CN111216138A - Robot calibration method, robot calibration system and readable storage medium - Google Patents
Robot calibration method, robot calibration system and readable storage medium Download PDFInfo
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- CN111216138A CN111216138A CN202010271645.4A CN202010271645A CN111216138A CN 111216138 A CN111216138 A CN 111216138A CN 202010271645 A CN202010271645 A CN 202010271645A CN 111216138 A CN111216138 A CN 111216138A
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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
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1653—Programme controls characterised by the control loop parameters identification, estimation, stiffness, accuracy, error analysis
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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
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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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
- B25J9/16—Programme controls
- B25J9/1679—Programme controls characterised by the tasks executed
- B25J9/1692—Calibration of manipulator
Abstract
The invention discloses a robot calibration method, a robot calibration system and a readable storage medium, wherein the robot calibration method comprises the following steps: the robot calibration method comprises the following steps: recording joint data of each joint of the robot; obtaining the tail end simulation position of the robot by establishing a robot connecting rod structure D-H model; constructing a tail end simulation position error model according to the joint data and the tail end simulation position of the robot; constructing a zero error model according to the joint data and the D-H model of the robot connecting rod structure; and compensating the tail end simulation position error model into the zero position error model to obtain the joint zero position error. The robot calibration method can improve the track precision of the robot on the premise of simple operation.
Description
Technical Field
The invention relates to the technical field of robot calibration, in particular to a robot calibration method, a robot calibration system and a readable storage medium.
Background
In the actual application process of the serial articulated robot, if the zero position of each or a certain joint and/or the coordinate accuracy of a tool are not enough, the track path deviation of the tail end of the robot is large, and the actual application effect is influenced.
In the existing calibration method, high-precision equipment such as a laser tracker and the like is generally arranged on measuring equipment for calibration. This method is not only expensive, but also tends to cause hysteresis due to an excessively large amount of data processed by the processor, and can improve the trajectory accuracy of the robot, but is complicated in operation and high in cost.
Disclosure of Invention
The invention mainly aims to provide a robot calibration method, aiming at improving the track precision of a robot on the premise of simple operation.
In order to achieve the purpose, the robot calibration method provided by the invention comprises the following steps:
recording joint data of each joint of the robot;
obtaining the tail end simulation position of the robot by establishing a robot connecting rod structure D-H model;
constructing a tail end simulation position error model according to the joint data and the tail end simulation position of the robot;
constructing a zero error model according to the joint data and the D-H model of the robot connecting rod structure;
and compensating the tail end simulation position error model into the zero position error model to obtain the joint zero position error.
Preferably, the step of obtaining the simulated position of the tail end of the robot by establishing a D-H model of the robot link structure includes:
establishing a robot connecting rod structure D-H model according to a positive kinematics algorithm of the robot;
calculating the relation between the simulation position of the robot and the joint data of the robot according to the D-H model of the robot connecting rod structure;
and acquiring the terminal simulation position under the joint data corresponding to the actual position of each terminal according to the relation.
Preferably, the step of constructing a tip simulation position error model based on the joint data and the tip simulation position of the robot includes:
taking joint data of the robot twice at random to obtain a terminal simulation position of the robot under the corresponding joint data; when the corresponding tail end actual positions of the robot joint data of any two times are the same, establishing an equation set through the relation between the tail end actual positions and the tail end simulation positions under the same joint data, and obtaining the difference between the tail end simulation positions of any two times according to the equation set;
and repeating the operation for N times, and constructing an error model of the tail end simulation position according to the difference between any two tail end simulation positions obtained by N times and the Jacobian matrix.
Preferably, the step of constructing a tip simulation position error model based on the joint data and the tip simulation position of the robot includes:
the error between the actual position of the tip and the simulated position of the tip corresponding to the same joint data is
（6）
Converting the formula (6) to obtain the actual position of the tail end as
Wherein p iscFor the actual position of said end, pnFor the purpose of simulating the position of the end,
j is a Jacobian matrix as the zero error model;
taking any two times of joint data, wherein the corresponding tail end actual positions of the joint data of any two times are the same, then
Thus, the method can obtain the product,
wherein the content of the first and second substances,
the difference between the simulated positions of the ends,
and
obtaining the difference between any two terminal simulation positions for different terminal simulation positions;
measuring joint data again for N times, obtaining the difference of N tail end simulation positions according to the measured joint data for N times, and constructing a tail end simulation position error model:
preferably, the robot end is provided with a first measuring point; a second measuring point is fixedly arranged at the position opposite to the first measuring point;
preferably, the step of recording joint data of each joint of the robot includes:
under the condition that the robot is controlled to operate and the first measuring point and the second measuring point are kept opposite, joint data of each joint of the robot under different postures are obtained by changing the postures of the robot;
preferably, after the step of obtaining the null error of the joint, the method further comprises:
detecting whether the zero position error of the joint meets the error requirement;
if the zero position error does not meet the error requirement, the difference between the tail end simulation positions of any two times is recalculated to update the zero position error of the joint until the updated zero position error of the joint meets the error requirement.
