Man-machine cooperation aviation automatic gluing control system and control method thereof

Abstract

The invention provides a man-machine cooperation aviation automatic gluing control system and a control method thereof, and relates to the field of industrial robot automatic control. The robot comprises a lifting platform installed on an AGV trolley, a mechanical arm arranged on the lifting platform, an end effector installed at one end of the mechanical arm and a visual assembly installed beside the end effector. The end effector comprises a single-liquid screw pump, a glue outlet nozzle communicated with the single-liquid screw pump, and a glue scraping piece arranged on one side of the glue outlet nozzle; and the single-liquid screw pump is controlled to change the total glue discharging amount, the glue discharging speed and the back suction speed. An aircraft fuselage curved surface workbench to be subjected to surface machining is erected at a preset position within the range to which the AGV trolley can move; a rectangular-ambulatory-plane opposite seam and / or a linear opposite seam are / is formed on the curved-surface workbench through adhesive tape laying and pasting, and the opposite seams are scanned through the visual assembly. The device can control continuous scanning of opposite seams to acquire data, glue coating and glue scraping, realizes an automatic process, and improves the glue coating quality and flexibility.

Description

Technical Field

[0001] The present invention relates to the field of industrial robot automatic control, and in particular to a human-machine collaborative aviation automatic gluing control system and a control method thereof. Background Art

[0002] Currently, in many assembly industries, particularly aircraft assembly, the large size and weight of aircraft parts often preclude integrated production. Therefore, the manufacturing process typically involves individually fabricating each component and then gradually assembling it. Modern aircraft are typically constructed from multiple components and materials, including aluminum alloys and composite materials. Sealing and gluing techniques are required at the joints between these materials, particularly at the seams, to ensure bond strength and durability. Innovations in materials science and coating technology have led to the development of a wide range of high-performance adhesives and sealants. These materials demonstrate excellent bonding properties, high-temperature resistance, and aging resistance, making their use in high-stress, complex environments feasible. Gluing seams on the exterior of an aircraft fuselage is a critical technical step, taking into account multiple factors, including structural strength, airtightness, corrosion resistance, and weight, and is crucial for ensuring aircraft safety and reliability.

[0003] However, many current automated gluing methods for fuselage exterior seams involve manual tape application; manual or automated gluing; manual scraping; and manual quality inspection. Large fuselages often have long seams with varying shapes, such as straight, U-shaped, and T-shaped, distributed across the curved surface. Manually applying glue with a handheld glue bucket not only makes it difficult to precisely control the amount, speed, and continuity of glue application, making it difficult to guarantee overall gluing quality, but also poses safety concerns when operating at high seams. Summary of the Invention

[0004] Purpose of the invention: To propose a human-machine collaborative aviation automated gluing control system, and further propose a control method for the automated gluing robot, so as to solve the above-mentioned problems existing in the prior art.

[0005] A first aspect of the present invention provides a human-machine collaborative aviation automated gluing control system, comprising: an AGV vehicle, a lifting platform mounted on the AGV vehicle, a robotic arm disposed on the lifting platform, an end effector mounted at one end of the robotic arm, and a vision component mounted adjacent to the end effector;

[0006] The end effector comprises a single-liquid screw pump, a glue outlet nozzle connected to the single-liquid screw pump, and a glue scraper arranged on one side of the glue outlet nozzle; the single-liquid screw pump is controlled to change the total glue output, glue output speed, and back-sucking speed;

[0007] The visual component includes a binocular camera and a line laser sensor; the visual component is used to identify the gluing position on the outer surface of the aircraft fuselage curved surface workbench and correct the operation trajectory in real time;

[0008] The curved surface workbench of the aircraft fuselage to be surface processed is set up at a predetermined position within the range that the AGV can move to;

[0009] The curved workbench is paved with adhesive tape to form U-shaped seams and / or straight seams, and the visual component is used to scan the seams.

