A method, device and medium for multi-level geometric entity cognitive behavior modeling

Abstract

The application discloses a kind of multilevel geometric entity cognitive behavior modeling method, device and medium, belong to computer-aided path field.The method includes: in the part modeling stage, interactive feature pair (IFP) is associated, and the belief-desire-intention cognitive behavior model of multilevel geometric entity is established based on interactive feature pair;Wherein, multilevel geometric entity includes basic interactive feature pair (B-IFP), composite interactive feature pair (C-IFP) and part;According to the belief-desire-intention cognitive behavior model constructed, the part with cognitive ability realizes assembly path planning process autonomously.The application establishes the method of multilevel geometric entity cognitive behavior model, enhances the cognitive ability of part, reduces the heavy man-machine interactive operation in assembly process, effectively improves the intelligent degree of assembly path planning process.

Description

Technical Field

[0001] This invention relates to the field of computer-aided path design, and more particularly to a method, apparatus, and medium for multi-level geometric entity cognitive behavior modeling. Background Technology

[0002] Assembly path planning is one of the most effective ways to solve complex product assembly problems. A good assembly path ensures the continuity of the assembly process, while a poor one significantly increases product costs and reduces production efficiency. Although most assembly path planning methods are now highly automated, the lack of autonomous recognition by parts means that the process is not truly autonomous. For forward assembly path planning methods, some human-machine interaction is still required, such as manually setting the assembly start and end points. For disassembly-based methods, operators need to pre-assemble the product. These cumbersome human-machine interactions result in low levels of intelligence in the assembly path planning process. Furthermore, because the designer's interactive intent (information on how parts should fit together) during the part modeling stage cannot be transmitted to the assembly modeling stage, a disconnect exists between upstream and downstream product design and manufacturing, severely hindering improvements in manufacturing efficiency. Summary of the Invention

[0003] In order to at least partially solve one of the technical problems existing in the prior art, the present invention aims to provide a method, apparatus and medium for multi-level geometric entity cognitive behavior modeling for autonomous assembly path planning.

[0004] The technical solution adopted in this invention is:

[0005] A method for modeling the cognitive behavior of multi-level geometric entities includes the following steps:

[0006] In the part modeling stage, associated interactive feature pairs (IFPs) are used to establish a multi-level geometric entity belief-desire-intention cognitive behavior model based on the interactive feature pairs; among them, the multi-level geometric entities include basic interactive feature pairs (B-IFPs), composite interactive feature pairs (C-IFPs), and parts.

[0007] Based on the constructed belief-desire-intention cognitive behavior model, parts with cognitive abilities autonomously realize the assembly path planning process.

[0008] Furthermore, the step of associating interactive feature pairs during the part modeling stage and establishing a multi-level geometric entity belief-desire-intention cognitive behavior model based on these interactive feature pairs includes:

[0009] The part is loaded into the assembly environment, and the part determines its starting pose q in the assembly path planning process based on the associated interaction features.ini Establish self-belief; determine the target pose q in the assembly path planning process by matching with parts of other related interactive feature pairs. tar Build a belief in the environment;

[0010] Based on established beliefs, the desired outcomes of the component include: finding a path that can be transformed from the initial pose q through a series of pose changes. ini To the target pose q tar The desire for a non-interference and feasible assembly path;

[0011] The intention of the parts includes: to realize their own desires through assembly path planning algorithms.

[0012] Furthermore, the beliefs of the basic interactive feature pairs include determining their own initial pose q. ini and target pose q tar The desire of a basic interaction feature pair is to find an interference-free path between two matching basic interaction feature pairs to complete the assembly; the intention of the basic interaction feature pair is a path planning algorithm.

[0013] The belief of a composite interaction feature pair is the set of beliefs of all the basic interaction feature pairs contained within it, such as the q of all the basic interaction feature pairs. ini The combined action yielded the q of the composite interactive feature pairs. ini The intention of a composite interactive feature pair is similar to the desire of a basic interactive feature pair; the intention of a composite interactive feature pair is the same as the intention of a basic interactive feature pair.

[0014] Furthermore, the information in the interactive feature pairs includes all planes and cylinders on the part that are associated with the interactive feature pairs. The normals of these planes and the axes of the cylinders work together to form a relative coordinate system, representing the current pose of the part. The pose is represented as q = (x,y,z,α,β,γ), where (x,y,z) represents the position of the origin of the relative coordinate system in the world coordinate system, and (α,β,γ) represents the angles between the x-axis, y-axis, and z-axis of the relative coordinate system and the x-axis, y-axis, and z-axis of the world coordinate system.

