A Method for Constructing a 3D Point Cloud Gap and Step Difference Calculation Model Based on Plane Mapping

Abstract

This invention relates to a method for constructing a calculation model for gaps and steps in three-dimensional point clouds based on planar mapping. The invention includes obtaining the parametric equations of the direction lines in the seam regions of a three-dimensional point cloud and constructing a cross-section of the three-dimensional point cloud accordingly; calculating the unit principal normal vectors of all non-seam region point clouds in the three-dimensional point cloud and constructing a mapping plane accordingly; obtaining the set of two-dimensional coordinate points and two-dimensional planar curve points corresponding to the seam region point clouds and direction lines within the cross-section in the mapping plane; calculating the left and right region attribute indices of the two-dimensional coordinate points and dividing the seam region point clouds within the cross-section into left and right regions accordingly; determining the left and right measurement base points corresponding to each of the left and right regions; and constructing mathematical models based on the coordinates of the left and right measurement base points and with the unit principal normal vector as the vertical direction to calculate the measured values ​​of gaps and steps in the point clouds within the cross-section.

Description

Technical Field

[0001] This invention relates to the field of 3D point cloud technology, and in particular to a method for constructing a 3D point cloud gap and step difference calculation model based on planar mapping. Background Technology

[0002] In industrial manufacturing, most industrial products with complex structures are assembled from multiple components. The quality of this assembly directly affects the performance of the product itself. "Gap" and "step difference" are two core evaluation indicators widely used in assessing the assembly quality of industrial products. For example... Figure 2 As shown, a cross-section of a certain 3D point cloud contains point clouds that reflect the characteristics of "gap" and "step difference". The corresponding schematic diagram is shown below. Figure 3 As shown in the figure, "gap" refers to the distance between the two measurement base points along the horizontal direction, and "step difference" refers to the distance between the two measurement base points along the vertical direction. To accurately measure the "gap" and "step difference," a calculation model for "gap" and "step difference" needs to be constructed first, and then the measured values ​​of "gap" and "step difference" on the point cloud on the cross-section can be calculated based on this model. However, accurately determining the two measurement base points is crucial in constructing the calculation model for "gap" and "step difference."

[0003] Due to the diversity of industrial products, point clouds on a cross-section may exhibit two different types: "separate" and "continuous," such as... Figure 4 and Figure 5 As shown. For "separated" cross-sectional point clouds, clustering can be used to divide them into left and right regions, and then the left and right measurement base points can be determined. However, for "continuous" cross-sectional point clouds, clustering may fail, making it impossible to accurately divide the cross-sectional point cloud into left and right regions. This makes it more difficult to determine the left and right measurement base points, and consequently, the construction of the "gap" and "step difference" calculation model fails. Summary of the Invention

[0004] To this end, the present invention provides a method for constructing a three-dimensional point cloud gap and step difference calculation model based on planar mapping. By calculating the unit normal vector of the point cloud in all non-seam region areas, constructing the cross-sectional mapping plane, and dividing the left and right regions of the cross-sectional point cloud, the determined measurement base point can more accurately reflect the true value of "gap" and "step difference", making the calculated "gap" and "step difference" values ​​more accurate.

[0005] To address the aforementioned technical problems, this invention provides a method for constructing a 3D point cloud gap and step difference calculation model based on planar mapping, comprising:

[0006] A three-dimensional point cloud set of the industrial product to be tested is obtained, and the three-dimensional point cloud set is divided into a seam region point cloud set and a non-seam region point cloud set.

[0007] Based on the point cloud set of the seam region, the parametric equation of the direction line is obtained, and based on the parametric equation of the direction line, a cross section of the three-dimensional point cloud is constructed.

[0008] Based on the point cloud set of the non-seamless region, the unit principal normal vector of all point clouds is calculated using the principal component analysis method.

