Point position copying method based on fixed deviation

Abstract

The invention discloses a point location copying method based on fixed deviation. The method comprises the following steps that an image sensor on a first machine shoots a calibration plate to obtain first point location data; an image sensor on the second machine shoots the calibration plate to obtain second point location data; reversely solving a conversion relation model between the first machine and the second machine through the first point location data and the second point location data; and converting the initial point location data on the first machine table into duplicated point location data on the second machine table through the conversion relation model. According to the point location replication method based on the fixed deviation, the conversion relation between the first machine table and the second machine table is found through the point location characteristics of the calibration board, so that the initial point location data is accurately converted into the replication point location data, and the problem of tolerance between different devices is avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of mechanical processing, and in particular relates to a point replication method based on fixed deviation. Background Art

[0002] There are usually multiple dispensing machines at a production site. When the processing points have been set in one dispensing machine, if you need to process it on another dispensing machine, you need to copy the point program to the other dispensing machine so that the other dispensing machine can also perform the same processing.

[0003] Due to the equipment tolerances between different dispensing machines, there may be certain deviations in the point data after being copied to another dispensing machine, which requires manual supplementary adjustments. Summary of the invention

[0004] The purpose of the present invention is to propose a point replication method based on fixed deviation to solve the problem in the prior art that point data may have deviation after being copied to another dispensing machine.

[0005] To this end, the present invention provides a point replication method based on fixed deviation, comprising the following steps: an image sensor on a first machine platform photographs a calibration plate to obtain first point data;

[0006] The image sensor on the second machine photographs the calibration plate to obtain second point data;

[0007] Reversely solving a conversion relationship model between the first machine and the second machine through the first point data and the second point data;

[0008] The initial point data on the first machine is converted into duplicate point data on the second machine through the conversion relationship model.

[0009] Preferably, the step of photographing the calibration plate by the image sensor on the first machine to obtain the first point position data comprises:

[0010] The image sensor on the first machine photographs the calibration plate to obtain a first calibration image, identifies the image coordinates of the point position of the calibration plate in the first calibration image through an edge detection algorithm, and converts the image coordinates of the point position of the calibration plate in the first calibration image into three-dimensional coordinates of the point position in the first machine coordinate system as the first point position data.

[0011] Preferably, the step of photographing the calibration plate by the image sensor on the second machine to obtain the second point position data comprises:

[0012] The image sensor on the second machine photographs the calibration plate to obtain a second calibration image, identifies the image coordinates of the point positions of the calibration plate in the second calibration image through an edge detection algorithm, and converts the image coordinates of the point positions of the calibration plate in the second calibration image into three-dimensional coordinates of the point positions in the second machine coordinate system as second point position data.

[0013] Preferably, the step of inversely solving the conversion relationship model between the first machine and the second machine through the first point data and the second point data comprises:

[0014] Constructing an RT matrix according to the first point data and the second point data;

[0015] Get the approximate rotation matrix based on the RT matrix

[0016] According to the first point data, the second point data and the approximate rotation matrix Get the approximate translation matrix

[0017] Preferably, the RT matrix is ​​constructed according to the first point data and the second point data as follows:

[0018] P B =RP A +T.

[0019] Where P A is the first point data, P B is the second point data, R is the rotation matrix, and T is the translation matrix.

[0020] Preferably, the approximate rotation matrix obtained according to the RT matrix is is: within the range that satisfies the conditions of the rotation matrix R, the rotation matrix that is closest to the rotation matrix R in terms of norm.

[0021] Preferably, the approximate rotation matrix Obtained through the SVD algorithm.

[0022] Preferably, the approximate rotation matrix By using the approximate closed solution algorithm

[0023] Preferably, the first point data, the second point data and the approximate rotation matrix Get the approximate translation matrix The steps include:

[0024] Build The matrix gets the approximate translation matrix Right now

[0025]

[0026] Where P A is the first point data, P B is the second point data, is the approximate rotation matrix, is the approximate translation matrix.

[0027] Preferably, the step of converting the initial point data on the first machine into the duplicate point data on the second machine through the conversion relationship model includes:

[0028] The initial point data is obtained by The matrix solution obtains the replicated point data, namely:

[0029]

[0030] Where P A ′ is the initial point data, P B ′ To copy point data, is the approximate rotation matrix, is the approximate translation matrix.

