Double-Scara mechanical arm calibration method based on TCP

Abstract

According to the double-Scara mechanical arm calibration method based on the TCP, the limited number of calibration points are selected on the chessboard, the coordinate points of the calibration points relative to the chessboard and the mechanical arm base are obtained, operation and calibration are carried out, and the tedious steps of early-stage double-mechanical-arm calibration can be greatly reduced; it can be ensured that the double-mechanical-arm system can accurately position and operate a target object when executing a task, and the production efficiency and the product quality are improved. Meanwhile, the method further has wide application prospects and important significance, and powerful technical support is provided for development of the fields of industrial automation, robot service, scientific research and exploration and the like.

Description

Technical Field

[0001] The invention relates to the technical field of tool coordinate system calibration of a double Scara robot arm relative to a chessboard operating table, in particular to a double Scara robot arm calibration method based on TCP. Background Art

[0002] The Scara robot arm is a cylindrical coordinate industrial robot with three rotating joints and one mobile joint. Its structure is similar to that of a human arm, consisting of a vertical support and a horizontal arm, which enables precise positioning and orientation within a plane while performing assembly or printing operations in the vertical direction.

[0003] In 3D printing tasks, especially in advanced application scenarios involving two or more robotic arms working together, it is crucial to ensure that they can achieve precise and coordinated movements in a unified printing coordinate system. This collaborative operation capability not only greatly expands the scope of application of 3D printing technology, but also promotes its innovative application in complex structure manufacturing, large component assembly and other fields. However, to achieve this goal, the first thing that needs to be solved is the inconsistency between the independent coordinate systems of the robotic arms and the global coordinate system required for the printed model.

[0004] Each robot arm plans and executes motion based on its own coordinate system. These local coordinate systems often deviate from the desired global coordinate system for printing, including position offset and angle rotation, etc. If not properly corrected, these deviations will directly lead to printing errors, affecting the quality and accuracy of the finished product. Especially in collaborative printing tasks, any slight deviation may be magnified, causing printing failure or damage to the integrity of the model structure.

[0005] To overcome this challenge, TCP calibration can be used. TCP calibration can be achieved through drag-teaching algorithms and conversion algorithms to establish a transformation relationship between the robot arm and the chessboard operation table. The drag-teaching algorithm allows the operator to manually guide the end effector of the robot arm (such as a nozzle or tool head) to move along a predetermined path while recording the position information. This process is actually "teaching" the robot arm to understand and simulate the operator's desired motion trajectory, thereby establishing a reference point or path corresponding to the printing global coordinate system in the local coordinate system of the robot arm. The coordinate system conversion algorithm can convert these recorded position information from the local coordinate system of the robot arm to a unified global printing coordinate system. This conversion process usually involves matrix operations, including translation and rotation transformations, to accurately calculate the relative position and posture between the two coordinate systems. Once this transformation relationship is established, the robot arm can be programmed to move precisely along a preset path and speed in the global printing coordinate system. In collaborative printing tasks, this means that two or more robot arms can perform their respective printing tasks synchronously and without error, whether it is synchronous deposition of materials, collaborative construction of complex structures, or precise adjustment of the position and posture of printed parts, to achieve high consistency and accuracy.

[0006] The technical comparison is as follows:

[0007] Technical comparison with patent CN118789539A "A method for calibrating the length and zero point of a scara arm in industrial application sites"

[0008] Patent CN118789539A discloses a method for calibrating the arm length and zero point of a SCARA robot for industrial sites, including the following steps: installing a calibration pin at the end of the robot TCP, randomly selecting at least 10 points within the working range to place a second calibration pin, using the kinematic equation to derive the arm length and zero point of the first and second axes, and using the least squares method to perform optimization iterations until the calibration requirements are met. This method is simple and efficient, and can accurately calibrate the key parameters of the first and second axes of the SCARA robot, solving the absolute position accuracy problem at industrial sites.

[0009] The present invention proposes a dual SCARA robot arm calibration method based on TCP, which is innovative and practical. By selecting limited calibration points on the chessboard, obtaining the coordinates of the calibration points relative to the chessboard and the robot arm base, and performing calculations and calibrations, and importing 3D slicing codes, the cumbersome process of dual robot arm calibration is greatly simplified. This method can ensure that the dual robot arm system can accurately locate and operate the target object during task execution, thereby improving production efficiency and product quality.

