CN111013883A - Robot control method for intelligent spraying of multiple vehicle types - Google Patents
Robot control method for intelligent spraying of multiple vehicle types Download PDFInfo
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- CN111013883A CN111013883A CN201911166205.6A CN201911166205A CN111013883A CN 111013883 A CN111013883 A CN 111013883A CN 201911166205 A CN201911166205 A CN 201911166205A CN 111013883 A CN111013883 A CN 111013883A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B13/00—Machines or plants for applying liquids or other fluent materials to surfaces of objects or other work by spraying, not covered by groups B05B1/00 - B05B11/00
- B05B13/02—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work
- B05B13/04—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation
- B05B13/0431—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation with spray heads moved by robots or articulated arms, e.g. for applying liquid or other fluent material to 3D-surfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/12—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus
- B05B12/122—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus responsive to presence or shape of target
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B13/00—Machines or plants for applying liquids or other fluent materials to surfaces of objects or other work by spraying, not covered by groups B05B1/00 - B05B11/00
- B05B13/02—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work
- B05B13/04—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B15/00—Details of spraying plant or spraying apparatus not otherwise provided for; Accessories
- B05B15/70—Arrangements for moving spray heads automatically to or from the working position
Abstract
The invention provides a robot control method for intelligent spraying of multiple vehicle types. The wheel hub particle spraying device is used for identifying wheel hubs of different vehicle types and performing particle spraying. The method comprises the steps of acquiring a two-dimensional picture of a target processing area in real time through a preset position, judging whether a workpiece enters or not according to the change of characteristic points in gray value images of the two-dimensional picture before and after the workpiece enters, and further determining whether the workpiece is a hub workpiece or not when the first three-dimensional profile characteristic of the target workpiece is acquired; the first three-dimensional profile characteristics are compared with the existing three-dimensional model set of the preset hub model library, so that the first three-dimensional model corresponding to the target workpiece is rapidly obtained, and the operation burden of newly generating a new three-dimensional model and increasing equipment is avoided.
Description
Technical Field
The invention relates to the field of automatic control of intelligent machines, in particular to a robot control method for intelligent spraying of multiple vehicle types.
Background
As the explosive development of electronic technology began in the 80's of the last century, various information-based robots began to perform various industrial production activities instead of some workers. With the improvement of the informatization technology, the industrial robot technology is generally applied to production lines, and the robot performs the operation in the aspects of assembly, welding, gluing and the like. For example, the performance and appearance of machined articles such as automobiles are also increasingly required. The automotive finish is the most direct impression of the appearance of an automobile. The automobile painting process is one of four major processes (stamping, welding, painting, final assembly) in automobile manufacturing, and the quality of the automobile painting process directly influences the first impression of a consumer on the automobile brand. Since the coating quality of automobiles is affected by various factors, such as: the coating, the coating environment, the setting of various process parameters and the like make the automobile coating become a work with high precision and difficulty.
The spraying robot has the advantages of accurate spraying and controllable spraying range, so that a large amount of industrial coatings are saved in the spraying process, less paint waste is generated in the spraying process, and the damage to the environment is reduced. Therefore, a large number of novel spraying robots and related control technologies have also become hot spots of research, and a large number of such patents "workpiece spraying systems" as in patent application No. CN201811569171.0 appear, but the structures of hardware systems of the spraying robots are all the same and different, so the research directions of the existing spraying robots mainly lie in directions of trajectory planning, spraying control, machine vision, and the like.
Most of the existing spraying robots perform spraying operation according to the generated ideal track, in order to ensure the spraying quality, a workpiece to be sprayed is required to be placed at an ideal position, but a position error exists when the workpiece to be sprayed is actually fixed, so that the ideal effect cannot be achieved during spraying. The method of obtaining a workpiece model by field scanning of a workpiece and obtaining a real-time model of the workpiece by reproducing field processing scanning data increases the computational burden of equipment, thereby causing the spraying consumption time of a single workpiece to be prolonged and the processor loss of the spraying robot to be accelerated. For a workpiece which is an automobile hub and has a complex profile and needs to be sprayed in a short time and in a large scale, a method which has the advantages of high spraying efficiency, good spraying effect, small equipment loss and high spraying precision and can realize the identification and spraying of a spraying robot on the hubs of a large number of different automobile types in a short time becomes necessary.
Disclosure of Invention
In order to solve the technical problem, the invention provides a robot control method for intelligent spraying of multiple vehicle types, which is used for identifying hubs of different vehicle types and performing particle spraying.