[0009] Using the unit principal normal vector as the normal vector and the coordinates of any point cloud in the three-dimensional point cloud set as the origin, a spatial plane is constructed; all three-dimensional point clouds on the cross section and the parametric equations of the direction lines are mapped to a point on the cross section onto the spatial plane to obtain the set of two-dimensional coordinate points corresponding to the coordinate points of the three-dimensional point clouds and the two-dimensional plane curve points corresponding to the direction lines.

[0010] Based on the set of two-dimensional coordinate points and the mapped two-dimensional plane curve points, the left and right region attribute indices of any two-dimensional coordinate point in the set of two-dimensional coordinate points are obtained.

[0011] Based on the left and right region attribute indicators, the point cloud on the cross section corresponding to the two-dimensional coordinate point is divided into a left region and a right region.

[0012] Based on the attribution of the point clouds in the left and right regions to the seam or non-seam regions, they are divided into the left seam point cloud set, the left non-seam point cloud set, the right seam point cloud set, and the right non-seam point cloud set.

[0013] Based on the point cloud set of the left seam region and the point cloud set of the right seam region, the optimal left reference circle and the optimal right reference circle are fitted. Based on the point cloud set of the left non-seam region and the point cloud set of the right non-seam region, the left reference line and the right reference line are fitted.

[0014] Search for two first tangents perpendicular to the left reference line and its extension in the tangent family of the optimal left reference circle, and obtain two left intersection points of these two first tangents with the left reference line and its extension; search for two second tangents perpendicular to the right reference line and its extension in the tangent family of the right reference circle, and obtain two right intersection points of these two second tangents with the right reference line and its extension; based on the two left intersection points and the two right intersection points, select the pair of intersection points with the smallest Euclidean distance, and use them as the left measurement base point and the right measurement base point, respectively;

[0015] Based on the left and right measurement base points, and with the unit principal normal vector as the vertical direction, calculation models for the step difference and gap of the cross-sectional point cloud are constructed respectively.

[0016] In one embodiment of the present invention, based on the point cloud set of the seam region, the parametric equation of the direction line is obtained, and based on the parametric equation of the direction line, a cross section is constructed, including:

[0017] Calculate the parametric equation of the direction line according to the following formula;

[0018] ;

[0019] In the formula, It is the parametric equation of the direction line;

[0020] t is a continuous normalized parameter. ;

[0021] , and These are the component functions of the direction line with respect to t on the x-axis, y-axis, and z-axis, respectively, all of which are smooth and differentiable;

[0022] When the parametric equation of the direction line Get parameters At that time, any cross-section can be constructed. ;in, It is a fixed step size for parameter t. The number of fixed step sizes and .

[0023] In one embodiment of the present invention, the unit principal normal vector is calculated according to the following formula:

[0024] ;

[0025] In the formula, It is the unit principal normal vector;

[0026] A collection of point clouds representing non-seam regions;

[0027] yes The total number of all point clouds;

[0028] yes The normal vector of each point cloud in the cloud;

[0029] yes The weight corresponding to each point cloud in the data;

[0030] in:

[0031] ;

[0032] In the formula, yes The curvature of each point cloud in the cloud;

[0033] and This was obtained based on principal component analysis.

[0034] In one embodiment of the present invention, the two-dimensional coordinate points are calculated according to the following formula:

[0035] ;

[0036] In the formula, It is the constructed plane Any set of orthogonal unit basis vectors on;

[0037] Let all points in a 3D point cloud Form a set ;

[0038] It is a set The point cloud coordinates of any point in the plane are used as the construction plane. The origin of time;

[0039] It is a two-dimensional coordinate point;

[0040] It is the identity matrix;

[0041] It is the unit principal normal vector;

[0042] It is a cross section The coordinates of the three-dimensional point cloud on the surface.

[0043] In one embodiment of the present invention, the two-dimensional plane curve points are calculated according to the following formula:

[0044] ;

[0045] In the formula, It is the constructed plane Any set of orthogonal unit basis vectors on;

[0046] Let all points in a 3D point cloud Form a set ;

[0047] It is a set The point cloud coordinates of any point in the plane are used as the construction plane. The origin of time;

[0048] It is the identity matrix;

[0049] It is the unit principal normal vector;

[0050] The direction line parametric equation in the cross section The three-dimensional coordinates of a point at that location.