[0031] Beneficial effects:

[0032] 1. The present invention provides a point replication method based on fixed deviation, which finds the conversion relationship between the first machine and the second machine through the point characteristics of the calibration plate, so that the initial point data can be accurately converted into the replicated point data, avoiding the tolerance problem between different devices.

[0033] 2. By calculating the approximate rotation matrix and the approximate translation matrix get Matrix, reducing the error when converting the initial point data to the copied point data, further improving the accuracy of the conversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 The present invention is a flowchart of a point replication method based on fixed deviation.

[0036] Figure 2 This is a flow chart of step S3 of a point replication method based on fixed deviation in the present invention. DETAILED DESCRIPTION

[0037] The content of the present invention can be more easily understood by selecting the following detailed description of the preferred implementation method of the present invention and the embodiments included. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art to which the present invention belongs. When there is a conflict, the definition in this specification shall prevail.

[0038] Embodiment 1:

[0039] like Figure 1 As shown, this embodiment provides a point replication method based on fixed deviation, including the following steps:

[0040] S1, the image sensor on the first machine photographs the calibration plate to obtain the first point data;

[0041] The image sensor on the first machine photographs the calibration plate to obtain a first calibration image, identifies the image coordinates of the points on the calibration plate in the first calibration image through an edge detection algorithm, and converts the image coordinates of the points on the calibration plate in the first calibration image into three-dimensional coordinates of the points in the first machine coordinate system as first point data. Wherein, black and white grids are arranged on the calibration plate, and the intersection of the boundary lines of the black and white grids is the point, and the boundary of the black and white grids is obvious, which facilitates the identification of the position of the point through the edge detection algorithm. The edge detection algorithms that can be selected include the Sobel operator, the Canny operator, the Laplacian operator, and the Roberts operator. The image sensor on the first machine can be selected as a camera, which has a built-in intrinsic parameter matrix and an external parameter matrix obtained by calibration, and can convert the image coordinates of the points in the image into three-dimensional coordinates of the first machine coordinate system.

[0042] S2, the image sensor on the second machine photographs the calibration plate to obtain second point data;

[0043] The image sensor on the second machine photographs the calibration plate to obtain a second calibration image, identifies the image coordinates of the point position of the calibration plate in the second calibration image through an edge detection algorithm, and converts the image coordinates of the point position of the calibration plate in the second calibration image into three-dimensional coordinates of the point position in the second machine coordinate system as the second point position data. The step of obtaining the second point position data by the second machine is the same as S1.

[0044] S3, inversely solving a conversion relationship model between the first machine and the second machine through the first point data and the second point data;

[0045] Among them, Figure 2 As shown, the following steps are included:

[0046] S31, constructing an RT matrix according to the first point data and the second point data; the constructing an RT matrix according to the first point data and the second point data is:

[0047] P B =RP A +T.

[0048] Where P A is the first point data, P B is the second point data, R is the rotation matrix, and T is the translation matrix.

[0049] S32. Obtain an approximate rotation matrix based on the RT matrix

[0050] The approximate rotation matrix obtained according to the RT matrix is: within the range that satisfies the conditions of the rotation matrix R, the rotation matrix that is closest to the rotation matrix R in terms of norm.

[0051] Calculate

[0052] In this embodiment, the approximate rotation matrix Obtained through the SVD algorithm.

[0053]

[0054] Removal and Irrelevant items have become

[0055] Let the SVD decomposition of R be R = USV T , where S 11 ≥S 22 ≥S 33 ≥0,

[0056]

[0057] make

[0058] When S 33 >0, the maximum value is achieved when Q is the unit matrix.

[0059] Right now

[0060] S33, according to the first point data, the second point data and the approximate rotation matrix Get the approximate translation matrix

[0061] Build The matrix gets the approximate translation matrix Right now

[0062]

[0063] Where P A is the first point data, P B is the second point data, is the approximate rotation matrix, is the approximate translation matrix.

[0064] S4. Convert the initial point data on the first machine into duplicate point data on the second machine through a conversion relationship model.

