CN117067219B - Sheet metal mechanical arm control method and system for trolley body molding - Google Patents
Sheet metal mechanical arm control method and system for trolley body molding Download PDFInfo
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- CN117067219B CN117067219B CN202311326757.5A CN202311326757A CN117067219B CN 117067219 B CN117067219 B CN 117067219B CN 202311326757 A CN202311326757 A CN 202311326757A CN 117067219 B CN117067219 B CN 117067219B
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- 239000002184 metal Substances 0.000 title claims abstract description 116
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000000465 moulding Methods 0.000 title claims description 3
- 229910000831 Steel Inorganic materials 0.000 claims description 65
- 239000010959 steel Substances 0.000 claims description 65
- 238000007493 shaping process Methods 0.000 claims description 11
- 230000009191 jumping Effects 0.000 claims description 6
- 230000009286 beneficial effect Effects 0.000 description 7
- 239000003086 colorant Substances 0.000 description 6
- 238000003384 imaging method Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000004080 punching Methods 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
- B25J9/1697—Vision controlled systems
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- Engineering & Computer Science (AREA)
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- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
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Abstract
The invention discloses a sheet metal mechanical arm control method and a sheet metal mechanical arm control system for forming an electric car body, which belong to the technical field of control systems.
Description
Technical Field
The invention relates to the technical field of control systems, in particular to a sheet metal mechanical arm control method and system for shaping an electric car body.
Background
When stamping the trolley body steel plate, the trolley body steel plate needs to be grabbed by the sheet metal mechanical arm and moved to the region to be stamped. In the process, the sheet metal mechanical arm needs to accurately grasp the trolley body steel plate, so that the follow-up accurate placement in a punching area is ensured, and the forming shape of the trolley body steel plate is determined at the position of the punching area. Therefore, the electric car body steel plate needs to be accurately grabbed by the sheet metal mechanical arm, in the use process of the sheet metal mechanical arm, the movement path of the sheet metal mechanical arm is designed in advance, the sheet metal mechanical arm moves according to the designed movement path, but due to loosening or aging of parts caused by the use time, deviation exists in the position where the sheet metal mechanical arm grabs the electric car body steel plate, and the electric car body steel plate cannot be accurately grabbed.
Disclosure of Invention
Aiming at the defects in the prior art, the sheet metal mechanical arm control method and the sheet metal mechanical arm control system for forming the trolley body solve the problem that the position where the sheet metal mechanical arm grabs a trolley body steel plate has deviation.
In order to achieve the aim of the invention, the invention adopts the following technical scheme: a sheet metal mechanical arm control method for shaping an electric car body comprises the following steps:
s1, moving a sheet metal mechanical arm to the position above a trolley body steel plate;
s2, acquiring images of the sheet metal mechanical arm and a trolley body steel plate through an image sensor to obtain a mixed image;
s3, acquiring a sheet metal mechanical arm region in the mixed image;
s4, moving the sheet metal mechanical arm according to coordinates of pixel points on the sheet metal mechanical arm area.
Further, the step S3 includes the following sub-steps:
s31, classifying the pixel points on the mixed image to obtain each classification area;
s32, finding out the trolley body steel plate areas in each classification area;
s33, taking other classification areas surrounded by the trolley body steel plate area as sheet metal mechanical arm areas.
The beneficial effects of the above further scheme are: according to the method, the pixel points on the mixed image are classified to obtain each classification area, so that each object in the mixed image is divided into different areas, the trolley body steel plate area is found, and the surrounding area is a sheet metal mechanical arm area according to the regular structure of the trolley body steel plate.
Further, the step S31 includes the following sub-steps:
s311, taking any pixel point in an unclassified area on the mixed image as a classification comparison point;
s312, calculating the color approximation degree of other pixel points and classification contrast points in the unclassified area on the mixed image;
s313, classifying the pixel points with the color similarity smaller than the approximate threshold value into a classification area, and jumping to the step S311 until all the pixel points on the mixed image are classified.
