Design, fabrication and autonomous assembly method of self-replicating robots

Abstract

The application relates to a design, manufacturing and autonomous assembly method of a self-replicating robot, comprising the following steps: step S1, constructing a large language model; step S2, fine-tuning the large language model by using design drawing data and drawing codes; step S3, generating various component design drawings by using the large language model obtained in step S2; step S4, printing various components by using a 3D printing device based on the design drawings; step S5, simulating assembly in a simulation environment and confirming an optimal assembly mode; and step S6, assembling various components into a robot in an actual environment according to the optimal assembly mode obtained in step S5. The application realizes self-design, manufacturing and autonomous assembly of the robot, greatly reduces the production cost and production cycle of the robot, simulates and optimizes the assembly mode in a virtual space, and greatly and effectively improves the production efficiency and production quality.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to a method for designing, manufacturing, and autonomously assembling a self-replicating robot. Background Technology

[0002] In existing technologies, the design, manufacturing, and assembly of most robots require human intervention, and the design, manufacturing, and assembly processes of each robot typically require specialized equipment and personnel, which significantly increases the production cost and cycle time. Therefore, researching a method for the design, manufacturing, and autonomous assembly of self-replicating robots is an urgent problem to be solved in the current technology. Summary of the Invention

[0003] To address the technical problems existing in the prior art, the present invention aims to provide a method for designing, manufacturing, and autonomously assembling a self-replicating robot, thereby enabling the robot to be self-designed, manufactured, and autonomously assembled, reducing production costs and production cycles, and improving production efficiency and quality.

[0004] To achieve the above-mentioned objectives, this invention provides a method for designing, manufacturing, and autonomously assembling a self-replicating robot, comprising the following steps:

[0005] Step S1: Construct a large language model;

[0006] Step S2: Fine-tune the large language model using design drawing data and drawing codes;

[0007] Step S3: Use the large language model obtained in step S2 to generate design drawings for each component;

[0008] Step S4: Based on the design drawings, print each component using a 3D printing device;

[0009] Step S5: Simulate assembly in the simulation environment to confirm the optimal assembly method;

[0010] Step S6: Based on the optimal assembly method obtained in step S5, assemble the various components into a self-replicating robot in a real environment.

[0011] According to one aspect of the invention, step S1 further includes: loading a 3D printing device for manufacturing various parts of the self-replicating robot, and constructing an assembly simulation model for simulating the assembly of the various parts.

[0012] According to one aspect of the present invention, step S2 specifically includes:

[0013] Step S21: Obtain the drawings and drawing generation code, and construct the first training set;

[0014] Step S22: Obtain the drawing generation code and the features of each component of the self-replicating robot, and construct the second training set;

[0015] Step S23: Train the large language model using the first training set to establish a mapping relationship between drawings and drawing generation codes;

[0016] Step S24: Use the second training set to train the large language model and establish a mapping relationship between the drawing generation code and the features of each part of the self-replicating robot.

[0017] According to one aspect of the invention, in step S2, the features of each component of the self-replicating robot include at least the number of joints, load capacity, workspace, and the size, shape, and material of the self-replicating robot arm.

[0018] According to one aspect of the present invention, step S4 specifically includes:

[0019] Step S41: Convert the design drawings into 3D printing code;

[0020] Step S42: Call the corresponding 3D printing device;

[0021] Step S43: Based on the generated 3D printing code, control the 3D printing device to print each component.

[0022] According to one aspect of the present invention, printing various components using a 3D printing apparatus specifically includes:

[0023] The 3D printing device is mounted on a tool robot, which controls the position of the 3D printing device to complete the printing of various parts. The tool robot includes an external robotic arm or robot.

[0024] According to one aspect of the invention, step S4 further includes:

[0025] The printing status of the 3D printing device is monitored in real time, and the printing process is dynamically adjusted.

[0026] According to one aspect of the invention, step S5 includes:

[0027] Based on the pre-designed assembly plan, autonomous assembly experiments are conducted in a simulation environment. Based on the factors affecting assembly, the feasibility of the assembly plan is verified, and the assembly process is optimized through autonomous learning.

[0028] The simulated assembly process includes at least checking the feasible range of the robotic arm, collisions, and joint over-limits.

[0029] The factors affecting assembly include at least the installation sequence of components, the installation method, and the installation tools.

[0030] According to one aspect of the present invention, step S3 further includes performing a feasible range detection for the self-replicating robot when generating design drawings for each component.

