A method for manufacturing a humanoid robot bone-like structure using magnetic control enhanced 4D printing

Abstract

The application discloses a method for manufacturing bone-like structure of humanoid robot by 4D printing with magnetic control enhancement. The method first reconstructs a three-dimensional model containing the characteristics of cortical bone and cancellous bone through high-resolution CT data, extracts structural arrangement parameters for digital modeling, and constructs a digital prototype with a solid shell and an internal grid structure. Then, the printing path vector is aligned with the direction of bone trabeculae using slicing software. A composite material mixed with a non-metal polymer matrix, reinforcing fibers and magnetic nanoparticles is made into a magnetic control enhancement filament through a screw extruder. In the printing process, the magnetic field generating device on the periphery of the nozzle is used to induce the directional arrangement of fibers and particles, realizing the anisotropy of mechanical properties. Based on machine learning and artificial intelligence closed-loop control algorithm, the mapping database is established to optimize the composite material ratio and printing parameters during the printing process. The application solves the problem of single structure and difficult precise adaptation of mechanical properties of traditional 3D printed humanoid robot parts, realizes the combination of humanoid robot parts and bone structure, and improves the macro size and micro performance.

Description

Technical Field

[0001] This invention relates to the field of design and manufacturing technology of biomimetic parts for humanoid robots, specifically to a method for manufacturing humanoid robot skeletal parts with a bone-inspired anisotropic structure using magnetron sputtering enhanced 3D printing. Background Technology

[0002] Currently, key load-bearing components of humanoid robots (such as skeletal structures) are mainly manufactured using metal processing (such as CNC machining and casting) or conventional 3D printing (such as FDM and SLA). These methods typically rely on the mechanical properties of the materials themselves, such as stainless steel or engineering plastics, as illustrated in Chinese patent publication CN117162538B. Additionally, load-bearing capacity is improved by increasing material usage or optimizing the external structure, as illustrated in Chinese patent publications CN119141588B and CN118081718A. However, these structures are generally homogeneous and isotropic, lacking the directional reinforcement design features specific to the stress path, similar to human skeletons.

[0003] Existing component manufacturing methods produce parts that lack biomimetic features, failing to incorporate the hierarchical structure of cortical and cancellous bone and the anisotropic arrangement of trabeculae in natural skeletons. Furthermore, relying solely on material stacking makes it difficult to achieve both lightweight and high stiffness. In addition, the short-cut fibers in traditional FDM 3D printing are randomly distributed, making directional reinforcement impossible. Therefore, existing manufacturing methods cannot achieve the comprehensive "lightweight-high strength-anisotropy" properties similar to human bone. Summary of the Invention

[0004] Inspired by the structure of cortical bone and cancellous bone and the arrangement of trabecular bone, this invention analyzes high-resolution CT data, extracts structural parameters, and combines magnetically controlled 4D printing technology to achieve the directional arrangement of magnetic particles and short-cut fibers during the printing process. This results in the manufacture of humanoid robot parts with bone biomimetic structural features, and proposes a manufacturing method that can achieve lightweight and high strength.

[0005] This invention provides the following technical solution: a method for manufacturing a humanoid robot skeletal structure using magnetron sputtering enhanced 4D printing, the method comprising the following steps: S1. Acquire high-resolution CT data of human bones and generate a three-dimensional reconstructed bone model containing the arrangement features of cortical and cancellous bone. S2. Based on the three-dimensional reconstructed skeletal model, extract the structural arrangement parameters of cortical bone and cancellous bone; S3. Based on the structural arrangement parameters, perform parametric design and modeling in 3D visualization software to construct a biomimetic skeleton digital prototype with a solid shell and an internal mesh structure. S4. Convert the bionic bone digital prototype into STL format, and use the slicing software of the magnetically controlled enhanced 4D printing equipment to perform slicing operations so that the printing path vector is aligned with the growth direction of the bone trabeculae. S5. Mix the polymer matrix, reinforcing fibers and magnetic nanoparticles in a predetermined ratio to prepare a magneto-controlled composite material; S6. The magnetron composite material is processed into composite filaments using a screw extruder; S7. Using a magnetron sputtering 4D printing device, print mechanical property test specimens using the composite filament; S8. Use a universal testing machine to test the stiffness of the test specimen and record the test results; S9. Establish a mapping database between test results and composite material ratios, and compare the stiffness obtained from the test with the target stiffness of human bone. Optimize the composite material ratios to control the difference between the two within ±15%. S10. Based on the optimized composite material ratio and the slice data obtained in step (4), biomimetic bone parts are printed using a magnetron sputtering 4D printing device. S11. Establish a mapping database between the dimensional error of printed parts and printing parameters, and adjust the printing parameters through artificial intelligence algorithms to control the dimensional error within ±0.5mm; S12. The printed bionic bone parts are subjected to support stripping, annealing and fine polishing to obtain the final product.

