A robot glue-containing edge sewing process parameter self-adaptive solving method

Abstract

The present application relates to a kind of robot rubberized edge process parameter self-adaptive solution method, comprising: determining the pose of rubberized edge robot end in base coordinate system;According to the modeling of improved D-H parameter to rubberized edge robot, the pose of rubberized edge robot end in base coordinate is verified in working space;Solving the joint angle group of rubberized edge robot, and selecting optimal joint angle of rubberized edge;Developing robot rubberized edge process parameter self-adaptive software tool, and the simulation verification of optimal joint angle information of rubberized edge is carried out.The present application will tire membrane curved surface curve equation, rubberized edge parameter as input, by determining rubberized edge target point Frenet frame, pose transformation, joint angle solving and selection, finally output optimal joint angle information of rubberized edge and carry out rubberized edge process simulation, realizes the quick and accurate response to the change of rubberized edge parameter, solves the defect that traditional robot demonstration is long in time, cannot adapt to the change of rubberized edge parameter.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of digital design and manufacturing of automobile body, and particularly relates to a robot-contained glue rolling process parameter self-adaptive solving method. BACKGROUND

[0002] The automobile body door cover part is an extremely important outer cover part which determines the appearance of the automobile body. After assembly, it not only needs to ensure the uniform assembly gap with the surrounding parts, but also needs to have a certain degree of aesthetics. The processing and manufacturing of the automobile body door cover part usually needs to fold the edges of the inner and outer plates with high precision forming, apply glue, press and solidify and the like. The size precision of the press forming is an important embodiment of the automobile body manufacturing process level.

[0003] The edge covering machine edge covering as a traditional press forming method of the automobile body door cover part has defects such as complex equipment, high cost and difficult operation. Since the shape of the edge covering machine mold is fixed, only a specific automobile body door cover part of a certain vehicle model can be press formed by one edge covering machine, which is difficult to adapt to the objective requirements of the rapid update of vehicle models and the limited investment of equipment in automobile manufacturing. The robot edge rolling process is to install a roller at the end of an industrial robot, to make the roller move according to a specific trajectory and pose by controlling the change of the joint angle of the robot, so as to realize the accurate edge rolling forming of the automobile body door cover part.

[0004] In order to meet the requirements of automobile lightweight, the inner plate of the automobile body door cover part is made of steel to ensure the strength and stiffness, and the outer plate is made of aluminum alloy to reduce the weight of the automobile body. During the edge rolling process, the edge folding glue is applied between the inner and outer plates, which can not only enhance the connection strength of the inner and outer plates, but also avoid the electrochemical corrosion between the heterogeneous metal materials. However, since the edge folding glue is a non-Newtonian fluid, it will produce a stick pressure effect during the edge rolling forming process. Therefore, for different types of edge folding glue, corresponding edge rolling parameters need to be adapted to ensure the forming quality of the edge rolling of the automobile body door cover part. The inner and outer plate materials of the automobile body door cover part of different vehicle manufacturers and different vehicle models are different, and the adapted edge folding glue components are also different, which leads to the difference of the edge rolling parameters among different vehicle models. In addition, factors such as the shape of the automobile body door cover part, the edge rolling pass and the edge rolling flange type will also affect the edge rolling parameters.

[0005] The traditional robot edge rolling is to obtain the edge rolling trajectory and pose of the automobile body door cover part by manual teaching. In order to meet the accuracy requirements of the edge rolling, a large amount of time is needed for manual teaching. When the process parameters such as the tire film geometry and the edge rolling parameters change, the teaching work needs to be repeated. Therefore, a solving method is needed, which can respond to the changes of the process parameters in time, accurately and quickly obtain the joint angle information required by the edge rolling robot, solve the optimal joint angle adapted to the changes of the process parameters, simulate the edge rolling process, and detect the collision and interference, so as to guide the robot to roll the automobile body door cover part and ensure the edge rolling forming quality and improve the processing efficiency. SUMMARY

[0006] The present application aims at overcoming the defects of the prior art and provides a robot glue-containing hemming process parameter adaptive solving method, which can respond to changes in hemming parameters caused by changes in hemming glue types and changes in tire membrane geometry in a timely manner and solve a set of optimal joint angles for hemming to guide a hemming robot to complete the glue-containing hemming process, while developing an adaptive solving software tool to simulate the hemming process.

