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

Abstract

The application provides an industrial robot stiffness identification method, device, system, control equipment and medium, and belongs to the technical field of robots. The method comprises the following steps: obtaining DH parameters of an 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 preset configuration position, obtaining first end pose data of the industrial robot when the industrial robot is in an empty state, and end force data and second end pose data when the end of the industrial robot is subjected to an external force applied by a winch device; then, according to the first end pose data and the second end pose data, error solving optimization is performed to obtain actual end pose deformation data; and finally, according to the plurality of Jacobian matrices corresponding to the industrial robot at the plurality of preset configuration positions, the plurality of end pose deformation data and the plurality of end force data, the stiffness identification result of the industrial robot is obtained by solving. The application can improve the stiffness identification accuracy and efficiency of the industrial robot.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of robots, in particular to an industrial robot stiffness identification method, device, system, control equipment and medium. BACKGROUND

[0002] In the prior art, the actual end pose deformation data is obtained by directly subtracting the end pose data of the industrial robot before and after loading, and then the stiffness identification of the industrial robot is performed in combination with the end force data of the industrial robot after loading. However, the current stiffness identification is single and uncontrollable in force application condition, which affects the stiffness identification accuracy; in addition, the end pose data of the industrial robot is generally represented in the form of Euler angles, and if the end pose data of the industrial robot before and after loading is directly subtracted, the angle range will be chaotic, which causes the stiffness identification result of the industrial robot to be inaccurate. SUMMARY

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

[0004] To achieve the above-mentioned purpose, one aspect of the present application proposes an industrial robot stiffness identification method, which comprises:

[0005] obtaining the 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, first, the first end pose data of the industrial robot under no load is obtained, and then when the end of the industrial robot is subjected to an external force applied by a winch device, the end force data and the second end pose data of the industrial robot after loading are obtained, and subsequently, the error solving optimization is performed according to the first end pose data and the second end pose data to obtain the end pose deformation data of the industrial robot in the Cartesian space caused by the force;

[0007] According to the plurality of Jacobian matrices corresponding to the industrial robot at the plurality of preset configuration positions, the plurality of end pose deformation data and the plurality of end force data, the stiffness identification result of the industrial robot is obtained.

[0008] Further, the first end pose data comprises first end position data and first end attitude data, and the second end pose data comprises second end position data and second end attitude data; the error solving optimization according to the first end pose data and the second end pose data comprises:

[0009] According to the first end attitude data, a posture conversion matrix is calculated;

[0010] According to the first end attitude data and the second end attitude data, error solving is performed, and the error solving result is optimized according to the posture conversion matrix to obtain end attitude deformation data;

[0011] According to the first end position data, the second end position data and the end attitude deformation data, the end pose deformation data is determined.

[0012] Further, the solving of the plurality of Jacobian matrices, the plurality of end pose deformation data and the plurality of end force data of the industrial robot at the plurality of preset configuration positions to obtain the stiffness identification result of the industrial robot comprises:

[0013] A stiffness identification mathematical model of the industrial robot is obtained, which is used to represent the relationship between the end pose deformation of the industrial robot and the Jacobian matrix, the end force and the joint stiffness;

[0014] The plurality of Jacobian matrices, the plurality of end pose deformation data and the plurality of end force data of the industrial robot at the plurality of preset configuration positions are substituted into the stiffness identification mathematical model of the industrial robot to construct an overdetermined equation set;

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

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

[0017] A first relationship, a second relationship, a third relationship and a fourth relationship are obtained, the first relationship is used to represent the relationship between the end force of the industrial robot and the Cartesian stiffness matrix and the end pose deformation, the second relationship is used to represent 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 represent 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 represent the relationship between the end pose deformation of the industrial robot and the Jacobian matrix and the joint angle deformation;

[0018] Derivate the joint angle of the third relationship, and perform conversion analysis according to the derivative result, the first relationship, the second relationship and the fourth relationship to obtain the stiffness identification mathematical model of the industrial robot.