Preferably, the zero error model is
Wherein the content of the first and second substances,
zero errors of joint axes 2,3,4 and 5 of the robot respectively,
zero errors of the first measuring point in the x, y and z directions are respectively.
Preferably, the robot calibration method further includes: and compensating the joint zero error into a controller of the robot.
Correspondingly, the invention also provides a robot, comprising:
the first measuring point is arranged at the tail end of the robot;
the second measuring point is fixedly arranged opposite to the first measuring point;
a memory for storing a computer program;
a processor for implementing the steps of the robot calibration method as described above when executing the computer program;
and the controller is used for specifically applying the tail end zero error compensation obtained by the processor to the running track of the robot.
Preferably, the first measuring point and the second measuring point are both needle-like structures,
and the needle tip of the first measuring point is opposite to the needle tip of the second measuring point.
Correspondingly, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a robot calibration program, and the robot calibration program, when executed by a processor, implements the steps of the robot calibration method as described above.
The robot calibration method can quickly realize calibration of the zero position of the robot joint and the tool coordinate (first measurement point), obtain the error between the actual zero position of the robot joint and the theoretical zero position of the robot joint, and then compensate the error into the controller, so that the track precision of the robot can be easily improved, and the use precision of the robot is improved.
The robot calibration method does not improve the precision of the running track of the robot firstly when the robot runs, and avoids the condition that the running track is corrected while the running track is executed in the prior art, which is easy to cause errors.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic flow chart diagram provided by an exemplary embodiment of the present invention;
fig. 2 is a schematic structural diagram of an entity according to an exemplary embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
The reference numbers illustrate:
| reference numerals | Name (R) | Reference numerals | Name (R) |
| 1 | |
2 | |
| 3 | Robot |
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the application provides a robot calibration method, which can quickly realize calibration of a robot joint zero position and a tool coordinate (a first measurement point), obtain an error between an actual robot joint zero position and a theoretical joint zero position, and compensate the error into a controller, so that the track precision of a robot can be easily improved, and the use precision of the robot is improved. The calibration method improves the robot precision by means of a software algorithm, overcomes the defects of high cost and complex operation of high-precision equipment adopted in the existing calibration process, and effectively avoids the condition that the motion trail is easy to be mistaken while the motion trail is executed and corrected in the prior art.
As shown in fig. 1, a robot calibration method according to an embodiment of the present application includes:
and step 101, recording joint data of each joint of the robot.
And 102, obtaining the tail end simulation position of the robot by establishing a D-H model of the robot connecting rod structure.
And 103, constructing a tail end simulation position error model according to the joint data and the tail end simulation position of the robot.
And 104, constructing a zero error model according to the joint data and the D-H model of the robot connecting rod structure.
And 105, compensating the tail end simulation position error model into the zero position error model to obtain a joint zero position error.
The tail end of a mechanical arm of the robot is provided with a first measuring point; and a second measuring point is fixedly arranged at the abutting position of the first measuring point.
The second measuring point may be arranged on the robot, for example: the base of the robot can also be arranged at other positions outside the robot, such as: the robot is placed on the ground.
In a specific embodiment, the step of step 101 includes:
and step 1011, under the condition that the robot is controlled to operate and the first measuring point and the second measuring point are kept opposite, acquiring joint data of each joint of the robot under different postures by changing the posture of the robot.
Specifically, the joint data of the robot is
Wherein the content of the first and second substances,
the joint angles of the joint axes 1, 2,3,4,5 and 6 of the robot respectively;
the first measuring point has the coordinates of
Wherein, the tool is the coordinate of the first measuring point,
the coordinates of the first measuring point in the x, y and z directions are respectively.