[0007] The object of the present application can be achieved by the following technical solutions:

[0008] A robot glue-containing hemming process parameter adaptive solving method is used to guide a hemming robot to complete the glue-containing hemming work in the case of frequent changes in hemming process parameters, quickly respond to changes in hemming process parameters, output optimal joint angle information for hemming, and perform simulation verification, and the method comprises the following steps:

[0009] S1, determining the pose of the hemming robot end in the base coordinate system;

[0010] S2, modeling the hemming robot according to the improved D-H parameters, and verifying the pose of the hemming robot end in the base coordinate system in the working space;

[0011] S3, solving the joint angle set of the hemming robot, selecting the optimal joint angle for hemming, and outputting the optimal joint angle information for hemming.

[0012] Further, in step S1, the hemming target point pose is taken as the target coordinate system, the robot target point pose is taken as the tool coordinate system, the robot end pose is taken as the wrist coordinate system, the coordinate system referenced by the tire membrane curved surface curve equation is taken as the workbench coordinate system, and the robot base is taken as the base coordinate system.

[0013] Further, step S1 is specifically: obtaining the pose of the hemming target point in the workbench coordinate system according to the curved surface curve characteristics of the tire membrane, and obtaining the pose of the glue-containing hemming robot end in the base coordinate system through the homogeneous transformation matrices of the wrist coordinate system to the tool coordinate system, the tool coordinate system to the target coordinate system, the target coordinate system to the workbench coordinate system, and the workbench coordinate system to the base coordinate system.

[0014] Step S1 comprises the following sub-steps:

[0015] S11, determine the membrane surface differential equation S(u, v), the tangent vector of the membrane edge line and the normal vector of the membrane surface at the membrane edge line, since the membrane surface is attached to the surface of the vehicle door cover, the membrane surface differential equation S(u, v) is consistent with the vehicle door cover surface differential equation, the vehicle door cover edge line is projected along the normal vector of the corresponding membrane surface to the membrane surface, and the membrane edge line C(u(t), v(t)) is obtained;

[0016] S12, based on step S11, establish the Frenet frame of the membrane edge line, that is, the rolling edge target point pose and the target coordinate system, which has:

[0017]

[0018] β(t)=γ(t)×α(t)

[0019]

[0020] In the formula, α(t) represents the tangent vector of the membrane edge line, γ(t) represents the normal vector of the membrane surface at the membrane edge line, β(t) vector and α(t), γ(t) constitute a right-hand Cartesian coordinate system, and S(u, v) is the membrane surface differential equation;

[0021] S13, determine the homogeneous transformation matrix of the wrist coordinate system to the tool coordinate system the homogeneous transformation matrix of the tool coordinate system to the target coordinate system the homogeneous transformation matrix of the target coordinate system to the workbench coordinate system and the homogeneous transformation matrix of the workbench coordinate system to the base coordinate system get the pose of the edge rolling robot end in the base coordinate system, that is, the homogeneous transformation matrix of the wrist coordinate system in the base coordinate system, which has:

[0022]

[0023] Further, according to the rolling edge parameters and the rolling wheel size, the homogeneous transformation matrix of the target coordinate system to the base coordinate system is obtained as:

[0024]

[0025] The homogeneous transformation matrix of the target coordinate system to the base coordinate system is determined by the membrane surface, the rolling wheel size and the rolling edge parameters. When the membrane surface, the rolling wheel size and the rolling edge parameters change, the homogeneous transformation matrix of the target coordinate system to the base coordinate system will change accordingly, so that the rapid response to the rolling edge parameters and other information can be realized.

