CN114932542B - Industrial robot distance error compensation method and system - Google Patents
Industrial robot distance error compensation method and system Download PDFInfo
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- CN114932542B CN114932542B CN202210695777.9A CN202210695777A CN114932542B CN 114932542 B CN114932542 B CN 114932542B CN 202210695777 A CN202210695777 A CN 202210695777A CN 114932542 B CN114932542 B CN 114932542B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/10—Programme-controlled manipulators characterised by positioning means for manipulator elements
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
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Abstract
The invention discloses a method and a system for compensating distance errors of an industrial robot. The method comprises the following steps: constructing a robot working space grid; acquiring actual distances between each reference point of the small cube grid and the reference point of the guyed kinematic calibration system, and reading joint angle data of each reference point and the locating point of the robot; predicting a distance error of a positioning point in the grid by using the acquired actual distance and joint angle data; and compensating the predicted distance error to the theoretical distance to obtain the distance after the positioning point compensation. The invention avoids the introduction of conversion errors; compared with the traditional kinematic calibration method, the method has the advantages that complex kinematic parameter identification is not needed, and the distance after the positioning point compensation can be obtained only by predicting the distance error of the positioning point in the grid; compared with the traditional kinematic calibration, the distance precision of the robot can be obviously improved; compared with a laser tracker, the cost is greatly reduced, and the environmental requirement for collecting data is lower.
Description
Technical Field
The invention relates to a method and a system for compensating distance errors of an industrial robot, and belongs to the technical field of industrial robot calibration.
Background
The positioning accuracy of the robot is one of important performance indexes of the robot, and the positioning accuracy comprises repeated positioning accuracy and absolute positioning accuracy. The repeated positioning accuracy is often higher than the absolute positioning accuracy, and the repeated positioning accuracy can reach 0.02mm to 0.1mm, and the absolute positioning accuracy can only reach 1mm to 3mm. Then, there are many factors that cause the absolute positioning accuracy of the robot to be poor, including a kinematic parameter error (due to deformation of the joint link due to long-term use), a load factor, an environmental factor, and the like.
Robot programming is classified into on-line programming and off-line programming. The online programming means that the robot executes corresponding instructions in a teaching mode, the production efficiency is low in the programming mode, and the robot is required to stop working to perform programming; the off-line programming means that the robot motion or processing is simulated on a computer through the virtual simulation software of the robot, then the automatic generation code is sent to a robot controller, and the robot can move according to the simulation track. Currently, offline programming is widely used in the industry, but the key to the implementation of offline programming is the absolute positioning accuracy of the robot body.
Reference "Qiao Guifang, lv Zhongyan, zhang Ying, et al, robot positioning accuracy improvement based on BAS-PSO algorithm [ J ]. Optical precision engineering, 2021, 29 (4): 763-771 in order to improve the positioning accuracy of the robot, a BAS-PSO algorithm is proposed. The article aims at a Staublitx60 industrial robot, and the advantages that the longhorn beetle whisker search algorithm (BAS) can realize efficient optimization without gradient information compared with other intelligent optimization algorithms are considered, but the algorithm is easy to fall into a local optimal solution, and the particle swarm optimization algorithm (PSO) has parallel operation characteristics, and the optimization is realized through mutual cooperation of a plurality of individuals, so that the local optimization is not easy to fall into. Therefore, a BAS-PSO parameter identification algorithm is comprehensively provided, so that the accuracy of the position of the tail end of the robot after compensation is improved compared with that of the robot by a single method. At present, similar calibration methods are commonly adopted in the field of robots to improve the positioning accuracy of the robots, and the method has the following defects:
(1) The calibration method based on the position information needs to be pre-identified before the kinematic parameters are identified, namely the conversion between the measurement coordinate system and the robot base coordinate system, and the conversion process is complex in operation and is inevitably free from introducing conversion errors, so that the final calibration result is inaccurate.
(2) The robot calibration requires the use of an optimization algorithm to identify kinematic parameters, and then compensates the identified parameters into a robot controller, so that the accuracy of the robot is improved, wherein the parameter identification process is complex and difficult to realize.
