Position calibration method, device and system and readable storage medium

Abstract

The invention provides a position calibration method, device and system and a readable storage medium. The method comprises the following steps: acquiring first relative position information between a first reference object and an image acquisition unit, second relative position information between a second reference object and a target block, a target image and optical characteristic parameters of an internal acquisition device of the image acquisition unit; determining a conversion matrix between a first coordinate system corresponding to the image acquisition unit and a second coordinate system corresponding to the target block based on the target image and the optical characteristic parameters; and determining target relative position information between the first measurement module and the second measurement module based on the first relative position information, the second relative position information and the conversion matrix. Through the implementation of the scheme of the invention, the target block is taken as a geometric reference, and the spatial correlation between the two measurement modules is established through the target image, so that the target relative position information between the two measurement modules is determined, and the accurate calibration of the relative position relationship between the measurement modules can be completed on site.

Description

Technical Field

[0001] This application relates to the field of automotive technology, and in particular to a position calibration method, apparatus, system, and readable storage medium. Background Technology

[0002] Four-wheel alignment parameters are key indicators that determine the relative position of the wheels and the axle. Their rationality directly affects the overall performance of the vehicle. Four-wheel alignment parameters include wheel camber angle, wheel toe-in, wheel caster angle, and wheel kingpin inclination angle. The rational selection of four-wheel alignment parameters is of great significance for improving driving comfort, reducing fuel consumption, increasing tire life and improving driving safety.

[0003] In related technologies, the four-wheel alignment parameters of a car can be obtained through two measuring modules. The two measuring modules are rigidly connected by a crossbeam, and their relative positional relationship is usually fixed before leaving the factory. However, the relative positional relationship of the two measuring modules is needed in the calculation of the four-wheel alignment parameters. If a single measuring module fails (such as camera damage or target misalignment), the original fixed positional relationship between the two measuring modules is broken after replacing the new measuring module. The process of returning to the manufacturer for overall recalibration is cumbersome and increases the time for vehicle inspection and repair. Summary of the Invention

[0004] This application provides a position calibration method, apparatus, system, and readable storage medium, aiming to solve the problem that the relative positional relationship between measurement modules is difficult to calibrate on-site in related technologies.

[0005] A first aspect of this application provides a position calibration method applied to a vehicle four-wheel alignment system. The vehicle four-wheel alignment system is configured with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object. The second measurement module includes a target block and a second reference object. The image acquisition unit's capture direction is towards the target block to acquire a target image of the target block. The position calibration method includes: Acquire the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit; Based on the target image and the optical characteristic parameters, determine the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block; Based on the first relative position information, the second relative position information, and the transformation matrix, the target relative position information between the first measurement module and the second measurement module is determined.

[0006] A second aspect of this application provides a position calibration device applied to a vehicle four-wheel alignment system. The vehicle four-wheel alignment system is configured with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object. The second measurement module includes a target block and a second reference object. The image acquisition unit's capture direction is towards the target block to acquire a target image of the target block. The position calibration device includes: The acquisition module is used to acquire the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit; The first determining module is used to determine the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block based on the target image and the optical characteristic parameters. The second determining module is used to determine the target relative position information between the first measuring module and the second measuring module based on the first relative position information, the second relative position information, and the transformation matrix.

[0007] A third aspect of this application provides a vehicle four-wheel alignment system, comprising: a first measurement module, a second measurement module, a memory, and a processor. The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit is directed towards the target block to acquire a target image of the target block. The processor executes a computer program stored in the memory, and when executing the computer program, it implements the steps of the position calibration method provided in the first aspect of this application.

[0008] The fourth aspect of this application provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the position calibration method provided in the first aspect of this application.

[0009] As can be seen from the above, according to the position calibration method, device, system, and readable storage medium provided in this application, the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit are obtained; based on the target image and the optical characteristic parameters, the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block is determined; based on the first relative position information, the second relative position information, and the transformation matrix, the target relative position information between the first measurement module and the second measurement module is determined. Through the implementation of this application, using the target block as a geometric reference, the spatial association between the first measurement module and the second measurement module is established through the target image, strengthening the association characteristics between the first measurement module and the second measurement module, thereby determining the transformation relationship between the two, that is, determining the transformation matrix, and then the target relative position information between the first measurement module and the second measurement module can be determined based on the transformation matrix, thus achieving accurate calibration of the relative position relationship between the measurement modules on site. The target relative position information between the first and second measurement modules is determined by the transformation matrix. Compared with the existing technology of returning the measurement modules to the manufacturer for repair, this reduces the repair time of the measurement modules and improves the repair efficiency of the measurement modules. Attached Figure Description

[0010] Figure 1 This is a basic flowchart illustrating a position calibration method provided in the first embodiment of this application; Figure 2 This is a schematic diagram of the overall structure of a first measurement module provided in the first embodiment of this application; Figure 3 This is a schematic diagram of the overall structure of a second measurement module provided in the first embodiment of this application; Figure 4 This is a schematic diagram of the target image before the addition of the rotating rectangle in some embodiments of the first embodiment of this application; Figure 5 A schematic diagram of a target image after adding a rotated rectangle in some embodiments of the first embodiment of this application; Figure 6 This is a schematic diagram of a target image after adding a rotated rectangle and reference lines in some embodiments of the first embodiment of this application; Figure 7 This is a schematic diagram of a target image marked with graphic labels in some embodiments of the first embodiment of this application; Figure 8 This is a schematic diagram illustrating the region detection of the target image with the second row as a reference row in some other embodiments of the first embodiment of this application; Figure 9This is a schematic diagram illustrating the region detection of the target image using the first or third row as a reference row in some other embodiments of the first embodiment of this application; Figure 10 A detailed flowchart illustrating a position calibration method provided in the second embodiment of this application; Figure 11 This is a schematic diagram of the program modules of the position calibration device provided in the third embodiment of this application; Figure 12 This is a schematic diagram of the structure of the vehicle four-wheel alignment system provided in the fourth embodiment of this application. Detailed Implementation

[0011] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0012] In the description of the embodiments of this application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. They are only for the convenience of describing the embodiments of this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the present invention.

[0013] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0014] In the embodiments of this application, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0015] To address the difficulty in calibrating the relative positions of measurement modules on-site in related technologies, the first embodiment of this application provides a position calibration method applied to a vehicle four-wheel alignment system. The vehicle four-wheel alignment system is configured with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit's capture direction is towards the target block to acquire a target image of the target block; for example... Figure 1 This is a basic flowchart illustrating the location calibration method provided in this embodiment. The location calibration method includes the following steps: Step 101: Obtain the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit.

