High-precision hand-eye calibration method for robot system

Abstract

The invention relates to a high-precision hand-eye calibration method for a robot system. The method comprises the following steps: planning a plurality of random robot poses; in the process of operating the pose of the robot, the coordinate value of a target ball point is measured through a laser tracker, an end effector tool coordinate system is constructed and converted into a robot base coordinate system, and an actual measurement rotation matrix and a displacement vector are obtained through calculation. In combination with the theoretical rotation matrix and the displacement vector, pose compensation is achieved through a rotation operator and a translation operator which are finely adjusted, and the target pose and displacement of the robot are adjusted; and after compensation, repeatedly measuring the actual measurement pose and calculating the residual error, and taking the residual error as a compensation value of next iteration until the residual error meets a preset precision threshold value or reaches the maximum number of iterations. And finally, recording the corresponding relation between the pose of the calibration plate in the 3D camera coordinate system and the theoretical pose of the robot to complete the robot hand-eye calibration process. According to the method, the calibration precision is improved, and the high-precision machining and assembling requirements are met.

Description

Technical Field

[0001] The present invention relates to the technical field of robot hand-eye calibration, and in particular to a high-precision hand-eye calibration method for a robot system. Background Art

[0002] Robot measurement, operation and processing integrated technology has broad application prospects in the processing and assembly of large and complex components in the aviation, aerospace, high-speed rail, wind power and other industries. Compared with traditional manufacturing, higher precision requirements are placed on robot measurement, operation and processing, especially in the manufacturing and assembly process of large aircraft parts. Taking the hole making of small connectors for large aircraft as an example, there are thousands of brackets on the aircraft used for the installation and positioning of cables, pipes, sound insulation cotton and other system parts. There are many types of long spars, sheet metal frames, corner pieces, beams, etc. connected to the brackets. The connection holes on the parts currently still rely on manual measurement and marking positioning. The workload is heavy and the efficiency of manual marking is low. It is urgently needed to improve automation and flexibility.

[0003] In recent years, robots have attracted a lot of attention in the field of digital measurement, operation and processing of aircraft due to their high flexibility and low cost. Applying visual feature recognition and positioning, precision compensation and other technologies to aviation hole-making robots can effectively improve the automation and flexibility of the hole-making system, but the robot's own structural factors lead to its low processing accuracy.

[0004] Patent CN 107443377 A discloses a sensor-robot coordinate system conversion method and a robot hand-eye calibration method. The robot movement is based on the robot base coordinate system, and the laser line scanning sensor obtains the pose information of the image relative to the sensor coordinate system. In order to ensure that the robot can accurately move to the workpiece pose identified by the laser line scanning sensor, it is necessary to find the conversion relationship between the sensor coordinate system and the robot coordinate system, that is, the conversion matrix from the sensor coordinate system to the robot base coordinate system. This method gives the conversion relationship between the sensor coordinate system and the robot coordinate system, but there is no more detailed explanation on how to improve the accuracy of hand-eye calibration.

[0005] Patent CN 109623822 A discloses a robot hand-eye calibration method. The robot is calibrated using a laser tracker and a carefully designed tetrahedron to avoid the hand-eye calibration being affected by the parameter errors of the industrial robot. The measurement accuracy is higher and the calibration results are accurate and reliable. This method uses a laser scanner installed on the robot and requires special calibration tooling, so it is not suitable for desktop robot assembly application scenarios.

[0006] Patent CN112223285A discloses a robot hand-eye calibration method based on combined measurement, including using marker points, checkerboard calibration plates and C-Track optical dynamic tracking system to build a hand-eye calibration test platform as an intermediate measurement system; calculating the matrix transformation relationship of the coordinate system; solving the matrix transformation relationship between the camera coordinate system and the robot flange coordinate system, that is, the hand-eye relationship matrix, according to the closed-loop coordinate system matrix transformation relationship. During the hand-eye calibration process, it is not necessary to move the robotic arm, which avoids the introduction of robotic arm kinematic errors due to the movement of the robotic arm, improves the accuracy of hand-eye calibration, establishes a closed-loop coordinate system matrix transformation relationship, and only needs to measure once to solve the hand-eye relationship matrix, which simplifies the hand-eye calibration process and improves the efficiency of hand-eye calibration. This method utilizes the need for a C-Track optical dynamic tracking system, and requires the use of dedicated or modified marker points and checkerboard calibration plates, and has a small range of applicable scenarios.

