CN114494449A - Visual calibration and alignment laminating method for special-shaped product lamination - Google Patents
Visual calibration and alignment laminating method for special-shaped product lamination Download PDFInfo
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Abstract
The invention discloses a visual calibration and alignment fitting method for fitting a special-shaped product, wherein an assembly object is transported through an xy theta material adsorption platform, and the material adsorption platform can move up and down, left and right; fixing and assembling the object through the loading platform; the method comprises the steps of enabling a calibrated material adsorption platform to move through a control mechanism, obtaining a motion coordinate system of the control mechanism, then using a dot matrix calibration plate containing X, Y coordinate information, transmitting the calibration plate to a loading platform incapable of moving through a material adsorption platform, collecting calibration information on the calibration plate through at least one camera installed on the loading platform, obtaining the position of each camera through calculation, calculating a calibration conversion matrix between the position of the camera and the loading platform, and further obtaining a central reference position and a reference angle of an installed workpiece.
Description
Technical Field
The invention relates to a visual calibration and alignment fitting method for fitting of a special-shaped product, and belongs to the technical field of camera calibration.
Background
The workpiece is difficult to guarantee consistency in the material taking position in the assembling process, and high-precision transfer usually needs to adopt a proper mode to carry out vision calibration, position correction and alignment fitting. The position deviation of the assembly workpiece is calculated through a vision calibration system, and the correction position is corrected through a compensation mechanism, so that the assembly is accurate. In order to meet the requirements of large-size and local high-precision detection of workpieces, a visual calibration method with low cost and high precision is particularly needed.
The existing special-shaped attaching method mainly adopts a single camera with a large visual field for imaging, so that the problems that the precision is not high enough, imaging is difficult to achieve under the condition of inconsistent depth of field and the like are brought, and meanwhile, the cost of a large-size camera is high.
The high-precision calibration of a camera system is relatively complex work in the field of computer vision, high-precision and high-stability hardware is often required to be designed to ensure the stability of the whole measuring system in long-time work, and for a complex multi-camera system, the design cost of the hardware is very expensive.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems and the defects in the prior art, the invention provides a visual calibration and alignment bonding method for bonding a special-shaped product, which is a coordinate fusion calibration method. Meanwhile, the invention provides a visual calibration method which can be used for solving the problems of various complex scenes and has the advantages of simple operation and obviously reduced hardware cost.
A visual calibration and alignment fitting method for fitting a special-shaped product is characterized in that an assembly object is transported through an xy theta material adsorption platform, and the material adsorption platform can move up and down (along the theta direction) and left and right (along the x and y directions); and fixing the assembled object through the loading platform. The method comprises the steps of enabling a calibrated material adsorption platform to move through a control mechanism, obtaining a motion coordinate system of the control mechanism, then using a dot matrix calibration plate containing X, Y coordinate information, transmitting the calibration plate to a loading platform incapable of moving through a material adsorption platform, collecting calibration information on the calibration plate through at least one camera installed on the loading platform, obtaining the position of each camera through calculation, calculating a calibration conversion matrix between the position of the camera and the loading platform, and further obtaining a central reference position and a reference angle of an installed workpiece.
The method specifically comprises the following steps:
s1, moving the material adsorption platform to the area where the calibration plate is located to collect the calibration plate image; the direction of a coordinate system of the calibration plate is consistent with the motion direction of the material adsorption platform, and at least one complete dot matrix set area with digital coordinate information is required to be contained in the visual field range of the camera at the photographing phase; the calibration plate is a dot matrix calibration plate with digital coordinate information.
S2, 9 points (coordinate points) are randomly selected from the collected calibration plate picture, calibration plate coordinate data are set (digital information corresponding to the nine points is recorded), the conversion relation between the coordinate system of the material adsorption platform and the coordinate system of the camera vision field associated with the immovable loading platform is completed, the conversion relation can convert pixel coordinates in the camera vision field into physical coordinates on the loading platform, and therefore the posture of the workpiece on the loading platform can be described.
And S3, controlling the material adsorption platform to transfer the calibration plate to the loading platform, and enabling the camera corresponding to the transfer platform to acquire the image of the calibration plate.
