Industrial robot precision calibration method suitable for multiple installation states, storage medium, equipment and computer program product

Abstract

The invention discloses an industrial robot precision calibration method suitable for multiple installation states, a storage medium, equipment and a computer program product, and the method comprises the steps: enabling an industrial robot to be in three installation states: vertical fixation, inverted hanging fixation and side hanging fixation, and building a world coordinate system; the method comprises the following steps: collecting space coordinates of a target ball of the laser tracker under different world coordinate systems, unifying the space coordinates to the same world coordinate system through coordinate conversion, and carrying out identification parameter error correction on the space coordinates of the target ball of the laser tracker subjected to space coordinate conversion and theoretical coordinates based on an iterative reweighted least square method to obtain the identification parameter error of the industrial robot. And the precision calibration of the industrial robot is realized. According to the calibration method, the robot has unified precision performance during vertical fixation, inverted hanging fixation and side hanging fixation, so that the time for re-calibration can be saved, and the working efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial robot calibration, and in particular to an industrial robot precision calibration method, storage medium, device and computer program product applicable to multiple installation states. Background Art

[0002] With the development of robot technology, industrial robots are gradually used in welding, cutting, assembly and other fields, but the absolute positioning accuracy of industrial robots is still poor and cannot be applied to high-end manufacturing fields such as the aerospace industry. Studies have shown that robot calibration technology can effectively improve the accuracy performance of robots.

[0003] The positioning error of industrial robots is usually divided into joint error, geometric parameter error and non-geometric parameter error, among which geometric parameter error accounts for more than 80% of the total error. The geometric parameter calibration process of industrial robots is mainly divided into four steps: modeling, measurement, identification and compensation. The modeling step in the calibration process of industrial robots is mainly to establish a geometric parameter error model, which usually includes three types: posture error model, position error model and distance error model. Studies have shown that the posture error model is more complete than the other two error models, and the accuracy of the parameter identification result is relatively high. At present, the calibration work of industrial robots is to fix the industrial robot on the ground and use laser trackers and other equipment to measure the error. With the increasing application of industrial robots, industrial robots are also installed on gantry or wall. Due to the different installation states of industrial robots, additional errors will be generated. In this case, recalibration is required, which will generate a large workload for end users. Therefore, it is urgent to invent and design a calibration method that enables a robot to have uniform accuracy performance when it is fixed vertically, hung upside down, or fixed on a wall, thereby saving the time for re-calibration and improving work efficiency. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the technical defects and shortcomings of the prior art and provide an industrial robot precision calibration method, storage medium, equipment and computer program product suitable for multiple installation states, so that the robot has a calibration method with uniform precision performance when it is fixed vertically, inverted or side-mounted, thereby saving time for re-calibration and improving work efficiency.

[0005] To achieve the above technical objectives, the present invention adopts the following technical solution: a precision calibration method for an industrial robot applicable to multiple installation states, specifically comprising the following steps:

[0006] Step 1: Place the laser tracker target ball on the upper surface of the turntable at a horizontal position of 0°;

[0007] Step 2: Place the laser tracker target ball at several non-collinear positions, use the laser tracker to read the spatial coordinates of each position, and fit the first plane S g1 ;

[0008] Step 3: Fix the industrial robot on the turntable, fix the laser tracker target ball on the end of the industrial robot, randomly rotate the first rotation axis of the industrial robot to different angles, use the laser tracker to read the spatial coordinates of the laser tracker target ball at different rotation angles, fit the circle and determine the center of the circle, and project the center of the circle onto the first plane S g1 Get point P1;

[0009] Step 4: Randomly rotate the second rotation axis of the industrial robot to different angles, use the laser tracker to read the spatial coordinates of the laser tracker target ball at different rotation angles, and fit the second plane S xz1 ;

[0010] Step 5: Take point P1 as the coordinate origin and the second plane S xz1 is the xz plane, the first plane S g1 For the xy plane, establish the first world coordinate system W xyz1 ;

[0011] Step 6: Place the laser tracker target ball on a turntable that rotates 90°, and establish the second world coordinate system W according to steps 2 to 5. xyz2 ;