[0007] Therefore, providing a high-precision hand-eye calibration method for a robot system is of great significance to the subsequent robot processing / assembly accuracy. Summary of the invention

[0008] To this end, the present invention provides a high-precision hand-eye calibration method for a robot system, which improves the accuracy of hand-eye calibration, thereby reducing the accumulation and amplification of errors in the vision guidance system, and corrects the posture error through an iterative compensation method. The final calibration accuracy can reach the theoretical robot repeat positioning accuracy, meeting the needs of high-precision hole making and assembly.

[0009] In order to solve the above technical problems, the present invention provides a high-precision hand-eye calibration method for a robot system, wherein a 3D camera is installed at the end of the robot wrist, a calibration plate is configured on one side of the camera 3D camera, and multiple target ball points are set on the end effector of the robot. The hand-eye calibration method comprises: Plan multiple random robot poses; Use the laser tracker to perform hand-eye calibration and obtain the transformation matrix between the laser tracker measurement coordinate system and the robot base coordinate system And the conversion relationship between the robot flange origin coordinate system and the end effector tooling coordinate system ; Run the current robot posture and perform the measured posture acquisition step, which includes: Get the current controller theoretical rotation matrix And get the current controller theoretical displacement vector , get the current theoretical position of the robot controller ; The laser tracker is used to obtain the coordinate values ​​of the plurality of target points, and the end effector tooling coordinate system is established according to the coordinate values ​​of the plurality of target points. Based on the end effector tooling coordinate system, the coordinate parameters of the end effector tooling coordinate system in the laser tracker measurement coordinate system are obtained. , based on the transformation matrix , the coordinate parameters Convert to the robot base coordinate system to obtain the coordinate parameters of the end effector tooling coordinate system in the robot base coordinate system ; According to the conversion relationship and the coordinate parameters , and get the measured rotation matrix and the measured displacement vector ; Perform a posture compensation step, which includes: rotating the matrix according to the theoretical rotation matrix and the measured rotation matrix , and obtain the slightly adjusted rotation operator ΔR, according to the theoretical displacement vector and the measured displacement vector , and obtain the slightly adjusted translation operator ΔP; According to the slightly adjusted rotation operator ΔR and the current controller theoretical rotation matrix , get the adjusted target posture ; According to the slightly adjusted translation operator ΔP and the current controller theoretical displacement vector , and get the adjusted displacement vector ; According to the adjusted target posture and the adjusted displacement vector , adjust the current robot posture, and perform the measured posture acquisition step again to obtain the adjusted measured posture ; Perform an iterative correction step, including adjusting the theoretical position of the current robot controller according to the and the measured pose after adjustment , and the residual error is , determine the residual error Whether it meets the preset accuracy threshold, if not, the current residual error As the compensation value for the next iteration, the posture compensation step is performed again until the accuracy threshold or the maximum number of iterations is reached. The measured posture at this time is used as the theoretical posture of the robot, and the posture of the calibration plate in the 3D camera coordinate system is obtained at this time; Run to the rest of the robot postures, repeat the measured posture acquisition step, the posture compensation step and the posture compensation step, obtain the posture of the corresponding calibration plate in the 3D camera coordinate system and the robot theoretical posture under each robot posture, and then perform the robot hand-eye calibration process; According to the conversion relationship and the coordinate parameters , and get the measured rotation matrix and the measured displacement vector ,include: Calculate the parameters of the robot flange origin in the robot base coordinate system : ; in, is a 4×4 matrix, expressed as , the measured rotation matrix is a 3×3 matrix, the measured displacement vector is a 3×1 matrix.

[0010] In one embodiment of the present invention, planning a plurality of random robot poses comprises: Planning multiple translation pose points and multiple pose change pose points so that each robot pose can capture the calibration plate; wherein the translation pose points are arranged in a pyramidal manner around the initial photographing pose, and the pose change pose points are arranged in a satellite manner to adjust the robot's pose around the initial photographing pose; According to the internal parameters of the 3D camera, the shooting distance of each pose point is determined to ensure that the shooting distance of the 3D camera is between the near field of view and the far field of view of its field of view.

[0011] In one embodiment of the present invention, the coordinate parameters of the end effector tooling coordinate system in the robot base coordinate system are The calculation is as follows: .