S4, randomly selecting 9 points on the image in the camera view field, setting calibration coordinate data, and completing the correlation calculation matrix conversion relation of the loading platform corresponding to the material adsorption platform through a nine-point calibration algorithm, (X)t,Yt) Representing coordinates in the output load platform, (X)i,Yi) Representing image coordinates in the field of view of the platform camera, (X)o,Yo) Representing the position of the origin of the output loading platform in the image coordinate system, wherein alpha is an included angle between the output coordinate system and the image coordinate system, and the conversion formula is as follows:
s5, fixing the calibration plate on the material adsorption platform, enabling the calibration plate to rotate and move for five different angles in the visual field of the corresponding camera, recording image characteristics, and finally calculating the rotation center of the material adsorption platform, if the material adsorption platform is provided with two or more cameras, sequentially calculating and averaging according to the sequence to obtain the rotation center (x2, y2) of the material adsorption platform.
x＝(x1-x2)cosθ-(y1-y2)sinθ+x2
y＝(y1-y2)cosθ+(x1-x2)sinθ+y2
x2 and y2 are rotation centers, x1 and y1 are physical coordinates obtained by calibrating and calculating, theta is a rotation angle, and x and y are coordinates obtained by rotating a selected calibration point around the rotation centers (x2 and y2) by theta.
S6, respectively translating the offset corresponding to the calculated rotation center (x, y) into a nine-point calibration matrix corresponding to each camera to obtain the final accurate physical mapping relation between the material adsorption platform and the image coordinate system:
wherein x and y are offset of the center of rotation, HaScaling the matrix for nine points, HbIs the final mapping matrix.
And S7, moving the material adsorption platform right above the installed camera, recording the reference coordinate of the material adsorption platform at the moment, storing the obtained reference coordinate, and taking the reference coordinate as the position reference of the corresponding camera.
And S8, imaging through a camera arranged below the loading platform, obtaining the pixel coordinates of the object characteristic points by using an image processing algorithm, and converting the pixel coordinates of the object characteristic points into the offset value of the position reference obtained in the step S7 through the calibration matrix obtained in the step S6.
S9, the coordinate system of the mechanism rotation center obtained in step S5 and the posture offset of the workpiece on the platform obtained in step S6 are used to calculate the (x, y, θ) offset amount with respect to the set reference, and the (x, y, θ) offset amount between the new position and the set reference is obtained by the reference set in step S6 and step S7 of the material loading platform.
And S10, superposing the offset of the material adsorption platform and the loading platform calculated in the step S9 to obtain a final action amount (x, y, theta), and executing the assembly action according to the final action amount.
A kind ofFirstly, manufacturing a calibration plate with point coordinates, wherein the point coordinates are coordinates of the point coordinates in a dot matrix, and the coordinate system of the calibration plate is the coordinate system of the dot matrix; placing the calibration plate in the visual field of each camera, so that the cameras shoot the calibration plate with a coordinate system lattice; and controlling each camera to take pictures, reading point coordinates on the calibration plate, converting pixel point coordinates into actual mechanical coordinates by nine-point calibration of the read points, obtaining a radiation transformation matrix from each camera coordinate system to the calibration plate coordinate system, and completing calibration of the camera vision and the mechanism platform at the moment. (X)t,Yt) Represents the coordinates in the output coordinate system, (X)i,Yi) Representing coordinates in the image coordinate system, (X)o,Yo) Representing the position of the origin of the output coordinate system in the image coordinate system, wherein alpha is the included angle between the output coordinate system and the image coordinate system, and the conversion formula is as follows:
the calibration board can calibrate the vision and the platform coordinates, so that the point coordinate transmission carries coordinate information of a point coordinate transmission center in a calibration board coordinate system, and the calibration process does not need grid angular points and fills coordinates of the angular points, so that the calibration process is simple and can be completed without a professional.
The calibration plate is a calibration plate based on CTP (rubber scorch retarder). The standard plate with the CTP (rubber scorch retarder) base has the characteristics of small thermal expansion coefficient, high strength, high hardness, good wear resistance, low thermal conductivity, good acid and alkali resistance and the like, and the good surface diffuse reflection treatment of the standard plate solves the problem of light reflection of a glass calibration plate under the condition of a front light source in the application process, and can better identify the pattern detail information of the calibration plate so as to achieve higher calibration precision and measurement precision.