[0051] It is a two-dimensional plane curve point.

[0052] In one embodiment of the present invention, the left and right region attribute indicators are calculated according to the following formula:

[0053] ;

[0054] In the formula, These are attribute indicators for the left and right regions;

[0055] It is a set of two-dimensional coordinate points Any two-dimensional coordinate point in the array;

[0056] It is a point on a two-dimensional plane curve; yes The corresponding tangent vector;

[0057] ;

[0058] ;

[0059] In the formula, and The parametric equation of the direction line is mapped to the space plane and then... The value at;

[0060] and They are respectively and about The derivative of .

[0061] In one embodiment of the present invention, based on the left and right region attribute indices, the point cloud on the cross section corresponding to the two-dimensional coordinate point is divided into a left region and a right region, including:

[0062] When the left and right region attribute indices are greater than 0, the point cloud on the cross section corresponding to the two-dimensional coordinate point is divided into the left region;

[0063] When the left and right region attribute indices are less than 0, the point cloud on the cross section corresponding to the two-dimensional coordinate point is divided into the right region.

[0064] In one embodiment of the present invention, the point cloud set of the left seam region, the point cloud set of the left non-seam region, the point cloud set of the right seam region, and the point cloud set of the right non-seam region are respectively represented as follows:

[0065] ;

[0066] In the formula, It is the point cloud set of the left-side seam region;

[0067] It is the set of point clouds in the non-seam region on the left;

[0068] It is the point cloud set of the right-side seam region;

[0069] It is a collection of point clouds in the right non-seam region;

[0070] It is the left area;

[0071] It is the right-hand area;

[0072] It is a collection of point clouds in the seam region;

[0073] It is a collection of point clouds in non-seam regions.

[0074] In one embodiment of the present invention, the step difference is calculated according to the following formula:

[0075] ;

[0076] In the formula, It is the order difference;

[0077] It is the left measurement base point;

[0078] It is the right measurement base point;

[0079] It is the unit principal normal vector.

[0080] In one embodiment of the present invention, the gap is calculated according to the following formula:

[0081] ;

[0082] In the formula, It is a gap;

[0083] It is the left measurement base point;

[0084] It is the right measurement base point;

[0085] yes It is the order difference.

[0086] The technical solution of the present invention has the following advantages compared with the prior art:

[0087] The present invention discloses a method for constructing a 3D point cloud gap and step difference calculation model based on planar mapping. The planar mapping-based method for dividing the cross-sectional point cloud into left and right regions can quickly and accurately divide the point cloud in any state on the cross-section into left and right regions, thereby determining the left and right measurement base points and enabling the rapid construction of the "gap" and "step difference" calculation model. This method has strong versatility.

[0088] This invention proposes a new method for determining left and right measurement base points. The measurement base points determined by this method can more accurately reflect the true value of the "gap".

[0089] This invention uses the principal normal vector of the point cloud in the non-seam region on the cross section as the vertical direction, making the calculated "step difference" value more accurate. Attached Figure Description

[0090] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0091] Figure 1 This is a flowchart of the method for constructing a three-dimensional point cloud gap and step difference calculation model based on planar mapping according to the present invention.

[0092] Figure 2 It is a schematic diagram of a three-dimensional point cloud on a cross section.

[0093] Figure 3 This is a schematic diagram of the gap and step difference.

[0094] Figure 4 This is a schematic diagram showing the separation of three-dimensional point clouds on a cross section.

[0095] Figure 5 This is a schematic diagram of a continuous three-dimensional point cloud on a cross section.

[0096] Figure 6 This is a schematic diagram of different regions in a 3D point cloud.

[0097] Figure 7 This is a schematic diagram of the seam region point cloud and its direction lines extracted from a 3D point cloud.

[0098] Figure 8 This is a schematic diagram of a cross-sectional point cloud constructed along the direction line of the seam region in a three-dimensional point cloud.