The invention provides a robot control method for intelligent spraying of multiple vehicle types, which comprises the following steps: s1, detecting whether a workpiece exists in the target machining area; s2, when the workpiece exists, acquiring a first three-dimensional contour feature of the target workpiece; s3, comparing the first three-dimensional profile characteristic of the target workpiece with a three-dimensional model set of a preset hub model library, and judging whether a first three-dimensional model corresponding to the target workpiece exists in the preset hub model library or not; s4, when a first three-dimensional model corresponding to the target workpiece is determined to exist, selecting a first spraying parameter set corresponding to the first three-dimensional model from a first color spraying database; s5, according to the relative distance between each feature point of the first three-dimensional model and the space coordinates of part of the feature points in the target processing area, further acquiring space coordinate parameters corresponding to each position of the first three-dimensional model; s6, generating first running track information capable of carrying out full-coverage spraying on the target workpiece according to the space coordinate parameters corresponding to the positions of the first three-dimensional model and the limit spraying range of the spraying robot spray gun; and S7, controlling the robot spray gun to move along the first running track at a certain moving speed according to the first running track information and the first spraying parameter set, and further spraying different positions of the target workpiece by using corresponding color particles.
Further, the step S1 of "determining whether or not the workpiece exists in the target machining area" specifically includes: s11, shooting a two-dimensional picture of the target processing area from a preset position; s12, converting the two-dimensional picture of the target processing area into a gray image; s13, comparing the gray level image with the gray level image of the two-dimensional picture shot from the same position before the target processing area when no workpiece exists; and S14, determining that the workpiece exists in the target processing area when the difference between the characteristic points of the gray level images of the two-dimensional pictures of the target processing area is detected to exceed a first preset difference value.
Further, the step S2 of "acquiring the first three-dimensional contour feature of the target workpiece" specifically includes: s21, acquiring characteristic points of each outline edge outside the target workpiece through a three-dimensional laser scanner arranged in the target processing area, and converging the characteristic points into first point cloud by adopting an automatic registration method; s22, converting each point data of the first point cloud into a first reference coordinate system; s23, denoising the first point cloud in the first reference coordinate system by adopting an average curvature flow filtering algorithm; s24, establishing a topological relation of scattered point clouds of the denoised first point cloud, and directly compressing point cloud data; and S25, performing three-dimensional reconstruction on the point cloud by adopting a micro-tangent plane method, thereby obtaining first point cloud data including the first three-dimensional contour feature of the target workpiece.
Further, the preset hub model library comprises hub model data of automobiles of various different vehicle types, and when the point cloud data of the first three-dimensional contour feature and the preset point cloud data of a certain hub model of the preset hub model library are 99% of same phase, the first three-dimensional model exists.
Further, the first color spraying database stores spraying parameters corresponding to a preset hub model library, each three-dimensional model in the preset hub model library corresponds to a plurality of spraying parameter sets in the first color spraying database, and different spraying parameter sets record different spraying schemes.
Further, when the parameter set corresponding to the first stereo model in the first color spraying database does not meet the use requirement, the parameters of the first spraying parameter set can be adjusted on line according to the first stereo model, so that a second spraying parameter set meeting the spraying requirement is obtained, and meanwhile, the second spraying parameters are stored in the first color spraying database.
Further, step S5 specifically includes: s51, establishing a target space coordinate system by using one end point of the target processing area; s52, selecting a plurality of edge feature points of the target workpiece, and determining corresponding positions of the edge feature points in the point cloud of the first three-dimensional model; and S53, determining the coordinates of each edge feature point in the target space coordinate system through the three-dimensional laser scanner, and obtaining the space coordinate parameters corresponding to each position of the first three-dimensional model by combining the relative position relation among the feature points in the first three-dimensional model.
Further, step S6 specifically includes: s61, acquiring the limit spraying range of the spray gun of the spraying robot; s62, acquiring a region needing spraying of the first three-dimensional model from the first spraying parameter set; s63, generating a first auxiliary track which can connect the spraying areas along the surface of the first three-dimensional model according to the area and the position information of the areas, needing spraying, of the first three-dimensional model; s64, generating second auxiliary tracks moving in the areas needing spraying according to the entry points and the separation points of the areas needing spraying of the first auxiliary tracks, the area of the areas and the spraying limit spraying range; and S65, integrating the first auxiliary track and the second auxiliary track to obtain first running track information capable of performing full-coverage spraying on the target workpiece.
Further, in the first auxiliary trajectory and the second auxiliary trajectory, the distance of the spray gun of the spray robot from each of the spray areas during the movement is substantially the same.
