CN115409809A - Weld joint recognition method and device, welding robot and storage medium - Google Patents
Weld joint recognition method and device, welding robot and storage medium Download PDFInfo
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Abstract
The application provides a welding seam identification method and device, a welding robot and a storage medium. The weld joint identification method comprises the following steps: acquiring three-dimensional point cloud data of a V-shaped groove workpiece; carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes; extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; on the basis of the vertical feet of a plurality of adjacent points on the corresponding intersecting straight line, comparing the distance between every two vertical feet on the intersecting straight line to obtain two target vertical feet corresponding to the maximum distance; and identifying the point of the target foot on the intersecting straight line as the weld joint characteristic point of the V-shaped groove workpiece. According to the method and the device, the efficiency of identifying the weld characteristic points of the V-shaped groove workpiece can be improved, and meanwhile, the accuracy of identifying the weld characteristic points of the V-shaped groove workpiece is also improved.
Description
Technical Field
The application relates to the technical field of welding, in particular to a welding seam identification method and device, a welding robot and a storage medium.
Background
In the robot welding technology, it is necessary to recognize a weld of a workpiece in order to perform welding. At present, a linear laser scanning robot welding and an artificial teaching programming robot welding are mainly adopted, the accuracy of the linear laser scanning robot welding on the weld joint identification of a V-shaped groove workpiece is poor, and the artificial teaching programming robot welding is troublesome in operation and low in weld joint identification efficiency. Therefore, the existing mode of carrying out weld joint identification on the V-shaped groove workpiece is difficult to realize both efficiency and accuracy.
Disclosure of Invention
An object of the present application is to provide a weld recognition method, a weld recognition apparatus, a welding robot, and a storage medium, which improve the accuracy of recognizing weld characteristic points of a V-groove workpiece while improving the efficiency of recognizing weld characteristic points of a V-groove workpiece, at least to some extent.
According to an aspect of an embodiment of the present application, there is provided a weld identifying method including:
acquiring three-dimensional point cloud data of a V-shaped groove workpiece;
carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes;
extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight lines;
based on the vertical feet of a plurality of adjacent points on the corresponding intersecting straight line, comparing the distance between every two vertical feet on the intersecting straight line to obtain two target vertical feet corresponding to the maximum distance;
identifying the point of the target foot on the intersecting straight line as a weld characteristic point of the V-groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
According to an aspect of an embodiment of the present application, there is provided a weld identifying apparatus including:
the acquisition module is used for acquiring three-dimensional point cloud data of the V-shaped groove workpiece;
the intersection straight line detection module is used for carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes;
the adjacent point extraction module is used for extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight line;
the distance comparison module is used for comparing the distance between every two vertical feet on the intersecting straight line based on the vertical feet of the adjacent points on the corresponding intersecting straight line to obtain two target vertical feet corresponding to the maximum distance;
the welding seam characteristic point identification module is used for identifying the point of the target foot on the intersecting straight line as the welding seam characteristic point of the V-shaped groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
In some embodiments of the present application, based on the above technical solutions, the weld identifying apparatus is configured to:
performing plane segmentation processing on the three-dimensional point cloud data to obtain at least two planes corresponding to the V-shaped groove workpiece; the at least two planes comprise at least two planes of a horizontal plane, a first inclined plane and a second inclined plane corresponding to the V-groove workpiece;
respectively detecting intersecting straight lines between every two planes to obtain the intersecting straight lines; the intersecting straight line comprises at least one of a first straight line, a second straight line and a third straight line; the first straight line is a straight line where the horizontal plane intersects with the first inclined plane, the second straight line is a straight line where the horizontal plane intersects with the second inclined plane, and the third straight line is a straight line where the first inclined plane intersects with the second inclined plane.
In some embodiments of the present application, based on the above technical solutions, the weld joint identification apparatus is configured to:
detecting the distance between each point in the three-dimensional point cloud data and the intersecting straight line;
all points in the three-dimensional point cloud data with the distance smaller than or equal to a preset distance are used as the adjacent points;
projecting each adjacent point to the intersecting straight line to obtain a foot of each adjacent point on the intersecting straight line;
determining the distance between every two drop feet;
comparing the distance between every two vertical feet to obtain the maximum distance;
two target footholds corresponding to the maximum distance are acquired.
