CN112917513A - TCP calibration method of three-dimensional dispensing needle head based on machine vision - Google Patents
TCP calibration method of three-dimensional dispensing needle head based on machine vision Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/0095—Means or methods for testing manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/0075—Manipulators for painting or coating
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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 TCP calibration method of a three-dimensional dispensing needle head based on machine vision, which comprises the following steps: firstly, a camera and a lens, two surface light sources and a prism are arranged in a motion space of a mechanical arm; manually marking a TCP coordinate system of the point glue needle head; controlling a Z axis of a TCP coordinate system of a dispensing needle head at the tail end of the dispensing robot to be vertical to an XOY plane of the dispensing robot; according to a TCP coordinate system which is calibrated manually; obtaining the position of the center of the needle tip after the calibration of hands and eyes as Pbase0 through a vision algorithm; carrying out attitude calibration; repeating the steps six times; establishing an equation set and solving the equation set under the condition that the coordinates of the midpoints of the four TCP dispensing needle heads in the world coordinate system are equal; and judging whether the TCP calibration result meets the requirement. The invention directly carries out TCP calibration on the dispensing needle head through machine vision, and compared with the prior scheme that the TCP calibration is carried out without an intermediate object, the invention has the advantages of high flexibility, simplicity and easiness in operation, high precision, visualization, easiness in debugging and the like.
Description
Technical Field
The invention relates to the technical field of three-dimensional dispensing of six-axis industrial robots, in particular to a TCP calibration method of a three-dimensional dispensing needle head based on machine vision.
Background
More and more robots are applied to the field of intelligent manufacturing, automatic dispensing equipment is also applied more and more widely in the field of intelligent manufacturing, and conventional planar 2D dispensing is difficult to meet actual requirements. For complex 3D curved surfaces, the method for realizing the dispensing process of complex paths and multiple postures through the six-axis industrial robot is the most widely applied mode at present. The calibration error of the tool center point TCP (toolcenter point) has a great influence on the positioning accuracy of the robot, and the positioning accuracy is an important factor influencing the performance of the robot; TCP calibration is also the basis of the robot off-line programming technology. Therefore, how to calibrate the TCP quickly and accurately is important.
The existing TCP calibration method is mainly a single-constraint point calibration method, and the method has the main defects that manual operation is needed, the calibration precision depends on manual operation experience, large errors are easy to occur, the production line is required to be completely stopped, the consumed time is long, and for dispensing equipment, the production efficiency of an automatic production line is seriously influenced by the manual mode due to the fact that a needle needs to be frequently replaced. Currently there are a few calibration systems based on external measurements, such as:
201811207015.X, a method and a device for realizing six-degree-of-freedom TCP on-line rapid calibration, on-off signals of a correlation photoelectric sensor need to be calibrated according to a specific track, and the process is relatively complex and the cost is high.
201810640287.2, the automatic high-precision non-contact robot TCP calibration method is realized by an ultrasonic device, the algorithm is relatively complex, and the cost of the ultrasonic device is high.
201910538251.8, a TCP calibration method for a robot based on vertical reflection, which proposes to realize TCP calibration by using a plane mirror as an auxiliary tool and a binocular vision system, but needs to be installed at the tail end of the robot in application, and may be difficult to be applied on site due to space and structure limitations in practice.
202010180243.3, a vision-based robot TCP calibration method, which realizes TCP calibration by two cameras forming a 90 degree included angle and a fixed sphere, wherein the moving process is 1 unit step at a time, which greatly limits the working efficiency, and the application of the sphere needing to be fixed not only increases the complexity but also is greatly limited.
202010316233.8, a system and a method for rapidly calibrating the tool coordinate system of an arc welding robot on line, which realizes TCP calibration through two-dimensional laser sensors, but the cost is relatively high and the installation requirement on the laser is high.