[0099] Figure 9 This is a schematic diagram of the construction of the mapping plane.

[0100] Figure 10 This is a schematic diagram of a plane mapping.

[0101] Figure 11 This is a schematic diagram showing the determination of the left and right base points on the cross section.

[0102] Figure 12 This is a schematic diagram of the calculation model for "gap" and "step difference". Detailed Implementation

[0103] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0104] In this invention, when directions (up, down, left, right, front, and back) are described, it is only for the convenience of describing the technical solution of this invention, and does not indicate or imply that the technical features referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0105] In this invention, "several" means one or more, "multiple" means two or more, "greater than," "less than," "exceeding," etc., are understood to exclude the stated number; "above," "below," "within," etc., are understood to include the stated number. In the description of this invention, the terms "first" and "second" are used only to distinguish technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0106] In this invention, unless otherwise explicitly defined, the terms "setting," "installing," and "connecting" should be interpreted broadly. For example, they can refer to a direct connection or an indirect connection through an intermediate medium; a fixed connection, a detachable connection, or an integrally formed connection; a mechanical connection, an electrical connection, or a connection capable of mutual communication; or the internal connection of two components or the interaction between two components. Those skilled in the art can reasonably determine the specific meaning of the above terms in this invention based on the specific content of the technical solution.

[0107] Reference Figure 1 As shown, a method for constructing a 3D point cloud gap and step difference calculation model based on planar mapping includes the following steps:

[0108] S1. Obtain the 3D point cloud set of the industrial product to be tested. The three-dimensional point cloud set is divided into point cloud sets of seam regions. and point cloud sets of non-seam regions ;

[0109] S2, Based on the point cloud set of the seam region The parametric equations of the direction lines are obtained. Based on the direction line parameter equation Construct a cross section .

[0110] Reference Figure 6 As shown, the set of three-dimensional point clouds corresponding to the entire industrial product is known. The collection of point clouds of all non-seamless regions in the data. And the complete point cloud set of the seam area (Right now ).

[0111] Reference Figure 7 As shown, a known 3D point cloud center seam area Direction line parametric equation In the formula, t is a continuous normalized parameter. . , and These are the component functions of the direction line with respect to t along the x, y, and z axes, respectively, all of which are smooth and differentiable. When the parametric equation of the direction line... Get parameters Time (of which, It is a fixed step size for parameter t. The number of fixed step sizes and , can Figure 6 Constructing a 3D point cloud as shown Figure 8 The cross section shown .

[0112] Specifically, principal component analysis is used to calculate the three-dimensional point cloud set. All the clouds Corresponding curvature and normal vector .

[0113] Let all points in a 3D point cloud Form a set Ren Yidianyun All point clouds in the neighborhood Form a set .but Each point cloud covariance matrix It can be expressed by formula (1):

[0114] (1)

[0115] In the formula , It is a set The total number of all point clouds.

[0116] According to formula (2) Singular value decomposition yields:

[0117] (2)

[0118] In the formula It is composed of eigenvectors , and The orthogonal matrix formed (i.e. ), It is by , and The corresponding eigenvalues , and The diagonal matrix formed (i.e.) ),and .

[0119] but and It can be expressed as follows according to formulas (3) and (4):

[0120] (3)

[0121] (4)

[0122] Next, the left and right regions of the cross-sectional point cloud will be divided.

[0123] S3. Based on the point cloud set of the non-seamless region Based on the principal component analysis method described above, the unit principal normal vectors of all point clouds are calculated. .

[0124] Figure 8 Point cloud collection of the China-Africa seam region The unit principal normal vector of all point clouds It can be calculated according to formula (5):

[0125] (5)

[0126] In the formula, It is the unit principal normal vector;

[0127] A collection of point clouds representing non-seam regions;

[0128] yes The total number of all point clouds;

[0129] yes The normal vector of each point cloud in the cloud;

[0130] yes The weight corresponding to each point cloud in the data;

[0131] in:

[0132] ;

[0133] In the formula, yes The curvature of each point cloud in the cloud.