In some embodiments of the present application, based on the above technical solutions, the weld identifying apparatus is configured to:
acquiring original three-dimensional point cloud data for the V-groove workpiece;
performing coordinate conversion on the original three-dimensional point cloud data to obtain actual three-dimensional point cloud data under a welding robot base coordinate system;
and clustering the actual three-dimensional point cloud data to obtain the three-dimensional point cloud data.
In some embodiments of the present application, based on the above technical solutions, the weld identifying apparatus is configured to:
acquiring a value range of the actual three-dimensional point cloud data on a preset dimension;
traversing each point in the actual three-dimensional point cloud data, and determining the value of the point on the preset dimension; the preset dimension is a preset dimension used for indicating the direction towards the ground;
acquiring all points of which the values are not in the value range;
filtering all points with values not in the value range to obtain real three-dimensional point cloud data;
sampling the real three-dimensional point cloud data to obtain sampled three-dimensional point cloud data;
and clustering the sampled three-dimensional point cloud data to obtain a spatial noise point and target three-dimensional point cloud data, and taking the target three-dimensional point cloud data as the three-dimensional point cloud data.
In some embodiments of the present application, based on the above technical solutions, the weld joint identification apparatus is configured to:
and performing coordinate conversion on the original three-dimensional point cloud data based on the attitude matrix of the tool central point at the end of the welding robot and the robot eye matrix to obtain actual three-dimensional point cloud data under the welding robot base coordinate system.
In some embodiments of the present application, based on the above technical solutions, the weld identifying apparatus is configured to:
and welding the V-shaped groove workpiece based on the weld joint characteristic points of the V-shaped groove workpiece.
According to an aspect of an embodiment of the present application, there is provided a welding robot including: one or more processors; a storage device for storing one or more programs that, when executed by the one or more processors, cause the welding robot to implement the methods provided in the various alternative implementations described above.
According to an aspect of embodiments of the present application, there is provided a computer program medium having stored thereon computer readable instructions, which, when executed by a processor of a computer, cause the computer to perform the method provided in the above various alternative implementations.
According to an aspect of embodiments herein, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided in the above-mentioned various alternative implementation modes.
According to the technical scheme, the method comprises the steps of dividing each plane of the V-shaped groove workpiece by combining three-dimensional point cloud data according to the characteristics of the V-shaped groove workpiece, obtaining an intersecting straight line between the two planes, obtaining two target pendants with the maximum distance based on pendants of adjacent points of the intersecting straight line on the straight line, and identifying points of the target pendants on the straight line to obtain characteristic points of the welding seam of the V-shaped groove workpiece. On the one hand, compare in line laser scanning's two-dimensional data processing mode, this application can reflect the characteristics of V type groove work piece on the cubical space more accurately through three-dimensional data to obtain more accurate extreme point, on the other hand, compare and become the mode of robot welding in artifical teaching, this application directly carries out welding seam discernment according to three-dimensional point cloud data and obtains the welding seam characteristic point, and it is higher for artifical mode efficiency. Therefore, the efficiency and the accuracy of the method for recognizing the weld joint of the V-shaped groove workpiece are both considered.
Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The above and other objects, features and advantages of the present application will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
Fig. 1 is a schematic flowchart illustrating a weld joint identification method according to an embodiment of the present disclosure.
Fig. 2 shows a schematic diagram of a V-groove workpiece according to an embodiment of the present application.
Fig. 3 is a schematic flow chart illustrating a weld joint identification method according to a second embodiment of the present application.
Fig. 4 shows a schematic diagram of a relationship between a ground point cloud and a virtual point cloud of a V-groove workpiece according to the second embodiment of the present application.
Fig. 5 shows a schematic diagram of three planes obtained by cutting according to the second embodiment of the present application.
Fig. 6 is a schematic diagram illustrating a relationship between a plane intersecting straight line and an adjacent point according to the second embodiment of the present application.
FIG. 7 shows a schematic diagram of weld feature points of a V-groove workpiece according to the second embodiment of the present application.
Fig. 8 shows a detailed flowchart of weld seam identification in a specific scenario according to the second embodiment of the present application.
Fig. 9 shows a schematic structural diagram of a weld joint identification device according to a third embodiment of the present application.
Fig. 10 shows a schematic structural diagram of a welding robot according to a fourth embodiment of the present application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The drawings are merely schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments. In the following description, numerous specific details are provided to give a thorough understanding of example embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, steps, and so forth. In other instances, well-known structures, methods, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the application.
Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
Fig. 1 shows a schematic flowchart of a weld joint identification method in a first embodiment of the present application. The method comprises the following steps:
step S101: acquiring three-dimensional point cloud data of a V-shaped groove workpiece;
the V-groove workpiece is a groove-shaped workpiece having a V-groove. The three-dimensional point cloud data is data of point cloud information having three different dimensions. The three-dimensional point cloud data includes position information, such as coordinate information, of the point cloud. The three-dimensional point cloud data can be acquired through a three-dimensional camera at the tail end of a welding gun of the welding robot.
As an optional implementation manner, after the three-dimensional camera acquires the data, the acquired data is used as three-dimensional point cloud data, and the three-dimensional point cloud data can be quickly acquired.
As an optional implementation manner, after the three-dimensional camera acquires the data, the data may be further processed to obtain more accurate three-dimensional point cloud data.
Step S102: carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes;
as an optional implementation manner, performing plane segmentation processing and intersection line detection on the three-dimensional point cloud data to obtain an intersection line between every two planes, including: performing plane segmentation processing on the three-dimensional point cloud data to obtain at least two planes corresponding to the V-shaped groove workpiece; the at least two planes comprise at least two planes of a horizontal plane, a first inclined plane and a second inclined plane which correspond to the V-groove workpiece; respectively detecting the intersected straight lines between every two planes to obtain the intersected straight lines; the intersecting straight line comprises at least one of a first straight line, a second straight line and a third straight line; the first straight line is a straight line of the horizontal plane intersecting the first inclined plane, the second straight line is a straight line of the horizontal plane intersecting the second inclined plane, and the third straight line is a straight line of the first inclined plane intersecting the second inclined plane.
The V-groove workpiece has multiple flat surfaces, such as: horizontal and inclined planes. Wherein the horizontal plane refers to a plane parallel to the horizontal line in the workpiece with the V-shaped groove. The inclined plane is a plane connected with a horizontal plane, and the inclined plane has a larger inclination amplitude relative to the horizontal line.
And performing plane segmentation processing on the three-dimensional point cloud data to obtain three planes. Referring to fig. 2, the three planes are a plane a, a plane B, and a plane C, respectively. Where plane a is a horizontal plane, which is divided into two parts. The plane B and the plane C are inclined planes. Plane a has an intersecting straight line a with plane B, plane B has an intersecting straight line B with plane C, and plane C has an intersecting straight line C with plane a.
In order to obtain all weld characteristic points, when performing plane segmentation processing, each plane of the V-groove workpiece is segmented, intersecting straight lines between every two planes are obtained by detection and segmentation, and a straight line equation is calculated.
Step S103: extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight lines;
as an optional implementation manner, extracting a plurality of adjacent points corresponding to intersecting straight lines from the three-dimensional point cloud data includes: detecting the distance between each point in the three-dimensional point cloud data and an intersecting straight line; and taking all points in the three-dimensional point cloud data with the distance less than or equal to the preset distance as adjacent points.
The preset distance is a distance for a preset point that is in the vicinity of the intersecting straight line and is approximately adjacent to the intersecting straight line. All points in the three-dimensional point cloud data with the distance less than or equal to the preset distance can be respectively acquired from two sides of the intersecting straight line to serve as adjacent points.
As an alternative embodiment, a point closest to the intersecting straight line in the vertical axis direction may be extracted from the three-dimensional point cloud data as an adjacent point along the axial direction perpendicular to the intersecting straight line within a certain distance on both sides of the intersecting straight line. For example, if the intersecting straight line is taken as the X axis and the straight line perpendicular to the intersecting straight line is taken as the Y axis, there may be a plurality of points at a certain distance along the Y axis direction, and the closest point to the X axis among the points may be taken as the neighboring point.
Step S104: on the basis of the vertical feet of a plurality of adjacent points on the corresponding intersecting straight line, comparing the distance between every two vertical feet on the intersecting straight line to obtain two target vertical feet corresponding to the maximum distance;
as an alternative embodiment, comparing the distance between each two of the drop feet on the intersecting straight line based on the drop feet of the plurality of adjacent points on the corresponding intersecting straight line to obtain two target drop feet corresponding to the maximum distance, includes: projecting each adjacent point to an intersecting straight line to obtain a foot of each adjacent point on the intersecting straight line; determining the distance between every two vertical feet; comparing the distance between every two vertical feet to obtain the maximum distance; two target footholds corresponding to the maximum distance are acquired.
