Method and system for spray robot path intelligence generation and feedback control

Abstract

The application belongs to the technical field of spraying process, and proposes a method and system for intelligent generation and feedback control of a spraying robot path. By calculating the coating distribution difference between adjacent spraying areas and accumulating the sum of the absolute differences, not only can local abnormalities in a single spraying area be detected, but also the coating distribution differences between adjacent areas can be effectively reflected. Combined with visual measurement technology, the system can obtain coating distribution information of the spraying surface in real time, thereby accurately identifying abnormal conditions at the junction of multiple curved surfaces. Especially in the spraying process of complex workpieces, due to changes in surface curvature, overlapping of robot trajectories, or insufficient adaptation of spraying parameters, coating accumulation, excessive thinness, or incomplete coverage at the junction are prone to occur, thereby significantly improving the detection capability of abnormalities and more accurately capturing typical process defects such as coating accumulation and incomplete coverage in the transition area of multiple curved surfaces.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of spraying process, and particularly relates to a method and system for intelligent generation and feedback control of a spraying robot path. BACKGROUND

[0002] In an automatic spraying operation, a spraying gun of a spraying robot moves back and forth around a surface of a workpiece to be painted, and an off-line programming system of the spraying robot mainly comprises a robot spraying gun trajectory optimization module, a robot motion trajectory generation module, a robot program generation module, and the like. The robot motion trajectory generation module and the robot program generation module basically belong to common modules in an off-line programming system of a general industrial robot. A visual measurement technology can be applied to the robot spraying gun trajectory optimization module. By acquiring a shape and a coating distribution of the surface of the workpiece in real time, the visual measurement technology helps to optimize a spraying gun motion trajectory and avoid unevenness of the coating distribution. However, when a complex and delicate small workpiece is sprayed, many small-area smooth surfaces or many edges and corners are encountered. When the spraying robot sprays the above parts, the coating is prone to form an abnormal distribution on the surface, causing edge coating sagging and coating orange peel phenomenon in a place with less coating distribution, and causing a tendency of cracking in a place with too thick coating. A current solution is to accurately analyze and segment arc-shaped curved surface parts, and to use different spraying parameters for different parts. However, when facing many curved surfaces, the above method greatly affects a computer calculation rate when facing complex small workpieces. Although a current industrial control system can adjust spraying parameters and a spraying gun position in real time to reduce unevenness of the coating at a junction and improve stability and consistency of a spraying process, when the spraying gun is vertically positioned on the workpiece surface and moves in a certain direction, the coating forms a kind of stripe deposition distribution on the workpiece surface. When the spraying head sweeps a curved surface, an irregular stripe distribution is often generated at the junction due to the influence of a curvature change on a spraying characteristic of the coating on the plane. At this time, it is difficult to realize coating consistency even when spraying again. SUMMARY

[0003] The present application aims to provide a method and system for intelligent generation and feedback control of a spraying robot path to solve one or more technical problems in the prior art and at least provide a beneficial choice or create conditions.

[0004] In order to achieve the above-mentioned purpose, according to an aspect of the present application, a method for intelligent generation and feedback control of a spraying robot path is provided, and the method comprises the following steps.

[0005] S100, drawing a workpiece curved surface model, using three-dimensional software to carry out curved surface partitioning on the three-dimensional model;

[0006] S200, presetting a spraying path according to requirements in the partitioning and setting a spraying site on the spraying path, and setting a standard spraying height at the spraying site;

[0007] S300, based on the drawn workpiece curved surface model and the preset spraying path, controlling a spraying robot to carry out preview running and obtaining a preview spraying distance block;

[0008] S400, obtaining a spraying error according to the preview spraying distance block and the standard spraying height, and correcting the spraying error according to the workpiece curved surface partitioning to obtain a correction model;

[0009] S500, correcting the preset spraying path according to the correction model to obtain an actual path, and controlling the spraying robot to run spraying according to the actual path.

[0010] Further, in S100, the specific method for drawing a workpiece curved surface model and using three-dimensional software to carry out curved surface partitioning on a three-dimensional model is as follows: first, drawing a curved surface model of the workpiece by using FreeCAD software, then carrying out curvature variation analysis on the curved surface model by using Blender software, and dividing the entire curved surface into three parts according to the variation of the curvature, an arc surface type curved surface being part A, the remaining two smooth parts being planes B and C respectively, and obtaining a boundary line L2 of the curved surface B and the curved surface A and a boundary line L3 of the curved surface C and the curved surface A.

