Industrial robot rigidity identification method, device and system, control equipment and medium

Abstract

The invention provides an industrial robot rigidity identification method, device and system, control equipment and a medium, and belongs to the technical field of robots. The method comprises the following steps: acquiring a DH parameter of the industrial robot to determine a plurality of Jacobian matrixes corresponding to a plurality of preset configuration positions of the industrial robot; after the industrial robot is controlled to reach each preset configuration position, first tail end pose data of the industrial robot in the no-load state and tail end stress data and second tail end pose data of the industrial robot when the tail end of the industrial robot is subjected to external force applied by the winch device are obtained; error solving optimization is carried out according to the first tail end pose data and the second tail end pose data, and actual tail end pose deformation data is obtained; and solving according to the plurality of Jacobian matrixes, the plurality of tail end pose deformation data and the plurality of tail end stress data corresponding to the plurality of preset configuration positions of the industrial robot to obtain a rigidity identification result of the industrial robot. The rigidity identification precision and efficiency of the industrial robot can be improved.

Description

Technical Field

[0001] The present application relates to the field of robotics, and in particular to a method, device, system, control equipment, and medium for identifying stiffness of an industrial robot. Background Art

[0002] In existing technology, the actual end-position deformation data of an industrial robot is typically obtained by directly subtracting the data before and after loading. This data is then combined with the end-position force data after loading to determine the stiffness of the industrial robot. However, current stiffness identification uses a single and uncontrollable force condition, which affects the accuracy of stiffness identification. Furthermore, the end-position data of an industrial robot is generally expressed in Euler angles. Directly subtracting the end-position data before and after loading can lead to confusion in the angle range, resulting in inaccurate stiffness identification results. Summary of the Invention

[0003] The main purpose of this application is to propose an industrial robot stiffness identification method, device, system, control equipment and medium, aiming to improve the stiffness identification accuracy and efficiency of industrial robots.

[0004] To achieve the above objectives, one aspect of the present application provides a method for identifying stiffness of an industrial robot, the method comprising:

[0005] Obtaining DH parameters of the industrial robot to determine a plurality of Jacobian matrices corresponding to the industrial robot at a plurality of preset configuration positions;

[0006] After controlling the industrial robot to reach each of the preset configuration positions, firstly obtaining first terminal position data of the industrial robot when unloaded, then obtaining terminal force data and second terminal position data of the industrial robot after loading when the terminal of the industrial robot is subjected to an external force applied by a hoist device, and then performing error solution optimization based on the first terminal position data and the second terminal position data to obtain terminal position deformation data of the industrial robot in Cartesian space caused by the force;

[0007] The stiffness identification result of the industrial robot is obtained by solving the multiple Jacobian matrices, the multiple terminal posture deformation data and the multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions.

[0008] Furthermore, the first terminal posture data includes first terminal position data and first terminal posture data, and the second terminal posture data includes second terminal position data and second terminal posture data; and the error solution optimization is performed based on the first terminal posture data and the second terminal posture data to obtain the terminal posture deformation data of the industrial robot in the Cartesian space caused by the force, including:

[0009] Calculating a posture conversion matrix based on the first terminal posture data;

[0010] performing error solving based on the first terminal posture data and the second terminal posture data, and then optimizing the error solving result based on the posture transformation matrix to obtain terminal posture deformation data;

[0011] The terminal position deformation data is determined according to the first terminal position data, the second terminal position data and the terminal posture deformation data.

[0012] Furthermore, the stiffness identification result of the industrial robot is obtained by solving the multiple Jacobian matrices, the multiple terminal posture deformation data, and the multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions, including:

[0013] Obtaining a stiffness identification mathematical model of the industrial robot, which is used to characterize the relationship between the end position deformation of the industrial robot and the Jacobian matrix, the end force and the joint stiffness;

[0014] Substituting multiple Jacobian matrices, multiple terminal posture deformation data, and multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions into the stiffness identification mathematical model of the industrial robot to construct an overdetermined set of equations;

[0015] The overdetermined set of equations is solved to obtain joint stiffness data of the industrial robot.

[0016] Furthermore, the stiffness identification mathematical model of the industrial robot is obtained by the following method:

[0017] Obtaining a predetermined first, second, third, and fourth relationship, wherein the first relationship is used to characterize the relationship between the end force of the industrial robot and the Cartesian stiffness matrix and the end posture deformation; the second relationship is used to characterize the relationship between the joint torque of the industrial robot and the joint stiffness matrix and the joint angle deformation; the third relationship is used to characterize the relationship between the joint torque of the industrial robot and the Jacobian matrix and the end force; and the fourth relationship is used to characterize the relationship between the end posture deformation of the industrial robot and the Jacobian matrix and the joint angle deformation;

[0018] The third relational expression is derived with respect to the joint angle, and then a conversion analysis is performed based on the derivative result, the first relational expression, the second relational expression, and the fourth relational expression to obtain a stiffness identification mathematical model of the industrial robot.