[0031] According to one aspect of the present invention, step S6 specifically includes:

[0032] Step S61: Obtain environmental information and analyze the impact of the environmental information on the optimal assembly method obtained in step S5;

[0033] Step S62: Based on the analysis in step S61, correct the optimal assembly method obtained in step S5;

[0034] Step S63: Assemble each component according to the revised assembly method.

[0035] According to one aspect of the invention, in step S63, a tool robot or a robotic arm is used to assemble the various components.

[0036] According to one aspect of the present invention, a robot is provided, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory, and when the robot is running, the processor executes the one or more computer programs stored in the memory to cause the robot to perform a method for designing, manufacturing, and autonomously assembling a self-replicating robot as described in any of the above technical solutions.

[0037] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement a method for designing, manufacturing, and autonomously assembling a self-replicating robot as described in any of the above technical solutions.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] This invention discloses a method for designing, manufacturing, and autonomously assembling a self-replicating robot. By constructing a large language model and utilizing its generation capabilities, it can generate drawing information for each component of the robot. During the design phase, it can automatically design and generate part drawings and assembly drawings for each component of the robot. Then, it can print each component using a 3D printing device. Through simulation assembly, simulation, and inspection in virtual space using the large language model, the feasibility of the autonomous assembly scheme is verified. For example, it checks the feasible range, obstacle limitations, and feasibility of the tool robot arm to obtain the optimal assembly method. Finally, it assembles the components into a complete robot in a real environment. That is, the self-replication task of the robot is completed by the tool robot, realizing the self-design, manufacturing, and autonomous assembly of the robot, which greatly reduces the production cost and production cycle of the robot.

[0040] Furthermore, the adoption of large language models and 3D printing technology enables the design, manufacturing, and assembly processes of robots to be completed automatically in both virtual and real spaces. The assembly method is simulated and optimized in virtual space, which greatly and effectively improves production efficiency and quality. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0042] Figure 1 This schematic diagram illustrates a flowchart of a method for designing, manufacturing, and autonomously assembling a self-replicating robot according to an embodiment of the present invention.

[0043] Figure 2 This schematic diagram illustrates the specific flowchart of step S2 in an embodiment of the present invention.

[0044] Figure 3 This schematic diagram illustrates the specific flowchart of step S4 in an embodiment of the present invention.

[0045] Figure 4 The schematic diagram illustrates the specific flowchart of step S6 in an embodiment of the present invention. Detailed Implementation

[0046] The description of the embodiments in this specification should be taken in conjunction with the accompanying drawings, which should form part of the complete specification. In the drawings, the shape or thickness of the embodiments may be exaggerated and may be indicated in a simplified or convenient manner. Furthermore, parts of the various structures in the drawings will be described separately; it is worth noting that elements not shown in the figures or not described in words are in a form known to those skilled in the art.

[0047] The descriptions of the embodiments herein, including any references to directions and orientations, are for ease of description only and should not be construed as limiting the scope of the invention. The following description of preferred embodiments involves combinations of features, which may exist independently or in combination; the invention is not particularly limited to the preferred embodiments. The scope of the invention is defined by the claims.

[0048] like Figure 1 and Figure 4 As shown, a method for designing, manufacturing, and autonomously assembling a self-replicating robot according to the present invention includes the following steps:

[0049] Step S1: Construct a large language model;

[0050] Step S2: Fine-tune the large language model using design drawing data and drawing codes;

[0051] Step S3: Use the large language model obtained in step S2 to generate design drawings for each component;

[0052] Step S4: Based on the design drawings, print each component using a 3D printing device;

[0053] Step S5: Simulate assembly in the simulation environment to confirm the optimal assembly method;

[0054] Step S6: Based on the optimal assembly method obtained in step S5, assemble the various components into a self-replicating robot in a real environment.

[0055] In this embodiment, by constructing a large language model and utilizing its generation capabilities, drawing information about each component of the robot can be generated. During the design phase, part drawings and assembly drawings of each component of the robot can be automatically designed and generated. Then, each component is printed using a 3D printing device. The optimal assembly method is obtained through simulated assembly in a virtual space. Finally, the components are assembled into a complete robot in a real environment. That is, the robot autonomously replicates a robot, realizing the self-design, manufacturing, and autonomous assembly of the robot, which greatly reduces the production cost and production cycle of the robot.