[0011] Further, in S200, the specific method for presetting a spraying path according to requirements in the partitioning and setting a spraying site on the spraying path, and setting a standard spraying height at the spraying site is as follows: setting the working parameters of the spraying robot as follows: a spraying speed (1-3 m / s), a standard spraying height (150-300 mm), a spraying angle (15°-30°), a spraying pressure (200-400 kpa), and a spraying flow (100-500 ml / min).

[0012] Further, in S300, the specific method for presetting a spraying path based on the drawn workpiece curved surface model, controlling a spraying robot to carry out preview running, and obtaining a preview spraying distance block is as follows:

[0013] The preset spraying path is combined with the main controller instruction to generate a robot control program, the workpiece is placed in the robot motion space and a workpiece coordinate system is established, after verifying the trajectory feasibility in the robot simulation software, the robot control program is uploaded to the robot controller, the spraying program is previewed and executed, and in the process of previewing and executing, the spraying distance block formed by the spraying robot at each spraying site is measured and recorded according to the distance measuring sensor previously installed on the robot, wherein the spraying distance block is a distance set formed from each point in the spraying area to the vertical plane of the spray head when the spraying robot completes spraying at the spraying site, and the distance set includes distance information of each point in the spraying area to the vertical plane of the spray head and position information of each point in the spraying area.

[0014] Further, in S400, the spraying error is obtained according to the preview spraying distance block and the standard spraying distance, and the specific method of correcting the spraying error according to the workpiece surface partition to obtain the corrected model is that: taking the spraying site as the center P i of the spraying area, i represents the serial number of the spraying site, and i ∈ [1, M], M represents the number of spraying sites, in the spraying distance block, the position information of all points is LC j , and the distance information is DIS j , wherein j represents the serial number of the position point included in the spraying distance block.

[0015] Let the position information of all spraying sites be LOC i , the vertical distance of all spraying sites to L2 be VD i , the vertical distance of all spraying sites to L3 be VE i , the average value of the vertical distance VD i of all spraying sites to L2 be VD mean , the average value of the vertical distance VE i of all spraying sites to L3 be VE mean , the spraying site satisfying VD i < VD mean or VE i < VE mean is marked as an affected point, the spraying area corresponding to the affected point is marked as a flow area, and the distance set of the obtained flow area is a flow distance block.

[0016] The atomization of the paint during spraying is completed by the centrifugal force generated by the high-speed rotation of the rotary cup, the electric field force of high-voltage static electricity and the inertial force of the shaping air, and the spatial distribution of the paint generated thereby is annular. When the parameters such as the static voltage, the spacing, the rotary cup rotation speed, the paint flow and the paint viscosity remain unchanged, the spatial distribution of the paint formed on the workpiece surface by the fixed-point spraying of the spray gun perpendicular to the workpiece surface for a period of time is a hollow annular shape. When the spray gun is moved in parallel in a certain direction perpendicular to the workpiece surface, the paint will form a kind of striped deposition distribution on the workpiece surface, which presents the characteristics of large middle distance and small peripheral distance in the distance block constituted by the data obtained by the distance sensor. Therefore, the preset effect cannot be achieved by one-time spraying at this time. At present, the method for solving the above problems is two-time spraying to achieve the purpose of consistent coating. When the spray head sweeps the intersection between curved surfaces, due to the influence of the curvature change on the planar spraying characteristics of the spray material, irregular striped distribution is often generated at the intersection. At this time, it is also difficult to achieve consistent coating by re-spraying. In order to solve the above problems, the following method is proposed in the present application to generate a correction model of the second spraying path by calculating the deviation index of all spraying areas.