[0019] To achieve the above objectives, another aspect of the present application provides an industrial robot stiffness identification device, the device comprising:

[0020] The first module is used to obtain DH parameters of the industrial robot to determine a plurality of Jacobian matrices corresponding to the industrial robot at a plurality of preset configuration positions;

[0021] a second module, configured to control the industrial robot to reach each of the preset configuration positions, first obtain first terminal position data of the industrial robot when unloaded, then obtain terminal force data and second terminal position data of the industrial robot after loading when the terminal of the industrial robot is subjected to an external force applied by a hoist device, and then perform error solution optimization based on the first terminal position data and the second terminal position data to obtain terminal position deformation data of the industrial robot in Cartesian space caused by the force;

[0022] The third module is used to solve the multiple Jacobian matrices, multiple terminal posture deformation data and multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions to obtain the stiffness identification result of the industrial robot.

[0023] To achieve the above-mentioned purpose, another aspect of the present application provides a control device, which is used to implement the above-mentioned industrial robot stiffness identification method.

[0024] To achieve the above-mentioned object, another aspect of the present application provides an industrial robot stiffness identification system, the system comprising a hoist device, a six-dimensional force / torque sensor, a posture acquisition device, and the above-mentioned control device;

[0025] The six-dimensional force / torque sensor is used to collect the end force data of the industrial robot and transmit it to the control device; the posture acquisition device is used to collect the end posture data of the industrial robot and transmit it to the control device; the control device is used to generate a control signal based on the error between the preset end expected force data and the end force data of the industrial robot transmitted by the six-dimensional force / torque sensor, and transmit it to the winch device; the winch device is used to apply external force to the end of the industrial robot according to the control signal.

[0026] Furthermore, the hoist device includes a hoist, a servo motor and a servo drive, the hoist has a drum, and the drum is connected to the end of the industrial robot via a steel cable;

[0027] The servo driver is used to drive the servo motor to rotate according to the control signal, and the servo motor is used to drive the reel to rotate in a rotating state to synchronously wind the steel cable to apply external force to the end of the industrial robot.

[0028] Furthermore, the posture acquisition device includes a laser tracker and a laser tracking target adapted thereto.

[0029] To achieve the above-mentioned purpose, another aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned industrial robot stiffness identification method is implemented.

[0030] This application has at least the following beneficial effects: By optimizing the error solution of the end-point pose data of an industrial robot before and after loading, more reliable end-point pose deformation data can be obtained. This data, combined with the Jacobian matrix of the industrial robot and its end-point force data after loading, can be solved to improve the stiffness identification accuracy of the industrial robot. By utilizing a control device, a hoist device, and a six-dimensional force / torque sensor to achieve closed-loop force control, and then applying a stable and adjustable external force to the end-point of the industrial robot, the deformation properties of each joint of the industrial robot can be effectively stimulated, the efficiency of stiffness identification of the industrial robot can be improved, and the industrial robot body can be effectively protected from damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a flow chart of a method for identifying stiffness of an industrial robot provided in an embodiment of the present application;

[0032] Figure 2 Schematic diagram of the composition of an industrial robot stiffness identification device provided in an embodiment of the present application;

[0033] Figure 3 This is a schematic diagram of the composition of an industrial robot stiffness identification system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are merely examples of devices, systems and methods that are consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0035] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0036] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0038] Before explaining the embodiments of the present application in detail, some of the nouns and terms involved in the embodiments of the present application are first explained. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0039] Denavit-Hartenberg (DH) parameters describe the geometric relationship between the joints and linkages of industrial robots. They primarily define the relative position and rotation of each joint using four parameters: linkage offset, linkage length, torsion angle, and joint angle. The introduction of DH parameters makes the kinematic equations of industrial robots more unified and simplified.

[0040] The Jacobian matrix, used to describe the relationship between the joint velocities and the end-effector velocities of an industrial robot, is typically represented as a 6×n partial derivative matrix, where n is the number of joints in the industrial robot. Each row of the Jacobian matrix corresponds to a linear velocity component and an angular velocity component of the end-effector in Cartesian space. The construction of the Jacobian matrix facilitates forward and inverse kinematic analysis of industrial robots.

[0041] The robot's terminal posture deformation data refers to the angular velocity of the robot's terminal posture data before and after loading. It is obtained by the terminal angular rotation velocity vector and the transformation matrix. The terminal angular rotation velocity vector is the difference in the robot's terminal Euler angles before and after loading.

