Intelligent reference scheme based on STEP extraction, knowledge model construction and spatial search

Abstract

The invention discloses an intelligent reference scheme based on STEP extraction, knowledge model construction and spatial search. The method comprises the steps of obtaining a digital model of a part; triggering the knowledge model to determine geometric feature information required by the positioning part; triggering a geometric analysis module to analyze the digital model, and determining a feature point cloud matched with the geometric feature information; triggering the knowledge model to determine candidate reference point clouds and evaluation point clouds according to the feature point clouds; and the trigger reasoning module determines whether the type of the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, and determines a positioning reference point of the part in combination with the type of the part. By adopting the technical scheme provided by the invention, the geometric analysis module firstly analyzes the digital model to determine the feature point cloud matched with the geometric feature information, then the knowledge model determines the candidate reference point cloud and the evaluation knowledge point cloud, and finally the reference point cloud of the part is determined by utilizing the reasoning module, so that the positioning reference point of the part can be quickly and accurately determined.

Description

Technical Field

[0001] The present application relates to the field of positioning technology, and specifically to an intelligent benchmarking solution based on STEP extraction, knowledge model construction, and spatial search. Background Art

[0002] At present, the determination of the positioning base points of automobile parts mainly relies on the experience of engineers or the positioning reference principle.

[0003] When determining the positioning reference points based on the engineers' experience, there are certain differences in the positioning reference points of parts designed by different engineers, and multiple rounds of meeting reviews are required to output relatively reasonable and relatively consistent results.

[0004] When determining the positioning reference points based on the positioning reference principle, the positioning reference principle has a certain ambiguity, and different engineers have different understandings, resulting in differences in the positioning reference points they determine. To ensure the quality of the positioning reference points, experienced engineers or experts need to review, which is inefficient.

[0005] It should be noted that the expert review results are manually assessed and lack objective indicators. It takes a lot of time for participants to reach a consensus. In addition, when determining the positioning reference points, most of the time, engineers need to operate manually. There is a certain probability of errors in the operation and transmission process, and the efficiency is not high.

[0006] Therefore, how to determine the positioning reference points of parts with high quality and efficiency is a technical problem that needs to be solved urgently. Summary of the invention

[0007] The present application provides an intelligent benchmark solution based on STEP extraction, knowledge model construction, and spatial search, which can determine positioning benchmark points with high quality and efficiency.

[0008] In a first aspect, an embodiment of the present application provides a method for determining a positioning reference point of a part (i.e., an intelligent reference solution based on STEP extraction, knowledge model construction, and spatial search), the method comprising:

[0009] Obtain a digital model of the part;

[0010] Triggering the knowledge model to determine geometric feature information required to locate the part;

[0011] Triggering a geometric analysis module to analyze the digital model and determine a feature point cloud matching the geometric feature information;

[0012] Triggering the knowledge model to determine candidate reference point clouds and evaluation point clouds according to the feature point clouds;

[0013] The triggering reasoning module determines whether the category of the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, and determines the positioning reference point of the part according to the category of the part.

[0014] By adopting the technical solution provided by this application, the geometric analysis module first analyzes the digital model to determine the feature point cloud that matches the geometric feature information required for positioning the part, then the knowledge model determines the candidate reference point cloud and the evaluation knowledge point cloud, and finally the reasoning module is used to determine the reference point cloud of the part. This application can quickly and accurately determine the part positioning reference point.

[0015] In another possible implementation, the method further includes: constructing a knowledge model according to the part positioning logic and the part positioning principle.

[0016] In another possible implementation, the triggering reasoning module determines whether the category of the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud, and the evaluation point cloud, including:

[0017] Inputting the candidate point cloud and the evaluation point cloud into a reasoning module;

[0018] The reasoning module determines the initial version of the positioning reference point set according to the rigid part positioning reference reasoning algorithm;

[0019] Determining a deformed point cloud using computer-aided engineering based on the preliminary positioning reference point set and the digital model;

[0020] The type of the part is determined based on the initial version positioning reference point set and the deformed point cloud, whether it is a rigid part or a flexible part.

