CN114387228A - Automatic workpiece locating and aligning method based on line structured light - Google Patents

Abstract

The invention relates to the field of electronic detection methods, in particular to a linear structured light-based automatic workpiece locating and aligning method. The method comprises the following steps: s1, fixing a workpiece; s2, irradiating line-structured light; s3, acquiring a light bar image; s4, image processing; s5, acquiring three-dimensional coordinates of points on the light bars; and S6, calculating the deviation from the ideal position. The invention has the advantages of high processing efficiency, low labor cost, flexible operation and high processing precision, can effectively shorten the processing period, is suitable for a single-piece small-batch mode, and can better meet the current market demand.

Description

Automatic workpiece locating and aligning method based on line structured light

Technical Field

The invention relates to the field of electronic detection methods, in particular to a linear structured light-based automatic workpiece locating and aligning method.

Background

In the field of machining, workpiece positioning is an important step in the workpiece machining process. After the workpiece is positioned, workpiece clamping and workpiece machining operations are performed, which affects the efficiency of the whole workpiece machining process and the workpiece machining precision. In a mass production mode, a dedicated high precision jig may be employed. However, in the process of processing single-piece small-batch workpieces, manual alignment is still mainly performed by operators. Under the condition, the processing precision is greatly reduced, the processing efficiency is seriously reduced, the labor cost is greatly increased, and the utilization rate of a processing center is reduced. Therefore, the conventional method cannot well meet the current market demand. Therefore, the present invention provides an automatic locating and aligning method. Different from the traditional workpiece positioning method, the automatic locating and aligning method does not need to accurately align the initial posture of the workpiece, and adopts active locating and pose adjusting to replace passive locating. The automatic locating and aligning method is high in machining efficiency, low in labor cost, flexible in operation, high in machining precision, capable of effectively shortening the machining period and suitable for a single-piece small-batch mode.

Disclosure of Invention

The invention aims to overcome the defects in the prior art, and provides a linear structured light-based automatic workpiece locating and aligning method which can be used for automatic locating and pose adjustment of a workpiece on a horizontal machining center.

The technical scheme for realizing the purpose of the invention is as follows:

a workpiece automatic locating and aligning method based on line structured light comprises the following steps:

s1, fixing a workpiece: mounting a workpiece on a rotary worktable of a horizontal machining center by using a clamp or a fixing element;

s2, illuminating line structure light: irradiating the linear structure light on the surface of a workpiece by using a laser, wherein bright stripes appear on the surface of the workpiece;

s3, acquiring a light bar image: acquiring an image of the light bar by using a CCD (charge coupled device) camera to obtain a two-dimensional image of the light bar;

s4, image processing: carrying out image filtering, image segmentation and contour extraction on the obtained image;

s5, acquiring three-dimensional coordinates of points on the light bars: the two-dimensional image coordinate can be converted into a three-dimensional actual coordinate through CCD camera calibration;

s6, calculating the deviation between the position and the ideal position: the three-dimensional actual coordinates can accurately describe the position of the workpiece on the machining center, and the position deviation comprising the rotation amount and the translation amount can be obtained by comparing the three-dimensional actual coordinates with the correct position of the workpiece;

s7, adjusting the pose of the workpiece: and adjusting the workpiece to a correct position through the rotary worktable.

Further, in S3, the CCD camera is calibrated to obtain a conversion relationship between the three-dimensional coordinates and the two-dimensional coordinates, the CCD camera includes a left camera and a right camera, and the calibration of the positional relationship between the two cameras is required in addition to the calibration of the internal and external parameters of the camera, the camera calibration target is first placed in the field of view of the two cameras, and the translation amount between the coordinate systems of the left camera and the right camera and the world coordinate system is set to T₁、T₂The rotation matrix is R₁、R₂The coordinate of a certain calibration point on the calibration target under the coordinate system of the left camera is P_l＝(X_cl,Y_cl,Z_cl)^TAnd the coordinate is Pr ═ X under the coordinate system of the right camera_cr,Y_cr,Z_cr)^TIn the world coordinate system, the coordinate is P ═ X (Xw, Y)_w,Z_w)^T(ii) a Then there are:

can obtain

Wherein,

by the above formula, the conversion relation between the left camera coordinate system and the right camera coordinate system can be obtained;

the optical axes of the two cameras are parallel, the optical axes are vertical to the image plane, and the distance between the two cameras is d; c_l、C_rSetting the three-dimensional point P as (X) under the left camera coordinate system_cl,Y_cl,Z_cl) In the right camera coordinate system is (X)_cr,Y_cr,Z_cr) The relationship between the pixel coordinate system and the image coordinate system is as follows:

wherein u0 and v0 are camera internal parameters (u)_l,v_l)、(u_r,v_r) Is the coordinate of P in the left and right pixel coordinate systems, (x)_l,y_l)、(x_r,y_r) Is the coordinate of P in the image coordinate system;

combining the relationship between the image coordinate system and the camera coordinate system, we can obtain:

wherein, f is the focal length of the camera, α is f/dx, β is f/dy is the camera parameter, and the coordinate conversion between the image coordinate system and the world coordinate system can be realized by the above formula.

Further, in S4, after the light bars are acquired, the center of the light bars is extracted by using a gray scale gravity center method, where a calculation formula of the gray scale gravity center method is as follows:

wherein (X)_i,Y_i) Is the coordinate, phase, of a certain pixel point in the plane of the light stripThe gray value of the pixel point is I (X)_i,Y_i) (i is 1,2, …, N), where N is the number of pixels in the cross-section and (X)_c,Y_c) Is the coordinate of the center of the light bar. Thus, coordinates of the center point of the light bar can be obtained.

In S6, the projection is made on a plane where Y is 0, and two arbitrary points a on the projection are defined_i，B_jRespectively has coordinates of A_i(X_Ai,Z_Ai)，Bj(X_Bj,Z_Bj) (ii) a Line segment A is drawn by passing through A_iC_i,jParallel to X_wShaft, passing through B_jMaking a line segment B_jC_i,jParallel to Z_wShaft, A_iC_i,jAnd B_iC_i,jIntersect at C_i,jThen C is_i,jCoordinate is C_i,j(X_Bj,Z_Ai) And is combined with A_iC_i,jAnd A_iB_jAngle alpha of_i,j(ii) a Then there are:

it is possible to obtain:

the final required rotation angle is:

wherein N is the number of the obtained coordinate points;

if the measured coordinate point is (Xi, Yi) and the coordinate point corresponding to the correct position is (Xi, Yi), the translation amount of the position deviation is:

after the technical scheme is adopted, the invention has the following positive effects:

(1) the invention has the advantages of high processing efficiency, low labor cost, flexible operation and high processing precision, can effectively shorten the processing period, is suitable for a single-piece small-batch mode, and can better meet the current market demand.

Drawings

In order that the present disclosure may be more readily and clearly understood, reference is now made to the following detailed description of the present disclosure taken in conjunction with the accompanying drawings, in which

FIG. 1 is a work flow diagram;

FIG. 2 is a diagram of a seek system;

FIG. 3 is a diagram of a camera system model;

fig. 4 is a schematic view of the rotation angle.

Detailed Description

A workpiece automatic locating and aligning method based on line structured light comprises the following steps:

s1, fixing a workpiece: mounting a workpiece on a rotary worktable of a horizontal machining center by using a clamp or a fixing element;

s2, illuminating line structure light: irradiating the linear structure light on the surface of a workpiece by using a laser, wherein bright stripes appear on the surface of the workpiece;

s3, acquiring a light bar image: acquiring an image of the light bar by using a CCD (charge coupled device) camera to obtain a two-dimensional image of the light bar;

s4, image processing: processing the obtained image such as image filtering, image segmentation, contour extraction and the like;

s5, acquiring three-dimensional coordinates of points on the light bars: the two-dimensional image coordinate can be converted into a three-dimensional actual coordinate through CCD camera calibration;

s6, calculating the deviation between the position and the ideal position: the three-dimensional actual coordinates can accurately describe the position of the workpiece on the machining center, and the position deviation comprising the rotation amount and the translation amount can be obtained by comparing the three-dimensional actual coordinates with the correct position of the workpiece;

s7, adjusting the pose of the workpiece: and adjusting the workpiece to a correct position through the rotary worktable.

