the current identification feature of each of the current images of the vehicle body and the corresponding current identification feature image coordinates; Determining whether the current identification feature matches the preset identification feature; If they match, determining whether the current identification feature image coordinates corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature; If not, the robot arm offset is determined according to the current image identification feature coordinates corresponding to a plurality of different current identification features.

[0004] In one embodiment of the present invention, the method further comprises: A motion instruction is sent to the robotic arm according to the robotic arm offset.

[0005] In one embodiment of the present invention, the determining of the robot arm offset according to the current image identification feature coordinates corresponding to the multiple different current identification features includes: Convert the current image identification feature coordinates into the current identification feature camera coordinates in the camera coordinate system; Convert the current identification feature camera coordinates into the current identification feature manipulator arm coordinates in the manipulator arm coordinate system; The mechanical arm offset is determined according to the preset mechanical arm coordinates of the current identification feature and the mechanical arm coordinates of the current identification feature.

[0006] In one embodiment of the present invention, the determining of the robot arm offset according to the preset robot arm coordinates of the current identification feature and the robot arm coordinates of the current identification feature includes: Determine an average translation deviation of the robot arm according to a plurality of preset robot arm coordinates of the current identification features and the robot arm coordinates of the current identification features; Respectively centering the plurality of current identification feature preset mechanical arm coordinates and the current identification feature mechanical arm coordinates to obtain preset centralized coordinates and current centralized coordinates; Constructing a covariance matrix according to the preset centered coordinates and the current centered coordinates; Performing singular value decomposition on the covariance matrix; Calculate the robot arm rotation deviation matrix according to the singular value decomposition result; Converting the robot arm rotation error matrix into the robot arm rotation Euler angle; The offset of the robotic arm is determined according to the average translation deviation of the robotic arm and the Euler angle of rotation of the robotic arm.

[0007] A second aspect of an embodiment of the present invention provides a vehicle gluing positioning device, comprising: The first acquisition module is used to acquire the current vehicle model and current process when the vehicle body to be glued moves to the glue coating station; A first determination module, used to determine a preset identification feature and a corresponding preset identification feature image coordinate according to the current vehicle model and the current process; A second acquisition module is used to acquire current images of the vehicle body to be coated with glue at at least three parts of the vehicle body captured by at least three industrial cameras respectively; A second determination module is used to identify each of the current images of the vehicle body, and determine the current identification feature of each of the current images of the vehicle body and the corresponding current identification feature image coordinates; A matching module, used to determine whether the current identification feature matches the preset identification feature; A judgment module, used for judging whether the image coordinates of the current identification feature corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature if there is a match; A calculation module is used to determine the robot arm offset according to the current image identification feature coordinates corresponding to multiple different current identification features.

[0008] In one embodiment of the present invention, it further includes: a sending module, used to send a motion instruction to the robotic arm according to the offset of the robotic arm.

[0009] In one embodiment of the present invention, the determining of the robot arm offset according to the current image identification feature coordinates corresponding to the multiple different current identification features includes: Convert the current image identification feature coordinates into the current identification feature camera coordinates in the camera coordinate system; Convert the current identification feature camera coordinates into the current identification feature manipulator arm coordinates in the manipulator arm coordinate system; The mechanical arm offset is determined according to the preset mechanical arm coordinates of the current identification feature and the mechanical arm coordinates of the current identification feature.

[0010] In one embodiment of the present invention, the method includes: determining the offset of the mechanical arm according to the preset mechanical arm coordinates of the current identification feature and the mechanical arm coordinates of the current identification feature, including: Determine an average translation deviation of the robot arm according to a plurality of preset robot arm coordinates of the current identification features and the robot arm coordinates of the current identification features; Respectively centering the plurality of current identification feature preset mechanical arm coordinates and the current identification feature mechanical arm coordinates to obtain preset centralized coordinates and current centralized coordinates; Constructing a covariance matrix according to the preset centered coordinates and the current centered coordinates; Performing singular value decomposition on the covariance matrix; Calculate the robot arm rotation deviation matrix according to the singular value decomposition result; Converting the robot arm rotation error matrix into the robot arm rotation Euler angle; The offset of the robotic arm is determined according to the average translation deviation of the robotic arm and the Euler angle of rotation of the robotic arm.

