A workpiece point cloud model generation method and related device

Abstract

The application provides a workpiece point cloud model generation method and related device, according to the face structure type in the target point cloud, the base vector correlation characteristics in the target point cloud under the point cloud coordinate system are collected, the orthogonal base vector of the target point cloud is generated based on the base vector correlation characteristics; based on the orthogonal base vector and the point cloud centroid of the target point cloud, a coordinate transformation matrix is constructed; according to the coordinate transformation matrix, the target point cloud is converted from the point cloud coordinate system to the workpiece point cloud model under the workpiece coordinate system. Through the construction of the coordinate transformation matrix, the target point cloud is converted from the point cloud coordinate system to the workpiece point cloud model under the workpiece coordinate system, so that the subsequent identification result is more suitable for the workpiece coordinate system under the real working condition.

Description

Technical Field

[0001] This invention relates to the field of welding, and more specifically, to a method and related apparatus for generating a workpiece point cloud model. Background Technology

[0002] There is a large demand for welding in modern industrial settings. Welding robots can be used to improve welding efficiency. Welding robots need to identify weld seams and plan welding paths in advance.

[0003] However, current recognition methods are all performed in a point cloud coordinate system. How to ensure that the recognition results are more consistent with the workpiece coordinate system under real working conditions has become a difficult problem of concern to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a method and related apparatus for generating a point cloud model of a workpiece, so as to improve the above-mentioned problems.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows: In a first aspect, embodiments of the present invention provide a method for generating a workpiece point cloud model, the method comprising: Based on the surface structure type in the target point cloud, the basis vector association features in the target point cloud coordinate system are collected, and orthogonal basis vectors of the target point cloud are generated based on the basis vector association features. Based on the orthogonal basis vectors and the centroid of the target point cloud, a coordinate transformation matrix is ​​constructed; Based on the coordinate transformation matrix, the target point cloud is transformed from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system.

[0006] Secondly, embodiments of the present invention provide a workpiece point cloud model generation device, the device comprising: The first processing unit is used to collect the basis vector association features of the target point cloud in the point cloud coordinate system according to the surface structure type in the target point cloud, and generate the orthogonal basis vectors of the target point cloud based on the basis vector association features. The first processing unit is further configured to construct a coordinate transformation matrix based on the orthogonal basis vectors and the centroid of the target point cloud; The second processing unit is used to convert the target point cloud from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system according to the coordinate transformation matrix.

[0007] Thirdly, embodiments of the present invention provide a storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0008] Fourthly, embodiments of the present invention provide an electronic device, the electronic device comprising: a processor and a memory, the memory being used to store one or more programs; when the one or more programs are executed by the processor, the above-described method is implemented.

[0009] Compared to existing technologies, the workpiece point cloud model generation method and related apparatus provided in this invention collect basis vector association features of the target point cloud in a point cloud coordinate system based on the surface structure type in the target point cloud; generate orthogonal basis vectors of the target point cloud based on the basis vector association features; construct a coordinate transformation matrix based on the orthogonal basis vectors and the centroid of the target point cloud; and transform the target point cloud from the point cloud coordinate system to a workpiece point cloud model in the workpiece coordinate system according to the coordinate transformation matrix. By constructing a coordinate transformation matrix to transform the target point cloud from the point cloud coordinate system to a workpiece point cloud model in the workpiece coordinate system, the subsequent recognition results are more consistent with the workpiece coordinate system under real working conditions.

[0010] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0013] Figure 2 This is a flowchart illustrating the method for generating a workpiece point cloud model according to an embodiment of the present invention.

[0014] Figure 3 This is a schematic diagram of a workpiece point cloud model generation device provided in an embodiment of the present invention.

[0015] In the diagram: 10-Processor; 11-Memory; 12-Bus; 13-Communication interface; 501-First processing unit; 502-Second processing unit. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0017] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0018] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0019] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0020] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of this invention is usually placed when in use. They are only for the convenience of describing this invention 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 this invention.

[0021] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; 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; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0022] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0023] This invention provides an electronic device, which may be a computer, a mobile phone, or a server, etc. Please refer to... Figure 1 This is a schematic diagram of the structure of an electronic device. The electronic device includes a processor 10, a memory 11, and a bus 12. The processor 10 and the memory 11 are connected via the bus 12. The processor 10 is used to execute executable modules, such as computer programs, stored in the memory 11.