The target foot is the foot corresponding to the maximum distance. The euclidean distance between every two footholds can be calculated, and the maximum euclidean distance is taken as the maximum distance.
The method has the advantages that the drop feet are obtained by projecting adjacent points to the intersecting straight line, the points of the drop feet on the straight line are obtained after the maximum distance is compared on the basis of the distance between the drop feet, compared with the mode that the end points are obtained by searching the coincident point of the intersecting straight line and the three-dimensional point cloud data, the problem that the end points on the two sides are failed to be searched due to the fact that the coincident point does not exist between the end points on the two sides and the intersecting straight line can be avoided, and the welding seam feature points are corresponding to the actual three-dimensional point cloud data due to the fact that the points of the drop feet on the intersecting straight line of the points in the three-dimensional point cloud are obtained in the embodiment, and therefore the welding seam feature points are accurate.
Step S105: identifying the point of the target foot on the intersecting straight line as a weld joint characteristic point of the V-shaped groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
As an alternative embodiment, after identifying the point of the target foot on the intersecting straight line as the weld feature point of the V-groove workpiece, the method further comprises: and welding the V-shaped groove workpiece based on the weld joint characteristic points of the V-shaped groove workpiece. The relative position between the welding robot and the workpiece can be reflected more truly through the three-dimensional point cloud data, the welding robot can be guided to make a real welding motion track according to the identified welding seam, the welding precision can be improved, and the welding efficiency can also be improved.
As shown in fig. 2, the weld feature points are pt1, pt2, pt3, pt4, pt5, and pt6, for example.
Compared with a line laser which carries out welding seam identification based on a two-dimensional camera, the welding seam position is easy to identify deviation, the welding seam identification is carried out through three-dimensional point cloud data, and the welding seam feature points can be identified more accurately. Compared with the manual demonstrating method, the method needs manual participation and is high in energy consumption, the three-dimensional point cloud data are processed, the weld characteristic points of the V-shaped groove workpiece are obtained, and the efficiency is higher.
Fig. 3 shows a schematic flow chart of a weld joint identification method according to the second embodiment of the present application. The method comprises the following steps:
step S201: acquiring original three-dimensional point cloud data aiming at a V-shaped groove workpiece;
the embodiment describes how to obtain more accurate three-dimensional point cloud data, so that the accuracy of the identified weld characteristic points is higher than that of weld identification directly by adopting originally acquired three-dimensional point cloud data.
Step S202: carrying out coordinate conversion on the original three-dimensional point cloud data to obtain actual three-dimensional point cloud data under a welding robot base coordinate system;
as an optional implementation manner, performing coordinate transformation on the original three-dimensional point cloud data to obtain actual three-dimensional point cloud data under a welding robot base coordinate system, including: and performing coordinate conversion on the original three-dimensional point cloud data based on the attitude matrix of the tool central point at the end of the welding robot and the robot hand-eye matrix to obtain actual three-dimensional point cloud data under the welding robot base coordinate system.
As an alternative embodiment, the tool center point is the welding robot torch tip point.
Step S203: clustering actual three-dimensional point cloud data to obtain three-dimensional point cloud data;
as an optional implementation manner, clustering the actual three-dimensional point cloud data to obtain three-dimensional point cloud data includes: acquiring a value range of actual three-dimensional point cloud data on a preset dimension; traversing each point in the actual three-dimensional point cloud data, and determining the value of the point on a preset dimension; the preset dimension is a preset dimension used for indicating the direction towards the ground; acquiring all points of which the values are not in the value range; filtering all points with values not within the value range to obtain real three-dimensional point cloud data; sampling the real three-dimensional point cloud data to obtain sampled three-dimensional point cloud data; and clustering the sampled three-dimensional point cloud data to obtain a spatial noise point and target three-dimensional point cloud data, and taking the target three-dimensional point cloud data as the three-dimensional point cloud data.
The real three-dimensional point cloud data is three-dimensional point cloud data from which the ground point cloud data is removed. The sampled three-dimensional point cloud data is data which are partially sampled in the real three-dimensional point cloud data. The target three-dimensional point cloud data is point cloud data except spatial noise points in the sampled three-dimensional point cloud data.
