Object model file generation method and device

Abstract

The embodiment of the invention provides an object model file generation method and device, and the method comprises the steps: obtaining an initial model file of a to-be-generated object, and determining an initial specification parameter of the to-be-generated object based on the initial model file; a task processing instruction in at least one test scene is received, and the task processing instruction carries task information and scene limitation information; executing a task processing instruction according to the task information, the initial specification parameter and the scene limitation information; under the condition that the task processing instruction in any test scene fails to be executed, the initial model file is adjusted based on the target scene limiting information and the initial specification parameters, a target model file of the to-be-generated object is obtained, and the target model file is used for manufacturing the to-be-generated object in a real scene. By executing the task processing instruction, the processing operation for the to-be-generated object can be simulated in the virtual test scene, and the to-be-generated object does not need to be manufactured, so that the generation efficiency of the target model file is improved.

Description

Technical Field

[0001] This specification relates to the field of computer technology, and in particular to a method and apparatus for generating object model files. Background Technology

[0002] In industrial production, raw materials are often purchased from different suppliers. To improve the efficiency of raw material transportation and storage and to avoid damage during transportation, companies typically manufacture containers to hold the raw materials, thereby enabling bulk transportation and management of the materials.

[0003] Currently, the process often involves first creating container blueprints based on business requirements, then manufacturing actual containers based on those blueprints, and finally testing them in real-world business scenarios. If the manufactured containers do not meet business requirements, the blueprints need to be updated, and new containers need to be manufactured. This cycle continues until the manufactured containers meet the business requirements. Taking the automotive industry as an example, a car involves thousands of parts, and the container for each part requires separate design, planning, and iterative updates, which is extremely time-consuming and costly, resulting in very low container manufacturing efficiency. Summary of the Invention

[0004] In view of this, embodiments of this specification provide a method for generating object model files. One or more embodiments of this specification also relate to an apparatus for generating object model files, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0005] According to a first aspect of the embodiments of this specification, a method for generating a model file of an object is provided, comprising:

[0006] Obtain the initial model file of the object to be generated, and determine the initial specification parameters of the object to be generated based on the initial model file;

[0007] Receive at least one task processing instruction in a test scenario, wherein the task processing instruction carries task information and scenario limitation information;

[0008] Execute task processing instructions based on task information, initial specification parameters, and scenario limitation information;

[0009] If the task processing instruction fails to execute in any test scenario, the initial model file is adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. The target model file is used to manufacture the object to be generated in the real scenario.

[0010] According to a second aspect of the embodiments of this specification, an apparatus for generating model files of objects is provided, comprising:

[0011] The acquisition module is configured to acquire the initial model file of the object to be generated and determine the initial specification parameters of the object to be generated based on the initial model file.

[0012] The receiving module is configured to receive task processing instructions in at least one test scenario, wherein the task processing instructions carry task information and scenario limitation information;

[0013] The execution module is configured to execute task processing instructions based on task information, initial specification parameters, and scenario constraint information;

[0014] The adjustment module is configured to adjust the initial model file based on the target scene constraint information and initial specification parameters in the event that the task processing instruction fails to execute in any test scenario, thereby obtaining the target model file of the object to be generated. The target model file is used to manufacture the object to be generated in the real scene.

[0015] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising:

[0016] Memory and processor;

[0017] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the model file generation method for the above-mentioned object.

[0018] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the model file generation method for the object described above.

[0019] According to a fifth aspect of the embodiments of this specification, a computer program product is provided, including a computer program / instructions that, when executed by a processor, implement the steps of the model file generation method for the object described above.

[0020] One embodiment of this specification implements obtaining an initial model file of an object to be generated, determining initial specification parameters of the object to be generated based on the initial model file; receiving a task processing instruction in at least one test scenario, wherein the task processing instruction carries task information and scenario constraint information; executing the task processing instruction according to the task information, initial specification parameters, and scenario constraint information; and adjusting the initial model file based on the target scenario constraint information and initial specification parameters to obtain a target model file of the object to be generated, wherein the target model file is used to manufacture the object to be generated in a real scenario.

[0021] Thus, by determining the initial specification parameters of the object to be generated, and upon receiving task processing instructions in at least one test scenario, the task processing instructions are executed based on task information, initial specification parameters, and scenario constraint information. This allows for the simulation of processing operations on the object to be generated within a virtual test scenario, based on task information, initial specification parameters, and scenario constraint information. Consequently, testing whether the object meets the business requirements of each scenario can be completed without manufacturing a physical copy of the object during the testing process, simplifying the object manufacturing process and reducing testing costs. Furthermore, if the task processing instructions in any test scenario fail to execute, the initial model file is adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. This improves the efficiency of initial model file adjustment, thereby increasing the efficiency of generating the target model file of the object, and ultimately improving the manufacturing efficiency of objects that meet the business requirements of each scenario. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a method for generating an object model file, as provided in one embodiment of this specification.

[0023] Figure 2 This is a flowchart illustrating the process of generating an object model file according to one embodiment of this specification.

[0024] Figure 3 This is a flowchart illustrating the process of generating a model file for another object, as provided in one embodiment of this specification.

[0025] Figure 4 This is a flowchart illustrating the process of another object model file generation method provided in one embodiment of this specification;

[0026] Figure 5 This is a schematic diagram of the structure of an object model file generation device provided in one embodiment of this specification;

[0027] Figure 6 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0028] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0029] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0030] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0031] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0032] In one or more embodiments of this specification, a large model refers to a deep learning model with a large number of model parameters, typically containing hundreds of millions, tens of billions, hundreds of billions, trillions, or even tens of trillions of model parameters. A large model can also be called a foundational model. It is pre-trained using large-scale unlabeled corpora to produce a pre-trained model with hundreds of millions of parameters. Such models can adapt to a wide range of downstream tasks and have good generalization ability. Examples include Large Language Models (LLMs) and multi-modal pre-training models.

