A method for optimizing the design of balance force parameters of a robotic arm follow-up suspension system

Abstract

A method for optimizing the design of balancing force parameters of a manipulator follower suspension system comprises the following steps: designing a ground test manipulator configuration and path, and generating a joint angle data file; establishing a parameterized manipulator dynamics model in ADAMS, and importing the joint angle data file; further establishing a parameterized follower suspension system dynamics model; saving the model as a standard dynamics model for calculating the joint torque during the manipulator test under the effects of gravity and the follower suspension system; and designing an objective function, calling the standard dynamics model, and employing an intelligent optimization algorithm to determine the optimal balancing force of the follower suspension system.

Description

Technical Field

[0001] The invention relates to a method for optimizing the design of balance force parameters of a follow-up suspension system of a robotic arm, and belongs to the technical field of space robotic arms. Background Art

[0002] During the development of a space robotic arm, it is typically mounted on a satellite or a simulated wall to conduct ground-based tests such as precision calibration, performance testing, and functional verification. Space robotic arms are designed for the weightless environment of space, and during ground-based testing, a servo suspension system is often used for gravity compensation, simulating the microgravity of space.

[0003] The servo suspension system uses a gravity balance device to compensate for the gravity of the manipulator's joints and arm. The manipulator and its servo suspension system, under the combined effects of balancing force and gravity, present a complex multi-body dynamics system. One of the challenges in conducting ground-based tests of space manipulators using a servo suspension system is selecting the balancing force, a design process that requires parameter optimization. Improper balancing force can generate significant forces and torques at various joints, potentially causing the drive motor to malfunction or even damaging the manipulator.

[0004] After searching, it was found that the information about the follow-up suspension system of the ground test of the space manipulator was mainly based on hardware implementation such as the gravity balance device, but no optimization design method for the balance force parameters of the manipulator follow-up suspension system was found. Summary of the Invention

[0005] The technical problem solved by the present invention is: in view of the technical defects of the current prior art in the optimization design technology of the balance force parameters of the manipulator follow-up suspension system, a method for optimizing the balance force parameters of the manipulator follow-up suspension system is proposed.

[0006] The present invention solves the above technical problems by the following technical solutions:

[0007] A method for optimizing the design of balancing force parameters of a robotic arm follower suspension system includes:

[0008] Design the manipulator configuration and motion path for ground tests, and generate joint angle data for the manipulator;

[0009] Establish a dynamic model of the robotic arm in a gravity environment and input joint angle data;

[0010] A dynamic model of the follower suspension system is established, which is used together with the dynamic model of the robotic arm as a standard dynamic model to calculate the joint torque data of the robotic arm during movement under the action of any set of external balancing force parameters.

[0011] The joint torque data output by the standard dynamics model is used as input, and the objective function is designed. The objective function value corresponding to the joint torque data is calculated. The balancing force parameters are updated through the intelligent optimization algorithm, and a set of balancing force parameters that minimizes the objective function value is selected as the optimal balancing force of the follow-up suspension system.

[0012] The mechanical arm dynamics model is established according to the mechanical arm kinematic parameters and dynamic parameters. The mechanical arm dynamics model is set on an external base, and the base is set on a simulation wall or an air floating platform.

[0013] The dynamic model of the follow-up suspension system includes a gravity balance mechanism model and a balance force equivalent model. The modeling method of the gravity balance mechanism model is as follows:

[0014] Each gravity balancing mechanism is equivalent to an equal number of mass points, which are connected to the robot arm connecting rod in the robot arm dynamics model through a fixed pair. The mass and installation parameters of each mass point are preset to determine the gravity balancing mechanism model.

[0015] The modeling method of the equilibrium force equivalent model is specifically as follows:

[0016] The steel wire rope that applies the balancing force to the follow-up suspension system is simplified into an external force acting in the opposite direction of gravity and on the gravity balancing mechanism. The magnitude of each force is set as a design variable, and an equivalent model of the balancing force is established.

[0017] The dynamic model of the robotic arm and the dynamic model of the follower suspension system are integrated into a standard dynamic model through ADAMS and called. A simplified set of external force values ​​is used as model input, and a set of torque data of each joint of the robotic arm is obtained as output.