[0019] To achieve the above-mentioned purpose, another aspect of the present application proposes an industrial robot stiffness identification device, which comprises:

[0020] The first module is configured to obtain the 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] The second module is configured to, after the industrial robot reaches each preset configuration position, first obtain first end pose data of the industrial robot when it is in an empty state, and then obtain end force data and second end pose data of the industrial robot when its end is subjected to an external force applied by a winch device, and subsequently perform error solving optimization according to the first end pose data and the second end pose data to obtain end pose deformation data of the industrial robot in the Cartesian space caused by the force;

[0022] The third module is configured to perform solving according to the plurality of Jacobian matrices corresponding to the industrial robot at the plurality of preset configuration positions, the plurality of end pose deformation data and the plurality of end force data to obtain the stiffness identification result of the industrial robot.

[0023] To achieve the above-mentioned purpose, another aspect of the present application proposes a control device for implementing the above-mentioned industrial robot stiffness identification method.

[0024] To achieve the above-mentioned purpose, another aspect of the present application proposes an industrial robot stiffness identification system, which comprises a winch device, a six-dimensional force / torque sensor, a pose acquisition device and the above-mentioned control device.

[0025] The six-dimensional force / torque sensor is configured to acquire end force data of the industrial robot and transmit the data to the control device; the pose acquisition device is configured to acquire end pose data of the industrial robot and transmit the data to the control device; the control device is configured to generate a control signal according to 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 the control signal to the winch device; and the winch device is configured to apply an external force to the end of the industrial robot according to the control signal.

[0026] Further, the hoist device comprises a hoist, a servo motor and a servo driver, the hoist has a winding drum, the winding drum is connected with the end of the industrial robot through a steel cable;

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

[0028] Further, the pose acquisition device comprises a laser tracker and an adapted laser tracking target thereof.

[0029] To achieve the above object, another aspect of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the industrial robot stiffness identification method.

[0030] The present application has at least the following beneficial effects: by solving and optimizing the error of the end pose data of the industrial robot before and after loading, more reliable end pose deformation data can be obtained, and by solving the Jacobian matrix of the industrial robot and the end force data after loading, the stiffness identification accuracy of the industrial robot can be improved. By using the control device, the hoist device and the six-dimensional force / torque sensor to realize closed-loop force control, and then applying stable and adjustable external force to the end of the industrial robot, the properties of the deformation of each joint of the industrial robot can be effectively stimulated, the stiffness identification efficiency of the industrial robot can be improved, and the industrial robot body can be well protected from damage. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 is a flowchart of an industrial robot stiffness identification method provided by an embodiment of the present application;

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

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

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

[0035] It can be understood that the terms "first", "second" and the like as used in the present application can be used herein to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon determining" or "in response to determining".

[0036] The terms "at least one", "multiple", "each", "any" and the like used in the present application include one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

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

[0038] Before the embodiments of the present application are described in detail, first, some nouns and terms involved in the embodiments of the present application are described, and the nouns and terms involved in the embodiments of the present application are applicable to the following explanations.

[0039] DH (Denavit-Hartenberg) parameters are used to describe the geometric relationship between the joints and links of an industrial robot, and the relative positions and rotations of each joint of the industrial robot are mainly defined by four parameters of link offset, link length, twist angle and joint angle. The introduction of DH parameters makes the establishment of kinematics equations of the industrial robot more unified and simplified.

[0040] Jacobian Matrix, used to describe the relationship between joint velocity and end effector velocity of an industrial robot, is usually represented as a 6 x n partial derivative matrix, n being the number of joints of 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 the Cartesian space. The construction of the Jacobian matrix helps to achieve the forward kinematics analysis and inverse kinematics analysis of the industrial robot.

[0041] Robot end pose deformation data refers to the angular velocity of the end pose data of the robot before and after loading, which is obtained through the end angular rotation velocity vector and the conversion matrix. Among them, the end angular rotation velocity vector is the difference value of the end Euler angle before and after the robot is loaded.