In the above-described technical solution, in order to ensure that the robot end always remains at the same position when acquiring the joint data of each joint of the robot, the second measurement point is set as a reference object, the first measurement point is set at the robot arm end of the robot 3, and the robot end (i.e., the first measurement point) is always ensured to be at the same position by limiting the first measurement point and the second measurement point to always abut against each other. In practical operation, in order to ensure that the first measuring point and the second measuring point can be accurately arranged oppositely, please refer to fig. 2, the entity of the first measuring point and the second measuring point is set to be a needle-shaped structure, and the tip of the first measuring point (i.e. the first tip 1) and the tip of the second measuring point (i.e. the second tip 2) are abutted against each other.
In a particular embodiment, after step 105, the method further comprises:
and 106, detecting whether the zero position error of the joint meets the error requirement.
And 107, if the zero position error does not meet the requirement, recalculating the difference between the tail end simulation positions of any two times to update the zero position error of the joint until the updated zero position error of the joint meets the error requirement.
In a specific embodiment, the robot linkage structure D-H model is established, and the method further includes:
and establishing a robot connecting rod structure D-H model according to the joint data and a positive kinematics algorithm of the robot.
In a specific embodiment, the step of step 102 includes:
step 1021, establishing a robot connecting rod structure D-H model according to the recorded joint data and a positive kinematics algorithm of the robot;
step 1022, calculating the relation between the simulation position of the robot and the joint data of the robot according to the D-H model of the robot connecting rod structure;
and 1023, acquiring the terminal simulation position under the joint data corresponding to each terminal actual position according to the relation.
Specifically, the step of establishing the robot connecting rod structure D-H model comprises the following steps:
establishing a homogeneous transformation matrix of adjacent links as
Wherein the content of the first and second substances,
are all the DH parameters of the robot link i,
uniformly transforming a matrix for adjacent connecting rods;
the coordinate relation between the first measuring point and the base of the robot is
Wherein T is the coordinate relation of the first measuring point relative to the central point of the robot base,
is a homogeneous transformation matrix of the link 1 relative to the base,
is a homogeneous transformation matrix of link 2 relative to link 1,
is a homogeneous transformation matrix of link 3 relative to link 2,
is connected toA homogeneous transformation matrix of the rods 4 with respect to the connecting rods 3,
is a homogeneous transformation matrix of links 5 relative to links 4,
is a homogeneous transformation matrix of links 6 relative to links 5,
is a homogeneous transformation matrix of the tool relative to the link 5.
In this embodiment, the coordinate system is established with the center point of the base of the robot as the coordinate origin, but in other embodiments, the coordinate origin may be set at other positions to establish the coordinate system, and the D-H model of the robot linkage structure may be established.
In addition, in this embodiment, algorithm setting is performed by the six-axis degree-of-freedom robot arm, and corresponding algorithm adjustment may be performed according to the degree of freedom of the robot arm for specific applications, which is not described herein again.
Specifically, the relation between the first measuring point and the joint data of the robot can be deduced according to a robot connecting rod structure D-H model and a robot kinematic algorithm
Wherein p is the relationship between the first measuring point and the joint data of the robot, q is the joint movement data of the robot, tool is the coordinate data of the first measuring point, and function f is the function relationship of inputting specific joint data to obtain the corresponding terminal simulation position.
Moreover, according to the formula (3) and the formula (4), the coordinate relationship between the robot tail end (first measurement) and the center point of the robot base can be obtained according to the activity parameters of each joint axis in the established robot connecting rod structure D-H model; that is, the relationship p (i.e., function f) between the first measurement point and the joint data of the robot is a disassembly deformation of the coordinate relationship T of the first measurement point with respect to the center point of the robot base in the formula (3). The specific D-H model of the robot connecting rod structure is disassembled to obtain the relation between the first measuring point and the joint data of the robot, which is not the key point of the application, so that a specific disassembling formula is not given.
And acquiring the terminal simulation position under the joint data corresponding to the actual position of each terminal according to the relation.
Specifically, step 103, constructing a distal end simulated position error model based on the joint data and the distal end simulated position of the robot, includes:
taking joint data of the robot twice at random to obtain a terminal simulation position of the robot under the corresponding joint data; when the corresponding tail end actual positions of the robot joint data of any two times are the same, establishing an equation set through the relation between the tail end actual positions and the tail end simulation positions under the same joint data, and obtaining the difference between the tail end simulation positions of any two times according to the equation set;
and repeating the operation for N times, and constructing an error model of the tail end simulation position according to the difference between any two tail end simulation positions obtained by N times and the Jacobian matrix.