[0017] Let all the flow distance blocks be DIB k , wherein k represents the serial number of the flow distance block, and the distance information DIS in all the flow distance blocks is traversed within the value range of k kj , the maximum value of the distance information in the flow distance block DIB k is marked as DIS kmax , the minimum value of the distance information in the flow distance block DIBk is marked as DIS kmin , the average distance information of each flow distance block is calculated as DIS kmean , the unit vector between the point corresponding to the maximum value and the point corresponding to the minimum value is recorded as the flow unit vector, and the product of the Euclidean distance between the point corresponding to the maximum value and the point corresponding to the minimum value and the flow unit vector is recorded as the flow vector , wherein j represents the serial number of the position point included in the spraying distance block, and the vector of the spraying site to each point in the spraying area is calculated The deviation index is calculated by the formula , wherein the function represents the projection vector of the vector on , the module of the projection vector of on is used to calculate the module of the projection vector of on k , the number of points contained in the distance block DIB k , the deviation index Flow kmean is compared with the average distance information DIS k , and if the deviation index Flow k is greater than DISkmean , then the distance block DIB k The corresponding spraying area has a coating distribution anomaly, and the spraying point position needs to be corrected, otherwise the distance block DIB k The corresponding spraying area has no coating distribution anomaly, and the spraying point position does not need to be corrected.

[0018] The above method constructs a local coating flow model by the distance information distribution difference in each flow distance block. The point corresponding to the maximum value of the distance information indicates that the coating is significantly more than other spraying areas, and the point corresponding to the minimum value of the distance information indicates that the coating is significantly less than other spraying areas. The above formula can reflect the coating distribution of the spraying effect formed by the current spraying area under the preset path. Even in the face of small uneven distribution characteristics, the above method can amplify the small differences by the way of accumulation and summation. At the same time, the above formula introduces the normal vector to consider the influence of the surface curvature of the workpiece on the spraying effect when the nozzle parameters are consistent, and has high detection accuracy and response speed. However, the above method only considers the irregular distribution of the coating at the curved surface intersection in each spraying area. When continuous spraying, adjacent spraying areas will also affect each other. To solve the above problem, the present application proposes the following correction method:

[0019] All flow distance blocks DIB k According to the collection time sequence, all the distance information DISk in the flow distance block DIB j is traversed in the value range of k. k The maximum value of the distance information in the flow distance block DIB kmax is DIS k , and the minimum value of the distance information in the flow distance block DIB kmin is DIS kmax . The direction from the point corresponding to DIS kmin to the point corresponding to DIS kmean is marked as the flow direction, and the average distance information DIS max of all flow distance blocks is calculated. The deviation index is calculated, wherein DIS min represents the larger value between the maximum value of the distance information in the kth flow distance block and the maximum value of the distance information between the k+1th flow distance block, wherein DIS k represents the smaller value between the minimum value of the distance information in the kth flow distance block and the minimum value of the distance information between the k+1th flow distance block. The deviation index Flow kmean is compared with the average distance information DIS kthe number of points, if the deviation index Flow k greater than DIS kmean then the distance block DIB k corresponding to the spraying area has a coating distribution anomaly, and the spraying point position needs to be corrected, otherwise the distance block DIB k corresponding to the spraying area has no coating distribution anomaly, and the spraying point position does not need to be corrected.

[0020] Further, the correction method is: sequentially obtaining all spraying point position information needing correction, taking the direction of the flow vector of the spraying area corresponding to all spraying points needing correction as the adjustment direction, and adjusting the difference between the deviation index and the average distance information along the flow direction to obtain the distance.

[0021] The beneficial effects of the above steps are: by calculating the difference of the position information of each point in the adjacent distance block and accumulating, the coating distribution anomaly at the intersection of the curved surface can be effectively captured. Since the change of the curved surface structure usually accompanies the mutation of the position information, the accumulation of the difference will significantly amplify the abnormal signal of such area, thereby clearly identifying the local deviation of the coating thickness or uniformity, and significantly improving the sensitivity of the detection. At the same time, through the flow vector of the corresponding points in the adjacent distance block, the influence of the adjacent spraying area can be reflected, and the accuracy of the detection is improved.

[0022] The application also provides a system for intelligent generation and feedback control of a spraying robot path, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to run in the following system units:

[0023] a model drawing unit, configured to draw a workpiece curved surface model and perform curved surface partitioning on the three-dimensional model by using software;

[0024] a path simulation unit, configured to preset a spraying path in the partition according to requirements and set a spraying site on the spraying path, and set a standard spraying height at the spraying site;

[0025] a spraying preview unit, configured to control a spraying robot to perform preview operation based on the drawn workpiece curved surface model and the preset spraying path, and obtain a preview spraying distance block;

[0026] an error calculation unit, configured to obtain a spraying error according to the preview spraying distance block and the standard spraying height, and correct the spraying error according to the workpiece curved surface partition to obtain a corrected model;

[0027] a model correction unit, configured to correct the preset spraying path according to the corrected model to obtain an actual path, and control the spraying robot to perform spraying operation according to the actual path.