[0042] High-precision industrial robots cannot be separated from flexible compensation, and in addition to the need for accurate dynamic model, accurate robot joint stiffness is also needed. The weak rigidity of the industrial robot is one of the main factors affecting its accuracy, and the flexibility shown is caused by the joint flexibility and the link flexibility. For most industrial robots, the link has sufficient rigidity, and the flexibility deformation of the robot is mainly caused by the joint flexibility. Therefore, obtaining accurate joint stiffness value is of great significance to improve the accuracy of the industrial robot, such as robot joint flexibility error compensation.

[0043] In the prior art, the actual end pose deformation data is usually obtained by directly subtracting the end pose data of the industrial robot before and after loading, and then combined with the end force data of the industrial robot after loading to identify the stiffness of the industrial robot. However, since the end pose data of the industrial robot is generally represented in the form of Euler angle, if the end pose data of the industrial robot before and after loading is directly subtracted, the angle range will be chaotic (such as the periodicity of the angle, the universal joint lock problem, etc.), which will cause the stiffness identification result of the industrial robot to be inaccurate.

[0044] In addition, in order to make each joint of the industrial robot deform during the joint stiffness identification process, an external pulling force needs to be provided to the industrial robot. Based on this, some technicians propose to apply an external force by directly hanging a fixed load at the end of the industrial robot, but the external force generated by the fixed load cannot make the first joint of the industrial robot be subjected to a torsional moment, so the stiffness of the first joint cannot be identified. Some technicians propose to use a pulley device to apply an external force to the end of the industrial robot, but the size of the end force of the industrial robot needs to be controlled by installing loads of different masses, which is inefficient to implement.

[0045] Therefore, the embodiment of the present application provides an industrial robot stiffness identification method, device, system, control equipment and medium. The method introduces a winch device to apply an external force to the end of the industrial robot in the actual application process, and introduces an error solving optimization mechanism to determine the end pose deformation data of the industrial robot, which is beneficial to improve the stiffness identification accuracy and efficiency of the industrial robot.

[0046] The industrial robot stiffness identification method provided by the embodiment of the present application relates to the technical field of robots, can be applied to a terminal, can be applied to a server, and can also be software running in the terminal or the server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto; the server end can be configured as a stand-alone physical server, a server cluster composed of multiple physical servers or a distributed system, a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN and big data and artificial intelligence platform, or a node server in a blockchain network; and the software can be an application program for implementing the above method, etc., but is not limited to the above forms.

[0047] Please refer to Figure 1 , Figure 1 is an optional flowchart of an industrial robot stiffness identification method provided by the embodiment of the present application. The method can include, but is not limited to, the following steps S101 to S103:

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

[0049] Step S102, after controlling the industrial robot to reach each preset configuration position, first obtaining the first end pose data of the industrial robot when it is unloaded, then obtaining the end force data and the second end pose data of the industrial robot after the end of the industrial robot is subjected to the external force applied by the winch device, and subsequently performing error solving optimization according to the first end pose data and the second end pose data to obtain the end pose deformation data of the industrial robot in the Cartesian space caused by the force;

[0050] Step S103, solving according to the plurality of Jacobian matrices corresponding to the industrial robot at the plurality of preset configuration positions, the plurality of end pose deformation data and the plurality of end force data to obtain the stiffness identification result of the industrial robot.

[0051] In step S101 of some embodiments, the DH parameters of the industrial robot are obtained after kinematic calibration of the industrial robot when it is empty, and the preset configuration position of the industrial robot can be understood as the preset angle value of each joint of the industrial robot. As for the Jacobian matrix corresponding to the industrial robot at a single preset configuration position, it can be obtained in the following manner:

[0052] Firstly, the joint angle values contained in the DH parameters of the industrial robot are replaced by the preset configuration position of the industrial robot to obtain updated DH parameters of the industrial robot. Secondly, the homogeneous transformation matrix of each link of the industrial robot is calculated according to the updated DH parameters of the industrial robot, one link corresponding to one joint, and then the pose transformation matrix of the end effector of the industrial robot is calculated by matrix multiplication. Thirdly, the Z-axis direction vectors of each link of the industrial robot are correspondingly extracted from the homogeneous transformation matrix of each link of the industrial robot to construct the angular velocity matrix of the end effector of the industrial robot. Moreover, the position vectors of each joint of the industrial robot are correspondingly extracted from the homogeneous transformation matrix of each link of the industrial robot, and the position vector of the end effector of the industrial robot is extracted from the pose transformation matrix of the end effector of the industrial robot. Then, the position deviation vectors between the end effector of the industrial robot and each joint are obtained by subtracting the position vectors of each joint of the industrial robot from the position vector of the end effector of the industrial robot. Subsequently, the cross product calculation is performed on the Z-axis direction vectors of each link of the industrial robot and the position deviation vectors 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 the 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 end pose data of the industrial robot when it is empty includes the first end position data and the first end attitude data of the industrial robot when it is empty, and the second end pose data of the industrial robot after loading includes the second end position data and the second end attitude data of the industrial robot after loading. As for the step of obtaining the end pose deformation data in the Cartesian space of the industrial robot caused by the force effect through error solving optimization according to the first end pose data of the industrial robot when it is empty and the second end pose data of the industrial robot after loading, the corresponding implementation process can include but is not limited to the following steps S201 to S203:

[0054] In step S201, the attitude conversion matrix is calculated according to the first end attitude data of the industrial robot when it is empty, which can be realized by using the following expression:

[0055]

[0056] wherein I is a pose transformation matrix, used to represent the relationship between the angular velocity vector and the angular rotation velocity vector, the first end pose data of the industrial robot when unloaded is denoted as is the roll angle of the industrial robot before and after loading (which represents the angle of rotation around the Z axis), θ0 is the pitch angle of the industrial robot when unloaded (which represents the angle of rotation around the Y axis), ψ0 is the yaw angle of the industrial robot when unloaded (which represents the angle of rotation around the X axis), s denotes the sin symbol (i.e. the sine function), and c denotes the cos symbol (i.e. the cosine function).

[0057] In step S202, error solving is performed according to the first end pose data of the industrial robot when unloaded and the second end pose data of the industrial robot after loading, and the error solving result is optimized according to the pose transformation matrix, to obtain the end pose deformation data in the Cartesian space of the industrial robot caused by the force effect.

[0058] Specifically, the first end pose data of the industrial robot when unloaded and the second end pose data of the industrial robot after loading are subtracted to obtain the initial end pose deformation data in the Cartesian space of the industrial robot caused by the force effect, i.e. the angular rotation velocity vector, which can be implemented by using the following expression:

[0059]

[0060] wherein the initial end pose deformation data in the Cartesian space of the industrial robot caused by the force effect is denoted as is the roll angle change of the industrial robot before and after loading, is the pitch angle change of the industrial robot before and after loading, is the yaw angle change of the industrial robot before and after loading, and the second end pose data of the industrial robot after loading is denoted 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 pose transformation matrix is multiplied by the initial end pose deformation data in the Cartesian space of the industrial robot caused by the force effect to obtain the end pose deformation data in the Cartesian space of the industrial robot caused by the force effect, which can be implemented by using the following expression:

[0062]

[0063] wherein The end pose deformation data of the industrial robot in the Cartesian space caused by the force effect.

[0064] In step S203, the end pose deformation data of the industrial robot in the Cartesian space caused by the force effect is determined according to the first end position data of the industrial robot when unloaded, the second end position data of the industrial robot after loaded, and the end pose deformation data of the industrial robot in the Cartesian space caused by the force effect.

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

[0066]

[0067] In the formula, The end position deformation data of the industrial robot in the Cartesian space caused by the force effect is denoted as {x, y, z}, the first end position data of the industrial robot when unloaded is denoted as {x0, y0, z0}, and the second end position data of the industrial robot after loaded is denoted as {x, y, z}.

[0068] The end position deformation data and the end pose deformation data of the industrial robot in the Cartesian space caused by the force effect are directly combined to obtain the end pose deformation data of the industrial robot in the Cartesian space caused by the force effect, which is denoted as T is a transpose symbol.