By adopting the mode, ground point cloud and space noise points can be removed, and more accurate three-dimensional point cloud data of the workpiece can be obtained. And the computational power of welding seam identification can be reduced through sampling, and compared with the method for processing all points, the welding seam identification efficiency can be improved.
Step S204: carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes;
step S205: extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight lines;
as an alternative embodiment, a plurality of adjacent points corresponding to intersecting straight lines may be obtained from the real three-dimensional point cloud data.
Step S206: based on the feet of the plurality of adjacent points on the corresponding intersecting straight lines, comparing the distance between every two feet on the intersecting straight lines to obtain two target feet corresponding to the maximum distance;
step S207: identifying the point of the target foot on the intersecting straight line as a weld joint characteristic point of the V-shaped groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
Hereinafter, with reference to fig. 4 to 8, a technical solution of the present embodiment is described with reference to a specific scenario.
In conjunction with the flow chart of steps shown in fig. 8. The weld joint identification process comprises the following steps:
acquiring original three-dimensional point cloud data of a V-shaped groove workpiece: and (3) carrying out point cloud collection on the V-shaped groove welding workpiece by adopting a three-dimensional data camera to obtain the pcd0.
Converting the original three-dimensional point cloud data into a robot base coordinate system: and (3) converting the pcd0 into a welding robot base coordinate system through a toolPos attitude matrix of a TCP at the tail end of the welding robot and a hand eye matrix hand eye to obtain the actual point cloud pcd1 of the V-shaped groove welding workpiece. The conversion method is as follows:
pcd1＝transform(pcd0,toolPos*handEye)。
filtering the ground point cloud: and filtering out the point cloud irrelevant to the V-shaped groove workpiece in the pcd1, namely the ground point cloud through a filter, so that the real point cloud pcd2 of the V-shaped groove workpiece can be obtained at the moment. The relationship between the ground point cloud and the V-groove workpiece point cloud is shown in fig. 4. The ground point cloud and the V-shaped groove point cloud have different positions in the vertical dimension, and according to the characteristics, the ground point cloud can be filtered by a filter.
Sampling point clouds of the V-shaped groove workpiece: the real point cloud pcd2 of the V-shaped groove workpiece is uniformly sampled to obtain a point cloud pcd3, and the point cloud number of the actual point cloud can be reduced in the process, so that the extraction computing power of the V-shaped groove weld is reduced.
Clustering point clouds of the V-shaped groove workpieces: and clustering and partitioning the actual point cloud pcd3 of the V-shaped groove workpiece, removing spatial noise points except the actual point cloud of the V-shaped groove workpiece to obtain a point cloud pcd4, and avoiding interference on extraction of the V-shaped groove weld.
Performing plane segmentation on the point cloud of the V-shaped groove workpiece: and (3) carrying out plane segmentation on the actual point cloud pcd4 of the V-shaped groove workpiece to respectively obtain plane equations of the point cloud planes 1, 2 and 3. A schematic plan view of the resulting planes 1, 2 and 3 is shown in fig. 5.
Whether an intersecting straight line exists between point cloud planes of the V-shaped groove workpiece, traversing the point cloud of the planes: and traversing all the divided plane point clouds plane1, plane2 and plane3, judging whether an intersecting straight line exists between every two plane point clouds, if so, calculating a corresponding straight line, and obtaining straight line equations L1, L2 and L3 respectively.
And (3) solving the foot drop of all points near the intersecting straight line on the straight line: in the actual point cloud pcd4 of the V-shaped groove workpiece, adjacent points within a certain threshold value of the straight lines L1, L2 and L3 are respectively obtained, the obtained adjacent points are projected onto the straight lines, and the foot of each adjacent point on the straight lines is obtained. The relationship between adjacent points and the straight lines L1, L2, and L3 is shown in fig. 5.
End points between all the drop feet are calculated: the end points of all the drop feet on each straight line are calculated. The end points on the straight line are two points with the largest distance between every two vertical feet on the straight line as end points, and the Euclidean distance formula between the two points is as follows:
d＝sqrt((x1-x2)^2+(y1-y2)^2+(z1-z2)^2)。
the 6 end points are shown in fig. 6 and comprise V-groove weld starting point points pt1, pt2, pt3, pt4, pt5 and pt6. These 6 end points are the weld feature points.