[0010] Different from the patent CN118789539A which focuses on the calibration method of using SCARA arm length and zero point in industrial application sites, the present invention unifies the 3D model slice coordinate system, the chessboard operating table coordinate system and the SCARA robot arm coordinate system through a small number of calibration points. Through these calibration points, TCP calibration can be performed for two Scara robot arms, thereby greatly shortening the time required for calibration. Summary of the invention

[0011] In response to the above problems, the present invention proposes a dual Scara robotic arm calibration method based on TCP, which not only improves the efficiency of calibration, but also ensures the movement accuracy of the robotic arm in collaborative operation, and provides strong technical support for the wide application of dual robotic arms in 3D printing, automated assembly and other fields.

[0012] To achieve the above object, the technical solution adopted by the present invention is:

[0013] The dual Scara robot arm calibration method based on TCP is characterized by comprising the following steps:

[0014] First, we need to identify the key points in the two coordinate systems;

[0015] In the chessboard coordinate system, the origin O is defined s (O1), point X on the positive half axis of the X axis s1 , point Y on the positive half axis of the Y axis s1 , and the point Z on the positive half axis of the Z axis obtained by cross multiplication after normalization s1 ;

[0016] First determine O s , this point is the reference point for all measurements and positioning, representing a fixed and known position in the print space, X s1 Determining the direction of the X-axis also provides a key reference for subsequent coordinate transformation. Similarly, on the positive half of the Y-axis, Y is selected. s1 , this point and X s1 The two-dimensional plane of the printing coordinate system is jointly defined, and then the direction of the Z axis is determined by the method of unitization and cross multiplication;

[0017] Specifically, the vectors corresponding to the points on the X-axis and Y-axis are first normalized;

[0018] Then, the two unit vectors are cross-multiplied to obtain the direction vector of the Z axis, which represents the point on the positive half axis of the Z axis in the printing coordinate system.

[0019]

[0020] The three points are measured by a ruler, the distance between the calibration points is greater than 150mm, the measurement error is ±0.5mm, and the error after unitization does not exceed 0.3%. In the robot base coordinate system, the corresponding points O2 and X s2 , Y s2 and Z s2 , move the robot arm to the calibration point, and obtain O2, X s2 , Y s2 and Z s2 Compare the coordinate values ​​with those of the robot base coordinate system and normalize them;

[0021]

[0022] By O s (O1), X s1 , Y s1 Indicates O2, X s2 , Y s2 As shown in formula (3), R b You can get the rotation matrix of the printing coordinate system into the robot coordinate system, and then get the translation vector This is usually (0,0,0);

[0023]

[0024] Finally, we get the coordinate transformation matrix T b , this matrix T b It is the bridge between the printing coordinate system and the robot coordinate system, and contains all the necessary information of rotation and translation, so that any point in the chessboard coordinate system can be accurately converted to the robot coordinate system;

[0025]

[0026] After obtaining the coordinate transformation matrix T b After that, this algorithm is further used to convert the coordinate information in the G-code file generated by the 3D slicing software Simplify3D into the coordinates of the robot arm coordinate system. b After importing the G-code file, all coordinate information in the G-code file will be automatically converted into position information relative to the robot base coordinate system.

[0027] Matrix operations are performed based on the coordinate positions of the calibration points in the chessboard coordinate system and the robot base coordinate system to obtain the rotation matrix from the robot to the chessboard. The offset matrix can be obtained from the chessboard origin and the center point of the robot base coordinate system. The two matrices are combined and upgraded to obtain the transformation matrix from the robot to the chessboard.

[0028] The calibration process also includes precise adjustment of the initial position of the robot arm to ensure that the end of the robot arm tool can accurately contact the calibration point, thereby improving the accuracy of the calibration.

[0029] As a further improvement of the present invention, the two robotic arms are calibrated simultaneously through calibration points on the chessboard operating table.

[0030] As a further improvement of the present invention, the coordinate position of the calibration point generated by the G code is the same as the position of the calibration point relative to the chessboard coordinate system, and the transformation matrix between the chessboard coordinate system and the robot base coordinate system can be directly applied in the G code.

[0031] As a further improvement of the present invention, the calibration point adopts a robotic arm tool, which is fixedly installed on the robotic arm flange. The end of the tool is overlapped with the calibration point to obtain the coordinate position of the calibration point relative to the robotic arm base coordinate system.

[0032] As a further improvement of the present invention, the calibration points on the chessboard operating table are set according to a predetermined pattern or layout. After the calibration is completed, the motion trajectory of the robot arm is also verified and corrected.