[0018] The objective function specifically includes:

[0019] Based on the objective function of optimizing the joint torque extreme value or the objective function of optimizing the joint torque average extreme value, the gravity compensation effect of a group of follow-up suspension systems under the balance force is evaluated by the joint torque extreme value or the joint torque average extreme value, respectively, where:

[0020] The objective function based on the optimal extreme value of joint torque is specifically:

[0021] τ f =max(τ ij )

[0022] In the formula, max(τ ij ) is the maximum absolute value of all joint torques in a set of joint torque data.

[0023] The objective function based on the optimal average range of joint torque is specifically:

[0024]

[0025] Where, τ jmax and τ jmin is the maximum and minimum value of the torque applied to joint j in a set of joint torque data, and n is the degree of freedom of the robotic arm.

[0026] The intelligent optimization algorithm is a particle swarm optimization algorithm, which is implemented using a linearly decreasing dynamic inertia weight strategy.

[0027] The specific method of calling the standard kinetic model is:

[0028] Create a batch file run.bat to automatically start ADAMS at runtime and exit ADAMS after ADAMS finishes running;

[0029] Initialize or optimize the updated equilibrium force vector F = ■F1F2F k ■F q ■, where q is the number of gravity balancing mechanisms;

[0030] Create the ADAMS command script file aview.cmd, open the standard dynamics model after ADAMS starts, assign each element of the equilibrium force vector F to the q design variables representing the equilibrium force magnitude of the standard dynamics model, perform simulation calculations, and output the joint torque data file Tz_GuanJie.txt;

[0031] Run the batch file run.bat to call the ADAMS standard dynamics model;

[0032] Continue searching for the joint torque data file Tz_GuanJie.txt until the data file is found, completing a standard dynamics model call of ADAMS.

[0033] Calling the standard dynamics model, processing joint torque data to calculate the objective function value, and using the optimization algorithm to update the balance force parameters are all implemented through Matlab simulation. Among them, the command for calling the ADAMS standard dynamics model in batch mode in the Matlab simulation environment is system('run.bat').

[0034] The advantages of the present invention compared with the prior art are:

[0035] (1) The present invention provides a method for optimizing the design of the balance force parameters of a manipulator follow-up suspension system. By using the mechanical system virtual prototype ADAMS modeling and mathematical optimization, suitable balance force parameters are designed and obtained as the force input of the follow-up suspension system for a space manipulator ground test, ensuring that each joint of the manipulator does not bear excessive torque during the test. The method is easy to implement and has significant effects. The mechanical system virtual prototype software ADAMS is used to realize the standard dynamics integrated modeling of the follow-up suspension system for a space manipulator ground test, avoiding the tedious mathematical derivation process and making the physical meaning more intuitive and clear.

[0036] (2) The present invention quantitatively evaluates the gravity compensation effect of a set of follow-up suspension systems under the action of the balancing force by calculating the objective function value, taking into account the joint torque information of the entire process of the manipulator ground test operation task, thereby avoiding the possibility of missing excessive joint torque when only considering a few task configurations, and making more effective use of data information;

[0037] (3) The present invention uses a particle swarm algorithm to optimize the balance force parameters of the manipulator's follow-up suspension system, and designs a set of globally optimal balance force parameters as the force input of the follow-up suspension system for the ground test of the space manipulator, ensuring that the joints of the manipulator do not bear excessive torque during the test. The implementation is easy and the effect is significant. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the space manipulator and ground test follow-up suspension system provided for the invention;

[0039] Figure 2 Schematic diagram of the seven-degree-of-freedom robotic arm and connecting rod coordinate system provided for the invention;

[0040] Figure 3 A flow chart of the method for optimizing the design of the balance force parameters of the robotic arm follower suspension system provided by the invention;

[0041] Figure 4 A schematic diagram of the time-joint angle planning curve of the manipulator for the ground test mission provided by the invention;

[0042] Figure 5 A schematic diagram of the installation parameters of the gravity balancing mechanism provided for the invention;

[0043] Figure 6 Schematic diagram of the ADAMS standard dynamic model of the manipulator-follower suspension system provided for the invention;

[0044] Figure 7 A schematic diagram of the operation flow of the particle swarm algorithm provided for the invention;