[0033] In practical applications, large models only require a small number of samples to fine-tune the pre-trained model before they can be applied to different tasks. Large models can be widely used in fields such as Natural Language Processing (NLP) and Computer Vision. Specifically, they can be applied to computer vision tasks such as Visual Question Answering (VQA), Image Captioning (IC), and Image Generation, as well as NLP tasks such as text-based sentiment classification, text summarization, and machine translation. The main application scenarios for large models include digital assistants, intelligent robots, search, online education, office software, e-commerce, and intelligent design.

[0034] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0035] Containers: In the automotive industry, containers are used to carry automotive parts, thereby protecting them from damage during transportation.

[0036] Loading unit: The smallest transport unit in the parts transportation process. It is obtained by combining multiple containers and can improve the safety and efficiency of parts transportation.

[0037] Unreal Engine (Unreal Engine) is a virtual game engine with many advantages, including powerful graphics rendering capabilities, a flexible scripting language and blueprint system, rich community support and resources, cross-platform support, and powerful virtual reality (VR) support. It is widely used in the field of game development.

[0038] In industrial production, raw materials are often purchased from different suppliers. To improve the efficiency of raw material transportation and storage and to avoid damage during transportation, companies typically manufacture containers to hold the raw materials, thereby enabling bulk transportation and management of the materials.

[0039] Currently, the process often involves first creating container blueprints based on business requirements, then manufacturing actual containers based on those blueprints, and finally testing them in real-world business scenarios. If the manufactured containers do not meet business requirements, the blueprints need to be updated, and new containers need to be manufactured. This cycle continues until the manufactured containers meet the business requirements. Taking the automotive industry as an example, a car involves thousands of parts, and the container for each part requires separate design, planning, and iterative updates, which is extremely time-consuming and costly, resulting in very low container manufacturing efficiency.

[0040] Based on this, one embodiment of this specification provides a method for generating a model file of an object, which involves obtaining an initial model file of the object to be generated, determining initial specification parameters of the object to be generated based on the initial model file, receiving a task processing instruction in at least one test scenario, wherein the task processing instruction carries task information and scenario restriction information, executing the task processing instruction according to the task information, initial specification parameters, and scenario restriction information, and, in the event that the task processing instruction in any test scenario fails to execute, adjusting the initial model file based on the target scenario restriction information and initial specification parameters to obtain a target model file of the object to be generated, wherein the target model file is used to manufacture the object to be generated in a real scenario.

[0041] Thus, by determining the initial specification parameters of the object to be generated, and upon receiving task processing instructions in at least one test scenario, the task processing instructions are executed based on task information, initial specification parameters, and scenario constraint information. This allows for the simulation of processing operations on the object to be generated within a virtual test scenario, based on task information, initial specification parameters, and scenario constraint information. Consequently, testing whether the object meets the business requirements of each scenario can be completed without manufacturing a physical copy of the object during the testing process, simplifying the object manufacturing process and reducing testing costs. Furthermore, if the task processing instructions in any test scenario fail to execute, the initial model file is adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. This improves the efficiency of initial model file adjustment, thereby increasing the efficiency of generating the target model file of the object, and ultimately improving the manufacturing efficiency of objects that meet the business requirements of each scenario.

[0042] This specification provides a method for generating object model files. It also relates to an object model file generation apparatus, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail in the following embodiments.

[0043] See Figure 1 , Figure 1 A flowchart of a method for generating a model file of an object according to an embodiment of this specification is shown, which specifically includes the following steps.

[0044] Step 102: Obtain the initial model file of the object to be generated, and determine the initial specification parameters of the object to be generated based on the initial model file.

[0045] According to an optional embodiment of this specification, an initial model file of the object to be generated can be obtained, and the initial specification parameters of the object to be generated can be determined based on the initial model file.

[0046] Specifically, the object to be generated can be understood as an object in a real-world scene that needs to be manufactured, which can be used to load items, including containers, shipping containers, bins, etc. The initial model file can be understood as a 3D modeling file of the object to be generated, used for 3D modeling of the object in a virtual scene, or for manufacturing the object in a real-world scene. The initial model file can include the specification parameters of the object to be generated, which can include the object's geometry, material properties, surface treatment information, dimensions, view information, weight information, etc.

[0047] According to another optional embodiment of this specification, an initial model file of the object to be generated can also be obtained, and a three-dimensional model component of the object to be generated can be obtained by rendering in a virtual scene based on the initial model file, and the initial specification parameters of the object to be generated can be determined.

[0048] In practice, developers can perform secondary development based on virtual engines such as Unreal and Unity to obtain editors for editing model files and displayers for performing simulation operations and showing simulation operation animations.

[0049] Business users, such as designers and other technical personnel of the object to be generated, can edit the components of the object using the editor to obtain the initial model file of the object. Furthermore, business users can retrieve the pre-edited initial model file of the object in the display window by identifying it. The display window can then render the 3D model of the object in a virtual scene based on the initial model file and determine the initial specifications of the object based on the initial model file.

[0050] According to an optional embodiment of this specification, obtaining the initial model file of the object to be generated may include the following steps:

[0051] Obtain the object drawing file of the object to be generated;

[0052] Based on the object drawing file and the operation information performed on the object to be generated, an initial model file for the object to be generated is generated.