[0010] A second aspect of the present invention provides a control method for the above-mentioned human-machine collaborative aviation automated gluing control system, comprising the following steps:

[0011] Calibrate the coordinate system of the end effector;

[0012] Using adhesive tape to form U-shaped seams and / or straight seams on a curved workbench;

[0013] Establish the relative position relationship between the end effector and the curved workbench, obtain the working area, and control the AGV to move to the working area;

[0014] When the AGV arrives at the working area, it controls the robotic arm to move toward the seam and uses the visual component to identify the seam information;

[0015] Calculate the gluing trajectory and gluing mode based on the seam alignment information and the moving speed of the robot arm;

[0016] The robotic arm drives the end effector to complete the gluing;

[0017] After gluing is completed, the tape is torn off manually, and the robotic arm drives the binocular camera to scan and check the gluing quality; if the gluing quality is found to be unqualified at a certain place, the gluing robot position information corresponding to that place is output, and the glue is manually added.

[0018] In a further embodiment of the second aspect, establishing a relative positional relationship between the end effector and the curved worktable specifically includes:

[0019] The cross laser emitted by the line laser sensor is dragged to illuminate the reference hole on the curved worktable. At this time, the binocular camera captures and measures the three-dimensional coordinates of multiple reference rivet heads in the robot arm base coordinate system, and calculates the relative position between the curved worktable coordinate system and the robot arm base coordinate system.

[0020] In a further embodiment of the second aspect, identifying the seam information using a visual component specifically includes:

[0021] Scanning the seam with a line laser sensor to obtain a number of point cloud raw data, wherein the point cloud raw data includes the X coordinate and the Z coordinate of each point;

[0022] Divide all the original point cloud data into 16 groups, each containing 2N points. Record the average value of the x-coordinate and y-coordinate of the first N points as average1x, average1y; record the average value of the x-coordinate and y-coordinate of the last N points as average2x, average2y.

[0023] And calculate the slope for each group:

[0024] ;

[0025] Recursively deduce the slope of each group, compare the slope of each group, and take the maximum slope and minimum value As the mutation points at both ends of the seam at this moment, the coordinates of the two points are recorded at the same time, that is, ( ),( );

[0026] Calculate the coordinates of the middle point of the mutation points at both ends as the target point of the robot tool coordinate system when applying glue , and its coordinate values are as follows:

[0027] ;

[0028] ;

[0029] .

[0030] In a further embodiment of the second aspect, the gluing trajectory and the gluing mode are calculated based on the seam alignment information and the moving speed of the robot arm, specifically including:

[0031] The vector in the Z-axis direction of the relative position of the line laser sensor to the robot arm As the Z-axis direction of the end effector coordinate system;

[0032] Assume that the Z-axis direction of the robot base coordinate system is the Y-axis direction of the end effector coordinate system, that is, = , then the X-axis direction of the end effector coordinate system is = , find the Y-axis vector of the end effector coordinate system ; Combine the three direction vectors into a 3x3 rotation matrix =[ ];

[0033] According to the rotation matrix Calculate the Euler angles Roll, Pitch, and Yaw, which correspond to A, B, and C in Cartesian coordinates respectively;

[0034] Calculate the coordinates of the middle point of the seam in the robot base coordinates:

[0035] ;

[0036] Output the complete pose of the midpoint of the seam in the robot base coordinate system (X,Y,Z,A,B,C);

[0037] Import all the pose information generated after scanning into ROBODK software for simulation. After deleting the points that deviate from the trajectory, determine the NC code for the end-effector coordinate system and save it as an NC file.

[0038] Perform B-spline curve interpolation on the points in the NC file to optimize the gluing trajectory.

[0039] In a further embodiment of the second aspect, the robotic arm drives the end effector to complete the gluing, specifically comprising:

[0040] The host computer reads the NC file and drives the end effector to move along the trajectory. When it moves to the first point, the glue dispensing start command is triggered, and the end effector starts to dispense glue, and the glue nozzle is equipped with a scraper to scrape the glue; when it moves to the last point, the end command is triggered, and the end effector stops dispensing glue.

[0041] In a further embodiment of the second aspect, after the gluing is completed, the tape is manually torn off, and the robotic arm drives the binocular camera to scan and check the gluing quality, specifically including:

[0042] Starting from the first point in each scan, the absolute value of the difference between all adjacent points is recorded in sequence. , calculate the difference between the absolute value of each difference and the gap depth d ;

[0043] When the difference If it exceeds the preset value, the glue coating quality is judged as unqualified.