Although these methods can achieve TCP calibration, such systems are usually relatively expensive or not simple and flexible enough for practical applications. Therefore, in order to solve the practical application, a method for calibrating the three-dimensional dispensing robot TCP, which is simple and easy to operate, low in price, short in time consumption and high in efficiency, needs to be provided urgently.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art and provide a TCP calibration method of a three-dimensional dispensing needle head based on machine vision.
In order to solve the technical problems, the invention provides the following technical scheme:
the invention relates to a TCP calibration method of a three-dimensional dispensing needle head based on machine vision, which comprises the following steps:
firstly, a camera and a lens, two surface light sources and a prism are arranged in a motion space of a mechanical arm, and the position of a needle head in the other direction is observed in one camera through the prism with the angle of 45 degrees;
secondly, manually marking a TCP coordinate system of the point glue needle head;
thirdly, controlling a dispensing needle TCP coordinate system at the tail end of the dispensing robot to enable the Z axis to be vertical to an XOY plane of the dispensing robot, enabling the X axis direction of the movement of the robot to be approximately vertical to the optical axis of the camera, enabling the Y axis of the movement of the robot to be approximately parallel to the optical axis of the camera, controlling the robot to move to a proper position of the needle correcting device, enabling the needle to be in the middle of the visual field of the camera, and enabling the current position to be P0(X0, Y0 and Z0) through imaging and clear recording in a prism;
step four, calibrating the hand and the eye according to a manually calibrated TCP coordinate system, calibrating an XZ plane and a YZ plane by the hand and the eye, establishing a conversion relation between an image coordinate and a robot coordinate, determining the Juqiu position of the midpoint of the dispensing needle head, and recording three-dimensional position information through a machine vision algorithm program;
step five, moving the dispensing robot to a position P0, triggering a camera by an upper computer to take a picture, obtaining the position of the center of the needle tip after the hand-eye calibration through a vision algorithm as Pbase0(Xbase0, Ybase0 and Zbase0), and taking the position as the reference position of the dispensing needle head as attitude 0,
sixthly, carrying out posture calibration, rotating the robot to different postures, calculating the difference value of the current position and the reference position in the direction of X, Y, Z through a visual algorithm, and moving the robot according to the difference value;
step seven, repeating the step six twice, and enabling the needle tip to move to the reference position close to the midpoint of the dispensing needle head after rotating three times by a method of continuous iterative movement;
step eight, building a block of equations and solving under the condition that the coordinates of the midpoint of the TCP dispensing needle head in the world coordinate system are equal for four times, so as to realize the calibration of the position of the TCP tool coordinate system of the midpoint of the dispensing needle head;
and step nine, judging whether the TCP calibration result meets the requirements, if not, repeating the step six, the step seven and the step eight according to the current TCP calibration result, and reducing the error of the TCP calibration result through iteration of the calibration result.
As a preferred technical solution of the present invention, when performing the hand-eye calibration in step four, firstly calibrating the XZ plane of the dispensing robot, at which the Y value of the calibration point is a fixed value, establishing Txz a conversion relationship between the XZ axis coordinate of the glue starting robot and the image coordinate by using a hand-eye 9-point calibration method, then calibrating the YZ plane of the glue starting robot, that is, the imaging surface of the prism in the camera, at which the X value of the calibration point is a fixed value, and establishing Tyz a conversion relationship between the YZ axis coordinate of the glue starting robot and the image coordinate by using a hand-eye 9-point calibration method.
As a preferred technical scheme of the present invention, the hand-eye 9-point calibration algorithm has a hand-eye correspondence relationship in which a center point of the dispensing needle is obtained by a visual algorithm and a robot coordinate obtained by each robot moving according to a manually calibrated TCP coordinate system is in one-to-one correspondence, and 9 sets of corresponding robot coordinates and image coordinates of the dispensing needle in the image coordinate system are obtained, so as to perform hand-eye calibration.
As a preferred technical scheme of the present invention, the method for obtaining the midpoint of the dispensing needle finds straight line features L1, L2 and L3 on an XZ plane by using a visual algorithm, obtains an intersection point C1 of L1 and L3 and an intersection point C2 of L2 and L3, and obtains the centers of C1 and C2, which are midpoint coordinates of the dispensing needle on an X and Z plane, and obtains the midpoint of the dispensing needle on a YZ plane by using the same method, thereby obtaining the three-dimensional coordinates of the midpoint of the dispensing needle.
