A high-precision hand-eye calibration method for a robot system

Abstract

The present application relates to a kind of robot system high-precision hand-eye calibration method.The present application includes by planning multiple random robot poses;During the process of running robot pose, the coordinate values of target ball points are measured by laser tracker, end effector tool coordinate system is constructed, and is converted to robot base coordinate system, and the measured rotation matrix and displacement vector are calculated.Combined with theoretical rotation matrix and displacement vector, the pose compensation is realized by the rotation operator and the translation operator of trace adjustment, and the robot target posture and displacement are adjusted;After compensation, the measured pose is repeatedly measured, residual error is calculated, and it is used as the compensation value of next iteration, until residual error meets preset precision threshold or reaches maximum iteration number.Finally, the pose of calibration plate in 3D camera coordinate system and the corresponding relationship of robot theoretical pose are recorded, for completing robot hand-eye calibration process.The method improves calibration accuracy, meets high-precision machining and assembly requirements.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of robot hand-eye calibration, and particularly to a high-precision robot system hand-eye calibration method. BACKGROUND

[0002] Robot measurement operation processing integrated technology has wide application prospects in the processing and assembly fields of large complex components in the aviation, aerospace, high-speed rail, wind power and other industries. Compared with traditional manufacturing, especially in the process of manufacturing and assembling parts of large aircraft, higher precision requirements are put forward for robot measurement operation processing. Taking the drilling of small connectors of large aircraft as an example, there are thousands of brackets on the aircraft for the installation and positioning of cable, pipeline, soundproof cotton and other system components, and the types of brackets connected to the longerons, sheet metal frames, angle pieces and cross beams are various. The connection hole positions on the parts still rely on manual measurement and line positioning, which is laborious and inefficient, and automation and flexibility are urgently needed.

[0003] In recent years, robots have attracted a lot of attention in the field of aircraft digital measurement operation processing due to their high flexibility and low cost. The application of visual feature recognition and positioning, precision compensation and other technologies to aviation drilling robots can effectively improve the automation and flexibility of the drilling system, but the structure of the robot itself leads to low processing precision.

[0004] In patent CN 107443377 A, a sensor-robot coordinate system conversion method and a robot hand-eye calibration method are disclosed. The robot motion is based on the robot base coordinate system, while the pose information of the laser line scanning sensor is obtained relative to the sensor coordinate system. In order to ensure that the robot can accurately move to the workpiece pose recognized by the laser line scanning sensor, the conversion relationship between the sensor coordinate system and the robot coordinate system needs to be obtained, i.e. 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 does not provide more detailed instructions on how to improve the hand-eye calibration precision.

[0005] In patent CN 109623822 A, a robot hand-eye calibration method is disclosed. A laser tracker and a carefully designed tetrahedron are used to calibrate the robot hand-eye, which avoids the influence of industrial robot parameter errors on hand-eye calibration, and has higher measurement precision and accurate and reliable calibration results. This method uses a laser scanner installed on the robot, which requires a special calibration tool, 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, a checkerboard calibration plate, and a 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; and solving the matrix transformation relationship between the camera coordinate system and the robot flange coordinate system, i.e., the hand-eye relationship matrix, based on the closed-loop coordinate system matrix transformation relationship. During the hand-eye calibration process, there is no need to move the robotic arm, which avoids the introduction of robotic arm kinematic errors due to moving the robotic arm, improves the accuracy of hand-eye calibration, establishes a closed-loop coordinate system matrix transformation relationship, and only requires one measurement 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 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] To solve the above technical problems, the present invention 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, and multiple target points are set on the robot end effector. The hand-eye calibration method includes:

[0010] Plan multiple random robot poses;

[0011] 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 ;

[0012] Run the current robot posture and perform the measured posture acquisition step, which includes:

[0013] Get the current controller theoretical rotation matrix And get the current controller theoretical displacement vector , get the current robot controller theoretical pose ;

[0014] The coordinate values ​​of the target points are obtained by using a laser tracker, and an end effector tooling coordinate system is established according to the coordinate values ​​of the 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 ;

