CN114310890A - Intelligent frame-selection paint spraying method for front and rear bar metal plate paint spraying areas - Google Patents
Intelligent frame-selection paint spraying method for front and rear bar metal plate paint spraying areas Download PDFInfo
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- CN114310890A CN114310890A CN202111633319.4A CN202111633319A CN114310890A CN 114310890 A CN114310890 A CN 114310890A CN 202111633319 A CN202111633319 A CN 202111633319A CN 114310890 A CN114310890 A CN 114310890A
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- 238000005507 spraying Methods 0.000 title claims abstract description 105
- 239000002184 metal Substances 0.000 title claims abstract description 89
- 229910052751 metal Inorganic materials 0.000 title claims abstract description 89
- 239000003973 paint Substances 0.000 title claims abstract description 84
- 230000000007 visual effect Effects 0.000 claims description 53
- 238000010422 painting Methods 0.000 claims description 51
- 238000009432 framing Methods 0.000 claims description 29
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- 238000009434 installation Methods 0.000 abstract 1
- 230000033001 locomotion Effects 0.000 description 8
- 238000012423 maintenance Methods 0.000 description 7
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Abstract
The invention discloses an intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area, which comprises the following steps: s1, building a system assembly; a. preparing device equipment required for building a system assembly; the equipment comprises but not limited to an industrial personal computer, a display, a control electric cabinet, a 3D camera calibration board, an XY-axis truss, a robot and a 3D vision camera, b, step S1, the 3D vision camera prepared in the step A is installed on a six-axis clamp of the robot, thereby completing the fixed installation work of the 3D vision camera, the intelligent frame-selection paint spraying method for the front and rear bar metal plate paint spraying areas is characterized in that the metal plate is photographed and spliced through a single 3D vision camera, the sheet metal part appearance reconstruction work can be completed quickly, meanwhile, each area of the metal plate needing paint spraying work can be subdivided, a specific and unique paint spraying space range is formed, and the paint spraying method can automatically frame-select each point cloud area quickly to generate effective spraying data information until the whole block of the metal plate is framed and selected completely.
Description
Technical Field
The invention relates to the technical field of intelligent spraying, in particular to an intelligent frame-selecting paint spraying method for a front and rear bar metal plate paint spraying area.
Background
The automobile metal plate is a processing method for automobile maintenance, which is called cold working, namely direct point, if the appearance of an automobile body is damaged and deformed, the metal plate is needed, automobile collision repair is developed from original 'smashing, pulling, welding and repairing' into automobile body secondary manufacturing and assembling, the repair of a vehicle in a collision accident is not simple to beat and beat the automobile metal plate, the repair quality cannot be observed by naked eyes, and a maintenance worker needs to know the technical parameters and the external dimensions of the automobile body, needs to master the characteristics of the automobile body material, and transmits the deformation tendency and the stress point of the automobile body and the production process of the automobile body, such as a welding process and the like.
In the current automotive industry, automobile manufacturers, automobile 4S shop in the aspect of automobile paint spraying in order to avoid causing certain injury to the personnel health of spraying paint to use spraying robot automatic paint spraying basically, automobile manufacturers 'automobile of the fixed model product of automobile spraying production line only spraying, to the spraying orbit of robot, generally accomplish through artifical teaching, and the automobile maintenance shop or the automobile spraying in 4S shop, the motorcycle type is many, the panel beating type is different, spraying panel beating model is different at every turn, the shape size of panel beating is different, especially to the more complicated sheet metal component of this kind of panel beating face of front and back thick stick, need divide into a plurality of regions and accomplish the work of spraying paint, the mode of adopting artifical frame to select is more loaded down with trivial details, operating time is of a specified duration, can't satisfy the production demand.