[0012] Step 7: Place the laser tracker target ball on a turntable that rotates 180°, and establish the third world coordinate system W according to steps 2 to 5. xyz3 ;

[0013] Step 8, respectively in the first world coordinate system W xyz1 , the second world coordinate system W xyz2 and the third world coordinate system W xyz3 The spatial coordinates of the target ball of the laser tracker under different motion positions of the industrial robot are randomly collected, and the second world coordinate system W xyz2 and the third world coordinate system W xyz3 The spatial coordinates under are transformed into the first world coordinate system W xyz1 Down;

[0014] Step 9: Correct the error of the identification parameters of the industrial robot based on the iterative reweighted least square method by comparing the spatial coordinates of the target ball of the laser tracker that is undergoing spatial coordinate transformation with the theoretical coordinates, so as to achieve precision calibration of the industrial robot.

[0015] Furthermore, the first rotation axis and the second rotation axis of the industrial robot refer to the first rotation axis and the second rotation axis of the industrial robot in the direction from the base to the end, respectively.

[0016] Furthermore, in step 8, the second world coordinate system W xyz2 Convert to the first world coordinate system W xyz1 The process is:

[0017] W xyz1 =W xyz2 *H1

[0018] The third world coordinate system W xyz3 Convert to the first world coordinate system W xyz1 The process is:

[0019] W xyz1 =W xyz3 *H2

[0020] Among them, H1 represents the second world coordinate system W xyz2 Convert to the first world coordinate system W xyz1 The transformation matrix H2 represents the transformation of the third world coordinate system W xyz3 Convert to the first world coordinate system W xyz1 The transformation matrix.

[0021] Furthermore, step 9 includes the following sub-steps:

[0022] Step 9.1, calculate the difference between the spatial coordinates of the target ball of the laser tracker that is undergoing spatial coordinate transformation and the corresponding theoretical coordinates, establish an M-DH error model, and determine the error Jacobian matrix;

[0023] Step 9.2, establish the identification objective function based on iterative reweighted least squares method through the calculated difference, and determine the initial identification parameter error through the least squares method, and determine the coefficient of the initial Ramsay weight function in combination with the error Jacobian matrix;

[0024] Step 9.3, input the coefficient into the Ramsay weight function, obtain the iteration weight, and then input the iteration weight into the identification objective function to calculate the identification parameter error;

[0025] Step 9.4: Update the coefficients of the Ramsay weight function in combination with the error Jacobian matrix, and repeat step 9.3 until the identification objective function converges to obtain the optimal identification parameter error;

[0026] Step 9.5: Use the optimal identification parameter error for precision calibration of the industrial robot.

[0027] Furthermore, the M-DH error model is:

[0028]

[0029] Wherein, ΔT=[Δn, Δo, Δb, Δp] represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates, Δn represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the x-axis, Δo represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the y-axis, Δb represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the z-axis, Δp represents the error value between the spatial coordinate vector of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinate vector, Δη=[Δθ i ,Δd i ,Δa i ,Δα i ,Δβ i ] is the identification parameter error of the industrial robot, N is the number of joints of the industrial robot, i is the index of N, Δθ i represents the joint angle error of the i-th joint, Δd i represents the offset error of the link on the i-th joint, Δa i represents the link length error of the i-th joint, Δα i represents the torsion angle error of the link on the i-th joint, Δβ i represents the joint offset error of the i-th joint; represents the error Jacobian matrix, H n represents the error transformation matrix of the x-axis, H o represents the error transformation matrix of the y-axis, H b represents the error transformation matrix of the z-axis, H p Represents the error transformation matrix of the vector.

[0030] Furthermore, the specific process of establishing the identification objective function based on iterative reweighted least squares method by calculating the difference in step 9.2 is:

[0031]

[0032] Where W represents the Ramsay weight, c represents the weight decay rate, δ represents the coefficient of the Ramsay weight function, and the initial value of δ is B0 represents the initial identification parameter error of the industrial robot, Q represents The interquartile range.