As a preferred technical solution of the present invention, in the step six, the following operations are performed:
firstly, controlling the robot to rotate around a certain direction according to a manually initialized TCP coordinate system, wherein the rotation angle needs to be larger than 5 degrees and is used as a gesture 1, triggering a camera to take a picture, obtaining the current position of the center of the needle tip as Pc1(Xc1, Yc1 and Zc1) through a visual algorithm, calculating the difference value between Pc1 and Pbase0 as delta p (delta x is Xc1-Xbase0, delta y is Yc1-Ybase0 and delta z is Zc1-Zbase0), sending the delta p (delta x is Xc1-Xbase0, delta y is Yc1-Ybase0 and delta z is Zc1-Zbase0) to the robot through upper computer communication, and moving the robot according to the offset of the three directions obtained by the delta p;
when the robot finishes the moving process, triggering the camera again to acquire the offset between the current position and the dispensing needle reference position (posture 0), wherein the offset is Δ p1(Δ x1 is Xc1-Xbase0, Δ y1 is Yc1-Ybase0, and Δ z1 is Zc 1-Ybase 0), and judging whether three direction offset components of Δ p1 (whether Δ x1 is smaller than a standard value S, whether Δ y1 is smaller than the standard value S, and whether Δ z1 is smaller than the standard value S) are all smaller than the standard value S;
and if the measured values are less than the standard value S, the robot stops moving and records the position of the robot after moving. And if the deviation component in a certain direction is larger than the standard value S, continuing to send the deviation data to the robot, and continuing to move the robot until the final deviation components in the three directions are all smaller than the standard value S.
As a preferable technical solution of the present invention, the standard value S is set to 0.05 mm.
Compared with the prior art, the invention has the following beneficial effects:
1: the invention directly carries out TCP calibration on the dispensing needle head through machine vision, does not need to carry out TCP calibration by means of an intermediate object (such as a sphere) compared with the prior scheme, and has the advantages of high flexibility, simplicity, easiness in operation, high precision, visualization, easiness in debugging and the like, thereby reducing the shutdown maintenance time of the industrial robot and improving the efficiency and the productivity of an industrial production line.
2: the invention obtains the coordinate of the midpoint of the dispensing needle under the image coordinate and the corresponding robot coordinate through a visual algorithm, moves the robot, establishes 9 points of corresponding relation, thereby realizing the hand-eye calibration of an XZ plane and a YZ plane, establishes the relation between the image coordinate system and the robot coordinate system, quickly realizes the measurement of the midpoint of the dispensing needle to the position of a reference point in the TCP calibration process, enables the dispensing needle to be moved to the position of the reference point through an iterative process for two times, and is quicker compared with the method of stepping 1 unit each time.
3: the invention can realize the rapid TCP calibration of the dispensing needle head only by using a system of one camera, one lens, two light sources and one prism, and has relatively low cost.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a front view of a TCP calibration system of the present invention;
FIG. 2 is a front view of the apparatus of the present invention;
FIG. 3 is an overall connection diagram of the present invention;
FIG. 4 is a schematic illustration of the hand-eye calibration method of the present invention;
FIG. 5 is a schematic diagram of the present invention illustrating the acquisition of the midpoint position of the needle tip by a machine vision algorithm;
FIG. 6 is a schematic diagram of the TCP four-point method of the present invention;
FIG. 7 is a flow chart diagram of a TCP calibration method of the present invention;
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1
As shown in fig. 1-7, the present invention provides a TCP calibration method for three-dimensional dispensing needle based on machine vision, which includes a first step of installing a camera and a lens, two surface light sources and a prism in a motion space of a mechanical arm, and observing the position of the needle in another direction in one camera through the 45 ° prism, which is equivalent to two 90 ° installed cameras, so as to monitor the 3D position of the needle, as shown in fig. 1, 2 and 3.