[0045] Figure 8A schematic diagram of the joint torque curve of the manipulator arm when conducting a ground test without using a follow-up suspension system in an embodiment of the invention;

[0046] Figure 9 A schematic diagram of a mechanical arm joint torque curve when a follow-up suspension system is set according to the balance force parameter 1 and a ground test is carried out in accordance with the embodiment of the invention;

[0047] Figure 10 A schematic diagram of a mechanical arm joint torque curve when a follow-up suspension system is set according to the balance force parameter 2 and a ground test is carried out in accordance with the embodiment of the invention; DETAILED DESCRIPTION

[0048] A method for optimizing the design of the balancing force parameters of a manipulator's servo suspension system is proposed. During ground tests of a space manipulator, appropriate balancing force parameters are designed through ADAMS modeling and mathematical optimization of a virtual prototype of the mechanical system. These parameters serve as the force input for the manipulator's servo suspension system during ground tests, ensuring that the manipulator's joints are not subjected to excessive torque. The method is easy to implement and has significant effects.

[0049] The specific process of parameter optimization design method is as follows:

[0050] Design the manipulator configuration and motion path for ground tests, and generate joint angle data for the manipulator;

[0051] Establish a dynamic model of the robotic arm in a gravity environment and input joint angle data;

[0052] A dynamic model of the follower suspension system is established, which is used together with the dynamic model of the robotic arm as a standard dynamic model to calculate the joint torque data of the robotic arm during movement under the action of any set of external balancing force parameters.

[0053] The joint torque data output by the standard dynamics model is used as input, and the objective function is designed. The objective function value corresponding to the joint torque data is calculated. The balancing force parameters are updated through the intelligent optimization algorithm, and a set of balancing force parameters that minimizes the objective function value is selected as the optimal balancing force of the follow-up suspension system.

[0054] Among them, the dynamic model of the manipulator is established according to the manipulator configuration, all motion paths, and the joint angle data corresponding to each motion path. The dynamic model of the manipulator is set on an external base, which is set on a simulation wall or an air floating platform;

[0055] The dynamic model of the follow-up suspension system includes a gravity balance mechanism model and a balance force equivalent model. The modeling method of the gravity balance mechanism model is as follows:

[0056] Each gravity balance mechanism is equivalent to an equal number of mass points, which are connected to the manipulator link in the manipulator dynamics model through a fixed pair. The mass and installation parameters of each mass point are preset to determine the gravity balance mechanism model.

[0057] The modeling method of the equilibrium force equivalent model is as follows:

[0058] The steel wire rope that applies the balancing force to the follow-up suspension system is simplified into an external force acting in the opposite direction of gravity and on the gravity balancing mechanism. The magnitude of each force is set as a design variable, and an equivalent model of the balancing force is established.

[0059] The dynamic model of the robotic arm and the dynamic model of the follower suspension system are integrated into a standard dynamic model through ADAMS and called. A simplified set of external force values ​​is used as model input, and a set of torque data of each joint of the robotic arm is obtained as output.

[0060] The objective function specifically includes:

[0061] Based on the objective function of optimizing the joint torque extreme value or the objective function of optimizing the joint torque average extreme value, the gravity compensation effect of a group of follow-up suspension systems under the balance force is evaluated by the joint torque extreme value or the joint torque average extreme value, respectively, where:

[0062] The objective function based on the optimal extreme value of joint torque is specifically:

[0063] τ f =max(τ ij )

[0064] In the formula, max(τ ij ) is the maximum absolute value of all joint torques in a set of joint torque data;

[0065] The objective function based on the optimal average range of joint torque is specifically:

[0066]

[0067] Where, τ jmax and τ jmin is the maximum and minimum value of the torque on joint j in a set of joint torque data, and n is the degree of freedom of the robotic arm;

[0068] The intelligent optimization algorithm is the particle swarm algorithm, which is implemented using a linearly decreasing dynamic inertia weight strategy;

[0069] The specific method of calling the standard kinetic model is:

[0070] Create a batch file run.bat to automatically start ADAMS at runtime and exit ADAMS after ADAMS finishes running;

[0071] Generate the equilibrium force vector F=■F1F2F according to the equilibrium force equivalent model k ■F q ■, where q is the number of gravity balancing mechanisms;

[0072] Create the ADAMS command script file aview.cmd, open the standard dynamics model after ADAMS starts, assign each element of the equilibrium force vector F to the q design variables representing the equilibrium force magnitude of the standard dynamics model, perform simulation calculations, and output the joint torque data file Tz_GuanJie.txt;

[0073] Run the batch file run.bat to call the ADAMS standard dynamics model;

[0074] Continue searching for the joint torque data file Tz_GuanJie.txt until the data file is found, completing a call to the ADAMS standard dynamics model.