The beneficial effects of the above further scheme are: in the invention, any pixel point in the unclassified area is always taken as the classification comparison point, and the color approximation degree of other pixel points and the classification comparison point is always compared, so that the pixel points with similar colors are classified into one class, and the color of the steel plate is uniform, so that the pixel points belonging to the steel plate can be classified into one class.
Further, the formula for calculating the color approximation degree between other pixels in the unclassified region and the classification contrast point in the mixed image in S312 is as follows:
，
wherein S is i R is the color approximation of the ith pixel point and the classification contrast point in the unclassified area on the mixed image i R channel value, G for the ith pixel point in unclassified region on blended image i G channel value, B for the ith pixel point in unclassified region on blended image i B channel value, R for the ith pixel point in unclassified region on blended image o To classify the R channel value of the comparison point, G o To classify the G channel value of the comparison point, B o B-channel values for the classification comparison points.
The beneficial effects of the above further scheme are: according to the invention, the pixel points are classified by utilizing the color approximation degree, the differences are calculated from three channels of the colors respectively, and the colors of the three channels are ensured to be approximate.
Further, the step S32 includes the following sub-steps:
s321, find area in (m up ,m down ) A classification region within the range, where m is up For the upper area threshold, m down Is a lower area threshold;
s322, extracting edge pixel points of the suspected classification area;
and S323, when the plurality of continuous edge pixel points meet the edge condition, the suspected classification area is a trolley body steel plate area.
The beneficial effects of the above further scheme are: in the invention, the area can be expressed by the number of the pixel points, and when the image sensor is fixed, the size of the trolley body steel plate is also fixed, so that the imaging size of the trolley body steel plate is fixed, the suspected classification area can be screened out by an area mode, and then the trolley body steel plate area is determined by a trolley body steel plate regular structure.
Further, the edge condition in S323 is:
，
，
wherein θ n Is the angle of the nth edge pixel point, y n Is the ordinate, x of the nth edge pixel point n Is the abscissa, y, of the nth edge pixel point n-1 Is the ordinate, x of the n-1 th edge pixel point n-1 Is the abscissa of the N-1 th edge pixel point, N is the number of continuous edge pixel points, theta th For the angle difference threshold, arctan is an arctangent function.
The beneficial effects of the above further scheme are: the invention utilizes the regular structure of the trolley body steel plate, thereby taking a plurality of continuous edge pixel points, judging whether the plurality of continuous edge pixel points are regular, namely whether the edge condition is met, and whether the angle between each edge pixel point and the adjacent edge pixel point is consistent, if so, the trolley body steel plate area is obtained.
Further, the step S4 includes the following sub-steps:
s41, calculating real-time geometric center coordinates according to coordinates of pixel points on the sheet metal mechanical arm region;
s42, calculating the distance between the real-time geometric center coordinates and the standard geometric center coordinates;
s43, judging whether the distance is larger than a distance threshold, if so, obtaining a transverse distance difference and a longitudinal distance difference according to the real-time geometric center coordinates and the standard geometric center coordinates, and jumping to the step S44, if not, enabling the sheet metal mechanical arm to reach the standard position;
s44, transversely moving the sheet metal mechanical arm according to the transverse distance difference;
s45, longitudinally moving the sheet metal mechanical arm according to the longitudinal distance difference.
The beneficial effects of the above further scheme are: according to the invention, a sheet metal mechanical arm region is found according to the trolley body steel plate region, and the real-time geometric center coordinates of the sheet metal mechanical arm region are compared with the standard geometric center coordinates, so that the deviation distance is determined, and the sheet metal mechanical arm is adjusted.
Further, the formula for calculating the real-time geometric center coordinates in S41 is:
，
，
wherein x is c Is the real-time geometric center abscissa, y c X is the ordinate of the geometric center in real time k Is the abscissa, y of the kth pixel point on the sheet metal mechanical arm area k The ordinate of the kth pixel point on the sheet metal mechanical arm area is K, and the number of the pixel points on the sheet metal mechanical arm area is K.