Secondly, manually calibrating a TCP coordinate system of the tail end dispensing needle head of the industrial robot;
and step three, controlling a Z axis of a dispensing needle TCP coordinate system at the tail end of the dispensing robot to be vertical to an XOY plane of the dispensing robot, controlling the robot to move to a proper position of the needle correcting device, wherein the X axis direction of the robot motion is approximately vertical to the optical axis of the camera, the Y axis of the robot motion is approximately parallel to the optical axis of the camera, the needle head is in the middle of the visual field of the camera and is imaged clearly in the prism, and the current position is recorded as P0(X0, Y0 and Z0).
And step four, performing hand-eye calibration according to a manually calibrated TCP coordinate system, firstly calibrating an XZ plane of the glue dispensing robot, setting the Y value of the calibration point as a fixed value, establishing a conversion relation Txz between the XZ axis coordinate of the glue dispensing robot and the image coordinate by a hand-eye 9-point calibration method, then calibrating a YZ plane of the glue dispensing robot, namely the imaging surface of the prism in the camera, setting the X value of the calibration point as a fixed value, and establishing a conversion relation Tyz between the YZ axis coordinate of the glue dispensing robot and the image coordinate by a hand-eye 9-point calibration method.
The corresponding relationship between hands and eyes of the hand-eye 9-point calibration algorithm is that the center point of the dispensing needle head is obtained through a visual algorithm to be in one-to-one correspondence with the robot coordinate obtained by the robot moving according to the manually calibrated TCP coordinate system, and 9 groups of corresponding robot coordinates and the image coordinates of the dispensing needle head in the image coordinate system can be obtained in such a way, as shown in FIG. 4, so that the hand-eye calibration can be performed.
The method for obtaining the midpoint of the dispensing needle is, as shown in fig. 5, to find straight line features L1, L2 and L3 on an XZ plane by a vision algorithm, to obtain an intersection point C1 of L1 and L3 and an intersection point C2 of L2 and L3, and centers of C1 and C2 are midpoint coordinates of the dispensing needle on an X and Z plane, and to obtain the midpoint of the dispensing needle on a YZ plane by the same method, thereby obtaining the three-dimensional coordinates of the midpoint of the dispensing needle.
And step five, moving the dispensing robot to a position P0, triggering a camera by an upper computer to take a picture, obtaining the position of the center of the needle tip after the hand-eye calibration through a vision algorithm as Pbase0(Xbase0, Ybase0 and Zbase0), and taking the position as the reference position of the dispensing needle head, namely posture 0.
And sixthly, performing posture calibration, controlling the robot to rotate around a certain direction according to a manually initialized TCP coordinate system, taking the robot as a posture 1 when the rotation angle is larger than 5 degrees for ensuring the precision, triggering a camera to take a picture, and obtaining the current position of the center of the needle point as Pc1(Xc1, Yc1 and Zc1) through a visual algorithm. Calculating a difference between Pc1 and Pbase0 as Δ p (Δ x ═ Xc1-Xbase0, Δ y ═ Yc1-Ybase0, Δ z ═ Zc1-Zbase0), sending Δ p (Δ x ═ Xc1-Xbase0, Δ y ═ Yc1-Ybase0, Δ z ═ Zc1-Zbase0) to the robot through host computer communication, the robot moving according to the three direction offsets obtained by Δ p, when the robot completes the moving process, triggering the camera again to obtain the offset between the current position and the dispensing needle reference position (posture 0), determining Δ p1(Δ x1 ═ Xc1-xb 1, Δ y1 ═ Yc1-Ybase 1, Δ z 1-Zbase 1, determining whether Δ x ═ Zbase 1 is smaller than the Δ z standard value 1, Δ z1 is smaller than the Δ S1, and whether Δ z is smaller than the Δ S1, and Δ x ≦ zs 1 is smaller than the standard value of Δ S1, and Δ x ≦ S1, if the deviation components in the certain direction are larger than the standard value S, continuing to send the deviation data to the robot, and continuing to move the robot until the final deviation components in the three directions are smaller than the standard value S.