[0011] A third aspect of an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a vehicle gluing positioning method provided by the first aspect of an embodiment of the present invention is implemented.

[0012] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, a vehicle glue coating positioning method provided by the first aspect of an embodiment of the present invention is implemented.

[0013] Beneficial effects of the present invention: The present invention determines the current image identification feature coordinates through image recognition using multiple marking identification features on the vehicle body, thereby obtaining the mechanical arm offset between the current position and the preset working position of the mechanical arm. After calculating the mechanical arm offset, the control system will adjust the position of the mechanical arm so that it can accurately align with the current position of the vehicle body. This dynamic adjustment mechanism ensures that the mechanical arm is accurately positioned during gluing, thereby greatly improving the accuracy and consistency of gluing.

[0014] Other identifying features and advantages of the present invention will be described in the subsequent description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0015] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 A schematic flow chart of a vehicle gluing positioning method provided by an embodiment of the present invention; Figure 2 A block diagram of a vehicle gluing positioning device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0018] like Figure 1 As shown, a first aspect of an embodiment of the present invention provides a vehicle gluing positioning method, comprising the following steps: Step 11, when the vehicle body to be glued moves to the gluing station, the current vehicle model and current process are obtained.

[0019] Step 12: Determine the preset identification feature and the corresponding preset identification feature image coordinates according to the current vehicle model and the current process.

[0020] Step 13, obtaining current images of at least three parts of the vehicle body captured by at least three industrial cameras respectively.

[0021] Step 14, identifying each current image of the vehicle body, and determining the current identification feature of each current image of the vehicle body and the corresponding current identification feature image coordinates.

[0022] Step 15, determining whether the current identification feature matches the preset identification feature.

[0023] Step 16: If there is a match, determine whether the current identification feature image coordinates corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature.

[0024] Step 17: If not, determine the robot arm offset according to the current image identification feature coordinates corresponding to multiple different current identification features.

[0025] The present invention determines the current image identification feature coordinates through image recognition using the marking identification features on multiple vehicle bodies, thereby obtaining the robot arm offset between the current position and the preset working position of the robot arm. After calculating the robot arm offset, the control system adjusts the position of the robot arm so that it can accurately align with the current position of the vehicle body to be glued. Each time the vehicle body to be glued is transported to the workstation, the offset is calculated before the glue is applied. This dynamic adjustment mechanism ensures that the robot arm is accurately positioned each time when gluing, thereby greatly improving the accuracy and consistency of gluing.

[0026] A second aspect of an embodiment of the present invention provides a vehicle gluing positioning method, comprising the following steps: Step 21, when the vehicle body to be glued moves to the glue coating station, the current vehicle model and current process are obtained.

[0027] When the car body to be glued is transported to the glue coating station, the PLC control system will obtain the current model information and the current process. The current model can be obtained according to the information set during initialization or according to the model identification of the car body to be glued, which can be obtained by scanning the model identification code on the car body to be glued; the current process can be obtained according to the process information of the previous car body that has been glued. The current process can be the same or different from the process of the previous car body that has been glued.

[0028] Step 22, determining the preset identification feature and the corresponding preset identification feature image coordinates according to the current vehicle model and the current process.

[0029] In this step, after obtaining the current vehicle model and the current process, the corresponding preset identification feature information can be searched in the preset database to obtain the corresponding preset identification feature and preset identification feature image coordinates. Here, the preset identification feature can be one or more. The identification feature can be a hole, but other features such as corners and edges can also be used.