(3) The current common equipment for collecting data is a laser tracker, which is expensive and has high requirements on the operating environment.
Disclosure of Invention
The invention provides a method and a system for compensating a distance error of an industrial robot, which are used for compensating a theoretical distance according to a predicted distance error and obtaining a compensated distance.
The technical scheme of the invention is as follows: an industrial robot distance error compensation method, comprising:
step 1, constructing a robot working space grid;
step 2, for each small cube grid in the robot working space grid, collecting each reference point K of the small cube grid pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj Reading each reference point K of the robot pj And positioning point K p Is included in the joint angle data; wherein K is pj A j-th reference point representing a p-th microcube grid; p=1, 2, …, m, m represents the total number of small cube meshes; j=1, 2, …,8; k (K) p Representing anchor points located in the p-th small cube mesh space;
step 3, using the actual distance L acquired in step 2 pj And joint angle data predicts a distance error at a location point within the grid;
step 4: compensating for a predicted distance error to a theoretical distance LT p On, obtain the locating point K p After compensationDistance L of (2) p ′。
The robot working space grid is constructed specifically as follows: and in the reachable range of the robot, dividing the working space of the robot into a series of small cube grids according to the set side length to obtain the working space grids of the robot.
The step 3 includes:
step 3.1, according to the positioning point K p The range of the joint angle of the robot in the joint space of the robot is determined to be a locating point K p The small cube grid is the p-th small cube grid in the robot working space grid; calculating each reference point K in the p-th small cube grid according to the collected joint angle data pj And positioning point K p Is a theoretical coordinate of (2);
step 3.2, according to each reference point K in the small cube grid p pj And positioning point K p Calculating the locating point K p With locating point K p Each reference point K of the small cube grid pj Distance d between pj The method comprises the steps of carrying out a first treatment on the surface of the According to distance d pj Calculating anchor point K using inverse distance weighting formula p To each reference point K pj Weight q of (2) pj ；
Step 3.3, according to each reference point K in the small cube grid p pj And from the acquired actual distance L pj Together identify P 0 Coordinates of the points; using P 0 Coordinates of points, reference points K in the small cube grid p pj And positioning point K p Calculating each reference point and reference point P 0 Theoretical distance LT between points pj Calculating the locating point K p And datum point P 0 Theoretical distance LT between points p ；
Step 3.4, using the actual distance L of each reference point acquired in step 2 pj And theoretical distance LT pj Calculating a distance error
Step 3.5, using the obtained weight q pj And distance error of each reference pointPredicting p-th microcube lattice localization point K p Distance error of->
An industrial robot distance error compensation system, comprising:
the construction module is used for constructing a robot working space grid;
the data set module is used for collecting each reference point K of each small cube grid in the robot working space grid pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj Reading each reference point K of the robot pj And positioning point K p Is included in the joint angle data; wherein K is pj A j-th reference point representing a p-th microcube grid; p=1, 2, …, m, m represents the total number of small cube meshes; j=1, 2, …,8; k (K) p Representing anchor points located in the p-th small cube mesh space;
a prediction module for using the actual distance L collected by the data set module pj And joint angle data predicts a distance error at a location point within the grid;
an acquisition module for compensating the predicted distance error to a theoretical distance LT p On, obtain the locating point K p Distance L after compensation p ′。
The beneficial effects of the invention are as follows:
(1) The invention does not need to convert the coordinate system, and avoids the introduction of conversion errors.
(2) Compared with the traditional kinematic calibration method, the method does not need to carry out complex kinematic parameter identification, and the distance after the positioning point compensation can be obtained only by predicting the distance error of the positioning point in the grid.
(3) Compared with the traditional kinematic calibration, the method can obviously improve the distance precision of the robot.
(4) The invention adopts a guyed kinematic calibration system when collecting data, which greatly reduces the cost compared with a laser tracker and has lower requirement on the environment for collecting data.
Drawings
FIG. 1 is a schematic illustration of a robot workspace meshing;
FIG. 2 is a schematic diagram of the distance error spatial interpolation compensation of the present invention;
fig. 3 is a graph of distance error similarity versus joint angle spacing for the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples, but the invention is not limited to the scope.