[0012] In one embodiment of the present invention, the slightly adjusted rotation operator ΔR is calculated as follows: ; ; In one embodiment of the present invention, the adjusted target posture The calculation is as follows: ; In one embodiment of the present invention, the adjusted displacement vector The calculation is as follows: ; ; In one embodiment of the present invention, the accuracy threshold is between 0.05 mm and 0.15 mm.

[0013] In one embodiment of the present invention, at least three target ball points are provided.

[0014] In one embodiment of the present invention, performing a robot hand-eye calibration process includes: performing a robot hand-eye calibration process includes: estimating a value of X using a least squares method according to the following formula: , Among them, X represents the pose transformation relationship from the 3D camera to the robot flange origin coordinate system; A represents the pose of the calibration plate in the 3D camera coordinate system; B represents the transformation relationship from the robot flange origin coordinate system to the robot base coordinate system.

[0015] The above technical solution of the present invention has the following advantages compared with the prior art: The high-precision hand-eye calibration method for a robot system described in the present invention effectively improves the absolute positioning accuracy of the robot by introducing a laser tracker to compensate for the robot's posture error during the robot hand-eye calibration process, thereby obtaining more accurate hand-eye calibration parameters. This method significantly improves the workpiece positioning accuracy of a visually guided processing / assembly robot system, which is of great significance for improving the overall accuracy of subsequent processing and assembly of the robot.

[0016] The present invention only needs to use the laser tracker to perform hand-eye calibration once during the robot system debugging phase. After the calibration is completed, high-precision hand-eye calibration parameters can be obtained, and there is no need to rely on the laser tracker again during subsequent use. This not only reduces the application cost of the system, but also ensures the long-term stability of accuracy, which plays an important role in improving the efficiency and accuracy of robot processing and assembly. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings.

[0018] Figure 1 Schematic diagram of the flexible hole-making system based on vision-guided robots.

[0019] Figure 2 Schematic diagram of the error transmission chain of robot vision-guided hole making.

[0020] Figure 3 Schematic diagram of the conventional hand-eye calibration coordinate transformation relationship of the robot.

[0021] Figure 4Schematic diagram of the robot hand-eye calibration process without robot pose correction.

[0022] Figure 5 Schematic diagram of using laser tracker to measure the target ball and correct the robot's posture.

[0023] Figure 6 Schematic diagram of the robot's iterative correction principle.

[0024] Figure 7 Schematic diagram of the hand-eye calibration coordinate transformation relationship for correcting the robot's posture using a laser tracker.

[0025] Figure 8 Schematic diagram of the robot hand-eye calibration process through robot pose correction. DETAILED DESCRIPTION

[0026] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0027] In the present invention, "several" means one or more, "multiple" means more than two, "greater than", "less than", "exceed" and the like are understood to exclude the number itself; "above", "below", "within" and the like are understood to include the number itself. In the description of the present invention, if there is a description of "first" or "second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0028] Aiming at the needs of adaptive flexible hole making by robots for aircraft parts, taking robot hole making as an example, refer to Figure 1 The figure shows a flexible hole-making system based on visual guidance robot. The system is mainly composed of a robot, a 3D camera, a spindle (drill), and a flexible tooling (pneumatic fixture). The main debugging process of the system is robot absolute positioning accuracy calibration, hand-eye calibration, and TCP position compensation. The main workflow is: flexible tooling workpiece clamping, workpiece type identification, camera photography, hole position information, and start hole making. Applying visual feature recognition and positioning, precision compensation and other technologies to aviation hole-making robots can effectively improve the automation and flexibility of the hole-making system, and the overall hole-making accuracy target is within ±0.5mm. The 3D camera is installed at the end of the robot wrist. The robot extracts relevant features based on the part digital model, processes the 3D point cloud information of the image, obtains the position data of the part hole-making, and then guides the robot to the specified position for hole-making. Establishing a matching relationship between machine vision and the three-dimensional CAD model of the part can quickly, efficiently and accurately identify the part type and the hole-making point position.