The three-dimensional image information of the surface of the workpiece of the CCD camera is obtained by adopting a binocular linear structured light measurement technology, and a measurement system consists of a laser, the CCD camera and a computer system. The CCD camera comprises a left camera and a right camera.

The software part consists of structured light scanning control, image processing, contour extraction and the like. When the laser projects line structured light onto the surface of the workpiece, a light bar is formed on the surface of the workpiece, the light bar containing three-dimensional coordinate information of the measured surface. Furthermore, the position finding system adopts two CCD cameras for shooting the surface of the workpiece from different directions to simulate human eyes so as to obtain the three-dimensional information of the surface of the workpiece, thereby obtaining the coordinate information of multiple points on the surface of the workpiece. The three-dimensional coordinate information on the light bars is converted into two-dimensional image coordinate system information by the camera. In this step, calibration of the camera is essential to obtain the conversion relationship between the actual three-dimensional coordinates and the two-dimensional coordinates of the image. The conversion between the three-dimensional coordinate and the two-dimensional coordinate can be realized through the parameter matrix obtained by calibrating the camera.

And performing image preprocessing on the obtained light bar image containing the coordinate information and extracting the light bar center. To obtain a clear and complete picture with high quality, the original image must be preprocessed by filtering, image segmentation and the like, so that the precision is improved. And then carrying out edge detection and feature point extraction on the image so as to obtain the required light stripe center information.

And converting the obtained central coordinates of the stripes into three-dimensional world coordinates, and calculating the position deviation between the central coordinates and the correct position through certain mathematical operation. This positional deviation specifically includes a rotation amount and a displacement amount.

Example 1

The specific working flow of the method is shown in fig. 1, and the locating system is shown in fig. 2. First, the workpiece is mounted on a rotary table of a horizontal machining center with a jig or a fixing member without putting the workpiece at its correct position. The line structure light is irradiated on the surface of the workpiece by using a laser, and bright stripes appear on the surface of the workpiece. The points on the light bar contain three-dimensional coordinate information of the object points on the workpiece. And (3) carrying out image acquisition on the light bar by using a CCD (charge coupled device) camera to obtain a two-dimensional image of the light bar. The obtained image is subjected to image filtering, image segmentation, contour extraction and other processing, and a matrix obtained through camera calibration can convert two-dimensional image coordinates into three-dimensional actual coordinates. A series of three-dimensional coordinates can accurately describe the position of the workpiece on the machining center, and the position deviation comprising the rotation amount and the translation amount can be obtained by comparing the position of the workpiece with the correct position. And finally, adjusting the workpiece to a correct position through the rotary worktable.

The purpose of camera calibration is to obtain a conversion relationship between a three-dimensional coordinate and a two-dimensional coordinate, and besides calibration of internal and external parameters of a camera, calibration of a position relationship between two cameras is also needed. Firstly, a camera calibration target is placed in the visual field range of a two-camera. Let T be the translation between the left and right camera coordinate systems and the world coordinate system₁、T₂The rotation matrix is R₁、R₂. The coordinate of a certain calibration point on the calibration target under the coordinate system of the left camera is P_l＝(X_cl,Y_cl,Z_cl)^TAnd the coordinate is Pr ═ X under the coordinate system of the right camera_cr,Y_cr,Z_cr)^TIn the world coordinate system, the coordinate is P ═ X (Xw, Y)_w,Z_w)^T. Then there are:

can obtain

Wherein,

through the above formula, the conversion relationship between the left and right camera coordinate systems can be obtained.