[0069] Further, the derivation process of the pose conversion matrix is specifically described as follows:

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

[0071]

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

[0073] The expression for δω in the Cartesian space coordinate system is expressed in terms of the derivatives of the Euler angles:

[0074]

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

[0076]

[0077] is the rotation of the end pose of the industrial robot about the Z axis when the robot is unloaded

[0078] is the rotation of the end pose of the industrial robot about the Z axis when the robot is unloaded

[0079]

[0080]

[0081] where is the rotation matrix resulting from the rotation of the end of the industrial robot about the Z axis by an angle θ0, R Y (θ0) is the rotation matrix resulting from the rotation of the end of the industrial robot about the Y axis by an angle θ0;

[0082] The conversion vector for δω The conversion vector for δω The conversion vector for δω The conversion vector for δω and the conversion vector for δω is substituted into the converted expression for δω, resulting in:

[0083] In this expression, it can be understood that the initial end pose deformation data in the Cartesian space resulting from the forces affecting the industrial robot is optimized using the pose conversion matrix I.

[0084]

[0085] ​​​​​​​It should be noted that, in the process of performing the above step S102, in order to more reliably and without interference obtain the end pose deformation data and the end force data of the industrial robot at different preset configuration positions, after obtaining the end pose deformation data and the end force data of the industrial robot at a current preset configuration position, 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 loaded end force data and the second end pose data of the industrial robot, it should be ensured that the external force applied to the end of the industrial robot by the winch device can reach the preset end expected 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 can include but is not limited to the following steps S301 to S303:

[0087] Step S301, obtaining a stiffness identification mathematical model of the industrial robot, which is used to represent the relationship between the end pose deformation of the industrial robot and the Jacobian matrix, the end force and the joint stiffness, and can be expressed as follows:

[0088] δd=Jdiag(J T F)C

[0089]

[0090] In the formula, is the end pose deformation of the industrial robot, is the Jacobian matrix of the industrial robot, is 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 a designated matrix for convenient description, T is a transpose symbol, and diag is a diagonal matrix symbol.

[0091] Step S302, substituting the multiple Jacobian matrices, the multiple end pose deformation data and the multiple end force data of the industrial robot at the multiple preset configuration positions into the stiffness identification mathematical model of the industrial robot to construct an overdetermined equation group;

[0092] Specifically, the plurality of Jacobian matrices, the plurality of end pose deformation data and the plurality of end force data corresponding to the plurality of preset configuration positions of the industrial robot are substituted into the stiffness identification mathematical model of the industrial robot to obtain a plurality of initial equations corresponding to the plurality of preset configuration positions of the industrial robot, and unknown parameters contained in each initial equation only include the stiffness of each joint of the industrial robot. Then, the plurality of initial equations corresponding to the plurality of preset configuration positions of the industrial robot are combined to form an over-determined equation set. The number of the plurality of preset configuration positions is preferably 30.

[0093] In step S303, the over-determined equation set is solved to obtain the joint stiffness data of the industrial robot.

[0094] Optionally, the least square method is used to solve the over-determined equation set, that is, the square sum of errors or residuals of the plurality of initial equations is minimized to find the appropriate joint stiffness data of the industrial robot.

[0095] In the embodiments of the present application, by constructing an over-determined equation set according to the stiffness identification mathematical model of the industrial robot and the plurality of Jacobian matrices, the plurality of end pose deformation data and the plurality of end force data corresponding to the plurality of preset configuration positions of the industrial robot, and then solving the over-determined equation set, 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 in some embodiments, before the derivation process of the stiffness identification mathematical model of the industrial robot is described, the stiffness identification principle of the industrial robot is first briefly explained as follows:

[0097] The flexibility of the industrial robot is caused by the joint flexibility and the link flexibility. However, since the link flexibility accounts for a small proportion, the link of the industrial robot is usually assumed to be a rigid body and the joint is assumed to be an elastic torsional spring when the stiffness of the industrial robot is modeled, so as to simplify the model. At the same time, the joint damping is also ignored for the consideration of simplifying the model, so that the stiffness model of the industrial robot system is a virtual joint model.