In the above technical solution, because the joint data of the robot collected in this technical solution are collected under the condition that the first measurement point and the second measurement point are abutted against each other, that is, the position of the first measurement point is always unchanged, the actual positions of the ends corresponding to the joint data of the robot collected at any two times are the same and are both the second measurement point. And the relation between the actual position of the tail end and the simulated position of the tail end is that the difference between the actual position of the tail end and the simulated position of the tail end is equal to the product of the zero error model and the Jacobian matrix, which is detailed in a formula (6). Therefore, according to the fact that the actual positions of the tail ends corresponding to the joint data of the robot in any two times are the same, it can be known that the equation relation between the difference of the simulated positions of the tail ends and the jacobian matrix and the zero error model can be obtained by subtracting the simulated positions of the tail ends corresponding to the joint data of the robot in any two times, and the equation relation can be seen in the formula (8) and the formula (9).
Specifically, the step of constructing a distal end simulated position error model based on the joint data and the distal end simulated position of the robot includes:
the error between the actual position of the tip and the simulated position of the tip corresponding to the same joint data is
（6）
Converting the formula (6) to obtain the end actual position of
Wherein p iscTo the actual position of the end, pnIn order to simulate the position of the end,
a zero error model is adopted, and J is a Jacobian matrix;
taking the joint data measured at any two times, wherein the actual positions (the positions of the first measuring points) of the tail ends corresponding to the joint data measured at any two times are the same and are the positions of the second measuring points, then
Thus, the method can obtain the product,
wherein the content of the first and second substances,
the difference between the simulated positions of the ends,
and
obtaining the difference between any two terminal simulation positions for different terminal simulation positions;
measuring joint data again for N times, obtaining the difference of N tail end simulation positions according to the measured joint data for N times, and constructing a tail end simulation position error model:
obtaining a zero error model according to a least square method as
And substituting the tail end simulation position and the Jacobian matrix into a formula (12) to obtain a zero error model. And performing iterative calculation by using a least square method.
Specifically, the zero error model is
Wherein the content of the first and second substances,
the zero position errors of joints of the 2 nd, 3 rd, 4 th and 5 th joint axes of the robot respectively,
zero errors of the first measuring point in the x, y and z directions are respectively. From this, the null error model includes the joint null error.
A robot, comprising:
the first measuring point is arranged at the tail end of the robot;
the second measuring point is fixedly arranged opposite to the first measuring point;
a memory for storing a computer program;
a processor for implementing the steps of the robot calibration method when executing the computer program;
and the controller is used for specifically applying the joint zero error compensation obtained by the processor to the running track of the robot.
In one embodiment, the first measuring point and the second measuring point are needle-shaped structures, and the needle tip (i.e. the first needle tip 1) of the first measuring point and the needle tip (i.e. the second needle tip 2) of the second measuring point are abutted against each other.
Furthermore, the present invention also proposes a computer-readable storage medium having stored thereon a program of a robot calibration method, which when executed by a processor implements the steps of robot calibration as described above.
The specific embodiment of the computer-readable storage medium of the present invention is substantially the same as the embodiments of the robot calibration method described above, and will not be described in detail herein.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A robot calibration method is characterized by comprising the following steps:
recording joint data of each joint of the robot;
obtaining the tail end simulation position of the robot by establishing a robot connecting rod structure D-H model;
constructing a tail end simulation position error model according to the joint data and the tail end simulation position of the robot;
constructing a zero error model according to the joint data and the D-H model of the robot connecting rod structure;
and compensating the tail end simulation position error model into the zero position error model to obtain the joint zero position error.
2. The robot calibration method according to claim 1, wherein the step of obtaining the simulated position of the end of the robot by establishing a D-H model of the robot link structure comprises:
establishing a robot connecting rod structure D-H model according to a positive kinematics algorithm of the robot;
calculating the relation between the simulation position of the robot and the joint data of the robot according to the D-H model of the robot connecting rod structure;
and acquiring the terminal simulation position under the joint data corresponding to the actual position of each terminal according to the relation.