[0024] Processor 10 can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the workpiece point cloud model generation method can be completed through integrated logic circuits in the hardware or software instructions within processor 10. Processor 10 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0025] The memory 11 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage.

[0026] Bus 12 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. Figure 1 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus 12 or one type of bus 12.

[0027] The memory 11 is used to store programs, such as the program corresponding to the workpiece point cloud model generation device. The workpiece point cloud model generation device includes at least one software function module that can be stored in the memory 11 in the form of software or firmware or embedded in the operating system (OS) of the electronic device. After receiving the execution instruction, the processor 10 executes the program to implement the workpiece point cloud model generation method.

[0028] The electronic device provided in this embodiment of the invention may further include a communication interface 13. The communication interface 13 is connected to the processor 10 via a bus.

[0029] It should be understood that, Figure 1 The structure shown is only a partial schematic diagram of the electronic device; the electronic device may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof.

[0030] The workpiece point cloud model generation method provided in this embodiment of the invention can be applied to, but is not limited to, [various applications]. Figure 1 For the specific process of the electronic devices shown, please refer to [link / reference]. Figure 2 The methods for generating workpiece point cloud models include S10, S20, and S30, which are described in detail below.

[0031] S10: Based on the surface structure type in the target point cloud, collect the basis vector association features in the target point cloud coordinate system, and generate orthogonal basis vectors of the target point cloud based on the basis vector association features.

[0032] S20: Based on orthogonal basis vectors and the centroid of the target point cloud, construct the coordinate transformation matrix.

[0033] Among them, the centroid of the point cloud refers to the centroid of the workpiece in the target point cloud.

[0034] S30, based on the coordinate transformation matrix, transform the target point cloud from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system.

[0035] The point cloud is transformed from the sensor coordinate system to the workpiece coordinate system for subsequent weld identification and path planning.

[0036] In the workpiece point cloud model generation method provided in this embodiment of the invention, a coordinate transformation matrix is ​​constructed to convert the target point cloud from the point cloud coordinate system to the workpiece point cloud model in the workpiece coordinate system, thereby ensuring that the subsequent recognition results are more consistent with the workpiece coordinate system under real working conditions.

[0037] Based on the preceding text, regarding the content of S10, this embodiment of the invention also provides an optional implementation method, please refer to the following. When the surface structure type in the target point cloud is a three-face structure, the three faces intersect each other in pairs, resulting in three surface intersection lines. In S10, according to the surface structure type in the target point cloud, the basis vector association features in the target point cloud coordinate system are collected. Based on the basis vector association features, orthogonal basis vectors of the target point cloud are generated, including: S111-S113, which are specifically described below.

[0038] S111, determine the common intersection point of the three-sided structure in the target point cloud.

[0039] Among them, the intersection point (intersection_point) belongs to three face structures simultaneously.

[0040] S112, take one point from each of the three intersection lines, namely the first point, the second point, and the third point.

[0041] It should be noted that the first point (point1), the second point (point2), and the third point (point3) do not overlap with the common intersection point. When the surface structure type in the target point cloud is a three-sided structure, the basis vector association features include the aforementioned common intersection point, the first point, the second point, and the third point.

[0042] S113, orthogonalize the first vector, the second vector and the third vector to obtain the three-axis orthogonal basis vectors.

[0043] Wherein, the first vector is the vector from the common intersection point to the first point, the second vector is the vector from the common intersection point to the second point, and the third vector is the vector from the common intersection point to the third point.

[0044] The first vector OA1 = intersection_point - point1; The second vector OA2 = intersection_point - point2; The third vector OA3 = intersection_point - point3.

[0045] Based on the preceding text, regarding the content in S113, this embodiment of the invention also provides an optional implementation method, please refer to the following. S113, orthogonalization processing is performed on the first vector, the second vector, and the third vector to obtain three-axis orthogonal basis vectors, including: S113A-S113D, as detailed below.

[0046] S113A performs normalization processing on the first vector, the second vector, and the third vector respectively.