[0015] According to the conversion relationship and the coordinate parameters , and get the measured rotation matrix and the measured displacement vector ;

[0016] Perform a posture compensation step, which includes: rotating the matrix according to the theoretical and the measured rotation matrix , we get the slightly adjusted rotation operator ΔR, according to the theoretical displacement vector and the measured displacement vector , we get the slightly adjusted translation operator ΔP;

[0017] 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 , get the adjusted displacement vector ;

[0018] 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 ;

[0019] 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 obtained , 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 at this time is obtained;

[0020] The measured pose obtaining step, the pose compensation step and the pose compensation step are repeated to obtain the pose of the corresponding calibration plate in the 3D camera coordinate system and the theoretical pose of the robot at each robot pose, and then a robot hand-eye calibration process is performed;

[0021] According to the conversion relationship And the coordinate parameters , the measured rotation matrix And the measured displacement vector , comprising:

[0022] The parameters of the robot flange origin in the robot base coordinate system are calculated :

[0023] ;

[0024] Wherein, is a 4x4 matrix, represented as , the measured rotation matrix is a 3x3 matrix, and the measured displacement vector is a 3x1 matrix.

[0025] In an embodiment of the present application, a plurality of random robot poses are planned, comprising:

[0026] A plurality of translation pose points and a plurality of attitude change pose points are planned, so that each robot pose can capture the calibration plate; wherein the translation pose points are arranged in a pyramid method, and are arranged around the four sides of the initial shooting pose, and the attitude change pose points are arranged in a satellite method, and the attitude of the robot is adjusted around the initial shooting pose;

[0027] 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 located between the near field and the far field of its field of view.

[0028] In an embodiment of the present application, the coordinate parameters of the end effector tool coordinate system in the robot base coordinate system The calculation is as follows:

[0029] .

[0030] In an embodiment of the present application, the micro-adjusted rotation operator ΔR is calculated as follows:

[0031] ;

[0032] ;

[0033] In an embodiment of the present application, the adjusted target pose is calculated as follows:

[0034]

[0035] In an embodiment of the present application, the adjusted displacement vector is calculated as follows:

[0036]

[0037]

[0038] In an embodiment of the present application, the precision threshold is between 0.05mm and 0.15mm.

[0039] In an embodiment of the present application, the target ball point is provided with at least three.

[0040] In an embodiment of the present application, the robot hand-eye calibration process is performed, comprising: performing the robot hand-eye calibration process, comprising: estimating the value of X by using the least square method according to the following formula:

[0041] wherein X represents the pose transformation relationship of the 3D camera to the robot flange origin coordinate system; A represents the pose of the calibration board under the 3D camera coordinate system; and B represents the transformation relationship of the robot flange origin coordinate system to the robot base coordinate system.

[0042] The above technical solution of the present application has the following advantages compared with the prior art:

[0043] The robot system high-precision hand-eye calibration method provided by the present application introduces a laser tracker to compensate for the robot pose error in the robot hand-eye calibration process, effectively improves the absolute positioning accuracy of the robot, and thus obtains higher-precision hand-eye calibration parameters. This method significantly improves the workpiece positioning accuracy of the machining / assembly robot system based on visual guidance, and has important significance for improving the overall accuracy of subsequent machining and assembly of the robot.

[0044] The present application only needs to use a laser tracker to perform hand-eye calibration once during the debugging stage of the robot system, and high-precision hand-eye calibration parameters can be obtained after calibration. In the subsequent use process, the laser tracker does not need to be relied on again. This not only reduces the application cost of the system, but also ensures the long-term stability of the precision, and plays an important role in improving the efficiency and precision of robot machining and assembly. BRIEF DESCRIPTION OF DRAWINGS

[0045] ​​​​In order to make the content of the present application more easily understood, the present application will be further described in detail below according to specific embodiments of the present application and in conjunction with the accompanying drawings.

[0046] Figure 1 Schematic diagram of a vision-guided robot flexible hole-making system.

[0047] Figure 2 Schematic diagram of robot vision-guided hole-making error transmission.