[0015] Furthermore, the part autonomously implements the assembly path planning process, including:

[0016] A1. Load the part set P{p1,p2,…,p n}, where n is the total number of parts; the part with the largest volume is selected as the reference part;

[0017] A2. Let i = 1;

[0018] A3. Select a path planning algorithm;

[0019] A4, Part pi The belief that is autonomously established in the assembly path planning process;

[0020] A5, Part p i The desire to autonomously generate during the assembly path planning process;

[0021] A6, in part p i If there is no interference with other parts in the assembly environment during the pose transformation process, proceed to step A7; otherwise, repeat step A5.

[0022] A7. If part p i The target pose, q, has been achieved through pose transformation. cur =q tar If yes, proceed to step A8; otherwise, repeat step A5.

[0023] A8, Part p i Autonomously realize the intent in the assembly path planning process;

[0024] A9. If i = i + 1, and i ≤ n - 1, repeat steps A5 to A8 to complete the autonomous assembly path planning for the remaining parts; otherwise, end the autonomous assembly path planning process.

[0025] Further, step A4 includes:

[0026] Part p i Extract information from its associated interaction feature pairs to determine its starting pose q during the assembly path planning process. ini Based on the matching of interaction feature pairs between parts, part p i Determine the part p to be assembled with. k Part p i From part p k Information is extracted from associated interactive feature pairs to determine the target pose q during the assembly path planning process. tar .

[0027] Further, step A5 includes:

[0028] Part p i By transforming the pose, a non-interference and feasible assembly path is found, and the pose q of the device in the current assembly environment is determined by the associated interactive feature pairs. cur .

[0029] Further, step A8 includes:

[0030] Part p i A non-interference, feasible assembly path τ will be generated using the selected path planning algorithm. i , and along τ iThe assembly is completed through a series of pose changes.

[0031] Another technical solution adopted in this invention is:

[0032] A device for modeling the cognitive behavior of multi-level geometric entities, comprising:

[0033] At least one processor;

[0034] At least one memory for storing at least one program;

[0035] When the at least one program is executed by the at least one processor, the at least one processor performs the method as described above.

[0036] Another technical solution adopted in this invention is:

[0037] A computer-readable storage medium storing a processor-executable program, which, when executed by a processor, performs the method described above.

[0038] The beneficial effects of this invention are: by establishing a multi-level geometric entity cognitive behavior model, this invention enhances the cognitive ability of parts, reduces the heavy human-computer interaction operations during assembly, and effectively improves the intelligence level of the assembly path planning process. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following description is provided with accompanying drawings of the relevant technical solutions in the embodiments of the present invention or the prior art. It should be understood that the accompanying drawings described below are only for the purpose of clearly illustrating some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0040] Figure 1 This is a flowchart of a method for multi-level geometric entity cognitive behavior modeling for autonomous assembly path planning in an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of a multi-level geometric entity cognitive behavior model in an embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of the structure of the rubber wheel and knurled aluminum column in an embodiment of the present invention;

[0043] Figure 4 This is a flowchart illustrating the autonomous assembly path planning of parts in an embodiment of the present invention.

[0044] Figure 3Chinese figure reference numerals: 1-Rubber wheel; 2-Knurled aluminum cylinder; 3-Flat surface of rubber wheel B-IFP1; 4-Cylinder surface of rubber wheel B-IFP2; 5-Flat surface of knurled aluminum cylinder B-IFP3; 6-Cylinder surface of knurled aluminum cylinder B-IFP4. Detailed Implementation

[0045] The embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0046] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., are based on the orientation or positional relationship shown in the accompanying drawings. 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.

[0047] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing 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.

[0048] Furthermore, in the description of this invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0049] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0050] To address the aforementioned issues, this invention proposes the concept of Interactive Feature Pairs (IFPs) to describe and capture the interactive intentions in the designer's mind, and to endow parts with the ability to autonomously recognize their matching parts. Furthermore, research has found that endowing parts with cognitive abilities is consistent with research on cognitive behavior in cognitive science. However, how to model the cognitive behavior of parts during assembly path planning has not been extensively studied, which has prevented the complete realization of autonomous assembly path planning.

[0051] like Figure 1 As shown, this embodiment provides a method for multi-level geometric entity cognitive behavior modeling for autonomous assembly path planning, including the following steps:

[0052] Step 1: In the part modeling stage, associate interaction feature pairs and establish a multi-level geometric entity belief-wish-intention cognitive behavior model based on the interaction feature pairs, explicitly representing the interaction intentions captured and transmitted by the interaction feature pairs. Among them, the multi-level geometric entities include basic interaction feature pairs (B-IFP), composite interaction feature pairs (C-IFP), and parts.