The two-dimensional picture of the target processing area is obtained in real time through the preset position, whether a workpiece enters or not is judged according to the change of the characteristic points in the gray value images of the two-dimensional picture before and after the workpiece enters, and meanwhile, whether the workpiece is a hub workpiece or not can be further determined when the first three-dimensional profile characteristic of the target workpiece is obtained; according to the invention, the first three-dimensional profile characteristic is compared with the three-dimensional model set of the existing preset hub model library, so that the first three-dimensional model corresponding to the target workpiece is rapidly obtained, and the operation burden of newly generating a new three-dimensional model and increasing equipment is avoided. According to the invention, the three-dimensional laser scanner is used for selecting a plurality of edge characteristic points of the target workpiece, the spatial coordinates of each position of the target hub are rapidly obtained according to the characteristic points and the first three-dimensional model, and accurate workpiece position information is obtained through a small amount of system operation, so that the subsequent operation track of a spray gun of the spraying robot is conveniently formulated, and the error caused by the existing method that the spraying workpiece is fixed at the specified position and the coordinates of each position point of the workpiece are positioned at the specified position is reduced. According to the invention, a first auxiliary track which can connect all the spraying areas along the surface of the first three-dimensional model is obtained according to the areas needing spraying of the target workpiece, then a second auxiliary track which moves in each area needing spraying is generated according to the entry points and the separation points, the area of the areas and the spraying limit spraying range, and the first auxiliary track and the second auxiliary track are integrated to generate the first running track, so that the redundant movement of a spray gun of the spraying robot is reduced, the spraying efficiency is improved, and the spraying time is reduced.
Drawings
Fig. 1 is a flowchart of a robot control method for intelligent painting of multiple vehicle models according to the present invention;
fig. 2 is a flowchart of a robot control method for intelligent painting of multiple vehicle models according to the present invention, in step S1;
fig. 3 is a flowchart of a robot control method for intelligent painting of multiple vehicle models according to the present invention, in step S2;
fig. 4 is a flowchart of a robot control method for intelligent painting of multiple vehicle models according to the present invention, in step S5;
fig. 5 is a flowchart of step S6 of the robot control method for intelligent painting of multiple vehicle models according to the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention and/or the technical solutions in the prior art, the following description will explain specific embodiments of the present invention with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort. In addition, the term "orientation" merely indicates a relative positional relationship between the respective members, not an absolute positional relationship.
As shown in fig. 1, the present invention provides a robot control method for intelligent painting of multiple vehicle models, which is used for identifying hubs of different vehicle models and performing particle painting, and includes the following steps S1 to S7.
And S1, detecting whether the workpiece exists in the target machining area.
As shown in fig. 1 and 2, step S1 in the present invention specifically includes: s11, shooting a two-dimensional picture of the target processing area from a preset position; s12, converting the two-dimensional picture of the target processing area into a gray image; s13, comparing the gray level image with the gray level image of the two-dimensional picture shot from the same position before the target processing area when no workpiece exists; and S14, determining that the workpiece exists in the target processing area when the difference between the characteristic points of the gray level images of the two-dimensional pictures of the target processing area is detected to exceed a first preset difference value. The acquisition of the two-dimensional picture can be completed by a camera arranged in a target processing area, and can also be completed by a built-in camera of a three-dimensional laser scanner.
And S2, when the workpiece exists, acquiring a first three-dimensional profile characteristic of the target workpiece.
As shown in fig. 3, the first three-dimensional contour feature of the target workpiece obtained by the present invention specifically includes: s21, acquiring characteristic points of each outline edge outside the target workpiece through a three-dimensional laser scanner arranged in the target processing area, and converging the characteristic points into first point cloud by adopting an automatic registration method; s22, converting each point data of the first point cloud into a first reference coordinate system; s23, denoising the first point cloud in the first reference coordinate system by adopting an average curvature flow filtering algorithm; s24, establishing a topological relation of scattered point clouds of the denoised first point cloud, and directly compressing point cloud data; and S25, performing three-dimensional reconstruction on the point cloud by adopting a micro-tangent plane method, thereby obtaining first point cloud data including the first three-dimensional contour feature of the target workpiece. According to the invention, only the characteristic points of the outer contour edge of the target workpiece are obtained, so that all data do not need to be measured, and the degree of matching with the preset hub model library can be achieved, so that a large amount of calculation work is reduced, and meanwhile, the accuracy of measurement is ensured.
The preset hub model library comprises hub model data of automobiles of various different vehicle types, and when the point cloud data of the first three-dimensional outline characteristic and the preset point cloud data of one hub model of the preset hub model library are 99% of same phase, the first three-dimensional model exists.