[0026] Further, step S2 includes the following substeps:

[0027] S21, according to the size of the edge rolling robot link and the relative position between each link and joint, the improved D-H parameters of the edge rolling robot are obtained, and the homogeneous transformation matrix between adjacent joints of the robot is established;

[0028] S22, a plurality of random joint angles are created within the joint angle range of the edge rolling robot, and an envelope space composed of the end point of the edge rolling robot is obtained, which is the working space of the edge rolling robot;

[0029] S23, it is judged whether the obtained end position and posture of the edge rolling robot is in the working space of the edge rolling robot, if it is in the working space, the subsequent step is carried out, if it is not in the working space, the edge rolling parameters are corrected and the above steps are repeated.

[0030] Further, in step S21, the improved D-H parameters without containing the information of the rolling wheel are used to model the edge rolling robot, so that the change of the rolling wheel has no influence on the D-H parameter model of the edge rolling robot, thereby improving the stability of the robot glue rolling process parameter self-adaptive solving method.

[0031] Further, step S3 includes the following substeps:

[0032] S31, since the axes of joints 4, 5 and 6 of the edge rolling robot intersect at a point, the position of the end of the edge rolling robot only depends on joints 1, 2 and 3, according to the Pieper principle, the inverse kinematics problem of the six degrees of freedom of the edge rolling robot is simplified to the inverse kinematics problem of three links, and the joint angles of joints 1, 2 and 3 are solved, and the joint angles of joints 4, 5 and 6 are solved by inverse matrix method; there is:

[0033]

[0034] represents the position matrix of the 6th joint of the robot in the base coordinate system (0th joint of the robot), represents the position matrix of the 4th joint of the robot in the base coordinate system, represents the homogeneous transformation matrix of the 1st joint of the robot to the base coordinate system, represents the homogeneous transformation matrix of the 2nd joint to the 1st joint, represents the homogeneous transformation matrix of the 3rd joint to the 2nd joint, represents the homogeneous transformation matrix of the 4th joint to the 3rd coordinate system, represents the homogeneous transformation matrix of the 5th joint to the 4th coordinate system, represents the homogeneous transformation matrix of the 6th joint to the 5th coordinate system.

[0035] S32, solve joint angles θ1, θ2, θ3, θ4, θ5, θ6, obtain eight sets of joint angle solutions of the rolling machine, select one set of optimal joint angles of rolling from the eight sets of joint angle solutions.

[0036] Further, in step S32, to ensure the stability of the rolling robot during the rolling process, the joint angles should be selected to have the minimum change of the joint angles of adjacent target points. Since joints 1, 2 and 3 have a greater impact on the position of the robot arm, the solutions that do not meet the joint angle limit of the rolling robot should be removed from the eight sets of joint angle solutions. Then, the set of joint angles with the minimum Euclidean distance of joints 1, 2 and 3 should be selected. If the Euclidean distances of joints 1, 2 and 3 are the same, the Euclidean distances of joints 4, 5 and 6 should be compared and the joint angle solution with the smaller Euclidean distance should be selected as the optimal joint angle of rolling.

[0037] Further, the method further comprises step S4: developing a robot glue-containing rolling process parameter adaptive software tool to simulate and verify the rolling optimal joint angle information.

[0038] Step S4 comprises the following sub-steps:

[0039] S40, develop a robot glue-containing rolling process parameter adaptive solution method interface to facilitate the input of various parameters and intuitively display the results obtained in steps S1, S2 and S3. In this process, Matlab is used to implement the codes of steps S1, S2 and S3, and the Appdesigner interface development tool in Matlab is used to develop the software tool.

[0040] S41, establish a three-dimensional model of the robot rolling, which comprises a robot model, a tire membrane model and a roller model, and assemble them according to the coordinate system information involved in steps S1, S2 and S3, and finally import them into the robot simulation software V-rep.

[0041] S42, use SOCKET communication to establish data exchange between Matlab and V-rep, transmit the rolling optimal joint angle information obtained by Matlab to V-rep, and perform robot rolling simulation in V-rep and check for collision and interference.

[0042] Further, according to the relative position information between the tire membrane and the rolling robot, the rolling robot and the tire membrane model are established in the three-dimensional drawing software and imported into V-rep. The joint rotation axes of the rolling robot are established in V-rep, and the rotation angles of the joint rotation axes of the rolling robot are guided according to the rolling optimal joint angle information received from Matlab, so as to realize the simulation of the rolling process.