[0016] Specifically, in this embodiment, the first reference object can be any component on the first measurement module that has a certain relative distance from the image acquisition unit. Similarly, the second reference object can be any component on the second measurement module that has a certain relative distance from the target block; no limitation is imposed here. In some embodiments, the first measurement module can be a three-camera measurement module, that is, the first measurement module is equipped with three cameras, which can be set facing different directions respectively. For example, such as... Figure 2 As shown, one camera in the first measurement module can serve as an image acquisition unit 1 for acquiring target images, and is positioned below one side of the module; the other two cameras in the first measurement module can serve as first reference objects 2, positioned on a side other than the side where the image acquisition unit is located, and the two cameras (i.e., the first reference objects 2) can be located in the middle and above of that side. The second measurement module can be a dual-camera measurement module, that is, the second measurement module has two cameras, for example, as shown in the figure. Figure 3 As shown, the two cameras can be set on the same side of the second measurement module as the second reference object 4, and the camera (i.e. the second reference object 4) and the target block 3 of the second measurement module can be set on different sides respectively.

[0017] It is understood that in the vehicle four-wheel alignment system of this embodiment, each camera can be used to acquire wheel images at different positions of the vehicle and target images on the measurement module, so as to calculate the corresponding four-wheel alignment parameters based on the acquired images; and the first measurement module and the second measurement module can form a mutual viewing system, and realize the on-site calibration of the relative positional relationship between the first measurement module and the second measurement module through the acquisition and calculation processing of the target images.

[0018] Step 102: Based on the target image and optical characteristic parameters, determine the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block.

[0019] Specifically, optical characteristic parameters can refer to camera intrinsic parameters, such as the camera's pixel focal length and distortion coefficient. Based on the target image and optical characteristic parameters, the transformation relationship between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block can be determined, that is, the relative pose between the image acquisition unit and the target can be determined, and represented by a transformation matrix.

[0020] In some embodiments of this example, the step of determining the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block based on the target image and optical characteristic parameters includes: extracting the contour parameters of all marker graphics in the target image; wherein, the marker graphics are the graphics of the markers of the target block presented in the target image; determining the first center coordinates of each marker graphic in the first coordinate system corresponding to the image acquisition unit according to the contour parameters; obtaining the second center coordinates of the markers of the target block in the second coordinate system corresponding to the target block; and inputting each first center coordinate, each second center coordinate, and the optical characteristic parameters into a preset perspective projection model to obtain the transformation matrix between the first coordinate system and the second coordinate system.

[0021] Specifically, the first coordinate system can refer to the camera coordinate system corresponding to the image acquisition unit (camera) used to acquire the target image, and the second coordinate system can refer to the world coordinate system. Correspondingly, the first center coordinate can refer to the two-dimensional pixel coordinates in the corresponding camera coordinate system, and the second center coordinate can refer to the three-dimensional coordinates in the world coordinate system. It should be understood that the second center coordinates corresponding to each mark on the target block are determined before leaving the factory and can be directly retrieved from the corresponding database. Before leaving the factory, a 3D camera can be used to measure the second center coordinates corresponding to each mark and store them in the database. The first center coordinates corresponding to each mark graphic can refer to the pixel coordinates of all mark graphics on the target image in the two-dimensional image captured by the camera. Optical characteristic parameters can include the pixel focal lengths fx and fy of the camera in the x and y directions, as well as the principal point coordinates u0 and v0, and radial distortion coefficients k1, k2, and k3, tangential distortion coefficients p1 and p2, etc., without limitation. The perspective projection model can be a Solve Perspective-n-Point (solvePnP) algorithm model for camera pose calculation. By inputting the coordinates of each first center, each second center, and optical characteristic parameters into the preset solvePnP algorithm model, the transformation matrix between the first coordinate system and the second coordinate system can be calculated by the solvePnP algorithm. The transformation matrix can include a rotation matrix and a translation matrix. The rotation matrix can be used to represent the rotational attitude of the second coordinate system relative to the first coordinate system, and the translation matrix can be used to represent the position of the origin of the second coordinate system in the first coordinate system.

[0022] Specifically, in the embodiments of this application, a specific method for determining the first center coordinates based on contour parameters may be to perform edge detection and ellipse detection (detectEllipses method) using the EdgeDrawing (ED) algorithm and the improved (SCHARR) operator.

[0023] Furthermore, in some embodiments of this example, the target block is provided with multiple concentric circle markers spaced apart, and the marker pattern is a graphic of the concentric circle markers presented in the target image; the contour parameters include a first contour parameter of the outer contour of each marker pattern and a second contour parameter of the inner contour; correspondingly, the step of determining the first center coordinates of each marker pattern in the first coordinate system corresponding to the image acquisition unit based on the contour parameters includes: determining a first initial parameter matrix of each outer contour based on the first contour parameter; determining a second initial parameter matrix of each inner contour based on the second contour parameter; constructing a characteristic equation of each marker pattern based on each first initial parameter matrix and each second initial parameter matrix; wherein, each characteristic equation is used to characterize the geometric transformation relationship between the outer contour and inner contour of the corresponding marker pattern; and calculating the first center coordinates corresponding to each marker pattern based on each characteristic equation.

[0024] In this embodiment, the first center coordinates corresponding to each marker graphic are the center coordinates of the concentric circle markers in the pixel coordinate system. It can be understood that the second center coordinates corresponding to each marker graphic are the three-dimensional coordinates of the center of the concentric circle markers in the world coordinate system.

[0025] In other embodiments, when the marker graphic is a rectangle or other regular polygon, the first center coordinates corresponding to each marker graphic are the center coordinates of the rotation center of the marker graphic in the pixel coordinate system. It can be understood that the second center coordinates corresponding to each marker graphic are the three-dimensional coordinates of the rotation center of the marker graphic in the world coordinate system.

[0026] Specifically, due to potential deviations in the shooting angle, the marker graphics corresponding to the concentric circle markers may be either concentric circles or concentric ellipses. Regardless of whether the marker graphics are concentric circles or concentric ellipses, the contour parameters include the first contour parameters of the outer contour and the second contour parameters of the inner contour of each marker graphic. The target image can be optimized using the method of this embodiment. In this embodiment, the parameter matrix can be a quadratic curve matrix characterizing the geometric features of the marker graphics (circle or ellipse). Its elements correspond to the parameters in the general equation of the marker graphics, reflecting information such as the shape and rotation angle of the marker graphics. The process of constructing the characteristic equation can be as follows: perform an inverse transformation on the second initial parameter matrix to obtain the inverse matrix of the second initial parameter matrix; multiply this inverse matrix by the first initial parameter matrix to obtain the characteristic equation. In this embodiment, the contour parameters are divided into two groups: the first contour parameters of the outer contour and the second contour parameters of the inner contour. The parameter matrix characterizes the geometric features of the outer and inner contours, and the relative transformation relationship between the inner and outer contours is determined by constructing the characteristic equation. This eliminates the common interference between the two, allowing for more accurate calculation of the required first center coordinates.