And S4, when the first three-dimensional model corresponding to the target workpiece is determined to exist, selecting a first spraying parameter set corresponding to the first three-dimensional model from a first color spraying database.
In the invention, the first color spraying database stores spraying parameters corresponding to the preset hub model library, each three-dimensional model in the preset hub model library corresponds to a plurality of spraying parameter sets in the first color spraying database, and different spraying parameter sets record different spraying schemes. When the parameter set corresponding to the first stereo model in the first color spraying database does not meet the use requirement, the parameters of the first spraying parameter set can be adjusted on line according to the first stereo model, so that a second spraying parameter set meeting the spraying requirement is obtained. The first spraying parameter set comprises the color and the thickness parameter to be sprayed of the paint particles to be sprayed of each position point of the first three-dimensional model. While storing the second spray parameters in the first color spray database. Therefore, the subsequent same workpiece is processed conveniently, and secondary adjustment can be avoided.
And S5, acquiring space coordinate parameters corresponding to each position of the first three-dimensional model according to the relative distance between each feature point of the first three-dimensional model and the space coordinates of part feature points in the target processing area.
As shown in fig. 4. Step S5 specifically includes: s51, establishing a target space coordinate system by using one end point of the target processing area; s52, selecting a plurality of edge feature points of the target workpiece, and determining corresponding positions of the edge feature points in the point cloud of the first three-dimensional model; and S53, determining the coordinates of each edge feature point in the target space coordinate system through the three-dimensional laser scanner, and obtaining the space coordinate parameters corresponding to each position of the first three-dimensional model by combining the relative position relation among the feature points in the first three-dimensional model.
And S6, generating first running track information capable of carrying out full-coverage spraying on the target workpiece according to the space coordinate parameters corresponding to the positions of the first three-dimensional model and the limit spraying range of the spraying robot spray gun.
As shown in fig. 5, step S6 further includes the following sub-steps. S61, acquiring the limit spraying range of the spray gun of the spraying robot; s62, acquiring a region needing spraying of the first three-dimensional model from the first spraying parameter set; s63, generating a first auxiliary track which can connect the spraying areas along the surface of the first three-dimensional model according to the area and the position information of the areas, needing spraying, of the first three-dimensional model; s64, generating second auxiliary tracks moving in the areas needing spraying according to the entry points and the separation points of the areas needing spraying of the first auxiliary tracks, the area of the areas and the spraying limit spraying range; and S65, integrating the first auxiliary track and the second auxiliary track to obtain first running track information capable of performing full-coverage spraying on the target workpiece.
And S7, controlling the robot spray gun to move along the first running track at a certain moving speed according to the first running track information and the first spraying parameter set, and further spraying different positions of the target workpiece by using corresponding color particles.
In the first auxiliary track and the second auxiliary track, the distance between the spray gun of the spraying robot and each spraying area is approximately the same in the moving process, so that a large amount of burrs can not appear in the sprayed paint particles, and the spraying quality is improved.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (9)
1. A robot control method for intelligent spraying of multiple vehicle types is used for identifying hubs of different vehicle types and spraying particles, and comprises the following steps: s1, detecting whether a workpiece exists in the target machining area; s2, when the workpiece exists, acquiring a first three-dimensional contour feature of the target workpiece; s3, comparing the first three-dimensional profile characteristic of the target workpiece with a three-dimensional model set of a preset hub model library, and judging whether a first three-dimensional model corresponding to the target workpiece exists in the preset hub model library or not; s4, when a first three-dimensional model corresponding to the target workpiece is determined to exist, selecting a first spraying parameter set corresponding to the first three-dimensional model from a first color spraying database; s5, according to the relative distance between each feature point of the first three-dimensional model and the space coordinates of part of the feature points in the target processing area, further acquiring space coordinate parameters corresponding to each position of the first three-dimensional model; s6, generating first running track information capable of carrying out full-coverage spraying on the target workpiece according to the space coordinate parameters corresponding to the positions of the first three-dimensional model and the limit spraying range of the spraying robot spray gun; and S7, controlling the robot spray gun to move along the first running track at a certain moving speed according to the first running track information and the first spraying parameter set, and further spraying different positions of the target workpiece by using corresponding color particles.