[0030] Step 23, obtain the current images of at least three parts of the vehicle body to be coated with glue, which are respectively captured by at least three industrial cameras. Each industrial camera captures a part of the vehicle body, and each industrial camera captures different parts of the vehicle body. In this embodiment, four industrial cameras are taken as an example to capture the current images of the vehicle body at four different parts. Each current image of the vehicle body includes at least one identification feature. The preset identification feature is obtained by pre-capturing a standard image with an industrial camera for feature extraction. The standard image is an image captured when the vehicle body to be coated with glue is in the standard position under ideal working conditions at the gluing station. The coordinates of the identification feature in the image are the coordinates at the standard position, that is, the preset identification feature image coordinates.

[0031] Step 24, identifying each current image of the vehicle body, and determining the current identification feature of each current image of the vehicle body and the corresponding current identification feature image coordinates.

[0032] In this step, image recognition is performed on the current image of the vehicle body to obtain one or more current identification features and the current identification feature image coordinates corresponding to each current identification feature.

[0033] Step 25, matching the current identification feature with the preset identification feature, and determining whether the current identification feature matches the preset identification feature.

[0034] In this step, a feature matching the current identification feature is searched in the preset identification features, and if a matching preset identification feature is found, the match is successful. If the match is not successful, the industrial camera re-collects the current image of the vehicle body.

[0035] Step 26: If there is a match, determine whether the current identification feature image coordinates corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature.

[0036] In this step, if the match is successful, it is necessary to determine whether the preset identification feature image coordinates of the matched preset identification feature are the same as the current identification feature image coordinates. If they are the same, it means that the current position of the body to be glued is the standard position and the glue spraying operation can be carried out directly. If they are not the same, it means that the current position of the body to be glued has shifted, and it is necessary to continue to calculate the offset so that the robot arm moves to the offset position for glue coating. In this way, the relative position of the robot arm and the body to be glued remains unchanged, and the glue coating position is accurate.

[0037] Here, four industrial cameras capture multiple current images of the vehicle body, so that multiple current identification features can be obtained. Through the collaborative work of multiple cameras, the system can obtain richer and more comprehensive feature information, avoiding the information loss or error that may be caused by a single perspective. Calculating the offset based on the coordinates of multiple current identification features can balance the error and make the calculated offset more accurate.

[0038] Step 27: If they are not the same, determine the robot arm offset according to the current image identification feature coordinates corresponding to multiple different current identification features.

[0039] The specific steps of step 27 include step 271 to step 273: Step 271 , converting a plurality of current image identification feature coordinates into a plurality of current identification feature camera coordinates in a camera coordinate system.

[0040] In this step, the image coordinates ( u , v ) is converted to the camera coordinate system ( XC , Y , Zc ) is: in,( u , v ) is the pixel coordinate in the image coordinate system, ( u 0, v 0) is the principal point of the image (usually the center of the image), fx and fy is the focal length of the camera (in pixels), Zc is the depth of the object in the camera coordinate system (usually obtained by a depth camera or triangulation).

[0041] Substitute each current image identification feature coordinate into the formula to calculate the current identification feature camera coordinate in the camera coordinate system.

[0042] Step 272, converting the multiple current identification feature camera coordinates into multiple current identification feature manipulator coordinates in the manipulator coordinate system.

[0043] In this step, the camera coordinate system ( XC , Y , Zc ) is converted to the six-degree-of-freedom robot arm coordinate system ( Xr , Yr , Zr ) is: in, Tc It is the homogeneous transformation matrix from the camera coordinate system to the robot coordinate system, including the rotation matrix R and translation vectors t : is the rotation matrix, which represents the rotation of the camera coordinate system relative to the robot coordinate system. is the translation vector, which represents the position of the origin of the camera coordinate system in the robot coordinate system.

[0044] Rotation Matrix R and translation vectors t The calculation is usually completed through hand-eye calibration.

