CN112935562A - Laser precision machining method based on paraxial offline measurement - Google Patents
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Abstract
The invention discloses a laser precision machining method based on paraxial offline measurement, which obtains a one-to-one corresponding relation between a camera and a world three-dimensional coordinate system of an object to be measured through camera imaging to obtain an image and a conversion matrix under a world coordinate, obtains the relative position relation of the object to be machined relative to a laser machining plane through the conversion matrix by utilizing the conversion relation between the world coordinate and a pixel coordinate, and thus skips the complicated step of re-matching the machining plane and the machining object after moving the object every time. Meanwhile, the method can realize the paraxial arrangement of the camera and the object to be processed at any pose, effectively solves the problems of complicated process and low precision of coaxial processing, has higher processing precision and simple process, and provides a novel method with low cost, high efficiency and accuracy for the field of laser precision processing.
Description
Technical Field
The invention relates to the field of laser precision machining, in particular to a laser precision machining method based on paraxial offline measurement.
Background
In the field of conventional laser precision machining, laser machining is a precision operation that meets the requirements for precision objects. The laser processing system mainly comprises a mirror vibrating system for reflecting laser and a CCD image acquisition system for distinguishing a processing position, wherein the mirror vibrating system collects the laser to the position to be processed of the laser processing operation platform according to the principle of multiple reflection and refraction, and the CCD image acquisition system is mainly used for acquiring image information of an object to be processed, so that the laser can be accurately processed conveniently. The existing laser processing technology mainly utilizes a coaxial method, and the main operation mode is as follows: the method comprises the steps of firstly placing an object to be processed on a laser processing operation platform, obtaining accurate image information of the object to be processed through a CCD image acquisition system, removing the CCD image acquisition system and replacing the CCD image acquisition system with a galvanometer system for laser processing after obtaining the information of the object to be processed through accurate measurement, and processing the object to be processed through the relationship between the galvanometer system and the CCD image acquisition system which is calibrated in advance.
The coaxial processing mode needs to continuously change the galvanometer system and the CCD image system to sequentially perform step operation, meanwhile, the position of an object to be processed needs to be kept constant, if the position of the object to be processed is changed, the corresponding relation between the CCD image system and the galvanometer system needs to be obtained again, the process is complicated, and the problem of low processing precision is caused due to errors in the moving process.
The existing laser processing field is also processed by a paraxial method, the paraxial camera relative position relation and an image of an object to be processed are converted by an image conversion and affine conversion mode, and then the processing operation is carried out. Therefore, it is important to solve such problems.
Disclosure of Invention
In order to solve the problems, the invention provides a laser precision machining method based on paraxial offline measurement, which obtains a one-to-one correspondence relationship between a camera and a world three-dimensional coordinate system of an object to be measured through camera imaging to obtain a conversion matrix under an image and a world coordinate, obtains a relative position relationship of the object to be machined relative to a laser machining plane through the conversion matrix by utilizing the conversion relationship between the world coordinate and a pixel coordinate, and thus skips the complicated step of re-matching the machining plane and the machining object after moving the object every time.
In order to realize the technical scheme, the invention provides a laser precision machining method based on paraxial offline measurement, which comprises the following steps of:
the method comprises the following steps: acquiring sub-pixel coordinates of corner points of a shot picture, performing multi-shot of changing any position and any posture on a chessboard calibration plate with known size parameters by using a camera with fixed focal length to acquire an image, converting the image into a gray-scale image, binarizing the processed gray-scale image, judging whether the corner points exist by using a corner point detection algorithm, and if the corner points exist, acquiring accurate sub-pixel coordinates of the corner points;
step two: acquiring internal parameters of camera equipment, defining corresponding world coordinates corresponding to angular points of an image, acquiring one-to-one correspondence between the world coordinates of the angular points and the image coordinates, selecting the angular points of a plurality of groups of images and points on a corresponding world coordinate system, and acquiring the internal parameters and distortion coefficients for shooting the group of image camera equipment through a calibration algorithm;
step three: acquiring external parameters of camera equipment for shooting the group of pictures, keeping internal parameters such as focal length of the shooting camera unchanged, selecting three non-collinear points around the object to be processed on a laser processing plane, shooting the object to be processed by the camera at any position and in any posture to obtain an image, and obtaining the external parameters of the shot camera equipment through a multi-point positioning algorithm;
step four: fixing the position of the camera with the obtained internal and external parameters, keeping the imaging of the object to be processed in the camera view finding range, moving the object to be processed at will, acquiring the moved image again by the camera, obtaining pixel points on the shot image pixel by pixel, obtaining the visual relation between the laser processing plane and the image through the conversion matrix calculated by the internal and external parameters, and performing precision processing operation on any position on the image on the laser processing plane.