[0056] Furthermore, the adoption of large language models and 3D printing technology enables the design, manufacturing, and assembly processes of robots to be completed automatically in both virtual and real spaces. The assembly method is simulated and optimized in virtual space, which greatly and effectively improves production efficiency and quality.

[0057] The order of the 3D printing process in step S4 and the simulation assembly process in step S5 can be adjusted adaptively.

[0058] In one embodiment of the present invention, preferably, step S1 further includes: loading a 3D printing device for manufacturing various parts of the self-replicating robot, and constructing an assembly simulation model for simulating the assembly of the various parts.

[0059] like Figure 2 As shown, in one embodiment of the present invention, preferably, step S2 specifically includes:

[0060] Step S21: Obtain the drawings and drawing generation code, and construct the first training set;

[0061] Step S22: Obtain the drawing generation code and the features of each robot component to construct the second training set;

[0062] Step S23: Train the large language model using the first training set to establish a mapping relationship between drawings and drawing generation codes;

[0063] Step S24: Use the second training set to train the large language model and establish a mapping relationship between the drawing generation code and the features of each part of the self-replicating robot.

[0064] In this embodiment, it is necessary to collect a large number of design drawings (drawing codes) and corresponding drawing generation codes for various robot components (such as robot arms and connecting parts between arms) to build the first training set. This data can be obtained from open source datasets, other robot manufacturers, or self-designed and generated data. During the training process, deep learning techniques, such as the Transformer architecture, can be used to train the big oracle model to generate a model with good performance.

[0065] Next, the features of each component of the self-replicating robot (such as the number of joints, load capacity, workspace, etc.) and the corresponding drawing codes need to be trained. In this training process, the features are used as input and the drawing codes are used as output. Supervised learning method is used to train the large language model.

[0066] Furthermore, by establishing a mapping relationship between drawings and drawing generation code, as well as a mapping relationship between drawing generation code and the characteristics of various components of the self-replicating robot, the large language model can understand and master design rules, including but not limited to information such as the size, shape, material, and function of parts. Based on this, the large language model can use the learned knowledge to generate design drawings of various robot components that conform to the specifications, thus achieving autonomous robot design.

[0067] In one embodiment of the present invention, preferably, in step S2, the features of each component of the self-replicating robot include at least the number of joints, load capacity, workspace, and the size, shape, and material of the self-replicating robot arm.

[0068] like Figure 3 As shown, in one embodiment of the present invention, preferably, step S4 specifically includes:

[0069] Step S41: Convert the design drawings into 3D printing code;

[0070] Step S42: Call the corresponding 3D printing device;

[0071] Step S43: Based on the generated 3D printing code, control the 3D printing device to print each component.

[0072] In this embodiment, by converting design drawings into 3D printing code, the 3D printing device can identify each part in the drawing through the 3D printing code and determine its size, shape, position and other information.

[0073] The 3D printing device is configured on a tool robot, such as a pre-set or pre-designed robotic arm or robot (which can be a self-replicating robot or an additional robotic arm or robot). For example, the tool robot or robotic arm is used to operate the 3D printing pen or printing equipment. The tool robot or robotic arm controls the position of the 3D printing device. By precisely controlling the movement of the robotic arm, the printed parts are ensured to be dimensionally accurate and have a smooth surface, which is beneficial for robot assembly and robot movement.

[0074] In addition, during the 3D printing process, robots can autonomously print their own parts in real space. The printed parts include, but are not limited to, conventional parts, gearboxes, etc.

[0075] In one embodiment of the present invention, preferably, step S4 further includes:

[0076] The printing status of the 3D printing device is monitored in real time, and the printing process is dynamically adjusted to ensure that the size, shape and other information of the printed parts are completely consistent with the design drawings, providing a strong guarantee for subsequent assembly.

[0077] In one embodiment of the present invention, preferably, step S5 includes:

[0078] Based on the pre-designed assembly plan, autonomous assembly experiments are conducted in a simulation environment. Based on the factors affecting assembly, the feasibility of the assembly plan is verified, and the assembly process is optimized through autonomous learning.

[0079] The simulated assembly process includes at least checking the feasible range of the robotic arm, collisions, and joint over-limits.

[0080] Assembly factors include at least the installation sequence of components, installation method, and installation tools.

[0081] Step S3 also includes detecting the feasible range of the self-replicating robot when generating design drawings for each component.