Output endpoints on all lines: finally, outputting the real V-shaped point positions corresponding to the V-shaped grooves, and further providing real V-shaped groove weld joint initial point positions pt1, pt2, pt3, pt4, pt5 and pt6 for intelligent welding, wherein at the moment, the intelligent welding robot can plan the welding track of the V-shaped groove weld joint according to the output 6 end points, and the welding efficiency of the V-shaped groove weld joint is improved.
By adopting the mode, the efficiency and the precision of extracting the V-shaped groove weld joint of intelligent welding can be improved.
Fig. 9 shows a weld identifying apparatus according to a third embodiment of the present application, the apparatus including:
the acquisition module 301 is used for acquiring three-dimensional point cloud data of a V-shaped groove workpiece;
an intersecting straight line detection module 302, configured to perform plane segmentation processing and intersecting straight line detection on the three-dimensional point cloud data, so as to obtain an intersecting straight line between each two planes;
an adjacent point extracting module 303, configured to extract a plurality of adjacent points corresponding to intersecting straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight lines;
the distance comparison module 304 is used for comparing the distance between every two vertical feet on the intersecting straight line based on the vertical feet of the plurality of adjacent points on the corresponding intersecting straight line to obtain two target vertical feet corresponding to the maximum distance;
the weld characteristic point identification module 305 is used for identifying the points of the target foot on the intersecting straight lines as the weld characteristic points of the V-groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
In an exemplary embodiment of the present application, the weld identifying apparatus is configured to:
performing plane segmentation processing on the three-dimensional point cloud data to obtain at least two planes corresponding to the V-shaped groove workpiece; the at least two planes comprise at least two planes of a horizontal plane, a first inclined plane and a second inclined plane corresponding to the V-groove workpiece;
respectively detecting the intersected straight lines between every two planes to obtain the intersected straight lines; the intersecting straight line comprises at least one of a first straight line, a second straight line and a third straight line; the first straight line is a straight line of the horizontal plane intersecting the first inclined plane, the second straight line is a straight line of the horizontal plane intersecting the second inclined plane, and the third straight line is a straight line of the first inclined plane intersecting the second inclined plane.
In an exemplary embodiment of the present application, the weld identifying apparatus is configured to:
detecting the distance between each point in the three-dimensional point cloud data and an intersecting straight line;
taking all points in the three-dimensional point cloud data with the distance less than or equal to the preset distance as adjacent points;
projecting each adjacent point to an intersecting straight line to obtain a foot of each adjacent point on the intersecting straight line;
determining the distance between every two drop feet;
comparing the distance between every two vertical feet to obtain the maximum distance;
two target footholds corresponding to the maximum distance are acquired.
In an exemplary embodiment of the present application, the weld identifying apparatus is configured to:
acquiring original three-dimensional point cloud data for a V-shaped groove workpiece;
carrying out coordinate conversion on the original three-dimensional point cloud data to obtain actual three-dimensional point cloud data under a welding robot base coordinate system;
and clustering the actual three-dimensional point cloud data to obtain the three-dimensional point cloud data.
In an exemplary embodiment of the present application, the weld identifying apparatus is configured to:
acquiring a value range of actual three-dimensional point cloud data on a preset dimension;
traversing each point in the actual three-dimensional point cloud data, and determining the value of the point on a preset dimension; the preset dimension is a preset dimension used for indicating the direction towards the ground;
acquiring all points of which the values are not in the value range;
filtering all points with values not within the value range to obtain real three-dimensional point cloud data;
sampling the real three-dimensional point cloud data to obtain sampled three-dimensional point cloud data;
and clustering the sampled three-dimensional point cloud data to obtain a spatial noise point and target three-dimensional point cloud data, and taking the target three-dimensional point cloud data as the three-dimensional point cloud data.
In an exemplary embodiment of the present application, the weld identifying apparatus is configured to:
and performing coordinate conversion on the original three-dimensional point cloud data based on the attitude matrix of the tool center point at the tail end of the welding robot and the robot eye matrix to obtain actual three-dimensional point cloud data under the welding robot base coordinate system.
In an exemplary embodiment of the present application, the weld identifying apparatus is configured to:
and welding the V-shaped groove workpiece based on the weld joint characteristic points of the V-shaped groove workpiece.
A welding robot 40 according to the fourth embodiment of the present application is described below with reference to fig. 10. The welding robot 40 shown in fig. 10 is only an example, and should not bring any limitation to the function and the range of use of the embodiment of the present application.