The camera system is shown in fig. 3, where the optical axes of the two cameras are parallel and the optical axes are perpendicular to the image plane. The distance between the two cameras is d. C_l、C_rLeft and right camera coordinate systems. Let three-dimensional point P be (X) under the left camera coordinate system_cl,Y_cl,Z_cl) In the right camera coordinate system is (X)_cr,Y_cr,Z_cr). The relationship between the pixel coordinate system and the image coordinate system is:

wherein u0 and v0 are camera internal parameters (u)_l,v_l)、(u_r,v_r) Is the coordinate of P in the left and right pixel coordinate systems, (x)_l,y_l)、(x_r,y_r) Is the coordinate of P in the image coordinate system.

Combining the relationship between the image coordinate system and the camera coordinate system, we can obtain:

wherein, f is the focal length of the camera, α ═ f/dx, β ═ f/dy is the camera intrinsic parameter. The coordinate transformation between the image coordinate system and the world coordinate system can be realized through the above formula.

After the CCD camera obtains the light bar image, the obtained image should be preprocessed and the light bar center extracted. The image preprocessing mainly comprises eliminating operations such as image noise and the like to enable the image to better reflect real light bars and prepare for extracting the centers of the subsequent light bars. The link is mainly divided into image filtering, image segmentation and light bar center extraction.

Firstly, the median filtering is adopted to eliminate impulse noise, and meanwhile, the influence on image edge information can not be caused. Then, histogram processing is adopted to eliminate irrelevant information in the image and make important characteristic information in the image stand out, thereby improving the image quality. Image segmentation is performed next, which aims to extract bright areas in the image to facilitate subsequent feature extraction. A threshold segmentation method is used here. The threshold segmentation is mainly based on the gray difference between a target and a background in an image, a reasonable threshold is selected, and a pixel point in the image is compared with the selected threshold so as to judge whether the point is the target or the background. After the image is divided, clear light bar images can be obtained, and then the light bars can be extracted from the images by carrying out image thinning operation. And extracting the light strip center by adopting a gray gravity center method. The gray center-of-gravity method is to use the center of gray distribution of pixels in the image as the center point of the light bar, so as to reduce the error of uneven gray distribution of the light bar. The calculation formula of the gray scale gravity center method is as follows:

wherein (X)_i,Y_i) The gray value of a pixel point is I (X) which is the coordinate of a certain pixel point in the plane of the light strip_i,Y_i) (i is 1,2, …, N), where N is the number of pixels in the cross-section and (X)_c,Y_c) Is the coordinate of the center of the light bar. Thus, coordinates of the center point of the light bar can be obtained.

Through the steps, the coordinate information of the surface of the workpiece can be obtained, and then the position deviation between the surface of the workpiece and the correct position is calculated.

As shown in fig. 4, the coordinate points on the workpiece surface obtained in the above-described steps are projected on a plane where Y is 0, and arbitrary two points a on the projection are set_i，B_jRespectively has coordinates of A_i(X_Ai,Z_Ai)，Bj(X_Bj,Z_Bj). Line segment A is drawn by passing through A_iC_i,jParallel to X_wShaft, passing through B_jMaking a line segment B_jC_i,jParallel to Z_wShaft, A_iC_i,jAnd B_iC_i,jIntersect at C_i,jThen C is_i,jCoordinate is C_i,j(X_Bj,Z_Ai) And is combined with A_iC_i,jAnd A_iB_jAngle alpha of_i,j. Then there are:

it is possible to obtain:

the final required rotation angle is:

wherein N is the number of coordinate points obtained.

If the measured coordinate point is (Xi, Yi) and the coordinate point corresponding to the correct position is (Xi, Yi), the translation amount of the position deviation is:

and finally, sending the position deviation to a machining center, and placing the workpiece at a correct position through a rotary worktable.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (4)