[0082] In this embodiment, step S5 mainly refers to the entire process of the robot autonomously designing the assembly process in the simulation environment. During the overall simulation, the operation of each component of the robot is simulated, including at least the movement of the robotic arm, the rotation of the joints, and the picking and placing of parts. At the same time, during the simulation, problems that occur during the operation of the tool robot, such as collisions and joint over-limits, are detected in real time, and relevant solutions and optimization schemes are generated.

[0083] Leveraging machine learning and simulation technologies, the large language model automatically plans the assembly process and conducts simulation tests. During this process, the large language model comprehensively considers various factors, such as the installation sequence of parts, installation methods, and tool selection, to achieve the optimal assembly effect. Simultaneously, the model automatically detects and corrects potential design problems, such as part conflicts and assembly feasibility, thereby obtaining the optimal assembly solution. This provides support for subsequent assembly in real-world environments, reducing assembly failures and component damage caused by imperfect assembly plans in real-world scenarios, and improving the stability and reliability of the design, manufacturing, and autonomous assembly of the self-replicating robot.

[0084] like Figure 4 As shown, in one embodiment of the present invention, preferably, step S6 specifically includes:

[0085] Step S61: Obtain environmental information and analyze the impact of environmental information on the optimal assembly method obtained in step S5;

[0086] Step S62: Based on the analysis in step S61, correct the optimal assembly method obtained in step S5.

[0087] Step S63: Assemble each component according to the revised assembly method.

[0088] In this embodiment, the tool robot or robotic arm can use various sensors (such as vision, tactile and position sensors) to acquire environmental information, and detect and correct problems that may occur during the assembly process based on the environmental information, and modify the assembly scheme (assembly method) obtained by simulation, thereby further improving the stability and reliability of the design, manufacturing and autonomous assembly of the self-replicating robot.

[0089] Specifically, the tool robot or robotic arm uses various sensors to acquire real-time assembly status. When a problem is detected, the system adjusts the assembly process in real time based on the feedback information to ensure smooth assembly. Simultaneously, it compares the result with a preset assembly status (the assembly status corresponding to the optimal assembly scheme obtained in step S5). If a deviation is found, the tool robot or robotic arm adjusts according to a preset strategy to ensure assembly accuracy, significantly improve assembly efficiency, and reduce assembly difficulty.

[0090] In one embodiment of the present invention, preferably, a design, manufacturing, and autonomous assembly system for a self-replicating robot is provided, comprising:

[0091] The building module is used to build a large language model, which is then used to generate design drawings for each component.

[0092] The training module is used to fine-tune the large language model using design drawing data and drawing codes;

[0093] 3D printing equipment is used to print various parts based on design drawings;

[0094] The simulation module is used to simulate assembly and determine the optimal assembly method.

[0095] Tool robots or robotic arms are used to assemble individual components into a self-replicating robot in a real-world environment.

[0096] According to one aspect of the present invention, a robot is provided, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory, and when the robot is running, the processor executes the one or more computer programs stored in the memory to enable the robot to perform a method for designing, manufacturing, and autonomously assembling a self-replicating robot as described in any of the above technical solutions.

[0097] According to one aspect of the present invention, a computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement a method for designing, manufacturing, and autonomously assembling a self-replicating robot as described in any of the above technical solutions.

[0098] This invention discloses a method for designing, manufacturing, and autonomously assembling a self-replicating robot, comprising the following steps: Step S1, constructing a large language model; Step S2, fine-tuning the large language model using design drawing data and drawing codes; Step S3, generating design drawings for each component using the large language model obtained in Step S2; Step S4, printing each component using a 3D printing device based on the design drawings; Step S5, simulating assembly in a simulation environment to confirm the optimal assembly method; Step S6, assembling each component into a robot in a real-world environment according to the optimal assembly method obtained in Step S5. By constructing a large language model and utilizing its generation capabilities, drawing information about each component of the robot can be generated. During the design phase, part drawings and assembly drawings for each component of the robot can be automatically designed and generated. Then, each component is printed using a 3D printing device. Through simulated assembly in virtual space, the optimal assembly method is obtained. Finally, the components are assembled into a complete robot in a real-world environment, realizing the self-design, manufacturing, and autonomous assembly of the robot, significantly reducing the robot's production cost and production cycle.

[0099] Furthermore, the adoption of large language models and 3D printing technology enables the design, manufacturing, and assembly processes of robots to be completed automatically in both virtual and real spaces. The assembly method is simulated and optimized in virtual space, and the assembly is completed automatically in real space, which greatly and effectively improves production efficiency and quality.