[0134] and It can be obtained from formulas (1) to (4).

[0135] S4, using the aforementioned unit principal normal vector As the normal vector, the three-dimensional point cloud set Construct a spatial plane with the coordinates of any point cloud as the origin. ; the cross section All 3D point clouds and the parametric equation of the direction line In the cross section a little bit Mapped to the space plane The above yields two-dimensional coordinate points. Two-dimensional coordinate point set and two-dimensional plane curve points .

[0136] Specifically, such as Figure 9 As shown, with For normal vectors, set The coordinates of any point cloud in the 3D point cloud (for ease of demonstration, this embodiment uses the coordinates of the point above the 3D point cloud). Construct a spatial plane with the origin as the origin. .like Figure 10 As shown, the cross-section All 3D point clouds and the direction line of the seam area In cross section a little bit Mapping to a plane The mapping results can be denoted as follows: and At this time, the set any point in It can be viewed as a two-dimensional coordinate point. It can be viewed as a point on a two-dimensional plane curve. Among them, and This can be expressed using formulas (6) and (7) respectively:

[0137] (6)

[0138] (7)

[0139] In the formula, It is the constructed plane Any set of orthogonal unit basis vectors on;

[0140] It is a two-dimensional coordinate point;

[0141] It maps the coordinates of points on a two-dimensional plane curve;

[0142] It is the identity matrix;

[0143] It is the unit principal normal vector;

[0144] These are the coordinates of a three-dimensional point cloud on the cross section;

[0145] It represents the three-dimensional coordinates of a point on the cross section where the direction line parametric equation is located;

[0146] Let all points in a 3D point cloud Form a set ;

[0147] It is a set The point cloud coordinates of any point in the plane are used as the construction plane. The origin of time.

[0148] S5. Based on the set of two-dimensional coordinate points and the two-dimensional plane curve points The set of two-dimensional coordinate points is obtained. any two-dimensional coordinate point Left and right area attribute indicators .

[0149] Specifically, let Its corresponding tangent vector can be expressed as .

[0150] in, and The parametric equation of the direction line Mapping to a plane Later The value at the given location (which can be calculated according to formula (7));

[0151] and They are respectively and about The derivative of .

[0152] For a spatial plane any point on According to formula (8), the left and right area attribute indicators are defined. :

[0153] (8)

[0154] S6. Based on the left and right region attribute indicators , the cross section The above and the two-dimensional coordinate points Corresponding point cloud Divided into the left area and the right area Specifically, this includes:

[0155] When the left and right region attribute indicators When >0, the cross section The above and the two-dimensional coordinate points Corresponding point cloud Divided into the left area ;

[0156] When the left and right region attribute indicators When <0, the cross section The above and the two-dimensional coordinate points Corresponding point cloud Divided into the right area .

[0157] Next, the left and right measurement base points will be determined.

[0158] On the cross section After dividing the point cloud into left and right regions, the cross section can be determined by following these steps. Left and right measurement base points of the upper point cloud.

[0159] S7, Based on the left region and the right-hand region The point clouds in each region are assigned to either the seam-side or non-seam-side regions, and are divided into a left seam-side region point cloud set. Point cloud set of the non-seam region on the left Point cloud set of the right seam region and point cloud set of the right non-seam region .

[0160] Specifically, the point cloud set of the left seam region The point cloud set of the left non-seam region The point cloud set of the right seam region and the point cloud set of the right non-seam region They are represented as follows:

[0161] (9)

[0162] In the formula, It is the point cloud set of the left-side seam region;

[0163] It is the set of point clouds in the non-seam region on the left;

[0164] It is the point cloud set of the right-side seam region;

[0165] It is a collection of point clouds in the right non-seam region;

[0166] It is the left area;

[0167] It is the right-hand area;

[0168] It is a collection of point clouds in the seam region;

[0169] It is a collection of point clouds in non-seam regions.