And seventhly, repeating the six steps twice, and only rotating the robot around the other two directions. By continuously and iteratively moving, the needle tip moves to a reference position (posture 0) which is very close to the midpoint of the dispensing needle after three turns, as shown in fig. 6.
And step eight, building a cubic equation group and solving under the condition that the coordinates of the midpoint of the TCP dispensing needle head in the world coordinate system are equal for four times, namely solving TCP by a classical four-point method, thereby realizing the calibration of the position of the TCP tool coordinate system of the midpoint of the dispensing needle head.
And step nine, judging whether the TCP calibration result meets the requirements, if not, repeating the step six, the step seven and the step eight according to the current TCP calibration result, and reducing the error of the TCP calibration result through iteration of the calibration result.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A TCP calibration method of a three-dimensional dispensing needle head based on machine vision is characterized by comprising the following steps:
firstly, a camera and a lens, two surface light sources and a prism are arranged in a motion space of a mechanical arm, and the position of a needle head in the other direction is observed in one camera through the prism with the angle of 45 degrees;
secondly, manually marking a TCP coordinate system of the point glue needle head;
thirdly, controlling a Z axis of a dispensing needle TCP coordinate system at the tail end of the dispensing robot to be vertical to an XOY plane of the dispensing robot, controlling the robot to move to a proper position of the needle correcting device, and controlling the needle to be in the middle of the visual field of the camera and clearly recording the current position of the imaging in a prism to be P0(X0, Y0 and Z0), wherein the X axis direction of the movement of the robot is approximately vertical to the optical axis of the camera and the Y axis of the movement of the robot is approximately parallel to the optical axis of the camera;
step four, calibrating the hand and the eye according to a manually calibrated TCP coordinate system, calibrating an XZ plane and a YZ plane by the hand and the eye, establishing a conversion relation between an image coordinate and a robot coordinate, determining the Juqiu position of the midpoint of the dispensing needle head, and recording three-dimensional position information through a machine vision algorithm program;
step five, moving the dispensing robot to a position P0, triggering a camera by an upper computer to take a picture, obtaining the position of the center of the needle tip after the hand-eye calibration through a vision algorithm as Pbase0(Xbase0, Ybase0 and Zbase0), and taking the position as the reference position of the dispensing needle head as attitude 0,
sixthly, carrying out posture calibration, rotating the robot to different postures, calculating the difference value of the current position and the reference position in the direction of X, Y, Z through a visual algorithm, and moving the robot according to the difference value;
step seven, repeating the step six twice, and enabling the needle tip to move to the reference position close to the midpoint of the dispensing needle head after rotating three times by a method of continuous iterative movement;
step eight, establishing an equation set and solving on the condition that coordinates of the midpoint of the TCP dispensing needle head in the world coordinate system are equal for four times, so as to realize the calibration of the position of the TCP tool coordinate system of the midpoint of the dispensing needle head;
and step nine, judging whether the TCP calibration result meets the requirements, if not, repeating the step six, the step seven and the step eight according to the current TCP calibration result, and reducing the error of the TCP calibration result through iteration of the calibration result.
2. The TCP calibration method for a three-dimensional dispensing needle head based on machine vision as claimed in claim 1, characterized in that in the fourth step, when performing hand-eye calibration, firstly calibrating the XZ plane of the dispensing robot, at which time the Y value of the calibration point is a fixed value, establishing Txz a conversion relationship between the X Z axis coordinate of the dispensing robot and the image coordinate by the hand-eye 9-point calibration method, then calibrating the YZ plane of the dispensing robot, that is, the imaging plane of the prism in the camera, at which time the X value of the calibration point is a fixed value, and establishing Tyz a conversion relationship between the YZ axis coordinate of the dispensing robot and the image coordinate by the hand-eye 9-point calibration method.