[0028] The beneficial effects of the present application are: by calculating the coating distribution difference between adjacent spraying areas and accumulating the sum of the absolute difference, the method can not only detect local abnormalities in a single spraying area, but also effectively reflect the coating distribution difference between adjacent areas, thereby accurately identifying abnormal conditions at the junction of multi-curved surfaces. Combined with visual measurement technology, the system can obtain coating distribution information of the sprayed surface in real time, and through image recognition and analysis, the detection accuracy of local coating abnormalities is further improved. In the complex workpiece spraying process, due to the change of curvature of curved surface, overlapping of robot trajectory or insufficient adaptation of spraying parameters, coating accumulation, excessive thinness or incomplete coverage at the junction are prone to occur. By quantifying the gradient change of adjacent areas, the detection ability of abnormalities is significantly improved, and typical process defects such as coating accumulation and incomplete coverage in the transition area of multi-curved surfaces can be accurately captured. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 A flow chart of a method for intelligent generation and feedback control of a spraying robot path is shown.

[0030] Figure 2 A system structure diagram for intelligent generation and feedback control of a spraying robot path is shown. DETAILED DESCRIPTION

[0031] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0032] Example 1:

[0033] Figure 1 A flow chart of a method for intelligent generation and feedback control of a spraying robot path is shown.

[0034] Referring to Figure 1 , the present application proposes a method for intelligent generation and feedback control of a spraying robot path, which comprises the following steps:

[0035] S100, drawing a workpiece curved surface model, using a three-dimensional software to divide the three-dimensional model into curved surfaces;

[0036] S200, presetting a spraying path in the partition according to requirements and setting a spraying site on the spraying path, and setting a standard spraying height at the spraying site;

[0037] S300, based on the drawn workpiece curved surface model and the set spraying path, controlling the spraying robot to perform a preview run, and obtaining a preview spraying distance block;

[0038] S400, obtaining a spraying error according to the preview spraying distance block and the standard spraying height, and correcting the spraying error according to the workpiece surface partition to obtain a correction model;

[0039] S500, correcting a preset spraying path according to the correction model to obtain an actual path, and controlling the spraying robot to run spraying according to the actual path.

[0040] Further, in S100, the workpiece surface model is drawn, and the specific method for surface partitioning of the three-dimensional model by using three-dimensional software is as follows: first, the FreeCAD software is used to draw the surface model of the workpiece, then the Blender software is used to analyze the curvature variation of the surface model, the entire surface is divided into three parts according to the variation of the curvature, the cambered surface is part A, and the remaining two smooth parts are planes B and C respectively, and the boundary line L2 of the surface B and the surface A and the boundary line L3 of the surface C and the surface A are obtained.

[0041] Further, in S200, the preset spraying path is set in the partition according to the requirements, and the standard spraying height is set on the spraying path, and the specific method is as follows: the working parameters of the spraying robot are set as follows: the spraying speed is 3 m / s, the standard spraying height is 200 mm, the spraying angle is 20°, the spraying pressure is 300 kpa, and the spraying flow is 300 ml / min.

[0042] Further, in S300, the preset spraying path is set based on the drawn workpiece surface model, the spraying robot is controlled to run in preview, and the specific method for obtaining the preview spraying distance block is as follows:

[0043] The preset spraying path is combined with the main controller instruction to generate a robot control program, the workpiece is placed in the robot motion space and the workpiece coordinate system is established, the trajectory feasibility is verified in the robot simulation software, the robot control program is uploaded to the robot controller after verification, the spraying program is previewed and executed, and in the process of preview running, the spraying distance block formed by the spraying robot at each spraying site is measured and recorded according to the distance measuring sensor installed on the robot in advance, wherein the spraying distance block is a distance set from each point in the spraying area to the vertical plane of the spray head formed by the distance measuring sensor when the spraying robot completes spraying at the spraying site, and the distance set includes the distance information from each point in the spraying area to the vertical plane of the spray head and the position information of each point in the spraying area.

