A structural design method of a large-load large-platform redundant drive parallel robot

Abstract

The application relates to the technical field of automation, and particularly provides a structural design method of a large-load large-platform redundant drive parallel robot, which comprises the following steps: S1, establishing a parameterized dynamic model of the redundant drive parallel robot; S2, giving the end trajectory and stress condition of the parallel robot, and using the inverse solution of the parallel robot dynamics and combining an existing drive force optimization distribution method to calculate the drive force of each supporting leg and coordinately distributing the redundant drive force; and S3, taking the square sum of the drive force of each supporting leg as an objective function, and using an intelligent optimization algorithm to optimize the structural parameters. The application can make the distribution of the drive force of each supporting leg more uniform and reasonable, and can meet the design requirements of the redundant parallel robot under a large-load working condition.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automation, in particular to a structure design method of a large-load large-platform redundant drive parallel robot. BACKGROUND

[0002] Parallel robots have high rigidity, high bearing capacity, high precision, good dynamic response, low motion inertia and many other advantages, making them widely used in parallel machine tools, optical precision pointing, micro-positioning and motion simulation of large equipment such as aircraft, tanks, infantry fighting vehicles, etc. Redundant drive parallel robots can increase the bearing capacity of the structure by using redundant drive without increasing the driving capacity of the driver, to meet the needs of motion simulation and pointing positioning of large equipment such as aircraft, tanks, infantry fighting vehicles, large optical instruments, etc.

[0003] At present, redundant drive parallel robots are widely used, but the research on their structure design is still relatively less. The common structure design methods of redundant drive parallel robots in the prior art are mainly empirical method and parameter optimization method, of which the parameter optimization method is relatively more scientific and has more development potential. The existing parameter optimization methods include: 1) taking the condition number of the Jacobian matrix as the objective function, and using genetic algorithm for parameter optimization; 2) taking the force transmission performance index as the objective function, and optimizing the rod parameters; 3) considering the line velocity transmission and force transmission performance, and optimizing the structure parameters by principal component analysis method; 4) taking the velocity, driving force and power as the objective function, and optimizing the structure parameters; 5) taking the leg extension amount and driving power as the objective function, and optimizing the structure parameters. Although the above parameter optimization methods can meet the structure optimization needs of some redundant drive parallel robots, in heavy load working conditions, the leg forces need to be studied in detail, and the above methods still have great defects.

[0004] In summary, how to propose a structure design method of a redundant drive parallel robot to meet the performance requirements of the parallel robot under large load and large platform is a problem to be solved at present. SUMMARY

[0005] To solve the above problems, the present application provides a structure design method of a large-load large-platform redundant drive parallel robot, which can meet the design requirements of the redundant parallel robot under large load working conditions.

[0006] A structure design method of a large-load large-platform redundant drive parallel robot, comprising the following steps:

[0007] S1: establishing a parameterized dynamics model of the redundant drive parallel robot;

[0008] S2: calculating the driving force of each leg of the parallel robot, and coordinating and distributing the redundant driving force;

[0009] S3: Using the minimum sum of squares of the driving forces of each leg as the objective function, the structural parameters are optimized using an intelligent optimization algorithm.

[0010] Preferably, in step S2, given the end-effector trajectory and force conditions of the parallel robot, the driving force of each leg is calculated using the inverse kinematics of the parallel robot and combined with the existing optimization distribution method of driving force.

[0011] Preferably, existing methods for optimizing the allocation of driving forces include the generalized inverse method, the least 2 norm method, the weighted pseudo-inverse method, the Lagrange coefficient method, or the direct substitution method.

[0012] Preferably, in S1, the initial parameterized dynamic model of the redundant-driven parallel robot is established using the d'Alembert principle-virtual displacement principle method.

[0013] Beneficial effects of this invention:

[0014] 1. The present invention uses the minimum sum of squares of the driving forces of each leg as the objective function, which is more reasonable than the objective function of existing structural optimization methods and is more suitable for the design requirements of heavy load conditions.

[0015] 2. After optimizing the allocation of redundant driving forces, this invention optimizes the structural parameters by minimizing the sum of the squares of the driving forces of each leg. Compared with existing structural parameter optimization methods, this invention adds a driving force optimization allocation step, which can make the distribution of driving forces of each leg more uniform and reasonable. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the design process of the redundant drive parallel robot structure design method in this embodiment of the invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the following description is provided in conjunction with the appendix. Figure 1 The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and do not constitute a limitation thereof.

[0018] A structural design method for a large-load, large-platform redundant-drive parallel robot is presented in this embodiment, using a 6-DOF, 12-drive redundant parallel robot as an example. Those skilled in the art can also design other redundant-drive parallel robots using this structural design method. The parallel robot includes an upper platform, a lower platform, and multiple legs connecting the upper and lower platforms. Each leg includes an upper leg connected to the upper platform and a lower leg connected to the lower platform. The upper and lower legs are connected to the upper and lower platforms respectively via hinges. The specific steps include:

[0019] S1: Establishing an initial parameterized dynamics model of the redundant drive parallel robot by using the principle of D' Alembert - virtual displacement principle method.

[0020] S2: Given the end trajectory and force of the parallel robot, the driving force of each leg is calculated by using the inverse dynamics of the parallel robot combined with the existing driving force optimization distribution method to coordinate and distribute the redundant driving force; wherein the existing driving force optimization distribution method includes the generalized inverse method, the least two norm method, the weighted pseudo-inverse method, the Lagrange coefficient method or the direct replacement method.

