CN114299237A - Intelligent identification and deletion method for single sheet metal tool model - Google Patents
Intelligent identification and deletion method for single sheet metal tool model Download PDFInfo
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- CN114299237A CN114299237A CN202111682203.XA CN202111682203A CN114299237A CN 114299237 A CN114299237 A CN 114299237A CN 202111682203 A CN202111682203 A CN 202111682203A CN 114299237 A CN114299237 A CN 114299237A
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- 230000009466 transformation Effects 0.000 claims description 3
- 238000005507 spraying Methods 0.000 description 16
- 239000003973 paint Substances 0.000 description 12
- 238000010009 beating Methods 0.000 description 6
- 238000012423 maintenance Methods 0.000 description 6
- 230000008439 repair process Effects 0.000 description 3
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Abstract
The invention discloses an intelligent identification and deletion method for a single sheet metal tool model, which comprises the following steps: s1, building a system assembly; s2, calibrating the hands and eyes of a 3D vision camera, S3, photographing the 3D vision camera, S4, establishing a tool model and S5, and deleting tool point cloud data.
Description
Technical Field
The invention relates to the technical field of intelligent spraying, in particular to an intelligent identification and deletion method for a single sheet metal tool model.
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 automobile industry, automobile manufacturers, automobile 4S shop is in the aspect of automobile paint spraying in order to avoid causing certain injury to the personnel health that sprays paint to use spraying robot to spray paint automatically basically, automobile manufacturers ' automobile that an automobile spraying production line only sprays fixed model product, and automobile 4S shop ' S automobile spraying, the motorcycle type is many, the panel beating type is different, spraying panel beating model is different at every turn, panel beating shape size is different, need design specific panel beating frock and put monolithic panel beating work of spraying paint, in the technique of three-dimensional reconstruction, need delete the point cloud data of panel beating frock earlier before the automatic spraying orbit that generates the robot, however, the mode that adopts artifical deletion is more loaded down with trivial details, operating time is of a specified duration, can't satisfy the production demand, work efficiency has been reduced.
Disclosure of Invention
The invention aims to provide an intelligent identification and deletion method for a single sheet metal tool model, which aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: an intelligent identification and deletion method for a single sheet metal tool model 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, and simultaneously 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 tooling is set in the automobile sheet metal tooling room, so that the subsequent identification work of the sheet metal tooling 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. performing manual calculation after the steps are completed, so that a rotation matrix between the robot and the 3D vision camera is calculated;
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 all the sub-steps of the step S2 are completed, the sheet metal tool is conveyed to a set tool range;
b. step S3, moving the truss after a is finished, and enabling the sheet metal tool to enter the photographing view range of the 3D vision camera;
c. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
d. setting one-time coverage characteristics of the 3D visual camera view in a photographing range;
e. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, b-c until the 3D vision camera covers the whole area;
s4, establishing a tool model;
a. storing and splicing point cloud data information obtained by photographing the 3D vision camera for multiple times obtained in the step S3, e by using 3D vision software to form a sheet metal tooling model;
s5, deleting the point cloud data of the tool;
a. placing the sheet metal part and the tool in a specific range in a production mode of 3D vision software;
b. the robot moves to a 3D visual camera photographing position, and the truss moves to the 3D visual camera photographing position;
c. step S5, after step B, when the whole area enters the photographing visual field, the 3D visual camera starts photographing to obtain point cloud data information of the whole area;
d. setting the range size of an X, Y, Z axis at the position of the tool according to the tool model;
e. the 3D vision software automatically identifies the set tool size range and automatically deletes the tool point cloud data information;
f. and automatically recognizing the end of the deleting 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, three-axis coordinate information).
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 step S5, c, after the 3D vision camera starts to photograph, the sheet metal workpiece model may be subjected to point cloud data registration with an actually produced tool, so as to set the range size of the sheet metal tool according to the registered tool point cloud data.