Further, the formula for calculating the distance between the real-time geometric center coordinate and the standard geometric center coordinate in S42 is as follows:
，
wherein d is the distance between the real-time geometric center coordinate and the standard geometric center coordinate, and x is the distance between the real-time geometric center coordinate and the standard geometric center coordinate c Is the real-time geometric center abscissa, y c X is the ordinate of the geometric center in real time o Is the abscissa of the standard geometric center, y o Is the ordinate of the standard geometric center.
A system of a sheet metal mechanical arm control method for shaping an electric car body comprises the following steps: the system comprises a first mobile unit, an acquisition unit and a second mobile unit;
the first moving unit is used for moving the sheet metal mechanical arm to the position above the trolley body steel plate;
the acquisition unit is used for acquiring images of the sheet metal mechanical arm and the trolley body steel plate through the image sensor to obtain a mixed image;
the acquisition unit is used for acquiring a sheet metal mechanical arm area in the mixed image;
the second moving unit is used for moving the sheet metal mechanical arm according to coordinates of pixel points on the sheet metal mechanical arm area.
In summary, the invention has the following beneficial effects: after the sheet metal mechanical arm moves above the trolley body steel plate, the image sensor is used for collecting images of the sheet metal mechanical arm and the trolley body steel plate, so that a sheet metal mechanical arm area in the mixed image is determined, the position of the sheet metal mechanical arm can be determined according to the coordinates of the pixel points on the sheet metal mechanical arm area, the position of the sheet metal mechanical arm can be accurately moved to reach the target position, the sheet metal mechanical arm can reach the upper part of the trolley body steel plate after moving according to the originally designed movement path, but due to long-time use, small movement deviation of the sheet metal mechanical arm exists, the position of the sheet metal mechanical arm can be corrected again, and the problem of deviation of the position of the sheet metal mechanical arm for grabbing the trolley body steel plate is solved.
Drawings
Fig. 1 is a flowchart of a sheet metal mechanical arm control method for shaping an electric car body.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and all the inventions which make use of the inventive concept are protected by the spirit and scope of the present invention as defined and defined in the appended claims to those skilled in the art.
As shown in fig. 1, a sheet metal mechanical arm control method for shaping an electric car body comprises the following steps:
s1, moving a sheet metal mechanical arm to the position above a trolley body steel plate;
s2, acquiring images of the sheet metal mechanical arm and a trolley body steel plate through an image sensor to obtain a mixed image;
in the invention, the image sensor is fixed above the sheet metal mechanical arm and the trolley body steel plate, so that the sheet metal mechanical arm and the trolley body steel plate can be conveniently collected into an image, and the position of the trolley body steel plate area can be conveniently found.
S3, acquiring a sheet metal mechanical arm region in the mixed image;
s4, moving the sheet metal mechanical arm according to coordinates of pixel points on the sheet metal mechanical arm area.
The step S3 comprises the following substeps:
s31, classifying the pixel points on the mixed image to obtain each classification area;
s32, finding out the trolley body steel plate areas in each classification area;
s33, taking other classification areas surrounded by the trolley body steel plate area as sheet metal mechanical arm areas.
According to the method, the pixel points on the mixed image are classified to obtain each classification area, so that each object in the mixed image is divided into different areas, the trolley body steel plate area is found, and the surrounding area is a sheet metal mechanical arm area according to the regular structure of the trolley body steel plate. In the invention, the image sensor is fixed above the sheet metal mechanical arm and the trolley body steel plate, and the sheet metal mechanical arm is above the trolley body steel plate, so after imaging, the sheet metal mechanical arm area is in the trolley body steel plate area.
The step S31 comprises the following substeps:
s311, taking any pixel point in an unclassified area on the mixed image as a classification comparison point;
s312, calculating the color approximation degree of other pixel points and classification contrast points in the unclassified area on the mixed image;
s313, classifying the pixel points with the color similarity smaller than the approximate threshold value into a classification area, and jumping to the step S311 until all the pixel points on the mixed image are classified.
In the invention, any pixel point in the unclassified area is always taken as the classification comparison point, and the color approximation degree of other pixel points and the classification comparison point is always compared, so that the pixel points with similar colors are classified into one class, and the color of the steel plate is uniform, so that the pixel points belonging to the steel plate can be classified into one class.