[0053] When a part is loaded into the assembly environment, it extracts information from interaction feature pairs, forming beliefs that include its own beliefs and its beliefs about the environment. The information in the interaction feature pairs includes all planes and cylinders on the part associated with these interaction feature pairs. The normals of these planes and the axes of the cylinders interact to form a relative coordinate system representing the part's current pose, specifically q = (x, y, z, α, β, γ), where (x, y, z) represents the position of the origin of this relative coordinate system in the world coordinate system, and (α, β, γ) represent the angles between the x, y, and z axes of this relative coordinate system and the x, y, and z axes of the world coordinate system, respectively. The part's belief about itself is its pose after being loaded into the assembly environment, i.e., the initial pose q for path planning. ini The assembly objects of the parts are determined by the matching between interactive feature pairs, which forms the part's belief in the environment, i.e., the target pose q of the path planning. tar The desires generated by a part include wanting to find a non-interference and feasible assembly path to complete the final assembly; the ultimate intention of a part is to output an assembly path that satisfies its own desires through the selected path planning algorithm.

[0054] See Figure 2 Among them, the belief of the basic interactive feature pair includes determining its own initial pose q. ini and target pose q tarThe features include planar or cylindrical surfaces, and constraint types include coaxial or mating constraints. The objective is to find a non-interference path between two matching basic interactive feature pairs to complete the assembly, similar to the objective of composite interactive feature pairs and parts. The intent is the path planning algorithm, which is the same as that of composite interactive feature pairs and parts. The belief of a composite interactive feature pair is the set of beliefs of all its constituent basic interactive feature pairs, such as the q of all basic interactive feature pairs. ini The combined action yielded the q of the composite interactive feature pairs. ini The beliefs of a part are derived from the complex interactive features associated with it; for example, a part in an assembly environment can know how many other parts can cooperate with it.

[0055] Step 2: Parts with cognitive abilities autonomously implement the assembly path planning process.

[0056] In one embodiment of the present invention, a rubber wheel and a knurled aluminum column are used for assembly, such as... Figure 3 As shown, where Figure 3 (a) is a schematic diagram of the rubber wheel. Figure 3 (b) is a structural schematic diagram of the knurled aluminum column. See also Figure 4 , Figure 4 This demonstrates the specific steps involved in autonomous assembly path planning:

[0057] Step 2.1. Load the parts set P{knurled aluminum cylinder p1, rubber wheel p2}, the total number of parts n=2, and select rubber wheel p2 as the reference part;

[0058] Step 2.2. Set i = 1;

[0059] Step 2.3. Select a suitable path planning algorithm;

[0060] Step 2.4. Part p i A belief that is autonomously established in the assembly path planning process. Part p i Extract information from its associated interaction feature pairs to determine its starting pose q during the assembly path planning process. ini Based on the matching of interaction feature pairs between parts, part p i The part p to be assembled with can be determined. k Part p i From part p k Information is extracted from associated interactive feature pairs to determine the target pose q during the assembly path planning process. tar B-IFP3 and B-IFP4 of the knurled aluminum column form its initial pose, while B-IFP1 and B-IFP2 of the rubber wheel form the target pose of the knurled aluminum column.

[0061] Step 2.5. Part p i The desire to autonomously generate during the assembly path planning process. Part p i The system attempts to find a non-interference and feasible assembly path through pose transformation, and determines its pose q in the current assembly environment through associated interactive feature pairs. cur ;

[0062] Step 2.6. In part p i During the pose transformation, if there is no interference with other parts in the assembly environment, proceed to step 2.7; otherwise, repeat step 2.5.

[0063] Step 2.7. If part p i The target pose, q, has been achieved through pose transformation. cur =q tar If yes, proceed to step 2.8; otherwise, repeat step 2.5.

[0064] Step 2.8. Part p i Autonomously realize the intent during the assembly path planning process. Part p i A non-interference, feasible assembly path τ will be generated using the selected path planning algorithm. i , and along τ i Assembly is completed after a series of pose changes;

[0065] Step 2.9. i = i + 1. If i ≤ n - 1, repeat steps 2.5 to 2.8 to complete the autonomous assembly path planning for the remaining parts; otherwise, end the autonomous assembly path planning process.

[0066] Once all parts have achieved their intended purpose, they are assembled according to the non-interference and feasible assembly path they generate. This reduces cumbersome human-machine interaction operations, shortens the assembly cycle, and fully realizes autonomous assembly path planning for parts.

[0067] This embodiment also provides an apparatus for multi-level geometric entity cognitive behavior modeling, including:

[0068] At least one processor;

[0069] At least one memory for storing at least one program;

[0070] When the at least one program is executed by the at least one processor, the at least one processor performs the following: Figure 1 The method shown.

[0071] This embodiment of the apparatus for multi-level geometric entity cognitive behavior modeling can execute the method for multi-level geometric entity cognitive behavior modeling provided in the method embodiment of the present invention, and can execute any combination of implementation steps of the method embodiment, and has the corresponding functions and beneficial effects of the method.

[0072] This application also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform... Figure 1 The method shown.

