CN115319726A - A Robot Calibration Method Based on Position and Distance Constraints - Google Patents

Abstract

The invention discloses a robot calibration method based on position and distance constraints, which comprises the steps of establishing a kinematic model of a robot and a kinematic error model based on position constraints and distance constraints; mounting the tail end calibration device to the tail end of the robot, and mounting the geometric constraint device into a working space of the robot; dragging the robot to make the calibration ball of the tail end calibration device constrained to each ball seat on the geometric constraint device, touching each ball seat for a plurality of times in different configurations, and reading and recording joint angle data measured each time; identifying kinematic model parameters of the corresponding robot; and compensating the identified kinematic model parameter errors to a controller of the robot. The invention has the advantages of low cost, good portability, simple and convenient operation, difficult damage and the like.

Description

A Robot Calibration Method Based on Position and Distance Constraints

technical field

The invention belongs to the technical field of robot calibration, and in particular relates to a robot calibration method based on position and distance constraints.

Background technique

A collaborative robot is a new type of industrial robot that can work closely with humans. Compared with traditional industrial robots, collaborative robots have the advantages of light weight, good flexibility, high safety, draggable teaching, easy deployment and implementation, and support for human-machine collaboration. Variety production needs, but also can be applied to the field of social services, to achieve safe and friendly human-computer interaction, has a very broad development prospects.

However, due to certain errors in the processing and assembly of collaborative robots, the absolute positioning accuracy of collaborative robots is poor. Therefore, in order to improve the absolute positioning accuracy of the collaborative robot, it is often necessary to calibrate the robot.

For robot calibration, scholars at home and abroad have carried out fruitful research work and established a robot kinematics calibration method consisting of four main steps: error modeling, pose measurement, parameter identification, and error compensation, which effectively improves the absolute accuracy of industrial robots. positioning accuracy. However, most of the existing robot kinematics calibration methods need to rely on external precision measurement equipment such as laser trackers, arm-type three-coordinate measuring instruments, and wire-drawn measurement systems to measure the position or pose of the robot, and these large-scale precision measurement equipment has a price It is relatively expensive, high in use and maintenance costs, poor in convenience, and difficult in on-site deployment and implementation, making it difficult to meet the regular on-site calibration needs of collaborative robots.

In response to the above problems, in recent years, many researchers have begun to explore low-cost, portable self-calibration devices. CN107042528A discloses an industrial robot calibration device. Three detection clubs fixed at the end of the robot are contacted with a target sphere fixed on the desktop, and the readings of three displacement sensors are read. The same or different spheres are touched twice, and the nominal distance and the actual distance are used. The deviation of the value calibrates the robot. However, when the displacement sensor of the above-mentioned device touches the sphere, the force direction does not coincide with the measurement direction of the displacement sensor, which easily causes force deformation of the detection club, which in turn affects the subsequent calibration accuracy of the device.

How to provide a low-cost, portable, and non-destructive collaborative robot calibration solution is an urgent problem to be solved.

Contents of the invention

The main purpose of the present invention is to provide a robot calibration method based on position and distance constraints with low cost, good portability, and not easy to damage, so as to overcome the shortcomings of the prior art.

In order to achieve the aforementioned object of the invention, the technical solution adopted by the present invention includes: a robot calibration method based on position and distance constraints, the method is realized based on a robot calibration device, and the robot calibration device includes an end calibration device and a geometric constraint device, The end calibration device includes a connection base and a calibration ball installed at one end of the connection base, the geometric constraint device includes a constraint support base and a plurality of ball seats arranged on the constraint support base, and the method includes:

S1, establishing a model, the model including a kinematics model of the robot, a first kinematics error model based on a position constraint, and a second kinematics error model based on a distance constraint;

S2, measuring installation, including measuring the first relative pose between the calibration ball on the end calibration device and the connecting seat, and the second relative pose between the ball seats on the geometric constraint device , after the measurement, install the end calibration device on the end of the robot, and install the geometric constraint device in the working space of the robot;