Disclosure of Invention
The invention aims to provide an intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area, and aims to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: an intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area comprises the following steps:
s1, building a system assembly;
a. preparing device equipment required for building a system assembly; the equipment comprises but is not limited to an industrial personal computer, a display, a control cabinet, a 3D camera calibration board, an XY axis truss, a robot and a 3D vision camera;
b. mounting the 3D vision camera prepared in the step S1, a on a six-axis jig of the robot, thereby completing the fixed mounting work of the 3D vision camera;
c. hoisting the robot provided with the 3D vision camera obtained in the step S1 and b on an XY-axis truss;
d. the placing range of the automobile sheet metal part is set in the automobile sheet metal paint spraying room, so that the subsequent processing work of sheet metal paint spraying is facilitated;
e. teaching tool coordinates of the robot in step S1, c;
s2, calibrating the hand and the eye of the 3D vision camera;
a. after the 3D vision camera is installed, the calibration plate is placed in the visual field range of the robot, and normal calibration and debugging work of the 3D vision camera is guaranteed;
b. moving the robot to the position of the characteristic point of the calibration plate, and recording the current position data information of the robot;
c. after the data recording is finished, photographing by the 3D vision camera to identify the feature points, and recording specific position data information of the feature points;
d. after the steps are completed, a rotation matrix between the robot and the 3D vision camera is calculated manually;
e. when the calculation of step S2 and d is completed, storing the data parameters, and ending the calibration;
s3, taking a picture by the 3D visual camera;
a. when the whole substeps of the step S2 are completely finished, the sheet metal part needing paint spraying enters the photographing visual field range of the 3D visual camera, and the truss stops moving at the moment;
b. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
c. setting one-time coverage characteristics of the 3D visual camera view in the paint spraying range;
d. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, a-c until the 3D vision camera covers the whole area;
e. splicing point cloud data acquired by photographing for multiple times by using a 3D visual camera together by using 3D visual software;
s4, displaying point cloud data;
a. transmitting the spliced point cloud data information obtained in the step S3, e to 3D visual software;
b. displaying and checking by using 3D vision software, checking whether the point cloud data splicing is complete, and repeating the step S3, e if splicing omission occurs;
s5, automatically selecting a painting area to generate a painting path;
a. storing the point cloud data obtained in the step S4 and b after splicing the whole sheet metal part, and performing area number subdivision processing;
b. according to the subdivided region range obtained in the step S5, automatically selecting the painting regions in sequence, and generating the painting paths in the single region;
c. determining whether the sheet metal part is completely framed, and if the omission of framing occurs, repeating the step S5 and the step B;
s6, data transmission and robot paint spraying;
a. carrying out path data transmission on the framing information obtained in the step s5 and c after framing;
b. the robot receives the painting path data information in step S6, a;
c. the robot reads and executes the painting action;
d. and finishing the intelligent frame selection paint spraying work.
Preferably, in step S1, the robot is a six-axis jig robot.
Preferably, in step S2, b, the robot needs to move different positions in the calibration board and perform data recording operation when moving.
Preferably, in step S2, b, the robot moves with no less than 9 sets of position feature points, and performs data calculation by using a least square method, and obtains a transformation relation between the robot coordinate system and the 3D vision coordinate system.
Preferably, in step S3, b, the point cloud data information is coordinate information (X, Y, Z axis).
Preferably, the point cloud data processing includes filtering the point cloud data, filtering out interference point cloud and invalid point cloud data information, and storing valid point cloud information data.
Preferably, in the step S5, the framing manner in the step S5 is that after each frame of the whole sheet metal part is finished, the point cloud data information in the area range is automatically shielded until the framing of the whole sheet metal part is finished.
Preferably, the data terminal for receiving the framing path information in S6, a is an industrial personal computer, and the industrial personal computer is connected to the robot through an ethernet network.
Compared with the prior art, the invention has the beneficial effects that:
according to the intelligent frame-selection paint spraying method for the front and rear bar metal plate paint spraying areas, a single 3D vision camera is used for shooting and splicing the metal plate, the appearance reconstruction work of the metal plate can be completed quickly, and meanwhile, each area of the metal plate needing paint spraying can be subdivided to form a specific and unique paint spraying space range;
and the painting method can automatically and rapidly select each painting area, generate effective painting point cloud data information, and can be adapted to painting of more sheet metal parts of different types and shapes without manual frame selection until the whole sheet metal part is completely selected, thereby reducing operation steps, reducing the painting complexity, realizing full-automatic painting effect, being suitable for daily painting maintenance of an automobile maintenance shop, greatly improving the working efficiency and increasing the economic income.