[0006] Furthermore, the high-definition CT data acquisition and three-dimensional reconstruction described in step S1 includes using a CT scanner to perform tomographic scanning of the target bone, with the scan slice thickness controlled between 0.1 mm and 0.5 mm, to obtain raw medical image data in DICOM format; extracting grayscale values ​​from the DICOM data using a threshold segmentation algorithm to distinguish between high-density areas of cortical bone and low-density areas of cancellous bone; and using the MarchingCubes algorithm to perform surface reconstruction to generate a high-fidelity three-dimensional mesh model.

[0007] Furthermore, the analysis of the arrangement of cortical and cancellous bone structures in real bones in step S2 refers to extracting the average pore size, porosity, and spatial anisotropy characteristics of the trabeculae through cross-sectional analysis of the three-dimensional mesh model; wherein, the cortical bone corresponds to the dense outer shell layer of the digital prototype of the bionic bone in step S3, and the cancellous bone corresponds to the porous mesh support area inside the digital prototype of the bionic bone.

[0008] Furthermore, the slicing design of the printing path along the trabecular direction mentioned in step S4 refers to aligning the path vector of the print head with the growth direction of the trabecular bone and the expected force vector through slicing software, thereby achieving anisotropy of mechanical properties.

[0009] Furthermore, the magnetron composite material described in step S5 includes a non-metallic polymer matrix material, reinforcing fibers, and magnetic nanoparticles; wherein the matrix material is one of polyetheretherketone (PEEK), nylon (PA), or polylactic acid (PLA); the reinforcing fibers are carbon fibers or glass fibers; the magnetic nanoparticles are one or more of Fe3O4, carbonyl iron, samarium iron nitrogen, or neodymium iron boron powder, and their particle size is approximately normally distributed, mainly distributed between 50 nm and 500 nm, accounting for 10% to 30% of the total volume of the composite material; after the materials are mixed in proportion, they are placed in a forced-air drying oven, and the composite material with polyetheretherketone (PEEK) as the matrix material is dried at 150°C for 5 hours; the composite material with nylon (PA) as the matrix material is dried at 100°C for 5 hours.

[0010] Furthermore, in step S6, during the production of composite filaments using a screw extruder, for polyether... For composite materials with ketone (PEEK) as the matrix material, the extrusion temperature is controlled at 330℃-360℃ and the extrusion speed is controlled at 10mm / s; for composite materials with nylon (PA) as the matrix material, the extrusion temperature is controlled at 270℃-280℃ and the extrusion speed is controlled at 10mm / s; for composite materials with polylactic acid (PLA) as the matrix material, the extrusion temperature is controlled at 210℃-220℃ and the extrusion speed is controlled at 10mm / s.

[0011] Furthermore, the magnetron sputtering enhanced 4D printing equipment described in steps S7 and S10 is equipped with a magnetic field generating device on the outer periphery of the printing nozzle; the magnetic field generating device is an electromagnetic coil wound around the nozzle, which can generate a pulsed magnetic field with an intensity of 6T and a constant magnetic field of 40mT, used to induce the magnetic nanoparticles and reinforcing fibers in the filament to form an oriented alignment effect along the printing path along the trabecular direction described in step S4 during the melting and transport of the magnetron sputtering composite material.

[0012] Furthermore, in step S9, a database mapping test results to composite material proportions is established, and regression analysis or neural network algorithms in machine learning are used for fitting. The optimization of the composite material proportions is achieved by adjusting the volume fraction of magnetic particles, the volume fraction of reinforcing fibers, and the aspect ratio of reinforcing fibers until the error between the stiffness of the sample and the actual stiffness of human bone is controlled within ±15%, so as to simulate the stiffness characteristics of human bone.