[0029] Reference Figure 2As shown in the figure, the main factors affecting the robot's hole making error mainly include the workpiece positioning error, the TCP calibration error of the hole making tool (drill), the robot body positioning error, and the robot deformation error caused by the processing force. The superposition of errors from multiple factors jointly affects the robot's hole making error. Among them, the robot body accuracy is the main factor affecting the robot's hole making accuracy. After the robot body is calibrated with absolute accuracy, it can theoretically reach 0.2-0.3mm. However, due to the cumulative amplification of errors and the superposition of errors from multiple factors, the final robot hole making accuracy can only reach about 1mm, which still cannot meet the requirement of aviation hole making accuracy better than ±0.5mm.

[0030] At present, the nominal data of resolution and accuracy of high-precision industrial 3D cameras or 3D scanners are less than 0.1mm, while the positioning error of the robot body is about millimeter level if the accuracy of the robot body has not been calibrated with absolute accuracy. After absolute accuracy calibration, the error can be less than 0.5mm. The accuracy of 3D cameras is about an order of magnitude higher than that of the robot body, so the main source of the robot's hand-eye calibration error is still the robot body error. Figure 2 It can be seen that the entire error transmission chain of visual positioning of the workpiece is the longest, and the robot body error is at the upstream of the entire error transmission chain. The hand-eye calibration error caused by the robot body error will gradually accumulate and amplify with the subsequent visual photography process, which will have a significant impact on the subsequent workpiece positioning error. Therefore, improving the robot hand-eye calibration accuracy has a positive significance for improving the overall processing accuracy of the robot.

[0031] Reference Figure 3 As shown in the figure, the 3D camera is installed at the end of the robot wrist, which is a typical 3D camera hand-eye calibration problem with the eye in the hand. Among them, X represents the pose transformation relationship from the 3D camera to the robot flange origin coordinate system, A represents the pose of the calibration plate in the camera coordinate system, and B represents the transformation relationship from the robot flange origin coordinate system to the robot base coordinate system.

[0032] Reference Figure 4 As shown in the figure, it is a conventional robot hand-eye calibration process without robot posture correction. The robot posture for hand-eye calibration is planned, multiple different robot postures are planned, and it is ensured that the calibration plate can be photographed. The robot runs to each posture in turn to take pictures, records the photographing data A, and reads the posture parameter B from the robot controller for recording. The parameters of group A and group B are input into the calibration software, X is calculated, and the corresponding error results are output. The hand-eye calibration accuracy is judged according to the error results. Since the calibration plate does not move during the entire robot calibration process, the position relationship between the calibration plate and the robot base coordinate system is fixed. After the robot takes pictures at position 1 and position 2, the following equation can be constructed: ; go through After the coordinates change, the position of the calibration plate in the robot base coordinate system is obtained, which is fixed, so both sides of the equation are equal.

[0033] Both sides of the equation can be transformed into: ; Among them, , , which can be simplified to:

[0034] At this point, a typical AX=XB problem is formed, and the value of X can usually be estimated using the least squares method.

[0035] However, if you want to improve the accuracy of hand-eye calibration, the first problem to be solved is to have relatively accurate parameters A and B, and then consider using a suitable optimization algorithm to optimize the value of X. If the obtained parameters A and B are not accurate enough, it is difficult to get a relatively accurate parameter X value using any optimization algorithm.

[0036] The accuracy of parameter A depends on the measurement accuracy of the camera body. To improve the accuracy of parameter A, a camera with higher measurement accuracy is needed. In general usage scenarios, the accuracy of the camera body is much higher than that of the robot body. Parameter B is the transformation relationship between the robot flange origin coordinate system and the robot base coordinate system. If B directly reads the parameters in the robot controller, it will introduce the robot absolute accuracy error, which may result in a large error.

[0037] Therefore, if the accuracy of parameter B can be improved, the accuracy of the entire hand-eye calibration can be greatly improved. If the robot posture error is used for detection and correction, and the corrected parameters are obtained, the error of parameter B can be greatly reduced. Parameter B can be changed from a teach pendant parameter to a parameter that is closer to the actual measurement value after compensation, and the accuracy of solving parameter X is also improved accordingly, so a more accurate hand-eye calibration result can be obtained.