[0042] High-precision industrial robots rely on flexibility compensation, which requires not only an accurate dynamic model but also precise robot joint stiffness. The weak stiffness of industrial robots is a major factor affecting their precision. The flexibility they exhibit is the result of the combined effects of joint and link flexibility. For most industrial robots, links have sufficient rigidity, and the robot's flexible deformation is primarily caused by joint flexibility. Therefore, obtaining accurate joint stiffness values ​​is crucial for improving the precision of industrial robots, such as compensating for joint flexibility errors.

[0043] In the existing technology, the end-position data of the industrial robot before and after loading are usually directly obtained and subtracted to obtain the actual end-position deformation data, and then the stiffness of the industrial robot is identified by combining the end-force data of the industrial robot after loading. However, since the end-position data of the industrial robot is generally expressed in the form of Euler angles, if the end-position data of the industrial robot before and after loading are directly subtracted, it will lead to angle range confusion problems (such as angle periodicity problems, universal joint lock problems, etc.), thereby causing inaccurate stiffness identification results of the industrial robot.

[0044] Furthermore, in order to deform the joints of an industrial robot during the joint stiffness identification process, an external pulling force must be applied to the robot. For this reason, some researchers have proposed applying external force by directly hanging a fixed load on the end of the robot. However, the external force generated by the fixed load cannot exert a torsional torque on the first joint of the industrial robot, making it impossible to identify the stiffness of the first joint. Other researchers have proposed using a pulley device to apply external force to the end of the industrial robot. However, this requires controlling the force applied to the end of the industrial robot by installing loads of varying masses, making this inefficient.

[0045] In view of this, the embodiments of the present application provide an industrial robot stiffness identification method, device, system, control equipment and medium. By introducing a winch device to apply external force to the end of the industrial robot during actual application, and introducing an error solution optimization mechanism to determine the end posture deformation data of the industrial robot, it is beneficial to improve the stiffness identification accuracy and efficiency of the industrial robot.

[0046] The present application provides an industrial robot stiffness identification method, which relates to the field of robotics technology and can be applied to a terminal or a server, or can be software running on a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet computer, laptop computer, desktop computer, etc., but is not limited thereto; the server side can be configured as an independent physical server, or as a server cluster or distributed system consisting of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application that implements the above method, etc., but is not limited to the above forms.

[0047] See also Figure 1 , Figure 1 This is an optional flow chart of an industrial robot stiffness identification method provided in an embodiment of the present application. The method may include, but is not limited to, the following steps S101 to S103:

[0048] Step S101: obtaining DH parameters of the industrial robot to determine a plurality of Jacobian matrices corresponding to the industrial robot at a plurality of preset configuration positions;

[0049] Step S102: After the industrial robot reaches each preset configuration position, first obtain first terminal pose data of the industrial robot when unloaded. Then, when the terminal of the industrial robot is subjected to an external force applied by the hoist device, obtain terminal force data and second terminal pose data of the industrial robot after loading. Then, error solution optimization is performed based on the first terminal pose data and the second terminal pose data to obtain terminal pose deformation data of the industrial robot in Cartesian space caused by the force.

[0050] Step S103 , performing a solution based on a plurality of Jacobian matrices, a plurality of terminal position deformation data, and a plurality of terminal force data corresponding to the industrial robot at a plurality of preset configuration positions, to obtain a stiffness identification result of the industrial robot.

[0051] In step S101 of some embodiments, the DH parameters of the industrial robot are obtained by kinematically calibrating the industrial robot when it is unloaded. The preset configuration position of the industrial robot can be understood as the preset angle value of each joint of the industrial robot. The Jacobian matrix corresponding to the industrial robot at a single preset configuration position can be obtained by the following method:

[0052] First, the joint angle values ​​contained in the DH parameters of the industrial robot are replaced with the preset configuration positions of the industrial robot to obtain the updated DH parameters of the industrial robot; secondly, the homogeneous transformation matrices of the various links of the industrial robot are calculated based on the updated DH parameters of the industrial robot, where one link corresponds to one joint, and then the pose transformation matrix of the end effector of the industrial robot is calculated by matrix multiplication; then, the Z-axis direction vectors of the various links of the industrial robot are correspondingly extracted from the homogeneous transformation matrices of the various links of the industrial robot to construct the angular velocity matrix of the end effector of the industrial robot; and the positions of the various joints of the industrial robot correspondingly extracted from the homogeneous transformation matrices of the various links of the industrial robot are Vector, and extract the position vector of the end effector of the industrial robot from the posture transformation matrix of the end effector of the industrial robot, and then subtract the position vector of the end effector of the industrial robot from the position vector of each joint of the industrial robot to obtain the position deviation vector between the end effector of the industrial robot and each joint, and then perform cross product calculation on the Z-axis direction vector of each connecting rod of the industrial robot and the position deviation vector between the end effector of the industrial robot and each joint to construct the linear velocity matrix of the end effector of the industrial robot; finally, the linear velocity matrix and angular velocity matrix of the end effector of the industrial robot are combined to obtain the Jacobian matrix corresponding to the industrial robot at the preset configuration position.