As shown in fig. 10, the welding robot 40 is in the form of a general purpose computing device. The components of the welding robot 40 may include, but are not limited to: the at least one processing unit 410, the at least one memory unit 420, and a bus 430 that couples various system components including the memory unit 420 and the processing unit 410.
Wherein the memory unit stores program code that can be executed by the processing unit 410 such that the processing unit 410 performs the steps according to various exemplary embodiments of the present invention as described in the description part of the above exemplary methods of the present specification. For example, processing unit 410 may perform various steps as shown in fig. 1.
The storage unit 420 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM) 4201 and/or a cache memory unit 4202, and may further include a read only memory unit (ROM) 4203.
The storage unit 420 may also include a program/utility 4204 having a set (at least one) of program modules 4205, such program modules 4205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof may comprise an implementation of a network environment.
The welding robot 40 can also communicate with one or more devices that enable a user to interact with the welding robot 40, and/or with any device (e.g., router, modem, etc.) that enables the welding robot 40 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 450. An input/output (I/O) interface 450 is connected to the display unit 440. Also, the welding robot 40 can communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 460. As shown, the network adapter 460 communicates with the other modules of the welding robot 40 via the bus 430. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the welding robot 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (including a welding robot) execute the method according to the embodiments of the present application.
In an exemplary embodiment of the present application, there is also provided a computer-readable storage medium having stored thereon computer-readable instructions which, when executed by a processor of a computer, cause the computer to perform the method described in the above method embodiment section.
According to an embodiment of the present application, there is also provided a program product for implementing the method in the above-described method embodiment, which can employ a portable compact disc read only memory (CD-ROM) and include program code, and can be run on a welding robot. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as JAVA, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods herein are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (including a welding robot) execute the method according to the embodiments of the present application.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
Claims (10)
1. A weld recognition method, comprising:
acquiring three-dimensional point cloud data of a V-shaped groove workpiece;
carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes;
extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight line;
based on the vertical feet of a plurality of adjacent points on the corresponding intersecting straight line, comparing the distance between every two vertical feet on the intersecting straight line to obtain two target vertical feet corresponding to the maximum distance;
identifying the point of the target foot on the intersecting straight line as a weld characteristic point of the V-groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
2. The method of claim 1, wherein performing plane segmentation processing and intersecting line detection on the three-dimensional point cloud data to obtain an intersecting line between each two planes comprises:
performing plane segmentation processing on the three-dimensional point cloud data to obtain at least two planes corresponding to the V-shaped groove workpiece; the at least two planes comprise at least two planes of a horizontal plane, a first inclined plane and a second inclined plane corresponding to the V-groove workpiece;
respectively detecting the intersected straight line between every two planes to obtain the intersected straight line; the intersecting straight line comprises at least one of a first straight line, a second straight line and a third straight line; the first straight line is a straight line where the horizontal plane intersects with the first inclined plane, the second straight line is a straight line where the horizontal plane intersects with the second inclined plane, and the third straight line is a straight line where the first inclined plane intersects with the second inclined plane.
3. The method of claim 1, wherein extracting a plurality of adjacent points corresponding to the intersecting straight line from the three-dimensional point cloud data, and comparing the distance between each two feet on the intersecting straight line based on the feet of the adjacent points on the corresponding intersecting straight line to obtain two target feet corresponding to the maximum distance comprises:
detecting the distance between each point in the three-dimensional point cloud data and the intersecting straight line;
all points in the three-dimensional point cloud data with the distance smaller than or equal to a preset distance are used as the adjacent points;
projecting each adjacent point to the intersecting straight line to obtain a foot of each adjacent point on the intersecting straight line;
determining the distance between every two drop feet;
comparing the distance between every two vertical feet to obtain the maximum distance;
two target footholds corresponding to the maximum distance are acquired.
4. The method of claim 1, wherein obtaining three-dimensional point cloud data for a V-groove workpiece comprises:
acquiring original three-dimensional point cloud data for the V-groove workpiece;
performing coordinate conversion on the original three-dimensional point cloud data to obtain actual three-dimensional point cloud data under a welding robot base coordinate system;
and clustering the actual three-dimensional point cloud data to obtain the three-dimensional point cloud data.