S3, data acquisition, including changing the position of the geometric constraint device in the working space of the robot multiple times, dragging the robot at each position, so that the calibration ball of the end calibration device is constrained to each ball on the geometric constraint device Seat, and each ball seat is touched several times in different configurations, and the joint angle data after each measurement operation is stabilized is read and recorded;

S4, parameter identification, including dividing the joint angle data into several groups according to different geometric constraint device poses, and then dividing them into several groups according to different ball seat positions, and substituting pairs of data from the same group into the first motion In the kinematic error model, the data of the same group but different groups are paired into the second kinematic error model, and then the two error model data are mixed to identify the corresponding kinematic model parameters of the robot;

S5, error compensation, including compensating the identified kinematics model parameter error to the controller of the robot.

In a preferred embodiment, in said S1, the corresponding relationship between the end pose of the robot and the joint angle, joint screw and initial pose is established through the global exponential product formula, and the kinematics model is constructed; through the adjoint transformation matrix The corresponding relationship between the position constraint error, the joint screw error and the initial pose error is established, and the first kinematics error model is constructed; the distance constraint error, the joint screw error, and the initial pose error are established through the adjoint transformation matrix The corresponding relationship among them is used to construct the second kinematics error model.

In a preferred embodiment, the global exponential product formula is expressed as follows:

Among them, T _{0, n+1} represents the coordinates of the end pose of the robot in the base coordinate system, s _i (i=1, 2, ..., n) represents the coordinates of the joint screw of the robot in the base coordinate system, q _i (i=1, 2, ..., n) represents the rotation angle of each joint of the robot, that is, the joint angle, and T _{0, n+1} (0) represents the initial pose of the end of the robot relative to the base coordinate system.

In a preferred embodiment, the first kinematic error model is expressed as follows:

Y _PC = A _PC X;

表示两种不同构型下的末端位置误差，X表示待辨识的模型参数误差，A_PC表示末端位置误差与模型参数误差之间的位置约束关系矩阵，所述A_PC表示为：in,

Represents the terminal position error under two different configurations, X represents the model parameter error to be identified, A _PC represents the position constraint relationship matrix between the terminal position error and the model parameter error, and the A _PC is expressed as:

Among them, p is the coordinate of the nominal end position, I ₃ represents the identity matrix of 3×3, Ad(·) represents the accompanying transformation matrix corresponding to the homogeneous transformation matrix, and A _j (j=1, 2) is expressed as:

In a preferred embodiment, the second kinematic error model is expressed as follows:

Y _DC = A _DC X,;

表示两种不同构型下的名义末端距离与实际值之间的偏差，X表示待辨识的模型参数误差，A_DC表示末端距离误差与模型参数误差之间的距离约束关系矩阵，所述A_DC表示为：in,

Represents the deviation between the nominal terminal distance and the actual value under two different configurations, X represents the model parameter error to be identified, A _DC represents the distance constraint relationship matrix between the terminal distance error and the model parameter error, and the A _DC Expressed as:

In a preferred embodiment, a mixed error model is formed by mixing the first kinematic error model and the second kinematic error model, and the mixed error model is expressed as:

Y = AX;

Among them, Y is a vector composed of m ₁ terminal position errors and m ₂ terminal distance errors, A represents the combined relationship matrix composed of m ₁ position constraint relationship matrices and m ₂ distance constraint relationship matrices, m ₁ and m ₂ are integers greater than or equal to 1.

In a preferred embodiment, in S4, the least squares method is used to iteratively identify the error of the kinematics model parameters, and the formula of the least squares method is expressed as:

X=(A ^T A) ^-1 A ^T Y.

In a preferred embodiment, in said S5, the identified kinematics model parameter error is compensated to the controller of the robot by means of direct compensation or indirect compensation.

In a preferred embodiment, the direct compensation method includes directly modifying kinematic model parameters in the controller.

In a preferred embodiment, the indirect compensation method includes correcting the target pose with the kinematics model parameters obtained through identification, inputting the corrected target pose into the original controller, and performing error correction on the original kinematics model. compensate.