[0027] Furthermore, in some embodiments of this example, the step of calculating the first center coordinates of each marker graphic based on each characteristic equation includes: performing feature decomposition on each characteristic equation to obtain the feature values ​​of each characteristic equation; determining the first target parameter matrix of each outer contour and the second target parameter matrix of each inner contour based on each feature value; and calculating the first center coordinates of each marker graphic based on the first target parameter matrix and the corresponding second target parameter matrix of each marker graphic.

[0028] Specifically, eigenvalues ​​can be used to reflect the scaling characteristics of contour curves. By applying eigenvalues, sub-pixel-level center coordinate positioning can be achieved, while filtering out misidentifications of non-target areas and non-marked graphic coordinates.

[0029] Furthermore, in some embodiments of this example, one feature equation corresponds to multiple feature values; correspondingly, the steps of determining the first target parameter matrix of each outer contour and the second target parameter matrix of each inner contour based on each feature value include: calculating a first difference between multiple feature values ​​of a single feature equation; if the first difference is less than or equal to a first preset threshold, then determining the marked graphic corresponding to the first difference as the graphic to be processed; performing scaling radius compensation on the outer contour and inner contour of the graphic to be processed based on a preset scaling ratio to obtain the target contour parameters of the compensated graphic to be processed; calculating multiple target feature values ​​of the compensated graphic to be processed according to the target contour parameters, and calculating the feature distance between the multiple target feature values; calculating the first target parameter matrix of the outer contour of the compensated graphic to be processed and the second target parameter matrix of the corresponding inner contour according to the feature distance.

[0030] Specifically, for example, the first preset threshold can be 0.2. When the first preset threshold is greater than the preset threshold (0.2), the corresponding inner and outer contours are determined to be non-concentric circles or misidentifications belonging to non-target areas, and can be excluded. If the difference is less than or equal to the first preset threshold, the corresponding inner and outer contours are retained as candidate groups. Further, for the retained candidate groups, scaling radius compensation can be performed according to the theoretical radius ratio of the original marker graphics corresponding to the inner and outer contours (i.e., the preset scaling ratio) to eliminate the feature value ratio interference caused by the difference in inner and outer contour radii. Based on the compensated feature values, the feature distance between feature values ​​is calculated. This feature distance can be used to quantify the consistency of the inner and outer contours in geometric characteristics. Finally, the candidate group corresponding to the smallest feature distance can be selected from the feature distances calculated above. Based on the outer contour parameter matrix (i.e., the first target parameter matrix) and inner contour parameter matrix (i.e., the second target parameter matrix) of the selected candidate groups, the sub-pixel level first center coordinates are calculated through matrix parameter transformation.

[0031] In another embodiment of this invention, edge detection and fitting algorithms can be combined to optimize the target image, thereby accurately obtaining the first center coordinates corresponding to each marker graphic. For example, taking the extraction of elliptical contour parameters and center fitting as an example: the target image can be preprocessed first; the preprocessing includes performing Gaussian blur on the original target image to smooth high-frequency noise, and performing contrast enhancement operation when the target image contrast is low to increase the grayscale difference between the elliptical contour and the background; then, gradient calculation can be performed on the preprocessed image to filter out pixels with edge strength exceeding a preset intensity threshold as potential edge pixels; edge segment connection is performed on the aforementioned potential edge pixels; based on the geometric features of the ellipse, elliptical candidate edge segments are filtered from the edge segments obtained in the above edge segment connection operation steps; elliptical parameter fitting is performed on the filtered elliptical candidate edge segments, thereby determining the center coordinates of the inner contour and the center coordinates of the outer contour; then, the average value of the center coordinates of the inner contour and the center coordinates of the outer contour can be used as the first center coordinates of the marker graphic.

[0032] In some embodiments of this example, the target block is provided with multiple concentric circle markers distributed at intervals, and the marker pattern is the pattern of the concentric circle markers presented in the target image; the above-mentioned position calibration method further includes: calculating a second difference between the number of concentric circle markers on the target block and the number of marker patterns in the target image; if the second difference satisfies the condition for supplementing the target image with markers, then the center coordinates of the pattern to be supplemented in the target image are determined based on the pattern distribution rules of the target block and the first center coordinates.

[0033] Specifically, when determining whether the second difference meets the conditions for supplementing the target image with markers, the following method can be used: determine whether the second difference is greater than zero and less than a preset threshold; if the second difference is equal to zero, it means that the target image has no missing markers; if the second difference is greater than zero and less than the preset threshold, it means that the target image has no more than two missing markers, meeting the conditions for supplementing the target image with markers; if the second difference is greater than the preset threshold, it means that the target image has many missing markers, and the target image needs to be re-acquired. The definition of rotating rectangles and reference lines facilitates faster and more accurate detection of the positions of missing markers.

[0034] Furthermore, in some embodiments of this example, the step of determining the center coordinates of the graphic to be supplemented in the target image based on the graphic distribution rules of the target block and the first center coordinates if the second difference satisfies the condition for supplementing the target image with markers includes: if the second difference satisfies the condition for supplementing the target image with markers, determining the sorting direction of the marker graphics in the target image based on the graphic distribution rules of the target block; calculating the distance parameter between the first center coordinates of two adjacent marker graphics along the sorting direction; if the distance parameter is greater than a second preset threshold, determining that there is a missing marker graphic between the two marker graphics corresponding to the distance parameter; and determining the center coordinates of the graphic to be supplemented in the target image based on the first center coordinates of the two marker graphics corresponding to the distance parameter.

[0035] Specifically, taking concentric circle markers as an example, the first center coordinates of each marker are the center coordinates of the concentric circle marker. When a single or multiple consecutive markers are missing, and there are normally displayed markers before and after the missing marker along the sorting direction (i.e., there is a missing marker between two adjacent normally displayed markers along the sorting direction), the center coordinates of the marker to be supplemented can be calculated using the above method. The pattern distribution rules can refer to: multiple concentric circles evenly distributed and arranged in rows with intervals, multiple concentric circles evenly distributed and arranged in columns with intervals, multiple concentric circles evenly distributed and arranged in circles with intervals, etc., without any restrictions here. Furthermore, in some specific implementations, for cases where the preset quantity threshold is set to two: if the calculated distance parameter is greater than the second preset threshold and less than or equal to the third preset threshold, it is determined that one marker is missing between the two markers corresponding to the distance parameter (i.e., there is one marker to be supplemented between the two markers corresponding to the distance parameter); then, the center coordinates of the marker to be supplemented can be calculated based on the first center coordinates of the two markers before and after the marker to be supplemented; if the calculated distance parameter is greater than the third preset threshold, it is determined that two markers are consecutively missing between the two markers corresponding to the distance parameter (i.e., there are two markers to be supplemented between the two markers corresponding to the distance parameter); then, the center coordinates of the two markers to be supplemented can be calculated based on the first center coordinates of the two markers corresponding to the distance parameter.