[0044] According to a third aspect of the present invention, an electronic device is proposed, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus; the memory is used to store a plurality of executable instructions, and the executable instructions enable the processor to execute the control method of the human-machine collaborative aviation automated gluing control system as described in the second aspect of the present invention.

[0045] In a fourth aspect of the present invention, a computer-readable storage medium is proposed, which stores a plurality of executable instructions. When the executable instructions are run on an electronic device, the electronic device executes the control method of the human-machine collaborative aviation automated gluing control system as described in the second aspect.

[0046] Compared with existing technologies, the present invention offers the following advantages: It automates the entire process of gluing, scraping, and quality inspection of fuselage exterior seams. Multiple experiments have demonstrated that the present invention maintains highly consistent glue application and placement during the gluing process, reducing material waste and avoiding potential errors associated with manual operation, thereby improving overall product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a structural diagram of the collaborative robot arm gluing system in an example of the present invention.

[0048] Figure 2 Schematic diagram of the connection between the robot, line laser sensor and end effector in the example of the present invention.

[0049] Figure 3 Schematic diagram of a curved workbench in an example of the present invention.

[0050] Figure 4 This is a schematic diagram of the principle of the line laser sensor scanning the seam in an example of the present invention.

[0051] Figure 5 This is a control relationship flow chart in an example of the present invention.

[0052] Figure 6 Schematic diagram of the gluing process in an example of the present invention.

[0053] The reference numerals in the figure are as follows: host computer 1, robot controller 2, AGV trolley 3, robotic arm 4, curved workbench 5, U-shaped seam 5-1, linear seam 5-2, end effector 6, single-liquid screw pump 6-1, binocular camera 6-2, rubber scraper 6-3, line laser sensor 6-4, rubber barrel 6-5, lifting platform 7. DETAILED DESCRIPTION

[0054] In the following description, numerous specific details are provided to provide a more thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced without one or more of these details. In other instances, certain technical features well known in the art have not been described to avoid confusion with the present invention.

[0055] like Figure 1This example provides a method for applying glue to the seams on the outer surface of a fuselage using a collaborative robot arm 4 carrying a line laser sensor 6-4, which mainly includes a host computer 1, a robot controller 2, an AGV trolley 3, a collaborative robot arm 4, a gluing workbench, a line laser sensor 6-4, an end effector 6, and a lifting platform 7.

[0056] like Figure 2 As shown, the line laser sensor 6-4 is installed on the flange of the collaborative robot arm 4 together with the end effector 6. The end effector 6 includes a single-liquid screw pump 6-1, a rubber scraper 6-3, and a rubber barrel 6-5.

[0057] like Figure 4 As shown, glue is laid on the curved workbench 5 to form a U-shaped seam 5 - 1 and a straight seam 5 - 2 .

[0058] like Figure 3 As shown, the line laser sensor 6-4 is scanning the seam.

[0059] As a technical solution of the present invention, a method for human-machine collaborative aviation automatic gluing is provided, wherein the control relationship and process are shown in FIG. Figure 5 and Figure 6 , the steps are as follows:

[0060] Step S1: Power on the robot, turn on the sensor power, use the teach pendant to operate the robot to scan the ceramic standard ball, process the scan data, calculate the hand-eye matrix according to the integrated calibration algorithm, and complete the hand-eye calibration of the sensor and the robot.

[0061] Step S2: Use the robot's own handheld four-point calibration method to complete the calibration of the end effector 6 relative to the tool coordinate system (TCP) of the robot end.

[0062] Step S3: Lay a thin layer of tape on the curved workbench 5, and then lay double-sided tape on it to create a gap of about 2-3 mm in width to simulate the seam.

[0063] Step S4: Use ROBODK industrial robot offline programming software to import the digital models of the robot, experimental platform, sensor, screw valve and other equipment and establish relative position relationships, perform offline programming simulation on the real experimental scene, and obtain the NC code of the line scan sensor during scanning.