In a further improvement, in the step one, the gray scale map of the image is to set the gray scale value of the image to be 0 to 255, 255 represents all white, and 0 represents all black; the white and black are divided into a plurality of equal steps according to the logarithmic relation, and the gray level is divided into 256 steps.
In the first step, the corner detection algorithm includes the following steps of continuously taking out each picture of a group of pictures which are taken and subjected to graying processing, and executing the following operations for each picture:
the method comprises the following steps: preprocessing an image, binarizing the image, and converting a gray level image into a binary image;
step two: searching adjacent grids of each grid, recording the number of the adjacent grids, and classifying all the adjacent grids according to the principle that all the grids in the class are adjacent;
step three: judging whether the squares in each class are the sought chessboard squares or not according to the known number of the angular points, confirming whether the positions and the number of the squares are correct or not, if so, extracting the connection points of any two squares of the sought chessboard squares, namely the sought angular points, and obtaining the accurate sub-pixel coordinates of all the angular points; if not, the chessboard angular point detection fails.
In a further improvement, the camera device external parameter acquisition comprises the following steps, for the camera model with the obtained internal parameters, the following operations are carried out: keeping the internal parameters such as the focal length of a camera and the like unchanged, placing an object to be processed on a laser processing operation platform, selecting three non-collinear points around the object to be processed on a laser processing plane, shooting the object to be processed by using a laser, shooting an image containing the object to be processed and the three non-collinear points shot by using the laser by using the camera at any position and posture of a paraxial of a laser processing platform, and obtaining the external parameters of the shooting camera at the moment through a multi-point positioning algorithm.
The further improvement lies in that: the multi-point positioning algorithm comprises the following steps of executing the following operations on the obtained camera shooting images:
the method comprises the following steps: inputting laser processing plane coordinates of three points around an object to be processed selected on a laser processing plane;
step two: inputting corresponding world coordinates of three points on a laser processing plane which is shot by the laser;
step three: and by means of cosine law, a translation and rotation matrix of the camera system image coordinate system shot at the moment relative to the world coordinate system can be obtained by utilizing a point cloud registration method.
The further improvement lies in that: the method comprises the steps of obtaining a matrix representation form of all pixel points on a shot image through a pixel-by-pixel retrieval mode of an image shot again after an object to be processed is moved, calculating a transformation matrix obtained through internal and external parameters and all the pixel points to obtain new transformed pixel point matrix coordinates, remapping all the coordinates on another plane through a visualization method, placing the visualized image obtained at the moment on a laser processing plane according to scales, obtaining the corresponding relation of the laser processing plane relative to the object to be processed, and performing laser precision processing.
The invention has the beneficial effects that: the invention provides a laser precision machining method based on paraxial offline measurement, which obtains a one-to-one corresponding relation between a camera and a world three-dimensional coordinate system of an object to be machined through camera imaging to obtain an image and a conversion matrix under a world coordinate, obtains the relative position relation of the object to be machined relative to a laser machining plane through the conversion matrix by utilizing the conversion relation between the world coordinate and a pixel coordinate, and thus skips the complicated step of re-matching the machining plane and the machining object after moving the object every time. Meanwhile, the method can realize the paraxial arrangement of the camera and the object to be processed at any pose, effectively solves the problems of complicated process and low precision of coaxial processing, has higher processing precision and simple process, and provides a novel method with low cost, high efficiency and accuracy for the field of laser precision processing.
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FIG. 1 is a flow chart of the present invention.
Fig. 2 is a schematic structural diagram of the overall device of the present invention.
Fig. 3 is an exemplary schematic view of an object to be processed according to the present invention.
Fig. 4 is a schematic diagram illustrating an exemplary operation effect of the present invention.