[0036] For example, in some embodiments of this example, taking concentric circle markers as an example, the first center coordinates corresponding to each marker are the center coordinates of the concentric circle markers. The process of interpolating and supplementing the center coordinates of missing markers can be performed as follows: First, identify all markers in the target image and obtain the center coordinates of the markers, such as... Figure 4 As shown; 2. Identify the center positions of the four outermost marked shapes and construct a rotated rectangle, as shown. Figure 5As shown; 3. Determine the sorting direction of the marker graphics in the target image based on the direction of the long side of the rotating rectangle, and the reference line P, as shown. Figure 6 As shown; after obtaining the center sorting direction, sort these 11 marker graphics according to the sorting direction. The sorting rule is as follows: calculate the position of each point relative to the line p; sort the positions from bottom to top and from left to right. The four marker graphics below the line are numbered 0, 1, 2, and 3 from left to right; the marker graphics on the reference line are numbered 4, 5, and 6 from left to right; and the marker graphics above the line are numbered 7, 8, 9, and 10 from left to right. The sorted target marker graphics are numbered as follows: Figure 7 As shown. Fourth, after determining that no more than two marker graphics are missing in the target image, calculate the distance parameter between the first center coordinates of adjacent marker graphics along the sorting direction. If any of the calculated distance parameters has a target distance parameter greater than the second preset threshold, it indicates that a marker graphic is missing between the two adjacent marker graphics corresponding to this target distance parameter. Thus, the pixel coordinates of the missing marker graphics can be predicted by the sorting direction of the center, and the center coordinates of the missing marker graphics can be interpolated and supplemented according to the geometric positional relationship of the pixel coordinates.

[0037] This implementation is understandable as it applies to cases where there are no missing graphic markers on the outer edge, meaning it's suitable for successfully constructing a rotating rectangle. In some specific implementations, the ordinate of the center coordinates of the marked graphics can be used for filtering, eliminating marked graphics in the middle rows (i.e., the x-coordinates of the marked graphics in rows with missing markers should correspond one-to-one with the x-coordinates of the marked graphics in the remaining rows). This allows the rotating rectangle to be determined based on the center positions of the 6-8 marked circles on the outer edge (to handle cases where 2, 1, or 0 marked graphics are missing). Then, the specific 8 circles can be determined based on the x and ordinates of the remaining at least 6 circles. For example, if the top row has 2 marked graphics and the next row has 4, the x-coordinates of the circles to be added can be determined by the two circles in the next row with different x-coordinates, and then the center coordinates can be derived.

[0038] In other embodiments of this example, multiple concentric circle markers are arranged in multiple rows and symmetrically distributed in the target block; correspondingly, the step of determining the center coordinates of the graphic to be supplemented in the target image based on the graphic distribution rules of the target block and the first center coordinates if the second difference satisfies the condition for supplementing the target image with markers includes: if the second difference satisfies the condition for supplementing the target image with markers, determining the row number corresponding to each marker graphic in the target image based on each first center coordinate, and counting the number of graphic markers corresponding to each row number; determining the row number to which the graphic to be supplemented belongs based on the number of graphic markers corresponding to each row number, and determining the ordinate of the center of the graphic to be supplemented in the target image; determining the abscissa of the center of the graphic to be supplemented based on the graphic distribution rules; and determining the center coordinates of the graphic to be supplemented based on the ordinate and abscissa.

[0039] Specifically, taking concentric circle markers as an example, the first center coordinates of each marker are the center coordinates of the concentric circle marker. In practical applications, markers corresponding to concentric circles in the same row usually have the same ordinate in the pixel coordinate system (i.e., the first coordinate system mentioned above). Therefore, the ordinate of the to-be-added graphic can be determined based on the ordinates of other markers in the row where the graphic to be added is located. After determining the abscissa of the to-be-added graphic, the abscissa in the center coordinates of the to-be-added graphic can be further determined based on the symmetrical distribution rule. Using the above method to determine the center coordinates of the to-be-added graphic is beneficial to reducing the computational complexity of the coordinate parameter determination process. It is understandable that for some special cases, such as when the target image is taken at an angle of inclination, the row number of each marker can also be determined by the mapping relationship between the ordinates of each marker and the preset ordinate threshold range. Alternatively, the center coordinates of the to-be-added graphic in that row can be determined by linear fitting of the first center coordinates of the markers in the same row, without any restrictions.

[0040] Furthermore, in some specific implementations, the concentric circles of adjacent rows are staggered in the target block; correspondingly, the step of determining the abscissa of the center of the graphic to be supplemented based on the graphic distribution rules includes: determining reference rows in the target graphic that do not lack marker graphics based on the graphic distribution rules; performing region detection on the target image based on the first center coordinates of each marker graphic in the reference rows to determine the target region where the graphic to be supplemented is located in the target image; determining reference marker graphics corresponding to the target region based on the graphic distribution rules; and determining the abscissa of the center of the graphic to be supplemented based on the abscissa of the first center coordinates of the reference marker graphics.

[0041] Specifically, taking concentric circle markers as an example, the first center coordinates of each marker are the center coordinates of the concentric circle marker. The markers in the target image are arranged in 3 rows (theoretically, the first and third rows each have 4 markers, the second row has 3 markers, and the markers in the first and third rows are symmetrically distributed about the second row). When a missing marker is found, the number of markers corresponding to each row number can be counted to determine which row or rows are missing. After determining the row where the missing marker is located, the center coordinates of the missing marker are determined based on the preset marker distribution rules and with the first center coordinates of the normally displayed marker as a reference.

[0042] like Figure 8 As shown, if the row number of the graphic to be supplemented is found to be one or three, the second row can be determined as the reference row. The target image can be divided into four regions using the horizontal coordinates of each marked graphic in the second row as the region boundary, and region detection can be performed. When the number of marked graphics in a certain region is less than 2, the region is determined as the target region.

[0043] For example, if the location of the graphic to be supplemented is the location corresponding to label 1, that is, the area where the graphic of label 1 is located is the target area, based on the graphic distribution rules, it can be known that label graphic 8 can be determined as the reference label graphic, or label graphic 2 and label graphic 3 can be determined as reference label graphics simultaneously. Further, if label graphic 8 is determined as the reference label graphic, the abscissa of the center of label graphic 8 is the same as the abscissa of the center of the graphic to be supplemented; that is, the abscissa of the center of label graphic 8 can be directly determined as the abscissa of the center of the graphic to be supplemented. If label graphic 2 and label graphic 3 are determined as reference label graphics simultaneously, the difference between the abscissa of the center of label graphic 2 and the abscissa of the center of the graphic to be supplemented is equal to the difference between the abscissa of the center of label graphic 3 and the abscissa of the center of label graphic 2. Therefore, based on the above positional relationship, the abscissa of the center of the graphic to be supplemented can be calculated. It is understood that in some other implementations, other marker graphics in the target graphic can be identified as reference marker graphics based on the graphic distribution rules, and the abscissa of the center of the graphic to be supplemented can be further calculated based on the first center coordinate of the reference marker graphics and the graphic distribution rules, without any limitation.