[0098] Strictly speaking, there is a nonlinear relationship between the joint torque and the deformation of the industrial robot, and the joint stiffness value will change with the change of the joint torque. However, the nonlinearity degree of the RV reducer installed at each joint of the industrial robot is small, and the joint stiffness is regarded as a constant value in the embodiments of the present application for the consideration of engineering usability, that is, the linear relationship between the joint torque and the deformation of the industrial robot is set, 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 can include but is not limited to the following steps S401 to S402:

[0100] In step S401, a first relationship, a second relationship, a third relationship and a fourth relationship are obtained.

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

[0102] F = Kd

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

[0104] τ = K θ δθ

[0105] The third relationship is used to represent the relationship between the joint torque of the industrial robot and the Jacobian matrix and the end force, which is obtained by using the virtual work principle considering that the joint torque and the end force of the industrial robot reach equilibrium under static conditions, and can be expressed as follows:

[0106] τ = J T F

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

[0108] d = J

[0109] In the formula, F is the end force of the industrial robot, K is the Cartesian stiffness matrix of the industrial robot, d is the end pose deformation of the industrial robot, τ is the joint torque of the industrial robot, K is the joint stiffness matrix of the industrial robot, θ is the joint angle deformation of the industrial robot, J is the Jacobian matrix of the industrial robot, and T is the transpose symbol.

[0110] In step S402, the joint angle of the third relationship is differentiated, and the stiffness identification mathematical model of the industrial robot is obtained by conversion analysis according to the differentiation result, the first relationship, the second relationship and the fourth relationship.

[0111] Specifically, the joint angle is differentiated on both sides of the third relationship, and the differentiation result is obtained as follows:

[0112]

[0113] The derivative result, the first relationship and the second relationship are combined and converted to obtain a first conversion relationship as follows:

[0114]

[0115] The first conversion relationship and the fourth relationship are combined and converted to obtain a second conversion relationship as follows:

[0116]

[0117] Neglecting K c The influence of stiffness identification, mainly considering the mapping relationship between the joint static stiffness and the end stiffness of the industrial robot, the second conversion relationship is simplified and converted to obtain a third conversion relationship as follows:

[0118] K=J -T K θ J -1

[0119] The third conversion relationship and the first relationship are combined and converted to obtain a fourth conversion relationship as follows:

[0120] δd=JK θ -1 J T F

[0121] The fourth conversion relationship is rewritten to obtain a stiffness identification mathematical model of the industrial robot 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 the above step S103 is performed, the multiple first end pose data, the multiple second end pose data and the multiple end force data corresponding to the multiple preset configuration positions of the industrial robot and the stiffness identification result of the industrial robot can be visually visualized through an interface.

[0125] The industrial robot stiffness identification method provided in the embodiment of the application can obtain more reliable end position deformation data by solving and optimizing the error of the end position data of the industrial robot before and after loading, and can improve the stiffness identification accuracy of the industrial robot by solving the Jacobian matrix of the industrial robot and the end force data after loading.

[0126] Referring to Figure 2 , Figure 2 is an optional component schematic diagram of an industrial robot stiffness identification device provided by the embodiment of the application, which can implement the industrial robot stiffness identification method described above, and the device can but not limited to include the following:

[0127] The first module 501 is configured to obtain the 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;

[0128] The second module 502 is configured to, after the industrial robot reaches each preset configuration position, first obtain first end position data of the industrial robot when the industrial robot is unloaded, and then obtain end force data and second end position data of the industrial robot after the end of the industrial robot is subjected to an external force applied by the winch device, and subsequently solve and optimize the error of the first end position data and the second end position data to obtain end position deformation data of the industrial robot in the Cartesian space caused by the force;

[0129] The third module 503 is configured to solve the Jacobian matrices corresponding to the industrial robot at the plurality of preset configuration positions, the plurality of end position deformation data and the plurality of end force data to obtain a stiffness identification result of the industrial robot.

[0130] It can be understood that the contents in the above method embodiments are all applicable to the device embodiments, the device embodiments specifically implement the same functions as the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0131] The embodiment of the application further provides a control device for implementing the industrial robot stiffness identification method described above.

[0132] It can be understood that the contents in the above method embodiments are all applicable to the device embodiments, the device embodiments specifically implement the same functions as the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0133] Referring to Figure 3 , Figure 3is a schematic diagram of an optional component of a stiffness identification system for an industrial robot provided by embodiments of the present application. The system can include, but is not limited to, a control device, a winch device connected to the control device, a six-axis force / torque sensor, and a pose acquisition device.