[0021] In another possible implementation, determining the positioning reference point of the part according to the category of the part includes:

[0022] When it is determined that the part is a rigid part, directly outputting the coordinates of the positioning reference point of the part;

[0023] When it is determined that the category of the part is a flexible part, the "deformation point cloud" and the "initial positioning reference" are input into the flexible part positioning reasoning module to determine the coordinates of the positioning reference positioning points of the part.

[0024] In another possible implementation, triggering the knowledge model to determine a candidate reference point cloud and an evaluation point cloud according to the feature point cloud includes:

[0025] The triggering of the knowledge model determines candidate primary reference point clouds, secondary reference point clouds, primary evaluation point clouds, and secondary evaluation point clouds according to the feature point clouds.

[0026] In another possible implementation, the data model is a data model in STEP format.

[0027] In a second aspect, the present application provides a device for determining a positioning reference point of a part, the device comprising:

[0028] An acquisition module, used to acquire a digital model of a part;

[0029] A knowledge model for determining geometric feature information required to locate the part;

[0030] A geometric analysis module, used to analyze the digital model and determine a feature point cloud matching the geometric feature information;

[0031] The knowledge model is also used to determine candidate reference point clouds and evaluation point clouds based on the feature point clouds;

[0032] The reasoning module is used to determine whether the category of the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, and to determine the positioning reference point of the part according to the category of the part.

[0033] In another possible implementation manner, the determining device further includes:

[0034] A building module is used to build a knowledge model based on part location logic and part location principles.

[0035] In a third aspect, the present application provides a processing device, comprising: a memory and a processor, the memory storing a computer program executable by the processor, and the processor executing the method for determining the positioning reference point of a part described in the first aspect or any possible implementation of the first aspect.

[0036] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is read and executed, the processor executes the method for determining the positioning reference point of a part described in the first aspect or any possible implementation of the first aspect.

[0037] In the embodiment of the present application, the geometric analysis module first analyzes the digital model to determine the feature point cloud that matches the geometric feature information, then the knowledge model determines the candidate reference point cloud and the evaluation knowledge point cloud, and finally the reasoning module is used to determine the reference point cloud of the part. The present application does not rely on the personal experience and subjective judgment of the operator, but is based on the knowledge model determined by experience, so that the determined positioning reference point is more accurate, and since the processing process does not require manual operation, it has a higher processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1AIt is a schematic diagram of the six degrees of freedom involved in part positioning;

[0039] Figure 1B It is a schematic diagram of the three positioning reference points A1, A2 and A3 of the identification part;

[0040] Figure 1C It is a schematic diagram of two positioning reference points B and C for identifying parts;

[0041] Figure 2 It is a flowchart of a method for determining a part positioning reference point provided in an embodiment of the present application;

[0042] Figure 3 is a schematic diagram of a candidate reference point cloud and an evaluation reference point cloud determined in an embodiment of the present application;

[0043] Figure 4A It is a structural schematic diagram of a device for determining a part positioning reference point provided in an embodiment of the present application;

[0044] Figure 4B It is a schematic diagram of the processing process of a device for determining a part positioning reference in one embodiment of the present application;

[0045] Figure 4C is a schematic diagram of the processing process of the geometric analysis module in one embodiment of the present application;

[0046] Figure 4D is a schematic diagram of the processing process of the knowledge model in one embodiment of the present application;

[0047] Figure 4E is a schematic diagram of the processing process of the reasoning module in one embodiment of the present application;

[0048] Figure 5 It is a structural schematic diagram of a processing device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] Any unconstrained object has six independent movements in space. Take the rectangle shown in Figure 1 as an example. It can have three translations and three rotations in the rectangular coordinate system oxyz. The three translations are translations along the x, y, and z axes, and the three rotations are rotations around the x, y, and z axes. It is customary to call the above six independent movements six degrees of freedom. If certain constraints are taken to eliminate the six degrees of freedom of the object, the object will be completely positioned.

[0051] In the automotive industry and other industries, in the processes of parts processing, welding, and assembly, it is necessary to determine the part positioning reference points to fix the parts. The determination of the part positioning reference points has an important impact on the quality and accuracy of the processed parts.