Example 1: as shown in fig. 1 to 3, an industrial robot distance error compensation method includes:
step 1, constructing a robot working space grid;
step 2, for each small cube grid in the robot working space grid, acquiring each reference point K of the small cube grid by using a guyed kinematic calibration system pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj Reading each reference point K of the robot by using an upper computer pj And positioning point K p Is included in the joint angle data; wherein K is pj Representing the jth reference point of the p-th small cube grid, wherein each reference point of the small cube grid is the vertex of the small cube grid; p=1, 2, …, m, m represents the total number of small cube meshes; j=1, 2, …,8; k (K) p Representing anchor points located in the p-th small cube mesh space;
step 3, using each reference point K of the small cube grid acquired in the step 2 pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj And joint angle data prediction grid localization point K p Distance error of (2);
step 4: compensating for a predicted distance error to a theoretical distance LT p On, obtain the locating point K p Distance L after compensation p ′。
Optionally, the constructing a robot workspace grid specifically includes: and in the reachable range of the robot, dividing the working space of the robot into a series of small cube grids according to the set side length to obtain the working space grids of the robot. In particular, a planning program for the entire cubic space grid may be written in the robot demonstrator, thereby constructing the robot workspace grid.
Optionally, the step 3 includes:
step 3.1, according to the positioning point K p The range of the joint angle of the robot in the joint space of the robot is determined to be a locating point K p The small cube grid is the p-th small cube grid in the robot working space grid; calculating each reference point K in the p-th small cube grid according to the collected joint angle data pj And positioning point K p Is a theoretical coordinate of (2);
step 3.2, according to each reference point K in the small cube grid p pj And positioning point K p Calculating the locating point K p With locating point K p Each reference point K of the small cube grid pj Distance d between pj (only d is marked in FIG. 2) p1 Other distances are similar; i.e. the Euclidean distance formula can be adopted to calculate d pj ) The method comprises the steps of carrying out a first treatment on the surface of the According to distance d pj Calculating anchor point K using inverse distance weighting formula p To each reference point K pj Weight q of (2) pj ；
Step 3.3, according to each reference point K in the small cube grid p pj And from the acquired actual distance L pj Together identify P 0 Coordinates of the points; using P 0 Coordinates of points, reference points K in the small cube grid p pj And positioning point K p Calculating each reference point and reference point P 0 Theoretical distance LT between points pj Calculating the locating point K p And datum point P 0 Theoretical distance LT between points p (i.e. using P 0 Coordinates of points, reference points K in the small cube grid p pj The theoretical coordinates of (2) are calculated by Euclidean distance formulaPoint and datum point P 0 Theoretical distance LT between points pj Using P 0 Coordinates of the point, anchor point K p The theoretical coordinates of (2) are calculated to obtain a locating point K by using an Euclidean distance formula p And datum point P 0 Theoretical distance LT between points p )；
Step 3.4, using the actual distance L of each reference point acquired in step 2 pj And theoretical distance LT pj Calculating a distance errorThe distance error is the actual distance L of each reference point pj And theoretical distance LT pj Absolute value of the difference;
step 3.5, using the obtained weight q pj And distance error of each reference pointPredicting p-th microcube lattice localization point K p Distance error of->
In step 1, in order to ensure similarity of distance errors, when the robot is used for grid division of a working space, the posture of the robot when moving from one grid to the next grid reference point should be kept consistent, or the changed angle should be as small as possible. The relationship between the distance error and the division amount h of each joint angle of the robot (namely, the Euclidean distance between the joint angles) is represented by a variation function value gamma, the value of the variation function is half of the increment variance of the distance error of the robot in the joint space, the similarity degree of the distance error of the robot can be quantitatively reflected, the relationship is as shown in figure 3, the smaller the division amount of the joint angle (namely, the closer the joint angle is), the smaller the variation function value is, the higher the similarity degree of the distance error is, which indicates that the similarity exists in the joint space of the robot, and the key of the space interpolation compensation method of the distance error is implemented. The formula of the variation function gamma formula and the formula of the joint angle dividing amount h are shown as follows:
since the local sample points of the robot are collected, the formula becomes:
where Δl (θ) is a distance error corresponding to the joint angle θ, and Δl (θ+h) is a distance error corresponding to a joint having a division amount of θ of h, θ u1 The joint angle of the ith joint, θ, as the first point u2 The joint angle of the u-th joint, where u=1, 2 …,6; n represents the number of samples collected.