[0033] The calibration points on the chessboard operating table are set according to a predetermined pattern or layout, which helps to quickly and accurately identify and locate the calibration points, improving calibration efficiency.

[0034] After the calibration is completed, the motion trajectory of the robot arm is also verified and corrected to ensure the accuracy and stability of the robot arm in actual work.

[0035] As a further improvement of the present invention, the G-code file also includes instructions for controlling the robotic arm to perform calibration movements. These instructions can guide the robotic arm to move to the calibration point according to a predetermined path and speed, thereby improving the efficiency and accuracy of the calibration.

[0036] As a further improvement of the present invention, the chessboard operating table is also equipped with a calibration device for calibrating the chessboard operating table before calibration to ensure that its flatness and position accuracy meet the calibration requirements.

[0037] The present invention aims to solve the problems of long time, complex process and error accumulation faced by dual manipulators in tool coordinate system calibration. The core of the method is to cleverly use a chessboard operating table with a limited number of high-precision calibration points to achieve simultaneous calibration of the TCP of two Scara manipulators. In this method, the chessboard operating table is a key auxiliary tool in the calibration process, and its surface is covered with regularly arranged marking points, which are not only easy to identify by the visual system of the manipulator, but also ensure the high precision of the calibration. Through these calibration points on the chessboard operating table, TCP calibration can be performed for two Scara manipulators at the same time, without the need to perform one by one like the traditional method, thereby greatly shortening the time required for calibration. More importantly, this simultaneous calibration method effectively reduces the error accumulation during the calibration process. In the traditional calibration process, since each manipulator needs to be measured and calculated multiple times separately, the error may gradually accumulate as the number of steps increases. The method proposed in the present invention significantly reduces the risk of such error accumulation by setting up a chessboard operating table once and using a limited number of calibration points to complete the calibration of two manipulators at the same time. In general, this innovative TCP-based dual Scara robotic arm calibration method not only improves the efficiency of calibration, but also ensures the motion accuracy of the robotic arm in collaborative operations, providing strong technical support for the widespread application of dual robotic arms in 3D printing, automated assembly and other fields.

[0038] Beneficial effects: The TCP-based dual Scara robotic arm calibration method disclosed in the present invention has the following beneficial effects:

[0039] 1. Improve printing accuracy:

[0040] Through accurate coordinate system correction, the precise movement of the robot arm in the printing coordinate system is ensured, thereby greatly improving the accuracy of the printed product. This method reduces the positioning error caused by inconsistent coordinate systems, making the printed model more in line with design requirements.

[0041] 2. Simplify the calibration process:

[0042] The traditional robot arm calibration process is often complicated and time-consuming, but this method simplifies the calibration process by using the drag-teaching algorithm and the conversion algorithm. During the calibration process, the robot arm only needs to be guided to move to a limited number of calibration points, and the transformation matrix can be quickly calculated, which greatly shortens the calibration time.

[0043] 3. Enhance system flexibility:

[0044] This method is not only applicable to Scara robotic arms, but can also be extended to other types of robotic arms as long as they can meet the basic kinematic model requirements. This enhances the flexibility of the system, allowing different types of robotic arms to work together on the same printing platform.

[0045] 4. Reduce error accumulation:

[0046] By setting up the chessboard table once and using a limited number of calibration points for calibration, the error accumulation during the calibration process is reduced. This method ensures that the motion error of the robot arm is kept within a small range throughout the printing area.

[0047] 5. Improve work efficiency:

[0048] Accurate coordinate system correction enables the robot arm to locate the specified position in the printing task more quickly, thereby improving overall work efficiency. In addition, by reducing repeated printing and correction work caused by inaccurate positioning, time and cost are further saved.

[0049] 6. Promote the development of automation and intelligence:

[0050] This method provides a basis for the automation and intelligent control of the robot arm. Through accurate coordinate system correction, the robot arm can be better integrated into a wider range of automation systems, achieving a more efficient and intelligent production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 is a system structure diagram of the present invention;

[0052] Figure 2 A framework diagram of the system design of the present invention;

[0053] Figure 3 It is a flow chart of the steps of the present invention. DETAILED DESCRIPTION

[0054] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments:

[0055] The system structure diagram is as follows Figure 1 As shown in the figure, the system design framework is as follows Figure 2 As shown in the flowchart, the steps are as follows Figure 3 shown.