Compared with the prior art, the beneficial effects of the present invention are at least:

For the position constraint of the robot, the present invention drags the calibration ball at the end to the same ball seat with two different robot configurations, and calibrates the robot by using the end position error obtained through two calculations; The calibration ball is dragged to two different ball seats, and the robot is calibrated by using the deviation between the calculated end distance and the actual distance. Compared with traditional external calibration devices, the present invention has the characteristics of low cost and good portability; compared with most of the existing self-calibration devices, the present invention does not contain additional sensors, and has the advantages of simple operation and not easy to be damaged.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments described in the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

Fig. 1 is the structural representation of the device of the embodiment of the present invention;

Fig. 2 is a schematic flow chart of the method in an embodiment of the present invention;

Fig. 3 is a schematic structural view of the terminal calibration device of the present invention;

Fig. 4 is a schematic structural view of the geometric constraint device of the present invention;

Fig. 5 is a schematic diagram of a calibration ball positioned on a ball seat;

Fig. 6 is a schematic diagram of positioning the calibration ball on the ball seat under different robot configurations;

Fig. 7 is a schematic diagram of calibration balls positioned on different ball seats.

Reference signs:

1. Robot, 2. Connection seat, 3. Calibration ball, 4. Ball seat, 5. Constraint support seat.

Detailed ways

The present invention will be more fully understood by reading the following detailed description in conjunction with the accompanying drawings. Detailed embodiments of the present invention are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the invention, which may be embodied in various forms. Therefore, specific functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a teaching to one skilled in the art that, in fact, any suitably detailed embodiment may differ in any suitably detailed embodiment. The manner employs the representative basis of the present invention.

A robot calibration method based on position and distance constraints disclosed by the present invention is implemented based on a robot calibration device. Aiming at the problems of expensive, poor portability, and easy damage in existing calibration devices, collaborative robots can be used to drag The teaching feature provides a low-cost, portable and non-destructive calibration device for the calibration of collaborative robots. For general industrial robots, if the function of dragging and teaching can be realized, then the present invention is equally applicable.

As shown in Figure 1, the above-mentioned robot calibration device includes a terminal calibration device and a geometric constraint device, wherein, as shown in Figure 3, the terminal calibration device is installed at the end of the robot 1, which specifically includes a connecting base 2 and a terminal mounted on one end of the connecting base 2 Calibration ball 3 ; as shown in FIG. 4 , the geometric constraint device is installed in the working space of the robot 1 , which mainly includes a constraint support base 5 and a plurality of ball seats 4 arranged on the constraint support base 5 . During calibration, the terminal calibration device is installed at the end of the robot 1, specifically, the connection base 2 is installed at the end of the robot 1; the geometric constraint device is installed in the working space of the robot 1. Drag the robot 1 so that the calibration ball 3 on the terminal calibration device is attracted to the ball seat 4 on the geometric constraint device through a magnet (not shown in the figure). For position constraints, the calibration ball 3 at the end is dragged to the same ball seat 4 in two different robot configurations, and the robot 1 is calibrated using the end position error obtained from the two calculations; for distance constraints, the calibration ball at the end is 3 is dragged to two different ball seats 4, and the robot 1 is calibrated by using the error between the end distance obtained by the two calculations and the actual distance.

As shown in Figure 2, a robot calibration method based on position and distance constraints disclosed by the present invention specifically includes the following steps:

S1. Establishing a model, the model including a kinematics model of the robot, a first kinematics error model based on a position constraint, and a second kinematics error model based on a distance constraint.

Specifically, the present invention calibrates the robot based on position and distance constraints, respectively. In this embodiment, the global exponential product formula is used to establish the kinematics model of the robot. Specifically, the kinematics model is constructed by establishing the corresponding relationship between the end pose of the robot and the joint angle, joint screw and initial pose. Among them, the global exponential product formula is expressed as follows:

Among them, T _{0, n+1} represents the coordinates of the end pose of the robot in the base coordinate system, s _i (i=1, 2, ..., n) represents the coordinates of the joint screw of the robot in the base coordinate system, q _i (i=1, 2, ..., n) represents the rotation angle of each joint of the robot, that is, the joint angle, and T _{0, n+1} (0) represents the initial pose of the end of the robot relative to the base coordinate system. The process of determining the base coordinates here mainly includes: the installation position of the robot relative to the position of the geometric constraint device can be predicted (for example, it can be determined by three-dimensional scanner, laser tracker, three-coordinate measuring instrument and other measurement methods). The position of the actual base coordinates can be calibrated by the calibration device of the present invention and then the base coordinate system of the robot after being calibrated by the calibration method of the present invention.