[0044] For example, if the location of the graphic to be supplemented is the location corresponding to label 2, that is, the area where the graphic of label 2 is located is the target area, based on the graphic distribution rules, it can be known that label graphic 9 can be determined as the reference label graphic, or label graphic 1 and label graphic 3 can be determined as reference label graphics simultaneously. Further, if label graphic 9 is determined as the reference label graphic, the abscissa of the center of label graphic 9 is the same as the abscissa of the center of the graphic to be supplemented, that is, the abscissa of the center of label graphic 9 can be directly determined as the abscissa of the center of the graphic to be supplemented. If label graphic 1 and label graphic 3 are determined as reference label graphics simultaneously, then based on the graphic distribution rules, the abscissa of the center of the graphic to be supplemented is equal to the difference between the abscissa of the center of label graphic 3 and the abscissa of the center of label graphic 1 divided by two. It is understood that in some other embodiments, other label graphics in the target graphic can also be determined as reference label graphics based on the graphic distribution rules, and the abscissa of the center of the graphic to be supplemented can be further calculated based on the first center coordinate of the reference label graphics and the graphic distribution rules, without limitation here.

[0045] like Figure 9 As shown, if the row number of the graphic to be supplemented is found to be second, the first or third row with no missing marker graphics can be determined as the reference row. Using the x-coordinates of each marker graphic in the reference row as the region boundaries, the target image is divided into three regions for region detection. When a region is found to be devoid of marker graphics, that region is determined as the target region. Therefore, based on the graphic distribution rules, the other two normally displayed marker graphics in the second row can be used as reference marker graphics. Specifically, for example, if the position of the graphic to be supplemented is the position corresponding to label 5, that is, the region where the graphic of label 5 is located is the target region, then marker graphics 6 and 7 are simultaneously determined as reference marker graphics. The difference between the x-coordinate of the center of marker graphics 6 and the x-coordinate of the center of the graphic to be supplemented is equal to the difference between the x-coordinate of the center of marker graphics 7 and the x-coordinate of the center of marker graphics 6. Therefore, based on the above positional relationship, the x-coordinate of the center of the graphic to be supplemented can be calculated. If the location of the graphic to be supplemented is the location corresponding to label 6, that is, the area where the graphic of label 6 is located is the target area, then label graphic 5 and label graphic 7 can be determined as reference label graphics at the same time. Based on the graphic distribution rules, it can be known that the x-coordinate of the center of the graphic to be supplemented is equal to the difference between the x-coordinate of the center of label graphic 7 and the x-coordinate of the center of label graphic 5, divided by two.

[0046] Understandably, for a target image missing two marker graphics, the calculation can also be performed based on the graphic distribution rules. That is, first find the row number to which the graphic to be supplemented belongs (at this time, at least one row has a complete marker graphic), and determine the ordinate of the center of the graphic to be supplemented. Further, the rows that do not have missing marker graphics can be used as reference rows to perform regional detection, determine the target area where each graphic to be supplemented is located, and then determine the reference marker graphics based on the graphic distribution rules. Then, based on the first center coordinate of the reference marker graphics, calculate the abscissa of the center of each graphic to be supplemented.

[0047] For example, if the row numbers of the graphics to be supplemented are found to be one and three, the second row can be determined as the reference row. The target image can be divided into four regions using the x-coordinates of the marker graphics in the second row as the region boundaries, and region detection can be performed. When the number of marker graphics in a certain region is less than 2, that region is determined as the target region. Taking the position of the graphics to be supplemented as the position corresponding to the numbers 1 and 9 as an example, the region where the graphics of numbers 1 and 9 are located is the target region. Based on the graphic distribution rules, the marker graphics 2 and 8 can be determined as reference marker graphics. The x-coordinate of the center of the circle of marker graphic 8 can be directly determined as the x-coordinate of the center of the circle of the graphics to be supplemented at position 1, and the y-coordinate of the center of the circle of marker graphic 8 can be determined as the y-coordinate of the center of the circle of the graphics to be supplemented at position 9. Similarly, the x-coordinate of the center of the circle of marker graphic 2 can be directly determined as the x-coordinate of the center of the circle of the graphics to be supplemented at position 9, and the y-coordinate of the center of the circle of marker graphic 2 can be determined as the y-coordinate of the center of the circle of the graphics to be supplemented at position 1.

[0048] For example, if the row number of the graphic to be supplemented is found to be one or two, then the third row can be determined as the reference row. First, the target image can be divided into three regions using the horizontal coordinates of each marker graphic in the third row as the region boundary, and region detection can be performed. When a marker graphic that is not present in a certain region is detected, that region is determined as the target region. Taking the position of the graphic to be supplemented as the position corresponding to the numbers 1 and 6 as an example, the region where the graphic with number 6 is located is the target region. Based on the graphic distribution rules, it can be known that marker graphics 5 and 7 can be determined as reference marker graphics. Furthermore, based on the graphic distribution rules, it can be known that the horizontal coordinate of the center of the graphic to be supplemented is equal to the difference between the horizontal coordinate of the center of marker graphics 7 and the horizontal coordinate of the center of marker graphics 5, divided by two. Then, using the x-coordinates of the markers in the second row as region boundaries, the target image can be divided into four regions. Region detection is then performed. When the number of markers in a region is less than 2, that region is determined as the target region. Taking the position of the marker to be supplemented as the position corresponding to marker number 2 as an example, based on the pattern distribution rules, marker 9 can be determined as the reference marker. The x-coordinate of the center of marker 9 should be the same as the x-coordinate of the center of the marker to be supplemented. That is, the x-coordinate of the center of marker 9 can be directly determined as the x-coordinate of the center of the marker to be supplemented. It should be understood that the remaining supplementation rules can refer to the cases above where the row number of the marker to be supplemented is one or three, and will not be elaborated here.

[0049] Step 103: Based on the first relative position information, the second relative position information, and the transformation matrix, determine the target relative position information between the first measurement module and the second measurement module.

[0050] Specifically, the first and second relative position information are predetermined before leaving the factory and can be directly retrieved from the corresponding databases. The first and second relative position information also include rotation and translation matrices, respectively. Using the first and second relative position information and the transformation matrices, the reference coordinate systems between the first and second measurement modules can be linked, ultimately determining their relative pose relationship.