[0052] In order to ensure the precise positioning of automotive parts during welding, assembly and other processes, and to achieve precise splicing and assembly of parts, it is necessary to determine the positioning reference points of the parts. The positioning reference points of the parts correspond to the position and number of the hand part installation points or the chucks of the tooling fixtures. Multiple hand part installation points or fixture combinations can achieve the goal of controlling the six degrees of freedom of the parts.

[0053] Constrain the parts' six degrees of freedom in 3D space, usually five, such as Figure 1B and Figure 1C A1, A2, A3, B and C. Corresponding to the 321 positioning reference method, that is, using three positioning reference points (A1, A2 and A3) to control the three degrees of freedom of the part, using the center point B of one positioning reference hole to control two degrees of freedom of the part, and using the center point of another positioning reference hole as the positioning reference C to control the last degree of freedom.

[0054] In order to determine the positioning reference points with high quality and efficiency, the present application provides an intelligent reference solution based on STEP extraction, knowledge model construction, and spatial search. The solution can be implemented through the following method for determining the part positioning reference points. The method for determining the part positioning reference points provided in the embodiment of the present application is introduced below in conjunction with the accompanying drawings.

[0055] See also Figure 2 , Figure 2 A schematic diagram of a flow chart of a method for determining a part positioning reference point provided by an embodiment of the present application. Figure 2 As shown, the method for determining the part positioning reference point provided in the embodiment of the present application includes steps 201 to 205. Steps 201 to 205 are described in detail below.

[0056] 201. Obtain the digital model of the part.

[0057] The digital model of the part may be a digital model in the format of the Stander for the Exchange of Product Model Data (STEP).

[0058] 202. The trigger knowledge model determines the geometric feature information required to locate the part.

[0059] The geometric feature information required to determine the positioning part may include: geometric information such as the bottom surface, circular hole, oblong hole, edge, etc., and may also include constraint information on the positioning reference point, such as the distance between the positioning reference point and the edge is greater than a preset length.

[0060] 203. Trigger the geometric analysis module to analyze the digital model and determine the feature point cloud that matches the geometric feature information.

[0061] 204. Trigger the knowledge model to determine candidate benchmark point clouds and evaluation point clouds based on the feature point clouds.

[0062] like Figure 3 As shown, the candidate point cloud can be Figure 3 The points corresponding to the circular marks with slashes in the middle can be the points corresponding to the hollow circle marks at the edge of the figure.

[0063] The triggering reasoning module determines whether the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, and determines the positioning reference point of the part according to the part category.

[0064] With this embodiment, the geometric analysis module first analyzes the digital model to determine the feature point cloud that matches the geometric feature information, then the knowledge model determines the candidate reference point cloud and the evaluation knowledge point cloud, and finally the reasoning module determines the reference point cloud of the part. This application does not rely on the personal experience and subjective judgment of the operator, and based on the knowledge model determined by experience, the determined positioning reference point is more accurate, and since the processing process does not require manual operation, it has a higher processing efficiency.

[0065] In some possible implementations, triggering the reasoning module to determine whether the category of a part is a rigid part or a flexible part based on the digital model, the candidate reference point cloud and the evaluation point cloud may include the following steps: inputting the candidate point cloud and the evaluation point cloud into the reasoning module; the reasoning module determines the initial version positioning reference point set according to the rigid part positioning reference reasoning algorithm; using computer aided engineering (CAE) to determine the deformed point cloud based on the initial version positioning reference point set and the digital model; determining whether the type of the part is a rigid part or a flexible part based on the initial version positioning reference point set and the deformed point cloud. Specifically, the point cloud whose deformation exceeds the preset value can be determined as a deformed point cloud. Among them, CAE uses computer-aided solution to analyze the structural mechanical properties of complex engineering and products, as well as optimize structural performance, etc., to organically organize various links of engineering (production). The key is to integrate relevant information. CAE can be used for static structural analysis and dynamic analysis; study linear and nonlinear problems; analyze structures (solids), fluids, electromagnetics, etc.

[0066] In some possible implementations, the positioning reference point of a part is determined according to the category of the part, including: when the category of the part is determined to be a rigid part, directly outputting the coordinates of the positioning reference point of the part; when the category of the part is determined to be a flexible part, inputting the "deformation point cloud" and the "initial positioning reference" into the flexible part positioning reasoning module to determine the coordinates of the positioning reference positioning point of the part.