通过一定的公式推导，可建立两种不同构型下的末端位置误差与运动学模型参数误差之间的关系式，即第一运动学误差模型表示如下：In the above robot kinematics model, q _i (i=1, 2, ..., n) can be directly read by the encoder of the robot, while s _i (i = 1, 2, ..., n) and T _{0, n+1} requires parameter identification. s _i (i=1, 2, ..., n) and T _{0, n+1} (0) can be expressed as 6 parameter variables to be identified, so there are 6 (n+1) parameters to be identified . Express the errors t ₁ , t ₂ ,..., t _n , t ₀ corresponding to these parameters as a vector to be identified

Through a certain formula derivation, the relationship between the terminal position error and the kinematic model parameter error under two different configurations can be established, that is, the first kinematic error model is expressed as follows:

Y _PC = A _PC X,;

表示两种不同构型下的末端位置误差，X表示待辨识的模型参数误差，A_PC表示末端位置误差与模型参数误差之间的位置约束关系矩阵，所述A_PC表示为：in,

Represents the terminal position error under two different configurations, X represents the model parameter error to be identified, A _PC represents the position constraint relationship matrix between the terminal position error and the model parameter error, and the A _PC is expressed as:

Among them, p is the coordinate of the nominal end position, I ₃ represents the identity matrix of 3×3, Ad(·) represents the accompanying transformation matrix corresponding to the homogeneous transformation matrix, and A _j (j=1, 2) is expressed as:

In this embodiment, similarly, a distance-based robot kinematics error model can also be established, that is, the second kinematics error model is expressed as follows:

Y _DC = A _DC X,;

表示两种不同构型下的名义末端距离与实际值之间的偏差，X同样表示待辨识的模型参数误差，A_DC表示末端距离误差与模型参数误差之间的距离约束关系矩阵，所述A_DC表示为：in,

Represents the deviation between the nominal terminal distance and the actual value under two different configurations, X also represents the model parameter error to be identified, A _DC represents the distance constraint relationship matrix between the terminal distance error and the model parameter error, the A _DC is expressed as:

Further, the above-mentioned first kinematic error model and the second kinematic error model are mixed to form a mixed error model, and the mixed error model specifically integrates m ₁ pairwise paired position constraint samples and m ₂ pairwise paired distance constraints samples, the mixed error model is specifically expressed as:

Y = AX;

Among them, Y is a vector composed of m ₁ terminal position errors and m ₂ terminal distance errors, A represents the combined relationship matrix composed of m ₁ position constraint relationship matrices and m ₂ distance constraint relationship matrices, m ₁ and m ₂ are integers greater than or equal to 1.

S2, measuring installation, including measuring the first relative pose between the calibration ball on the end calibration device and the connecting seat, and the second relative pose between the ball seats on the geometric constraint device , after the measurement, the end calibration device is installed on the end of the robot, and the geometric constraint device is installed in the working space of the robot.

During implementation, equipment such as a three-dimensional scanner may be used to measure the first relative pose and the second relative pose, where the first relative pose and the second relative pose are used as reference data for subsequent parameter identification.

S3, data acquisition, including changing the position of the geometric constraint device in the working space of the robot multiple times, dragging the robot at each position, so that the calibration ball of the end calibration device is constrained to each ball on the geometric constraint device Seat, and each ball seat was touched several times in different configurations, and the joint angle data after each measurement operation was stabilized was read and recorded.

Specifically, as shown in Fig. 5 and Fig. 6, the process of data acquisition based on position constraints is as follows: moving a calibration ball of the terminal calibration device to any ball seat on the geometric constraint device, and then using different robots to The configuration is moved to the same ball seat, and the joint angle readings after each operation are stabilized are read and recorded, so that a set of position constraint calibration data is collected. In order to reduce the influence of measurement errors and non-geometric errors, the pose of the geometric constraint device in the robot workspace can be changed multiple times to collect multiple sets of data.