[0053] Specifically, the object drawing file can be understood as a Cat.ia file, which is a 3D design drawing file pre-drawn by designers based on the requirements of various business scenarios for the objects to be generated. The operation information performed on the objects to be generated can be different in different business scenarios. For example, in a loading scenario, the operation information may include the object activity information of the objects to be generated, as well as the action information of placing the target loading object into the objects to be generated, etc.; in a warehousing scenario, the operation information may include the action information of stacking different objects to be generated, as well as the action information of using handling objects to move the objects to be generated, etc.

[0054] In practical applications, we can obtain the Cat ia file that has been pre-drawn for the object to be generated, and then, based on the functions of the virtual engine, add the above operation information to the components of the object to be generated to obtain the initial model file of the object to be generated.

[0055] It should be noted that in the editor, for each different object to be generated, the method provided in this embodiment can be used to generate a separate initial model file for that object.

[0056] Furthermore, in the display, the initial model file of the object to be generated can be obtained by inputting information such as the object identifier or object code of the object to be generated.

[0057] By applying this embodiment, the object drawing file of the object to be generated is obtained; based on the object drawing file and the operation information performed on the object to be generated, the initial model file of the object to be generated is generated. This can add operation information to the component of the object to be generated so that the component of the object to be generated can support the simulation of various types of operations in real business scenarios in the display, which is convenient for business personnel to test the object to be generated in a virtual test scenario and helps to improve the testing efficiency of the object to be generated.

[0058] Step 104: Receive at least one task processing instruction in a test scenario, wherein the task processing instruction carries task information and scenario restriction information.

[0059] According to an optional embodiment of this specification, at least one task processing instruction in a test scenario can be received, the object to be generated can be determined based on the task information, and the initial model file of the object to be generated can be obtained.

[0060] According to another optional embodiment of this specification, based on the initial model file of the object to be generated, at least one task processing instruction under a test scenario can be triggered based on the object to be generated.

[0061] Specifically, a test scenario can be understood as a virtual scenario obtained by simulating and modeling scenario information from a real business scenario. Task processing instructions can be used to trigger corresponding processing operations on the object to be generated within the test scenario. These processing operations simulate the operations performed on the object to be generated in a real business scenario. Task processing instructions can include task information and scenario constraint information. The task information and scenario constraint information can differ for different test scenarios. Task information can include the processing operations to be performed on the object to be generated. Scenario constraint information can be used to specify the standard operating parameters for the processing operations.

[0062] Taking the automotive industry as an example, in practical applications, the business scenarios corresponding to the objects to be generated can mainly include the following three types: loading scenarios, warehousing scenarios, and transportation scenarios. The loading scenario can be understood as placing the target loading object into the object to be generated. Task information in the loading scenario can include: loading the target loading object into the object to be generated; moving the object to be generated manually or mechanically, etc. The warehousing scenario can be understood as stacking the objects to be generated to store, move, or organize the objects to be generated and the target loading objects loaded within them. Task information in the warehousing scenario can include: stacking multiple objects to be generated to obtain a target loading unit; stacking multiple objects to be generated to obtain a target loading unit and using a target handling object to move the target loading unit; stacking multiple objects to be generated and placing them in a preset warehousing area; using a target handling object to move the objects to be generated, etc. The transportation scenario can be understood as placing multiple objects of the same or different types into a target transportation object. Task information in the transportation scenario can include: placing multiple objects to be generated within the target transportation object; moving the objects to be generated manually or mechanically, etc. Correspondingly, the scenario constraints corresponding to different task information can also be different.

[0063] Step 106: Execute task processing instructions based on task information, initial specification parameters, and scene limitation information.

[0064] In practical applications, task processing instructions can be executed based on task information, initial specification parameters, and scene constraints. Furthermore, task processing instructions can be executed using a display device, and the corresponding task execution animation can be displayed on the device.

[0065] For example, in a loading scenario, the process of placing the target loading object into the object to be generated can be performed based on task information, initial specification parameters, and scenario limitation information, and the corresponding loading animation can be displayed; in a warehousing scenario, the process of picking up the loading unit with a forklift can be performed based on task information, initial specification parameters, and scenario limitation information, and the corresponding picking and handling animation can be displayed; in a transportation scenario, the process of placing multiple objects to be generated in the truck bed can be performed based on task information, initial specification parameters, and scenario limitation information, and the animation of placing each object to be generated can be displayed.

[0066] By displaying task execution animations, business personnel can easily understand the task execution process visually. They can also perform customized processing operations through interactive controls in the display interface, which helps to improve the flexibility and convenience of the testing process.

[0067] According to an optional embodiment of this specification, the test scenario may include a loading scenario; accordingly, the task information may include: loading the target loading object into the object to be generated, wherein the target loading object is the object loaded inside the object to be generated; the scenario constraint information may include: the first specification parameters of the target loading object.

[0068] Based on the task information, initial specification parameters, and scene constraints, execute task processing instructions, including:

[0069] Based on the first specification parameters and the initial specification parameters, perform the processing operation of loading the target loading object into the object to be generated.

[0070] In practical applications, the initial model file of the object to be generated can be found in the display by searching for the object identifier of the object to be generated, and the activities of the object to be generated and the situation of putting the target loading object into the object to be generated can be simulated through the operation of business users.

[0071] Optionally, the processing operation of loading the target loading object into the object to be generated can be performed based on the first specification parameters and the initial specification parameters.

[0072] In actual implementation, when a task processing instruction is triggered, the system can automatically detect the compatibility between the first specification parameter and the initial specification parameter, thereby determining whether the loading operation can be successfully executed and generating a task execution result indicating success or failure. In the case of execution failure, the system can also generate prompt information for incompatible parameters, such as the specification parameters of the object to be generated not matching the first specification parameter.

[0073] Alternatively, manual handling of the object to be generated can be performed based on the first specification parameters and the initial specification parameters.