[0067] In some possible implementations, when it is determined that the category of a part is a rigid part, several points may be uniformly sampled from the previously determined candidate positioning reference point cloud and the evaluation point cloud as positioning reference points, and the coordinates of these positioning reference points may be output.

[0068] In some possible implementations, when it is determined that the category of a part is a flexible part, a flexible part positioning reasoning module determined empirically determines a positioning reference point and outputs its coordinates.

[0069] In some possible implementations, triggering the knowledge model to determine candidate reference point clouds and evaluation point clouds based on the feature point clouds includes: triggering the knowledge model to determine candidate primary reference point clouds, secondary reference point clouds, primary evaluation point clouds, and secondary evaluation point clouds based on the feature point clouds. For example, Figure 1B The three points A1, A2 and A3 in can be points in the main reference point cloud. Figure 1CThe centers B and C of the holes in the figure can be points in the secondary reference point cloud, that is, the primary reference point cloud can be three points in the same plane, and the secondary reference point cloud can be the center of the hole on the part. It should be noted that in some possible embodiments, the distances between points A1, A2 and A3 and the edge can be limited, such as more than 5 mm from the edge, and for a certain part, the distances between the three points in pairs exceed a preset length, such as 7 cm, etc. It can also be further limited that when there are multiple holes, circular holes are preferred. It can be understood that specific constraints and limitations can be set according to specific parts, and are not limited here.

[0070] The above introduces a method for determining a part positioning reference point applicable to an embodiment of the present application. Corresponding to the method for determining a part positioning reference point provided in an embodiment of the present application, the present application also provides a device for determining a part positioning reference point.

[0071] like Figure 4A , which is a schematic diagram of the structure of a device for determining a part positioning reference point provided in an embodiment of the present application. Figure 4A The device 400 for determining the part positioning reference point includes: an acquisition unit 401, a geometric analysis module 402, a knowledge model 403 and a reasoning module 404.

[0072] See also FIG. 4B to FIG. 4E The acquisition unit 401 is used to acquire the digital model of the part; the digital model of the part can be a digital model in STEP format. The knowledge model 403 is used to determine the geometric feature information required for locating the part. The geometric analysis module 402 is as follows: Figure 4C As shown in , it is used to parse the digital model of the part and determine the feature point cloud that matches the geometric feature information; the knowledge model 403 is also used to determine the candidate reference point cloud and the evaluation point cloud based on the feature point cloud. The reasoning module 404 is used to determine whether the category of the part is a rigid part or a flexible part based on the digital model, the candidate reference point cloud and the evaluation point cloud, and to determine the positioning reference point of the part according to the category of the part.

[0073] It should be noted that the part positioning logic and part positioning principles can be determined based on experience, such as Figure 4D As shown, a knowledge model can be constructed based on the part positioning logic and part positioning principle. For example, the part positioning logic may include: first determine the primary reference point cloud, then determine the secondary reference point cloud, etc. The part positioning principle may include, for example, that the distance between the positioning reference points of a certain part A is greater than 10 cm, etc. This is just an exemplary description, and the part positioning logic and part positioning principle are not limited, and can be determined based on actual conditions and experience.

[0074] like Figure 4EAs shown, in some possible implementations, when determining whether the category of a part is a rigid part or a flexible part, the reasoning module can be specifically used to input the candidate point cloud and the evaluation point cloud into the reasoning module; the reasoning module determines the initial version positioning reference point set according to the rigid part positioning reference reasoning algorithm; determines the deformed point cloud using computer-aided engineering based on the initial version positioning reference point set and the digital model; determines whether the type of the part is a rigid part or a flexible part based on the initial version positioning reference point set and the deformed point cloud. In some possible implementations, when determining the positioning reference point of a part according to the category of the part, the reasoning module can be specifically used to: when determining that the category of the part is a rigid part, directly output the coordinates of the positioning reference point of the part; when determining that the category of the part is a flexible part, input the "deformed point cloud" and the "initial version positioning reference" into the flexible part positioning reasoning module to determine the coordinates of the positioning reference positioning point of the part.