[0044] Further, in S400, the spraying error is obtained according to the preview spraying distance block and the standard spraying distance, and the correction model is obtained by correcting the spraying error according to the workpiece surface partition, and the specific method is as follows: taking the spraying site as the center P iLet i represent the index of the spraying location, and i∈[1,M], where M represents the number of spraying locations. In the spraying distance block, let the position information of all points be LC. j Distance information is DIS j , where j represents the position point number included in the spraying distance block;

[0045] Record the location information of all spraying locations as LOC. i Calculate the vertical distance VD from all spraying locations to L2. i Calculate the vertical distance VE from all spraying locations to L3. i Record the vertical distance VD from all spraying locations to L2. i The average value is VD mean The vertical distance VE from all spraying locations to L3 i The average value is VE mean This will satisfy VD i <VD mean Or VE i <VE mean The spraying locations are marked as affected points, the spraying areas corresponding to the affected points are marked as flow areas, and the distance set of the obtained flow areas is the flow distance block;

[0046] Set all flow distance blocks to DIB k Where k represents the sequence number of the flow distance block, and the distance information DIS in all flow distance blocks is traversed within the range of values ​​for k. kj Mark the flow distance block DIB k The maximum value of the mid-range information is DIS kmax The minimum value of the distance information in the flow distance block DIBk is DIS. kmin Calculate the average distance information of each of the flow distance blocks as DIS. kmean Let the unit vector between the point corresponding to the maximum value and the point corresponding to the minimum value be called the flow unit vector, and let the product of the Euclidean distance between the point corresponding to the maximum value and the point corresponding to the minimum value and the flow unit vector be called the flow vector. Where j represents the position point number included in the spraying distance block, and the vector from the spraying location to each point in the spraying area is calculated. Through formula Calculate the deviation index, where, Functions represent vectors exist The projection vector on, Used for calculation exist The magnitude of the projection vector on the distance block DIB, where N is the distance block DIB. kThe number of points included, compared to the deviation from the exponential flow. k With average distance information DIS kmean The magnitudes of both, if they deviate from the exponential flow k Greater than DIS kmean Then it is considered that the distance block DIB k If the paint distribution in the corresponding sprayed area is abnormal, the position of the spray point needs to be corrected; otherwise, it is considered a distance block DIB. k There was no abnormal local distribution of paint in the corresponding sprayed area, so there is no need to correct the position of the spray point in this area;

[0047] Furthermore, the correction method is as follows: sequentially obtain the position information of all spray points that need to be corrected, take the direction of the flow vector of the spray area corresponding to all spray points that need to be corrected as the adjustment direction, and adjust the position of the spray point along the flow direction to deviate from the difference between the index and the average distance information.

[0048] Example 2

[0049] This embodiment 2 replaces the method in embodiment 1, which involves obtaining the spraying error based on the preview spraying distance block and the standard spraying distance, and then correcting the spraying error based on the workpiece surface zoning to obtain a correction model. Specifically:

[0050] All flow distance blocks DIB k Arranged in chronological order of acquisition time, the distance information DISk in all flow distance blocks is traversed within the range of values ​​for k. j Mark the flow distance block DIB k The maximum value of the mid-range information is DIS kmax Flow distance block DIB k The minimum value of the mid-range information is DIS kmin , DIS kmax Corresponding point to DIS kmin The direction of the corresponding point is marked as the flow direction, and the average distance information of each of the flow distance blocks is calculated as DIS. kmean According to the formula Calculate the deviation index, where DIS max DIS represents the larger of the maximum distance information value in the k-th flow distance block and the maximum distance information value between the (k+1)-th flow distance blocks. min T represents the smaller value between the minimum distance information in the k-th flow distance block and the minimum distance information between the (k+1)-th flow distance blocks, where T represents the flow distance block DIB. k The quantity, compared to the deviation of the exponential flow k With average distance information DISkmean Both sizes, if deviating from the index Flow k DIS kmean The distance block DIB k The corresponding spraying area has coating local distribution abnormality, and the spraying point position needs to be corrected, otherwise the distance block DIB k The corresponding spraying area has no coating local distribution abnormality, and the spraying point position does not need to be corrected.

[0051] In addition, the present application also provides an embodiment of a system for intelligent generation and feedback control of a spraying robot path, as shown in Figure 2 The system structure diagram of the system for intelligent generation and feedback control of a spraying robot path of the present application is shown, and the system for intelligent generation and feedback control of a spraying robot path of the embodiment comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor implements the steps in the above-mentioned system embodiment for intelligent generation and feedback control of a spraying robot path when executing the computer program.