[0064] Step S5: Manually drag the end effector 6, and drag the cross laser emitted by the line laser sensor 6-4 to illuminate the reference hole. At this time, the binocular camera 6-2 shoots and measures the three-dimensional coordinates of multiple reference rivet heads in the base coordinate system of the collaborative robot arm 4, accurately calculates the relative position coordinate system of the product position and the position coordinate system of the gluing collaborative robot arm 4, and automatically updates it in offline programming.

[0065] Step S6: Use offline programming software to perform offline programming simulation on the real experimental scene to obtain the NC code of the line scan sensor during scanning.

[0066] Step S5: Connect the line laser sensor 6-4 to the host computer 1 via a signal line, and use the ScanControlConfiguration Tools software to match the sensor and the host computer 1 for communication. Set sensor initialization parameters such as laser exposure time, contour frequency, and points per contour.

[0067] Step S6: Control the AGV trolley 3 to move to the predetermined processing position, and at the same time control the lifting platform 7 to reach the predetermined working height; store the NC code of the offline programmed robot's posture (XYZABC) in a .txt file, place it in the program project working directory, and use the host computer 1 program to read the posture information in the .txt file to make the industrial collaborative robot arm 4 move continuously to these postures.

[0068] Step S7: Use the host computer 1 program to continuously read the current posture information of the end of the robot during the movement , set the reading cycle to 100ms.

[0069] Step S8: Use the program of the host computer 1 to make the sensor scan the seam to obtain the original data of the point cloud, that is, the x-coordinate and z-coordinate of each point, and make the data collected each time correspond to the current robot posture information after processing for calculation.

[0070] Step S9: Process the raw data, and obtain 1280 points of raw data each time. Start by recording the average of the x and y values of the first 40 points of each point, denoted as average1x and average1y respectively; record the average of the x and y values of the last 40 points of each point, denoted as average2x and average2y respectively, and calculate the slope of the point, and so on until the 600th point:

[0071] .

[0072] Step S10 compares the slopes in turn and takes the maximum slope and minimum value As the mutation points at both ends of the seam at this moment, the coordinates of the two points are recorded at the same time, that is, ( )、( ).

[0073] Step S11: Calculate the coordinates of the middle point of the two breakpoints as the target point of the robot tool coordinate system when applying glue :

[0074] ,

[0075] ,

[0076] .

[0077] Step S12: Convert the Cartesian coordinates of the robot end in step S7 into 4 4 transformation matrix , the hand-eye matrix with the relationship of the sensor to the robot flange Multiply to get the transformation matrix of the sensor relative to the robot Base .

[0078] Step S13: Get the vector in the Z-axis direction of the relative position of the sensor relative to the robot Base As the Z-axis direction of the gluing tool coordinate system, it ensures that the tool is always close to the normal direction of the workpiece surface during gluing.

[0079] Step S14: Assume that the Z-axis direction of the robot base coordinate system is the Y-axis direction of the glue tool coordinate system TCP. = , then the X-axis direction of TCP = , find the Y-axis vector of TCP . The three direction vectors form a TCP 3x3 rotation matrix =[ ].

[0080] Step S15: Calculate the Euler angles Roll, Pitch, and Yaw according to the TCP rotation matrix, which correspond to A, B, and C in the Cartesian coordinates respectively.

[0081] Step S16: Calculate the coordinates of the midpoint of the seam in the robot base coordinates:

[0082] .

[0083] Step S17: Output the complete pose of the seam midpoint in the robot base coordinate system: (X,Y,Z,A,B,C).

[0084] Step S18: Import all the pose information generated after the scan is completed into the ROBODK software for simulation. After deleting the points that deviate from the trajectory, determine the NC code for generating TCP and save it to a .txt file.

[0085] Step S19: Perform B-spline interpolation on the points in the NC code to optimize the gluing trajectory. The main feature of B-spline is that the curve can be changed locally by adjusting the control points. Its mathematical expression is:

[0086]

[0087] Where, ( ) is the basis function of the k-order (k-1) B-spline function, is the control point of the B-spline function, and the weight factor Set it to 1 to make the curve close to the corresponding control point.

[0088]

[0089] Since B-spline curves have the characteristic of local support, There are at most k+1 non-zero basis functions . Therefore, the B-spline curve can also be expressed in the following way:

[0090]

[0091] The l-th order derivative of the k-th order B-spline curve is calculated by the de Boor-Cox recursion formula:

[0092]

[0093] The repetition of the two nodes is set to k+1 so that the curve passes through the starting point and the end point, so only n-1 internal nodes need to be set. The cumulative chord length parameter method is used to normalize it:

[0094]

[0095] in .

