Redundant drive parallel robot digital platform design system

Abstract

The invention discloses a redundant drive parallel robot digital platform design system, and belongs to the technical field of digital platforms for robot design. An RAPRDev platform is designed to serve as a digital platform of the parallel robot and comprises a configuration selection module, a scale design module, a kinematics analysis module, a structure design module and a finite element simulation analysis module, and the modules are integrated through an integrated design environment module to achieve design of the parallel robot. By the adoption of the platform, the design process of the parallel robot is integrated on one platform, the technical scheme that multiple functions are integrated is achieved through the platform, and a redundant drive parallel robot design unified theoretical model is integrated into a digital platform. Based on the spinor theory, a unified expression model of the motion characteristics of the parallel robot is provided in the configuration selection module. A redundant drive parallel robot general scale optimization model with dexterity as a kinematics performance index is provided in a scale optimization module.

Description

Technical Field

[0001] This invention relates to the technical field of parallel robot design, and in particular to a redundancy-driven parallel robot digital platform design system. Background Technology

[0002] The design of redundant-drive parallel robots is more challenging than that of serial robots or even general parallel robots. The introduction of redundant drives not only brings additional kinematic chains and coupling constraints, but also requires the simultaneous coordination of conflicting parameters such as drive configuration, internal force distribution, and dynamic characteristics during the design process. Researchers must achieve a global balance among mutually constraining workspace, kinematic performance, stiffness characteristics, and dynamic response. Although existing CAD / CAE software can perform rapid simulation analysis of some performance indicators, manual reconstruction of the geometric model and reconfiguration of finite element solution parameters are still necessary after adjusting the posture or modifying the structure, resulting in a large number of repetitive operations and time consumption in the design process. These difficulties often limit researchers to making local improvements to a few classic configurations, making it difficult to systematically explore core parameters such as drive configuration and kinematic branch topology, directly leading to a scarcity of high-performance redundant-drive parallel robot configurations available for practical engineering. At the same time, the collaboration between multidisciplinary design methods faces high technical barriers, resulting in significant deviations between the predicted dynamic characteristics of redundant-drive parallel robots and their actual performance. Repeated debugging is still required after the physical prototype is manufactured, further increasing R&D costs. The existence of these problems has forced researchers to seek ways to simplify the design process digitally.

[0003] Traditional digital design of robots typically employs a decentralized development model, where the design process is divided into independent stages such as conceptual design, parameter optimization, structural design, simulation analysis, and prototype manufacturing, each relying on different software tools and design standards. This fragmented development approach leads to incompatible data formats and distorted transmission of design parameters, forcing designers to perform tedious manual data conversion and coordination across multiple platforms. Particularly in the parameter optimization stage, even minor configuration adjustments require rebuilding the kinematic model, updating finite element analysis boundary conditions, and manually correcting control algorithm parameters; this repetitive work severely slows down the iteration speed. More seriously, decentralized design struggles to achieve global performance optimization; kinematic indices and structural strength analysis are often conducted in isolation, resulting in significant compromises between dynamic characteristics and load-bearing capacity in the final design. Summary of the Invention

[0004] The purpose of this invention is to provide a digital platform design system for redundant-driven parallel robots, integrating a unified theoretical model for redundant-driven parallel robot design into the digital platform. Based on screw theory, a unified representation model describing the motion characteristics of the mechanism is proposed in the configuration design module. In the scale optimization module, a general scale optimization model for redundant-driven parallel robots with dexterity as the kinematic performance index is proposed. Based on the closed-loop vector method, a general abstract model for the inverse kinematics of parallel robots and a dynamic cyclic hierarchical search method compatible with multi-degree-of-freedom workspace estimation are proposed in the kinematic analysis module.

[0005] To achieve the above objectives, the present invention provides a design system for a redundant-drive parallel robot digital platform, comprising the following modules: The RAPRDev platform is designed as a digital platform for parallel robots, including a configuration selection module, a scale design module, a kinematics analysis module, a structural design module, and a finite element simulation analysis module. The above modules are integrated through an integrated design environment module to realize the design of parallel robots. The configuration selection module allows users to input the configuration features of the parallel robot, parametrically represent the joints and branches of the parallel robot, obtain motion screws, obtain constraint screws based on the motion screws, and obtain the topological configuration through the constraint screws. The topological configuration includes the selected joint types. The kinematics analysis module provides a general abstract model for the inverse kinematics solution of parallel robots based on the closed-loop vector method and a dynamic cyclic hierarchical search platform compatible with multi-degree-of-freedom workspace estimation, providing a kinematics analysis process for the scale design module. The scale design module transforms the topological configuration into structural parameters. Based on the distance between different branches of the parallel robot, the moving platform and the static platform are defined using the structural parameters. The scale factor is set to normalize the radius of the moving platform and the static platform. The kinematic analysis module calculates the global dexterity and selects the radius of the moving platform and the static platform corresponding to the global dexterity that meets the conditions as the design parameters. The structural design module uses design parameters to select, parametrically model, and automatically assemble the components of the parallel robot; it generates a 3D model, and then performs finite element analysis on the generated 3D model using the finite element analysis module. If the finite element analysis results do not meet the requirements, the model is modified. The finite element analysis module, based on the 3D model in the structural design module, performs preprocessing and finite element analysis on the 3D model to obtain finite element analysis cloud diagrams, providing finite element analysis results for the structural design module. Integrated Design Module: Based on database functionality, it enables data exchange and storage between the different modules mentioned above, and provides a user interface and design report. The user interface displays input configuration features, topological configurations, design parameters, 3D models, kinematic performance images, and finite element analysis cloud maps during the design process. The design report compiles the content displayed in the user interface into a report.

[0006] Preferably, the implementation process of the configuration selection module is as follows: To avoid illegal connections, the input configuration features are checked. Rotor theory is uniformly used to parameterize the motion characteristics of parallel robots. In parallel robots, the spinor of a joint motion... The formula is as follows: ; In the above formula, S Let be the direction vector of the kinematic pair position. Indicates rotation about the spinor axis r × S and moving parallel to the spinor axis pS Composition, in which Represents the position vector of any point on the axis of rotation. The pitch is represented by the linear rotation; the moving spin is represented as zero. Rotational spin due to its displacement A value of 0 indicates that... Define a general spinor system as follows: ; In the above formula, The constraint screw represents the actual motion state of the nth joint in a parallel robot. The constraint screw represents the constraint state on the system's motion caused by structural limitations. The constraint screw system of a parallel robot is considered as the common constraint on the overall motion of all joint constraint screws within the robot. Therefore, the overall constraint screw system is the union of the local constraint screw systems formed by each joint and branch. The formula is as follows: ; In the above formula, the superscript r Represents a locally constrained spinor system, subscript n Indicates the first n The motion screw system of a parallel robot is considered as the motion existing in all components within the robot, and the overall motion screw system is the intersection of the local motion screw systems formed by each joint and branch. The formula is as follows: ; The above formula In the middle, superscriptm Represents the local rotational system of motion, with subscripts. n Indicates the first n In the motion mode analysis of parallel robots, solving the motion screw system of the moving platform requires overcoming the complexity brought about by the common constraints between series branches. A method of finding the inverse screw system twice is used to obtain the final overall motion screw system. Specifically, the constraint screw system is determined by solving the inverse screw system of each branch's motion screw system. Then, the overall constraint screw system is derived by synthesizing the constraint screw systems of each branch. Finally, the overall motion screw system is obtained through inverse screw calculation. k The parallel robot has a linearly independent system of local motion spinors. k Based on the above calculations and analysis, the redundant-drive parallel robot with [number] degrees of freedom is abstracted into the following topology: [structure of the robot with] redundant drive parallel robots. n Composed of active branch chains k The formula for the drive redundancy in a parallel robot with multiple degrees of freedom is as follows: ; Use the above formula to filter out topological configurations that meet the conditions.