[0047] S113B takes the absolute value of the normalized first, second, and third vectors (meaning turning negative numbers in the vectors into positive ones).

[0048] S113C performs orthogonalization on the first, second, and third vectors after taking their absolute values.

[0049] S113D takes the vector with the largest Z-axis component among the first, second, and third vectors after orthogonalization as the Z-axis of the workpiece coordinate system, and takes the remaining two vectors as the X-axis and Y-axis of the workpiece coordinate system.

[0050] After calculating OA1, OA2, and OA3, normalization is required, for example, in the form (0.99, -0.03, 0.04). Then, take the absolute value of (0.99, 0.03, 0.04), followed by orthogonalization. Check if orthogonalization has been performed, and the result should be (0.99, -0.03, 0.04), (0.03, 0.99, -0.03), and (-0.03, 0.03, 0.99).

[0051] Based on the preceding text, regarding the content of S10, this embodiment of the invention also provides an optional implementation method, please refer to the following text. When the surface structure type in the target point cloud is a bifacial structure, there is a surface intersection line. In S10, according to the surface structure type in the target point cloud, the basis vector association features in the target point cloud in the point cloud coordinate system are collected. Based on the basis vector association features, orthogonal basis vectors of the target point cloud are generated, including: S121-S126, which are specifically described below.

[0052] S121, determine the normal vectors (plane1 and plane2) corresponding to the two faces respectively.

[0053] S122, take two different points on the intersection line, namely the fourth point and the fifth point.

[0054] S123, based on the fourth and fifth points, obtain the direction vector of the plane intersection line.

[0055] Wherein, the direction vector of the plane intersection line is equal to the subtraction of the fourth point (point4) and the fifth point (point5).

[0056] When the surface structure type in the target point cloud is a two-sided structure, the basis vector association features include the normal vectors (plane1 and plane2) corresponding to the two surfaces mentioned above, as well as the direction vector of the plane intersection line.

[0057] S124, if the X-axis component of the plane intersection direction vector is greater than the Y-axis component, then the plane intersection direction vector is taken as the X-axis of the workpiece coordinate system; if the Y-axis component of the plane intersection direction vector is greater than the X-axis component, then the plane intersection direction vector is taken as the Y-axis of the workpiece coordinate system.

[0058] S125, take the one with the largest Z-axis component among the two normal vectors as the Z-axis of the workpiece coordinate system.

[0059] S126, orthogonalize the plane intersection direction vector and the largest Z-axis component of the two normal vectors to obtain the orthogonal basis vectors of the target point cloud.

[0060] Of course, normalization, absolute value taking, and orthogonalization can also be performed here in sequence.

[0061] Based on the preceding text, regarding the content of S20, this embodiment of the invention also provides an optional implementation method, please refer to the following. S20, based on the orthogonal basis vectors and the centroid of the target point cloud, constructs a coordinate transformation matrix, including: S21-S23, as detailed below.

[0062] S21, construct a rotation matrix based on the obtained triaxial orthogonal basis vectors.

[0063] The rotation matrix R = X_axis, Y_axis, Z_axis, where X_axis represents the orthogonal basis vectors along the X-axis, Y_axis represents the orthogonal basis vectors along the Y-axis, and Z_axis represents the orthogonal basis vectors along the Z-axis.

[0064] S22, construct the translation vector (t) from the centroid of the target point cloud to the origin of the point cloud coordinate system.

[0065] S23. Construct the coordinate transformation matrix based on the rotation matrix and the translation vector.

[0066] coordinate transformation matrix , is a 4×4 homogeneous transformation matrix that transforms the point cloud from the sensor coordinate system to the workpiece coordinate system, satisfying the right-hand rule, with the Z-axis approximately upward and aligned with the weld structure.

[0067] Optionally, after constructing the rotation matrix based on the obtained triaxial orthogonal basis vectors, the workpiece point cloud model generation method further includes: S21-1 and S21-2, as follows.

[0068] S21-1, when the distance between the determinant of the rotation matrix and -1 is less than the first threshold, the direction of the Z-axis orthogonal basis vector is reversed (to ensure that the Z-axis is upward).