[0045] Step 273, determining the robot arm offset according to a plurality of current identification feature preset robot arm coordinates and a plurality of current identification feature robot arm coordinates.

[0046] The specific steps of step 273 include step A1 to step A7: Step A1, determining an average translation deviation of the robot arm according to a plurality of preset robot arm coordinates of current identification features and the robot arm coordinates of current identification features.

[0047] In this step, the current identification feature robot arm coordinates are P i =( x i , y i , z i )( i =1,2,…, n , n ≥3). n is the number of current identification features. The preset robot arm coordinates of multiple current identification features are marked as P i ′=( x i ′, y i ′, z i ′).

[0048] The calculation formula of the average translation deviation of the robot arm is as follows: ) ) ) Average translation deviation of the robot arm .

[0049] Step A2, respectively centering a plurality of current identification feature preset robot arm coordinates and the current identification feature robot arm coordinates to obtain preset centralized coordinates and current centralized coordinates; In this step, the center points of the preset robot arm coordinates of multiple current identification features are calculated. : Calculate the center point of the robot coordinates of multiple current identification features : Center the coordinates to get the preset centralized coordinates , the current central coordinates .

[0050] Step A3: Construct a covariance matrix based on the preset centering coordinates and the current centering coordinates H .

[0051] Step A4: performing singular value decomposition on the covariance matrix.

[0052] Step A5, calculating the robot arm rotation deviation matrix according to the singular value decomposition result.

[0053] Robot arm rotation deviation matrix .

[0054] Step A6, converting the robot arm rotation error matrix into the robot arm rotation Euler angle.

[0055] Step A7, determining the offset of the robot arm according to the average translation deviation of the robot arm and the Euler angle of rotation of the robot arm.

[0056] In this step, the average translation deviation and rotation Euler angle of the robot arm are calculated as the robot arm offset.

[0057] Step 28, sending a motion instruction to the robotic arm according to the robotic arm offset.

[0058] In this step, the current coordinates of the robot arm are calculated based on the preset working coordinates of the robot arm and the offset of the robot arm. The robot arm moves to the current coordinate position of the robot arm according to the current coordinate of the robot arm to start the gluing work.

[0059] In this embodiment, the visual system composed of four industrial cameras will realize 3D orientation recognition of various types of vehicle bodies; it can be expanded without adding hardware for vehicle models of similar size. When the stopping position of the vehicle body is within the transmission error range of ±30 mm, and the vehicle body is stationary without shaking, the positioning accuracy of the visual system is better than ±1 mm; when one of the cameras in the visual system fails, it can be downgraded and shielded to maintain the operation of the three cameras. The effective time occupied by the visual system, that is, from the start of the measurement signal sent by the PLC to the measurement orientation correction vector given by the visual system, the measurement process does not exceed 2000 milliseconds; the measurement success rate of the visual system after optimization and stabilization is above 99.9%.

[0060] Preferably, the industrial camera is also equipped with a light source device to provide fill light for capturing the current image of the vehicle body.

[0061] Furthermore, the vehicle body to be coated with glue is automatically transported on the production line through a skid; when the vehicle body to be coated with glue arrives at the gluing station, the visual system will communicate with the external PCL device, at which time the visual system will be automatically triggered, and the industrial camera and lights will be used to take pictures and identify different parts of the vehicle body at different angles fixedly installed on the vehicle body.

[0062] Furthermore, the visual system and the robotic arm system are equipped with a standard Ethernet card. The visual system controls the light / flip cover through the measurement preparation signal given by the PLC master station. The visual system and the robotic arm system are connected in slave mode, and the communication protocol can be selected in multiple ways. The image processing software used by the visual system has an intuitive and easy-to-operate multi-language user interface. The installation distance of the industrial camera is generally 2.5 to 3.5 meters, and the installation point can be adjusted within a range of 200mm up and down, left and right, and front and back.