[0075] For the sake of simplicity, the specific implementation of each unit module can refer to the description of the relevant steps in the previous method embodiment, which will not be repeated here.

[0076] It should be noted that a "unit" may be a software program, a hardware circuit, or a combination of the two that implements the above functions. The hardware circuit may include an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a dedicated processor, or a group processor, etc.) and a memory for executing one or more software or firmware programs, a combined logic circuit, and / or other suitable components that support the described functions.

[0077] Therefore, the units of each example described in the embodiments of the present application can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0078] Corresponding to the method for determining the part positioning reference point provided in the embodiment of the present application, the present application also provides a processing device, such as Figure 5 As shown, the processing device 500 includes: a memory 501 and a processor 502. The memory 501 stores a computer program executable by the processor 502, and the processor 502 implements the method for determining the part positioning reference point described in any of the above method embodiments when executing the computer program.

[0079] The present application also provides a computer program product, which, when executed by the processor 502 , implements the method for determining the part positioning reference point described in any method embodiment of the present application. The computer program product may be stored in the memory 501 .

[0080] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer, the method for determining a part positioning reference point described in any method embodiment of the present application is implemented.

[0081] The computer-readable storage medium may be a volatile memory or a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous connection dynamic random access memory (SLDRAM) and direct rambus RAM (DR RAM).

[0082] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0083] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0084] In the embodiments provided in the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device / network device embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0087] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0088] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0089] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for determining a part positioning reference point, characterized in that: The method comprises: Obtain a digital model of the part; Triggering the knowledge model to determine geometric feature information required to locate the part; Triggering a geometric analysis module to analyze the digital model and determine a feature point cloud matching the geometric feature information; Triggering the knowledge model to determine candidate reference point clouds and evaluation point clouds according to the feature point clouds; The triggering reasoning module determines whether the category of the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, and determines the positioning reference point of the part according to the category of the part.

2. The method according to claim 1, characterized in that The method further comprises: The knowledge model is constructed based on the part location logic and part location principles.

3. The method according to claim 1, characterized in that The triggering reasoning module determines whether the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, including: Inputting the candidate point cloud and the evaluation point cloud into a reasoning module; The reasoning module determines the initial version of the positioning reference point set according to the rigid part positioning reference reasoning algorithm; Determining a deformed point cloud using computer-aided engineering based on the preliminary positioning reference point set and the digital model; The type of the part is determined based on the initial version positioning reference point set and the deformed point cloud, whether it is a rigid part or a flexible part.

4. The method according to any one of claims 1 to 3, characterized in that: Determining the positioning reference point of the part according to the type of the part includes: When it is determined that the part is a rigid part, directly outputting the coordinates of the positioning reference point of the part; When it is determined that the category of the part is a flexible part, the "deformation point cloud" and the "initial positioning reference" are input into the flexible part positioning reasoning module to determine the coordinates of the positioning reference positioning points of the part.

5. The method according to any one of claims 1 to 3, characterized in that: The triggering of the knowledge model to determine the candidate reference point cloud and the evaluation point cloud according to the feature point cloud includes: The triggering of the knowledge model determines candidate primary reference point clouds, secondary reference point clouds, primary evaluation point clouds, and secondary evaluation point clouds according to the feature point clouds.

6. The method according to any one of claims 1 to 3, characterized in that: The data model is a data model in STEP format.

7. A device for determining a part positioning reference point, characterized in that: The device comprises: An acquisition module, used to acquire a digital model of a part; A knowledge model for determining geometric feature information required to locate the part; A geometric analysis module, used to analyze the digital model and determine a feature point cloud matching the geometric feature information; The knowledge model is also used to determine candidate reference point clouds and evaluation point clouds based on the feature point clouds; The reasoning module is used to determine whether the category of the part is a rigid part or a flexible part according to the digital model, the candidate reference point cloud and the evaluation point cloud, and to determine the positioning reference point of the part according to the category of the part.

8. The determination device according to claim 7, characterized in that: Also includes: A building module is used to build a knowledge model based on part location logic and part location principles.

9. A processing device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, the method for determining the part positioning reference point according to any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is read and executed, the method for determining the part positioning reference point according to any one of claims 1 to 6 is implemented.

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