[0033] Furthermore, the process of determining the initial identification parameter error B0 of the industrial robot is as follows: under the identification objective function without considering the Ramsay weight, the objective function value is determined by the least squares method, and the initial identification parameter error of the industrial robot is inferred by the M-DH error model.

[0034] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the industrial robot precision calibration method applicable to multiple installation states.

[0035] Furthermore, the present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the industrial robot precision calibration method applicable to multiple installation states is implemented.

[0036] Furthermore, the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the industrial robot precision calibration method applicable to multiple installation states.

[0037] Compared with the prior art, the present invention has the following beneficial effects: the present invention is applicable to the precision calibration method of industrial robots in multiple installation states, and can perform uniform precision calibration on industrial robots in three installation states: vertical fixation, inverted fixation, and side-hanging fixation, thereby avoiding secondary calibration of the industrial robot during use, saving calibration time, and improving work efficiency; at the same time, the present invention adopts an iterative reweighted least squares method to correct the identification parameter errors of the industrial robot, which can effectively reduce the influence of outliers in the measurement error on parameter identification, and at the same time can solve the problem of mismatch in the dimensions and magnitude of the posture and attitude in the identification objective function through weight iteration, thereby effectively improving the precision of the industrial robot identification parameter calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a schematic diagram of an industrial robot calibration system of the present invention;

[0039] Figure 2 is a schematic diagram of a rotating table in the present invention;

[0040] Figure 3 is a schematic diagram of an industrial robot of the industrial robot calibration system of the present invention being located on a horizontal turntable;

[0041] Figure 4 Schematic diagram of an industrial robot calibration system of the present invention, in which an industrial robot is located on a turntable rotated 90°

[0042] Figure 5 is a schematic diagram of an industrial robot of the industrial robot calibration system of the present invention located on a turntable rotated 180°;

[0043] Figure 6 It is a flow chart of the precision calibration method of an industrial robot applicable to multiple installation states of the present invention. DETAILED DESCRIPTION

[0044] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0045] like Figure 1 Schematic diagram of the industrial robot calibration system of the present invention, the industrial robot calibration system comprises: laser tracker 101, laser tracker target ball 102, target ball adapter plate 103, industrial robot 104, rotating table 105, laser tracker 101 is used to read the position coordinates of laser tracker target ball 102, industrial robot 104 is fixed on rotating table 105, target ball adapter plate 103 can fix the laser tracker target ball 102 and industrial robot 104. The industrial robot 104 is provided with a first rotating axis 1041 and a second rotating axis 1042, the first rotating axis 1041 and the second rotating axis 1042 of the industrial robot 104 respectively refer to the first rotating axis and the second rotating axis of the industrial robot 104 in the direction from the base to the end. Figure 2 The rotating platform 105 includes a base 201 , a rotating structure 202 and a rotating platform 203 . The rotating structure 202 is disposed on the base 201 , and the rotating structure 202 is connected to the rotating platform 203 .

[0046] like Figure 6 The present invention is a flow chart of a method for calibrating the precision of an industrial robot in multiple installation states, and the method specifically comprises the following steps:

[0047] Step 1: Place the laser tracker target ball on the upper surface of the turntable at a horizontal position of 0°;

[0048] Step 2: Place the laser tracker target ball at several non-collinear positions, use the laser tracker to read the spatial coordinates of each position, and fit the first plane S g1 ;

[0049] Step 3: Figure 3 , fix the industrial robot on the turntable, fix the laser tracker target ball on the end of the industrial robot, randomly rotate the first rotation axis of the industrial robot to different angles, use the laser tracker to read the spatial coordinates of the laser tracker target ball at different rotation angles, fit the circle and determine the center of the circle, and project the center of the circle onto the first plane S g1 Get point P1;

[0050] Step 4: Randomly rotate the second rotation axis of the industrial robot to different angles, use the laser tracker to read the spatial coordinates of the laser tracker target ball at different rotation angles, and fit the second plane S xz1 ;