[0074] In practical implementation, ergonomic parameters can be considered. Based on the initial specification parameters, AI algorithms can be used to calculate ergonomic parameters such as range of motion, visual fatigue, physical load, and comfort when manually handling the object to be generated. This allows for testing to determine whether the design of the object meets the needs of human work.

[0075] For example, if a container can hold more than five parts, it may exceed the weight limit that a human can bear during manual handling. Therefore, based on test results, the container design can be modified to ensure that the number of parts a container can hold does not exceed five. Alternatively, if the length and width of a container exceed a preset threshold, it may exceed the range of human reach, making it difficult to move large containers manually. Therefore, based on test results, the container design can be modified to reduce the length and width of the container.

[0076] Optionally, the target transport object can be transported to the object to be generated based on the first specification parameters and the initial specification parameters.

[0077] In practice, besides manually moving the objects to be generated, they can also be moved based on a target moving object. The target moving object can include AGVs, AMRs, forklifts, etc.

[0078] Furthermore, after executing the task processing instructions based on task information, initial specification parameters, and scenario constraint information, it may also include:

[0079] If the task processing result is that the first specification parameter does not meet the first preset matching condition with the initial specification parameter, it is determined that the task processing instruction in the loading scenario has failed to execute.

[0080] By applying this embodiment, the process of loading the target loading object into the object to be generated is performed according to the first specification parameters and the initial specification parameters. This process can be simulated in a virtual scene, and the test results of the simulation operation can be obtained. If the operation fails, prompt information can be automatically generated, which makes it easier for designers to change the specification parameters of the object to be generated or other objects in the scene, and helps to improve the optimization efficiency of the model file of the object to be generated.

[0081] According to another optional embodiment of this specification, the test scenario may include a warehousing scenario; accordingly, the task information may include: stacking multiple objects to be generated to obtain a target loading unit, and using a target transport object to transport the target loading unit; the scenario constraint information may include: the second specification parameters of the target loading unit, and the transport parameters of the target transport object;

[0082] Based on the task information, initial specification parameters, and scene constraints, execute task processing instructions, including:

[0083] Based on the second specification parameters, the transport parameters, and the initial specification parameters, the process of stacking multiple objects to be generated to obtain the target loading unit and transporting the target loading unit using the target transport object is executed.

[0084] In practical applications, the initial model file of the object to be generated can be found in the display by searching for the object identifier of the object to be generated. Then, through the operation of business users, the stacking of multiple objects to be generated and the operation of moving the objects to be generated can be simulated.

[0085] Specifically, multiple objects to be generated can be stacked to form a target loading unit. For example, two objects of the same type can be stacked vertically to form a target loading unit. Alternatively, depending on the needs of the application, a preset number of objects of the same type or different types can be stacked to obtain a target loading unit.

[0086] In practical applications, a single object to be generated can be moved through the target moving object, or the target loading unit can be moved through the target moving object.

[0087] Specifically, the second specification parameters may include information such as the quantity, type, volume, weight, and parts of the objects to be generated that make up the target loading unit; the handling parameters may include the load-bearing information of the AGV, the width of the fork spacing of the forklift, and so on.

[0088] Furthermore, after executing the task processing instructions based on task information, initial specification parameters, and scenario constraint information, it may also include:

[0089] If the loading unit specifications obtained based on the initial specification parameters do not conform to the second specification parameters, or if the loading unit specifications and handling parameters do not conform to the second preset matching condition, the task processing instruction in the warehousing scenario is determined to have failed to execute.

[0090] Specifically, situations that do not meet the second preset matching conditions may include: the number of objects to be generated in the target loading unit does not match the number of objects to be generated that the target handling equipment can handle; the height of the target loading unit does not match the height of the objects that the target handling equipment can handle; the width of the target loading unit does not match the fork spacing of the target handling equipment, etc.

[0091] By applying this embodiment, by simulating the stacking of multiple objects to be generated and simulating the handling operation of the target handling equipment on the objects to be generated, it is possible to determine whether the objects to be generated meet the business requirements in the warehousing scenario, and to generate corresponding prompt information in the event of execution failure, thereby improving the optimization efficiency of the initial model file.

[0092] According to another optional embodiment of this specification, the test scenario may include a transportation scenario; accordingly, the task information may include: placing multiple objects to be generated in a target transportation object, wherein the target transportation object is used to transport multiple objects to be generated; the scenario constraint information may include: object attribute information corresponding to the target transportation object.

[0093] Based on task information, initial specification parameters, and scene constraint information, execute task processing instructions, which may include:

[0094] Based on the initial specification parameters and object attribute information, perform a process to place multiple objects to be generated within the target transport object, and obtain at least one placement result.

[0095] In practical applications, the editor can reuse the initial model file pre-generated for the object to be generated. In the display, business users can search for multiple objects of the same or different types to be generated and place each object to be generated within the target transportation object in the virtual scene.

[0096] Specifically, the target transport object can include equipment capable of transporting the objects to be generated, such as trucks, trains, and aircraft cargo holds. Object attribute information can include the dimensions and capacity of the transport space of the target transport object, as well as information such as the transport type and speed. This object attribute information can be used to limit the type and quantity of objects to be generated transported by the target transport object.

[0097] In practical applications, the object attribute information of the target transportation object to be simulated can be determined, and based on the object attribute information, at least one object to be generated can be placed in the target transportation object.

[0098] Specifically, the objects to be generated can include one or more types, and the initial specifications of different types of objects can be different. The number of each type of object to be generated placed in the target transportation object can be determined according to actual needs. For example, they can be added or deleted during the simulation based on the real-time simulation results.

[0099] Taking a truck as the target transport object as an example, in practical applications, when the box model of the target truck is selected, multiple different containers can be added to the box model according to the requirements, and different container placement methods can be tried to simulate the placement results corresponding to different placement methods.