Compared with the prior art, the invention has the beneficial effects that:
the intelligent identification and deletion method for the single sheet metal tool model comprises the steps of shooting and splicing sheet metal tools through a single 3D vision camera, so that the model reconstruction work of the sheet metal tool appearance can be completed, an effective tool model is generated, point cloud data information comparison through data registration is performed, point cloud data of the tool model can be rapidly identified and deleted, the identification and deletion work is not needed manually, meanwhile, the intelligent identification and deletion method can be suitable for sheet metal parts of more different models and different shapes to be used, operation steps are reduced, the complexity of manual operation is reduced, the full-automatic identification and deletion effect is realized, the intelligent identification and deletion method is suitable for daily maintenance modeling of an automobile maintenance shop, the work efficiency is greatly improved, the production and work requirements are met, and the economic income is effectively increased.
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 identification and deletion method for a single sheet metal tool model 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, and simultaneously 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 tooling is set in the automobile sheet metal tooling room, so that the subsequent identification work of the sheet metal tooling 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. performing manual calculation after the steps are completed, so that a rotation matrix between the robot and the 3D vision camera is calculated;
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 all the sub-steps of the step S2 are completed, the sheet metal tool is conveyed to a set tool range;
b. step S3, moving the truss after a is finished, and enabling the sheet metal tool to enter the photographing view range of the 3D vision camera;
c. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
d. setting one-time coverage characteristics of the 3D visual camera view in a photographing range;
e. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, b-c until the 3D vision camera covers the whole area;
s4, establishing a tool model;
a. storing and splicing point cloud data information obtained by photographing the 3D vision camera for multiple times obtained in the step S3, e by using 3D vision software to form a sheet metal tooling model;
s5, deleting the point cloud data of the tool;
a. placing the sheet metal part and the tool in a specific range in a production mode of 3D vision software;
b. the robot moves to a 3D visual camera photographing position, and the truss moves to the 3D visual camera photographing position;
c. step S5, after step B, when the whole area enters the photographing visual field, the 3D visual camera starts photographing to obtain point cloud data information of the whole area;
d. setting the range size of an X, Y, Z axis at the position of the tool according to the tool model;
e. the 3D vision software automatically identifies the set tool size range and automatically deletes the tool point cloud data information;
f. and automatically recognizing the end of the deleting 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, three-axis coordinate information).
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 step S5, c, after the 3D vision camera starts to photograph, the sheet metal workpiece model may be subjected to point cloud data registration with an actually produced tool, so as to set the range size of the sheet metal tool according to the registered tool point cloud data.
The first embodiment is as follows:
an intelligent identification and deletion method for a single sheet metal tool model 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 pictures 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;
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, establishing a tool model;
a. storing and splicing point cloud data information obtained by photographing the 3D vision camera for multiple times obtained in the step S3, e by using 3D vision software to form a sheet metal tooling model;
s5, deleting the point cloud data of the tool;
a. placing the sheet metal part and the tool in a specific range in a production mode of 3D vision software;
b. the robot moves to a 3D visual camera photographing position, and the truss moves to the 3D visual camera photographing position;
c. step S5, after step B, when the whole area enters the photographing visual field, the 3D visual camera starts photographing to obtain point cloud data information of the whole area;
d. setting the range size of an X, Y, Z axis at the position of the tool according to the tool model;
e. the 3D vision software automatically identifies the set tool size range and automatically deletes the tool point cloud data information;
f. and automatically recognizing the end of the deleting work.
In the present 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.
Further, in step S2, b, the robot moves with no less than 9 sets of position feature points;
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).
Further, 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.
Further, as an alternative of the present invention, in step S5, c, after the 3D vision camera starts to take a picture, the sheet metal tooling model may be registered with the actually produced tooling point cloud data, so as to set the range size of the sheet metal tooling by the registered tooling point cloud data.
Example two:
an intelligent identification and deletion method for a single sheet metal tool model 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 pictures 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;
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, establishing a tool model;
a. storing and splicing point cloud data information obtained by photographing the 3D vision camera for multiple times obtained in the step S3, e by using 3D vision software to form a sheet metal tooling model;
s5, deleting the point cloud data of the tool;
a. placing the sheet metal part and the tool in a specific range in a production mode of 3D vision software;
b. the robot moves to a 3D visual camera photographing position, and the truss moves to the 3D visual camera photographing position;
c. step S5, after step B, when the whole area enters the photographing visual field, the 3D visual camera starts photographing to obtain point cloud data information of the whole area;
d. setting the range size of an X, Y, Z axis at the position of the tool according to the tool model;
e. the 3D vision software automatically identifies the set tool size range and automatically deletes the tool point cloud data information;
f. and automatically recognizing the end of the deleting work.