3. A robot calibration method according to claim 1, wherein the step of constructing a tip simulation position error model based on the joint data and the tip simulation position of the robot comprises:
taking joint data of the robot twice at random to obtain a terminal simulation position of the robot under the corresponding joint data; when the corresponding tail end actual positions of the robot joint data of any two times are the same, establishing an equation set through the relation between the tail end actual positions and the tail end simulation positions under the same joint data, and obtaining the difference between the tail end simulation positions of any two times according to the equation set;
and repeating the operation for N times, and constructing an error model of the tail end simulation position according to the difference between any two tail end simulation positions obtained by N times and the Jacobian matrix.
4. A robot calibration method according to claim 1, wherein the step of constructing a tip simulation position error model based on the joint data and the tip simulation position of the robot comprises:
the error between the actual position of the tip and the simulated position of the tip corresponding to the same joint data is
（6）
Converting the formula (6) to obtain the actual position of the tail end as
Wherein p iscFor the actual position of said end, pnFor the purpose of simulating the position of the end,
j is a Jacobian matrix as the zero error model;
taking any two times of joint data, wherein the corresponding tail end actual positions of the joint data of any two times are the same, then
Thus, the method can obtain the product,
wherein the content of the first and second substances,
the difference between the simulated positions of the ends,
and
obtaining the difference between any two terminal simulation positions for different terminal simulation positions;
measuring joint data again for N times, obtaining the difference of N tail end simulation positions according to the measured joint data for N times, and constructing a tail end simulation position error model:
5. a robot calibration method according to any one of claims 1 to 4, wherein a first measurement point is provided at the end of the robot; a second measuring point is fixedly arranged at the abutting position of the first measuring point;
the step of recording joint data of each joint of the robot includes:
under the condition that the robot is controlled to operate and the first measuring point and the second measuring point are kept opposite, acquiring the joint number of each joint of the robot under different postures by changing the postures of the robot;
after the step of obtaining the zero error of the joint, the method further comprises the following steps:
detecting whether the zero position error of the joint meets the error requirement;
if the zero position error does not meet the error requirement, the difference between the tail end simulation positions of any two times is recalculated to update the zero position error of the joint until the updated zero position error of the joint meets the error requirement.
6. A robot calibration method as claimed in claim 1, wherein said zero error model is
Wherein the content of the first and second substances,
the zero position errors of joints of the 2 nd, 3 rd, 4 th and 5 th joint axes of the robot respectively,
the terminal zero errors of the first measuring point in the x, y and z directions are respectively.
7. A robot calibration method according to claim 1, further comprising: and compensating the joint zero error into a controller of the robot.
8. A robot calibration system, comprising:
the first measuring point is arranged at the tail end of the robot;
the second measuring point is fixedly arranged opposite to the first measuring point;
a memory for storing a computer program;
a processor for implementing the steps of the robot calibration method according to any one of claims 1 to 7 when executing the computer program;
and the controller is used for specifically applying the tail end zero error compensation obtained by the processor to the running track of the robot.
9. A robot calibration system as defined in claim 8,
the first measuring point and the second measuring point are both needle-shaped structures,
and the needle tip of the first measuring point is opposite to the needle tip of the second measuring point.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a program for robot calibration, which when executed by a processor implements the steps of the robot calibration method according to any of claims 1-7.
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| CN111390914A (en) * | 2020-04-17 | 2020-07-10 | 上海智殷自动化科技有限公司 | Robot zero position and tool coordinate calibration method |
| CN112692828A (en) * | 2020-12-18 | 2021-04-23 | 上海新时达机器人有限公司 | Robot calibration method, system, device and storage medium |
| CN113532353A (en) * | 2021-07-29 | 2021-10-22 | 刘慧泉 | Precision measuring device |
| CN114089644A (en) * | 2021-11-12 | 2022-02-25 | 中冶赛迪技术研究中心有限公司 | Method, system, equipment and medium for remote simulation calibration and online programming based on openvpn |
| CN115533922A (en) * | 2022-11-29 | 2022-12-30 | 北京航空航天大学杭州创新研究院 | Pose relation calibration method and device, computer equipment and readable storage medium |
| CN115752321A (en) * | 2022-11-09 | 2023-03-07 | 中山大学 | Medical robot motion trajectory measurement and comparison method and computer-readable storage medium |
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| CN112692828A (en) * | 2020-12-18 | 2021-04-23 | 上海新时达机器人有限公司 | Robot calibration method, system, device and storage medium |
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