Drawings
FIG. 1 is a block diagram of a main process flow of the present invention;
fig. 2 is a schematic view of a 3D camera calibration flow structure according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: an intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area comprises the following steps:
s1, building a system assembly;
a. preparing device equipment required for building a system assembly; the equipment comprises but is not limited to an industrial personal computer, a display, a control cabinet, a 3D camera calibration board, an XY axis truss, a robot and a 3D vision camera;
b. mounting the 3D vision camera prepared in the step S1, a on a six-axis jig of the robot, thereby completing the fixed mounting work of the 3D vision camera;
c. hoisting the robot provided with the 3D vision camera obtained in the step S1 and b on an XY-axis truss;
d. the placing range of the automobile sheet metal part is set in the automobile sheet metal paint spraying room, so that the subsequent processing work of sheet metal paint spraying is facilitated;
e. teaching tool coordinates of the robot in step S1, c;
s2, calibrating the hand and the eye of the 3D vision camera;
a. after the 3D vision camera is installed, the calibration plate is placed in the visual field range of the robot, and normal calibration and debugging work of the 3D vision camera is guaranteed;
b. moving the robot to the position of the characteristic point of the calibration plate, and recording the current position data information of the robot;
c. after the data recording is finished, photographing by the 3D vision camera to identify the feature points, and recording specific position data information of the feature points;
d. after the steps are completed, a rotation matrix between the robot and the 3D vision camera is calculated manually;
e. when the calculation of step S2 and d is completed, storing the data parameters, and ending the calibration;
s3, taking a picture by the 3D visual camera;
a. when the whole substeps of the step S2 are completely finished, the sheet metal part needing paint spraying enters the photographing visual field range of the 3D visual camera, and the truss stops moving at the moment;
b. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
c. setting one-time coverage characteristics of the 3D visual camera view in the paint spraying range;
d. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, a-c until the 3D vision camera covers the whole area;
e. splicing point cloud data acquired by photographing for multiple times by using a 3D visual camera together by using 3D visual software;
s4, displaying point cloud data;
a. transmitting the spliced point cloud data information obtained in the step S3, e to 3D visual software;
b. displaying and checking by using 3D vision software, checking whether the point cloud data splicing is complete, and repeating the step S3, e if splicing omission occurs;
s5, automatically selecting a painting area to generate a painting path;
a. storing the point cloud data obtained in the step S4 and b after splicing the whole sheet metal part, and performing area number subdivision processing;
b. according to the subdivided region range obtained in the step S5, automatically selecting the painting regions in sequence, and generating the painting paths in the single region;
c. determining whether the sheet metal part is completely framed, and if the omission of framing occurs, repeating the step S5 and the step B;
s6, data transmission and robot paint spraying;
a. carrying out path data transmission on the framing information obtained in the step s5 and c after framing;
b. the robot receives the painting path data information in step S6, a;
c. the robot reads and executes the painting action;
d. and finishing the intelligent frame selection paint spraying work.
Preferably, in step S1, the robot is a six-axis jig robot.
Preferably, in step S2, b, the robot needs to move different positions in the calibration board and perform data recording operation when moving.
Preferably, in step S2, b, the robot moves with no less than 9 sets of position feature points, and performs data calculation by using a least square method, and obtains a transformation relation between the robot coordinate system and the 3D vision coordinate system.
Preferably, in step S3, b, the point cloud data information is coordinate information (X, Y, Z axis).
Preferably, the point cloud data processing includes filtering the point cloud data, filtering out interference point cloud and invalid point cloud data information, and storing valid point cloud information data.
Preferably, in the step S5, the framing manner in the step S5 is that after each frame of the whole sheet metal part is finished, the point cloud data information in the area range is automatically shielded until the framing of the whole sheet metal part is finished.
Preferably, the data terminal for receiving the framing path information in S6, a is an industrial personal computer, and the industrial personal computer is connected to the robot through an ethernet network.