Therefore, the core of the calibration plate adopting the CTP coordinate with the point is simple and efficient, and the calibration plate can be used for various complex scenes.
The calibration plate is easy to manufacture, the price cost is low, each local coordinate system pattern group can be used for establishing the corresponding relation between the pattern of the calibration plate image and a real object, the requirement on the calibration plate image during calibration is greatly reduced, and the calibration precision and efficiency are improved; the calibration method is easy to execute by a computer, has low requirements on the camera and the shot calibration plate image, is not easy to make mistakes, improves the calibration efficiency and has high calibration precision.
For accurate calibration, the camera model is preferably constrained as the camera sees the calibration targets fill most of the image. Colloquially, if a small calibration plate is used, a combination of many camera parameters may explain the observed image. Empirically, the area of the calibration plate should be at least half of the available pixel area when viewed from the front. The calibration board with point coordinates breaks through the limitation that the traditional origin calibration board needs to meet 1/4 of the visual field in image collection, and is just more convenient to use in various environments.
Drawings
FIG. 1 is a calibration plate layout of an embodiment of the present invention;
FIG. 2 is a schematic view of a calibrated reference position of the upper unit of an embodiment of the present invention;
FIG. 3 is a schematic view of a calibrated reference position of the lower unit of an embodiment of the present invention;
FIG. 4 is a schematic view of an upper and lower unit workpiece installation process according to an embodiment of the present invention;
FIG. 5 is a flowchart of a method for visual calibration and alignment of a shaped product during attachment according to an embodiment of the present invention;
FIG. 6 is a flow chart of a method of vision calibration according to an embodiment of the present invention;
FIG. 7 is a partial view of a calibration plate in the visual calibration method;
FIG. 8 is a schematic diagram of an application scenario of the visual calibration method;
FIG. 9 is a schematic diagram of an application scenario of the visual calibration method;
fig. 10 is a schematic diagram of a camera and calibration board layout in the visual calibration method.
Detailed Description
The present invention is further illustrated by the following examples, which are intended to be purely exemplary and are not intended to limit the scope of the invention, as various equivalent modifications of the invention will occur to those skilled in the art upon reading the present disclosure and fall within the scope of the appended claims.
As shown in fig. 1, a visual calibration and alignment fitting method for fitting a special-shaped product, wherein a material adsorption platform is a platform capable of executing xy theta motion, a loading platform is a bearing platform for fixing and assembling an object, a calibration plate is a group of dot matrix calibration plates with digital physical coordinate information, and the dots are arranged at equal intervals.
As shown in fig. 5, a visual calibration and alignment fitting method for fitting a special-shaped product includes the following steps:
s1: moving the material adsorption platform to the position area of the calibration plate to acquire the image of the calibration plate; the calibration plate is placed in the platform motion direction and is parallel, the coordinate system direction of the calibration plate is consistent with the motion direction of the material adsorption platform, and at least one complete dot matrix set area with digital coordinate information is required to be contained in the visual field range of the camera at the photographing position.
Firstly, the material adsorption platform is located at a calibration reference position, specifically, see fig. 2 (the material adsorption platform indicated by the upper unit in the figure), wherein the field of view of the image acquisition device (i.e. the camera) can clearly obtain an image similar to that in fig. 1 by adjusting the image acquisition device (i.e. the camera).
S2: and (3) randomly selecting 9 points according to the image in the camera view, setting coordinate data and finishing the conversion relation between a mechanism (material adsorption platform) coordinate system and an image coordinate system.
Referring to fig. 1, the positions of 9 calibration points are set, and then coordinate data are set, wherein the calculation is mainly used for constructing the construction relation between camera pixels and physical distances
Pixel coordinates in the image [ x y1]And physical coordinates
[X Y 1]The relationship between
After being unfolded, obtain
Wherein a, b, c, d, e and f represent the rotation and translation relationship from the camera pixel coordinate to the physical coordinate, six equation sets are needed to calculate the calibration matrix T according to the equation set of one time, wherein 9 points can construct 18 equations, and the minimum variance is used
Find the corresponding 6 values, where AxiWhich represents a new value found from one of the sets of pixel coordinates in conjunction with the set of physical coordinates, and beta represents the value in the ideal case.
S3: and moving the material adsorption platform to transfer the calibration plate to the loading platform so that the camera corresponding to the loading platform acquires the image of the calibration plate.