[0069] S21-2, after reversing the direction of the Z-axis orthogonal basis vector, if the distance between the determinant of the rotation matrix and 1 is greater than the first threshold, then swap the Y-axis orthogonal basis vector and the X-axis orthogonal basis vector.

[0070] Building upon the previous steps, we can also calculate the angle bisectors of the normal vectors (plane1 and plane2) corresponding to the two surfaces, which can be used for subsequent weld direction calculations.

[0071] Specifically, bisector = (plane1_normal + plane2_normal).normalized().

[0072] The workpiece point cloud model generation method provided in this embodiment of the invention automates the establishment of the workpiece coordinate system without manual calibration. The system automatically establishes a coordinate system aligned with the geometric features of the workpiece from the point cloud and structural information.

[0073] The origin of the coordinate system is located at the centroid of the point cloud, and the coordinate axes are aligned with the main plane / edge of the workpiece, satisfying the right-hand coordinate system rule. The Z-axis is automatically adjusted to the upward direction.

[0074] Robust orthogonalization processing can generate an orthogonal coordinate system even if the input vectors are not perfectly orthogonal.

[0075] The fault tolerance mechanism employs vector normalization, Gram-Schmidt orthogonalization, directional consistency adjustment (ensuring positive orientation of each axis), and handling of degradation cases (using the default coordinate system when collinear or coplanar). If collinearity or coplanarity occurs, the default coordinate system (X=[1,0,0], Y=[0,1,0], Z=[0,0,1]) is used.

[0076] Please see Figure 3 , Figure 3 The present invention provides a workpiece point cloud model generation device, which is optionally applied to the electronic device described above.

[0077] The workpiece point cloud model generation device includes: a first processing unit 501 and a second processing unit 502.

[0078] The first processing unit 501 is used to collect the basis vector association features of the target point cloud in the point cloud coordinate system according to the surface structure type in the target point cloud, and generate orthogonal basis vectors of the target point cloud based on the basis vector association features. The first processing unit 501 is also used to construct a coordinate transformation matrix based on the orthogonal basis vectors and the centroid of the target point cloud; The second processing unit 502 is used to convert the target point cloud from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system according to the coordinate transformation matrix.

[0079] It should be noted that the workpiece point cloud model generation device provided in this embodiment can execute the method flow shown in the above method flow embodiment to achieve the corresponding technical effects. For the sake of brevity, any parts not mentioned in this embodiment can be referred to the corresponding content in the above embodiments.

[0080] This invention also provides a storage medium storing computer instructions and programs, which, when read and executed, perform the workpiece point cloud model generation method described above. The storage medium may include memory, flash memory, registers, or a combination thereof.

[0081] The following describes an electronic device, which may be a computer device, a mobile phone device, or a server device, etc. This electronic device, for example... Figure 1 As shown, the above-described workpiece point cloud model generation method can be implemented. Specifically, the electronic device includes: a processor 10, a memory 11, and a bus 12. The processor 10 may be a CPU. The memory 11 is used to store one or more programs, which, when executed by the processor 10, execute the workpiece point cloud model generation method of the above embodiment.

[0082] In summary, the workpiece point cloud model generation method and related apparatus provided in this embodiment of the invention collect basis vector association features of the target point cloud in the point cloud coordinate system according to the surface structure type in the target point cloud; generate orthogonal basis vectors of the target point cloud based on the basis vector association features; construct a coordinate transformation matrix based on the orthogonal basis vectors and the centroid of the target point cloud; and transform the target point cloud from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system according to the coordinate transformation matrix. By constructing the coordinate transformation matrix to transform the target point cloud from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system, the subsequent recognition results are more consistent with the workpiece coordinate system under real working conditions.

[0083] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0084] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for generating a point cloud model of a workpiece, characterized in that, The method includes: Based on the surface structure type in the target point cloud, the basis vector association features in the target point cloud coordinate system are collected, and orthogonal basis vectors of the target point cloud are generated based on the basis vector association features. Based on the orthogonal basis vectors and the centroid of the target point cloud, a coordinate transformation matrix is ​​constructed; Based on the coordinate transformation matrix, the target point cloud is transformed from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system.