The formula for calculating the color approximation degree between other pixel points and the classification contrast point in the unclassified region on the mixed image in S312 is as follows:
，
wherein S is i R is the color approximation of the ith pixel point and the classification contrast point in the unclassified area on the mixed image i R channel value, G for the ith pixel point in unclassified region on blended image i G channel value, B for the ith pixel point in unclassified region on blended image i B channel value, R for the ith pixel point in unclassified region on blended image o To classify the R channel value of the comparison point, G o To classify the G channel value of the comparison point, B o B-channel values for the classification comparison points.
According to the invention, the pixel points are classified by utilizing the color approximation degree, the differences are calculated from three channels of the colors respectively, and the colors of the three channels are ensured to be approximate.
The step S32 comprises the following substeps:
s321, find area in (m up ,m down ) A classification region within the range, where m is up For the upper area threshold, m down Is a lower area threshold;
s322, extracting edge pixel points of the suspected classification area;
and S323, when the plurality of continuous edge pixel points meet the edge condition, the suspected classification area is a trolley body steel plate area.
In the present invention, the upper area threshold value and the lower area threshold value are set empirically or experimentally.
In the invention, the area can be expressed by the number of the pixel points, how many pixel points represent how large an area, and when the image sensor is fixed, the size of the trolley body steel plate is also fixed, so that the imaging size of the trolley body steel plate is fixed, suspected classification areas can be screened out by an area mode, and then the trolley body steel plate area is determined by a regular structure of the trolley body steel plate.
The edge condition in S323 is:
，
，
wherein θ n Is the angle of the nth edge pixel point, y n Is the ordinate, x of the nth edge pixel point n Is the abscissa, y, of the nth edge pixel point n-1 Is the ordinate, x of the n-1 th edge pixel point n-1 Is the abscissa of the N-1 th edge pixel point, N is the number of continuous edge pixel points, theta th For the angle difference threshold, arctan is an arctangent function.
The invention utilizes the regular structure of the trolley body steel plate, thereby taking a plurality of continuous edge pixel points, judging whether the plurality of continuous edge pixel points are regular, namely whether the edge condition is met, and whether the angle between each edge pixel point and the adjacent edge pixel point is consistent, if so, the trolley body steel plate area is obtained.
The step S4 comprises the following substeps:
s41, calculating real-time geometric center coordinates according to coordinates of pixel points on the sheet metal mechanical arm region;
s42, calculating the distance between the real-time geometric center coordinates and the standard geometric center coordinates;
s43, judging whether the distance is larger than a distance threshold, if so, obtaining a transverse distance difference and a longitudinal distance difference according to the real-time geometric center coordinates and the standard geometric center coordinates, and jumping to the step S44, if not, enabling the sheet metal mechanical arm to reach the standard position;
s44, transversely moving the sheet metal mechanical arm according to the transverse distance difference;
s45, longitudinally moving the sheet metal mechanical arm according to the longitudinal distance difference.
In the invention, the two abscissas of the real-time geometric center coordinate and the standard geometric center coordinate are subtracted, and then the proportional coefficient is multiplied to obtain the transverse distance difference.
In the invention, the two ordinate of the real-time geometric center coordinate and the standard geometric center coordinate are subtracted, and then the longitudinal distance difference is obtained by multiplying the two ordinate by the proportionality coefficient, wherein the proportionality coefficient is the conversion proportion of the image and the actual space.
According to the invention, a sheet metal mechanical arm region is found according to the trolley body steel plate region, and the real-time geometric center coordinates of the sheet metal mechanical arm region are compared with the standard geometric center coordinates, so that the deviation distance is determined, and the sheet metal mechanical arm is adjusted.
The formula for calculating the real-time geometric center coordinates in S41 is as follows:
，
，
wherein x is c Is the real-time geometric center abscissa, y c X is the ordinate of the geometric center in real time k Is the abscissa, y of the kth pixel point on the sheet metal mechanical arm area k The ordinate of the kth pixel point on the sheet metal mechanical arm area is K, and the number of the pixel points on the sheet metal mechanical arm area is K.