[0075] Calling the standard dynamics model, processing joint torque data to calculate the objective function value, and using the optimization algorithm to update the balance force parameters are all achieved through Matlab simulation. The command for calling the ADAMS standard dynamics model in batch mode in the Matlab simulation environment is system('run.bat');

[0076] The following is further described based on specific embodiments:

[0077] In order to better understand the technical solution of the present invention, the present invention is further described in detail with reference to the accompanying drawings and preferred embodiments, specifically:

[0078] In this embodiment, Figure 1 The space manipulator and the ground test servo suspension system are shown as the objects. The base of the manipulator is installed on the simulation wall, and the end of the manipulator is free.

[0079] like Figure 1 As shown in Table 1, the space manipulator is a seven-degree-of-freedom serial manipulator. The kinematic parameters (improved DH coordinates) and dynamic parameters of the manipulator are shown in Table 1 and Table 2, respectively. According to the improved DH coordinate rule, the link coordinate system is established, as shown in Table 2. Figure 2 shown.

[0080] Table 1 Kinematic parameters of the robotic arm (improved DH coordinates)

[0081]

[0082] Table 2 Dynamic parameters of the robotic arm

[0083]

[0084]

[0085] like Figure 3 As shown in the flowchart, in an embodiment of the present invention, the method for optimizing the design of the balancing force parameters of the robotic arm follower suspension system includes the following steps:

[0086] Step 101: Design the ground test manipulator configuration and path, and generate joint angle data files.

[0087] The key configurations of the ground test manipulator are shown in Table 3 below. Based on the segmented point-to-point quintic polynomial interpolation algorithm, a program was written in Matlab to perform joint space path planning for the test process. The time-joint angle sequence curve obtained by planning is shown in Figure 4 As shown, the planning results are saved as the joint angle data file Thetad_GuanJie.txt.

[0088] Table 3 Joint angle sequence of key configurations of the ground test manipulator

[0089]

[0090] Step 102: Establish a parameterized robotic arm dynamics model in ADAMS and import the joint angle data file.

[0091] Based on the kinematic and dynamic parameters of the manipulator shown in Tables 1 and 2, a dynamic model of the seven-degree-of-freedom manipulator was established using the mechanical system dynamics analysis software ADAMS. The model used the improved DH coordinates as design variables and parameterized all model elements, including the coordinate system, geometry, kinematic pairs, and driving forces. According to the S1 configuration data in Table 3, the design variables corresponding to each joint angle were modified to adjust the initial configuration of the manipulator. The joint angle data file Thetad_GuanJie.txt described in step 101 was imported into ADAMS, and the time-joint angle data was created as a SPLINE spline curve, which was then introduced into the manipulator joint motion drive.

[0092] Step 103: further establish a parameterized dynamic model of the follow-up suspension system.

[0093] A dynamic model of the follower suspension system is established based on the parameterized ADAMS dynamic model of the manipulator established in step 102. The dynamic model of the manipulator follower suspension system includes two parts: a simplified model of the gravity balance mechanism and an equivalent model of the balance force.

[0094] like Figure 1As shown, the follow-up suspension system has three gravity balance mechanisms. Mechanism 1 is connected to connecting rod 3, mechanism 2 is connected to connecting rod 4, and mechanism 3 is connected to connecting rod 7. The installation parameters of each gravity balance mechanism on the robot arm are as follows: Figure 5 The mass parameters of the gravity balance mechanism are shown in Table 4.