[0021] S2 includes the following sub-steps:

[0022] S21: Given the motion trajectory and force of the upper platform of the parallel robot, the initial parameterized dynamics model is shown in formula (1):

[0023]

[0024] Wherein, is the virtual work of the leg driving force, is the virtual work of the external force and external torque of the moving platform, is the virtual work of the inertial force and inertial torque of the moving platform, which is the upper platform of the parallel robot, is the virtual work of the external force and inertial force on the centroid of the upper leg, is the virtual work of the inertial torque of the upper leg, is the virtual work of the external force and inertial force on the centroid of the lower leg, is the virtual work of the inertial torque of the lower leg.

[0025] S22: Let f D = [f D1 f D2 … f D12 ] T , then The inverse velocity Jacobian matrix is transposed into a force Jacobian matrix and brought into formula (1) to obtain formula (2):

[0026]

[0027] Wherein, is the transposed inverse velocity Jacobian matrix, is the transposed inverse velocity Jacobian matrix of the centroid of the upper leg, is the transposed inverse angular velocity Jacobian matrix of the leg, is the transposed inverse velocity Jacobian matrix of the centroid of the lower leg, f D is the driving force of each leg; in the above formula, the transposed Jacobian matrix is determined by the pose of the hinge points on the upper platform and the lower platform of the parallel robot, the pose between the upper platform and the lower platform, and the pose of the upper platform, that is, it is directly related to the structural parameters of the parallel robot.

[0028] S23: The driving force is distributed in the dynamic model of formula (2) using the generalized inverse method, and the driving force f of each leg of the parallel robot is calculated by formula (3). D To coordinate and distribute redundant driving forces:

[0029]

[0030] in, Since The generalized inverse law.

[0031] S3: Using the minimum sum of squares of the driving forces of each leg as the objective function, the structural parameters are optimized using an intelligent optimization algorithm.

[0032] After initially determining the driving force f of each leg... D After that, with Using the minimum as the objective function, an intelligent optimization algorithm is used to optimize the hinge point poses on the upper and lower platforms of the parallel robot, as well as the poses between the upper and lower platforms, to obtain the optimal hinge point poses and the poses between the upper and lower platforms. This completes the structural design of a 6-DOF 12-redundant driven parallel robot under given end-effector motion trajectory and force conditions on the upper platform. Those skilled in the art can also design other redundant driven parallel robots using the above design method.

[0033] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0034] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A structural design method for a large-load, large-platform redundantly driven parallel robot, characterized in that, Includes the following steps: S1: Establish a parameterized dynamic model for the redundant-driven parallel robot; S2: Calculate the driving force of each leg of the parallel robot and coordinate the distribution of redundant driving forces; given the end-effector trajectory and force conditions of the parallel robot, use the inverse kinematics of the parallel robot and existing methods for optimizing the distribution of driving forces to calculate the driving force of each leg; specifically including: S21: Given the motion trajectory and forces acting on the end effector of the platform in a parallel robot, the initial parameterized dynamic model is as follows: in, The virtual work done by the supporting leg's driving force The virtual work done by the moving platform under external forces and torques, This refers to the virtual work done by the inertial force and torque of the moving platform, where the moving platform is the upper platform of the parallel robot. The work done by the external force and inertial force on the center of mass of the upper support leg is virtual. This is the virtual work done by the inertial torque of the upper support leg. The work done by the external force and inertial force on the center of mass of the lower support leg is virtual. This is the virtual work done by the inertial torque of the lower support leg; S22: Let f D =[f D1 f D2 …f D12 ] T ,but Substituting the inverse velocity Jacobian matrix into the force Jacobian matrix and replacing it with formula (1) yields formula (2): in, This is the transpose of the inverse velocity Jacobian matrix. The transpose of the Jacobian matrix of the inverse velocity of the center of mass of the upper support leg. The inverse angular velocity Jacobian matrix of the outrigger is transposed. f is the transpose of the Jacobian matrix of the inverse velocity of the lower outrigger's center of mass. D The driving force of each leg; the transpose of the Jacobian matrix in the above formula is determined by the pose of the hinge points on the upper and lower platforms of the parallel robot, the pose between the upper and lower platforms, and the pose of the upper platform, which is directly related to the structural parameters of the parallel robot. S23: The driving force is distributed in the dynamic model of formula (2) using the generalized inverse method, and the driving force f of each leg of the parallel robot is calculated by formula (3). D To coordinate and distribute redundant driving forces: in, That is The generalized inverse law; S3: Using the minimum sum of squares of the driving forces of each leg as the objective function, the structural parameters are optimized using an intelligent optimization algorithm. The poses of the hinge points on the upper and lower platforms of the parallel robot, as well as the poses between the upper and lower platforms, are optimized to obtain the optimal hinge point poses and the poses between the upper and lower platforms.

2. The structural design method for a large-load, large-platform redundant-drive parallel robot according to claim 1, characterized in that, Existing methods for optimizing the allocation of driving forces include the generalized inverse method, the least 2 norm method, the weighted pseudo-inverse method, the Lagrange coefficient method, or the direct substitution method.

3. The structural design method for a large-load, large-platform redundant-drive parallel robot according to claim 2, characterized in that, In S1, the initial parameterized dynamic model of the redundant-driven parallel robot is established using the d'Alembert principle-virtual displacement principle method.

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