[0063] like Figure 2 As shown, the third aspect of the embodiment of the present invention provides a vehicle gluing positioning device, comprising: The first acquisition module 31 is used to acquire the current vehicle model and current process when the vehicle body to be glued moves to the glue coating station; A first determination module 32, for determining a preset identification feature and a corresponding preset identification feature image coordinate according to a current vehicle model and a current process; The second acquisition module 33 is used to acquire the current images of the vehicle body to be coated with glue at least three parts of the vehicle body collected by at least three industrial cameras respectively; A second determination module 34 is used to identify each current image of the vehicle body, determine the current identification feature of each current image of the vehicle body and the corresponding current identification feature image coordinates; A matching module 35 is used to determine whether the current identification feature matches the preset identification feature; A judgment module 36, for judging whether the current identification feature image coordinates corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature if there is a match; The calculation module 37 is used to determine the robot arm offset according to the current image identification feature coordinates corresponding to multiple different current identification features.

[0064] In one embodiment of the present invention, it also includes: a sending module, used to send a motion instruction to the robotic arm according to the offset of the robotic arm.

[0065] In one embodiment of the present invention, determining the robot arm offset according to the current image identification feature coordinates corresponding to a plurality of different current identification features includes: Convert the current image identification feature coordinates to the current identification feature camera coordinates in the camera coordinate system; Convert the current identification feature camera coordinates to the current identification feature manipulator coordinates in the manipulator coordinate system; The robot arm offset is determined according to the preset robot arm coordinates of the current identification feature and the robot arm coordinates of the current identification feature.

[0066] In one embodiment of the present invention, determining the robot arm offset according to the preset robot arm coordinates of the current identification feature and the robot arm coordinates of the current identification feature includes: Determine the average translation deviation of the robot arm according to the preset robot arm coordinates of the multiple current identification features and the robot arm coordinates of the current identification features; Respectively centering a plurality of current identification feature preset robot arm coordinates and a current identification feature robot arm coordinate to obtain preset centralized coordinates and current centralized coordinates; Construct a covariance matrix based on the preset centering coordinates and the current centering coordinates; Perform singular value decomposition on the covariance matrix; Calculate the robot arm rotation deviation matrix based on the singular value decomposition result; Convert the robot arm rotation deviation matrix into the robot arm rotation Euler angle; The offset of the robot arm is determined based on the average translation deviation of the robot arm and the Euler angle of the robot arm rotation.

[0067] A fourth aspect of an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a vehicle gluing positioning method provided in the above embodiment of the present invention is implemented.

[0068] A fifth aspect of an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of a vehicle gluing positioning method provided in the above embodiment of the present invention are implemented.

[0069] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0070] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware systems.

[0071] The method provided in the embodiment of the present invention can be applied to electronic devices. Specifically, the electronic device can be: a desktop computer, a portable computer, an intelligent mobile terminal, a server, etc. This is not limited here, and any electronic device that can implement the present invention belongs to the protection scope of the present invention.

[0072] As for the device / electronic device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0073] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0074] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0076] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A vehicle gluing positioning method, characterized in that: The following steps are involved: When the car body to be glued moves to the gluing station, the current car model and current process are obtained; Determining a preset identification feature and a corresponding preset identification feature image coordinate according to the current vehicle model and the current process; Acquire current images of at least three parts of the vehicle body to be coated with glue, respectively captured by at least three industrial cameras; Identify each of the current images of the vehicle body, and determine the current identification feature of each of the current images of the vehicle body and the corresponding current identification feature image coordinates; Determining whether the current identification feature matches the preset identification feature; If they match, determining whether the current identification feature image coordinates corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature; If not, the robot arm offset is determined according to the current image identification feature coordinates corresponding to a plurality of different current identification features.

2. The method according to claim 1, characterized in that The method further comprises: A motion instruction is sent to the robotic arm according to the robotic arm offset.