[0095] Table 4 Mass parameters of gravity balance mechanism

[0096] Gravity balancing mechanism 1 Gravity balancing mechanism 2 Gravity balance mechanism 3 Mass (kg) 6.8 6.0 7.8

[0097] The simplified model of the gravity balance mechanism. The specific modeling method is as follows:

[0098] Ignoring the specific configuration of the mechanism, it is equivalent to three mass points and connected to the corresponding connecting rods of the robotic arm through fixed pairs. The position of each mass point matches the installation parameters of each gravity balance mechanism on the robotic arm connecting rod. The mass of each mass point is consistent with the mass parameters of each gravity balance mechanism, and its inertia tensor is not considered. For convenience of display, a spherical geometric outline is created at the simplified three mass points for illustration.

[0099] The coordinate system of the equivalent mass of the gravity balance mechanism is parameterized and the position vector of mass 1 relative to the connecting rod coordinate system {3} is: 3 d 1dd =

[60800] , the position vector of mass point 2 relative to the connecting rod coordinate system {4} is 4 d 2dd = [101600], the position vector of mass point 3 relative to the connecting rod coordinate system {7} is 7 d 3dd =[00-243.2].

[0100] The equivalent model of the balanced force, the specific modeling method is as follows:

[0101] The follow-up suspension system applies a balancing force through steel wire ropes. The lower end of the steel wire ropes is connected to the gravity balance mechanism, and the upper end is connected to the follow-up guide rail. In ADAMS, the force of each steel wire rope is simplified into an external force, which acts on the equivalent mass points of the three gravity balance mechanisms respectively. The force direction type is set to fixed in space, opposite to the direction of gravity, and the force function is set as a design variable to achieve equivalent modeling of the balancing force.

[0102] The coordinate systems of the balancing forces are associated with the equivalent mass points of the three gravity balancing mechanisms to achieve parametric modeling of the three balancing forces.

[0103] Step 104: Save the model as a standard dynamics model.

[0104] After the parameterized ADAMS dynamic model of the manipulator and follower suspension system is established, it is saved as a .bin file as a standard dynamic model for subsequent use. The model contains all the kinematic and dynamic information of the manipulator and follower suspension system, as well as all the manipulator configuration and joint path information required for ground testing; the ADAMS standard dynamic model is as follows: Figure 6 As shown in Figure 2, it is used to calculate the joint torque of the manipulator during the test process under the action of gravity and the follow-up suspension system.

[0105] Step 105: Design an objective function, call the standard dynamics model to output the joint torque and calculate the objective function value, and use an intelligent optimization algorithm to determine the optimal balancing force of the follow-up suspension system.

[0106] The method of calling the standard kinetic model is as follows:

[0107] (1) Create a text file in advance, named run.bat, with the following content:

[0108] ……\common\mdi aviewru-s b aview.cmd e

[0109] “…” is the installation path of the ADAMS software in the computer. This file will not be modified after it is created;

[0110] (2) Generate the equilibrium force vector F = [F1F2F3] using Matlab;

[0111] (3) Assume that the joint torque data file is named Tz_GuanJie.txt. Use Matlab commands to search for the data file in the current path. If it is not found, execute (4) directly. If it is found, delete the data file and then execute (4).

[0112] (4) Use Matlab to create an ADAMS command script file named aview.cmd. The command script file contains three parts: modifying the design variables corresponding to each equilibrium force according to the vector F, performing simulation calculations, and outputting the joint torque data file;

[0113] (5) Execute the statement system('run.bat') in Matlab. The computer will run the ADAMS software in the background in batch mode, execute the aview.cmd command file, call the standard dynamics model, modify the parameters of each equilibrium force and calculate;

[0114] (6) Continue searching for the joint torque data file Tz_GuanJie.txt in the current path until the data file is found, which indicates that the call of the standard dynamics model is completed.

[0115] The objective function is designed as follows:

[0116] Assume that the degree of freedom of the manipulator is n. In this embodiment, n=7. The joint torque data file has a total of w lines. Read the joint torque data file to obtain the joint torque matrix τs, which is expressed as:

[0117]

[0118] where τ j is the moment sequence of joint j under the action of the equilibrium force F during the test, which is a column vector of w×1;

[0119] Extract the j-th column joint torque τ in τs j The maximum value τ jmax and the minimum value τ jmin , design objective function 1:

[0120]

[0121] Extract the maximum absolute value of all joint torques in τs and design objective function 2:

[0122] τ f =max(τ ij )

[0123] Using the objective function τ f Measure the effect of the balancing force F on the gravity balance of the robotic arm during the test.