[0007] Preferably, the workflow of the kinematic analysis module is as follows: Establish a fixed coordinate system at the geometric center of the static platform. Establish a motion coordinate system at the geometric center of the moving platform. And sorted by branches in order, with the direction from the static platform to the moving platform as the positive z-axis, and so on. The geometric center pointing towards the joint between the branch and the static platform is defined as the positive x-axis, where... and These represent the centers of the moving joints installed on the static and moving platforms, respectively, in a fixed coordinate system. The position vector and the position unit vector are respectively and In the moving coordinate system, The position vector and the position unit vector are respectively and Geometric center of the moving platform The position vector is Vector use To indicate, Let represent the direction vector of the j-th motion axis of the i-th branch, where the first motion axis represents the motion axis fixed to the moving platform, and the last motion axis represents the motion axis fixed to the static platform. In the motion coordinate system Below is written as The formula for obtaining the vector of the joint axis is as follows: ; In the above formula, R The attitude change matrix of the moving platform is defined as follows: , and Let the precession angle, nutation angle, and rotation angle in the attitude change matrix represent the motion characteristics of the parallel robot in its spinor system. , , , , and Six independent parameters determine and describe the motion of the moving platform relative to the frame, with the centers of motion joints on both the stationary and moving platforms corresponding to the endpoints of each branch. and Let i = 1, 2, ..., n, and be related to the geometric centers of the moving platform and the static platform, respectively. and A vector closed-loop equation is formed, as shown in the following formula: ; The position vector in the above equation and Rewritten as follows: ; In the above formula, Indicates the radius of the static platform. This represents the radius of the moving platform, combining the formulas for the vectors of the joint axes, the vector closed-loop equations, and the position vectors mentioned above. and The inverse position equation and driving parameters of the parallel robot are derived. The generalized representation using scale and position parameters is as follows: ; In the above formula, This represents the inverse kinematics of a parallel robot. Indicates the first t The range of motion of a passive joint; Indicates the first t The range of motion of each passive joint; Indicates the first i The motion range of each active joint is calculated using a workspace hierarchical search algorithm. The motion ranges of the passive and active joints are obtained through inverse kinematics calculations. Based on this, a workspace prediction function is derived. The formula is as follows: ; In the above formula, This represents the independent variable characterizing the motion of the moving platform; This indicates the range of motion of the joint; l and m Representing the number of passive and active joints respectively, the workspace prediction function... Constraints are imposed by the range of motion of passive joints and the range of motion of active joints.

[0008] Preferably, the workflow of the scale design module is as follows: The given workspace prediction function is searched hierarchically using the kinematic analysis module. The range of motion and dimensional parameters of each joint affect the average dexterity across the entire range. To facilitate visualization of dexterity, the parameters need to be normalized based on the structure of the moving or static platform, and a scale factor needs to be defined. , … It is expressed as follows: ; In the above formula, This represents the nth design parameter. This represents the nth scaling factor. Norm This indicates that the design parameters are normalized to a scaling factor; in a perfectly driven system, the spinor of the end effector is determined by the angular velocity of the moving platform. linear velocity at the geometric center point Composition, in the On each branch, Indicates the first The rotational range of motion of each joint, and Indicates the first The immobile rotation of each joint and This forms a 6-DOF spinor space, and the motion spinor of the moving platform The formula is as follows: ; In the above formula, Indicates the first i The number of degrees of freedom of each branch. This indicates that the driving system is the first j r Each drive joint speed Indicates by the first Each branch provides the driving spin of the moving platform, and the driving spin of the moving platform is related to the motion spin of its own joints. Collinear, orthogonal to the other movable spinors; Indicates the first i Each branch provides a constraint spindle to the moving platform, which is related to the movable spindle on that branch. Duality yields the following formula: ; Based on the above description of the exact driving system, the driving Jacobian matrix of the exact driving system is... and constrained Jacobian matrix They are represented as follows: ; ; The system's general Jacobian matrix With the motion spinor of the moving platform Multiplying them together, we get the following formula: ; Choose three non-collinear geometric centers to connect each branch to the joint of the moving platform. , and These points, as characteristic motion points of the platform, are in the moving coordinate system Position vector in , and Forming the motion representation matrix of the moving platform as follows: ; Obtain the homogeneous Jacobian matrix of the driving system It is expressed as follows: ; ; In the above formula, For a matrix, In Represented as a rotation matrix; for this just-driven system, the local flexibility is the reciprocal of the condition number of the homogeneous Jacobian matrix under the current attitude, and the local flexibility... The formula is as follows: ; Since redundantly driven parallel robots have multiple drive systems, selecting the subsystem with the highest dexterity as the drive system yields the following overall local dexterity at the current pose. The formula is as follows: ; In the above formula, This indicates the exact number of drive systems in the redundantly driven parallel robot, where the subscript... m To drive the number of sidechains, superscript n For the number of degrees of freedom of the robot, This indicates the redundant drive parallel robot. nThe local dexterity of a given drive system is determined by the fact that the dexterity value changes with attitude. To measure the kinematic performance across the entire range, the average dexterity value across the entire range is taken as the performance index, as shown in the following formula: ; In the above formula, This represents the average dexterity across the entire domain. d μ The higher the value, the greater the dexterity within the workspace.

[0009] Preferably, the implementation process of the structural design module is as follows: Component selection function: During the design process, the components that need to be selected are named in the format of "type + installation location + model" and saved as SLDPRT format to the SW component image library. Since component selection requires comparison from multiple sources, in order to enable users to quickly view component images on the platform, a copy is saved as an STL format file to the OpenGL component visualization library. Subsequently, an independent component selection library is created using Access software, recording the index position of all components, the index position of the STL file, the index and position of replaceable components, and related parameters. Parametric modeling function: This function sets the parameters of a component, then maps the changes of the parameters to the model structure to all parts of the component, draws them one by one, and saves them as .STL files; Automated assembly: During parametric modeling, datum elements are added to parts according to a uniform pattern and named appropriately. These elements are selected directly by retrieving the project name. In parametric modeling, each part in both the component library and the self-selected component library needs a Flag data item to verify whether the updated part can be correctly assembled with its child / parent components. The Flag numbering rules are as follows: Parent component: 1_location_child component name_child component location_fit type; Sub-component: 2_Point_Parent component name_Parent component point_Match type; After completing the parameterization settings, all parts of the above types need to have their Flags verified to match the parent / child components before automatic assembly.