In the step 3, the main formula of the inverse distance weighting method is as follows:
wherein (X) pj ,Y pj ,Z pj ) Representing reference point K pj Theoretical coordinates of (X) p ,Y p ,Z p ) Representing the locating point K p P=1, 2, …, m; j=1, 2, …,8;
in the step 3, P is calculated 0 (x 0 、y 0 、z 0 ) The main formula of the point coordinates is as follows:
P 0 ＝(A T A) -1 A T Y
in CK n For the nth reference point selected from the robot workspace grid, n is the total number of selected reference points, L n Representing the nth reference point of acquisition to P 0 Actual distance of (x) n ,y n ,z n ) Representing the theoretical coordinates of the nth reference point.
In the step 4, the compensated distance is L p ' means:
L p ′＝LT p +ΔL p
the relevant scholars prove that the distance precision can be used as a measure of the absolute positioning precision of the robot, and the absolute positioning precision of the robot can be improved to a certain extent by improving the distance precision of the robot. As can be seen from the comparison of the simulation of the distance errors before and after compensation and the table 1, the purpose of improving the distance accuracy of the robot is achieved through the compensation, and the purpose of improving the absolute positioning accuracy of the robot is achieved to a certain extent.
Table 1 simulation contrast of distance errors before and after compensation
| 10 positioning point numbers | Distance error before compensation (unit mm) | Distance error after compensation (unit mm) |
| 1 | 0.197 | 0.00041 |
| 2 | 0.191 | 0.00047 |
| 3 | 0.182 | 0.00050 |
| 4 | 0.189 | 0.00044 |
| 5 | 0.200 | 0.00032 |
| 6 | 0.198 | 0.00030 |
| 7 | 0.193 | 0.00036 |
| 8 | 0.188 | 0.00042 |
| 9 | 0.181 | 0.00047 |
| 10 | 0.179 | 0.00045 |
Example 2: an industrial robot distance error compensation system, comprising:
the construction module is used for constructing a robot working space grid;
the data set module is used for collecting each reference point K of each small cube grid in the robot working space grid pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj Reading each reference point K of the robot pj And positioning point K p Is included in the joint angle data; wherein K is pj A j-th reference point representing a p-th microcube grid; p=1, 2, …, m, m represents the total number of small cube meshes; j=1, 2, …,8; k (K) p Representing anchor points located in the p-th small cube mesh space;
a prediction module for using the actual distance L collected by the data set module pj And joint angle data predicts a distance error at a location point within the grid;
an acquisition module for compensating the predicted distance error to a theoretical distance LT p On, obtain the locating point K p Distance L after compensation p ′。
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
While the present invention has been described in detail with reference to the drawings, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.
Claims (4)
1. An industrial robot distance error compensation method is characterized in that: comprising the following steps:
step 1, constructing a robot working space grid;
step 2, for each small cube grid in the robot working space grid, collecting each reference point K of the small cube grid pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj Reading each reference point K of the robot pj And positioning point K p Is included in the joint angle data; wherein K is pj A j-th reference point representing a p-th microcube grid; p=1, 2, …, m, m represents the total number of small cube meshes; j=1, 2, …,8; k (K) p Representing anchor points located in the p-th small cube mesh space;
step 3, using the actual distance L acquired in step 2 pj And joint angle data predicts a distance error at a location point within the grid;
step 4: compensating for a predicted distance error to a theoretical distance LT p On, obtain the locating point K p Distance L after compensation p ′；
In the step 1, when the robot is moved from one grid reference point to the next grid reference point, the change amount of each joint angle should be as small as possible, at this time, the joint angle dividing amount, that is, the euclidean distance between the joint angles is used to represent the approaching degree of the joint angles of each reference point of the robot, so as to reflect the changing degree of the joint angles between each reference point, and the variation function value γ is used to represent the similarity degree of the distance errors of the robot, so as to quantitatively reflect the relationship between the changing degree of the joint angles of the robot and the similarity degree of the distance errors; the formula of the variation function gamma formula and the formula of the joint angle dividing amount h are shown as follows:
where Δl (θ) is a distance error corresponding to the joint angle θ, and Δl (θ+h) is a distance error corresponding to a joint having a division amount of θ of h, θ u1 The joint angle of the ith joint, θ, as the first point u2 The joint angle of the u-th joint, u=1, 2 …,6; n represents the number of samples collected.