[0013] Furthermore, the artificial intelligence adjustment of printing parameters mentioned in step S11 refers to acquiring real-time image data of the printing layer through an online monitoring system, using a convolutional neural network (CNN) to identify dimensional deviations, and then adjusting the extruder flow rate, moving speed, and magnetic field strength to form a closed-loop control.

[0014] Furthermore, the annealing conditions described in step S12 are as follows: the printed solid part is placed in a vacuum oven and kept at a constant temperature of 20°C-50°C below the material melting point for 2-6 hours to eliminate thermal stress during the printing process and improve the interfacial bonding strength.

[0015] Compared with existing technologies, this method for manufacturing humanoid robot skeletal structures using magnetron sputtering enhanced 4D printing has the following advantages: I. This invention generates a biomimetic model containing features of cortical and cancellous bone through high-resolution CT scanning and 3D reconstruction technology, and extracts structural arrangement parameters based on this model for parametric design, solving the problem of biomimetic parts lacking realistic bone hierarchical structural features in traditional manufacturing methods. At the same time, by using slicing software to align the printing path vector with the growth direction of bone trabeculae, and in conjunction with magnetron sputtering enhanced 3D printing, magnetic nanoparticles and reinforcing fibers are oriented, achieving anisotropic design of mechanical properties. This overcomes the defects of random distribution of short-cut fibers and difficulty in directional reinforcement in existing FDM 3D printing, and significantly improves the load-bearing capacity of parts in the principal stress direction.

[0016] II. This invention establishes a mapping database between test results and composite material ratios, printing parameters, and dimensional errors. Utilizing machine learning regression analysis and artificial intelligence closed-loop control algorithms, the difference between the stiffness of the printed part and the stiffness of the target human bone is controlled within ±15%, and the dimensional error between the printed part and the 3D model is controlled within ±0.5mm. By precisely adjusting the proportion of magnetic particles and reinforcing fibers, as well as process parameters, improvements in both performance and precision are ensured, achieving "lightweight, high strength, and anisotropic" properties. The comprehensive performance optimization of "heterogeneous" effectively makes up for the technical shortcomings of traditional metal processing or conventional 3D printing, which rely solely on material accumulation and are difficult to balance lightweight and high rigidity. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0018] Figure 1 This is a flowchart of a method for manufacturing humanoid robot skeletal structures using magnetron sputtering enhanced 4D printing. Detailed Implementation

[0019] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features and effects of the present invention, in conjunction with the accompanying drawings and embodiments, is provided below.

[0020] Step S1: Acquisition of human skeleton CT data and reconstruction of high-fidelity 3D model CT scan data acquisition: Human bone samples were selected and thin-slice scans were performed using a 64-slice or higher spiral CT scanner. Scanning parameters were set as follows: tube voltage 120kV, slice thickness controlled between 0.1mm and 0.5mm, to obtain high-resolution DICOM format medical image raw data.

[0021] 3D Reconstruction and Feature Segmentation: DICOM data was imported into 3D image processing software, and a threshold segmentation algorithm was used to extract grayscale values, accurately distinguishing between cortical bone (high-density area) and cancellous bone (low-density area). Subsequently, the MarchingCubes algorithm was used for surface reconstruction, generating a high-fidelity 3D mesh model containing realistic bone grading features.

[0022] Steps S2 and S3: Extraction and digital modeling of skeletal structure arrangement parameters Arrangement parameter extraction: Perform cross-sectional analysis on the generated 3D mesh model to extract the average pore size, porosity, and anisotropic characteristics of the spatial distribution of the trabecular bone.

[0023] Digital modeling: Parametric design is performed in 3D visualization software based on the extracted structural arrangement parameters. The constructed biomimetic skeletal digital prototype has a solid and dense outer layer (corresponding to cortical bone) and an internal porous mesh structure (corresponding to cancellous bone structure).

[0024] Step S4: Slice Design and Path Planning Path vector alignment: The digital prototype was converted to STL format and imported into UltiMakerCura 5.10.0 software. By modifying the G-code file generated by the software, the path vector of the printhead was highly aligned with the direction of the trabecular bone and the principal stress direction inside the model, laying the foundation for achieving anisotropic mechanical properties.