[0051] Step 5: Take point P1 as the coordinate origin and the second plane S xz1 is the xz plane, the first plane S g1For the xy plane, establish the first world coordinate system W xyz1 ;

[0052] Step 6: Figure 4 , place the laser tracker target ball on a turntable that rotates 90°, and follow steps 2 to 5 to establish the second world coordinate system W xyz2 ;

[0053] Step 7: Figure 5 , place the laser tracker target ball on a turntable that rotates 180°, and follow steps 2 to 5 to establish the third world coordinate system W xyz3 ;

[0054] Step 8, respectively in the first world coordinate system W xyz1 , the second world coordinate system W xyz2 and the third world coordinate system W xyz3 The spatial coordinates of the target ball of the laser tracker under different motion positions of the industrial robot are randomly collected, and the second world coordinate system W xyz2 and the third world coordinate system W xyz3 The spatial coordinates under are transformed into the first world coordinate system W xyz1 Down;

[0055] Second world coordinate system W xyz2 Convert to the first world coordinate system W xyz1 The process is:

[0056] W xyz1 =W xyz2 *H1

[0057] The third world coordinate system W xyz3 Convert to the first world coordinate system W xyz1 The process is:

[0058] W xyz1 =W xyz3 *H2

[0059] Among them, H1 represents the second world coordinate system W xyz2 Convert to the first world coordinate system W xyz1 The transformation matrix H2 represents the transformation of the third world coordinate system W xyz3 Convert to the first world coordinate system W xyz1 The transformation matrix.

[0060] The present invention performs unified precision calibration on the industrial robot in three installation states of vertical fixation, inverted fixation, and side-hanging fixation by converting the coordinate system into the same world coordinate system, thereby avoiding secondary calibration of the industrial robot during use, saving calibration time, and improving work efficiency; in addition, the present invention can also set the calibration state to a continuous rotation state.

[0061] Step 9: The spatial coordinates of the target ball of the laser tracker that is undergoing spatial coordinate transformation and the theoretical coordinates are used to correct the identification parameter errors of the industrial robot based on the iterative reweighted least squares method, so as to better identify and correct abnormal values, and achieve a good balance in terms of dimension and magnitude, so as to achieve precision calibration of the industrial robot, which specifically includes the following sub-steps:

[0062] Step 9.1: Calculate the difference between the spatial coordinates of the laser tracker target ball that is undergoing spatial coordinate transformation and the corresponding theoretical coordinates. Establishing the M-DH error model Determine the error Jacobian matrix H = [Hn T Ho T Ha T Hp T ] T , where ΔT represents the spatial coordinate P of the laser tracker target ball for spatial coordinate transformation t The corresponding theoretical coordinates P N , Δn represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the x-axis, Δo represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the y-axis, Δb represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the z-axis, Δp represents the error value between the spatial coordinate vector of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinate vector, Δη=[Δθ i ,Δd i ,Δa i ,Δα i ,Δβ i ] is the identification parameter error of the industrial robot, N is the number of joints of the industrial robot, i is the index of N, Δθ i represents the joint angle error of the i-th joint, Δd i represents the offset error of the link on the i-th joint, Δa i represents the link length error of the i-th joint, Δα i represents the torsion angle error of the link on the i-th joint, Δβ i represents the joint offset error of the i-th joint; represents the error Jacobian matrix, H n represents the error transformation matrix of the x-axis, H o represents the error transformation matrix of the y-axis, H b represents the error transformation matrix of the z-axis, H p Represents the error transformation matrix of the vector.

[0063] Step 9.2: Establish the identification objective function based on iterative reweighted least squares method through the calculated difference, and determine the initial identification parameter error through the least squares method, and determine the coefficients of the initial Ramsay weight function in combination with the error Jacobian matrix.