[0100] By applying this embodiment, by performing a process operation of placing multiple objects to be generated in a target transport object according to the initial specification parameters and object attribute information, at least one placement result of the objects to be generated in the target transport object can be obtained, thereby simulating the placement method of the objects to be generated, which is convenient for staff to view.

[0101] In one or more embodiments of this specification, the arrangement of objects to be generated may include the type of objects to be generated, the quantity of each type of object to be generated, and the arrangement rules of each object to be generated in the target transport object.

[0102] Optionally, the placement of the objects to be generated can be customized and simulated by staff in a virtual scene; or it can be calculated based on AI algorithms. The AI ​​algorithm can calculate the placement of the objects to be generated within the target transport object based on the object attribute information of the target transport object and the initial specification parameters of each object to be generated.

[0103] For example, for containers 1, 2, 3 and truck body model A, there can be a variety of placement methods, one of which is: placing N containers 1 in area a inside truck A; placing M containers 2 in area b inside truck A; and placing L containers 3 on top of containers 1 by stacking.

[0104] Specifically, AI algorithms can be understood as a type of layout algorithm. Layout algorithms can be used to calculate and obtain a more suitable placement method for various target transportation objects, that is, a better placement method.

[0105] Furthermore, based on the initial specification parameters and object attribute information, after performing a process of placing multiple objects to be generated within the target transport object to obtain at least one placement result, it may further include:

[0106] Determine the object layout information corresponding to at least one placement result in the target transport object;

[0107] Based on the object layout information, the target placement result is obtained by filtering from at least one placement result, and the target placement rule corresponding to the target placement result is obtained.

[0108] In practical applications, based on the placement operations performed by business users on the objects to be generated, it can be determined whether the layout result after the placement operation conforms to the object attribute information. If it does not conform, an execution failure prompt message can be automatically generated, along with the reason for the execution failure.

[0109] For example, if the length or width of the object to be generated placed by the user exceeds the length or width of the target transport object's transport compartment, the execution will fail, and a prompt message describing that the length and width information does not match the object's attribute information will be automatically generated; if the user does not fill the target transport object's transport compartment as much as possible, a prompt message can also be generated to remind the user to continue placing objects to improve transport efficiency.

[0110] It should be noted that when placing objects to be generated, users can do so either based on individual objects or based on the target loading unit, depending on the specific needs of the application.

[0111] Specifically, object layout information can be understood as the arrangement of the objects to be generated within the target transport object after they have been placed according to a set arrangement. Object layout information can include the placement position of the objects to be generated, the quantity of objects to be generated, and the remaining space in the target transport object. Object layout information can be used to evaluate the quality of the placement result. The target placement result can be understood as the optimal container placement result. The target placement rule can be understood as the placement rule corresponding to the target placement result. The placement rule can indicate information such as the type, quantity, placement position, and placement method of the objects to be generated within the target transport object.

[0112] In practice, different container placement methods can be tried within a selected truck body model. Based on the simulated placement results, the optimal container placement rule can be selected from multiple methods. This allows for the determination of the most suitable container placement method for each truck in a container transportation scenario.

[0113] By applying this embodiment, the placement of the object to be generated in the target transportation object can be simulated, and the placement method of the object to be generated or whether the specification parameters of the object to be generated meet the business requirements of the transportation scenario can be automatically tested. This is beneficial to adjust the object to be generated or replace the target transportation object based on the test results, thereby improving the generation efficiency of the target model file of the object to be generated and thus improving the manufacturing efficiency of the object to be generated.

[0114] Step 108: If the task processing instruction fails to execute in any test scenario, adjust the initial model file based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. The target model file is used to manufacture the object to be generated in the real scenario.

[0115] In practical applications, if the task processing instruction fails to execute in any test scenario, the initial model file can be adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. The target model file is used to manufacture the object to be generated in the real scenario.

[0116] According to an optional embodiment of this specification, in the event that the task processing instruction fails to execute in any test scenario, the initial model file is adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated, which may include:

[0117] If a task processing instruction fails to execute in any test scenario, the target scenario limitation information is determined based on the test scenario corresponding to the failed task processing instruction.

[0118] Adjust the initial specification parameters based on the target scenario constraint information to obtain intermediate specification parameters;

[0119] Based on the task information, intermediate specification parameters, and scenario constraint information, execute the task processing instructions. If the task processing instructions are executed successfully in each test scenario, the intermediate specification parameters are determined as the target specification parameters of the object to be generated.

[0120] Adjust the initial model file based on the target specification parameters to obtain the target model file of the object to be generated.

[0121] Specifically, target scenario constraint information can be understood as the scenario constraint information under the test scenario corresponding to the failed task processing instruction. Target scenario constraint information can also be the scenario constraint information under other test scenarios besides the test scenario corresponding to the successfully executed task processing instruction.

[0122] In practical applications, initial specification parameters can be adjusted based on target scenario constraints to obtain intermediate specification parameters. Based on task information, intermediate specification parameters, and scenario constraints, task processing instructions can be executed to test whether the intermediate specification parameters meet the business requirements of any test scenario. If the task processing instructions in each test scenario are executed successfully, meaning the intermediate specification parameters of the object to be generated meet the business requirements of each scenario, these intermediate specification parameters can be determined as the target specification parameters of the object to be generated. Based on these target specification parameters, the initial model file can be adjusted to obtain the target model file of the object to be generated.

[0123] One embodiment of this specification implements obtaining an initial model file of an object to be generated, determining initial specification parameters of the object to be generated based on the initial model file; receiving a task processing instruction in at least one test scenario, wherein the task processing instruction carries task information and scenario constraint information; executing the task processing instruction according to the task information, initial specification parameters, and scenario constraint information; and adjusting the initial model file based on the target scenario constraint information and initial specification parameters to obtain a target model file of the object to be generated, wherein the target model file is used to manufacture the object to be generated in a real scenario.