[0025] Step S5: Preparation of Magnetron Enhancement Material Material proportioning and mixing: Mix non-metallic polymer matrix (such as PEEK, PA, or PLA) and additives according to a predetermined volume ratio. Strong fibers (carbon fiber or glass fiber) and magnetic nanoparticles (such as Fe3O4). Magnetic particles account for 10% to 30% of the total volume, and their particle size exhibits an approximately normal distribution, mainly between 50 nm and 500 nm.

[0026] Step S6: Magnetron Reinforced Wire Extrusion Drying and extrusion filament production: The mixed materials are placed in a forced-air drying oven for drying. For polyetheretherketone (PEEK), drying at 150℃ for 5 hours is required; for composite materials with nylon (PA) as the matrix, drying at 100℃ for 5 hours is required. During the production of composite filaments using a screw extruder, the extrusion temperature for PEEK-based composite materials is controlled at 330℃-360℃, and the extrusion speed is controlled at 10 mm / s; for nylon (PA)-based composite materials, the extrusion temperature is controlled at 270℃-280℃, and the extrusion speed is controlled at 10 mm / s.

[0027] Steps S7-S10: Sample testing and material ratio optimization Sample Printing and Mechanical Testing: Mechanical test samples were printed using a self-built magnetron sputtering 4D printing system. This system is based on a commercial FDM 3D printing system, with modifications made to the high-temperature printing nozzle. Two magnetic field generating coils were added to the nozzle area; the first applied a 6T pulsed magnetic field, and the second applied a 40mT constant magnetic field. These coils induce fiber and particle orientation along the path after the material melts. The stiffness of the printed samples was tested using a universal testing machine at a tensile testing speed of 0.083 mm / s.

[0028] Machine learning optimization: A mapping database between test results and material ratios was established, and a neural network algorithm was used for fitting. By adjusting the volume fraction of magnetic particles and the aspect ratio of reinforcing fibers, the difference between the stiffness of the printed part and the target stiffness of human bone was optimized to within ±15%.

[0029] Steps S11-S12: Artificial intelligence adjusts printing parameters and post-processing Printing parameter adjustment: During the actual printing of the bionic skeletal parts, an online monitoring system acquires images in real time, and a convolutional neural network (CNN) identifies dimensional deviations, providing real-time feedback to adjust the flow rate, printing speed, and magnetic field strength. This ensures that the final part's dimensional error is controlled within ±0.5mm.

[0030] Post-processing steps: The printed parts are then subjected to support peeling. Next, annealing is performed by placing them in a vacuum oven and maintaining a constant temperature of 20°C-50°C below the material's melting point for 2-6 hours to eliminate thermal stress. Finally, fine polishing is used to obtain the final product.

Claims

1. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering enhanced 4D printing, characterized in that, The method includes the following steps: S1. Acquire high-resolution CT data of human bones and generate a three-dimensional reconstructed bone model containing the arrangement features of cortical and cancellous bone. S2. Based on the three-dimensional reconstructed skeletal model, extract the structural arrangement parameters of cortical bone and cancellous bone; S3. Based on the structural arrangement parameters, perform parametric design and modeling in 3D visualization software to construct a biomimetic skeleton digital prototype with a solid shell and an internal mesh structure. S4. Convert the bionic bone digital prototype into STL format, and use the slicing software of the magnetron sputtering 4D printing equipment to perform slicing operations so that the printing path vector is aligned with the growth direction of the bone trabeculae. S5. Mix the polymer matrix, reinforcing fibers and magnetic nanoparticles in a predetermined ratio to prepare a magneto-controlled composite material; S6. The magnetron composite material is processed into composite filaments using a screw extruder; S7. Using a magnetron-enhanced 4D printing device, print mechanical property test specimens using the composite filament; S8. Use a universal testing machine to test the stiffness of the test specimen and record the test results; S9. Establish a mapping database between test results and composite material ratio, and compare the stiffness obtained from the test with the target stiffness of human bone. Optimize the composite material ratio to control the difference between the two within ±0.5GPa. S10. Based on the optimized composite material ratio and the slice data obtained in step (4), bionic bone parts are printed using a magnetron sputtering 4D printing device. S11. Establish a mapping database between the dimensional error of printed parts and printing parameters, and adjust the printing parameters through artificial intelligence algorithms to control the dimensional error within ±0.5mm; S12. The printed bionic bone parts are subjected to support stripping, annealing and fine polishing to obtain the final product.