[0064] The specific process of establishing the identification target function based on iterative reweighted least squares method by calculating the difference in the present invention is as follows:

[0065]

[0066] Where W represents the Ramsay weight, c represents the weight decay rate, δ represents the coefficient of the Ramsay weight function, and the initial value of δ is B0 represents the initial identification parameter error of the industrial robot. Without considering the identification objective function of Ramsay weight, the identification objective function value is determined by the least square method, and the initial identification parameter error of the industrial robot is inferred by the M-DH error model; Q represents The interquartile range. The construction of the identification objective function of the present invention introduces the concept of weight, which can balance the different numerical magnitudes and dimensions of the position error and the attitude error, so that the position error and the attitude error can be improved to the same extent. In addition, since the Ramsay weight function is continuous and smooth, the iterative Ramsay weight changes more smoothly in the iterative calculation, and the optimization process is more stable. At the same time, the Ramsay weight function can effectively reduce the impact of outliers on the results, while retaining the high weight of small deviation data, thereby improving the accuracy of the optimization of the identification objective function.

[0067] Step 9.3, input the coefficient into the Ramsay weight function, obtain the iteration weight, and input the iteration weight into the identification objective function to calculate the identification parameter error;

[0068] Step 9.4: Update the coefficients of the Ramsay weight function in combination with the error Jacobian matrix, and repeat step 9.3 until the identification objective function converges to obtain the optimal identification parameter error;

[0069] Step 9.5: Use the optimal identification parameter error for precision calibration of the industrial robot.

[0070] The present invention constructs an identification objective function based on the iterative reweighted least squares method, which can effectively reduce the influence of outliers on parameter identification and better balance the mismatch of the dimensional magnitude of the industrial robot's posture, thereby effectively improving the positioning accuracy of the serial industrial robot.

[0071] In a technical solution of the present invention, a computer-readable storage medium is further provided, storing a computer program, wherein the computer program enables a computer to execute the industrial robot precision calibration method applicable to multiple installation states.

[0072] In a technical solution of the present invention, an electronic device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the industrial robot precision calibration method applicable to multiple installation states is implemented.

[0073] In a technical solution of the present invention, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the industrial robot precision calibration method applicable to multiple installation states is implemented.

[0074] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0075] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0076] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A precision calibration method for industrial robots in multiple installation states, characterized in that: The specific steps include: Step 1: Place the laser tracker target ball on the upper surface of the turntable at a horizontal position of 0°; Step 2: Place the laser tracker target ball at several non-collinear positions, use the laser tracker to read the spatial coordinates of each position, and fit the first plane S g1 ; Step 3: Fix the industrial robot on the turntable, fix the laser tracker target ball on the end of the industrial robot, randomly rotate the first rotation axis of the industrial robot to different angles, use the laser tracker to read the spatial coordinates of the laser tracker target ball at different rotation angles, fit the circle and determine the center of the circle, and project the center of the circle onto the first plane S g1 Get point P1; Step 4: Randomly rotate the second rotation axis of the industrial robot to different angles, use the laser tracker to read the spatial coordinates of the laser tracker target ball at different rotation angles, and fit the second plane S xz1 ; Step 5: Take point P1 as the origin of the coordinate system and the second plane S xz1 is the xz plane, the first plane S g1 For the xy plane, establish the first world coordinate system W xyz1 ; Step 6: Place the laser tracker target ball on a turntable that rotates 90°, and establish the second world coordinate system W according to steps 2 to 5. xyz2 ; Step 7: Place the laser tracker target ball on a turntable that rotates 180°, and establish the third world coordinate system W according to steps 2 to 5. xyz3 ; Step 8, respectively in the first world coordinate system W xyz1 , the second world coordinate system W xyz2 and the third world coordinate system W xyz3 The spatial coordinates of the target ball of the laser tracker under different motion positions of the industrial robot are randomly collected, and the second world coordinate system W xyz2 and the third world coordinate system W xyz3 The spatial coordinates under are transformed into the first world coordinate system W xyz1 Down; Step 9: Correct the error of the identification parameters of the industrial robot based on the iterative reweighted least square method by comparing the spatial coordinates of the target ball of the laser tracker that is undergoing spatial coordinate transformation with the theoretical coordinates, so as to achieve precision calibration of the industrial robot.

2. The method for calibrating the precision of an industrial robot applicable to multiple installation states according to claim 1, characterized in that: The first rotation axis and the second rotation axis of the industrial robot refer to the first rotation axis and the second rotation axis of the industrial robot in the direction from the base to the end, respectively.