[0010] Preferably, the finite element analysis process is as follows: First, model preprocessing is performed, including component isolation, component deletion and feature removal, component renaming, component merging, and feature addition. The specific process is as follows: Component independence: When a model is imported from SolidWorks into SpaceClaim, even if it is imported through an intermediate file, parts or assemblies in multiple components may reference the same source file. They need to be handled independently to avoid referencing issues. Component removal and feature removal: Used to remove detailed features that have little impact on simulation analysis results, including small chamfers, small fillets, small holes, small bosses, small grooves, as well as standard parts, non-load-bearing parts, and non-structural parts in components, thereby improving mesh quality and solver computational efficiency, ensuring the smooth completion of finite element analysis, removing components in advance, and reducing the amount of computation when SpaceClaim selects features through PowerSelection; Component renaming: Components are renamed using a standardized method to ensure unique entity names. Then, the GetObjectByName method is used to quickly retrieve some components. Reducing the selection range of PowerSelection during feature selection is a necessary operation before feature removal. The naming rules are as follows: 1_Level 1 Assembly Name / Entity + Number of Components / Entities of the Same Type under the Current Parent Component_2_Level 2 Assembly Name / Entity + Number of Components or Entities of the Same Type under the Current Parent Component_…_n_Level n Assembly Name / Entity + Number of Components / Entities of the Same Type under the Current Parent Component; Component merging: Component merging is the process of integrating multiple components into a single entity, eliminating their assembly relationships. Its significance is complementary to that of component independence. Feature addition: For the problem of some feature information being lost, SpaceClaim's CAD function is used to repair the lost information, and SpaceClaim Script is used for targeted repair. Finite element analysis of a 3D model Mechanical is a module in Ansys Workbench used for structural mechanics and dynamics analysis. It provides a wide range of analysis functions, including statics, dynamics, and modal analysis. The automated preprocessing and finite element analysis of the RAPRDev platform are based on this module. Phase 1: The system divides user input parameters into two categories: basic parameters and derived parameters. Basic parameters are directly written into the corresponding fields of the database; derived parameters need to be preprocessed and calculated by the kinematic analysis module and the structural design module before the results are stored in the database. Phase 2: An interactive database management mechanism is adopted to support user read and write operations on data. The system architecture includes three core components: the main controller, which is responsible for connecting to the database QSqlDatabase and maintaining the material data cache MaterialList; data formatting to ensure that the output conforms to the syntax specification; and the ScriptFileHandler class, which provides complete file operation support, including template reading, script writing and syntax validation. Phase 3: The system executes according to the standardized data processing flow: (1) Responding to user actions triggers script generation; (2) Query the database to obtain parameter data; (3) Format the query results; (4) Merge the formatted data with the template; (5) Output the final design report.

[0011] Therefore, the present invention employs the above-described redundant drive parallel robot digital platform design system, which has the following advantages: (1) A unified theoretical model for redundant-driven parallel robot design is integrated into the digital platform. Based on spinor theory, a unified representation model describing the motion characteristics of parallel robots is proposed in the configuration selection module. In the scale optimization module, a general scale optimization model for redundant-driven parallel robots with dexterity as the kinematic performance index is proposed. Based on the closed-loop vector method, a general abstract model for the inverse kinematics solution of parallel robots and a dynamic cyclic hierarchical search method compatible with multi-degree-of-freedom workspace prediction are proposed in the kinematic analysis module.

[0012] (2) Integrating the technologies of each component into the development of each module. Based on OpenGL 3D rendering technology, model visualization in configuration selection is realized and extended to the entire platform. Based on MATLAB & QT hybrid programming technology, complex data calculation and data visualization of the platform are realized and applied to the scale optimization and kinematic performance analysis modules. Based on SolidWorks API secondary development technology, parametric modeling, automatic assembly and interference checking in the structural design module are realized. Based on Access software and QSql class in Qt, data storage is realized. A CAD-CAX model conversion method is proposed, based on SpaceClaim, Mechanical, Ansys Workbench, and Batch scripts, realizing automatic preprocessing and feature modification of the model, automated preprocessing, and finite element solution analysis. A new solution is provided for parametric design and analysis functions of CAD / CAE data transfer using neutral files. This solution can effectively solve the problem of feature information loss when neutral files are transferred across platforms. The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0013] Figure 1 A flowchart of a redundant drive parallel robot digital platform design system according to the present invention; Figure 2 This is a simplified diagram of the parallel robot in this invention; Figure 3 In an embodiment of the redundant drive parallel robot digital platform design system of the present invention, a 2UPR-2RPS configuration is matched. Figure 4This invention provides a 2UPR-2RPS scale optimization in an embodiment of a redundant-drive parallel robot digital platform design system. Figure 5 This is a schematic diagram of the estimated workspace of 2UPR-2RPS in an embodiment of the redundant drive parallel robot digital platform design system of the present invention; Figure 6 This is a structural design diagram of 2UPR-2RPS in an embodiment of a redundant drive parallel robot digital platform design system of the present invention; Figure 7 This is a diagram showing the finite element analysis results of 2UPR-2RPS in an embodiment of a redundant drive parallel robot digital platform design system according to the present invention. Figure 8 This is a schematic diagram of the load settings in the static analysis of 2UPR-2RPS in an embodiment of the redundant drive parallel robot digital platform design system of the present invention; Figure 9 This is a schematic diagram of the equivalent stress of the whole machine in the static analysis of 2UPR-2RPS in an embodiment of the redundant drive parallel robot digital platform design system of the present invention; Figure 10 This is a schematic diagram of the equivalent elastic strain of the whole machine in the static analysis of 2UPR-2RPS in an embodiment of the redundant drive parallel robot digital platform design system of the present invention. Figure 11 This is a schematic diagram of the total displacement distribution of the entire machine in the static analysis of a 2UPR-2RPS in an embodiment of the redundant drive parallel robot digital platform design system of the present invention. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Specific model specifications need to be selected and determined according to the actual specifications of the device, etc. The specific selection calculation platform adopts existing technology in the art, and therefore will not be described in detail.