[0065] The step of converting the initial point data on the first machine into the duplicate point data on the second machine through the conversion relationship model comprises:

[0066] The initial point data is obtained by The matrix solution obtains the replicated point data, namely:

[0067]

[0068] Where P A ′ is the initial point data, P B ′ To copy point data, is the approximate rotation matrix, is the approximate translation matrix.

[0069] Embodiment 2:

[0070] The difference between Example 2 and Example 1 is that the approximate rotation matrix It is obtained by an approximate closed-form solution algorithm.

[0071] Assume the unit quaternion q of the rotation matrix R = (q0, q1, q2, q3), the approximate rotation matrix The unit quaternion

[0072] Solving for argmax q tr(q T nq), where

[0073]

[0074] make Then it is argmax q tr(q T Uq)

[0075]

[0076] Each column of U is a multiple of q, but the rotation matrix R is noisy, so U will also be noisy, so the columns of U are weighted averaged and normalized.

[0077]

[0078] u max is the column with the largest norm in U.

[0079] get Then converted to an approximate rotation matrix

[0080] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A point replication method based on fixed deviation, characterized in that: The steps include: The image sensor on the first machine photographs the calibration plate to obtain first point data; The image sensor on the second machine photographs the calibration plate to obtain second point data; Reversely solving a conversion relationship model between the first machine and the second machine through the first point data and the second point data; The initial point data on the first machine is converted into duplicate point data on the second machine through the conversion relationship model.

2. A point replication method based on fixed deviation according to claim 1, characterized in that: The step of photographing the calibration plate with the image sensor on the first machine to obtain first point position data includes: The image sensor on the first machine photographs the calibration plate to obtain a first calibration image, identifies the image coordinates of the point position of the calibration plate in the first calibration image through an edge detection algorithm, and converts the image coordinates of the point position of the calibration plate in the first calibration image into three-dimensional coordinates of the point position in the first machine coordinate system as the first point position data.

3. A point replication method based on fixed deviation according to claim 1, characterized in that: The step of photographing the calibration plate by the image sensor on the second machine to obtain the second point data includes: The image sensor on the second machine photographs the calibration plate to obtain a second calibration image, identifies the image coordinates of the point positions of the calibration plate in the second calibration image through an edge detection algorithm, and converts the image coordinates of the point positions of the calibration plate in the second calibration image into three-dimensional coordinates of the point positions in the second machine coordinate system as second point position data.

4. A point replication method based on fixed deviation according to claim 1, characterized in that: The step of inversely solving the conversion relationship model between the first machine and the second machine through the first point data and the second point data comprises: Constructing an RT matrix according to the first point data and the second point data; Get the approximate rotation matrix based on the RT matrix According to the first point data, the second point data and the approximate rotation matrix Get the approximate translation matrix 5. A point replication method based on fixed deviation according to claim 4, characterized in that: The RT matrix constructed according to the first point data and the second point data is: P B =RP A +T。 Where P A is the first point data, P B is the second point data, R is the rotation matrix, and T is the translation matrix.

6. A point replication method based on fixed deviation according to claim 5, characterized in that: The approximate rotation matrix obtained according to the RT matrix is: within the range that satisfies the conditions of the rotation matrix R, the rotation matrix that is closest to the rotation matrix R in terms of norm.

7. A point replication method based on fixed deviation according to claim 6, characterized in that: The approximate rotation matrix Obtained through the SVD algorithm.

8. The method for point replication based on fixed deviation according to claim 6, characterized in that: The approximate rotation matrix It is obtained by an approximate closed-form solution algorithm.

9. The method for point replication based on fixed deviation according to claim 6, characterized in that: The method according to the first point data, the second point data and the approximate rotation matrix Get the approximate translation matrix The steps include: Build The matrix gets the approximate translation matrix Right now Where P A is the first point data, P B is the second point data, is the approximate rotation matrix, is the approximate translation matrix.

10. A point replication method based on fixed deviation according to claim 9, characterized in that: The step of converting the initial point data on the first machine into the duplicate point data on the second machine through the conversion relationship model comprises: The initial point data is obtained by The matrix solution obtains the replicated point data, namely: Where P A ′ is the initial point data, P B ' B To copy point data, is the approximate rotation matrix, is the approximate translation matrix.

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