[0052] The system comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program running in the following system units:

[0053] A model drawing unit draws a workpiece curved surface model, and uses three-dimensional software to perform curved surface partitioning on the three-dimensional model;

[0054] A path simulation unit is used to preset a spraying path in the partition according to requirements and set a spraying site on the spraying path, and set a standard spraying height at the spraying site;

[0055] A spraying preview unit is used to control a spraying robot to perform preview operation based on the drawn workpiece curved surface model and the set spraying path, and obtain a preview spraying distance block;

[0056] An error calculation unit is used to obtain a spraying error according to the preview spraying distance block and the standard spraying height, and correct the spraying error according to the workpiece curved surface partitioning to obtain a corrected model;

[0057] A model correction unit is used to correct a preset spraying path according to the corrected model to obtain an actual path, and control a spraying robot to perform spraying operation according to the actual path.

[0058] The system for intelligent path generation and feedback control of a spraying robot can run in a desktop small computer, a notebook, a palm computer, a cloud server and other computing devices. The system for intelligent path generation and feedback control of a spraying robot can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the examples are only examples of the system for intelligent path generation and feedback control of a spraying robot, and do not constitute a limitation on the system for intelligent path generation and feedback control of a spraying robot, and can include more or fewer components, or combine certain components, or different components, for example, the system for intelligent path generation and feedback control of a spraying robot can also include an input / output device, a network access device, a bus, etc.

[0059] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The processor is the control center of the system for intelligent path generation and feedback control of a spraying robot, and connects each part of the system for intelligent path generation and feedback control of a spraying robot through various interfaces and lines.

[0060] The memory can be used to store the computer programs and / or modules, and the processor realizes various functions of the system for intelligent path generation and feedback control of a spraying robot by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required for a function (such as a sound playing function, an image playing function, etc.), etc.; and the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0061] While the description of the application has been presented in considerable detail and particularity with respect to several embodiments thereof, it is not intended to restrict or in any way limit the scope of the application to such detail and particularity but rather it is intended to cover the intended scope of the application as defined by the appended claims. Moreover, the foregoing description has been presented for the purposes of illustration and description and is not intended to be exhaustive or to limit the application to the precise embodiments disclosed.

Claims

1. A method for spray robot path intelligence generation and feedback control, characterized in that, The method comprises the following steps: S100, drawing a workpiece curved surface model, using three-dimensional software to perform curved surface partitioning on a three-dimensional model; S200, presetting a spraying path according to requirements in the partitioning and setting a spraying site on the spraying path, and setting a standard spraying height at the spraying site; S300, based on the drawn workpiece curved surface model and the set spraying path, controlling a spraying robot to perform preview running and obtaining a preview spraying distance block; S400, obtaining a spraying error according to the preview spraying distance block and the standard spraying height, and correcting the spraying error according to the workpiece curved surface partitioning to obtain a correction model; S500, correcting the preset spraying path according to the correction model to obtain an actual path, and controlling the spraying robot to run spraying according to the actual path; The preview spraying distance block in step S300 is: when the spraying robot completes spraying at the spraying site, a distance set formed from each point in the spraying area to a vertical plane of the spray head obtained by a distance measuring sensor, and the distance set comprises distance information from each point in the spraying area to the vertical plane of the spray head and position information of each point in the spraying area.

2. The method for spray robot path intelligence generation and feedback control of claim 1, wherein, In S100, the method for drawing a workpiece curved surface model and performing curved surface partitioning on a three-dimensional model using three-dimensional software is: first, drawing a curved surface model of the workpiece by using FreeCAD software, then performing curvature variation analysis on the curved surface model by using Blender software, and dividing the entire curved surface into three parts according to the variation of the curvature, an arc surface type curved surface is part A, and the remaining two smooth parts are planar parts B and C, to obtain a boundary line L2 of curved surface B and curved surface A and a boundary line L3 of curved surface C and curved surface A.