In the present 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.
Further, in step S2, b, the robot moves with no less than 9 sets of position feature points;
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).
Further, 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.
Further, as an alternative of the present invention, in step S5, c, after the 3D vision camera starts to take a picture, the sheet metal tooling model may be registered with the actually produced tooling point cloud data, so as to set the range size of the sheet metal tooling by the registered tooling point cloud data.
The intelligent identification and deletion method for the single sheet metal tool model comprises the steps of shooting and splicing sheet metal tools through a single 3D vision camera, so that the model reconstruction work of the sheet metal tool appearance can be completed, an effective tool model is generated, point cloud data information comparison through data registration is performed, point cloud data of the tool model can be rapidly identified and deleted, the identification and deletion work is not needed manually, meanwhile, the intelligent identification and deletion method can be suitable for sheet metal parts of more different models and different shapes to be used, operation steps are reduced, the complexity of manual operation is reduced, the full-automatic identification and deletion effect is realized, the intelligent identification and deletion method is suitable for daily maintenance modeling of an automobile maintenance shop, the work efficiency is greatly improved, the production and work requirements are met, and the economic income is effectively 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 (7)
1. The method for intelligently identifying and deleting the single sheet metal tool model is characterized by comprising the following steps of:
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, and simultaneously 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 tooling is set in the automobile sheet metal tooling room, so that the subsequent identification work of the sheet metal tooling 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. performing manual calculation after the steps are completed, so that a rotation matrix between the robot and the 3D vision camera is calculated;
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 all the sub-steps of the step S2 are completed, the sheet metal tool is conveyed to a set tool range;
b. step S3, moving the truss after a is finished, and enabling the sheet metal tool to enter the photographing view range of the 3D vision camera;
c. the 3D vision camera takes a picture to acquire point cloud data information and carries out filtering processing;
d. setting one-time coverage characteristics of the 3D visual camera view in a photographing range;
e. if the vision software of the 3D vision camera cannot complete the one-time coverage effect, repeating the steps S3, b-c until the 3D vision camera covers the whole area;
s4, establishing a tool model;
a. storing and splicing point cloud data information obtained by photographing the 3D vision camera for multiple times obtained in the step S3, e by using 3D vision software to form a sheet metal tooling model;
s5, deleting the point cloud data of the tool;
a. placing the sheet metal part and the tool in a specific range in a production mode of 3D vision software;
b. the robot moves to a 3D visual camera photographing position, and the truss moves to the 3D visual camera photographing position;
c. step S5, after step B, when the whole area enters the photographing visual field, the 3D visual camera starts photographing to obtain point cloud data information of the whole area;
d. setting the range size of an X, Y, Z axis at the position of the tool according to the tool model;
e. the 3D vision software automatically identifies the set tool size range and automatically deletes the tool point cloud data information;
f. and automatically recognizing the end of the deleting work.
2. The intelligent identification and deletion method for the single sheet metal tool model according to claim 1, characterized in that: in the step S1, a, the robot is a six-axis jig robot.
3. The intelligent identification and deletion method for the single sheet metal tool model according to claim 1, 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 identification and deletion method for the single sheet metal tool model according to claim 1, 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 identification and deletion method for the single sheet metal tool model according to claim 1, characterized in that: in step S3, b, the point cloud data information is coordinate information (X, Y, Z axis, three-axis coordinate information).
6. The intelligent identification and deletion method for the single sheet metal tool model according to claim 1, 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 identification and deletion method for the single sheet metal tool model according to claim 1, characterized in that: in step S5, c, after the 3D vision camera starts to photograph, the sheet metal workpiece model may be subjected to point cloud data registration with an actually produced tool, so as to set the range size of the sheet metal tool by the point cloud data of the tool after registration.
Priority Applications (1)
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