3. The TCP calibration method for the three-dimensional dispensing needle head based on the machine vision as claimed in claim 2, characterized in that the hand-eye 9-point calibration algorithm is used to obtain the one-to-one correspondence between the center point of the dispensing needle head and the robot coordinates obtained by the robot moving according to the TCP coordinate system calibrated manually each time through the vision algorithm, and obtain 9 sets of corresponding robot coordinates and the image coordinates of the dispensing needle head in the image coordinate system, thereby performing the hand-eye calibration.
4. The TCP calibration method for a three-dimensional dispensing needle based on machine vision as claimed in claim 3, characterized in that the method for obtaining the midpoint of the dispensing needle is to find out the straight line features L1, L2 and L3 on the XZ plane by the vision algorithm, obtain the intersection points C1 of L1 and L3 and the intersection points C2 of L2 and L3, and the centers of C1 and C2 are the coordinates of the midpoint of the dispensing needle on the X and Z planes, and obtain the midpoint of the dispensing needle on the YZ plane by the same method, thereby obtaining the three-dimensional coordinates of the midpoint of the dispensing needle.
5. The TCP calibration method for three-dimensional dispensing needle head based on machine vision as claimed in claim 1, characterized in that in step six, the operation is as follows:
firstly, controlling the robot to rotate around a certain direction according to a manually initialized TCP coordinate system, wherein the rotation angle needs to be larger than 5 degrees and is used as a gesture 1, triggering a camera to take a picture, obtaining the current position of the center of the needle tip as Pc1(Xc1, Yc1 and Zc1) through a visual algorithm, calculating the difference value between Pc1 and Pbase0 as delta p (delta x is Xc1-Xbase0, delta y is Yc1-Ybase0 and delta z is Zc1-Zbase0), sending the delta p (delta x is Xc1-Xbase0, delta y is Yc1-Ybase0 and delta z is Zc1-Zbase0) to the robot through an upper computer, and moving the robot according to the offset of the three directions obtained by the delta p;
when the robot finishes a moving process, triggering the camera again to acquire the offset between the current position and the dispensing needle reference position (posture 0), wherein the offset is Δ p1(Δ x1 is Xc1-Xbase0, Δ y1 is Yc1-Ybase0, and Δ z1 is Zc 1-Ybase 0), and judging whether three direction offset components of Δ p1 (whether Δ x1 is smaller than a standard value S, whether Δ y1 is smaller than a standard value S, and whether Δ z1 is smaller than the standard value S) are all smaller than the standard value S;
and if the measured values are less than the standard value S, the robot stops moving and records the position of the robot after moving. And if the deviation component in a certain direction is larger than the standard value S, continuing to send the deviation data to the robot, and continuing to move the robot until the final deviation components in the three directions are all smaller than the standard value S.
6. The TCP calibration method for the three-dimensional dispensing needle head based on the machine vision as claimed in claim 5, characterized in that the standard value S is set to 0.05 mm.
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| CN113364956A (en) * | 2021-06-08 | 2021-09-07 | 博众精工科技股份有限公司 | Dispensing needle calibration device and method |
| CN113916200A (en) * | 2021-09-30 | 2022-01-11 | 南京中科煜宸激光技术有限公司 | Calibration system and method for coupling robot and external shaft |
| CN113942013A (en) * | 2021-11-02 | 2022-01-18 | 杭州迁移科技有限公司 | Rapid hand-eye calibration method and system based on data visualization |
| CN114152680A (en) * | 2021-11-26 | 2022-03-08 | 中国科学院合肥物质科学研究院 | TCP calibration method and device for six-axis mechanical arm ultrasonic detection system |
| CN114509035A (en) * | 2022-04-19 | 2022-05-17 | 江苏高凯精密流体技术股份有限公司 | Dispensing needle TCP measuring method and device |
| CN115830147A (en) * | 2023-02-20 | 2023-03-21 | 常州铭赛机器人科技股份有限公司 | Transfer printing and dispensing rotation center calibration method based on monocular vision |
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