The first embodiment is as follows:
an intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area comprises the following steps:
s1, building a system assembly;
a. preparing device equipment required for building a system assembly; the equipment comprises but is not limited to an industrial personal computer, a display, a control cabinet, a 3D camera calibration board, an XY axis truss, a robot and a 3D vision camera;
b. mounting the 3D vision camera prepared in the step S1, a on a six-axis jig of the robot, thereby completing the fixed mounting work of the 3D vision camera;
c. hoisting the robot provided with the 3D vision camera obtained in the step S1 and b on an XY-axis truss;
d. the placing range of the automobile sheet metal part is set in the automobile sheet metal paint spraying room, so that the subsequent processing work of sheet metal paint spraying is facilitated;
e. teaching tool coordinates of the robot in step S1, c;
s2, calibrating the hand and the eye of the 3D vision camera;
a. after the 3D vision camera is installed, the calibration plate is placed in the visual field range of the robot, and normal calibration and debugging work of the 3D vision camera is guaranteed;
b. moving the robot to the position of the characteristic point of the calibration plate, and recording the current position data information of the robot;
c. after the data recording is finished, photographing by the 3D vision camera to identify the feature points, and recording specific position data information of the feature points;
d. after the steps are completed, a rotation matrix between the robot and the 3D vision camera is calculated manually;
e. when the calculation of step S2 and d is completed, storing the data parameters, and ending the calibration;
wherein, the robot position is P1, and the 3D vision characteristic point position is P2:
the positional relationship between the robot and the 3D vision camera may be expressed as:
P1＝X*P2
wherein each symbol means:
p1: robot position coordinates;
p2: a 3D visual camera visual position coordinate;
r: a rotation matrix of the robot and camera positional relationship;
t: an offset matrix of robot and camera positional relationships.
S3, taking a picture by the 3D visual camera;
a. when the whole substeps of the step S2 are completely finished, the sheet metal part needing paint spraying enters the photographing visual field range of the 3D visual camera, and the truss stops moving at the moment;
b. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
c. setting one-time coverage characteristics of the 3D visual camera view in the paint spraying range;
d. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, a-c until the 3D vision camera covers the whole area;
e. splicing point cloud data acquired by photographing for multiple times by using a 3D visual camera together by using 3D visual software;
wherein the stitched point cloud relationship can be expressed as:
PC2＝PC1+P
wherein each symbol means:
PC 1: a first photographing coordinate value of the 3D visual camera;
PC 2: coordinate values of the 3D visual camera stitching data;
p: the offset of the truss.
S4, displaying point cloud data;
a. transmitting the spliced point cloud data information obtained in the step S3, e to 3D visual software;
b. displaying and checking by using 3D vision software, checking whether the point cloud data splicing is complete, and repeating the step S3, e if splicing omission occurs;
s5, automatically selecting a painting area to generate a painting path;
a. storing the point cloud data obtained in the step S4 and b after splicing the whole sheet metal part, and performing area number subdivision processing;
b. according to the subdivided region range obtained in the step S5, automatically selecting the painting regions in sequence, and generating the painting paths in the single region;
c. determining whether the sheet metal part is completely framed, and if the omission of framing occurs, repeating the step S5 and the step B;
referring to fig. 1, after acquiring point cloud data of a whole sheet metal part in steps S4 and S5, selecting a subdivided area number to be stored at present, automatically framing the sheet metal part according to a paint spraying space range set in the area and generating an effective spraying path, and automatically shielding the point cloud data of the area range after each frame of the area is selected until the whole sheet metal part is framed and selected;
meanwhile, the 3D vision cameras are spliced and converted into the spraying point cloud data of the robot, the spraying paths of all the subdivided areas of the sheet metal part are spliced together according to the model of the sheet metal part, the spraying paths of the whole sheet metal part are formed, the spraying paths are displayed and checked in the 3D vision software, and whether the point cloud data is spliced completely or not is checked.
S6, data transmission and robot paint spraying;
a. carrying out path data transmission on the framing information obtained in the step s5 and c after framing;
b. the robot receives the painting path data information in step S6, a;
c. the robot reads and executes the painting action;
d. and finishing the intelligent frame selection paint spraying work.
Further, in step S6, the obtained robot motion trajectory is divided into one or more times according to the motion range of the truss-matched robot to complete the painting, and the multiple painting data of the robot may be represented as:
Pn＝Pv+Pm
wherein each symbol means:
pn: and the robot generates point position data for each painting.
Pv: and (5) converting the transformed spraying point locus data.
Pm: compensation value for each movement of the painted truss.
In this embodiment, the robot in step S1, a is a six-axis jig robot.
In this embodiment, in step S2, b, the robot needs to move different positions in the calibration board and perform data recording operation when moving.
In this embodiment, in step S2, b, the robot has no less than 9 sets of position feature points during movement;
during actual implementation, 9 groups of robot positions and 9 groups of 3D vision camera calibration point positions are recorded respectively, and then R and T are calculated by using a least square method to obtain a conversion relation X between a robot coordinate system and a 3D vision coordinate system.