[0100] Furthermore, it should be noted that the present invention can be provided as a method, system, or computer program product. Therefore, embodiments of the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0101] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0103] It should also be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0104] Finally, it should be noted that the above description represents a preferred embodiment of the present invention. It should be pointed out that although preferred embodiments of the present invention have been described, those skilled in the art, once they understand the basic inventive concept of the present invention, will be able to interpret it without departing from the original intent of the invention.

[0105] Under the premise of understanding the principles, several improvements and modifications can be made, and these improvements and modifications should also be considered within the scope of protection of this invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this invention.

Claims

1. A method for designing, manufacturing, and autonomously assembling a self-replicating robot, characterized in that, Includes the following steps: Step S1: Construct a large language model; Step S2: Fine-tune the large language model using design drawing data and drawing codes, specifically including: Step S21: Obtain the drawings and drawing generation code, and construct the first training set; Step S22: Obtain the drawing generation code and the features of each component of the self-replicating robot, and construct the second training set; Step S23: Train the large language model using the first training set to establish a mapping relationship between drawings and drawing generation codes; Step S24: Use the second training set to train the large language model and establish the mapping relationship between the drawing generation code and the features of each part of the self-replicating robot. Step S3: Use the large language model obtained in step S2 to generate design drawings for each component; Step S4: Based on the design drawings, print each component using a 3D printing device; Step S5: Simulate assembly in the simulation environment to confirm the optimal assembly method; Step S6: Based on the optimal assembly method obtained in step S5, assemble the various components into a self-replicating robot in a real environment.

2. The design, manufacturing, and autonomous assembly method for a self-replicating robot according to claim 1, characterized in that, Step S1 further includes: loading a 3D printing device for manufacturing the various parts of the self-replicating robot, and constructing an assembly simulation model for simulating the assembly of the various parts.

3. The design, manufacturing, and autonomous assembly method for a self-replicating robot according to claim 1, characterized in that, In step S2, the features of each component of the self-replicating robot include at least the number of joints, load capacity, workspace, and the size, shape, and material of the self-replicating robot arm.

4. The design, manufacturing, and autonomous assembly method of the self-replicating robot according to claim 1, characterized in that, Step S4 specifically includes: Step S41: Convert the design drawings into 3D printing code; Step S42: Call the corresponding 3D printing device; Step S43: Based on the generated 3D printing code, control the 3D printing device to print each component.

5. The design, manufacturing, and autonomous assembly method of the self-replicating robot according to claim 1 or 4, characterized in that, The various parts are printed using a 3D printing device, specifically including: The 3D printing device is mounted on a tool robot, which controls the position of the 3D printing device to complete the printing of various parts. The tool robot includes an external robotic arm or robot.

6. The method for designing, manufacturing, and autonomously assembling a self-replicating robot according to claim 4, characterized in that, Step S4 further includes: The printing status of the 3D printing device is monitored in real time, and the printing process is dynamically adjusted.

7. The method for designing, manufacturing, and autonomously assembling a self-replicating robot according to claim 6, characterized in that, Step S5 includes: Based on the pre-designed assembly plan, autonomous assembly experiments are conducted in a simulation environment. Based on the factors affecting assembly, the feasibility of the assembly plan is verified, and the assembly process is optimized through autonomous learning. The simulated assembly process includes at least checking the feasible range of the robotic arm, collisions, and joint over-limits. The factors affecting assembly include at least the installation sequence of components, the installation method, and the installation tools.

8. The method for designing, manufacturing, and autonomously assembling a self-replicating robot according to claim 7, characterized in that, Step S6 specifically includes: Step S61: Obtain environmental information and analyze the impact of the environmental information on the optimal assembly method obtained in step S5; Step S62: Based on the analysis in step S61, correct the optimal assembly method obtained in step S5; Step S63: Assemble each component according to the revised assembly method.

9. The method for designing, manufacturing, and autonomously assembling a self-replicating robot according to claim 8, characterized in that, In step S63, a tool robot or robotic arm is used to assemble the various components.

10. A robot, characterized in that, include: One or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are stored in the memory, and when the robot is running, the processor executes the one or more computer programs stored in the memory to cause the robot to perform the design, manufacture, and autonomous assembly method of the self-replicating robot as described in any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, implement the design, manufacture, and autonomous assembly method of the self-replicating robot as described in any one of claims 1 to 9.

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