[0051] Furthermore, in some embodiments of this example, the step of determining the target relative position information between the first measurement module and the second measurement module based on the first relative position information, the second relative position information, and the transformation matrix includes: constructing a coordinate system transformation chain between the first measurement module and the second measurement module based on the first relative position information, the second relative position information, and the transformation matrix; and performing coordinate transformation calculations based on the coordinate system transformation chain to obtain the target relative position information between the first measurement module and the second measurement module.

[0052] Specifically, for example, the above transformation matrix can be denoted as RT1 (where R is the rotation matrix and T is the translation matrix), the second relative position information can be denoted as RT2, and the first relative position information can be denoted as RT3. Each RT in RT1, RT2, and RT3 has the following coordinate system relationship: 1. The source coordinate system of RT1 is the first coordinate system of the image acquisition unit (denoted as C3), and the target coordinate system of RT1 is the second coordinate system of the target block (denoted as T2). Points on C3 can be transformed to the target T2 through RT1; 2. The source coordinate system of RT2 is the coordinate system of the second reference object (denoted as C2), and the target coordinate system of RT2 is the second coordinate system of the target block (denoted as T2). Points on C2 can be transformed to T2 through RT2; 3. The source coordinate system of RT3 is the coordinate system of the first reference object (denoted as C1), and the target coordinate system of RT3 is the first coordinate system of the image acquisition unit (denoted as C3). Points in C1 can be transformed to C3 through RT3. Based on the above coordinate system relationship, a coordinate system transformation chain can be constructed between the first measurement module and the second measurement module. For example, the coordinate system transformation chain can be: C1 is transformed into C3 through RT3, C3 is transformed into T2 through RT1, and T2 is transformed into C3 through RT2. -1 Convert to C2. From this, the conversion relationship RT from C1 to C2 can be calculated, which gives us the target's relative position information.

[0053] Based on the technical solution of the above embodiments of this application, the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit are obtained; based on the target image and the optical characteristic parameters, the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block is determined; based on the first relative position information, the second relative position information, and the transformation matrix, the target relative position information between the first measurement module and the second measurement module is determined. Through the implementation of the solution of this application, using the target block as a geometric reference, the spatial relationship between the first measurement module and the second measurement module is established through the target image, thereby determining the transformation relationship between the two, that is, determining the transformation matrix, and then the target relative position information between the first measurement module and the second measurement module can be determined based on the transformation matrix, realizing the accurate calibration of the relative position relationship between the measurement modules on site.

[0054] Figure 10 The method described in the second embodiment of this application is a refined position calibration method applied to a vehicle four-wheel alignment system. The vehicle four-wheel alignment system is configured with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit's capture direction is towards the target block to acquire a target image of the target block. This position calibration method includes: Step 1001: Extract the contour parameters of the marker graphic from the target image obtained by the image acquisition unit.

[0055] Specifically, the target block has multiple concentric circle markers spaced apart; the aforementioned contour parameters include the contour parameters of all marker graphics corresponding to the concentric circle markers.

[0056] Step 1002: Determine the first initial parameter matrix of each outer contour and the second initial parameter matrix of each inner contour based on the contour parameters.

[0057] Step 1003: Based on each first initial parameter matrix and each second initial parameter matrix, construct the characteristic equations for each marked graphic.

[0058] Specifically, each characteristic equation is used to characterize the geometric transformation relationship between the outer and inner contours of the corresponding marked graphic.

[0059] Step 1004: Based on each characteristic equation, calculate the first center coordinates corresponding to each marked graphic.

[0060] Step 1005: Input the first center coordinates, the optical characteristic parameters corresponding to the image super unit, and the second center coordinates of each concentric circle mark in the second coordinate system corresponding to the target block into the preset perspective projection model to obtain the transformation matrix between the first coordinate system and the second coordinate system.

[0061] Specifically, the optical properties of the eucalyptus tree and the coordinates of the second center can be obtained from the database.

[0062] Step 1006: Based on the transformation matrix, the first relative position information between the first reference object of the first measurement module and the image acquisition unit, and the second relative position information between the second reference object of the second measurement module and the target block, construct a coordinate system transformation chain between the first measurement module and the second measurement module.

[0063] Specifically, the first relative position information and the second relative position information can be obtained from the database respectively.

[0064] Step 1007: Perform coordinate transformation calculation based on the coordinate system transformation chain to obtain the target relative position information between the first measurement module and the second measurement module.

[0065] Based on the technical solution of the above embodiments of this application, using a target block as a geometric reference, the spatial relationship between the first measurement module and the second measurement module is established through the target image. Specifically, the inner and outer contour parameters of the marker graphic are extracted, and the center coordinates of the inner and outer contours of the marker graphic are fitted based on the contour parameters to obtain the first center coordinates in the camera coordinate system. Then, based on the first center coordinates and the known second center coordinates in the target block coordinate system, a transformation matrix between the camera coordinate system and the target block coordinate system is constructed to accurately locate the transformation relationship between the two measurement modules, thereby accurately locating the target relative position information between the first and second measurement modules. It can be seen that by implementing the position calibration method of the embodiments, the spatial calibration accuracy of the measurement modules can be guaranteed, thereby effectively improving the measurement accuracy of the four-wheel alignment parameters.

[0066] It should be understood that the sequence number of each step in this embodiment does not imply the order in which the steps are executed. The execution order of each step should be determined by its function and internal logic, and should not constitute a unique limitation on the implementation process of this application embodiment.

[0067] Figure 11 This application provides a position calibration device according to a third embodiment. This position calibration device can be applied to the aforementioned position calibration method, specifically to a vehicle four-wheel alignment system. The vehicle four-wheel alignment system is equipped with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit's capture direction is towards the target block to acquire a target image of the target block. Figure 11 As shown, the position calibration device mainly includes: The acquisition module 1101 is used to acquire the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit; The first determining module 1102 is used to determine the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block based on the target image and optical characteristic parameters. The second determining module 1103 is used to determine the target relative position information between the first measuring module and the second measuring module based on the first relative position information, the second relative position information, and the transformation matrix.

[0068] In some embodiments of this example, the first determining module is specifically used to: extract the contour parameters of all marker graphics in the target image, wherein the marker graphics are the graphics of the markers of the target block presented in the target image; determine the first center coordinates of each marker graphic in the first coordinate system corresponding to the image acquisition unit according to the contour parameters; obtain the second center coordinates of the markers of the target block in the second coordinate system corresponding to the target block; and input each first center coordinate, each second center coordinate, and optical characteristic parameters into a preset perspective projection model to obtain the transformation matrix between the first coordinate system and the second coordinate system.