3. The method for calibrating the precision of an industrial robot applicable to multiple installation states according to claim 1, characterized in that: The second world coordinate system W in step 8 xyz2 Convert to the first world coordinate system W xyz1 The process is: IN xyz1 =In xyz2 *H1 The third world coordinate system W xyz3 Convert to the first world coordinate system W xyz1 The process is: W xyz1 =W xyz3 *H2 Among them, H1 represents the second world coordinate system W xyz2 Convert to the first world coordinate system W xyz1 The transformation matrix H2 represents the transformation of the third world coordinate system W xyz3 Convert to the first world coordinate system W xyz1 The transformation matrix.

4. The method for calibrating the precision of an industrial robot applicable to multiple installation states according to claim 1, characterized in that: Step 9 includes the following sub-steps: Step 9.1, calculate the difference between the spatial coordinates of the target ball of the laser tracker that is undergoing spatial coordinate transformation and the corresponding theoretical coordinates, establish an M-DH error model, and determine the error Jacobian matrix; Step 9.2, establish the identification objective function based on iterative reweighted least squares method through the calculated difference, and determine the initial identification parameter error through the least squares method, and determine the coefficient of the initial Ramsay weight function in combination with the error Jacobian matrix; Step 9.3, input the coefficient into the Ramsay weight function, obtain the iteration weight, and then input the iteration weight into the identification objective function to calculate the identification parameter error; Step 9.4: Update the coefficients of the Ramsay weight function in combination with the error Jacobian matrix, and repeat step 9.3 until the identification objective function converges to obtain the optimal identification parameter error; Step 9.5: Use the optimal identification parameter error for precision calibration of the industrial robot.

5. The method for calibrating the precision of an industrial robot applicable to multiple installation states according to claim 4, characterized in that: The M-DH error model is: Wherein, ΔT=[Δn, Δo, Δb, Δp] represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates, Δn represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the x-axis, Δo represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the y-axis, Δb represents the error value between the spatial coordinates of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinates on the z-axis, Δp represents the error value between the spatial coordinate vector of the laser tracker target ball for spatial coordinate transformation and the corresponding theoretical coordinate vector, Δη=[Δθ i ,Δd i ,Δa i ,Δα i ,Δβ i ] is the identification parameter error of the industrial robot, N is the number of joints of the industrial robot, i is the index of N, Δθ i represents the joint angle error of the i-th joint, Δd i represents the offset error of the link on the i-th joint, Δa i represents the link length error of the i-th joint, Δα i represents the torsion angle error of the link on the i-th joint, Δβ i represents the joint offset error of the i-th joint; represents the error Jacobian matrix, H n represents the error transformation matrix of the x-axis, H o represents the error transformation matrix of the y-axis, H b represents the error transformation matrix of the z-axis, H p Represents the error transformation matrix of the vector.

6. The method for calibrating the precision of an industrial robot applicable to multiple installation states according to claim 5, characterized in that: The specific process of establishing the identification objective function based on iterative reweighted least squares method by calculating the difference in step 9.2 is: Where W represents the Ramsay weight, c represents the weight decay rate, δ represents the coefficient of the Ramsay weight function, and the initial value of δ is B0 represents the initial identification parameter error of the industrial robot, Q represents The interquartile range.

7. The method for calibrating the precision of an industrial robot applicable to multiple installation states according to claim 6, characterized in that: The process of determining the initial identification parameter error B0 of the industrial robot is as follows: under the identification objective function without considering the Ramsay weight, the objective function value is determined by the least squares method, and the initial identification parameter error of the industrial robot is inferred by the M-DH error model.

8. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables a computer to execute the industrial robot precision calibration method applicable to multiple installation states as described in any one of claims 1 to 7.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for calibrating the precision of an industrial robot applicable to multiple installation states as described in any one of claims 1 to 7 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for calibrating the precision of an industrial robot applicable to multiple installation states as described in any one of claims 1 to 7 is implemented.

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