Referring to fig. 3, the coordinate plate is translated to the loading platform, so that the cameras of the upper and lower units can uniformly describe the size and posture of an object. In the figure, the upper unit refers to a material adsorption platform, and the lower unit refers to a loading platform.
S4: and (3) randomly selecting 9 points according to the image in the camera view field, setting calibration coordinate data, and finishing the conversion relation between the mechanism (loading platform) coordinate system and the image coordinate system.
Referring to fig. 3, a conversion relation matrix of the physical distance between the camera pixel and the calibration board is set according to the image and the step 2.
S5: and setting five angles of movement of an image characteristic rotating platform in the visual field of the upper unit to calculate the rotating center of the material adsorption platform, and if a plurality of cameras exist, calculating once to obtain an average value to obtain the rotating center of the material adsorption platform.
As the platform action is executed, the material adsorption platform is required to execute, the position of the rotation center of the mechanism determines the translation calculation after the rotation, the characteristic point pixel coordinate [ x y 1] acquired by the material adsorption platform camera is recorded and converted into a coordinate corresponding to the locking representation of the calibration plate, 5 groups of points are selected to obtain the rotation center coordinate O (x, y) of the material adsorption mechanism by using a least square method, and then the original calculated offset matrix is translated to the original point with O as the center.
S6: and translating the calibration matrix of each camera according to the calculated rotation center.
S7: a position reference for each camera is set.
S8: and calculating new position reference in each camera to calculate the attitude information of the workpiece.
S9: and moving the upper unit after superposing the workpiece pose information obtained by the upper unit and the lower unit.
S10: and executing the docking action.
Referring to fig. 4, according to the information of the feature points of the upper and lower units acquired by the upper and lower unit cameras, the central offset (Δ x, Δ y) and the angular deviation Δ θ between the upper and lower workpieces and the standard attitude are respectively calculated, the translation amounts of the two platforms are applied to the upper unit, and the angles of the two workpieces are superimposed, so that the transfer of the two workpieces can be completed.
In summary, according to the visual calibration and alignment fitting method for fitting the special-shaped product provided by the invention, the calibration plate is transmitted, so that the motion relation coordinate of the upper unit is transmitted to the immovable lower unit, the fitting of the product can be completed without trial assembly or a small amount of trial assembly correction, for the products with different shapes, due to the established standard and stable coordinate system, excessive workpiece dimension information is not required to be transmitted, meanwhile, the accurate measurement task of the workpiece can be completed according to the collection of the installation position of the camera, and the offset fitting work of the special-shaped product can be quickly, efficiently and economically completed in practical use.
A visual calibration method, as shown in fig. 6, includes the following steps:
and S1, manufacturing a dot matrix calibration board with digital coordinate information according to the size of the visual field.
In order to accommodate a field of view that is capable of capturing all 9 circular hole points, the circular hole size design should be smaller than 1/4 for the field of view.
S2, a calibration board is placed in the field of view of each camera.
As with the calibration plate shown in FIG. 8, each number represents the sequential coordinates of the hole where the center is missing, Y being first and X being second.
And S3, controlling the camera in each view to take pictures, selecting a dot matrix area, binarizing the dot matrix area, extracting a corresponding round hole area through block mass algorithm processing, filling digital coordinates corresponding to the selected dot matrix area, and obtaining an affine transformation matrix from a camera pixel coordinate system to a calibration plate through a nine-point calibration algorithm.
As shown in fig. 8, an image collected in a camera is shown (after entering a camera calibration interface, a draggable Roi rectangular box is automatically generated on the interface), a Roi control box is dragged to place the Roi control box on a dot matrix region (generally, it is considered appropriate as long as the range includes nine circular holes and numerical coordinate information is not blocked), then by setting high and low thresholds of a gray value in a blob processing algorithm, a final positioning result can be seen by clicking a preprocessing button, and a selected circular dot is covered by a corresponding circular blob region, which indicates that a positioning threshold is correctly set (if the dot selected by the Roi box is not covered by the corresponding circular blob region, or the blob region exceeds the dot matrix image range, the threshold is considered to be unreasonable set and needs to be reset), and then only by clicking an execution button, the internal portion of the calibration algorithm generates a calibration matrix from the blob region obtained by the preprocessing operation according to the nine-point calibration algorithm, as shown in fig. 9, the 9 calibration points in the positioning frame are sequentially filled with numbers, and the calibration of the physical relationship between the camera pixel and the coordinate system where the calibration board is located is completed.