[0043] Compared with the prior art, the present application has the following beneficial effects:

[0044] The present application takes the membrane camber curve equation and the rolling edge parameter as the input quantity, determines the rolling edge target point Frenet frame, pose transformation, joint angle solving and selection, finally outputs the rolling edge optimal joint angle information and performs the rolling edge process simulation, realizes the quick and accurate response to the rolling edge parameter change, solves the defects that the traditional robot teaching is time-consuming and cannot adapt to the rolling edge parameter change, guides the robot to perform the rolling edge on the vehicle body door cover piece, guarantees the rolling edge forming quality and improves the processing efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 Technical steps of the robot glue-containing rolling edge process parameter self-adaptive solving method;

[0046] Figure 2 Coordinate system transformation schematic diagram;

[0047] Figure 3 Projection method for establishing membrane camber curve schematic diagram;

[0048] Figure 4 Rolling edge target point pose schematic diagram;

[0049] Figure 5 Rolling edge robot joint coordinate system schematic diagram;

[0050] Figure 6 Rolling edge optimal joint angle selection algorithm schematic diagram;

[0051] The drawings show that: 0-target coordinate system; 1-tool coordinate system; 2-wrist coordinate system; 3-tool table coordinate system; 4-base coordinate system; 5-membrane edge line; 6-membrane; 7-vehicle body door cover piece outer plate; 8-rolling edge target point pose; 9-roller; 10-rolling edge robot 2nd joint; 11-rolling edge robot 6th joint; 12-rolling edge robot 5th joint; 13-rolling edge robot 4th joint; 14-rolling edge robot 3rd joint; 15-rolling edge robot 1st joint. DETAILED DESCRIPTION

[0052] The present application will be described in detail below in combination with the drawings and specific embodiments. The present embodiment is implemented on the premise of the technical scheme of the present application, and detailed implementation modes and specific operation processes are given, but the protection scope of the present application is not limited to the following embodiments.

[0053] Term explanation

[0054] Base coordinate system {B}: world coordinate system;

[0055] Target coordinate system {G}: pose of rolling edge target point;

[0056] Workbench coordinate system {S}: coordinate system used to establish the differential equation of the tire membrane surface and the tire membrane edge line;

[0057] Tool coordinate system {T}: pose of the robot target point;

[0058] Wrist coordinate system {W}: pose of the end of the rolling machine robot;

[0059] Press-in angle: angle formed by the normal of the rolling target point and the roller axis;

[0060] TCP-RTP value: vertical distance from the rolling target point to the roller axis;

[0061] Joint angle group: 8 groups of joint angle solutions of the rolling machine robot obtained according to the pose of the rolling target point;

[0062] Optimal joint angle of rolling: joint angle solution that makes the rolling machine robot over-smooth between adjacent rolling target points.

[0063] As shown in the following table, the steps for implementing the method for adaptively solving the process parameters of the robot glue-containing rolling process in the present application include the following steps: Figure 1

[0064] (1) Determine the pose of the end of the rolling machine robot in the base coordinate system {B};

[0065] (2) Model the rolling machine robot according to the improved D-H parameters, and verify the pose of the end of the rolling machine robot in the base coordinate system;

[0066] (3) Solve the joint angle group of the rolling machine robot, select the optimal joint angle of rolling, and output the optimal joint angle information of rolling;

[0067] (4) Develop a software tool for adaptively solving the process parameters of the robot glue-containing rolling process, and simulate and verify the output optimal joint angle information of rolling.

[0068] In the following examples, the parameters without units are in the International System of Units.

[0069] In the present embodiment, step (1) is specifically: obtaining the pose of the rolling target point in the workbench coordinate system {S} according to the curved surface curve characteristics of the tire membrane, and obtaining the pose of the end of the rolling machine robot in the base coordinate system {B} through the homogeneous transformation matrices from the wrist coordinate system {W} to the tool coordinate system {T}, from the tool coordinate system {T} to the target coordinate system {G}, from the target coordinate system {G} to the workbench coordinate system {S}, and from the workbench target system {S} to the base coordinate system {B}.