2. The workpiece point cloud model generation method as described in claim 1, characterized in that, When the surface structure type in the target point cloud is a three-sided structure, the step of collecting basis vector association features in the target point cloud coordinate system according to the surface structure type in the target point cloud, and generating orthogonal basis vectors of the target point cloud based on the basis vector association features, includes: Determine the common intersection points of the three-sided structures in the target point cloud; Take one point from each of the three intersection lines, namely the first point, the second point, and the third point; The first vector, the second vector, and the third vector are orthogonalized to obtain a triaxial orthogonal basis vector; wherein the first vector is the vector from the common intersection point to the first point, the second vector is the vector from the common intersection point to the second point, and the third vector is the vector from the common intersection point to the third point.

3. The workpiece point cloud model generation method as described in claim 2, characterized in that, The orthogonalization process based on the first vector, the second vector, and the third vector to obtain triaxial orthogonal basis vectors includes: Normalize the first vector, the second vector, and the third vector respectively; Take the absolute values ​​of the normalized first, second, and third vectors; Perform orthogonalization on the first, second, and third vectors after taking their absolute values; The vector with the largest Z-axis component among the first, second, and third vectors after orthogonalization is taken as the Z-axis of the workpiece coordinate system, and the remaining two vectors are taken as the X-axis and Y-axis of the workpiece coordinate system.

4. The method for generating a workpiece point cloud model as described in claim 1, characterized in that, When the surface structure type in the target point cloud is a biplane structure, the step of collecting basis vector association features in the target point cloud coordinate system according to the surface structure type, and generating orthogonal basis vectors of the target point cloud based on the basis vector association features, includes: Determine the normal vectors corresponding to the two faces; Take two distinct points on the intersection line, namely the fourth point and the fifth point; Based on the fourth and fifth points, the direction vector of the plane intersection line is obtained; If the X-axis component of the plane intersection direction vector is greater than the Y-axis component, then the plane intersection direction vector is taken as the X-axis of the workpiece coordinate system; if the Y-axis component of the plane intersection direction vector is greater than the X-axis component, then the plane intersection direction vector is taken as the Y-axis of the workpiece coordinate system. The one with the largest Z-axis component among the two normal vectors is taken as the Z-axis of the workpiece coordinate system; The plane intersection direction vector and the one with the largest Z-axis component among the two normal vectors are orthogonalized to obtain the orthogonal basis vectors of the target point cloud.

5. The method for generating a workpiece point cloud model as described in claim 1, characterized in that, The construction of the coordinate transformation matrix based on the orthogonal basis vectors and the centroid of the target point cloud includes: Construct a rotation matrix based on the obtained triaxial orthogonal basis vectors; Construct the translation vector from the centroid of the target point cloud to the origin of the point cloud coordinate system; The coordinate transformation matrix is ​​constructed based on the rotation matrix and the translation vector.

6. The method for generating a workpiece point cloud model as described in claim 5, characterized in that, After constructing the rotation matrix based on the obtained triaxial orthogonal basis vectors, the method further includes: When the distance between the determinant of the rotation matrix and -1 is less than the first threshold, the direction of the Z-axis orthogonal basis vector is reversed.

7. The method for generating a workpiece point cloud model as described in claim 6, characterized in that, The method further includes: After reversing the direction of the Z-axis orthogonal basis vector, if the distance between the determinant of the rotation matrix and 1 is greater than the first threshold, then swap the Y-axis orthogonal basis vector with the X-axis orthogonal basis vector.

8. A workpiece point cloud model generation device, characterized in that, The device includes: The first processing unit is used to collect the basis vector association features of the target point cloud in the point cloud coordinate system according to the surface structure type in the target point cloud, and generate the orthogonal basis vectors of the target point cloud based on the basis vector association features. The first processing unit is further configured to construct a coordinate transformation matrix based on the orthogonal basis vectors and the centroid of the target point cloud; The second processing unit is used to convert the target point cloud from the point cloud coordinate system into a workpiece point cloud model in the workpiece coordinate system according to the coordinate transformation matrix.

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

10. An electronic device, characterized in that, include: Processor and memory, the memory being used to store one or more programs; When the one or more programs are executed by the processor, the method as described in any one of claims 1-7 is implemented.

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