[0096] Step S20: The appropriate glue dispensing speed is estimated according to the seam length, width, depth and robot movement speed. The host computer 1 is connected to the single-liquid screw pump 6-1 through the RS485 communication program to set parameters such as glue dispensing amount, glue dispensing speed and back suction speed.

[0097] Step S21: The upper computer 1 reads the NC file and drives the robot end to move along the trajectory. When it moves to the first point, the glue discharging start instruction is triggered, and the end effector 6 starts to dissipate glue. The glue nozzle is equipped with a scraper 6-3 for scraping glue; when it moves to the last point, the end instruction is triggered, and the end effector 6 stops discharging glue.

[0098] Step S22: tear off the surface layer of the tape and manually observe whether the glue coating effect has obvious glue breakage or glue overflow.

[0099] Step S23: The robot carries the sensor end to scan the seam again, that is, runs the NC code in step 6 to detect the gluing quality.

[0100] Step S24: Detect the seam during the scanning process, starting from the first point in each scanning profile, that is, its Z coordinate is Compare with the next point The absolute value of the difference , and so on to record the difference of all adjacent points , calculate the absolute value of the difference between each value and the gap depth d Assuming the depth of the seam is 3.5mm, the following possibilities may occur:

[0101]

[0102] Among them, when When the glue coating quality is judged as unqualified, the possible situations are: glue breakage, glue leakage, glue overflow, and the specific situation can be further judged.

[0103] Step S25: Detect the seam during scanning, calculate the X coordinates of the points at the two edges of the gap after gluing, and obtain the width of the seam. ,Assuming the width of the seam is 3mm, the following possibilities will occur.

[0104]

[0105] When the glue coating quality is unqualified, the robot outputs the current posture information and saves the record for easy subsequent retrieval of the location. If glue breakage or leakage occurs, manual glue filling is required; if glue overflow occurs, manual glue scraping is required.

[0106] The control method disclosed in the above embodiment can be embedded in a field system for use by being written as executable code. The executable code runs in the field system in the form of software, and the software can be written to a computer-readable storage medium. More specific examples of the computer-readable storage medium in this embodiment may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0107] Computer-readable storage media may include a data signal transmitted in baseband or as part of a carrier wave, which carries readable program code. Such a transmitted data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0108] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as limiting the present invention itself. Various changes may be made to it in form and detail without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A human-machine collaborative aviation automated gluing control system, characterized in that: include: An AGV vehicle, a lifting platform mounted on the AGV vehicle, a robotic arm disposed on the lifting platform, an end effector mounted at one end of the robotic arm, and a vision component mounted next to the end effector; The end effector comprises a single-liquid screw pump, a glue outlet nozzle connected to the single-liquid screw pump, and a glue scraper arranged on one side of the glue outlet nozzle; the single-liquid screw pump is controlled to change the total glue output, glue output speed, and back-sucking speed; The visual component includes a binocular camera and a line laser sensor; the visual component is used to identify the gluing position on the outer surface of the aircraft fuselage curved surface workbench and correct the operation trajectory in real time; The curved surface workbench of the aircraft fuselage to be surface processed is set up at a predetermined position within the range that the AGV can move to; The curved workbench is paved with adhesive tape to form U-shaped seams and / or straight seams, and the visual component is used to scan the seams.

2. The control method of the human-machine collaborative aviation automatic gluing control system according to claim 1, characterized in that: The steps include: Calibrate the coordinate system of the end effector; Using adhesive tape to form U-shaped seams and / or straight seams on a curved workbench; Establish the relative position relationship between the end effector and the curved workbench, obtain the working area, and control the AGV to move to the working area; When the AGV arrives at the working area, it controls the robotic arm to move toward the seam and uses the visual component to identify the seam information; Calculate the gluing trajectory and gluing mode based on the seam alignment information and the moving speed of the robot arm; The robotic arm drives the end effector to complete the gluing; After gluing is completed, the tape is torn off manually, and the robotic arm drives the binocular camera to scan and check the gluing quality; if the gluing quality is found to be unqualified at a certain place, the gluing robot position information corresponding to this place is output, and manual glue is added.