2. The industrial robot distance error compensation method according to claim 1, wherein: the robot working space grid is constructed specifically as follows: and in the reachable range of the robot, dividing the working space of the robot into a series of small cube grids according to the set side length to obtain the working space grids of the robot.
3. The industrial robot distance error compensation method according to claim 1, wherein: the step 3 includes:
step 3.1, according to the positioning point K p The range of the joint angle of the robot in the joint space of the robot is determined to be a locating point K p The small cube grid is the p-th small cube grid in the robot working space grid; calculating each reference point K in the p-th small cube grid according to the collected joint angle data pj And positioning point K p Is a theoretical coordinate of (2);
step 3.2, according to each reference point K in the small cube grid p pj And positioning point K p Calculating the locating point K p With locating point K p Each reference point K of the small cube grid pj Distance d between pj The method comprises the steps of carrying out a first treatment on the surface of the According to distance d pj Calculating anchor point K using inverse distance weighting formula p To each reference point K pj Weight q of (2) pj ；
Step 3.3, according to each reference point K in the small cube grid p pj And from the acquired actual distance L pj Together identify P 0 Coordinates of the points; using P 0 Coordinates of points, reference points K in the small cube grid p pj And positioning point K p Calculating each reference point and reference point P 0 Theoretical distance LT between points pj Calculating the locating point K p And datum point P 0 Theoretical distance LT between points p ；
Step 3.4, using the actual distance L of each reference point acquired in step 2 pj And theoretical distance LT pj Calculate the distance error DeltaL pj ；
Step 3.5, using the obtained weight q pj And the distance error DeltaL of each reference point pj Predicting p-th microcube lattice localization point K p Distance error Δl of (a) p 。
4. An industrial robot distance error compensation system, characterized in that: comprising the following steps:
the construction module is used for constructing a robot working space grid;
the data acquisition module is used for acquiring each reference point K of each small cube grid in the robot working space grids pj Datum point P of stay wire type kinematic calibration system 0 Actual distance L between points pj Reading each reference point K of the robot pj And positioning point K p Is included in the joint angle data; wherein K is pj A j-th reference point representing a p-th microcube grid; p=1, 2, …, m, m represents the total number of small cube meshes; j=1, 2, …,8; k (K) p Representing anchor points located in the p-th small cube mesh space;
a prediction module for using the actual distance L acquired by the data acquisition module pj And joint angle data predicts a distance error at a location point within the grid;
an acquisition module for compensating the predicted distance error to a theoretical distance LT p On, obtain the locating point K p Distance L after compensation p ′；
In the construction module, when the robot working space grid is divided, the change amount of each joint angle is as small as possible when the robot moves from one grid reference point to the next grid reference point, at the moment, the joint angle dividing amount, namely the Euclidean distance between the joint angles, is used for representing the approaching degree of the joint angles of each reference point of the robot, so that the change degree of the joint angles between each reference point is reflected, the variation function value gamma is used for representing the similarity degree of the distance error of the robot, and the relationship between the change degree of the joint angles of the robot and the similarity degree of the distance error is quantitatively reflected; the formula of the variation function gamma formula and the formula of the joint angle dividing amount h are shown as follows:
where Δl (θ) is a distance error corresponding to the joint angle θ, and Δl (θ+h) is a distance error corresponding to a joint having a division amount of θ of h, θ u1 The joint angle of the ith joint, θ, as the first point u2 The joint angle of the u-th joint, u=1, 2 …,6; n represents the number of samples collected.
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