1. A workpiece automatic locating and aligning method based on line structured light is characterized in that: the method comprises the following steps:

s1, fixing a workpiece: mounting a workpiece on a rotary worktable of a horizontal machining center by using a clamp or a fixing element;

s2, illuminating line structure light: irradiating the linear structure light on the surface of a workpiece by using a laser, wherein bright stripes appear on the surface of the workpiece;

s3, acquiring a light bar image: acquiring an image of the light bar by using a CCD (charge coupled device) camera to obtain a two-dimensional image of the light bar;

s4, image processing: carrying out image filtering, image segmentation and contour extraction on the obtained image;

s5, acquiring three-dimensional coordinates of points on the light bars: the two-dimensional image coordinate can be converted into a three-dimensional actual coordinate through CCD camera calibration;

s6, calculating the deviation between the position and the ideal position: the three-dimensional actual coordinates can accurately describe the position of the workpiece on the machining center, and the position deviation comprising the rotation amount and the translation amount can be obtained by comparing the three-dimensional actual coordinates with the correct position of the workpiece;

s7, adjusting the pose of the workpiece: and adjusting the workpiece to a correct position through the rotary worktable.

2. The method of claim 1, wherein the method comprises: in S3, the CCD camera is calibrated to obtain a conversion relationship between the three-dimensional coordinates and the two-dimensional coordinates, the CCD camera includes a left camera and a right camera, and the calibration of the positional relationship between the two cameras is required in addition to the calibration of the internal and external parameters of the camera, first, the camera calibration target is placed in the visual field of the two cameras, and the translation amount between the coordinate systems of the left camera and the right camera and the world coordinate system is set to T₁、T₂The rotation matrix is R₁、R₂The coordinate of a certain calibration point on the calibration target under the coordinate system of the left camera is P_l＝(X_cl,Y_cl,Z_cl)^TAnd the coordinate is Pr ═ X under the coordinate system of the right camera_cr,Y_cr,Z_cr)^TIn the world coordinate system, the coordinate is P ═ X (Xw, Y)_w,Z_w)^T(ii) a Then there are:

can obtain

Wherein,

by the above formula, the conversion relation between the left camera coordinate system and the right camera coordinate system can be obtained;

the optical axes of the two cameras are parallel, the optical axes are vertical to the image plane, and the distance between the two cameras is d; c_l、C_rSetting the three-dimensional point P as (X) under the left camera coordinate system_cl,Y_cl,Z_cl) In the right camera coordinate system is (X)_cr,Y_cr,Z_cr) The relationship between the pixel coordinate system and the image coordinate system is as follows:

wherein u0 and v0 are camera internal parameters (u)_l,v_l)、(u_r,v_r) Is the coordinate of P in the left and right pixel coordinate systems, (x)_l,y_l)、(x_r,y_r) Is the coordinate of P in the image coordinate system;

combining the relationship between the image coordinate system and the camera coordinate system, we can obtain:

wherein, f is the focal length of the camera, α is f/dx, β is f/dy is the camera parameter, and the coordinate conversion between the image coordinate system and the world coordinate system can be realized by the above formula.

3. The method of claim 1, wherein the method comprises: in S4, after the light bars are obtained, the light bar centers are extracted by a gray scale gravity center method, where the calculation formula of the gray scale gravity center method is:

wherein (X)_i,Y_i) In the plane of the light barThe gray value of a certain pixel point is I (X) according to the coordinate of the corresponding pixel point_i,Y_i) (i is 1,2, …, N), where N is the number of pixels in the cross-section and (X)_c,Y_c) Is the coordinate of the center of the light bar. Thus, coordinates of the center point of the light bar can be obtained.

4. The method of claim 1, wherein the method comprises: in S6, the projection is made on a plane where Y is 0, and arbitrary two points a on the projection are set_i，B_jRespectively has coordinates of A_i(X_Ai,Z_Ai)，Bj(X_Bj,Z_Bj) (ii) a Line segment A is drawn by passing through A_iC_i,jParallel to X_wShaft, passing through B_jMaking a line segment B_jC_i,jParallel to Z_wShaft, A_iC_i,jAnd B_iC_i,jIntersect at C_i,jThen C is_i,jCoordinate is C_i,j(X_Bj,Z_Ai) And is combined with A_iC_i,jAnd A_iB_jAngle alpha of_i,j(ii) a Then there are:

it is possible to obtain:

the final required rotation angle is:

wherein N is the number of the obtained coordinate points;

if the measured coordinate point is (Xi, Yi) and the coordinate point corresponding to the correct position is (Xi, Yi), the translation amount of the position deviation is:

Images