[0038] If the robot posture error can be measured and corrected, the robot hand-eye calibration accuracy can be improved. Therefore, this embodiment provides a high-precision hand-eye calibration method for a robot system, a 3D camera is installed at the end of the robot wrist, a calibration plate is configured on one side of the camera 3D camera, and multiple target ball installation positions are set on the robot end effector to facilitate the installation of the target ball seat and the target ball. Figure 5As shown. Since the error caused by the deformation of the tooling is not on the same order of magnitude as the robot posture error, we assume that the entire tooling is rigid, the camera and the spindle are fixed together through the tooling, and their transformation relationship is fixed, which can be directly obtained through digital model calculation, or the laser tracker can be used to obtain its transformation relationship through hand-eye calibration. And the target ball installation position is processed by CNC machine tools to ensure the position accuracy. The laser tracker establishes the coordinate system of the end effector by measuring at least 3 target balls of the end effector, and the actual posture parameters of the robot flange origin coordinate system can be determined through the transformation relationship.

[0039] Reference Figure 8 As shown, the hand-eye calibration method includes: S1. Plan multiple random robot positions; including: Planning multiple (e.g., 10) translation pose points and multiple (e.g., 10) pose change pose points so that each robot pose can capture the calibration plate; wherein the translation pose points are arranged in a pyramidal manner around the initial photographing pose, and the pose change pose points are arranged in a satellite manner to adjust the robot's pose around the initial photographing pose; According to the internal parameters of the 3D camera, determine the shooting distance of each pose point to ensure that the shooting distance of the 3D camera is between the near field of view and the far field of view of its field of view. The line condition is normal indoor light. In case of insufficient light, fill light can be used.

[0040] S2. Use the laser tracker to perform hand-eye calibration and obtain the transformation matrix between the laser tracker measurement coordinate system and the robot base coordinate system And the conversion relationship between the robot flange origin coordinate system and the end effector tooling coordinate system , refer to Figure 7 As shown, Among them, the coordinate parameters The calculation is as follows: .

[0041] S3, running the current robot posture, and performing the measured posture acquisition step, which includes: S31. Run the robot program to make the robot run to the position set in the program and obtain the current controller theoretical rotation matrix And get the current controller theoretical displacement vector , get the current theoretical position of the robot controller ; S32, using a laser tracker to obtain the coordinate values ​​(X, Y, Z) of multiple (at least three) target points, establishing an end effector fixture coordinate system according to the coordinate values ​​of the multiple target points, and obtaining the coordinate parameters of the end effector fixture coordinate system in the laser tracker measurement coordinate system based on the end effector fixture coordinate system. , based on the transformation matrix , the coordinate parameters Convert to the robot base coordinate system to obtain the coordinate parameters of the end effector tooling coordinate system in the robot base coordinate system : ; S33, according to the conversion relationship and the coordinate parameters , and get the measured rotation matrix and the measured displacement vector ;include: Calculate the parameters of the robot flange origin in the robot base coordinate system : ; in, is a 4×4 matrix, expressed as , the measured rotation matrix A 3×3 matrix, measured displacement vector is a 3×1 matrix.

[0042] S4, performing a posture compensation step, which includes: S41, according to the theoretical rotation matrix and the measured rotation matrix , and obtain the slightly adjusted rotation operator ΔR, according to the theoretical displacement vector and the measured displacement vector , the slightly adjusted translation operator ΔP is obtained; the slightly adjusted rotation operator ΔR is calculated as follows: ; ; S42, the robot end effector needs to reach the theoretical posture At this point, the current measured posture needs to be adjusted to make the robot's measured posture close to the target posture. , need to calculate , according to the slightly adjusted rotation operator ΔR and the current controller theoretical rotation matrix , get the adjusted target posture : ; The updated target rotation matrix for the robot can be re- Convert Euler angles or quaternions and input them into the robot controller, run the robot to make it reach the new position, and perform actual measurement to measure the new measured rotation matrix , Position compensation is similar, according to the slightly adjusted translation operator ΔP and the current controller theoretical displacement vector , and get the adjusted displacement vector ;in: ; ; S43, according to the adjusted target posture and the adjusted displacement vector , forming a homogeneous transformation matrix : ; Adjust the current robot posture. After running to the new theoretical target pose, the laser tracker is used again to measure the actual pose acquisition step to obtain a new actual rotation matrix and the position vector , and get the adjusted measured pose .