3. The method for spray robot path intelligence generation and feedback control of claim 2, wherein, In S300, based on the drawn workpiece curved surface model and the set spraying path, the method for controlling a spraying robot to perform preview running and obtaining a preview spraying distance block is: obtaining a robot control program generated by combining a preset spraying path and a main controller instruction, placing the workpiece in a robot motion space and establishing a workpiece coordinate system, verifying the feasibility of the trajectory in a robot simulation software, uploading the robot control program to a robot controller after the verification, previewing the execution of the spraying program, and measuring and recording a spraying distance block formed by spraying of the spraying robot at each spraying site according to a distance measuring sensor pre-installed on the robot during the preview running.

4. The method for spray robot path intelligence generation and feedback control of claim 3, wherein, In S400, the spraying error is obtained according to the preview spraying distance block and the standard spraying height, and the method for correcting the spraying error according to the workpiece curved surface partition to obtain a corrected model is: let the spraying site be the center P of the spraying area i , i represents the serial number of the spraying site, and i ∈ [1, M], M represents the number of the spraying sites, in the spraying distance block, let the position information of all points be LC j , and the distance information be DIS j , wherein j represents the serial number of the position point included in the spraying distance block; Record the position information of all spraying locations as LOC i Calculate the vertical distance of all spraying locations to L2 as VD i Calculate the vertical distance of all spraying locations to L3 as VE i Record the average value of the vertical distance VD i of all spraying locations to L2 as VD mean The average value of the vertical distance VE i of all spraying locations to L3 as VE mean Mark the spraying locations that satisfy VD i < VD mean or VE i < VE mean as affected points, mark the spraying area corresponding to the affected points as a flow area, and the distance set of the obtained flow area is a flow distance block. Let all the flow distance blocks be DIB k , where k represents the serial number of the flow distance block, and the distance information DIS in all the flow distance blocks is traversed within the value range of k kj , the maximum value of the distance information in the flow distance block DIB k is marked as DIS kmax , the minimum value of the distance information in the flow distance block DIBk is marked as DIS kmin , the respective average distance information DIS in all the flow distance blocks is calculated kmean , the unit vector between the point corresponding to the maximum value and the point corresponding to the minimum value is recorded as the flow unit vector, and the product of the Euclidean distance between the point corresponding to the maximum value and the point corresponding to the minimum value and the flow unit vector is recorded as the flow vector , where j represents the serial number of the position point included in the spraying distance block, and the vector of the spraying point to each point in the spraying area is calculated , the deviation index is calculated by the formula Flow k , and the average distance information DIS kmean is compared in size, and if the deviation index Flow k is greater than DIS kmean , it is considered that the coating local distribution of the spraying area corresponding to the distance block DIB k is abnormal, and the spraying point position needs to be corrected, otherwise it is considered that the coating local distribution of the spraying area corresponding to the distance block DIB k does not occur, and the spraying point position does not need to be corrected; The position information of all spraying points needing correction is obtained in sequence, the direction of the flow vector of the spraying area corresponding to all spraying points needing correction is taken as the adjustment direction, and the difference between the deviation index and the average distance information of the spraying point position along the flow direction is taken as the result distance.

5. The method for spray robot path intelligence generation and feedback control of claim 4, wherein, The method for obtaining a spraying error according to the preview spraying distance block and the standard spraying height and correcting the spraying error according to the workpiece curved surface partitioning to obtain a correction model is replaced by: All the flow distance blocks DIB k According to the acquisition time sequence, the distance information DISk in all the flow distance blocks is traversed within the range of k values j The maximum value of the distance information in the flow distance block DIB k is DIS kmax The minimum value of the distance information in the flow distance block DIB k is DIS kmin The direction from the point corresponding to DIS kmax to the point corresponding to DIS kmin is marked as the flow direction, the average distance information DIS kmean of each of all the flow distance blocks is calculated, the deviation index is calculated according to the formula, and the deviation index Flow k is compared with the average distance information DIS kmean If the deviation index Flow k is greater than DIS kmean , it is considered that the coating area corresponding to the distance block DIB k has coating distribution abnormality, and the spraying point position at this place needs to be corrected, otherwise it is considered that the coating area corresponding to the distance block DIB k does not have coating distribution abnormality, and the spraying point position at this place does not need to be corrected.

6. A system for spray robot path intelligence generation and feedback control, characterized by, The system for intelligent generation and feedback control of a spraying robot path comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, and the processor implements the steps in the method for intelligent generation and feedback control of a spraying robot path according to any one of claims 1-5 when executing the computer program.

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