Detailed Description
In order to further understand the present invention, the following detailed description will be made with reference to the following examples, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
According to the illustration in fig. 1, the embodiment provides a laser precision machining method based on paraxial offline measurement, which comprises the following steps:
the method comprises the following steps: acquiring sub-pixel coordinates of corner points of a shot picture, performing multi-shot of changing any position and any posture on a chessboard calibration plate with known size parameters by using a camera with fixed focal length to acquire an image, converting the image into a gray-scale image, binarizing the processed gray-scale image, judging whether the corner points exist by using a corner point detection algorithm, and if the corner points exist, acquiring accurate sub-pixel coordinates of the corner points;
step two: acquiring internal parameters of camera equipment, defining corresponding world coordinates corresponding to angular points of an image, acquiring one-to-one correspondence between the world coordinates of the angular points and the image coordinates, selecting the angular points of a plurality of groups of images and points on a corresponding world coordinate system, and acquiring the internal parameters and distortion coefficients for shooting the group of image camera equipment through a calibration algorithm;
step three: acquiring external parameters of camera equipment for shooting the group of pictures, keeping internal parameters such as focal length of the shooting camera unchanged, selecting three non-collinear points around the object to be processed on a laser processing plane, shooting the object to be processed by the camera at any position and in any posture to obtain an image, and obtaining the external parameters of the shot camera equipment through a multi-point positioning algorithm;
step four: fixing the position of the camera with the obtained internal and external parameters, keeping the imaging of the object to be processed in the camera view finding range, moving the object to be processed at will, acquiring the moved image again by the camera, obtaining pixel points on the shot image pixel by pixel, obtaining the visual relation between the laser processing plane and the image through the conversion matrix calculated by the internal and external parameters, and performing precision processing operation on any position on the image on the laser processing plane.
In the embodiment, in the first step, the grayscale map of the image is to set the grayscale value of the image to 0 to 255, 255 represents full white, and 0 represents full black; the white and black are divided into a plurality of equal steps according to the logarithmic relation, and the gray level is divided into 256 steps.
In this embodiment, in the first step, the corner detection algorithm includes the following steps of continuously taking out each picture of a group of pictures which are taken and subjected to graying processing, and executing the following operations for each picture:
the method comprises the following steps: preprocessing an image, binarizing the image, and converting a gray level image into a binary image;
step two: searching adjacent grids of each grid, recording the number of the adjacent grids, and classifying all the adjacent grids according to the principle that all the grids in the class are adjacent;
step three: judging whether the squares in each class are the sought chessboard squares or not according to the known number of the angular points, confirming whether the positions and the number of the squares are correct or not, if so, extracting the connection points of any two squares of the sought chessboard squares, namely the sought angular points, and obtaining the accurate sub-pixel coordinates of all the angular points; if not, the chessboard angular point detection fails.
In this embodiment, the camera device extrinsic parameter acquisition includes the following steps, for the camera model with the obtained intrinsic parameters, to perform the following operations: keeping the internal parameters such as the focal length of a camera and the like unchanged, placing an object to be processed on a laser processing operation platform, selecting three non-collinear points around the object to be processed on a laser processing plane, shooting the object to be processed by using a laser, shooting an image containing the object to be processed and the three non-collinear points shot by using the laser by using the camera at any position and posture of a paraxial of a laser processing platform, and obtaining the external parameters of the shooting camera at the moment through a multi-point positioning algorithm.
In this embodiment, the multi-point positioning algorithm includes the following steps, for the obtained camera shooting image, to perform the following operations:
the method comprises the following steps: inputting laser processing plane coordinates of three points around an object to be processed selected on a laser processing plane;
step two: inputting corresponding world coordinates of three points on a laser processing plane which is shot by the laser;
step three: and by means of cosine law, a translation and rotation matrix of the camera system image coordinate system shot at the moment relative to the world coordinate system can be obtained by utilizing a point cloud registration method.
And obtaining a matrix representation form of all pixel points on the shot image by a pixel-by-pixel retrieval mode of the image re-shot after the object to be processed is moved, calculating a transformation matrix obtained through internal and external parameters and all the pixel points to obtain new transformed pixel point matrix coordinates, re-mapping all the coordinates on another plane by a visualization method, putting the visualized image obtained at the moment on a laser processing plane according to scales, thus obtaining the corresponding relation of the laser processing plane relative to the object to be processed, and performing laser precision processing.