As shown in fig. 7, the calibration method uses a special dot matrix calibration board with spatial coordinate information, sets a group of positions including 9 calibration points on the calibration board, and then sets coordinate data, where the calculation mainly constructs the construction relationship between the camera pixels and the physical distance of the region to be calibrated; pixel coordinates in the image [ x y1]And physical coordinates [ X Y1]The relationship between
Wherein a, b, c, d, e, f represent the camera pixel coordinates to physicsThe rotation and translation relation of the coordinates is obtained after expansion
The calibration matrix T can be obtained by six equation sets according to the linear equation set, wherein 18 equations can be constructed by 9 points, and the minimum variance is used
Find the corresponding 6 values, where AxiRepresents a new value found by the above equation set in conjunction, and b represents a value in an ideal case.
As shown in fig. 10, when the cameras are installed in different areas, a plurality of camera coordinate systems need to be unified into one coordinate system, a simultaneous solution equation set is also needed according to the conventional method, the process is complicated, in the experiment, the cameras can be directly unified into the same coordinate system through position information carried on the calibration plate, the adjustment of the cameras and the setting of the calibration matrix are the same, the operation and use of a user are convenient, meanwhile, the CTP plate is cheap, the precision is high, the wear resistance is high, the calibration of a plurality of cameras with large size and different directions can be realized within a certain precision range, and the precision measurement of the object is completed.
Claims (7)
1. A visual calibration and alignment laminating method for laminating of special-shaped products is characterized by comprising the following steps: transporting the assembled object through an xy theta material adsorption platform, wherein the material adsorption platform can move up and down, left and right, the up and down fingers are along the theta direction, and the left and right fingers are along the x and y directions; fixing and assembling the object through the loading platform; the method comprises the steps of enabling a calibrated material adsorption platform to move through a control mechanism, obtaining a motion coordinate system of the operation of the control mechanism, reusing a dot matrix calibration plate containing X, Y coordinate information, transmitting the calibration plate to a loading platform incapable of moving through the material adsorption platform, collecting calibration information on the calibration plate through at least one camera installed on the loading platform, obtaining the position of each camera through calculation, calculating a calibration conversion matrix between the position of the camera and the loading platform, and obtaining a central reference position and a reference angle of an installed workpiece.
2. The vision calibration and alignment fitting method for fitting the special-shaped product according to claim 1, which is characterized in that: moving the material adsorption platform to the position area of the calibration plate to acquire the image of the calibration plate; the direction of a coordinate system of the calibration plate is consistent with the motion direction of the material adsorption platform, and at least one complete dot matrix set area with digital coordinate information is required to be contained in the visual field range of the camera at the photographing phase; the calibration plate is a dot matrix calibration plate with digital coordinate information;
the conversion relation between the coordinate system of the material adsorption platform and the coordinate system of the camera vision related to the loading platform which cannot move is completed by randomly selecting 9 coordinate points in the collected calibration plate picture and setting the coordinate data of the calibration plate.
3. The vision calibration and alignment fitting method for fitting the special-shaped product according to claim 1, which is characterized in that: controlling the material adsorption platform to transfer the calibration plate to the loading platform, and enabling a camera corresponding to the transfer platform to acquire an image of the calibration plate;
randomly selecting 9 coordinate points on an image in the camera view field, setting calibration coordinate data, and completing the correlation calculation matrix conversion relation of the loading platform and the corresponding material adsorption platform through a nine-point calibration algorithm (X)t,Yt) Representing coordinates in the output load platform, (X)i,Yi) Representing image coordinates in the field of view of the platform camera, (X)o,Yo) Representing the position of the origin of the output loading platform in the image coordinate system, wherein alpha is an included angle between the output coordinate system and the image coordinate system, and the conversion formula is as follows:
fixing a calibration plate on a material adsorption platform, rotationally moving the calibration plate in five different angles in the visual field of a corresponding camera, recording image characteristics, and finally calculating the rotation center of the material adsorption platform, if two or more cameras are arranged on the material adsorption platform, sequentially calculating and averaging the images in sequence to obtain the rotation center (x2, y2) of the material adsorption platform;
x＝(x1-x2)cosθ-(y1-y2)sinθ+x2
y＝(y1-y2)cosθ+(x1-x2)sinθ+y2
x2 and y2 are rotation centers, x1 and y1 are physical coordinates obtained by calibration calculation, theta is a rotation angle, and x and y are coordinates obtained by rotating a selected calibration point around the rotation centers (x2 and y2) by theta.