In this embodiment, in step S3, b, the point cloud data information is coordinate information (X, Y, Z axis).
In this embodiment, the point cloud data processing includes filtering the point cloud data, filtering out interference point cloud and invalid point cloud data information, and storing valid point cloud information data.
In this embodiment, in the step S5, b, the framing manner is that after each frame is finished, the point cloud data information in the area range is automatically shielded until the whole sheet metal part is framed.
In this embodiment, the data terminal for receiving framing path information in S6, a is an industrial personal computer, and the industrial personal computer is connected to the robot through an ethernet network.
Example two:
an intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area comprises the following steps:
s1, building a system assembly;
a. preparing device equipment required for building a system assembly; the equipment comprises but is not limited to an industrial personal computer, a display, a control cabinet, a 3D camera calibration board, an XY axis truss, a robot and a 3D vision camera;
b. mounting the 3D vision camera prepared in the step S1, a on a six-axis jig of the robot, thereby completing the fixed mounting work of the 3D vision camera;
c. hoisting the robot provided with the 3D vision camera obtained in the step S1 and b on an XY-axis truss;
d. the placing range of the automobile sheet metal part is set in the automobile sheet metal paint spraying room, so that the subsequent processing work of sheet metal paint spraying is facilitated;
e. teaching tool coordinates of the robot in step S1, c;
s2, calibrating the hand and the eye of the 3D vision camera;
a. after the 3D vision camera is installed, the calibration plate is placed in the visual field range of the robot, and normal calibration and debugging work of the 3D vision camera is guaranteed;
b. moving the robot to the position of the characteristic point of the calibration plate, and recording the current position data information of the robot;
c. after the data recording is finished, photographing by the 3D vision camera to identify the feature points, and recording specific position data information of the feature points;
d. after the steps are completed, a rotation matrix between the robot and the 3D vision camera is calculated manually;
e. when the calculation of step S2 and d is completed, storing the data parameters, and ending the calibration;
wherein, this mode is in order to convert the data under the 3D vision coordinate system to the robot coordinate system, need carry out the hand eye with robot and 3D vision and mark, the 3D camera is fixed on the six-axis flange of robot, install the calibration plate in the field of vision scope of 3D camera, the robot moves to different positions at the calibration plate, and record position data, the position of 3D visual identification calibration plate characteristic point, the robot position is P1, 3D visual characteristic point is P2:
the positional relationship between the robot and the 3D vision camera may be expressed as:
P1＝X*P2
wherein each symbol means:
p1: robot position coordinates;
p2: a 3D visual camera visual position coordinate;
r: a rotation matrix of the robot and camera positional relationship;
t: an offset matrix of robot and camera positional relationships.
S3, taking a picture by the 3D visual camera;
a. when the whole substeps of the step S2 are completely finished, the sheet metal part needing paint spraying enters the photographing visual field range of the 3D visual camera, and the truss stops moving at the moment;
b. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
c. setting one-time coverage characteristics of the 3D visual camera view in the paint spraying range;
d. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, a-c until the 3D vision camera covers the whole area;
e. splicing point cloud data acquired by photographing for multiple times by using a 3D visual camera together by using 3D visual software;
further, in a set range, if the 3D vision software cannot cover the whole area at one time, the truss needs to be moved again to start the 3D vision camera to take a picture, point cloud data is acquired until the 3D vision camera covers the whole area, then the point cloud data acquired by the 3D vision software for many times are spliced together, and the spliced point cloud relationship can be expressed as:
PC2＝PC1+P
wherein each symbol means:
PC 1: a first photographing coordinate value of the 3D visual camera;
PC 2: coordinate values of the 3D visual camera stitching data;
p: the offset of the truss.