[0170] S8, such as Figure 11 As shown. Using the RANSAC circle fitting algorithm, based on the point cloud set of the left seam region respectively. and the point cloud set of the right seam region The optimal left reference circle was obtained by fitting. and the best right reference circle Using the RANSAC straight line fitting algorithm, based on the point cloud set of the left non-seam region respectively... and the point cloud set of the right non-seam region The left baseline was obtained by fitting. and right baseline ;

[0171] S9, in the optimal left reference circle Searching for the left baseline within the family of tangents. The two first tangents perpendicular to its extension are obtained, and the two first tangents and the left reference line are obtained. The two left intersection points of its extension line and ; in the right reference circle Searching for the right baseline within the tangent family. And its extension line perpendicular to two second tangent lines, and obtain the two second tangent lines and the right reference line. and the two right intersection points of its extension. and .

[0172] exist , , and Find the two intersection points with the shortest Euclidean distance among the four intersection points, and use them as the left measurement base points respectively. (Right now ) and right measurement base point (Right now ).

[0173] S10, Based on the left measurement base point (Right now ) and the right measurement base point (Right now ), with the unit principal normal vector For the vertical direction, the step difference of the point cloud of the cross section was calculated. and gap .

[0174] After determining the left and right measurement base points on the cross-sectional point cloud, a calculation model for the "gap" and "step difference" can be constructed. For example... Figure 12 As shown, in sets The unit principal normal vector of all point clouds The step difference of the cross-sectional point cloud is calculated in the vertical direction. Then, the gaps in the cross-sectional point cloud are calculated using the Pythagorean theorem. .in, and The calculations can be performed according to formulas (10) and (11) respectively.

[0175] (10)

[0176] (11)

[0177] In the formula, It is the left measurement base point;

[0178] It is the right measurement base point;

[0179] It is the unit principal normal vector.

[0180] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0181] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0182] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0183] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0184] Finally, it should be noted that the above specific embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for constructing a plane-mapping-based three-dimensional point cloud gap and step calculation model, characterized in that, The method comprises the following steps: acquiring a three-dimensional point cloud set of an industrial product to be measured, and dividing the three-dimensional point cloud set into a point cloud set of a jointing area and a point cloud set of a non-jointing area; based on the point cloud set of the jointing area, obtaining a parametric equation of a direction line, and based on the parametric equation of the direction line, constructing a cross section of the three-dimensional point cloud; based on the point cloud set of the non-jointing area, using a principal component analysis method to obtain unit principal normal vectors of all point clouds; taking the unit principal normal vectors as normal vectors and the coordinates of any point cloud in the three-dimensional point cloud set as an origin to construct a spatial plane; mapping all three-dimensional point clouds on the cross section and a point of the parametric equation of the direction line at the cross section to the spatial plane to obtain a two-dimensional coordinate point set corresponding to three-dimensional coordinate points of the point cloud and a two-dimensional plane curve point corresponding to the direction line; based on the two-dimensional coordinate point set and the two-dimensional plane curve point, obtaining a left-right area attribute index of any two-dimensional coordinate point in the two-dimensional coordinate point set; based on the left-right area attribute index, dividing the point cloud corresponding to the two-dimensional coordinate point on the cross section into a left area and a right area; based on the attribution of the point cloud in the left area and the right area to the jointing area or the non-jointing area, dividing the point cloud into a left jointing area point cloud set, a left non-jointing area point cloud set, a right jointing area point cloud set and a right non-jointing area point cloud set; based on the left jointing area point cloud set and the right jointing area point cloud set, fitting to obtain a best left reference circle and a best right reference circle, and based on the left non-jointing area point cloud set and the right non-jointing area point cloud set, fitting to obtain a left reference line and a right reference line; in a family of tangent lines of the best left reference circle, searching for two first tangent lines perpendicular to the left reference line and an extension line of the left reference line, and obtaining two left intersection points of the two first tangent lines and the left reference line and the extension line of the left reference line; in a family of tangent lines of the right reference circle, searching for two second tangent lines perpendicular to the right reference line and an extension line of the right reference line, and obtaining two right intersection points of the two second tangent lines and the right reference line and the extension line of the right reference line; based on the two left intersection points and the two right intersection points, selecting a pair of intersection points with the smallest Euclidean distance as a left measuring base point and a right measuring base point, respectively; based on the left measuring base point and the right measuring base point, taking the unit principal normal vectors as a vertical direction to construct a step difference and gap calculation model of the cross section point cloud, respectively; the left-right area attribute index is calculated according to the following formula: ； In the formula, is the left and right region attribute index; is a set of two-dimensional coordinate points any two-dimensional coordinate point in is a two-dimensional planar curve point; is a corresponding tangent vector; ； ； wherein and are the values of the parametric equation of the direction line after mapping to the spatial plane at ; and respectively and with respect to derivative.