5. The method of claim 4, wherein clustering the actual three-dimensional point cloud data to obtain the three-dimensional point cloud data comprises:
acquiring a value range of the actual three-dimensional point cloud data on a preset dimension;
traversing each point in the actual three-dimensional point cloud data, and determining the value of the point on the preset dimension; the preset dimension is a preset dimension used for indicating the direction towards the ground;
acquiring all points of which the values are not in the value range;
filtering all points with values not in the value range to obtain real three-dimensional point cloud data;
sampling the real three-dimensional point cloud data to obtain sampled three-dimensional point cloud data;
and clustering the sampled three-dimensional point cloud data to obtain a spatial noise point and target three-dimensional point cloud data, and taking the target three-dimensional point cloud data as the three-dimensional point cloud data.
6. The method of claim 4, wherein performing a coordinate transformation on the original three-dimensional point cloud data to obtain actual three-dimensional point cloud data in a welding robot base coordinate system comprises:
and performing coordinate conversion on the original three-dimensional point cloud data based on the attitude matrix of the tool central point at the end of the welding robot and the robot eye matrix to obtain actual three-dimensional point cloud data under the welding robot base coordinate system.
7. The method of claim 1, wherein after identifying the point of the target foot on the intersecting straight line as a weld feature point of the V-groove workpiece, the method further comprises:
and welding the V-shaped groove workpiece based on the weld joint characteristic points of the V-shaped groove workpiece.
8. A weld recognition device, comprising:
the acquisition module is used for acquiring three-dimensional point cloud data of the V-shaped groove workpiece;
the intersection straight line detection module is used for carrying out plane segmentation processing and intersection straight line detection on the three-dimensional point cloud data to obtain an intersection straight line between every two planes;
the adjacent point extraction module is used for extracting a plurality of adjacent points corresponding to the intersected straight lines from the three-dimensional point cloud data; the adjacent points are points in the three-dimensional point cloud data within a preset range of the intersecting straight line;
the distance comparison module is used for comparing the distance between every two vertical feet on the intersecting straight line based on the vertical feet of the plurality of adjacent points on the corresponding intersecting straight line to obtain two target vertical feet corresponding to the maximum distance;
the welding seam characteristic point identification module is used for identifying the point of the target foot on the intersecting straight line as the welding seam characteristic point of the V-shaped groove workpiece; the weld characteristic points are characteristic points at the weld joint of the V-groove workpiece.
9. A welding robot, comprising:
one or more processors;
storage means for storing one or more programs that, when executed by the one or more processors, cause the welding robot to implement the method of any one of claims 1 to 7.
10. A computer readable storage medium having computer readable instructions stored thereon which, when executed by a processor of a computer, cause the computer to perform the method of any one of claims 1 to 7.
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| CN202211063968.XA CN115409809A (en) | 2022-08-31 | 2022-08-31 | Weld joint recognition method and device, welding robot and storage medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117934616A (en) * | 2024-03-21 | 2024-04-26 | 深圳前海瑞集科技有限公司 | Method and device for determining welding seam of ship workpiece |
| CN118115477A (en) * | 2024-03-21 | 2024-05-31 | 深圳前海瑞集科技有限公司 | Method and device for segmenting welding seam of ship workpiece and computer medium |
| CN118212233A (en) * | 2024-05-20 | 2024-06-18 | 法奥意威(苏州)机器人系统有限公司 | Linear weld joint identification method and device and electronic equipment |
| CN118279250A (en) * | 2024-03-21 | 2024-07-02 | 深圳前海瑞集科技有限公司 | Ship workpiece point cloud processing method and device, equipment and computer medium |
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2022
- 2022-08-31 CN CN202211063968.XA patent/CN115409809A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117934616A (en) * | 2024-03-21 | 2024-04-26 | 深圳前海瑞集科技有限公司 | Method and device for determining welding seam of ship workpiece |
| CN117934616B (en) * | 2024-03-21 | 2024-05-28 | 深圳前海瑞集科技有限公司 | Method and device for determining welding seam of ship workpiece |
| CN118115477A (en) * | 2024-03-21 | 2024-05-31 | 深圳前海瑞集科技有限公司 | Method and device for segmenting welding seam of ship workpiece and computer medium |
| CN118279250A (en) * | 2024-03-21 | 2024-07-02 | 深圳前海瑞集科技有限公司 | Ship workpiece point cloud processing method and device, equipment and computer medium |
| CN118212233A (en) * | 2024-05-20 | 2024-06-18 | 法奥意威(苏州)机器人系统有限公司 | Linear weld joint identification method and device and electronic equipment |
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