3. The control method of the human-machine collaborative aviation automated gluing control system according to claim 2, characterized in that: Establish the relative position relationship between the end effector and the curved worktable, including: The cross laser emitted by the line laser sensor is dragged to illuminate the reference hole on the curved workbench. At this time, the binocular camera captures and measures the three-dimensional coordinates of multiple reference rivet heads in the robot arm base coordinate system, and calculates the relative position between the curved workbench coordinate system and the robot arm base coordinate system.

4. The control method of the human-machine collaborative aviation automated gluing control system according to claim 2, characterized in that: Use visual components to identify seam information, including: Scanning the seam with a line laser sensor to obtain a number of point cloud raw data, wherein the point cloud raw data includes the X coordinate and the Z coordinate of each point; Divide all the original point cloud data into 16 groups, each containing 2N points. Record the average value of the x-coordinate and y-coordinate of the first N points as average1x, average1y; record the average value of the x-coordinate and y-coordinate of the last N points as average2x, average2y. And calculate the slope for each group: ； Recursively deduce the slope of each group, compare the slope of each group, and take the maximum slope and minimum value As the mutation points at both ends of the seam, the coordinates of the two points are recorded at the same time, that is, ( ), ( ); Calculate the coordinates of the middle point of the mutation points at both ends as the target point of the robot tool coordinate system when applying glue , and its coordinate values are as follows: ； ； 。 5. The control method of the human-machine collaborative aviation automated gluing control system according to claim 2, characterized in that: According to the seam alignment information and the moving speed of the robot arm, the gluing trajectory and gluing mode are calculated, specifically including: The vector in the Z-axis direction of the relative position of the line laser sensor to the robot arm As the Z-axis direction of the end effector coordinate system; Assume that the Z-axis direction of the robot base coordinate system is the Y-axis direction of the end effector coordinate system, that is, = , then the X-axis direction of the end effector coordinate system is = , find the Y-axis vector of the end effector coordinate system ; Combine the three direction vectors into a 3x3 rotation matrix =[ ]; According to the rotation matrix Calculate the Euler angles Roll, Pitch, and Yaw, which correspond to A, B, and C in Cartesian coordinates respectively; Calculate the coordinates of the middle point of the seam in the robot base coordinates: ； Output the complete pose of the midpoint of the seam in the robot base coordinate system (X,Y,Z,A,B,C); Import all the pose information generated after scanning into ROBODK software for simulation. After deleting the points that deviate from the trajectory, determine the NC code for the end-effector coordinate system and save it as an NC file. Perform B-spline curve interpolation on the points in the NC file to optimize the gluing trajectory.

6. The control method of the human-machine collaborative aviation automatic gluing control system according to claim 5, characterized in that: The robotic arm drives the end effector to complete the gluing process, which includes: The host computer reads the NC file and drives the end effector to move along the trajectory. When it moves to the first point, the glue dispensing start command is triggered, and the end effector starts to dispense glue, and the glue nozzle is equipped with a scraper to scrape the glue; when it moves to the last point, the end command is triggered, and the end effector stops dispensing glue.

7. The control method of the human-machine collaborative aviation automated gluing control system according to claim 2, characterized in that: After the glue is applied, the tape is removed manually, and the robotic arm drives the binocular camera to scan and check the glue quality, including: Starting from the first point in each scan, the absolute value of the difference between all adjacent points is recorded in sequence. , calculate the difference between the absolute value of each difference and the gap depth d ; When the difference If it exceeds the preset value, the glue coating quality is judged as unqualified.

8. An electronic device, characterized in that: include: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store a plurality of executable instructions, and the executable instructions enable the processor to execute the control method of the human-machine collaborative aviation automatic gluing control system according to any one of claims 2 to 7.

9. A computer-readable storage medium, characterized in that The storage medium stores a plurality of executable instructions. When the executable instructions are executed on the electronic device, the electronic device executes the control method of the human-machine collaborative aviation automatic gluing control system according to any one of claims 2 to 7.

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