4. The vision calibration and alignment fitting method for fitting the special-shaped product according to claim 3, characterized in that: respectively translating the offset corresponding to the calculated rotation center (x, y) into a nine-point calibration matrix corresponding to each camera to obtain the final accurate physical mapping relation between the material adsorption platform and the image coordinate system:
wherein x and y are offset of the center of rotation, HaScaling the matrix for nine points, HbThe final mapping matrix is obtained;
moving the material adsorption platform right above the installation camera, recording a reference coordinate of the material adsorption platform at the moment, storing the obtained reference coordinate, and taking the reference coordinate as a position reference of the corresponding camera;
imaging through a camera arranged below the loading platform, obtaining the pixel coordinates of the characteristic points of the object by using an image processing algorithm, recording according to the pixel coordinates of the characteristic points of the workpiece at the debugging and installing position and the new loading position on the loading platform, and mapping through a mapping matrix HbObtaining the position offset and the angle offset of the new loading position and the debugging and installing position;
imaging through a camera below the material adsorption platform, obtaining pixel coordinates of characteristic points on the loaded object by using an image processing algorithm, and calculating the position offset and the angle offset of the loaded object between the debugging reference position of the loaded object on the material adsorption platform and the position offset of the loaded object; and moving the material adsorption platform to the loading position of the product on the loading platform, and executing assembly action.
5. A visual calibration method is characterized in that: firstly, manufacturing a calibration plate with point coordinates, wherein the point coordinates are coordinates of the point coordinates in a dot matrix, and the coordinate system of the calibration plate is a coordinate system where the dot matrix is located; placing the calibration plate in the visual field of each camera, so that the cameras shoot the calibration plate with a coordinate system lattice; and controlling each camera to take pictures, reading point coordinates on the calibration plate, converting pixel point coordinates into actual mechanical coordinates by nine-point calibration of the read points, and obtaining a radiation transformation matrix from each camera coordinate system to the calibration plate coordinate system.
6. The vision calibration method according to claim 5, wherein: randomly selecting 9 coordinate points on an image in the camera view field, setting calibration coordinate data, completing the correlation calculation matrix conversion relation from each camera coordinate system to a calibration plate coordinate system through a nine-point calibration algorithm, and enabling (X)t,Yt) Represents the coordinates in the output coordinate system, (X)i,Yi) Representing coordinates in the image coordinate system, (X)o,Yo) Representing the position of the origin of the output coordinate system in the image coordinate system, wherein alpha is the included angle between the output coordinate system and the image coordinate system, and the conversion formula is as follows:
7. the vision calibration method according to claim 5, wherein: the calibration plate is a calibration plate using a CTP substrate.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115979120A (en) * | 2022-09-28 | 2023-04-18 | 南京颖图电子技术有限公司 | Precision verification method for liquid crystal polarizer laminating system |
| CN116305484A (en) * | 2023-03-28 | 2023-06-23 | 山东方杰建工集团有限公司金乡二十分公司 | BIM-based assembly type building special-shaped piece module installation positioning method |
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- 2021-12-20 CN CN202111563418.XA patent/CN114494449A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115979120A (en) * | 2022-09-28 | 2023-04-18 | 南京颖图电子技术有限公司 | Precision verification method for liquid crystal polarizer laminating system |
| CN115979120B (en) * | 2022-09-28 | 2023-12-15 | 南京颖图电子技术有限公司 | Method for verifying precision of liquid crystal polarizer laminating system |
| CN116305484A (en) * | 2023-03-28 | 2023-06-23 | 山东方杰建工集团有限公司金乡二十分公司 | BIM-based assembly type building special-shaped piece module installation positioning method |
| CN116305484B (en) * | 2023-03-28 | 2023-10-10 | 山东方杰建工集团有限公司金乡二十分公司 | BIM-based assembly type building special-shaped piece module installation positioning method |
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