3. The method according to claim 2, characterized in that The determining of the robot arm offset according to the current image identification feature coordinates corresponding to the multiple different current identification features includes: Convert the current image identification feature coordinates into the current identification feature camera coordinates in the camera coordinate system; Convert the current identification feature camera coordinates into the current identification feature manipulator arm coordinates in the manipulator arm coordinate system; The mechanical arm offset is determined according to the preset mechanical arm coordinates of the current identification feature and the mechanical arm coordinates of the current identification feature.

4. The method according to claim 3, characterized in that The step of determining the offset of the robot arm according to the preset robot arm coordinates of the current identification feature and the robot arm coordinates of the current identification feature comprises: Determine an average translation deviation of the robot arm according to a plurality of preset robot arm coordinates of the current identification features and the robot arm coordinates of the current identification features; Respectively centering the plurality of current identification feature preset mechanical arm coordinates and the current identification feature mechanical arm coordinates to obtain preset centralized coordinates and current centralized coordinates; Constructing a covariance matrix according to the preset centered coordinates and the current centered coordinates; Performing singular value decomposition on the covariance matrix; Calculate the robot arm rotation deviation matrix according to the singular value decomposition result; Converting the robot arm rotation error matrix into the robot arm rotation Euler angle; The offset of the robotic arm is determined according to the average translation deviation of the robotic arm and the Euler angle of rotation of the robotic arm.

5. A vehicle gluing positioning device, characterized in that: include: The first acquisition module is used to acquire the current vehicle model and current process when the vehicle body to be glued moves to the glue coating station; A first determination module, used to determine a preset identification feature and a corresponding preset identification feature image coordinate according to the current vehicle model and the current process; A second acquisition module is used to acquire current images of the vehicle body to be coated with glue at at least three parts of the vehicle body captured by at least three industrial cameras respectively; A second determination module is used to identify each of the current images of the vehicle body, and determine the current identification feature of each of the current images of the vehicle body and the corresponding current identification feature image coordinates; A matching module, used to determine whether the current identification feature matches the preset identification feature; A judgment module, used for judging whether the image coordinates of the current identification feature corresponding to the current identification feature are the same as the preset identification feature image coordinates of the matched preset identification feature if there is a match; A calculation module is used to determine the robot arm offset according to the current image identification feature coordinates corresponding to multiple different current identification features.

6. The device according to claim 5, characterized in that Also includes: A sending module is used to send a motion instruction to the robotic arm according to the offset of the robotic arm.

7. The device according to claim 6, characterized in that The determining of the robot arm offset according to the current image identification feature coordinates corresponding to the multiple different current identification features includes: Convert the current image identification feature coordinates into the current identification feature camera coordinates in the camera coordinate system; Convert the current identification feature camera coordinates into the current identification feature manipulator arm coordinates in the manipulator arm coordinate system; The mechanical arm offset is determined according to the preset mechanical arm coordinates of the current identification feature and the mechanical arm coordinates of the current identification feature.

8. The device according to claim 7, characterized in that include: The step of determining the offset of the robot arm according to the preset robot arm coordinates of the current identification feature and the robot arm coordinates of the current identification feature comprises: Determine an average translation deviation of the robot arm according to a plurality of preset robot arm coordinates of the current identification features and the robot arm coordinates of the current identification features; Respectively centering the plurality of current identification feature preset mechanical arm coordinates and the current identification feature mechanical arm coordinates to obtain preset centralized coordinates and current centralized coordinates; Constructing a covariance matrix according to the preset centered coordinates and the current centered coordinates; Performing singular value decomposition on the covariance matrix; Calculate the robot arm rotation deviation matrix according to the singular value decomposition result; Converting the robot arm rotation error matrix into the robot arm rotation Euler angle; The offset of the robotic arm is determined according to the average translation deviation of the robotic arm and the Euler angle of rotation of the robotic arm.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the vehicle gluing positioning method as described in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle gluing positioning method according to any one of claims 1 to 4 is implemented.

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