[0070] As shown in the following table, the steps for implementing the method for adaptively solving the process parameters of the robot glue-containing rolling process in the present application include the following steps: Figure 2 ​As shown, the relative positions of the base coordinate system {B}, the wrist coordinate system {W}, the tool coordinate system {T}, the target coordinate system {G} and the worktable coordinate system {S} are marked.

[0071] In the embodiment, the step (1) comprises the following sub-steps:

[0072] (11) Determine the differential equation S(u, v) of the membrane surface differential equation and the differential equation of the membrane edge line; as Figure 3 As shown, the membrane surface is attached to the outer plate surface of the body door cover part, the membrane edge line is obtained by projecting the edge line of the outer plate surface of the body door cover part along the normal vector of the membrane surface to the membrane surface, and thus

[0073]

[0074] (12) Establish the Frenet frame of the membrane edge line: that is, α(t) represents the tangent vector of the membrane edge line, γ(t) represents the normal vector of the membrane surface at the membrane edge line, and β(t) vector forms a right-hand Cartesian coordinate system with α(t) and γ(t), and thus

[0075]

[0076] As shown, it is a schematic diagram of the pose of the rolling edge target point of the embodiment; Figure 4

[0077] (13) Determine the homogeneous transformation matrix of the wrist coordinate system to the tool coordinate system The homogeneous transformation matrix of the tool coordinate system to the target coordinate system The homogeneous transformation matrix of the target coordinate system to the worktable coordinate system And the homogeneous transformation matrix of the worktable coordinate system to the base coordinate system The pose of the rolling edge robot end in the base coordinate system is obtained, that is, the homogeneous transformation matrix of the wrist coordinate system in the base coordinate system, and thus

[0078]

[0079] According to the rolling edge parameters and the rolling wheel size, the homogeneous transformation matrix of the target coordinate system to the base coordinate system is obtained as

[0080]

[0081] The homogeneous transformation matrix of the target coordinate system to the base coordinate system is determined by the membrane surface, the rolling wheel size and the rolling edge parameters. When the membrane surface, the rolling wheel size and the rolling edge parameters change, the homogeneous transformation matrix of the target coordinate system to the base coordinate system will change accordingly, so that the quick response to the rolling edge parameters and other information can be realized.

[0082] ​Wherein the overlock parameters include the roller radius R = 0.03, the pressure angle θ = π / 4, the roller rod length L = 0.2 and the TCP-RTP value l = 0.001;

[0083] In the embodiment, the step (2) comprises the following sub-steps:

[0084] (21) According to Figure 5 The size of the overlock robot connecting rod and the relative position between each connecting rod and joint are shown in the figure, and the improved D-H parameters of the overlock robot are obtained, and then the homogeneous transformation matrix between adjacent joints of the robot is established;

[0085] As shown in the figure, it is a schematic diagram of the joint coordinate system of the overlock robot in the embodiment, wherein the improved D-H parameters of the overlock robot include: connecting rod length a1 = 0.5, a2 = 1.3, a3 = -0.055, connecting rod rotation angle α1 = -π / 2, α3 = -π / 2, α4 = π / 2, α5 = -π / 2, connecting rod offset d4 = 1.025 and joint angle θ; Figure 5 (22) 10000 random joint angles are created within the joint angle range of the overlock robot, and the working space of the overlock robot is obtained by substituting the overlock robot model;

[0086] (23) It is judged whether the end pose of the overlock robot satisfies the working space limitation of the overlock robot, if yes, the subsequent steps are executed, if not, the overlock parameters need to be corrected and the above steps are repeated.

[0087] In the embodiment, the step (3) comprises the following sub-steps:

[0088] (31) The axes of the 4th, 5th and 6th joints of the overlock robot intersect at a point, which indicates that the position of the end point of the robot is determined only by the 1st, 2nd and 3rd joints, so the solution of the joint angles of the overlock robot is simplified to a three-link joint angle solution problem according to the Pieper principle, so we have:

[0089]

[0090]

[0091] represents the position matrix of the 6th joint of the robot in the base coordinate system (the 0th joint of the robot), represents the position matrix of the 4th joint of the robot in the base coordinate system, represents the homogeneous transformation matrix of the 1st joint of the robot to the base coordinate system, represents the homogeneous transformation matrix of the 2nd joint to the 1st joint, represents the homogeneous transformation matrix of the 3rd joint to the 2nd joint, represents the homogeneous transformation matrix of the 4th joint to the 3rd coordinate system, represents the homogeneous transformation matrix of the 4th joint to the 3rd coordinate system, a homogeneous transformation matrix representing the 5th joint of the robot to the 4th coordinate system, a homogeneous transformation matrix representing the 6th joint of the robot to the 5th coordinate system.