[0015] Example like Figure 1 As shown, this invention provides a design system for a redundant-drive parallel robot digital platform, comprising the following modules: The RAPRDev platform is designed as a digital platform for parallel robots, including a configuration selection module, a scale design module, a kinematics analysis module, a structural design module, and a finite element simulation analysis module. The above modules are integrated through an integrated design environment module to realize the design of parallel robots. The configuration selection module allows users to input the configuration features of the parallel robot, parametrically represent the joints and branches of the parallel robot, obtain motion screws, obtain constraint screws based on the motion screws, and obtain the topological configuration through the constraint screws. The topological configuration includes the selected joint types. The parallel robot structure is decomposed into the parallel robot, branches, and basic joints. The series branches consist of five basic joint types: R (revolute joint), P (prismatic joint), U (Hooke's joint), S (spherical joint), and C (cylindrical joint). Series branches can directly form a parallel robot, or they can be used as parallel branches to form a parallel robot after a parallel mechanism has been established. Furthermore, most parallel robots today can be categorized into R-joint drives and P-joint drives based on the type of drive joints. To facilitate the addition of other configurations to the RAPRDev platform, spinor theory is uniformly used to parameterize the motion characteristics of the mechanism. The implementation process of the configuration selection module is as follows: To avoid illegal connections, the input configuration features are checked. Rotor theory is uniformly used to parameterize the motion characteristics of parallel robots. In parallel robots, the spinor of a joint motion... The formula is as follows: ; In the above formula, S Let be the direction vector of the kinematic pair position. Indicates rotation about the spinor axis r × S and moving parallel to the spinor axis pS Composition, in which Represents the position vector of any point on the axis of rotation. The pitch is represented by the linear rotation; the moving spin is represented as zero. Rotational spin due to its displacement A value of 0 indicates that... Define a general spinor system as follows: ; In the above formula, The motion screw represents the actual motion state of the nth joint in a parallel robot. Motion screws describe the actual motion state of each joint in a parallel robot system, while constraint screws describe the constraints on the system's motion caused by structural limitations. The constraint screw system of a parallel robot is considered as the common constraint on the overall motion of all joint constraint screws within the parallel robot. Therefore, the overall constraint screw system is the union of the local constraint screw systems formed by each joint and branch. as follows: ; In the above formula, the superscript r Represents a locally constrained spinor system, subscript n Indicates the first n The motion screw system of a parallel robot is considered as the motion existing in all components within the robot, and the overall motion screw system is the intersection of the local motion screw systems formed by each joint and branch. The formula is as follows: ; The above formula In the middle, superscript m Represents the local rotational system of motion, with subscripts. n Indicates the first n In the motion mode analysis of parallel robots, solving the motion screw system of the moving platform requires overcoming the complexity brought about by the common constraints between series branches. A method of finding the inverse screw system twice is used to obtain the final overall motion screw system. Specifically, the constraint screw system is determined by solving the inverse screw system of each branch's motion screw system. Then, the overall constraint screw system is derived by synthesizing the constraint screw systems of each branch. Finally, the overall motion screw system is obtained through inverse screw calculation. k The parallel robot has a linearly independent system of local motion spinors. k Based on the above calculations and analysis, the redundant-drive parallel robot with [number] degrees of freedom is abstracted into the following topology: [structure of the robot with] redundant drive parallel robots. n Composed of active branch chains k The formula for the drive redundancy in a parallel robot with multiple degrees of freedom is as follows: ; Use the above formula to filter out topological configurations that meet the conditions.

[0016] The kinematics analysis module provides a general abstract model for the inverse kinematics of parallel robots based on the closed-loop vector method, and a dynamic cyclic hierarchical search platform compatible with multi-degree-of-freedom workspace estimation, thus providing the kinematics analysis process for the scale design module. The workflow of the kinematics analysis module is as follows: like Figure 2 As shown, a fixed coordinate system is established at the geometric center of the static platform according to the right-hand spinor rule. Establish a motion coordinate system at the geometric center of the moving platform. And sorted by branches in order, with the direction from the static platform to the moving platform as the positive z-axis, and so on. The geometric center pointing towards the joint between the branch and the static platform is defined as the positive x-axis, where... and These represent the centers of the moving joints installed on the static and moving platforms, respectively, in a fixed coordinate system. The position vector and the position unit vector are respectively and In the moving coordinate system, The position vector and the position unit vector are respectively and Geometric center of the moving platform The position vector is Vector use To indicate, Let $\mathbf{i}$ represent the direction vector of the $j$-th motion axis of the $i$-th branch. The first motion axis represents the motion axis fixed to the moving platform, and the last motion axis represents the motion axis fixed to the stationary platform. Except for the cylindrical joint $U$, the axis numbers are indicated sequentially according to the rule of "stationary → moving". In the motion coordinate system Below is written as The formula for obtaining the vector of the joint axis is as follows: ; In the above formula, R The attitude change matrix of the moving platform is defined as follows: , and Let the precession angle, nutation angle, and rotation angle in the attitude change matrix represent the motion characteristics of the parallel robot in its spinor system. , , , , and Six independent parameters determine and describe the motion of the moving platform relative to the frame, with the centers of motion joints on both the stationary and moving platforms corresponding to the endpoints of each branch. and Let i = 1, 2, ..., n, and be related to the geometric centers of the moving platform and the static platform, respectively. and A vector closed-loop equation is formed, as shown in the following formula: ; The position vector in the above formula and Rewritten as follows: ; In the above formula, Indicates the radius of the static platform. This represents the radius of the moving platform, combining the formulas for the vectors of the joint axes, the vector closed-loop equations, and the position vectors mentioned above. and The inverse position equation and driving parameters of the parallel robot are derived. The generalized representation using scale and position parameters is as follows: ; In the above formula, This represents the inverse kinematics of a parallel robot. Indicates the first t The range of motion of a passive joint; Indicates the first t The range of motion of each passive joint; Indicates the first i The motion range of each active joint is calculated using a workspace hierarchical search algorithm. The motion ranges of the passive and active joints are obtained through inverse kinematics calculations. Based on this, a workspace prediction function is derived. The formula is as follows: ; In the above formula, This represents the independent variable characterizing the motion of the moving platform; This indicates the range of motion of the joint; l and m Representing the number of passive and active joints respectively, the workspace prediction function... Constraints are imposed by the range of motion of passive joints and the range of motion of active joints.

[0017] The development method for the kinematics analysis module: Hybrid programming is implemented using COM (Component Object Model). This requires ensuring the MATLAB version is compatible with the compiler used in the RAPRDev platform development and that MATLAB has a Compiler CDK. After verifying the compiler, the .m files are converted to .Function files. After verifying the C++ compiler, the compilation language and filename are set in the CDK, and then the .Function files are packaged into a dynamic link library file. .dll).

[0018] Add the above in the QT integrated development environment. .dll files are shared libraries and dependencies are automatically added. Data transfer between components and the platform is primarily achieved through the mwArray class. It is a core data type in the MATLAB mathematical library, automatically handling memory allocation and deallocation, and supporting all MATLAB data types (numerical matrices, strings, structures, cell arrays, etc.). It serves as a parameter container for C++ calls to MATLAB functions during mixed programming. It calls the MATLAB Runtime library to load workspace point cloud matrix data and display the workspace convex hull image on the interactive interface.