[0053] In step S102 of some embodiments, the first terminal posture data of the industrial robot when unloaded includes the first terminal position data and the first terminal posture data of the industrial robot when unloaded, and the second terminal posture data of the industrial robot after loading includes the second terminal position data and the second terminal posture data of the industrial robot after loading. Regarding the step of performing error solution optimization based on the first terminal posture data of the industrial robot when unloaded and the second terminal posture data of the industrial robot after loading to obtain the terminal posture deformation data of the industrial robot in Cartesian space caused by the force, the corresponding implementation process may include, but is not limited to, the following steps S201 to S203:

[0054] Step S201: Calculate the posture conversion matrix based on the first terminal posture data of the industrial robot when it is unloaded. This can be achieved using the following expression:

[0055]

[0056] Where I is the attitude conversion matrix, which is used to express the relationship between the angular rotation velocity vector and the angular velocity vector. The first terminal attitude data of the industrial robot when it is unloaded is recorded as is the roll angle of the industrial robot when it is unloaded (which indicates the angle of rotation around the Z axis), θ0 is the pitch angle of the industrial robot when it is unloaded (which indicates the angle of rotation around the Y axis), ψ0 is the yaw angle of the industrial robot when it is unloaded (which indicates the angle of rotation around the X axis), s refers to the sin sign (i.e., sine function), and c refers to the cos sign (i.e., cosine function).

[0057] Step S202: performing error calculation based on the first terminal posture data of the industrial robot when unloaded and the second terminal posture data of the industrial robot after loading, and then optimizing the error calculation results based on the posture transformation matrix to obtain terminal posture deformation data of the industrial robot in Cartesian space caused by the force;

[0058] Specifically, the first terminal posture data of the industrial robot when unloaded and the second terminal posture data of the industrial robot after loading are subtracted to obtain the initial terminal posture deformation data of the industrial robot in Cartesian space caused by the force, that is, the angular rotation velocity vector, which can be achieved using the following expression:

[0059]

[0060] In the formula, the initial terminal posture deformation data of the industrial robot in Cartesian space caused by the force is recorded as is the change in the roll angle of the industrial robot before and after loading, is the pitch angle change of the industrial robot before and after loading, is the change in yaw angle of the industrial robot before and after loading, and the second terminal posture data of the industrial robot after loading is recorded as is the roll angle of the industrial robot after loading, θ is the pitch angle of the industrial robot after loading, and ψ is the yaw angle of the industrial robot after loading;

[0061] The posture transformation matrix is ​​matrix-multiplied by the initial end posture deformation data of the industrial robot in Cartesian space caused by the force, and the end posture deformation data of the industrial robot in Cartesian space caused by the force is obtained. This can be achieved using the following expression:

[0062]

[0063] Where, It is the actual end posture deformation data of the industrial robot in Cartesian space caused by the influence of force.

[0064] Step S203: determining the terminal position deformation data of the industrial robot in the Cartesian space caused by the force based on the first terminal position data of the industrial robot when unloaded, the second terminal position data of the industrial robot after loading, and the terminal position deformation data of the industrial robot in the Cartesian space caused by the force;

[0065] Specifically, the first end position data of the industrial robot when unloaded and the second end position data of the industrial robot after loading are subtracted to obtain the end position deformation data of the industrial robot in Cartesian space caused by the force. This can be achieved using the following expression:

[0066]

[0067] Where, is the deformation data of the end position of the industrial robot in Cartesian space caused by the influence of force. The first end position data of the industrial robot when unloaded is recorded as {x0, y0, z0}, and the second end position data of the industrial robot after loading is recorded as {x, y, z};

[0068] The terminal position deformation data and terminal posture deformation data of the industrial robot in Cartesian space caused by the force are directly combined to obtain the terminal posture deformation data of the industrial robot in Cartesian space caused by the force, which is recorded as T is the transpose symbol.

[0069] Furthermore, the derivation process of the posture conversion matrix is ​​described in detail below:

[0070] The end posture deformation of the industrial robot can be expressed in the Cartesian space coordinate system as follows:

[0071]

[0072] In the formula, {ω x ,ω y ,ω z} is the angular velocity component of the end of the industrial robot in Cartesian space, ω x is the angular velocity of the end of the industrial robot around the X axis, ω y is the angular velocity of the end of the industrial robot around the Y axis, ω z is the angular velocity of the end of the industrial robot around the Z axis, and are all unit vectors, is the unit vector of the end of the industrial robot moving along the X axis, is the unit vector of the end of the industrial robot moving along the Y axis, is the unit vector of the end of the industrial robot moving along the Z axis;