[0092] (32) Solve the joint angles θ1, θ2, θ3, θ4, θ5, θ6 to obtain eight sets of rolling edge robot joint angle solutions, and select one set of rolling edge optimal joint angles from the eight sets of joint angle solutions;

[0093] As shown in Figure 6 To meet the requirement of smooth transition of the rolling edge robot between adjacent two rolling edge joint angles, among the eight sets of joint angle solutions, the solutions that do not meet the joint angle limit of the rolling edge robot need to be eliminated first, and then since the 1st, 2nd and 3rd joints of the rolling edge robot have a greater impact on the position of the robot arm end, the joint angle solution with the minimum Euclidean distance of the adjacent two rolling edge target points θ1, θ2, θ3 should be selected, if the Euclidean distances of the adjacent two rolling edge target points θ1, θ2, θ3 are equal, the Euclidean distances of θ4, θ5, θ6 need to be compared, and the joint angle solution with the smaller Euclidean distance is selected as the rolling edge optimal joint angle.

[0094] In the embodiment, the step (4) comprises the following sub-steps:

[0095] (40) Use the code implementation of steps (1), (2), (3) in Matlab, and develop the rolling edge robot parameter adaptive system using the Appdesigner interface development tool in Matlab;

[0096] (41) Establish a three-dimensional model of the robot rolling edge, including a robot model, a tire membrane model and a rolling wheel model, and assemble them according to the coordinate system information involved in steps (1), (2), (3), and finally import them into the robot simulation software V-rep;

[0097] (42) In the adaptive solving software tool, input the tire membrane surface curve equation and the rolling edge parameters, complete the calculation of the rolling edge optimal joint angle, and perform simulation;

[0098] The preferred embodiments of the application are described in detail above. It should be understood that those skilled in the art can make many modifications and changes without creative labor based on the concept of the present application. Therefore, any technical solution obtained by logical analysis, reasoning or limited experiment based on the prior art according to the concept of the present application shall be within the protection scope defined by the claims.

Claims

1. A robot glue-in rolling process parameter self-adaptive solving method, characterized in that, The method comprises the following steps: S1, determining the pose of the end of the edge rolling robot in the base coordinate system; S2, modeling the edge rolling robot according to the improved D-H parameters, and verifying the pose of the end of the edge rolling robot in the base coordinate system; S3, solving the joint angle group of the edge rolling robot, and selecting the optimal joint angle of edge rolling to output the optimal joint angle information of edge rolling; Step S2 comprises the following sub-steps: S21, obtaining the improved D-H parameters of the edge rolling robot according to the size of the connecting rod of the edge rolling robot and the relative position between each connecting rod and the joint, and establishing the homogeneous transformation matrix between adjacent joints of the robot; S22, creating a plurality of random joint angles in the joint angle range of the edge rolling robot to obtain an envelope space formed by the end point of the edge rolling robot, which is the working space of the edge rolling robot; S23, judging whether the obtained end pose of the edge rolling robot is in the working space of the edge rolling robot, if yes, the subsequent steps are performed, if not, the edge rolling parameters are corrected and the above steps are repeated; In step S21, the improved D-H parameters without roller information are used to model the edge rolling robot; Step S3 comprises the following sub-steps: S31, the axes of joints 4, 5 and 6 of the edge rolling robot intersect at a point, according to the Pieper principle, the inverse kinematics problem of the six-degree-of-freedom edge rolling robot is simplified to the inverse kinematics problem of a three-link mechanism, and the joint angles of joints 1, 2 and 3 are solved, and the joint angles of joints 4, 5 and 6 are solved by inverse matrix; S32, solving joint angles θ1, θ2, θ3, θ4, θ5 and θ6 to obtain eight groups of joint angle solutions of the edge rolling robot, selecting one group of optimal joint angles of edge rolling from the eight groups of joint angle solutions.