As shown in Figures 5 to 7, the process of data collection based on distance constraints is as follows: moving a calibration ball of the terminal calibration device to a ball seat on the geometric constraint device, and then moving to different balls with different robot configurations. Seat, read and record the joint angle readings after each operation is stable, so that a set of distance constraint calibration data is collected. Similarly, in order to reduce the impact of measurement errors and non-geometric errors, the pose of the geometric constraint device in the robot workspace can be changed multiple times to collect multiple sets of data.

In the actual data collection process, the position constraint and distance constraint calibration data can be measured simultaneously, and there is only a slight difference in the data processing in the subsequent identification calculation process. For example, by changing the position of the geometric constraint device in the working space of the robot multiple times, dragging the robot at each position, so that the calibration ball of the end calibration device is constrained to each ball seat on the geometric constraint device, and each The ball seat was touched several times in different configurations, and the joint angle data after each measurement operation was stabilized was read and recorded. Afterwards, all joint angle data are divided into several groups according to different geometric constraint device poses, and then divided into several groups according to different ball seat positions. Among them, the pairwise paired data of the same group of data is multiple sets of position constraint calibration data. The paired data of the same group but different groups of data is multiple sets of distance constraint calibration data.

S4, parameter identification, including dividing the joint angle data into several groups according to different geometric constraint device poses, and then dividing them into several groups according to different ball seat positions, and substituting pairs of data from the same group into the first motion In the kinematic error model, the data of the same group but different groups are paired into the second kinematic error model, and then the data of the two error models are mixed to identify the corresponding kinematic model parameters of the robot.

Specifically, in this embodiment, the least squares method is used to iteratively identify kinematics model parameter errors. For the least squares method, its formula can be expressed as:

X=(A ^T A) ^-1 A ^T Y.

Correct the kinematic model parameters by using the model parameter error calculated in each step, and then use the corrected parameters to substitute into the first kinematic error model and the second kinematic error model to calculate again, and so on until the kinematic model parameters No more changes, stop iterating. The kinematic model parameters at this time can be regarded as the actual model parameters.

S5, error compensation, including compensating the identified kinematics model parameter error to the controller of the robot.

Specifically, the identified kinematic model parameter error is compensated to the controller, and generally there are two compensation methods: direct compensation and indirect compensation. Direct compensation is to directly modify the kinematic model parameters in the controller, while indirect compensation is to correct the target pose through the calibrated kinematic model parameters, and input the corrected target pose into the original controller to realize the original control. Error compensation for kinematic models.

Compared with the traditional external robot calibration scheme, the present invention has the characteristics of low cost and good portability; and compared with most existing self-calibration devices, the present invention does not contain additional sensors, and has the advantages of easy operation and not easy to damage.

Aspects, embodiments, features and examples of the present invention are to be considered illustrative in all respects and not intended to be limiting, the scope of which is defined only by the claims. Other embodiments, modifications, and uses will be apparent to those skilled in the art without departing from the spirit and scope of the invention as claimed.

The use of headings and sections in this application is not meant to limit the invention; each section may apply to any aspect, embodiment or feature of the invention.

Claims (10)