[0043] S5, performing an iterative correction step, including: S51, according to the current robot controller theoretical posture and the measured pose after adjustment , and the residual error is , determine the residual error Whether the preset accuracy threshold is met ε , where the accuracy threshold ε Set according to the actual calibration requirements. Generally, you can refer to the robot's repeated positioning accuracy and accuracy threshold. ε Slightly higher than the robot's repeatability accuracy. Based on experience, it can be set between 0.05mm and 0.15mm. If the iteration termination requirements are not met, continue to perform iterative correction, use the current residual error as the compensation value for the next iteration, and perform the posture compensation step again (repeat S41-S43) until the accuracy threshold is reached ( < ε ) or the maximum number of iterations, it can be considered that the actual motion position of the robot has reached the theoretical position. The measured posture at this time is used as the robot theoretical posture, and parameter B is recorded as the current robot theoretical position, that is, the rotation matrix of the controller theory With theoretical position data , take a photo with a 3D camera and obtain the position and posture of the calibration plate in the 3D camera coordinate system (parameter A).

[0044] It should be noted that the principle of robot iterative correction is as follows Figure 6 As shown in the figure, the posture transformation of the robot can be achieved through the homogeneous transformation matrix, which is a 4×4 matrix including rotation operators and translation operators. According to the theory of spatial similarity of robot errors, when the inputs of each joint of the robot are close, the corresponding errors are also similar. The error between the theoretical posture and the measured posture of the robot is usually less than 1mm. The distance between the theoretical posture and the measured posture is relatively small. According to the theory of spatial similarity, the inputs of each joint of the robot are also close, and the corresponding errors are also similar. When controlling the movement of the robot to make a slight adjustment to the theoretical posture of the robot, the measured posture will also undergo a corresponding slight change.

[0045] The current posture of the robot can be compensated by using the rotation operator as the compensation amount. The posture compensation can be performed using quaternion, Euler angle or rotation matrix. Taking the rotation matrix method as an example, the current theoretical posture of the robot controller is In order to make the measured posture reach the target posture, the target posture 2 is input into the robot controller. The target posture 2 is obtained by transforming the target posture 1 through the rotation operator ΔT. At this time, the measured posture of the robot also moves to the measured posture 2. Under ideal conditions, the measured posture is also transformed based on the rotation operator ΔT, then the measured posture 2 just becomes the target posture, and the posture compensation is completed. However, in the actual compensation process, when the robot is compensated with the rotation operator ΔT as the compensation amount, due to the deviation between the theoretical kinematic parameters and the non-kinematic parameters, there is still a deviation when solving the joint variables corresponding to the compensation amount through the robot inverse kinematics. When the robot is driven by the compensated joint variables, its end posture can only reach the measured posture 2, and the compensation amount will still cause residual errors. This method ignores the nonlinear relationship between the compensation value and the positioning error and cannot complete the compensation of all error amounts. However, the residual error between the measured position 2 and the target posture can be , as the next iteration compensation value, and then the next iteration compensation is performed. This iterative compensation method is to perform error compensation multiple times based on the direct compensation method. Through multiple iterations, the residual error of the previous iteration is To compensate, when the residual error The iteration stops when the accuracy is less than the threshold or the number of iterations is reached.

[0046] S6. Run to the rest of the robot postures, repeat the measured posture acquisition step, posture compensation step and posture compensation step, obtain the posture of the corresponding calibration plate under each robot posture in the 3D camera coordinate system and the robot theoretical posture, and then perform the robot hand-eye calibration process.

[0047] The value of X is estimated using the least squares method according to the following formula:

[0048] Among them, X represents the pose transformation relationship from the 3D camera to the robot flange origin coordinate system; A represents the pose of the calibration plate in the 3D camera coordinate system; B represents the transformation relationship from the robot flange origin coordinate system to the robot base coordinate system.

[0049] Finally, X is the final robot hand-eye calibration data, which is saved in the visual software for subsequent workpiece photography and positioning, greatly improving the visual guidance accuracy of the workpiece.

[0050] Each posture of the robot is measured using a laser tracker, and then corrected using the iterative compensation method. After the correction is completed, a photo is taken, and the photo data A is recorded. At the same time, the posture parameters B are recorded. The parameters of group A and group B are input into the calibration software, X is calculated, and the corresponding error results are output. The hand-eye calibration accuracy is judged based on the error results. In theory, the hand-eye calibration accuracy should be less than 0.3mm to meet the actual hole making requirements.