[0069] Furthermore, in some embodiments of this example, the target block is provided with multiple concentric circle markers spaced apart, and the marker pattern is a graphic of the concentric circle markers presented in the target image; the contour parameters include a first contour parameter of the outer contour of each marker pattern and a second contour parameter of the inner contour. Correspondingly, when the first determining module performs the function of determining the first center coordinates of each marker pattern in the first coordinate system corresponding to the image acquisition unit based on the contour parameters, it is specifically used to: determine the first initial parameter matrix of each outer contour based on the first contour parameter; determine the second initial parameter matrix of each inner contour based on the second contour parameter; construct the characteristic equation of each marker pattern based on each first initial parameter matrix and each second initial parameter matrix; wherein, each characteristic equation is used to characterize the geometric transformation relationship between the outer contour and the inner contour of the corresponding marker pattern; and calculate the first center coordinates corresponding to each marker pattern based on each characteristic equation.

[0070] Furthermore, in some embodiments of this example, the target block is provided with multiple concentric circle markers spaced apart, and the marker pattern is the pattern of the concentric circle markers presented in the target image. When the first determining module performs the function of calculating the first center coordinates corresponding to each marker pattern based on each feature equation, it is specifically used to: perform feature decomposition on each feature equation to obtain the feature values ​​of each feature equation; determine the first target parameter matrix of each outer contour and the second target parameter matrix of each inner contour based on each feature value; and calculate the first center coordinates corresponding to each marker pattern based on the first target parameter matrix and the corresponding second target parameter matrix of each marker pattern.

[0071] Furthermore, in some embodiments of this example, one feature equation corresponds to multiple feature values; correspondingly, when the first determining module performs the function of determining the first target parameter matrix of each outer contour and the second target parameter matrix of each inner contour based on each feature value, it is specifically used to: calculate the first difference between multiple feature values ​​of a single feature equation; if the first difference is less than or equal to a first preset threshold, determine the marked graphic corresponding to the first difference as the graphic to be processed; perform scaling radius compensation on the outer contour and inner contour of the graphic to be processed based on a preset scaling ratio to obtain the target contour parameters of the compensated graphic to be processed; calculate multiple target feature values ​​of the compensated graphic to be processed according to the target contour parameters, and calculate the feature distance between the multiple target feature values; calculate the first target parameter matrix of the outer contour of the compensated graphic to be processed and the second target parameter matrix of the corresponding inner contour according to the feature distance.

[0072] In some embodiments of this example, the target block is provided with multiple concentric circle markers distributed at intervals, and the marker pattern is the pattern of the concentric circle markers presented in the target image; accordingly, the first determining module is also specifically used to: calculate a second difference between the number of concentric circle markers on the target block and the number of marker patterns in the target image; if the second difference satisfies the condition for supplementing the target image with markers, then based on the pattern distribution rules of the target block and the first center coordinates, determine the center coordinates of the pattern to be supplemented in the target image.

[0073] Furthermore, in some embodiments of this example, when the first determining module performs the function of determining the center coordinates of the graphic to be supplemented in the target image based on the graphic distribution rules of the target block and the first center coordinates if the second difference satisfies the condition for supplementing the target image with markings, it is specifically used for: if the second difference satisfies the condition for supplementing the target image with markings, determining the sorting direction of the marking graphics in the target image based on the graphic distribution rules of the target block; calculating the distance parameter between the first center coordinates of two adjacent marking graphics along the sorting direction; if the distance parameter is greater than a second preset threshold, determining that there is a missing marking graphic between the two marking graphics corresponding to the distance parameter; and determining the center coordinates of the graphic to be supplemented in the target image based on the first center coordinates of the two marking graphics corresponding to the distance parameter.

[0074] In other embodiments of this example, multiple concentric circle markers are arranged in multiple rows and symmetrically distributed in the target block. Correspondingly, when the first determining module performs the function of determining the center coordinates of the graphic to be supplemented in the target image based on the graphic distribution rules of the target block and the first center coordinates if the second difference satisfies the condition for supplementing the target image with markers, it is specifically used to: if the second difference satisfies the condition for supplementing the target image with markers, determine the row number corresponding to each marker graphic in the target image based on each first center coordinate, and count the number of graphic markers corresponding to each row number; determine the row number to which the graphic to be supplemented belongs based on the number of graphic markers corresponding to each row number, and determine the vertical coordinate of the center of the graphic to be supplemented in the target image; determine the horizontal coordinate of the center of the graphic to be supplemented based on the graphic distribution rules; and determine the center coordinates of the graphic to be supplemented based on the vertical and horizontal coordinates.

[0075] Furthermore, in some embodiments of this example, the concentric circles of adjacent rows are staggered in the target block; correspondingly, when the first determining module performs the function of determining the abscissa of the center of the graphic to be supplemented based on the graphic distribution rules, it is also specifically used for: determining reference rows in the target graphic that do not lack marker graphics based on the graphic distribution rules; performing region detection on the target image based on the first center coordinates of each marker graphic in the reference row to determine the target area where the graphic to be supplemented is located in the target image; determining reference marker graphics corresponding to the target area based on the graphic distribution rules; and determining the abscissa of the center of the graphic to be supplemented based on the abscissa of the first center coordinates of the reference marker graphics.

[0076] In some embodiments of this example, the second determining module is specifically used to: construct a coordinate system transformation chain between the first measurement module and the second measurement module based on the first relative position information, the second relative position information, and the transformation matrix; and perform coordinate transformation calculations based on the coordinate system transformation chain to obtain the target relative position information between the first measurement module and the second measurement module.

[0077] According to the position calibration device provided in this embodiment, the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit are acquired. Based on the target image and the optical characteristic parameters, the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block is determined. Based on the first relative position information, the second relative position information, and the transformation matrix, the target relative position information between the first measurement module and the second measurement module is determined. Through the implementation of the solution of this application, using the target block as a geometric reference, the spatial relationship between the first measurement module and the second measurement module is established through the target image, thereby determining the transformation relationship between the two, that is, determining the transformation matrix. Then, the target relative position information between the first measurement module and the second measurement module can be determined based on the transformation matrix, and the accurate calibration of the relative position relationship between the measurement modules can be achieved on site.

[0078] Figure 12 A vehicle four-wheel alignment system is provided in the fourth embodiment of this application. This vehicle four-wheel alignment system can be used to implement the position calibration method in the foregoing embodiments, and mainly includes: The system comprises a first measurement module 1201, a second measurement module 1202, a memory 1203, a processor 1204, and a computer program 1205 stored in the memory 1203 and executable on the processor 1204. The memory 1203 and the processor 1204 are communicatively connected. The first measurement module 1201 includes an image acquisition unit and a first reference object. The second measurement module includes a target block and a second reference object 1202. The image acquisition unit is directed towards the target block to acquire a target image. When the processor 1204 executes the computer program 1205, it implements the method described in Embodiment 1 or 2. The number of processors can be one or more.

[0079] The memory 1203 can be a high-speed random access memory (RAM) or a non-volatile memory, such as a disk storage device. The memory 1203 is used to store executable program code, and the processor 1204 is coupled to the memory 1203.