2. The method of claim 1, wherein, based on the point cloud set of the jointing area, obtaining a parametric equation of a direction line, and based on the parametric equation of the direction line, constructing a cross section, comprising: calculating the parametric equation of the direction line according to the following formula; ； wherein is the parametric equation of the direction line; t is a continuous normalizing parameter, ; , and are the component functions of the direction line on the x-axis, y-axis and z-axis with respect to t, respectively, and are all smooth and differentiable; When the parametric equation of the direction line is taken , then any cross section can be constructed, where is a fixed step size of the parameter t, is the number of fixed step sizes, and .

3. The method of claim 1, wherein, the unit principal normal vector is calculated according to the following formula: ； wherein is the unit principal normal vector; is a set of non-pairing region point clouds; is total number of all point clouds in the set; is a normal vector of each point cloud in the set of point clouds; is a weight corresponding to each point cloud in the pair; wherein: ； In the formula, is curvature of each point cloud in the middle and Based on principal component analysis method.

4. The method of claim 1, wherein, the two-dimensional coordinate point is calculated according to the following formula: ； wherein is any set of orthogonal unit basis vectors on the plane constructed Let all the points in a three-dimensional point cloud constitute a set , ; is the set of point cloud coordinates of any point in , which is taken as the origin when constructing the plane are two-dimensional coordinate points; is the identity matrix; is the unit principal normal vector; is a three-dimensional point cloud coordinate on the cross-section .

5. The method of claim 1, wherein, the two-dimensional plane curve point is calculated according to the following formula: ； wherein is any set of orthogonal unit basis vectors on the constructed plane ; Let all the points in a three-dimensional point cloud constitute a set , ; is the set of point cloud coordinates of any point in is the set of point cloud coordinates of any point in is the origin when constructing the plane is the identity matrix; is the unit principal normal vector; is the three-dimensional coordinate of a point of the direction line parameter equation at the section cut is a two-dimensional planar curve point.

6. The method of claim 1, wherein, based on the left-right area attribute index, dividing the point cloud corresponding to the two-dimensional coordinate point on the cross section into a left area and a right area, comprising: when the left-right area attribute index is greater than 0, dividing the point cloud corresponding to the two-dimensional coordinate point on the cross section into a left area; When the left-right region attribute index is less than 0, the point cloud corresponding to the two-dimensional coordinate point on the section is divided into a right region.

7. The method of claim 1, wherein the method further comprises: The left matching region point cloud set, the left non-matching region point cloud set, the right matching region point cloud set and the right non-matching region point cloud set are respectively represented as follows: ； In the formula, is a left pair-seam region point cloud set; is a set of left non-suture region point clouds; is a set of right-to-left region point clouds; is a set of right non-suture region point clouds; is the left region; is the right region; is a set of stitching area point clouds; is a set of non-mating area point clouds.

8. The method of claim 1, wherein, The step difference is calculated according to the following formula: ； In the formula, is the step difference; is the left measurement base point; is the right measuring base point; is the unit principal normal vector.

9. The method of claim 1, wherein, The gap is calculated according to the following formula: ； wherein is a gap; is the left measurement base point; is the right measuring base point; is is a step difference.

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