[0073] Express the expression of δω in the Cartesian space coordinate system using the derivative of the Euler angle:

[0074]

[0075] is the angular rotation velocity vector, where for:

[0076]

[0077] The end posture of the industrial robot around the Z axis when it is unloaded Rotation get:

[0078]

[0079] When the industrial robot is unloaded, the terminal posture first revolves around the Z axis Rotation Then around the Y axis Rotating θ0 yields:

[0080]

[0081] Where, Rotate the end of the industrial robot around the Z axis The rotation matrix generated by the angle, R Y (θ0) is the rotation matrix generated when the end of the industrial robot rotates around the Y axis by an angle of θ0;

[0082] will be about The conversion vector about The conversion vector and about The conversion vector Substituting this into the transformed expression for δω, we obtain:

[0083]

[0084] In this expression, it can be understood that the posture transformation matrix I is used to optimize the initial end posture deformation data of the industrial robot in the Cartesian space caused by the influence of force.

[0085] It should be noted that, in the process of executing the above-mentioned step S102, in order to obtain the terminal posture deformation data and terminal force data corresponding to the industrial robot at different preset configuration positions more reliably and without interference, after obtaining the terminal posture deformation data and terminal force data corresponding to the current preset configuration position of the industrial robot, the winch device is first controlled to completely unload the external force applied to the end of the industrial robot, and then the industrial robot is controlled to reach the next preset configuration position; in addition, before obtaining the terminal force data and the second terminal posture data of the industrial robot after loading, it should be ensured that the external force applied by the winch device to the end of the industrial robot can reach the preset expected terminal force data as much as possible, so that each joint of the industrial robot can produce effective rotational deformation.

[0086] In some embodiments, the above step S103 may include, but is not limited to, the following steps S301 to S303:

[0087] Step S301: Obtain a stiffness identification mathematical model of the industrial robot, which is used to characterize the relationship between the end-position deformation of the industrial robot and the Jacobian matrix, the end-force, and the joint stiffness. It can be expressed as follows:

[0088] δd=Jdiag(J T F)C

[0089]

[0090] Where, is the end pose deformation of the industrial robot, is the Jacobian matrix of the industrial robot, The end force of the industrial robot, is the stiffness of the nth joint of the industrial robot, n = 1, 2, 3, 4, 5, 6, C is the reference matrix formulated for the convenience of description, T is the transpose symbol, and diag is the diagonal matrix symbol.

[0091] Step S302: Substituting multiple Jacobian matrices, multiple terminal position deformation data, and multiple terminal force data corresponding to the industrial robot at multiple preset configuration positions into a stiffness identification mathematical model of the industrial robot to construct an overdetermined set of equations;

[0092] Specifically, multiple Jacobian matrices, multiple end-point pose deformation data, and multiple end-point force data corresponding to the industrial robot at multiple preset configuration positions are substituted into the industrial robot's stiffness identification mathematical model to obtain multiple initial equations corresponding to the industrial robot at multiple preset configuration positions. The only unknown parameters contained in each initial equation are the stiffness of each joint of the industrial robot. The multiple initial equations corresponding to the industrial robot at multiple preset configuration positions are then combined to form an overdetermined system of equations. The number of preset configuration positions is preferably set to 30.

[0093] Step S303: Solve the overdetermined equations to obtain joint stiffness data of the industrial robot;

[0094] Optionally, the least squares method is used to solve the overdetermined equations, that is, the goal is to minimize the sum of squares of errors or residuals of multiple initial equations to find suitable joint stiffness data of the industrial robot.

[0095] In an embodiment of the present application, by constructing an overdetermined set of equations based on the stiffness identification mathematical model of the industrial robot and multiple Jacobian matrices, multiple end posture deformation data and multiple end force data corresponding to the industrial robot at multiple preset configuration positions and then solving the equations, the stiffness identification accuracy of the industrial robot can be improved, and the robustness and reliability of the stiffness identification process can be improved.

[0096] In step S301 of some embodiments, before describing the derivation process of the stiffness identification mathematical model of the industrial robot, the following brief description of the stiffness identification principle of the industrial robot is given:

[0097] The flexibility exhibited by industrial robots is a result of the combined effects of joint flexibility and link flexibility. However, since link flexibility accounts for a relatively small proportion, to simplify the model, the stiffness modeling of industrial robots is usually based on the assumption that the links are rigid bodies and the joints are elastic torsion springs. Furthermore, to simplify the model, joint damping is also neglected, so the stiffness model of the industrial robot system is established as a virtual joint model.