Referring to fig. 1, in the step, all parameters are set before the main process automatically runs, a sheet metal part is placed in a specific area, a robot moves to a photographing position of a 3D visual camera, a truss moves to the photographing position of the 3D visual camera, after the sheet metal part enters a photographing field of vision, the 3D camera starts photographing to obtain point cloud data, point cloud data information comprises coordinates (X, Y, Z), filtering is performed on the point cloud data, and interference point cloud and invalid point cloud data are filtered out
S4, displaying point cloud data;
a. transmitting the spliced point cloud data information obtained in the step S3, e to 3D visual software;
b. displaying and checking by using 3D vision software, checking whether the point cloud data splicing is complete, and repeating the step S3, e if splicing omission occurs;
s5, automatically selecting a painting area to generate a painting path;
a. storing the point cloud data obtained in the step S4 and b after splicing the whole sheet metal part, and performing area number subdivision processing;
b. according to the subdivided region range obtained in the step S5, automatically selecting the painting regions in sequence, and generating the painting paths in the single region;
c. determining whether the sheet metal part is completely framed, and if the omission of framing occurs, repeating the step S5 and the step B;
referring to fig. 1, after acquiring point cloud data of a whole sheet metal part in steps S4 and S5, selecting a subdivided area number to be stored at present, automatically framing the sheet metal part according to a paint spraying space range set in the area and generating an effective spraying path, and automatically shielding the point cloud data of the area range after each frame of the area is selected until the whole sheet metal part is framed and selected;
meanwhile, the 3D vision cameras are spliced and converted into the spraying point cloud data of the robot, the spraying paths of all the subdivided areas of the sheet metal part are spliced together according to the model of the sheet metal part, the spraying paths of the whole sheet metal part are formed, the spraying paths are displayed and checked in the 3D vision software, and whether the point cloud data is spliced completely or not is checked.
S6, data transmission and robot paint spraying;
a. carrying out path data transmission on the framing information obtained in the step s5 and c after framing;
b. the robot receives the painting path data information in step S6, a;
c. the robot reads and executes the painting action;
d. and finishing the intelligent frame selection paint spraying work.
Further, in step S6, the obtained robot motion trajectory is divided into one or more times according to the motion range of the truss-matched robot to complete the painting, and the multiple painting data of the robot may be represented as:
Pn＝Pv+Pm
wherein each symbol means:
pn: and the robot generates point position data for each painting.
Pv: and (5) converting the transformed spraying point locus data.
Pm: compensation value for each movement of the painted truss.
In this embodiment, the robot in step S1, a is a six-axis jig robot.
In this embodiment, in step S2, b, the robot needs to move different positions in the calibration board and perform data recording operation when moving.
In this embodiment, in step S2, b, the robot has no less than 9 sets of position feature points during movement;
during actual implementation, 9 groups of robot positions and 9 groups of 3D vision camera calibration point positions are recorded respectively, and then R and T are calculated by using a least square method to obtain a conversion relation X between a robot coordinate system and a 3D vision coordinate system.
In this embodiment, in step S3, b, the point cloud data information is coordinate information (X, Y, Z axis).
In this embodiment, the point cloud data processing includes filtering the point cloud data, filtering out interference point cloud and invalid point cloud data information, and storing valid point cloud information data.
In this embodiment, in the step S5, b, the framing manner is that after each frame is finished, the point cloud data information in the area range is automatically shielded until the whole sheet metal part is framed.
In this embodiment, the data terminal for receiving framing and routing information in S6, a is an industrial personal computer, the industrial personal computer is in network connection with the robot in an ethernet manner, the industrial personal computer sends the robot spraying trajectory data to the robot, and the truss cooperates with the robot to perform a paint spraying action.
According to the intelligent frame-selection paint spraying method for the front and rear bar metal plate paint spraying areas, a single 3D vision camera is used for shooting and splicing the metal plate, the appearance reconstruction work of the metal plate can be completed quickly, and meanwhile, each area of the metal plate needing paint spraying can be subdivided to form a specific and unique paint spraying space range;
and the painting method can automatically and rapidly select each painting area to generate effective painting point cloud data information, and can adapt to more sheet metal parts of different types and shapes for painting until the whole sheet metal part is selected, so that the operation steps are reduced, the painting complexity is reduced, the full-automatic painting effect is realized, the painting method is suitable for daily maintenance and painting of an automobile maintenance shop, the working efficiency is greatly improved, and the economic income is increased.
In the description of the present invention, it is to be understood that the terms "coaxial", "bottom", "one end", "top", "middle", "other end", "upper", "one side", "top", "inner", "front", "center", "both ends", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the referenced device or element must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
Furthermore, the terms "first", "second", "third", "fourth" are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated, whereby the features defined as "first", "second", "third", "fourth" may explicitly or implicitly include at least one such feature.