[0124] Thus, by determining the initial specification parameters of the object to be generated, and upon receiving task processing instructions in at least one test scenario, the task processing instructions are executed based on task information, initial specification parameters, and scenario constraint information. This allows for the simulation of processing operations on the object to be generated within a virtual test scenario, based on task information, initial specification parameters, and scenario constraint information. Consequently, testing whether the object meets the business requirements of each scenario can be completed without manufacturing a physical copy of the object during the testing process, simplifying the object manufacturing process and reducing testing costs. Furthermore, if the task processing instructions in any test scenario fail to execute, the initial model file is adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. This improves the efficiency of initial model file adjustment, thereby increasing the efficiency of generating the target model file of the object, and ultimately improving the manufacturing efficiency of objects that meet the business requirements of each scenario.

[0125] The following is in conjunction with the appendix Figure 2 Taking the application of the object model file generation method provided in this specification in a loading scenario as an example, the object model file generation method will be further explained. Figure 2 The flowchart of a method for generating an object model file according to an embodiment of this specification is shown, which specifically includes the following steps.

[0126] Step 202: Import the Cat ia file of the container pre-drawn by the designer into the editor.

[0127] Step 204: Using the Unreal Engine, add active actions within the container component and add actions to put parts into the container.

[0128] Step 206: In the display, search for the corresponding container component by container code.

[0129] Step 208: Simulate the activities of the container components and the placement of parts into the container through user operation.

[0130] Step 210: Generate a prompt message if there is a conflict in the container component activity or if the part cannot be completely placed into the container.

[0131] In practical applications, business users can adjust the container's model file based on the prompts.

[0132] By applying this embodiment, a virtual scene is obtained by modeling the business scenario through a game engine, and container activities and the operation of putting parts into the container are simulated in the virtual scene. This allows the container to be tested in the virtual scene to see if it meets business requirements. In addition, ergonomic parameters can also be taken into account in the container design process. There is no need to manufacture physical containers based on drawings or test in real-world scenarios, which can reduce testing costs and improve container improvement and manufacturing efficiency.

[0133] The following is in conjunction with the appendix Figure 3 Taking the application of the object model file generation method provided in this specification in a warehousing scenario as an example, the method for generating the object model file will be further explained. Figure 3 The flowchart of another object model file generation method provided in one embodiment of this specification is shown, which specifically includes the following steps.

[0134] Step 302: Import the Cat ia file of the container pre-drawn by the designer into the editor.

[0135] Step 304: Using the Unreal Engine features, add stacking actions between containers within the container component, and add actions for moving containers with a forklift.

[0136] Step 306: In the display, the corresponding container component is found by searching for the container code.

[0137] Step 308: Simulate the stacking of different containers and the movement of containers by forklifts through user operation.

[0138] In practical applications, it can simulate the situation where multiple containers are stacked to form a loading unit; it can simulate the situation where forklifts of different sizes move containers; and it can also simulate the situation where forklifts move loading units based on containers.

[0139] Step 310: Generate a prompt message if containers cannot be stacked properly or if the fork gap width of the forklift does not match the container specifications.

[0140] By applying this embodiment, by simulating the stacking of containers and the handling of containers by forklifts in a virtual scene, it is possible to test the loading unit composed of containers and to test various business requirements in the warehousing scenario. Based on the test results, the container model file can be adjusted until it meets the business requirements. There is no need to manufacture physical containers based on drawings or to conduct tests in real scenarios, which can reduce the cost of the testing process and improve the efficiency of container improvement and manufacturing.

[0141] The following is in conjunction with the appendix Figure 4 Taking the application of the object model file generation method provided in this specification in a transportation scenario as an example, the method for generating the object model file will be further explained. Among other things, Figure 4 The flowchart of another object model file generation method provided in one embodiment of this specification is shown, which specifically includes the following steps.

[0142] Step 402: Reuse the container components that were pre-generated in the editor.

[0143] Step 404: In the display, select the target truck model and render the truck bed of the target truck.

[0144] In practical applications, the available truck models can include a variety of types.

[0145] Step 406: Search for multiple different types of container components through container coding, and simulate the placement of multiple different types of container components in the truck bed.

[0146] In practical applications, business personnel can place container components in the truck bed using methods such as clicking, dragging, and double-clicking, and test whether various placement methods meet business requirements. Additionally, based on the target truck bed specifications and the container specifications of the containers to be placed, a preset AI algorithm can be invoked to automatically generate the container placement results within the truck bed, and test whether the placement results meet business requirements.

[0147] Step 408: If the simulated placement does not meet business requirements, generate a prompt message.

[0148] By applying this embodiment, various business requirements in transportation scenarios can be tested by simulating the placement of different containers in a truck in a virtual scene. Based on the test results, the container model file can be adjusted until it meets the business requirements. This eliminates the need to manufacture physical containers based on drawings and to conduct tests in real-world scenarios, thereby reducing testing costs and improving container improvement and manufacturing efficiency.

[0149] Corresponding to the above method embodiments, this specification also provides embodiments of an object model file generation apparatus. Figure 5 A schematic diagram of an object model file generation apparatus according to one embodiment of this specification is shown. Figure 5 As shown, the device includes:

[0150] Acquisition module 502: configured to acquire the initial model file of the object to be generated, and determine the initial specification parameters of the object to be generated based on the initial model file.

[0151] Receiving module 504: configured to receive task processing instructions in at least one test scenario, wherein the task processing instructions carry task information and scenario restriction information.