[0098] Strictly speaking, there is a nonlinear relationship between the joint torque and deformation of an industrial robot. As the joint torque changes, the joint stiffness value will also change. However, for the RV reducer installed at each joint of the industrial robot, the degree of nonlinearity is relatively small. For the sake of engineering usability, the joint stiffness is regarded as a constant value in the embodiment of the present application, that is, a linear relationship is set between the joint torque and deformation of the industrial robot, and only the mechanical stiffness of the rotary joint around the rotation direction is considered.

[0099] On this basis, the derivation process of the stiffness identification mathematical model of the industrial robot may include, but is not limited to, the following steps S401 to S402:

[0100] Step S401: Obtain a predetermined first relational expression, a second relational expression, a third relational expression, and a fourth relational expression, wherein:

[0101] The first relationship is used to characterize the relationship between the end force of the industrial robot and the Cartesian stiffness matrix and the end posture deformation, which can be expressed as follows:

[0102] F=Kδd

[0103] The second relationship is used to characterize the relationship between the joint torque, joint stiffness matrix, and joint angular deformation of the industrial robot, and can be expressed as follows:

[0104] τ=K θ δθ

[0105] The third relationship is used to characterize the relationship between the joint torque, Jacobian matrix, and end force of the industrial robot. It is constructed using the principle of virtual work, taking into account the situation where the joint torque and end force of the industrial robot are balanced in static state. It can be expressed as follows:

[0106] τ=J T F

[0107] The fourth relation is used to characterize the relationship between the end-position deformation of the industrial robot and the Jacobian matrix and joint angle deformation, which can be expressed as follows:

[0108] δd=Jδθ

[0109] Where, The end force of the industrial robot, is the Cartesian stiffness matrix of the industrial robot, is the end pose deformation of the industrial robot, is the joint torque of the industrial robot, is the joint stiffness matrix of the industrial robot, is the joint angular deformation of the industrial robot, is the Jacobian matrix of the industrial robot, and T is the transpose symbol.

[0110] Step S402: Derivative the joint angle of the third relational expression, and then perform conversion analysis based on the derivative result, the first relational expression, the second relational expression, and the fourth relational expression to obtain a stiffness identification mathematical model of the industrial robot;

[0111] Specifically, the two sides of the third relationship are simultaneously derived with respect to the joint angle, and the derivative results are:

[0112]

[0113] Combining the derivative result, the first relational expression and the second relational expression, we get the first transformed relational expression:

[0114]

[0115] Combining the first conversion relational expression with the fourth conversion relational expression, the second conversion relational expression is obtained as follows:

[0116]

[0117] Ignore K c The impact on stiffness identification mainly considers the mapping relationship between the static stiffness of the joints and the end stiffness of the industrial robot. The second conversion relationship is simplified and transformed to obtain the third conversion relationship:

[0118] K=J -T K θ J -1

[0119] Combining the third conversion relational expression with the first conversion relational expression, the fourth conversion relational expression is obtained:

[0120] δd=JK θ -1 J T F

[0121] Rewriting the fourth conversion relationship, the stiffness identification mathematical model of the industrial robot is obtained as follows:

[0122]

[0123] In the formula, θ = [θ1, θ2, θ3, θ4, θ5, θ6] T is the joint angle of the industrial robot, θ n is the angle of the nth joint of the industrial robot, n=1,2,3,4,5,6, is the supplementary stiffness matrix of the industrial robot.

[0124] In some embodiments, after executing the above step S103, multiple first end posture data, multiple second end posture data and multiple end force data corresponding to the industrial robot at multiple preset configuration positions and the stiffness identification results of the industrial robot can be intuitively visualized in an interface.

[0125] The industrial robot stiffness identification method proposed in the embodiment of the present application can obtain more reliable end-position deformation data by optimizing the error solution of the end-position data of the industrial robot before and after loading. By combining the Jacobian matrix of the industrial robot and its end-position force data after loading for solution, the stiffness identification accuracy of the industrial robot can be improved.

[0126] See also Figure 2 , Figure 2 This is a schematic diagram of an optional component of an industrial robot stiffness identification device provided in an embodiment of the present application, which can implement the above-mentioned industrial robot stiffness identification method. The device may include, but is not limited to, the following:

[0127] The first module 501 is used to obtain DH parameters of the industrial robot to determine multiple Jacobian matrices corresponding to the industrial robot at multiple preset configuration positions;

[0128] The second module 502 is configured to control the industrial robot to reach each preset configuration position, first obtain first terminal end posture data of the industrial robot when it is unloaded, then obtain terminal end force data and second terminal end posture data of the industrial robot after loading when the terminal end of the industrial robot is subjected to an external force applied by the hoist device, and then perform error solution optimization based on the first terminal end posture data and the second terminal end posture data to obtain terminal end posture deformation data of the industrial robot in Cartesian space caused by the force;

[0129] The third module 503 is used to solve the stiffness identification result of the industrial robot according to multiple Jacobian matrices, multiple terminal posture deformation data and multiple terminal force data corresponding to the industrial robot at multiple preset configuration positions.