[0124] The process of calling the standard dynamics model is equivalent to executing a function operation. This function has no specific expression. Instead, it is based on virtual prototype technology to encapsulate the ADAMS dynamics model of the robotic arm follow-up suspension system into a black box, input a set of balancing forces, output the joint torque of the robotic arm test process, and calculate the objective function value.

[0125] The intelligent optimization algorithm is a particle swarm algorithm, which adopts a linear decreasing dynamic inertia weight strategy. The operation flow chart of the particle swarm algorithm of the embodiment of the present invention is as follows: Figure 7 The main parameters of the particle swarm algorithm are shown in Table 5. The equilibrium force vector F is a particle of the particle swarm algorithm, and the designed objective function τ f is the fitness function of the particle swarm algorithm; assuming that the maximum range of the spring scale and force sensor of the gravity balance mechanism of the follow-up suspension system is 400N, the parameters of the balance force are optimized in the range of 200N to 400N to determine the optimal balance force parameter F best , so that the objective function τ f Minimum.

[0126] Table 5 Particle Swarm Algorithm Parameters

[0127]

[0128]

[0129] According to Figure 3 、 Figure 7 The algorithm flow shown in the figure uses objective function 1 and objective function 2 as the fitness function of the particle swarm algorithm, uses Matlab to call the ADAMS standard dynamics model, and optimizes two sets of balance force parameters, as shown in Table 6.

[0130] Table 6 Two sets of balance force parameters after optimization of objective function 1 and objective function 2

[0131]

[0132] If the follow-up suspension system is not used and the ground test of the space manipulator is carried out directly, the joint torque curve during the task under the gravity of each link is as follows: Figure 8 The joint torque range is shown in Table 7.

[0133] Table 7 Joint torque range of the manipulator during the ground test (without using the follow-up suspension system)

[0134]

[0135]

[0136] It can be seen from Table 7 that when the follow-up suspension system is not used, the maximum joint torque during the ground test mission is greater than 1500 Nm, which far exceeds the bearing capacity of the space manipulator and will cause joint damage.

[0137] Use the follow-up suspension system to carry out ground tests of the space manipulator, and set the balance force F according to parameter 1. best =[318.85298.87332.29], the joint torque curve of the task process is as follows Figure 9 The torque range of each joint is shown in Table 8; set the balance force F according to parameter 2 best =[351.70271.04349.11], the joint torque curve of the task process is as follows Figure 10 The torque range of each joint is shown in Table 9.

[0138] Table 8 Joint torque range of the manipulator during the ground test (balance force parameter 1)

[0139]

[0140] Table 9 Joint torque range of the manipulator during the ground test (balance force parameter 2)

[0141]

[0142] Tables 8 and 9 show that when the follow-up suspension system is used, when objective function 1 is used as the optimization indicator and the balancing force is set according to parameter 1, during the ground test of the manipulator, the torque of joint 1 is the largest, approximately 20 Nm, and the maximum torques of the other joints are approximately 10 Nm. When objective function 2 is used as the optimization indicator and the balancing force is set according to parameter 2, during the ground test of the manipulator, the torques of the joints are relatively uniform, and the maximum torque is less than 10 Nm.

[0143] When different objective functions are selected as optimization indicators, the optimal balance force parameters obtained by design are different; in this embodiment, the follow-up suspension system is set according to the two sets of balance force parameters to carry out ground tests, and the torque of each joint is within the bearing capacity of the space robot arm, which can ensure the safety of the robot arm.

[0144] Of course, in other embodiments of the present invention, the designed objective function may also be in other forms, which does not affect the implementation of the embodiments of the present invention.

[0145] It can be seen from the above embodiments that, by using the method provided by the present invention, appropriate balancing force parameters can be designed through ADAMS modeling and mathematical optimization of the mechanical system virtual prototype, and used as the force input of the follow-up suspension system for the ground test of the space manipulator, ensuring that the joints of the manipulator do not bear excessive torque during the test. The method is easy to implement and has significant effects.