2. The method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The high-definition CT data acquisition and three-dimensional reconstruction described in step S1 include using a CT scanner to perform tomographic scanning of the target bone, with the scan slice thickness controlled between 0.1 mm and 0.5 mm, to obtain raw medical image data in DICOM format; extracting grayscale values ​​from the DICOM data using a threshold segmentation algorithm to distinguish between high-density areas of cortical bone and low-density areas of cancellous bone; and using the MarchingCubes algorithm to perform surface reconstruction to generate a high-fidelity three-dimensional mesh model.

3. The method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The analysis of the arrangement of cortical and cancellous bone structures in real bones in step S2 refers to extracting the average pore size, porosity, and spatial anisotropy characteristics of bone trabeculae through cross-sectional analysis of the three-dimensional mesh model. The cortical bone corresponds to the dense outer shell layer of the digital prototype of the bionic bone in step S3, and the cancellous bone corresponds to the porous mesh support area inside the digital prototype of the bionic bone.

4. The method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The slicing design of the printing path along the trabecular direction mentioned in step S4 refers to aligning the path vector of the print head with the growth direction of the trabecular bone and the expected force vector through slicing software, thereby achieving anisotropy of mechanical properties.

5. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The magnetron composite material described in step S5 includes a non-metallic polymer matrix material, reinforcing fibers, and magnetic nanoparticles; wherein the matrix material is one of polyetheretherketone (PEEK), nylon (PA), or polylactic acid (PLA); the reinforcing fibers are carbon fibers or glass fibers; the magnetic nanoparticles are one or more of Fe3O4, carbonyl iron, samarium iron nitrogen, or neodymium iron boron powder, and their particle size is approximately normally distributed, mainly distributed between 50 nm and 500 nm, accounting for 10% to 30% of the total volume of the composite material; after the materials are mixed in proportion, they are placed in a forced-air drying oven, and the composite material with polyetheretherketone (PEEK) as the matrix material is dried at 150°C for 5 hours; the composite material with nylon (PA) as the matrix material is dried at 100°C for 5 hours.

6. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing as described in claim 1. Its features are, In step S6, during the production of composite filaments using a screw extruder, the extrusion temperature of the composite material with polyether ether ketone (PEEK) as the matrix is ​​controlled at 330℃-360℃, and the extrusion speed is controlled at 10mm / s. For composite materials with nylon (PA) as the matrix material, the extrusion temperature is controlled at 270℃-280℃ and the extrusion speed is controlled at 10mm / s; for composite materials with polylactic acid (PLA) as the matrix material, the extrusion temperature is controlled at 210℃-220℃ and the extrusion speed is controlled at 10mm / s.

7. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The magnetron sputtering 4D printing equipment described in steps S7 and S10 has a magnetic field generating device on the outer periphery of the printing nozzle; the magnetic field generating device is an electromagnetic coil wound around the nozzle, which can generate a pulsed magnetic field with an intensity of 6T and a constant magnetic field of 40mT, used to induce the magnetic nanoparticles and reinforcing fibers in the filament to form an oriented alignment effect along the printing path along the trabecular direction described in step S4 during the melting and transport of the magnetron sputtering composite material.

8. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, In step S9, a database mapping test results to composite material proportions is established, and regression analysis or neural network algorithms in machine learning are used for fitting. The optimization of the composite material proportions is achieved by adjusting the volume fraction of magnetic particles, the volume fraction of reinforcing fibers, and the aspect ratio of reinforcing fibers until the error between the stiffness of the sample and the actual stiffness of human bone is controlled within ±15%, so as to simulate the stiffness characteristics of human bone.

9. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The artificial intelligence adjustment of printing parameters mentioned in step S11 refers to acquiring real-time image data of the printed layer through an online monitoring system, using a convolutional neural network (CNN) to identify dimensional deviations, and adjusting the extruder flow rate and movement accordingly. The degree and magnetic field strength are used to form a closed-loop control.

10. A method for manufacturing a humanoid robot skeletal structure using magnetron sputtering 4D printing according to claim 1, characterized in that, The annealing conditions described in step S12 are as follows: the printed solid part is placed in a vacuum oven and kept at a constant temperature of 20°C-50°C below the material melting point for 2-6 hours to eliminate thermal stress during the printing process and improve the interfacial bonding strength.

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