1. A robot calibration method based on position and distance constraints, characterized in that: the method is realized based on a robot calibration device, the robot calibration device includes a terminal calibration device and a geometric constraint device, and the terminal calibration device includes a connecting seat and a calibration ball installed at one end of the connection seat, the geometric constraint device includes a constraint support seat and a plurality of ball seats arranged on the constraint support seat, and the method includes: S1, establishing a model, the model including a kinematics model of the robot, a first kinematics error model based on a position constraint, and a second kinematics error model based on a distance constraint; S2, measuring installation, including measuring the first relative pose between the calibration ball on the end calibration device and the connecting seat, and the second relative pose between the ball seats on the geometric constraint device , after the measurement, install the end calibration device on the end of the robot, and install the geometric constraint device in the working space of the robot; S3, data acquisition, including changing the position of the geometric constraint device in the working space of the robot multiple times, dragging the robot at each position, so that the calibration ball of the end calibration device is constrained to each ball on the geometric constraint device Seat, and each ball seat is touched several times in different configurations, and the joint angle data after each measurement operation is stabilized is read and recorded; S4, parameter identification, including dividing the joint angle data into several groups according to different geometric constraint device poses, and then dividing them into several groups according to different ball seat positions, and substituting pairs of data from the same group into the first motion In the kinematic error model, the data of the same group but different groups are paired into the second kinematic error model, and then the two error model data are mixed to identify the corresponding kinematic model parameters of the robot; S5, error compensation, including compensating the identified kinematics model parameter error to the controller of the robot. 2. A robot calibration method based on position and distance constraints according to claim 1, characterized in that: in said S1, the robot terminal pose and joint angle, joint screw and initial position are established through the global exponential product formula The corresponding relationship between postures is constructed to construct the kinematics model; the corresponding relationship between the position constraint error and the joint screw error and the initial pose error is established through the adjoint transformation matrix, and the first kinematics error model is constructed; The accompanying transformation matrix establishes the corresponding relationship between the distance constraint error, the joint screw error, and the initial pose error, and constructs the second kinematic error model. 3. a kind of robot calibration method based on position and distance constraint according to claim 2, is characterized in that: described global exponential product formula is expressed as follows:

Among them, T _{0, n+1} represents the coordinates of the end pose of the robot in the base coordinate system, s _i (i=1, 2, ..., n) represents the coordinates of the joint screw of the robot in the base coordinate system, q _i (i=1, 2, ..., n) represents the rotation angle of each joint of the robot, that is, the joint angle, and T _{0, n+1} (0) represents the initial pose of the end of the robot relative to the base coordinate system. 4. a kind of robot calibration method based on position and distance constraints according to claim 3, is characterized in that: described first kinematics error model is expressed as follows: Y _PC = A _PC X; in,

Represents the terminal position error under two different configurations, X represents the model parameter error to be identified, A _PC represents the position constraint relationship matrix between the terminal position error and the model parameter error, and the A _PC is expressed as:

Among them, p is the coordinate of the nominal end position, I ₃ represents the identity matrix of 3×3, Ad(·) represents the accompanying transformation matrix corresponding to the homogeneous transformation matrix, and A _j (j=1, 2) is expressed as:

5. A kind of robot calibration method based on position and distance constraint according to claim 4, it is characterized in that: described second kinematics error model is expressed as follows: Y _DC = A _DC X,; in,

Represents the deviation between the nominal terminal distance and the actual value under two different configurations, X represents the model parameter error to be identified, A _DC represents the distance constraint relationship matrix between the terminal distance error and the model parameter error, and the A _DC Expressed as:

6. A robot calibration method based on position and distance constraints according to claim 5, characterized in that: a mixed error model is formed by mixing the first kinematic error model and the second kinematic error model, and the mixed The error model is expressed as: Y = AX;

Among them, Y is a vector composed of m ₁ terminal position errors and m ₂ terminal distance errors, A represents the combined relationship matrix composed of m ₁ position constraint relationship matrices and m ₂ distance constraint relationship matrices, m ₁ and m ₂ are integers greater than or equal to 1. 7. A robot calibration method based on position and distance constraints according to claim 6, characterized in that: in said S4, the least squares method is used to iteratively identify the kinematics model parameter error, and the least squares The multiplication formula is expressed as: X=(A ^T A) ^-1 A ^T Y. 8. A robot calibration method based on position and distance constraints according to claim 1, characterized in that in said S5, the identified kinematics model parameter errors are compensated by means of direct compensation or indirect compensation to the robot controller. 9. A robot calibration method based on position and distance constraints according to claim 8, characterized in that: the direct compensation method includes directly modifying the kinematics model parameters in the controller. 10. A robot calibration method based on position and distance constraints according to claim 8, characterized in that: the indirect compensation method includes correcting the target pose with the kinematics model parameters obtained through identification, and converting the corrected The target pose is input into the original controller to perform error compensation on the original kinematics model.

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