The formula for calculating the distance between the real-time geometric center coordinate and the standard geometric center coordinate in the step S42 is as follows:
，
wherein d is the distance between the real-time geometric center coordinate and the standard geometric center coordinate, and x is the distance between the real-time geometric center coordinate and the standard geometric center coordinate c Is the real-time geometric center abscissa, y c X is the ordinate of the geometric center in real time o Is the abscissa of the standard geometric center, y o Is the ordinate of the standard geometric center.
In the invention, the standard geometric center coordinates are target positions set in advance.
A system of a sheet metal mechanical arm control method for shaping an electric car body comprises the following steps: the system comprises a first mobile unit, an acquisition unit and a second mobile unit;
the first moving unit is used for moving the sheet metal mechanical arm to the position above the trolley body steel plate;
the acquisition unit is used for acquiring images of the sheet metal mechanical arm and the trolley body steel plate through the image sensor to obtain a mixed image;
the acquisition unit is used for acquiring a sheet metal mechanical arm area in the mixed image;
the second moving unit is used for moving the sheet metal mechanical arm according to coordinates of pixel points on the sheet metal mechanical arm area.
In this embodiment, the system and method are consistent with implementation.
After the sheet metal mechanical arm moves above the trolley body steel plate, the image sensor is used for collecting images of the sheet metal mechanical arm and the trolley body steel plate, so that a sheet metal mechanical arm area in the mixed image is determined, the position of the sheet metal mechanical arm can be determined according to the coordinates of the pixel points on the sheet metal mechanical arm area, the position of the sheet metal mechanical arm can be accurately moved to reach the target position, the sheet metal mechanical arm can reach the upper part of the trolley body steel plate after moving according to the originally designed movement path, but due to long-time use, small movement deviation of the sheet metal mechanical arm exists, the position of the sheet metal mechanical arm can be corrected again, and the problem of deviation of the position of the sheet metal mechanical arm for grabbing the trolley body steel plate is solved.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A sheet metal mechanical arm control method for shaping an electric car body is characterized by comprising the following steps:
s1, moving a sheet metal mechanical arm to the position above a trolley body steel plate;
s2, acquiring images of the sheet metal mechanical arm and a trolley body steel plate through an image sensor to obtain a mixed image;
s3, acquiring a sheet metal mechanical arm region in the mixed image;
s4, moving the sheet metal mechanical arm according to coordinates of pixel points on the sheet metal mechanical arm area;
the step S3 comprises the following substeps:
s31, classifying the pixel points on the mixed image according to the color approximation degree of the pixel points to obtain each classification area;
s32, finding out the trolley body steel plate areas in each classification area;
s33, taking other classification areas surrounded by the trolley body steel plate area as sheet metal mechanical arm areas.
2. The sheet metal mechanical arm control method for shaping an electric car body according to claim 1, wherein the step S31 includes the following sub-steps:
s311, taking any pixel point in an unclassified area on the mixed image as a classification comparison point;
s312, calculating the color approximation degree of other pixel points and classification contrast points in the unclassified area on the mixed image;
s313, classifying the pixel points with the color similarity smaller than the approximate threshold value into a classification area, and jumping to the step S311 until all the pixel points on the mixed image are classified.
3. The method for controlling a sheet metal mechanical arm for forming a trolley body according to claim 2, wherein the formula for calculating the color approximation degree between other pixels in the unclassified area and the classification contrast point in the mixed image in S312 is as follows:
，
wherein S is i R is the color approximation of the ith pixel point and the classification contrast point in the unclassified area on the mixed image i R channel value, G for the ith pixel point in unclassified region on blended image i G channel value, B for the ith pixel point in unclassified region on blended image i B channel value, R for the ith pixel point in unclassified region on blended image o To classify the R channel value of the comparison point, G o To classify the G channel value of the comparison point, B o B-channel values for the classification comparison points.
4. The sheet metal mechanical arm control method for shaping an electric car body according to claim 1, wherein the step S32 includes the following sub-steps:
s321, find area in (m up ,m down ) A classification region within the range, where m is up For the upper area threshold, m down Is a lower area threshold;
s322, extracting edge pixel points of the suspected classification area;
and S323, when the plurality of continuous edge pixel points meet the edge condition, the suspected classification area is a trolley body steel plate area.