[0130] It can be understood that the contents of the above method embodiments are all applicable to the embodiments of the present device, the functions specifically implemented by the embodiments of the present device are the same as the functions specifically implemented by the above method embodiments, and the beneficial effects achieved by the embodiments of the present device are also the same as the beneficial effects achieved by the above method embodiments.

[0131] An embodiment of the present application further provides a control device, which is used to implement the above-mentioned industrial robot stiffness identification method.

[0132] It can be understood that the contents of the above method embodiments are all applicable to the embodiments of the present device, the functions specifically implemented by the embodiments of the present device are the same as the functions specifically implemented by the above method embodiments, and the beneficial effects achieved by the embodiments of the present device are also the same as the beneficial effects achieved by the above method embodiments.

[0133] See also Figure 3 , Figure 3This is an optional composition diagram of an industrial robot stiffness identification system provided in an embodiment of the present application. The system may include, but is not limited to, a control device and a winch device connected thereto, a six-dimensional force / torque sensor, and a posture acquisition device.

[0134] In practical applications, when the control device is used to implement the above-mentioned industrial robot stiffness identification method, the end force data of the industrial robot is collected by the six-dimensional force / torque sensor and transmitted to the control device, and the end posture data of the industrial robot is collected by the posture acquisition device and transmitted to the control device; and the control device generates a control signal based on the error between the preset end expected force data and the end force data of the industrial robot transmitted by the six-dimensional force / torque sensor and transmits it to the winch device, and then the winch device applies external force to the end of the industrial robot according to the control signal.

[0135] In some embodiments, the hoist device includes a hoist, a servo motor and a servo drive, the hoist has a drum, and the drum is connected to the end of the industrial robot through a steel cable.

[0136] In actual applications, when the winch device receives the control signal transmitted by the control device, the servo driver drives the servo motor to rotate according to the control signal, and then the servo motor drives the reel to rotate in the rotating state to synchronously wind the steel cable (that is, synchronously adjust the length and tension of the steel cable) to apply external force to the end of the industrial robot.

[0137] In some embodiments, the posture acquisition device includes a laser tracker and its adapted laser tracking target (T-MAC). The laser tracking target is mounted on the end flange of the industrial robot, but the laser tracking target does not coincide with the center of the end flange of the industrial robot, and ensures that the laser tracking target is always within the field of view of the laser tracker during the movement of the industrial robot.

[0138] In practical applications, a laser tracker emits a laser beam to illuminate a laser tracking target, and then receives the reflected light emitted by the laser tracking target to obtain the end-point posture data of the industrial robot.

[0139] In some embodiments, the control device further includes a controller and a host computer; the controller can receive the end force desired signal sent by the host computer and the end force feedback signal sent by the six-dimensional force / torque sensor and perform closed-loop analysis to obtain the force control signal of the winch and send it to the servo driver, so that the servo driver drives the servo motor of the winch by controlling the current; the host computer can receive the end force feedback signal sent by the controller and the end posture signal sent by the laser tracker.

[0140] The industrial robot stiffness identification system proposed in the embodiment of the present application realizes closed-loop force control by utilizing control equipment, a winch device and a six-dimensional force / torque sensor, thereby applying a stable and adjustable external force to the end of the industrial robot. This can effectively stimulate the deformation properties of each joint of the industrial robot, improve the stiffness identification efficiency of the industrial robot, and also well protect the industrial robot body from damage.

[0141] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned industrial robot stiffness identification method is implemented.

[0142] It can be understood that the contents of the above method embodiments are all applicable to the present medium embodiment, the functions specifically implemented by the present medium embodiment are the same as the functions specifically implemented by the above method embodiment, and the beneficial effects achieved by the present medium embodiment are also the same as the beneficial effects achieved by the above method embodiment.

[0143] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] The relevant embodiments described above are intended to more clearly illustrate the technical solutions provided by the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0145] It will be understood by those skilled in the art that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown, or a combination of certain steps, or different steps. The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] The terms "first," "second," "third," "fourth," and the like that appear in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential sequence. It should be understood that the numbers used in this manner are interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions, e.g., a process, method, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products, or apparatus.

[0147] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A method for identifying stiffness of an industrial robot, characterized in that: The method comprises: Obtaining DH parameters of the industrial robot to determine a plurality of Jacobian matrices corresponding to the industrial robot at a plurality of preset configuration positions; After controlling the industrial robot to reach each of the preset configuration positions, firstly obtaining first terminal position data of the industrial robot when unloaded, then obtaining terminal force data and second terminal position data of the industrial robot after loading when the terminal of the industrial robot is subjected to an external force applied by a hoist device, and then performing error solution optimization based on the first terminal position data and the second terminal position data to obtain terminal position deformation data of the industrial robot in Cartesian space caused by the force; The stiffness identification result of the industrial robot is obtained by solving the multiple Jacobian matrices, the multiple terminal posture deformation data and the multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions.