[0019] The scale design module transforms the topological configuration into structural parameters. Based on the distance between different branches of the parallel robot, the moving platform and the static platform are defined using the structural parameters. The scale factor is set to normalize the radius of the moving platform and the static platform. The kinematic analysis module calculates the global dexterity and selects the radius of the moving platform and the static platform that meets the global dexterity requirement as the design parameters. The given workspace prediction function is searched hierarchically using the kinematic analysis module. The range of motion and dimensional parameters of each joint affect the average dexterity across the entire range. To facilitate visualization of dexterity, the parameters need to be normalized based on the structure of the moving or static platform, and a scale factor needs to be defined. , … It is expressed as follows: ; In the above formula, This represents the nth design parameter. This represents the nth scaling factor. Norm This indicates that the design parameters are normalized to a scaling factor; in a perfectly driven system, the spinor of the end effector is determined by the angular velocity of the moving platform. linear velocity at the geometric center point Composition, in the On each branch, Indicates the first The rotational range of motion of each joint, and Indicates the first The immobile rotation of each joint and This forms a 6-DOF spinor space, and the motion spinor of the moving platform The formula is as follows: ; In the above formula, Indicates the first i The number of degrees of freedom of each branch. This indicates that the driving system is the first jr Each drive joint speed Indicates by the first Each branch provides the driving spin of the moving platform, and the driving spin of the moving platform is related to the motion spin of its own joints. Collinear, orthogonal to the other movable spinors; Indicates the first i Each branch provides a constraint spindle to the moving platform, which is related to the movable spindle on that branch. Duality yields the following formula: ; Based on the above description of the exact driving system, the driving Jacobian matrix of the exact driving system is... and constrained Jacobian matrix They are represented as follows: ; ; The system's general Jacobian matrix With the motion spinor of the moving platform Multiplying them together, we get the following formula: ; Choose three non-collinear geometric centers to connect each branch to the joint of the moving platform. , and These points, as characteristic motion points of the platform, are in the moving coordinate system Position vector in , and Forming the motion representation matrix of the moving platform as follows: ; Obtain the homogeneous Jacobian matrix of the driving system It is expressed as follows: ; ; In the above formula, For a matrix, In Represented as a rotation matrix; for this just-driven system, the local flexibility is the reciprocal of the condition number of the homogeneous Jacobian matrix under the current attitude, and the local flexibility... The formula is as follows: ; Since redundantly driven parallel robots have multiple drive systems, selecting the subsystem with the highest dexterity as the drive system yields the following overall local dexterity at the current pose. The formula is as follows: ; In the above formula, This indicates the exact number of drive systems in the redundantly driven parallel robot, where the subscript... m To drive the number of sidechains, superscript n For the number of degrees of freedom of the robot, This indicates the redundant drive parallel robot. n The local dexterity of a given drive system is determined by the fact that the dexterity value changes with attitude. To measure the kinematic performance across the entire range, the average dexterity value across the entire range is taken as the performance index, as shown in the following formula: ; In the above formula, This represents the average dexterity across the entire domain. d μ The higher the value, the greater the dexterity within the workspace.

[0020] The development method for the scale module: Hybrid programming is implemented using COM (Component Object Model). This requires ensuring the MATLAB version is compatible with the compiler used in RAPRDev platform development and that MATLAB has a Compiler CDK. After verifying the compiler, the .m files are converted to .Function files. After verifying the C++ compiler, the compilation language and filename are set in the CDK, and then the .Function files are packaged into a dynamic link library file. .dll).

[0021] Add the above in the QT integrated development environment. .dll files are shared libraries and dependencies are automatically added. Data transfer between components and the platform is primarily achieved through the mwArray class. It is a core data type in the MATLAB mathematical library, automatically handling memory allocation and deallocation, and supporting all MATLAB data types (numerical matrices, strings, structures, cell arrays, etc.). It serves as a parameter container for C++ calls to MATLAB functions during mixed programming.

[0022] The system receives design parameters such as workspace, joint range of motion, and step length. Functions written using the EIGEN library convert these parameters into mwArray variables, which are then passed to the MATLAB-packaged component. The MATLAB calculation engine is then invoked to generate dexterity data. To avoid redundant calculations, the calculated dexterity data needs to be saved separately. The resulting data matrix is ​​then converted back from mwArray to Eigen::Matrix<> variables and saved to an Access database. When plotting the graph, the MATLAB engine is invoked again to obtain the global dexterity mean image.

[0023] For redundant-drive parallel robots, the dexterity calculation model changes with the configuration. Equations (10), (12), and (13) are used to calculate the global dexterity mean at the current scale. Within this framework, the external module (MATLAB engine) is highly decoupled from the internal program. Despite differences in models between configurations, and even differences in the number of scale factors, this part can be replaced. The .dll file can be used to switch between different models, greatly reducing the difficulty of subsequent expansion.

[0024] The structural design module uses design parameters to select, parametrically model, and automatically assemble the components of the parallel robot, generating a 3D model. The finite element analysis module then performs finite element analysis on the 3D model; if the results do not meet the requirements, the model is modified. The implementation process of the structural design module is as follows: it is mainly based on the existing SolidWorks API, and the specific content is as follows: Component selection function: During the design process, the components that need to be selected are named in the format of "type + installation location + model" and saved as SLDPRT format to the SW component image library. Since component selection requires comparison from multiple sources, in order to enable users to quickly view component images on the platform, a copy is saved as an STL format file to the OpenGL component visualization library. Subsequently, an independent component selection library is created using Access software, recording the index position of all components, the index position of the STL file, the index and position of replaceable components, and related parameters. Parametric modeling function: This function sets the parameters of a component, then maps the changes of the model structure caused by the parameters to all parts of the component, draws them one by one, and saves them as .STL files; Automated assembly: During parametric modeling, datum elements are added to parts according to a uniform pattern and named appropriately. These elements are selected directly by retrieving the project name. In parametric modeling, each part in both the component library and the self-selected component library needs a Flag data item to verify whether the updated part can be correctly assembled with its child / parent components. The Flag numbering rules are as follows: Parent component: 1_location_child component name_child component location_fit type; Sub-component: 2_Point_Parent component name_Parent component point_Match type; After completing the parameterization settings, all parts of the above types need to have their Flags verified to match the parent / child components before automatic assembly.

[0025] The finite element analysis module, based on the 3D model in the structural design module, performs preprocessing and finite element analysis on the 3D model to obtain finite element analysis contour plots. The finite element analysis process is as follows: (a) Model preprocessing: including component isolation, component deletion and feature removal, component renaming, component merging and feature addition, the specific process is as follows: (1) Component Independence: When a model is imported from SolidWorks into SpaceClaim, even if it is imported through an intermediate file, multiple components (parts or assemblies) may still reference the same source file. These components appear as "instances" in SpaceClaim, seemingly independent, but in fact sharing geometric definitions. This means that modifying one component will synchronously update all components of the same source.