[0056] When faced with two robotic arms with independent coordinate systems, it is crucial to ensure that they can achieve accurate and correct movement in a unified printing coordinate system, especially when performing collaborative 3D printing tasks. The need for such collaborative work is particularly prominent when manufacturing complex structures or large objects, because it can significantly improve production efficiency and printing accuracy. Especially for low-degree-of-freedom robotic arms like the Scara robotic arm, although its range of motion and kinematic model are relatively fixed and limited, this feature actually provides certain convenience for accurate correction of the coordinate system.

[0057] When the two Scara robotic arms are precisely mounted on the 3D printing platform, their initial coordinate systems may deviate from the preset printing coordinate system. This deviation may be caused by slight errors in the installation process, the manufacturing accuracy limitations of the robotic arms themselves, or the positioning accuracy of the printing platform itself. In addition, there may be deviations between the robotic arm coordinate system and the model coordinate system due to design or manufacturing reasons. If these deviations are not effectively corrected before the printing job, they will have a direct and significant impact on the printing accuracy and the quality of the final product, which may cause problems such as inaccurate size, distorted shape, or assembly difficulties of the printed objects.

[0058] Therefore, in order to ensure that the two Scara robotic arms can achieve high-precision motion control during the collaborative printing process, the coordinate system between the printing platform and the two robotic arms must be accurately calibrated before the printing job begins. This process usually involves precise measurement and positioning of the robotic arms, as well as a series of complex mathematical transformations to establish an accurate correspondence between the robotic arm coordinate system and the printing coordinate system. Only in this way can it be ensured that the two robotic arms can move accurately according to the preset path and speed during the printing process, thereby achieving high-quality collaborative 3D printing jobs.

[0059] In order to establish the transformation relationship between the robot coordinate system and the printing coordinate system, we first need to identify the key points in the two coordinate systems. In the chessboard operation table coordinate system, the origin O is defined. s (O1), point X on the positive half axis of the X axis s1 , point Y on the positive half axis of the Y axis s1 , and the point Z on the positive half axis of the Z axis obtained by cross multiplication after normalization s1 First determine O s , this point is the reference point for all measurements and positioning, it represents a fixed and known position in the print space. s1 It not only helps determine the direction of the X axis, but also provides a key reference for subsequent coordinate transformation. s1 , this point and X s1 Together they define the two-dimensional plane of the printing coordinate system. In order to completely define the printing coordinate system in three-dimensional space, the direction of the Z axis also needs to be determined. Since the Z axis is perpendicular to both the X axis and the Y axis, its direction cannot be determined simply by selecting a point. Therefore, the method of cross multiplication after normalization is adopted. Specifically, the vectors corresponding to the points on the X axis and the Y axis are first normalized to ensure that their lengths are all 1. Then, the cross multiplication operation is performed using these two unit vectors, and the resulting vector is the direction vector of the Z axis. This vector represents the point on the positive half axis of the Z axis in the printing coordinate system.

[0060]

[0061] The three points are measured by a ruler, the distance between the calibration points is greater than 150mm, the measurement error is ±0.5mm, and the error after unitization does not exceed 0.3%. In the robot base coordinate system, the corresponding points O2 and X s2 , Y s2 and Z s2 (Although Z s2 In Scara, this motion is usually not required, but is mentioned here for completeness. After moving the robot to the calibration point, O2 and X can be obtained. s2 , Y s2 and Z s2 Compare the coordinate values ​​of the robot base coordinate system and normalize them.

[0062]

[0063] By O s (O1), X s1 , Y s1 Indicates O2, X s2 , Y s2 As shown in formula (3), R b You can get the rotation matrix of the printing coordinate system into the robot coordinate system, and then get the translation vector This is usually (0,0,0).

[0064]

[0065] Finally, we get the coordinate transformation matrix T b , this matrix T b It is the bridge between the printing coordinate system and the robot coordinate system. It contains all the necessary information of rotation and translation, so that any point in the chessboard coordinate system can be accurately converted to the robot coordinate system. This step is a key link in the collaborative printing task, because it ensures that the data of the printed model can be accurately communicated to the robot, thereby achieving high-precision printing.