[0134] In actual applications, when the control device is used to implement the stiffness identification method for the industrial robot, the six-axis force / torque sensor acquires the force data of the end of the industrial robot and transmits the force data to the control device, the pose acquisition device acquires the pose data of the end of the industrial robot and transmits the pose data to the control device, and the control device generates a control signal according to an error between preset expected force data of the end and the force data of the end of the industrial robot transmitted by the six-axis force / torque sensor, and transmits the control signal to the winch device, which then applies an external force to the end of the industrial robot according to the control signal.

[0135] In some embodiments, the winch device includes a winch, a servo motor, and a servo driver, and the winch has a drum connected to the end of the industrial robot by 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 the servo motor drives the drum to rotate in the rotating state to apply an external force to the end of the industrial robot by synchronously winding the steel cable (i.e., synchronously adjusting the length and tension of the steel cable).

[0137] In some embodiments, the pose acquisition device includes a laser tracker and an adapted laser tracking target (T-MAC), the laser tracking target is installed 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 the laser tracking target is ensured to be always within the field of view of the laser tracker during the movement of the industrial robot.

[0138] In actual applications, the laser tracker emits a laser beam to irradiate the laser tracking target, and receives reflected light emitted by the laser tracking target to obtain the pose data of the end of the industrial robot.

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

[0140] The industrial robot rigidity identification system provided by the embodiment of the present application can effectively stimulate the deformation properties of each joint of the industrial robot, improve the rigidity identification efficiency of the industrial robot, and well protect the industrial robot body from damage.

[0141] The embodiment of the present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the industrial robot rigidity identification method.

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

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

[0144] The related embodiments described above are provided 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 can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0145] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than the figures shown, or combine certain steps, or different steps. The device embodiments described above are only schematic, and the units described as separate components can be or can not be physically separated, that is, they can be located in one place, or can be distributed on multiple network units. According to actual needs, part or all of the modules can be selected to achieve the purpose of the embodiment of the present application.

[0146] The terms "first", "second", "third", "fourth", and the like in the description and in the claims of this patent application of the present application are used for distinguishing between similar objects and not necessarily for describing a specific sequential or chronological order. It is to be understood that the use of these terms herein is to be construed to cover the possibility where more than one of the similar object recited are present. Also, the terms "comprise", "comprising", "include", "including", and the like are to be construed in an open-ended fashion, i.e., to mean the foregoing features or steps are to be considered a component of the process, method, or apparatus along with any future equivalents or substitutes. Also, the terms "comprise", "comprising", "include", "including", and the like are to be construed in an open-ended fashion, i.e., to mean the foregoing features or steps are to be considered a component of the process, method, or apparatus along with any future equivalents or substitutes.

[0147] The preferred embodiments of the present application have been described above with the aid of numerous reference to drawings. These embodiments are illustrative only, and not intended to limit the scope of the present application. Other embodiments of the present application, readily ascertainable by one skilled in the art, and modifications, equivalent replacements and improvements made thereto without departing from the scope and spirit of the present application, shall all fall within the scope of the present application.

Claims

1. A method for identifying the stiffness of an industrial robot, characterized in that, The method includes: Obtain the DH parameters of the industrial robot to determine multiple Jacobian matrices corresponding to the industrial robot at multiple preset configuration positions; After controlling the industrial robot to reach each of the preset configuration positions, firstly, the first end-effector pose data of the industrial robot when it is unloaded is obtained. Then, when the end of the industrial robot is subjected to an external force applied by the winch device, the end-effector force data and second end-effector pose data of the industrial robot after loading are obtained. Subsequently, error calculation and optimization are performed based on the first end-effector pose data and the second end-effector pose data to obtain the end-effector pose 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 multiple Jacobian matrices, multiple end pose deformation data and multiple end force data corresponding to multiple preset configuration positions of the industrial robot.