As shown in fig. 2, it is a camera capable of moving and changing the pose at will, and a conventional laser and laser processing platform assembly. In the device of the embodiment, the camera can be used for shooting a plurality of different angles of the laser processing platform by randomly changing the position, the posture and the focal length. The device in this example is only an example, and there are a plurality of laser processing platforms and cameras with different systems and specifications in actual operation, so that any similar device can be selected to perform the operation flow described in this embodiment in actual application.
As shown in fig. 3, a checkerboard is taken as an example of the present invention to perform a related explanation, in this embodiment, the default is to perform the step of obtaining internal parameters in the flow of fig. 1, and in the process of obtaining internal parameters by shooting a plurality of standard checkerboard calibration plates for calibration, the more pictures shot by the camera at different angles, the more accurate the obtained internal parameters, and the higher the final processing precision. In the example, the object to be processed is a checkerboard of 2mm × 2mm and is placed on a laser processing platform, at this time, the camera in the device shown in fig. 2 can select any position capable of shooting the object to be processed to shoot a plurality of objects at different poses, any 3 non-collinear points are selected from the obtained shot image, 3 corresponding points on the actually shot object to be processed are selected, and a rotation and translation matrix of the camera in the shooting state at this time is obtained through a multi-point positioning algorithm. And calculating the obtained internal and external parameters of the camera to obtain a conversion matrix of the image coordinate system and the world coordinate system, fixing the camera at the moment, not moving any more, and then randomly changing the position of the object to be processed relative to the laser processing platform, wherein the position of the object to be processed only needs to be ensured within the imaging range of the camera. The camera is used for shooting the moved object to be processed again, the relative position of the moved object relative to the laser is obtained through pixel-by-pixel calculation through the obtained conversion matrix, the relative position relation is expressed through a visualization method, and the visualized image corresponds to the laser processing plane, so that the actual operation can be directly carried out on the object to be processed on the laser processing plane. This example is merely an example, and to facilitate direct observation, a checkerboard calibration board is taken as an example for description, and in actual operation, any object may be selected to perform the operation flow described in this example.
As shown in fig. 4, the image is an actual operation result obtained after the steps shown in the flow chart of the apparatus shown in fig. 1-3 are performed, it should be noted that a range indicated by a shaded portion in fig. 4 is a range actually corresponding to the laser processing plane of fig. 3 after the movement, lower scales in fig. 4 are corresponding scales of the actual laser processing plane, and a dot matrix in fig. 4 is a corner position of a checkerboard in fig. 3, which has an effect of facilitating positioning, and directly represents a relative position of an object to be processed in the image through the dot matrix, thereby facilitating subsequent laser precision processing operation. The feasibility and the accuracy of the invention are proved by the embodiment.
Example two
A calibration algorithm comprises the following steps, for each image from which sub-pixel coordinate corners are successfully acquired:
the method comprises the following steps: defining world coordinate points corresponding to the coordinates of the angular points of the chessboard pattern calibration board on the image, wherein the world coordinate points need to be the same as the theoretical condition, namely the coordinate difference between two angular points is the real distance between the chessboard pattern calibration board grids used for shooting;
step two: and (4) inputting the world coordinates and the pixel coordinates of the defined corresponding corner points into a function in a matrix form to calculate the internal parameters and the distortion coefficients of the camera.
In this embodiment, the relationship between the pixel coordinates and the world coordinates is as follows:
wherein u and v represent coordinates in a pixel coordinate system, s represents a scale factor, fx, fy, u0, v0 and gamma represent 5 camera internal parameters, R and t represent camera external parameters, Xw, Yw and Zw (assuming that a calibration chessboard is positioned on a plane of which Zw is 0 in the world coordinate system) represent coordinates in the world coordinate system, that is, a plurality of sets of world coordinates and corresponding pixel coordinate points are input to obtain required camera internal parameters.