[0051] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0052] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0053] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0054] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0055] Finally, it should be noted that the above specific implementation methods are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A high-precision hand-eye calibration method for a robot system, characterized in that: A 3D camera is installed at the end of the robot wrist, a calibration plate is configured on one side of the camera 3D camera, and multiple target ball points are set on the end effector of the robot. The hand-eye calibration method includes: Plan multiple random robot poses; Use the laser tracker to perform hand-eye calibration and obtain the transformation matrix between the laser tracker measurement coordinate system and the robot base coordinate system And the conversion relationship between the robot flange origin coordinate system and the end effector tooling coordinate system ; Run the current robot posture and perform the measured posture acquisition step, which includes: Get the current controller theoretical rotation matrix And get the current controller theoretical displacement vector , get the current theoretical position of the robot controller ; The laser tracker is used to obtain the coordinate values ​​of the plurality of target points, and the end effector tooling coordinate system is established according to the coordinate values ​​of the plurality of target points. Based on the end effector tooling coordinate system, the coordinate parameters of the end effector tooling coordinate system in the laser tracker measurement coordinate system are obtained. , based on the transformation matrix , the coordinate parameters Convert to the robot base coordinate system to obtain the coordinate parameters of the end effector tooling coordinate system in the robot base coordinate system ; According to the conversion relationship and the coordinate parameters , and get the measured rotation matrix and the measured displacement vector ; Perform a posture compensation step, which includes: rotating the matrix according to the theoretical rotation matrix and the measured rotation matrix , and obtain the slightly adjusted rotation operator ΔR, according to the theoretical displacement vector and the measured displacement vector , and obtain the slightly adjusted translation operator ΔP; According to the slightly adjusted rotation operator ΔR and the current controller theoretical rotation matrix , get the adjusted target posture ; According to the slightly adjusted translation operator ΔP and the current controller theoretical displacement vector , and get the adjusted displacement vector ; According to the adjusted target posture and the adjusted displacement vector , adjust the current robot posture, and perform the measured posture acquisition step again to obtain the adjusted measured posture ; Perform an iterative correction step, including adjusting the theoretical position of the current robot controller according to the and the measured pose after adjustment , and the residual error is , determine the residual error Whether it meets the preset accuracy threshold, if not, the current residual error As the compensation value for the next iteration, the posture compensation step is performed again until the accuracy threshold or the maximum number of iterations is reached. The measured posture at this time is used as the theoretical posture of the robot, and the posture of the calibration plate in the 3D camera coordinate system is obtained at this time; Run to the rest of the robot postures, repeat the measured posture acquisition step, the posture compensation step and the posture compensation step, obtain the posture of the corresponding calibration plate in the 3D camera coordinate system and the robot theoretical posture under each robot posture, and then perform the robot hand-eye calibration process; According to the conversion relationship and the coordinate parameters , and get the measured rotation matrix and the measured displacement vector ,include: Calculate the parameters of the robot flange origin in the robot base coordinate system : ； in, is a 4×4 matrix, expressed as , the measured rotation matrix is a 3×3 matrix, the measured displacement vector is a 3×1 matrix.

2. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: Plan multiple random robot poses, including: Planning multiple translation pose points and multiple pose change pose points so that each robot pose can capture the calibration plate; wherein the translation pose points are arranged in a pyramidal manner around the initial photographing pose, and the pose change pose points are arranged in a satellite manner to adjust the robot's pose around the initial photographing pose; According to the internal parameters of the 3D camera, the shooting distance of each pose point is determined to ensure that the shooting distance of the 3D camera is between the near field of view and the far field of view of its field of view.

3. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: The coordinate parameters of the end effector tooling coordinate system in the robot base coordinate system The calculation is as follows: 。 4. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: The slightly adjusted rotation operator ΔR is calculated as follows: ； 。 5. The high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: The adjusted target posture The calculation is as follows: 。 6. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: The adjusted displacement vector The calculation is as follows: ； 。 7. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: The accuracy threshold is between 0.05 mm and 0.15 mm.

8. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: There are at least three target ball points.

9. A high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: The robot hand-eye calibration process includes: estimating the value of X using the least squares method according to the following formula: AX=XB Among them, X represents the pose transformation relationship from the 3D camera to the robot flange origin coordinate system; A represents the pose of the calibration plate in the 3D camera coordinate system; B represents the transformation relationship from the robot flange origin coordinate system to the robot base coordinate system.

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