[0073] This embodiment also provides a storage medium storing instructions or programs that can execute the method for multi-level geometric entity cognitive behavior modeling provided in the method embodiment of the present invention. When the instructions or programs are run, any combination of implementation steps of the method embodiment can be executed, and the method has the corresponding functions and beneficial effects.

[0074] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and sub-operations described as part of a larger operation are executed independently.

[0075] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the described functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0076] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0077] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0078] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0079] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0080] In the foregoing description of this specification, references to terms such as "one embodiment," "another embodiment," or "some embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0081] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0082] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A method for modeling the cognitive behavior of multi-level geometric entities, characterized in that, Includes the following steps: In the part modeling stage, associated interaction feature pairs are used to establish a belief-desire-intention cognitive behavior model of multi-level geometric entities based on the interaction feature pairs; among them, multi-level geometric entities include basic interaction feature pairs, composite interaction feature pairs and parts; Based on the constructed belief-desire-intention cognitive-behavioral model, the parts autonomously realize the assembly path planning process; The process of associating interactive feature pairs during the part modeling stage and establishing a multi-level cognitive behavior model of geometric entities based on these interactive feature pairs includes: The part is loaded into the assembly environment, and the part determines its starting pose in the assembly path planning process based on the associated interaction features. q ini Establish self-belief; determine the target pose of itself in the assembly path planning process by matching with parts of other related interactive feature pairs. q tar Build a belief in the environment; Based on established beliefs, the desired outcomes of the component include: finding a path that can be transformed from the initial pose through a series of pose changes. q ini Reach the target pose q tar The desire for a non-interference and feasible assembly path; The intention of the parts includes: to realize their own desires through assembly path planning algorithms; The basic interactive feature pairs' beliefs include determining their own initial pose. q ini and target pose q tar The desire of a basic interaction feature pair is to find an interference-free path between two matching basic interaction feature pairs to complete the assembly; the intention of the basic interaction feature pair is a path planning algorithm. The belief of a composite interaction feature pair is the set of beliefs of all the basic interaction feature pairs it contains; the intention of a composite interaction feature pair is similar to the desire of a basic interaction feature pair; the intention of a composite interaction feature pair is the same as the intention of a basic interaction feature pair. The information in the interactive feature pairs includes all planes and cylinders on the part associated with the interactive feature pairs. The normals of these planes and the axes of the cylinders together form a relative coordinate system, representing the current pose of the part; wherein, the pose is represented as... q = ( x , y , z , α , β , γ ), ( x , y , z This indicates the position of the origin of the relative coordinate system in the world coordinate system. α , β , γ ) represents the relative coordinate system x axis, y shaft and z Axis and world coordinate system x axis, y shaft and z The included angle of the axis; The process of autonomously planning the assembly path for the part includes: A1. Load Part Set P { p 1, p 2,…, p n }, n Given the total number of parts; select the part with the largest volume as the reference part; A2, take i = 1; A3. Select a path planning algorithm; A4, Parts p i The belief that is autonomously established in the assembly path planning process; A5, Parts p i The desire to autonomously generate during the assembly path planning process; A6. In parts p i If there is no interference with other parts in the assembly environment during the pose transformation process, proceed to step A7; otherwise, repeat step A5. A7. If the part p i The target pose has been achieved through pose transformation, i.e. q cur =q tar If yes, proceed to step A8; otherwise, repeat step A5. A8, Parts p i Autonomously realize the intent in the assembly path planning process; A9 i = i +1, if i ≤ n -1. Repeat steps A5 to A8 to complete the autonomous assembly path planning for the remaining parts; otherwise, end the autonomous assembly path planning process.

2. The method for modeling the cognitive behavior of multi-level geometric entities according to claim 1, characterized in that, Step A4 includes: Component p i Extract information from its associated interaction feature pairs to determine its starting pose during the assembly path planning process. q ini Based on the matching of interaction feature pairs between parts, the parts p i Determine the parts to be assembled with p k ,Component p i From parts p k Information is extracted from associated interactive feature pairs to determine the target pose during the assembly path planning process. q tar .

3. The method for modeling the cognitive behavior of multi-level geometric entities according to claim 1, characterized in that, Step A5 includes: Component p i By transforming the pose, a non-interference and feasible assembly path is found, and the pose of the device in the current assembly environment is determined by the associated interactive feature pairs. q cur .

4. The method for modeling the cognitive behavior of multi-level geometric entities according to claim 1, characterized in that, Step A8 includes: Component p i A non-interference, feasible assembly path will be generated using the selected path planning algorithm. τ i and along τ i The assembly is completed through a series of pose changes.

5. A device for modeling the cognitive behavior of multi-level geometric entities, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method of any one of claims 1-4.

6. A computer-readable storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to perform the method as described in any one of claims 1-4.

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