2. The method of claim 1, wherein, In step S1, the edge rolling target point pose is taken as the target coordinate system, the robot target point pose is taken as the tool coordinate system, the robot end pose is taken as the wrist coordinate system, the coordinate system referenced by the tire membrane curved surface curve equation is taken as the workbench coordinate system, and the robot base is taken as the base coordinate system.

3. The method of claim 2, wherein the method further comprises: Step S1 comprises the following sub-steps: S11, determining the tire membrane curved surface differential equation, the tangent vector of the tire membrane edge line and the normal vector of the tire membrane curved surface at the tire membrane edge line, projecting the vehicle body door cover edge line along the normal vector of the corresponding tire membrane curved surface to the tire membrane curved surface to obtain the tire membrane edge line C(u(t), v(t)); S12, based on step S11, establishing the Frenet frame of the tire membrane edge line, which has: β(t)=γ(t)×α(t) In the formula, α(t) represents the tangent vector of the tire membrane edge line, γ(t) represents the normal vector of the tire membrane curved surface at the tire membrane edge line, β(t) vector and α(t), γ(t) form a right-hand Cartesian coordinate system, and S(u, v) is the tire membrane curved surface differential equation; S13, determine the homogeneous transformation matrix of the wrist coordinate system to the tool coordinate system the homogeneous transformation matrix of the tool coordinate system to the target coordinate system the homogeneous transformation matrix of the target coordinate system to the worktable coordinate system and the homogeneous transformation matrix of the worktable coordinate system to the base coordinate system get the pose of the edge rolling robot end in the base coordinate system, that is, the homogeneous transformation matrix of the wrist coordinate system in the base coordinate system, that is 4. The method of claim 3, wherein, The homogeneous transformation matrix from the target coordinate system to the base coordinate system is: The homogeneous transformation matrix of the target coordinate system to the base coordinate system is determined by the tire membrane surface, the roller size and the rolling edge parameters. When the tire membrane surface, the roller size and the rolling edge parameters change, the homogeneous transformation matrix of the target coordinate system to the base coordinate system will change accordingly.

5. The method of claim 1, wherein, In step S32, among the eight sets of joint angle solutions, first, solutions that do not satisfy the joint angle limit of the rolling edge robot are eliminated; second, the set of joint angles with the minimum Euclidean distance of adjacent rolling edge target points 1, 2 and 3 is selected, if the Euclidean distances of joint angles 1, 2 and 3 are the same, the Euclidean distances of joint angles 4, 5 and 6 are compared and the joint angle solution with the smaller Euclidean distance is selected as the optimal joint angle for rolling edge.

6. The method of claim 1, wherein, The method further comprises step S4: developing a robot glue-containing rolling edge process parameter adaptive software tool, and simulating and verifying the rolling edge optimal joint angle information. Step S4 comprises the following sub-steps: S40, using Matlab to implement the codes of steps S1, S2 and S3, and using the Appdesigner interface development tool in Matlab to develop the software tool; S41, establishing a three-dimensional model of the robot rolling edge, the three-dimensional model comprising a robot model, a tire membrane model and a roller model, and assembling according to the coordinate system information involved in steps S1, S2 and S3, and finally importing into the robot simulation software V-rep; S42, using SOCKET communication to establish data exchange between Matlab and V-rep, transmitting the rolling edge optimal joint angle information obtained by Matlab to V-rep, and performing robot rolling edge simulation in V-rep and checking collision and interference.

7. The method of claim 6, wherein the method further comprises: According to the relative position information between the tire membrane and the rolling edge robot, the rolling edge robot and the tire membrane model are established in the three-dimensional drawing software and imported into V-rep, the joint rotation axis of the rolling edge robot is established in V-rep, and the rotation angle of the joint rotation axis of the rolling edge robot is guided according to the rolling edge optimal joint angle information received from Matlab, so as to realize the simulation of the rolling edge process.

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