[0152] Execution module 506 is configured to execute the task processing instructions based on the task information, the initial specification parameters, and the scene restriction information.

[0153] Adjustment module 508: configured to adjust the initial model file based on the target scene constraint information and the initial specification parameters in the event that the task processing instruction fails to execute in any test scenario, thereby obtaining the target model file of the object to be generated, wherein the target model file is used to manufacture the object to be generated in a real scene.

[0154] Optionally, the acquisition module 502 is further configured as follows:

[0155] Obtain the object drawing file of the object to be generated;

[0156] Based on the object drawing file and the operation information performed on the object to be generated, an initial model file for the object to be generated is generated.

[0157] Optionally, the test scenario includes a loading scenario; the task information includes: loading the target loading object into the object to be generated, wherein the target loading object is the object loaded inside the object to be generated; the scenario constraint information includes: the first specification parameters of the target loading object; the execution module 506 is further configured to:

[0158] Based on the first specification parameters and the initial specification parameters, perform the processing operation of loading the target loading object into the object to be generated.

[0159] Optionally, execution module 506 is further configured as follows:

[0160] If the task processing result is that the first specification parameter does not meet the first preset matching condition with the initial specification parameter, it is determined that the task processing instruction in the loading scenario has failed to execute.

[0161] Optionally, the test scenario includes a warehousing scenario; the task information includes: stacking multiple objects to be generated to obtain a target loading unit, and using a target transport object to transport the target loading unit; the scenario constraint information includes: the second specification parameters of the target loading unit, and the transport parameters of the target transport object; the execution module 506 is further configured as follows:

[0162] Based on the second specification parameters, the transport parameters, and the initial specification parameters, the process of stacking multiple objects to be generated to obtain the target loading unit and transporting the target loading unit using the target transport object is executed.

[0163] Optionally, execution module 506 is further configured as follows:

[0164] If the loading unit specifications obtained based on the initial specification parameters do not conform to the second specification parameters, or if the loading unit specifications and handling parameters do not conform to the second preset matching condition, the task processing instruction in the warehousing scenario is determined to have failed to execute.

[0165] Optionally, the test scenario includes a transportation scenario; the task information includes: placing multiple objects to be generated within a target transportation object, wherein the target transportation object is used to transport multiple objects to be generated; the scenario constraint information includes: object attribute information corresponding to the target transportation object; the execution module 506 is further configured to:

[0166] Based on the initial specification parameters and object attribute information, perform a process to place multiple objects to be generated within the target transport object, and obtain at least one placement result.

[0167] Optionally, execution module 506 is further configured as follows:

[0168] Determine the object layout information corresponding to at least one placement result in the target transport object;

[0169] Based on the object layout information, the target placement result is obtained by filtering from at least one placement result, and the target placement rule corresponding to the target placement result is obtained.

[0170] Optionally, adjustment module 508 is further configured as follows:

[0171] If a task processing instruction fails to execute in any test scenario, the target scenario limitation information is determined based on the test scenario corresponding to the failed task processing instruction.

[0172] Adjust the initial specification parameters based on the target scenario constraint information to obtain intermediate specification parameters;

[0173] Based on the task information, intermediate specification parameters, and scenario constraint information, execute the task processing instructions. If the task processing instructions are executed successfully in each test scenario, the intermediate specification parameters are determined as the target specification parameters of the object to be generated.

[0174] Adjust the initial model file based on the target specification parameters to obtain the target model file of the object to be generated.

[0175] By applying this embodiment, by determining the initial specification parameters of the object to be generated, and upon receiving task processing instructions in at least one test scenario, the task processing instructions are executed based on task information, initial specification parameters, and scenario constraint information. This allows for the simulation of processing operations on the object to be generated within a virtual test scenario, based on task information, initial specification parameters, and scenario constraint information. Therefore, testing whether the object meets the business requirements of each scenario can be completed without manufacturing a physical copy of the object during the testing process, simplifying the object manufacturing process and reducing testing costs. Furthermore, in the event of a task processing instruction failure in any test scenario, the initial model file is adjusted based on the target scenario constraint information and initial specification parameters to obtain the target model file of the object to be generated. This improves the efficiency of initial model file adjustment, thereby increasing the efficiency of generating the target model file of the object, and ultimately improving the manufacturing efficiency of objects that meet the business requirements of each scenario.

[0176] The above is a schematic scheme of an object model file generation apparatus according to this embodiment. It should be noted that the technical solution of this object model file generation apparatus and the technical solution of the object model file generation method described above belong to the same concept. For details not described in detail in the technical solution of the object model file generation apparatus, please refer to the description of the technical solution of the object model file generation method described above.

[0177] Figure 6 A structural block diagram of a computing device 600 according to one embodiment of this specification is shown. The components of the computing device 600 include, but are not limited to, a memory 610 and a processor 620. The processor 620 is connected to the memory 610 via a bus 630, and a database 650 is used to store data.

[0178] The computing device 600 also includes an access device 640, which enables the computing device 600 to communicate via one or more networks 660. Examples of such networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. Access device 640 may include one or more of any type of wired or wireless network interface (e.g., network interface card (NIC)), such as IEEE 802.11 Wireless Local Area Network (WLAN) interface, Wi-MAX (Worldwide Interoperability for Microwave Access) interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, Bluetooth interface, and Near Field Communication (NFC).

[0179] In one embodiment of this specification, the above-described components of the computing device 600 and Figure 6 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 6 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0180] The computing device 600 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 600 can also be a mobile or stationary server.

[0181] The processor 620 is configured to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the model file generation method for the aforementioned object.

[0182] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the above-described object model file generation method belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the above-described object model file generation method.

[0183] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the model file generation method for the above-described object.