2. The industrial robot stiffness identification method according to claim 1, characterized in that, The first end-effector pose data includes first end-effector position data and first end-effector orientation data; the second end-effector pose data includes second end-effector position data and second end-effector orientation data; the step of performing error calculation and optimization based on the first end-effector pose data and the second end-effector pose data to obtain the end-effector pose deformation data in Cartesian space caused by force influence of the industrial robot includes: Calculate the attitude transformation matrix based on the first end-effector attitude data; The error is solved based on the first end-effector attitude data and the second end-effector attitude data, and then the error is optimized based on the attitude transformation matrix to obtain the actual end-effector attitude deformation data. The end-effector pose deformation data is determined based on the first end-effector position data, the second end-effector position data, and the end-effector pose deformation data.

3. The industrial robot stiffness identification method according to claim 1, characterized in that, The process of solving for the stiffness identification result of the industrial robot based on multiple Jacobian matrices, multiple end-effector pose deformation data, and multiple end-effector force data corresponding to the multiple preset configuration positions includes: Obtain the stiffness identification mathematical model of the industrial robot, which is used to characterize the relationship between the end pose deformation of the industrial robot and the Jacobian matrix, end force and joint stiffness. Substitute the multiple Jacobian matrices, multiple end pose deformation data, and multiple end force data corresponding to the multiple preset configuration positions of the industrial robot into the stiffness identification mathematical model of the industrial robot to construct an overdetermined set of equations. The joint stiffness data of the industrial robot are obtained by solving the overdetermined equations.

4. The industrial robot stiffness identification method according to claim 3, characterized in that, The mathematical model for stiffness identification of the industrial robot is obtained in the following way: Obtain a predetermined first relation, a second relation, a third relation, and a fourth relation. The first relation is used to characterize the relationship between the end effector force of the industrial robot and the Cartesian stiffness matrix and the end effector pose deformation. The second relation 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 relation is used to characterize the relationship between the joint torque of the industrial robot and the Jacobian matrix and the end effector force. The fourth relation is used to characterize the relationship between the end effector pose deformation of the industrial robot and the Jacobian matrix and the joint angle deformation. The joint angle is differentiated from the third relation, and then a transformation analysis is performed based on the differentiation result, the first relation, the second relation, and the fourth relation to obtain the stiffness identification mathematical model of the industrial robot.

5. An industrial robot stiffness identification device, characterized in that, The device includes: The first module is used to obtain the DH parameters of the industrial robot in order to determine the multiple Jacobian matrices corresponding to the industrial robot at multiple preset configuration positions; The second module is used to control the industrial robot to reach each of the preset configuration positions, firstly acquire the first end pose data of the industrial robot when it is unloaded, and then acquire the end force data and second end pose data of the industrial robot after loading when the end of the industrial robot is subjected to an external force applied by the winch device. Subsequently, error calculation and optimization are performed based on the first end pose data and the second end pose data to obtain the end pose deformation data of the industrial robot in Cartesian space caused by the force. The third module is used to solve for the stiffness identification result of the industrial robot by calculating multiple Jacobian matrices, multiple end pose deformation data and multiple end force data corresponding to the multiple preset configuration positions 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 includes a winch device, a six-dimensional force / torque sensor, a posture acquisition device, and the control equipment as described in claim 6; The six-dimensional force / torque sensor is used to collect the end-effector force data of the industrial robot and transmit it to the control device; the pose acquisition device is used to collect the end-effector pose data of the industrial robot and transmit it to the control device; the control device is used to generate a control signal and transmit it to the winch device based on the error between the preset expected end-effector force data and the end-effector force data of the industrial robot transmitted by the six-dimensional force / torque sensor; the winch device is used to apply an external force to the end-effector of the industrial robot according to the control signal.

8. The industrial robot stiffness identification system according to claim 7, characterized in that, The winch device includes a winch, a servo motor, and a servo driver. The winch has a drum, which is connected to the end effector of the industrial robot via a steel cable. The servo driver is used to drive the servo motor to rotate according to the control signal. The servo motor is used to drive the drum to rotate in the rotating state, so as 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 pose acquisition device includes a laser tracker and a compatible laser tracking target.

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

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