[0026] (2) Component deletion and feature removal: These are used to delete detailed features (such as small chamfers, small fillets, small holes, small bosses, and small grooves) and components (such as standard parts, non-load-bearing parts, and non-structural parts) that have little impact on the simulation analysis results, thereby improving mesh quality and solver computational efficiency, and ensuring the smooth completion of finite element analysis. Deleting components in advance can reduce the amount of computation when SpaceClaim selects features through PowerSelection.

[0027] (3) Component renaming: Components are renamed using a standardized format to ensure that most entity names are unique. Then, the GetObjectByName() method is used to quickly retrieve some components, which reduces the selection range of PowerSelection during feature selection and is a necessary operation before feature removal. The naming rule is: 1_Level 1 Assembly Name / Entity + Current Parent Component's Same Type Component / Entity Number_2_Level 2 Assembly / Entity Name + Current Parent Component's Same Type Component / Entity Number_…_n_Level n Assembly / Entity Name + Current Parent Component's Same Type Component / Entity Number.

[0028] (4) Component Merging: Component merging combines multiple components into a single entity, eliminating their assembly relationships. Its significance complements that of component independence. Due to the complex structure of redundant parallel mechanisms, even after component deletion, there are still a large number of parts, resulting in a lengthy model tree that affects the efficiency of finite element script development. Merging components with similar materials and minimal constraint influence can reduce the amount of subsequent script development and improve the computational efficiency of the finite element analysis module.

[0029] (5) Feature Addition: When using x_t as an intermediate file, some feature information in SolidWorks may be lost. Therefore, the CAD functions of SpaceClaim can be used to repair some of the lost information. Using SpaceClaim Script for targeted repair, the target entity can be obtained by name traversal, and then the geometric center of the entity can be calculated using a weighted centroid method, binding it to the origin of the local coordinate system. The absolute coordinate system information of the x_t file will not be lost, and the axis direction of the newly created local coordinate system is the same as that of the absolute coordinate system by default. The local coordinate system axis is calculated and fixed using a rotation matrix method.

[0030] (ii) Finite element analysis of the three-dimensional model: Mechanical is a module in Ansys Workbench used for structural mechanics and dynamics analysis, providing a wide range of analysis functions, including statics, dynamics, and modal analysis. The automated preprocessing and finite element analysis of the RAPRDev platform are based on this module.

[0031] (1) Select elements using the WorkSheet method of the NS(Named Selection) object.

[0032] (2) After implementing the scripting of SpaceClaim, Mechanical, and Workbench, a database-driven automatic script generation scheme is proposed to support automated collaborative analysis across users and scenarios. This scheme constructs a highly reusable parametric finite element analysis workflow through the decoupling design of parameter configuration and script execution logic.

[0033] Phase 1: The system categorizes user input parameters into two types: basic parameters and derived parameters. Basic parameters are directly written to the corresponding fields in the database using QSqlQuery; derived parameters, on the other hand, require preprocessing calculations by the kinematics analysis module and the structural design module before the results are stored in the database.

[0034] Phase 2: An interactive database management mechanism is adopted to support user read and write operations on data. The system architecture includes three core components: the AccessData class acts as the main controller, responsible for database connection (QSqlDatabase) and maintaining the material data cache (MaterialList); the PythonScriptGenerator class is dedicated to data formatting, ensuring that the output conforms to Python syntax specifications; and the ScriptFileHandler class provides complete file operation support, including template reading, script writing, and syntax validation.

[0035] Phase 3: The system executes according to the standardized data processing flow: (1) responding to user operations to trigger script generation; (2) querying the database to obtain parameter data; (3) formatting the query results; (4) merging the formatted data with the template; (5) outputting the final script file.

[0036] (3) Automatic script loading: ①The Workbench script sends the script address directly to the submodule via the RunScript method to run the SC and Mechanical scripts; ② The RAPRDev platform loads Workbench scripts by running batch files.

[0037] Integrated Design Module: Based on database functionality, it enables data exchange and conversion between different modules, provides a user interface and design reports. The user interface allows users to input configuration features and displays topological configurations, design parameters, 3D models, kinematic performance images, and finite element analysis cloud maps during the design process.

[0038] Development Methodology of Integrated Design Module: The 3D visualization function of the RAPRDev platform uses OpenGL as the underlying graphics interface, and a 3D rendering function system is built in ImageFrame.cpp. The ImageFrame class initializes the OpenGL environment by overriding the initializeGL() method, configuring lighting parameters (ambientLight[], diffuseLight[]) and projection matrix, establishing a standardized coordinate system (world coordinate system ±900 units, model coordinate system ±300 units), and improving rendering efficiency through the unified material management interface setupColor(). Interactive control is achieved through event overloading to realize viewpoint transformation: dragging with the left mouse button triggers mouseMoveEvent() to realize model rotation (calculating the angle difference dx / dy), the right mouse button controls setZoom() to realize view distance adjustment, and the middle mouse button calls setXYTranslate() to realize view translation. The rotation angle is standardized by normalizeAngle() to ensure that the angle value is within the range of (0,360). The key rendering logic is implemented in paintGL(). The ImageFrame class initializes the OpenGL environment by overriding the initializeGL() method, configuring lighting parameters (ambientLight[], diffuseLight[]) and projection matrix, establishing a normalized coordinate system (world coordinate system ±900 units, model coordinate system ±300 units), and improving rendering efficiency through the unified material management interface setupColor(). Interactive control is achieved through event overloading: left-click drag triggers mouseMoveEvent() to rotate the model (calculating the angle difference dx / dy), right-click controls setZoom() to adjust the viewing distance, and middle-click calls setXYTranslate() to complete view translation. The rotation angle is normalized using normalizeAngle() to ensure the angle value is within the range (0, 360). Key rendering logic is implemented in paintGL().

[0039] Specific design experiments were conducted, using 2UPR-2RPS as the design object and employing the design platform of this application. Figure 3-8 , Figure 3 This indicates a 2UPR-2RPS configuration. Figure 4 This indicates 2UPR-2RPS scale optimization. Figure 5 This indicates a 2UPR-2RPS workspace estimate. Figure 6 Indicates structural design, Figure 7 This is a diagram showing the results of the finite element analysis. Figures 8 to 11This is a schematic diagram of the static analysis results. Through the complete digital design process described above, the operational stability, functional completeness, and design practicality of each module of the platform have been fully verified.