[0066]

[0067] After obtaining the coordinate transformation matrix T b After that, this algorithm is further used to convert the coordinate information in the G-code file generated by the 3D slicing software Simplify3D into the coordinates in the robot coordinate system. Simplify3D is a widely used 3D printing slicing software that can generate G-code files containing information such as printing path, speed, temperature, etc. based on 3D models. It should be noted that when Simplify3D software generates G-code files, its coordinate origin must coincide with the origin of the chessboard coordinate system. Therefore, when the coordinate transformation matrix Tb After importing the G-code file, all coordinate information in the G-code file will be automatically converted into position information relative to the robot base coordinate system.

[0068] This conversion process greatly simplifies the calibration of the robot arm. Normally, the calibration of the robot arm requires a lot of time and effort to perform precise measurements and adjustments. However, by using the coordinate transformation matrix T b The G-code files generated by the Simplify3D software can directly realize the precise calibration of the robot arm without tedious manual adjustments. This not only improves the calibration efficiency, but also reduces the difficulty of operation, allowing more users to easily perform high-precision collaborative printing jobs.

[0069] The calibration of the second robot arm can be done based on the relative position relationship between the two robots. b Transform or repeat the above steps. This can effectively solve the problem of inconsistent coordinate systems of two Scara robotic arms in collaborative 3D printing tasks.

[0070] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. A dual Scara robot arm calibration method based on TCP, characterized by: The following steps are involved: First, we need to identify the key points in the two coordinate systems; In the chessboard coordinate system, the origin O is defined s (O1), point X on the positive half axis of the X axis s1 , point Y on the positive half axis of the Y axis s1 , and the point Z on the positive half axis of the Z axis obtained by cross multiplication after normalization s1 ; First determine O s , this point is the reference point for all measurements and positioning, representing a fixed and known position in the print space, X s1 Determining the direction of the X-axis also provides a key reference for subsequent coordinate transformation. Similarly, on the positive half of the Y-axis, Y is selected. s1 , this point and X s1 The two-dimensional plane of the printing coordinate system is jointly defined, and then the direction of the Z axis is determined by the method of unitization and cross multiplication; Specifically, the vectors corresponding to the points on the X-axis and Y-axis are first normalized; Then, the two unit vectors are cross-multiplied to obtain the direction vector of the Z axis, which represents the point on the positive half axis of the Z axis in the printing coordinate system. The three points are measured by a ruler, the distance between the calibration points is greater than 150mm, the measurement error is ±0.5mm, and the error after unitization does not exceed 0.3%. In the robot base coordinate system, the corresponding points O2 and X s2 , Y s2 and Z s2 , move the robot arm to the calibration point, and obtain O2, X s2 , Y s2 and Z s2 Compare the coordinate values ​​with those of the robot base coordinate system and normalize them; By O s (O1), X s1 , Y s1 Indicates O2, X s2 , Y s2 As shown in formula (3), R b You can get the rotation matrix of the printing coordinate system into the robot coordinate system, and then get the translation vector This is usually (0,0,0); Finally, we get the coordinate transformation matrix T b , this matrix T b It is the bridge between the printing coordinate system and the robot coordinate system, and contains all the necessary information of rotation and translation, so that any point in the chessboard coordinate system can be accurately converted to the robot coordinate system; After obtaining the coordinate transformation matrix T b After that, this algorithm is further used to convert the coordinate information in the G-code file generated by the 3D slicing software Simplify3D into the coordinates of the robot arm coordinate system. b After importing the G-code file, all coordinate information in the G-code file will be automatically converted into position information relative to the robot base coordinate system.

2. The dual Scara robot arm calibration method based on TCP according to claim 1, characterized in that: The coordinate position of the calibration point generated by the G code is the same as the position of the calibration point relative to the chessboard coordinate system, and the transformation matrix between the chessboard coordinate system and the robot base coordinate system can be directly applied in the G code.

3. The TCP-based dual Scara robotic arm calibration method according to claim 1, characterized in that: The calibration point uses a robotic arm tool, which is fixedly installed on the robotic arm flange. The end of the tool is aligned with the calibration point to obtain the coordinate position of the calibration point relative to the robotic arm base coordinate system.

4. The TCP-based dual Scara robot arm calibration method according to claim 1, characterized in that: The calibration points on the chessboard console are set according to a predetermined pattern or layout. After the calibration is completed, the motion trajectory of the robot arm is also verified and corrected.

5. The TCP-based dual Scara robot arm calibration method according to claim 1, characterized in that: The G-code file also contains instructions for controlling the robot arm to perform calibration movements, and these instructions can guide the robot arm to move to the calibration point according to a predetermined path and speed.

Images