2. The method for identifying stiffness of an industrial robot according to claim 1, wherein: The first terminal posture data includes first terminal position data and first terminal posture data, and the second terminal posture data includes second terminal position data and second terminal posture data; the error solution optimization is performed based on the first terminal posture data and the second terminal posture data to obtain the terminal posture deformation data of the industrial robot in the Cartesian space caused by the force, including: Calculating a posture conversion matrix based on the first terminal posture data; performing error calculation based on the first terminal posture data and the second terminal posture data, and then optimizing and solving the error based on the posture transformation matrix to obtain actual terminal posture deformation data; The terminal position deformation data is determined according to the first terminal position data, the second terminal position data and the terminal posture deformation data.

3. The method for identifying stiffness of an industrial robot according to claim 1, wherein: The step of obtaining the stiffness identification result of the industrial robot by solving the plurality of Jacobian matrices, the plurality of terminal posture deformation data, and the plurality of terminal force data corresponding to the industrial robot at the plurality of preset configuration positions includes: Obtaining a stiffness identification mathematical model of the industrial robot, which is used to characterize the relationship between the end position deformation of the industrial robot and the Jacobian matrix, the end force and the joint stiffness; Substituting multiple Jacobian matrices, multiple terminal posture deformation data, and multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions into the stiffness identification mathematical model of the industrial robot to construct an overdetermined set of equations; The overdetermined set of equations is solved to obtain joint stiffness data of the industrial robot.

4. The method for identifying stiffness of an industrial robot according to claim 3, wherein: The stiffness identification mathematical model of the industrial robot is obtained by the following method: Obtaining a predetermined first, second, third, and fourth relationship, wherein the first relationship is used to characterize the relationship between the end force of the industrial robot and the Cartesian stiffness matrix and the end posture deformation; the second relationship is used to characterize the relationship between the joint torque of the industrial robot and the joint stiffness matrix and the joint angle deformation; the third relationship is used to characterize the relationship between the joint torque of the industrial robot and the Jacobian matrix and the end force; and the fourth relationship is used to characterize the relationship between the end posture deformation of the industrial robot and the Jacobian matrix and the joint angle deformation; The third relational expression is derived with respect to the joint angle, and then a conversion analysis is performed based on the derivative result, the first relational expression, the second relational expression, and the fourth relational expression to obtain a stiffness identification mathematical model of the industrial robot.

5. An industrial robot stiffness identification device, characterized in that: The device comprises: The first module is used to obtain DH parameters of the industrial robot to determine a plurality of Jacobian matrices corresponding to the industrial robot at a plurality of preset configuration positions; a second module, configured to control the industrial robot to reach each of the preset configuration positions, first obtain first terminal position data of the industrial robot when unloaded, then obtain terminal force data and second terminal position data of the industrial robot after loading when the terminal of the industrial robot is subjected to an external force applied by a hoist device, and then perform error solution optimization based on the first terminal position data and the second terminal position data to obtain terminal position deformation data of the industrial robot in Cartesian space caused by the force; The third module is used to solve the multiple Jacobian matrices, multiple terminal posture deformation data and multiple terminal force data corresponding to the industrial robot at the multiple preset configuration positions to obtain the stiffness identification result of the industrial robot.

6. A control device, characterized in that: The control device is used to implement the industrial robot stiffness identification method according to any one of claims 1 to 4.

7. An industrial robot stiffness identification system, characterized in that: The system comprises a hoist device, a six-dimensional force / torque sensor, a posture acquisition device and the control device according to claim 6; The six-dimensional force / torque sensor is used to collect the end force data of the industrial robot and transmit it to the control device; the posture acquisition device is used to collect the end posture data of the industrial robot and transmit it to the control device; the control device is used to generate a control signal based on the error between the preset end expected force data and the end force data of the industrial robot transmitted by the six-dimensional force / torque sensor, and transmit it to the winch device; the winch device is used to apply external force to the end of the industrial robot according to the control signal.

8. The industrial robot stiffness identification system according to claim 7, characterized in that: The hoist device includes a hoist, a servo motor and a servo drive, the hoist has a drum, and the drum is connected to the end of the industrial robot through a steel cable; The servo driver is used to drive the servo motor to rotate according to the control signal, and the servo motor is used to drive the reel to rotate in a rotating state to synchronously wind the steel cable to apply external force to the end of the industrial robot.

9. The industrial robot stiffness identification system according to claim 7, characterized in that: The position and posture acquisition device includes a laser tracker and an adapted laser tracking target.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the industrial robot stiffness identification method according to any one of claims 1 to 4 is implemented.

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