[0040] Therefore, this invention adopts a redundant drive parallel robot digital platform design system. Taking the 2UPR-2RPS parallel robot as an example, the digital platform is developed and the prototype is designed. The test results fully verify the operational stability, functional integrity and design practicality of each module of the platform.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A redundant-driven parallel robot digital platform design system, characterized in that: Includes the following modules: The RAPRDev platform is designed as a digital platform for parallel robots, including a configuration selection module, a scale design module, a kinematics analysis module, a structural design module, and a finite element simulation analysis module. The above modules are integrated through an integrated design environment module to realize the design of parallel robots. The configuration selection module allows users to input the configuration features of the parallel robot, parametrically represent the joints and branches of the parallel robot, obtain motion screws, obtain constraint screws based on the motion screws, and obtain the topological configuration through the constraint screws. The topological configuration includes the selected joint types. The kinematics analysis module provides a general abstract model for the inverse kinematics solution of parallel robots based on the closed-loop vector method and a dynamic cyclic hierarchical search platform compatible with multi-degree-of-freedom workspace estimation, providing a kinematics analysis process for the scale design module. The scale design module transforms the topological configuration into structural parameters. Based on the distance between different branches of the parallel robot, the moving platform and the static platform are defined using the structural parameters. The scale factor is set to normalize the radius of the moving platform and the static platform. The kinematic analysis module calculates the global dexterity and selects the radius of the moving platform and the static platform corresponding to the global dexterity that meets the conditions as the design parameters. The structural design module uses design parameters to perform actual selection, parametric modeling, and automatic assembly of the components of the parallel robot. Generate a 3D model, perform finite element analysis on the generated 3D model using the finite element analysis module, and modify the model if the finite element analysis results do not meet the requirements. The finite element analysis module, based on the 3D model in the structural design module, performs preprocessing and finite element analysis on the 3D model to obtain finite element analysis cloud diagrams, providing finite element analysis results for the structural design module. Integrated Design Module: Based on database functionality, it enables data exchange and storage between the different modules mentioned above, and provides a user interface and design report. The user interface displays input configuration features, topological configurations, design parameters, 3D models, kinematic performance images, and finite element analysis cloud maps during the design process. The design report compiles the content displayed in the user interface into a report.

2. The redundant drive parallel robot digital platform design system according to claim 1, characterized in that: The implementation process of the configuration selection module is as follows: To avoid illegal connections, the input configuration features are checked. Rotor theory is uniformly used to parameterize the motion characteristics of parallel robots. In parallel robots, the spinor of a joint motion... The formula is as follows: ； In the above formula, S Let be the direction vector of the kinematic pair position. Indicates rotation about the spinor axis r × S and moving parallel to the spinor axis pS Composition, in which Represents the position vector of any point on the axis of rotation. The pitch is represented by the linear rotation; the moving spin is represented as zero. Rotational spin due to its displacement A value of 0 indicates that... Define a general spinor system as follows: ； In the above formula, The motion screw represents the actual motion state of the nth joint in a parallel robot. The motion screw is used to describe the actual motion state of each joint in a parallel robot system. The constraint screw represents the constraint state on the system's motion caused by structural limitations. The constraint screw system of a parallel robot is considered as the common constraint on the overall motion of all joint constraint screws within the parallel robot. Therefore, the overall constraint screw system is the union of the local constraint screw systems formed by each joint and branch. The formula is as follows: ； In the above formula, the superscript r Represents a locally constrained spinor system, with subscripts. n Indicates the first n The motion screw system of a parallel robot is considered as the motion existing in all components within the robot, and the overall motion screw system is the intersection of the local motion screw systems formed by each joint and branch. The formula is as follows: ； The above formula In the middle, superscript m Represents the local rotational system of motion, with subscripts. n Indicates the first n In the motion mode analysis of parallel robots, solving the motion screw system of the moving platform requires overcoming the complexity brought about by the common constraints between series branches. A method of finding the inverse screw system twice is used to obtain the final overall motion screw system. Specifically, the constraint screw system is determined by solving the inverse screw system of each branch's motion screw system. Then, the overall constraint screw system is derived by synthesizing the constraint screw systems of each branch. Finally, the overall motion screw system is obtained through inverse screw calculation. k The parallel robot has a linearly independent system of local motion spinors. k Based on the above calculations and analysis, the redundant-drive parallel robot with [number] degrees of freedom is abstracted into the following topology: [structure of the robot with] redundant drive parallel robots. n Composed of active branch chains k The formula for the drive redundancy in a parallel robot with multiple degrees of freedom is as follows: ； Use the above formula to filter out topological configurations that meet the conditions.

3. The redundant drive parallel robot digital platform design system according to claim 2, characterized in that: The workflow of the kinematic analysis module is as follows: Establish a fixed coordinate system at the geometric center of the static platform. Establish a motion coordinate system at the geometric center of the moving platform. And sorted by branches in order, with the direction from the static platform to the moving platform as the positive z-axis, and so on. The geometric center pointing towards the joint between the branch and the static platform is defined as the positive x-axis, where... and These represent the centers of the moving joints installed on the static and moving platforms, respectively, in a fixed coordinate system. The position vector and the position unit vector are respectively and In the moving coordinate system, The position vector and the position unit vector are respectively and Geometric center of the moving platform The position vector is Vector use To indicate, Let represent the direction vector of the j-th motion axis of the i-th branch, where the first motion axis represents the motion axis fixed to the moving platform, and the last motion axis represents the motion axis fixed to the static platform. In the motion coordinate system Below is written as The formula for obtaining the vector of the joint axis is as follows: ； In the above formula, R The attitude change matrix of the moving platform is defined as follows: , and Let the precession angle, nutation angle, and rotation angle in the attitude change matrix represent the motion characteristics of the parallel robot in its spinor system. , , , , and Six independent parameters determine and describe the motion of the moving platform relative to the frame, with the centers of motion on both the stationary and moving platforms corresponding to the endpoints of each branch. and Let i = 1, 2, ..., n, and be related to the geometric centers of the moving platform and the static platform, respectively. and A vector closed-loop equation is formed, as shown in the following formula: ； The position vector in the above equation and Rewritten as follows: ； In the above formula, Indicates the radius of the static platform. This represents the radius of the moving platform, combining the formulas for the vectors of the joint axes, the vector closed-loop equations, and the position vectors mentioned above. and The inverse position equation and driving parameters of the parallel robot are derived. The generalized representation using scale and position parameters is as follows: ； In the above formula, This represents the inverse kinematics of a parallel robot. Indicates the first t The range of motion of a passive joint; Indicates the first t The range of motion of each passive joint; Indicates the first i The motion range of each active joint is calculated using a workspace hierarchical search algorithm. The motion ranges of the passive and active joints are obtained through inverse kinematics calculations. Based on this, a workspace prediction function is derived. The formula is as follows: ； In the above formula, This represents the independent variable characterizing the motion of the moving platform; This indicates the range of motion of the joint; l and m Representing the number of passive and active joints respectively, the workspace prediction function... Constraints are imposed by the range of motion of passive joints and the range of motion of active joints.