In this embodiment, the relationship of the distortion coefficients is:
u1＝u+(u-u0)[k1(x2+y2)+k2(x2+y2)2]
v1＝v+(v-v0)[k1(x2+y2)+k2(x2+y2)2]
wherein, (u, v) represents pixel coordinates of ideal distortion-free, (u1, v1) represents pixel coordinates in the case of distortion of an actual radial image, and (u0, v0) represents principal points, and is obtained directly in the obtained internal reference matrix regardless of the presence or absence of distortion.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
Claims (6)
1. A laser precision machining method based on paraxial offline measurement is characterized by comprising the following steps:
the method comprises the following steps: acquiring sub-pixel coordinates of corner points of a shot picture, performing multi-shot of changing any position and any posture on a chessboard calibration plate with known size parameters by using a camera with fixed focal length to acquire an image, converting the image into a gray-scale image, binarizing the processed gray-scale image, judging whether the corner points exist by using a corner point detection algorithm, and if the corner points exist, acquiring accurate sub-pixel coordinates of the corner points;
step two: acquiring internal parameters of camera equipment, defining corresponding world coordinates corresponding to angular points of an image, acquiring one-to-one correspondence between the world coordinates of the angular points and the image coordinates, selecting the angular points of a plurality of groups of images and points on a corresponding world coordinate system, and acquiring the internal parameters and distortion coefficients for shooting the group of image camera equipment through a calibration algorithm;
step three: acquiring external parameters of camera equipment for shooting the group of pictures, keeping internal parameters such as focal length of the shooting camera unchanged, selecting three non-collinear points around the object to be processed on a laser processing plane, shooting the object to be processed by the camera at any position and in any posture to obtain an image, and obtaining the external parameters of the shot camera equipment through a multi-point positioning algorithm;
step four: fixing the position of the camera with the obtained internal and external parameters, keeping the imaging of the object to be processed in the camera view finding range, moving the object to be processed at will, acquiring the moved image again by the camera, obtaining pixel points on the shot image pixel by pixel, obtaining the visual relation between the laser processing plane and the image through the conversion matrix calculated by the internal and external parameters, and performing precision processing operation on any position on the image on the laser processing plane.
2. The laser precision machining method based on paraxial offline measurement according to claim 1, wherein in the step one, the grayscale map of the image is such that the grayscale value of the image is set to 0 to 255, 255 represents full white, and 0 represents full black; the white and black are divided into a plurality of equal steps according to the logarithmic relation, and the gray level is divided into 256 steps.
3. The laser precision machining method based on paraxial offline measurement according to claim 1, wherein in the step one, the corner point detection algorithm comprises the following steps:
the method comprises the following steps: preprocessing an image, binarizing the image, and converting a gray level image into a binary image;
step two: searching adjacent grids of each grid, recording the number of the adjacent grids, and classifying all the adjacent grids according to the principle that all the grids in the class are adjacent;
step three: judging whether the squares in each class are the sought chessboard squares or not according to the known number of the angular points, confirming whether the positions and the number of the squares are correct or not, if so, extracting the connection points of any two squares of the sought chessboard squares, namely the sought angular points, and obtaining the accurate sub-pixel coordinates of all the angular points; if not, the chessboard angular point detection fails.
4. The laser precision machining method based on paraxial offline measurement as claimed in claim 1, wherein the camera equipment external parameter acquisition comprises the following steps: keeping the internal parameters such as the focal length of a camera and the like unchanged, placing an object to be processed on a laser processing operation platform, selecting three non-collinear points around the object to be processed on a laser processing plane, shooting the object to be processed by using a laser, shooting an image containing the object to be processed and the three non-collinear points shot by using the laser by using the camera at any position and posture of a paraxial of a laser processing platform, and obtaining the external parameters of the shooting camera at the moment through a multi-point positioning algorithm.
5. The laser precision machining method based on paraxial offline measurement according to claim 1 or 4, characterized in that: the multipoint positioning algorithm comprises the following steps:
the method comprises the following steps: inputting laser processing plane coordinates of three points around an object to be processed selected on a laser processing plane;
step two: inputting corresponding world coordinates of three points on a laser processing plane which is shot by the laser;
step three: and by means of cosine law, a translation and rotation matrix of the camera system image coordinate system shot at the moment relative to the world coordinate system can be obtained by utilizing a point cloud registration method.
6. The laser precision machining method based on paraxial offline measurement according to claim 1, characterized in that: the method comprises the steps of obtaining a matrix representation form of all pixel points on a shot image through a pixel-by-pixel retrieval mode of an image shot again after an object to be processed is moved, calculating a transformation matrix obtained through internal and external parameters and all the pixel points to obtain new transformed pixel point matrix coordinates, remapping all the coordinates on another plane through a visualization method, placing the visualized image obtained at the moment on a laser processing plane according to scales, obtaining the corresponding relation of the laser processing plane relative to the object to be processed, and performing laser precision processing.
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