5. The method for controlling a sheet metal mechanical arm for forming a trolley body according to claim 4, wherein the edge condition in S323 is:
，
，
wherein θ n Is the angle of the nth edge pixel point, y n Is the ordinate, x of the nth edge pixel point n Is the abscissa, y, of the nth edge pixel point n-1 Is the ordinate, x of the n-1 th edge pixel point n-1 Is the abscissa of the N-1 th edge pixel point, N is the number of continuous edge pixel points, theta th For the angle difference threshold, arctan is an arctangent function.
6. The sheet metal mechanical arm control method for shaping an electric car body according to claim 1, wherein the step S4 includes the following sub-steps:
s41, calculating real-time geometric center coordinates according to coordinates of pixel points on the sheet metal mechanical arm region;
s42, calculating the distance between the real-time geometric center coordinates and the standard geometric center coordinates;
s43, judging whether the distance is larger than a distance threshold, if so, obtaining a transverse distance difference and a longitudinal distance difference according to the real-time geometric center coordinates and the standard geometric center coordinates, and jumping to the step S44, if not, enabling the sheet metal mechanical arm to reach the standard position;
s44, transversely moving the sheet metal mechanical arm according to the transverse distance difference;
s45, longitudinally moving the sheet metal mechanical arm according to the longitudinal distance difference.
7. The method for controlling a sheet metal mechanical arm for shaping an electric car body according to claim 6, wherein the formula for calculating the real-time geometric center coordinates in S41 is:
，
，
wherein x is c Is the real-time geometric center abscissa, y c X is the ordinate of the geometric center in real time k Is the abscissa, y of the kth pixel point on the sheet metal mechanical arm area k The ordinate of the kth pixel point on the sheet metal mechanical arm area is K, and the number of the pixel points on the sheet metal mechanical arm area is K.
8. The method for controlling a sheet metal mechanical arm for forming a trolley body according to claim 6, wherein the formula for calculating the distance between the real-time geometric center coordinate and the standard geometric center coordinate in S42 is:
，
wherein d is the distance between the real-time geometric center coordinate and the standard geometric center coordinate, and x is the distance between the real-time geometric center coordinate and the standard geometric center coordinate c Is the real-time geometric center abscissa, y c X is the ordinate of the geometric center in real time o Is the abscissa of the standard geometric center, y o Is the ordinate of the standard geometric center.
9. The system of the sheet metal mechanical arm control method for trolley body molding according to any one of claims 1 to 8, characterized by comprising: the system comprises a first mobile unit, an acquisition unit and a second mobile unit;
the first moving unit is used for moving the sheet metal mechanical arm to the position above the trolley body steel plate;
the acquisition unit is used for acquiring images of the sheet metal mechanical arm and the trolley body steel plate through the image sensor to obtain a mixed image;
the acquisition unit is used for acquiring a sheet metal mechanical arm area in the mixed image;
the second moving unit is used for moving the sheet metal mechanical arm according to coordinates of pixel points on the sheet metal mechanical arm area.
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| CN109658413A (en) * | 2018-12-12 | 2019-04-19 | 深圳前海达闼云端智能科技有限公司 | A kind of method of robot target grasping body position detection |
| CN110480637A (en) * | 2019-08-12 | 2019-11-22 | 浙江大学 | A kind of mechanical arm part image identification grasping means based on Kinect sensor |
| CN110605740A (en) * | 2019-10-12 | 2019-12-24 | 上海德容智能科技有限公司 | Vision guide feeding system suitable for automatic automobile roof carrying process |
| CN113580149A (en) * | 2021-09-30 | 2021-11-02 | 湖南大学 | Unordered aliasing workpiece grabbing method and system based on key point prediction network |
| CN116175542A (en) * | 2021-11-28 | 2023-05-30 | 梅卡曼德（北京）机器人科技有限公司 | Grabbing control method, grabbing control device, electronic equipment and storage medium |
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