[0080] Furthermore, embodiments of this application also provide a computer-readable storage medium, which may be disposed in the aforementioned vehicle four-wheel alignment system, and the computer-readable storage medium may be the aforementioned... Figure 12 The memory in the illustrated embodiment.

[0081] The computer-readable storage medium stores a computer program that, when executed by a processor, implements the location calibration method described in the foregoing embodiments. Furthermore, the computer-readable storage medium can also be a USB flash drive, a portable hard drive, a read-only memory (ROM), RAM, a magnetic disk, or an optical disk, or any other medium capable of storing program code.

[0082] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0083] The modules described as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0084] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0085] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned readable storage medium includes various media capable of storing program code, such as USB flash drives, external hard drives, ROM, RAM, magnetic disks, or optical disks.

[0086] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0087] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0088] The above is a description of the location calibration method, apparatus, system and readable storage medium provided in this application. For those skilled in the art, based on the ideas of the embodiments of this application, there will be changes in the specific implementation and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A position calibration method, characterized in that, The method is applied to a vehicle four-wheel alignment system, which is configured with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit is directed towards the target block to acquire a target image of the target block. The position calibration method includes: Acquire the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit; Based on the target image and the optical characteristic parameters, determine the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block; Based on the first relative position information, the second relative position information, and the transformation matrix, the target relative position information between the first measurement module and the second measurement module is determined.

2. The position calibration method according to claim 1, characterized in that, The step of determining the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block based on the target image and the optical characteristic parameters includes: Extract the contour parameters of all marker graphics in the target image; wherein, the marker graphics are the graphics of the markers of the target block presented in the target image; Based on the contour parameters, determine the first center coordinates of each of the marked graphics in the first coordinate system corresponding to the image acquisition unit; Obtain the second center coordinates of the target block's mark in the second coordinate system corresponding to the target block; The first center coordinates, the second center coordinates, and the optical characteristic parameters are input into a preset perspective projection model to obtain the transformation matrix between the first coordinate system and the second coordinate system.

3. The position calibration method according to claim 2, characterized in that, The target block is provided with a plurality of concentric circle marks distributed at intervals, and the mark pattern is the graphic of the concentric circle marks presented in the target image; the contour parameters include a first contour parameter of the outer contour of each mark pattern and a second contour parameter of the inner contour. Determining the first center coordinates of each of the marked graphics in the first coordinate system corresponding to the image acquisition unit based on the contour parameters includes: Based on the first contour parameters, determine the first initial parameter matrix for each of the outer contours; Based on the second contour parameters, determine the second initial parameter matrix for each of the inner contours; Based on each of the first initial parameter matrices and each of the second initial parameter matrices, characteristic equations for each of the marked graphics are constructed respectively; wherein, each of the characteristic equations is used to characterize the geometric transformation relationship between the outer contour and the inner contour of the corresponding marked graphics; Based on the characteristic equations described above, the first center coordinates corresponding to each of the marked graphics are calculated.

4. The position calibration method according to claim 2, characterized in that, The target block is provided with multiple concentric circle marks distributed at intervals, and the mark pattern is the image of the concentric circle marks presented in the target image; The position calibration method further includes: Calculate a second difference between the number of concentric circle markers on the target block and the number of marker patterns in the target image; If the second difference satisfies the condition for marking and supplementing the target image, then the center coordinates of the graphic to be supplemented in the target image are determined based on the graphic distribution rules of the target block and the first center coordinates.

5. The position calibration method according to claim 4, characterized in that, If the second difference satisfies the condition for marking and supplementing the target image, then based on the graphic distribution rules of the target block and the first center coordinates, the center coordinates of the graphic to be supplemented in the target image are determined, including: If the second difference satisfies the condition for marking and supplementing the target image, then the sorting direction of the marked graphics in the target image is determined based on the graphic distribution rules of the target block; Calculate the distance parameter between the first center coordinates of two adjacent marked graphics along the sorting direction; If the distance parameter is greater than the second preset threshold, then it is determined that there is a missing marker between the two markers corresponding to the distance parameter; Based on the first center coordinates of the two marked graphics corresponding to the distance parameter, the center coordinates of the graphic to be supplemented in the target image are determined.

6. The position calibration method according to claim 4, characterized in that, Multiple concentric circle markers are arranged in multiple rows and are symmetrically distributed in the target block; If the second difference satisfies the condition for marking and supplementing the target image, then based on the graphic distribution rules of the target block and the first center coordinates, the center coordinates of the graphic to be supplemented in the target image are determined, including: If the second difference satisfies the condition for marking and supplementing the target image, then based on each of the first center coordinates, the row number corresponding to each marked graphic in the target image is determined, and the number of graphic marks corresponding to each row number is counted respectively. Based on the number of graphic markers corresponding to each row number, the row number to which the graphic to be supplemented belongs is determined, and the vertical coordinate of the center of the graphic to be supplemented in the target image is determined. The x-coordinate of the center of the graphic to be supplemented is determined based on the graphic distribution rules. The center coordinates of the graphic to be supplemented are determined based on the ordinate and the abscissa.

7. The position calibration method according to claim 6, characterized in that, The concentric circles in adjacent rows are staggered within the target block; The step of determining the abscissa of the center of the graphic to be supplemented based on the graphic distribution rules includes: Based on the graphic distribution rules, a reference row in the target graphic that does not contain missing marker graphics is determined; Based on the first center coordinates of each of the marked graphics in the reference row, the target image is divided into regions for detection to determine the target region where the graphic to be supplemented is located. Based on the graphic distribution rules, a reference marker graphic corresponding to the target region is determined; Based on the x-coordinate of the first center coordinate of the reference marker graphic, determine the x-coordinate of the center of the graphic to be supplemented.

8. A position calibration device, characterized in that, An application is made in a vehicle four-wheel alignment system, the vehicle four-wheel alignment system being configured with a first measurement module and a second measurement module. The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit is directed towards the target block to acquire a target image of the target block; the position calibration device includes: The acquisition module is used to acquire the first relative position information between the first reference object and the image acquisition unit, the second relative position information between the second reference object and the target block, the target image, and the optical characteristic parameters of the acquisition device inside the image acquisition unit; The first determining module is used to determine the transformation matrix between the first coordinate system corresponding to the image acquisition unit and the second coordinate system corresponding to the target block based on the target image and the optical characteristic parameters. The second determining module is used to determine the target relative position information between the first measuring module and the second measuring module based on the first relative position information, the second relative position information, and the transformation matrix.

9. A vehicle four-wheel alignment system, characterized in that, It includes a first measurement module, a second measurement module, a memory, and a processor, wherein: The first measurement module includes an image acquisition unit and a first reference object, and the second measurement module includes a target block and a second reference object. The image acquisition unit is positioned to capture the target block in order to acquire the target image of the target block. The processor is used to execute computer programs stored in the memory; When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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