4. The redundant drive parallel robot digital platform design system according to claim 3, characterized in that: The workflow of the scale design module is as follows: The given workspace prediction function is searched hierarchically using the kinematic analysis module. The range of motion and dimensional parameters of each joint affect the average dexterity across the entire range. To facilitate visualization of dexterity, the parameters need to be normalized based on the structure of the moving or static platform, and a scale factor needs to be defined. , … It is expressed as follows: ； In the above formula, This represents the nth design parameter. This represents the nth scaling factor. Norm This indicates that the design parameters are normalized to a scaling factor; in a perfectly driven system, the spinor of the end effector is determined by the angular velocity of the moving platform. linear velocity at the geometric center point Composition, in the On each branch, Indicates the first The rotational range of motion of each joint, and Indicates the first The immobile rotation of each joint and This forms a 6-DOF spinor space, and the motion spinor of the moving platform The formula is as follows: ； In the above formula, Indicates the first i The number of degrees of freedom of each branch. This indicates that the driving system is the first j r Each drive joint speed Indicates by the first Each branch provides the driving spin of the moving platform, and the driving spin of the moving platform is related to the motion spin of its own joints. Collinear, orthogonal to the other movable spinors; Indicates the first i Each branch provides a constraint spindle to the moving platform, which is related to the movable spindle on that branch. Duality yields the following formula: ； Based on the above description of the exact driving system, the driving Jacobian matrix of the exact driving system is... and constrained Jacobian matrix They are represented as follows: ； ； The system's general Jacobian matrix With the motion spinor of the moving platform Multiplying them together, we get the following formula: ； Choose three non-collinear geometric centers to connect each branch to the joint of the moving platform. , and These points, as characteristic motion points of the platform, are in the moving coordinate system Position vector in , and Forming the motion representation matrix of the moving platform as follows: ； Obtain the homogeneous Jacobian matrix of the driving system It is expressed as follows: ； ； In the above formula, For a matrix, In Represented as a rotation matrix; for this just-driven system, the local flexibility is the reciprocal of the condition number of the homogeneous Jacobian matrix under the current attitude, and the local flexibility... The formula is as follows: ； Since redundantly driven parallel robots have multiple drive systems, selecting the subsystem with the highest dexterity as the drive system yields the following overall local dexterity at the current pose. The formula is as follows: ； In the above formula, This indicates the exact number of drive systems in the redundantly driven parallel robot, where the subscript... m To drive the number of sidechains, superscript n For the number of degrees of freedom of the robot, This indicates the redundantly driven parallel robot. n The local dexterity of a given drive system is determined by the fact that the dexterity value changes with attitude. To measure the kinematic performance across the entire range, the average dexterity value across the entire range is taken as the performance index, as shown in the following formula: ； In the above formula, This represents the average agility across the entire domain. d μ The higher the value, the greater the dexterity within the workspace.

5. The redundant drive parallel robot digital platform design system according to claim 1, characterized in that: The implementation process of the structural design module is as follows: Component selection function: During the design process, the components that need to be selected are named in the format of "type + installation location + model" and saved as SLDPRT format to the SW component image library. Since component selection requires comparison from multiple sources, in order to enable users to quickly view component images on the platform, a copy is saved as an STL format file to the OpenGL component visualization library. Subsequently, an independent component selection library is created using Access software, recording the index position of all components, the index position of the STL file, the index and position of replaceable components, and related parameters. Parametric modeling function: This function sets the parameters of a component, then maps the changes of the model structure caused by the parameters to all parts of the component, draws them one by one, and saves them as .STL files; Automated assembly: During parametric modeling, datum elements are added to parts according to a uniform pattern and named appropriately. These elements are selected directly by retrieving the project name. In parametric modeling, each part in both the component library and the self-selected component library needs a Flag data item to verify whether the updated part can be correctly assembled with its child / parent components. The Flag numbering rules are as follows: Parent component: 1_location_child component name_child component location_fit type; Sub-component: 2_Point_Parent component name_Parent component point_Match type; After completing the parameterization settings, all parts of the above types need to have their Flags verified to match the parent / child components before automatic assembly.

6. The redundant drive parallel robot digital platform design system according to claim 1, characterized in that: The process of the finite element analysis is as follows: First, model preprocessing is performed, including component isolation, component deletion and feature removal, component renaming, component merging, and feature addition. The specific process is as follows: Component independence: When a model is imported from SolidWorks into SpaceClaim, even if it is imported through an intermediate file, parts or assemblies in multiple components may reference the same source file. They need to be handled independently to avoid referencing issues. Component removal and feature removal: Used to remove detailed features that have little impact on simulation analysis results, including small chamfers, small fillets, small holes, small bosses, small grooves, as well as standard parts, non-load-bearing parts, and non-structural parts in components, thereby improving mesh quality and solver computational efficiency, ensuring the smooth completion of finite element analysis, removing components in advance, and reducing the amount of computation when SpaceClaim selects features through PowerSelection; Component renaming: Components are renamed using a standardized method to ensure unique entity names. Then, the GetObjectByName method is used to quickly retrieve some components. Reducing the selection range of PowerSelection during feature selection is a necessary operation before feature removal. The naming rules are as follows: 1_Level 1 Assembly Name / Entity + Number of Components / Entities of the Same Type under the Current Parent Component_2_Level 2 Assembly Name / Entity + Number of Components or Entities of the Same Type under the Current Parent Component_…_n_Level n Assembly Name / Entity + Number of Components / Entities of the Same Type under the Current Parent Component; Component merging: Component merging is the process of integrating multiple components into a single entity, eliminating their assembly relationships. Its significance is complementary to that of component independence. Feature addition: For the problem of some feature information being lost, SpaceClaim's CAD function is used to repair the lost information, and SpaceClaim Script is used for targeted repair. Finite element analysis of a 3D model Mechanical is a module in Ansys Workbench used for structural mechanics and dynamics analysis. It provides a wide range of analysis functions, including statics, dynamics, and modal analysis. The automated preprocessing and finite element analysis of the RAPRDev platform are based on this module. Phase 1: The system divides user input parameters into two categories: basic parameters and derived parameters. Basic parameters are directly written into the corresponding fields of the database; derived parameters need to be preprocessed and calculated by the kinematic analysis module and the structural design module before the results are stored in the database. Phase 2: An interactive database management mechanism is adopted to support user read and write operations on data. The system architecture includes three core components: the main controller, which is responsible for connecting to the database QSqlDatabase and maintaining the material data cache MaterialList; data formatting to ensure that the output conforms to the syntax specification; and the ScriptFileHandler class, which provides complete file operation support, including template reading, script writing and syntax validation. Phase 3: The system executes according to the standardized data processing flow: (1) Responding to user actions triggers script generation; (2) Query the database to obtain parameter data; (3) Format the query results; (4) Merge the formatted data with the template; (5) Output the final design report.

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