[0146] The above content is only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

[0147] Although the present invention has been disclosed above in terms of preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solutions of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the scope of protection of the technical solutions of the present invention.

[0148] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for optimizing the design of balance force parameters of a robotic arm follow-up suspension system, characterized in that include: Design the manipulator configuration and motion path for ground tests, and generate joint angle data for the manipulator; Establish a dynamic model of the robotic arm in a gravity environment and input joint angle data; A dynamic model of the follower suspension system is established, which is used together with the dynamic model of the robotic arm as a standard dynamic model to calculate the joint torque data of the robotic arm during movement under the action of any set of external balancing force parameters. Using the joint torque data output by the standard dynamics model as input, an objective function is designed and the objective function value corresponding to the joint torque data is calculated. The balancing force parameters are updated using an intelligent optimization algorithm, and the set of balancing force parameters that minimizes the objective function value is selected as the optimal balancing force for the follow-up suspension system. The mechanical arm dynamics model is established according to the mechanical arm kinematic parameters and dynamic parameters, and the mechanical arm dynamics model is set on an external base, and the base is set on a simulation wall or an air floating platform; The dynamic model of the follow-up suspension system includes a gravity balance mechanism model and a balance force equivalent model. The modeling method of the gravity balance mechanism model is as follows: Each gravity balance mechanism is equivalent to an equal number of mass points, which are connected to the manipulator link in the manipulator dynamics model through a fixed pair. The mass and installation parameters of each mass point are preset to determine the gravity balance mechanism model. The modeling method of the equilibrium force equivalent model is specifically as follows: The steel wire rope that applies the balancing force to the follow-up suspension system is simplified into an external force acting in the opposite direction of gravity and on the gravity balancing mechanism. The magnitude of each force is set as a design variable, and an equivalent model of the balancing force is established. The dynamic model of the manipulator and the dynamic model of the follower suspension system are integrated into a standard dynamic model through ADAMS and called. A simplified set of external force values ​​is used as the model input, and a set of torque data of each joint of the manipulator is obtained as the output. The objective function specifically includes: Based on the objective function of optimizing the joint torque extreme value or the objective function of optimizing the joint torque average extreme value, the gravity compensation effect of a group of follow-up suspension systems under the balance force is evaluated by the joint torque extreme value or the joint torque average extreme value, respectively, where: The objective function based on the optimal extreme value of joint torque is specifically: t f =max(|τ ij |) In the formula, max(|τ ij |) is the maximum absolute value of all joint torques in a set of joint torque data; The specific method of calling the standard kinetic model is: Create a batch file run.bat to automatically start ADAMS at runtime and exit ADAMS after ADAMS finishes running; Initialize or optimize the updated equilibrium force vector F = [F1 F2 … F k … F q ], where q is the number of gravity balancing mechanisms; Create the ADAMS command script file aview.cmd, open the standard dynamics model after ADAMS starts, assign each element of the equilibrium force vector F to the q design variables representing the equilibrium force magnitude of the standard dynamics model, perform simulation calculations, and output the joint torque data file Tz_GuanJie.txt; Run the batch file run.bat to call the ADAMS standard dynamics model; Continue searching for the joint torque data file Tz_GuanJie.txt until the data file is found, completing a call to the ADAMS standard dynamics model; Calling the standard dynamics model, processing joint torque data to calculate the objective function value, and using the optimization algorithm to update the balance force parameters are all implemented through Matlab simulation. Among them, the command for calling the ADAMS standard dynamics model in batch mode in the Matlab simulation environment is system('run.bat').

2. The method for optimizing the design of the balancing force parameters of a robotic arm follower suspension system according to claim 1, characterized in that: The objective function based on the optimal average range of joint torque is specifically: Where, τ jmax and τ jmin is the maximum and minimum value of the torque applied to joint j in a set of joint torque data, and n is the degree of freedom of the robotic arm.

3. The method for optimizing the design of the balancing force parameters of a robotic arm follower suspension system according to claim 2, characterized in that: The intelligent optimization algorithm is a particle swarm optimization algorithm, which is implemented using a linearly decreasing dynamic inertia weight strategy.

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