In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "disposed," "connected," "secured," "screwed" and the like are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; the terms may be directly connected or indirectly connected through an intermediate, and may be communication between two elements or interaction relationship between two elements, unless otherwise specifically limited, and the specific meaning of the terms in the present invention will be understood by those skilled in the art according to specific situations.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. An intelligent frame-selection paint spraying method for a front and rear bar metal plate paint spraying area is characterized by comprising the following steps:
s1, building a system assembly;
a. preparing device equipment required for building a system assembly; the equipment comprises but is not limited to an industrial personal computer, a display, a control cabinet, a 3D camera calibration board, an XY axis truss, a robot and a 3D vision camera;
b. mounting the 3D vision camera prepared in the step S1, a on a six-axis jig of the robot, thereby completing the fixed mounting work of the 3D vision camera;
c. hoisting the robot provided with the 3D vision camera obtained in the step S1 and b on an XY-axis truss;
d. the placing range of the automobile sheet metal part is set in the automobile sheet metal paint spraying room, so that the subsequent processing work of sheet metal paint spraying is facilitated;
e. teaching tool coordinates of the robot in step S1, c;
s2, calibrating the hand and the eye of the 3D vision camera;
a. after the 3D vision camera is installed, the calibration plate is placed in the visual field range of the robot, and normal calibration and debugging work of the 3D vision camera is guaranteed;
b. moving the robot to the position of the characteristic point of the calibration plate, and recording the current position data information of the robot;
c. after the data recording is finished, photographing by the 3D vision camera to identify the feature points, and recording specific position data information of the feature points;
d. after the steps are completed, a rotation matrix between the robot and the 3D vision camera is calculated manually;
e. when the calculation of step S2 and d is completed, storing the data parameters, and ending the calibration;
s3, taking a picture by the 3D visual camera;
a. when the whole substeps of the step S2 are completely finished, the sheet metal part needing paint spraying enters the photographing visual field range of the 3D visual camera, and the truss stops moving at the moment;
b. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
c. setting one-time coverage characteristics of the 3D visual camera view in the paint spraying range;
d. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, a-c until the 3D vision camera covers the whole area;
e. splicing point cloud data acquired by photographing for multiple times by using a 3D visual camera together by using 3D visual software;
s4, displaying point cloud data;
a. transmitting the spliced point cloud data information obtained in the step S3, e to 3D visual software;
b. displaying and checking by using 3D vision software, checking whether the point cloud data splicing is complete, and repeating the step S3, e if splicing omission occurs;
s5, automatically selecting a painting area to generate a painting path;
a. storing the point cloud data obtained in the step S4 and b after splicing the whole sheet metal part, and performing area number subdivision processing;
b. according to the subdivided region range obtained in the step S5, automatically selecting the painting regions in sequence, and generating the painting paths in the single region;
c. determining whether the sheet metal part is completely framed, and if the omission of framing occurs, repeating the step S5 and the step B;
s6, data transmission and robot paint spraying;
a. carrying out path data transmission on the framing information obtained in the step s5 and c after framing;
b. the robot receives the painting path data information in step S6, a;
c. the robot reads and executes the painting action;
d. and finishing the intelligent frame selection paint spraying work.
2. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: in the step S1, a, the robot is a six-axis jig robot.
3. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: in step S2, b, the robot needs to move different positions in the calibration board and perform data recording operation when moving.
4. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: in step S2, b, the robot moves with no less than 9 sets of position feature points, and performs data calculation by using a least square method, and obtains a transformation relationship between the robot coordinate system and the 3D visual coordinate system.
5. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: in step S3, b, the point cloud data information is coordinate information (X, Y, Z axis).
6. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: the point cloud data processing comprises filtering the point cloud data, filtering out interference point cloud and invalid point cloud data information, and storing valid point cloud information data.
7. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: in the step S5, b, the framing mode is that after each frame is finished, one area automatically shields the point cloud data information in the area range until the whole sheet metal part is framed.
8. The intelligent frame-selecting paint spraying method for the front and rear bumper sheet metal paint spraying areas according to claim 1, is characterized in that: and in the S6, a, the data terminal for receiving the framing path information is an industrial personal computer, and the industrial personal computer is in network connection with the robot in an Ethernet mode.
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