2. The robot control method for intelligent painting of multiple vehicle types according to claim 1, wherein the step S1 of "determining whether there is a workpiece in the target machining area" includes: s11, shooting a two-dimensional picture of the target processing area from a preset position; s12, converting the two-dimensional picture of the target processing area into a gray image; s13, comparing the gray level image with the gray level image of the two-dimensional picture shot from the same position before the target processing area when no workpiece exists; and S14, determining that the workpiece exists in the target processing area when the difference between the characteristic points of the gray level images of the two-dimensional pictures of the target processing area is detected to exceed a first preset difference value.
3. The robot control method applicable to intelligent painting of multiple vehicle types according to claim 1, wherein the step S2 of acquiring the first three-dimensional contour feature of the target workpiece specifically comprises: s21, acquiring characteristic points of each outline edge outside the target workpiece through a three-dimensional laser scanner arranged in the target processing area, and converging the characteristic points into first point cloud by adopting an automatic registration method; s22, converting each point data of the first point cloud into a first reference coordinate system; s23, denoising the first point cloud in the first reference coordinate system by adopting an average curvature flow filtering algorithm; s24, establishing a topological relation of scattered point clouds of the denoised first point cloud, and directly compressing point cloud data; and S25, performing three-dimensional reconstruction on the point cloud by adopting a micro-tangent plane method, thereby obtaining first point cloud data including the first three-dimensional contour feature of the target workpiece.
4. The robot control method for intelligent painting available for multiple vehicle types according to claim 1 or 3, characterized in that: the preset hub model library comprises hub model data of automobiles of various different vehicle types, and when the point cloud data of the first three-dimensional outline characteristic and the preset point cloud data of a certain hub model of the preset hub model library are in the same phase of 99%, the first three-dimensional model exists.
5. The robot control method for intelligent painting of multiple vehicle types according to claim 1, characterized in that: the first color spraying database stores spraying parameters corresponding to a preset hub model library, each three-dimensional model in the preset hub model library corresponds to a plurality of spraying parameter sets in the first color spraying database, and different spraying parameter sets record different spraying schemes.
6. The robot control method for intelligent painting of multiple vehicle types according to claim 5, characterized in that: when the parameter set corresponding to the first stereo model in the first color spraying database does not meet the use requirement, the parameters of the first spraying parameter set can be adjusted on line according to the first stereo model, so that a second spraying parameter set meeting the spraying requirement is obtained, and meanwhile, the second spraying parameters are stored in the first color spraying database.
7. The robot control method applicable to intelligent painting of multiple vehicle types according to claim 5, wherein the step S5 specifically includes: s51, establishing a target space coordinate system by using one end point of the target processing area; s52, selecting a plurality of edge feature points of the target workpiece, and determining corresponding positions of the edge feature points in the point cloud of the first three-dimensional model; and S53, determining the coordinates of each edge feature point in the target space coordinate system through the three-dimensional laser scanner, and obtaining the space coordinate parameters corresponding to each position of the first three-dimensional model by combining the relative position relation among the feature points in the first three-dimensional model.
8. The robot control method for intelligent painting of multiple vehicle types according to claim 1, wherein the step S6 specifically includes: s61, acquiring the limit spraying range of the spray gun of the spraying robot; s62, acquiring a region needing spraying of the first three-dimensional model from the first spraying parameter set; s63, generating a first auxiliary track which can connect the spraying areas along the surface of the first three-dimensional model according to the area and the position information of the areas, needing spraying, of the first three-dimensional model; s64, generating second auxiliary tracks moving in the areas needing spraying according to the entry points and the separation points of the areas needing spraying of the first auxiliary tracks, the area of the areas and the spraying limit spraying range; and S65, integrating the first auxiliary track and the second auxiliary track to obtain first running track information capable of performing full-coverage spraying on the target workpiece.
9. The robot control method for intelligent painting of multi-vehicle type according to claim 8, wherein the distance between the spray gun of the painting robot and each painting area during the movement is substantially the same in the first auxiliary trajectory and the second auxiliary trajectory.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911166205.6A CN111013883A (en) | 2019-11-25 | 2019-11-25 | Robot control method for intelligent spraying of multiple vehicle types |
| RU2020135400A RU2758692C1 (en) | 2019-11-25 | 2019-12-12 | Method for controlling a robot for intelligent spraying of multiple models of vehicles |
| PCT/CN2019/124736 WO2021103154A1 (en) | 2019-11-25 | 2019-12-12 | Robot control method for smart spray coating of multiple vehicle models |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911166205.6A CN111013883A (en) | 2019-11-25 | 2019-11-25 | Robot control method for intelligent spraying of multiple vehicle types |
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| CN111013883A true CN111013883A (en) | 2020-04-17 |
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| CN (1) | CN111013883A (en) |
| RU (1) | RU2758692C1 (en) |
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