[0184] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the object model file generation method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the object model file generation method described above.

[0185] An embodiment of this specification also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the model file generation method for the above-described object.

[0186] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the above-described object model file generation method belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the above-described object model file generation method.

[0187] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0188] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0189] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0190] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0191] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A model file generation method of an object, characterized by, The method comprises the following steps: acquiring an initial model file of an object to be generated, and determining initial specification parameters of the object to be generated based on the initial model file; receiving a task processing instruction in at least one test scenario, wherein the task processing instruction carries task information and scenario limitation information; executing the task processing instruction according to the task information, the initial specification parameters and the scenario limitation information; in the case that the execution of the task processing instruction in any test scenario fails, adjusting the initial model file based on target scenario limitation information and the initial specification parameters to obtain a target model file of the object to be generated, wherein the target model file is used to manufacture the object to be generated in a real scenario.

2. The method of claim 1, wherein, The acquiring of the initial model file of the object to be generated comprises: acquiring an object drawing file of the object to be generated; generating the initial model file of the object to be generated according to the object drawing file and operation information performed on the object to be generated.

3. The method of claim 1, wherein, The test scenario comprises a loading scenario; the task information comprises loading a target loading object into the object to be generated, wherein the target loading object is an object loaded in the object to be generated; and the scenario limitation information comprises first specification parameters of the target loading object. The execution of the task processing instruction according to the task information, the initial specification parameters and the scenario limitation information comprises: executing a processing operation of loading the target loading object into the object to be generated according to the first specification parameters and the initial specification parameters.

4. The method of claim 3, wherein, After the execution of the task processing instruction according to the task information, the initial specification parameters and the scenario limitation information, the method further comprises: in the case that the task processing result is that the first specification parameters do not meet a first preset matching condition with the initial specification parameters, determining that the execution of the task processing instruction in the loading scenario fails.

5. The method of claim 1, wherein, The test scenario comprises a storage scenario; the task information comprises stacking a plurality of objects to be generated to obtain a target loading unit, and using a target carrying object to carry the target loading unit; and the scenario limitation information comprises second specification parameters of the target loading unit and carrying parameters of the target carrying object. The execution of the task processing instruction according to the task information, the initial specification parameters and the scenario limitation information comprises: executing a processing operation of stacking a plurality of objects to be generated to obtain a target loading unit, and using a target carrying object to carry the target loading unit according to the second specification parameters, the carrying parameters and the initial specification parameters.

6. The method of claim 5, wherein, After the execution of the task processing instruction according to the task information, the initial specification parameters and the scenario limitation information, the method further comprises: in the case that a loading unit specification parameter obtained by stacking based on the initial specification parameters does not meet the second specification parameters, or the loading unit specification parameter does not meet a second preset matching condition with the carrying parameters, determining that the execution of the task processing instruction in the storage scenario fails.

7. The method of claim 1, wherein, The test scene includes a transportation scene; the task information includes: placing a plurality of to-be-generated objects in a target transportation object, wherein the target transportation object is used to transport the plurality of to-be-generated objects; and the scene restriction information includes: object attribute information corresponding to the target transportation object; The execution of the task processing instruction according to the task information, the initial specification parameter and the scene restriction information includes: According to the initial specification parameter and the object attribute information, the processing operation of placing the plurality of to-be-generated objects in the target transportation object is performed to obtain at least one placement result.

8. The method of claim 7, wherein, After the processing operation of placing the plurality of to-be-generated objects in the target transportation object is performed according to the initial specification parameter and the object attribute information to obtain at least one placement result, the method further includes: determining object layout information corresponding to the at least one placement result in the target transportation object respectively; According to the object layout information, a target placement result is selected from the at least one placement result, and a target placement rule corresponding to the target placement result is obtained.

9. The method according to any one of claims 1 to 8, characterized in that, In the case that the task processing instruction in any test scene fails, the initial model file is adjusted based on the target scene restriction information and the initial specification parameter to obtain a target model file of the to-be-generated object, including: In the case that the task processing instruction in any test scene fails, the target scene restriction information is determined based on the test scene corresponding to the failed task processing instruction; The initial specification parameter is adjusted based on the target scene restriction information to obtain an intermediate specification parameter; In the case that the task processing instruction in each test scene is successfully executed, the intermediate specification parameter is determined as a target specification parameter of the to-be-generated object according to the task information, the intermediate specification parameter and the scene restriction information; The initial model file is adjusted based on the target specification parameter to obtain a target model file of the to-be-generated object.

10. A model file generation apparatus of an object, characterized by comprising: It includes: The acquisition module is configured to acquire an initial model file of a to-be-generated object, and determine an initial specification parameter of the to-be-generated object based on the initial model file; The receiving module is configured to receive a task processing instruction in at least one test scene, wherein the task processing instruction carries task information and scene restriction information; The execution module is configured to execute the task processing instruction according to the task information, the initial specification parameter and the scene restriction information; The adjustment module is configured to adjust the initial model file based on target scene restriction information and the initial specification parameter in the case that the task processing instruction in any test scene fails to obtain a target model file of the to-be-generated object, wherein the target model file is used to manufacture the to-be-generated object in a real scene.

11. A computing device, comprising: It includes: a memory and a processor; The memory is configured to store computer programs / instructions, and the processor is configured to execute the computer programs / instructions, so as to implement the steps of the model file generation method of the object according to any one of claims 1-9.

12. A computer-readable storage medium, characterized in that, The computer program / instruction stored in the memory is configured to be executed by the processor, so as to implement the steps of the model file generation method of the object according to any one of claims 1-9.

13. A computer program product, characterised in that, The computer program / instruction is configured to be executed by the processor, so as to implement the steps of the model file generation method of the object according to any one of claims 1-9.

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