[0048] Figure 3 Schematic diagram of robot conventional hand-eye calibration coordinate transformation relationship.

[0049] Figure 4 Schematic diagram of robot hand-eye calibration process without robot pose correction.

[0050] Figure 5 Schematic diagram of laser tracker measuring target ball correcting robot pose.

[0051] Figure 6 Schematic diagram of robot iterative correction principle.

[0052] Figure 7 Schematic diagram of laser tracker correcting robot pose hand-eye calibration coordinate transformation relationship.

[0053] Figure 8 Schematic diagram of robot hand-eye calibration process through robot pose correction. DETAILED DESCRIPTION

[0054] The present application will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present application and implement it, but the embodiments are not limiting the present application.

[0055] In the present application, the meaning of "several" is one or more, the meaning of "multiple" is two or more, and "greater than", "less than", "exceed" and the like are not included in the number; "above", "below", "within" and the like are understood to include the number. In the description of the present application, if "first", "second" are described, they are 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 indicated technical features or implicitly indicating the sequence of indicated technical features.

[0056] Facing the demand of robot adaptive flexible hole-making for aircraft parts, taking robot hole-making machining as an example, referring to Figure 1As shown, it is a flexible drilling system based on visual guidance robot. The system mainly consists of a robot, a 3D camera, a main shaft (drill bit), and a flexible tooling (pneumatic clamp). 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 shooting, giving hole position information, starting drilling, applying visual feature recognition and positioning, precision compensation, etc. to the aviation drilling robot, which can effectively improve the automation and flexibility of the drilling system, and the overall drilling precision 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 model, processes the 3D point cloud information of the image, obtains the position data of the part drilling, and then guides the robot to the specified position for drilling. The matching relationship between machine vision and three-dimensional CAD model of the part is established, which can quickly and efficiently identify the type of the part and the drilling point position.

[0057] Referring to Figure 2 As shown, it is the main factor affecting the drilling error of the robot, mainly including workpiece positioning error, TCP calibration error of drilling tool (drill bit), robot body positioning error, and deformation error of the robot caused by machining force. The superposition of various factor errors jointly affects the drilling error of the robot. Among them, the robot body precision is the main factor affecting the drilling precision of the robot. After the absolute precision calibration of the robot body, it can theoretically reach 0.2-0.3mm. However, due to the cumulative amplification of errors and the superposition of errors of various factors, the final drilling precision of the robot can only reach about 1mm, which still cannot meet the requirement of aviation drilling precision better than ±0.5mm.

[0058] At present, the resolution and precision of high-precision industrial 3D cameras or 3D scanners are both less than 0.1mm. If the precision of the robot body is not calibrated absolutely, its positioning error is about millimeter level. After absolute precision calibration, the error can be less than 0.5mm. The precision of the 3D camera is about one order of magnitude higher than that of the robot body. Therefore, the main source of the hand-eye calibration error of the robot is still the robot body error. From Figure 2 It can be seen that the whole error transmission chain of visual positioning workpiece is the longest, and the robot body error is at the most upstream of the whole error transmission chain. The hand-eye calibration error caused by the robot body error will gradually accumulate and amplify during the subsequent visual shooting process, which will have a significant impact on the subsequent workpiece positioning error. Therefore, improving the robot hand-eye calibration precision has a positive significance for improving the overall machining precision of the robot.

[0059] Referring to Figure 3As shown, the 3D camera is installed at the end of the robot wrist, which belongs to the typical eye-in-hand 3D camera hand-eye calibration problem. Wherein X represents the pose transformation relationship of the 3D camera to the robot flange origin coordinate system, A represents the pose of the calibration board in the camera coordinate system, and B represents the transformation relationship from the robot flange origin coordinate system to the robot base coordinate system.

[0060] Referring to Figure 4 As shown, it is a conventional robot hand-eye calibration process without robot pose correction, the robot hand-eye calibration robot pose is planned, a plurality of different robot poses are planned, and it is ensured that the calibration board can be shot. The robot runs to each pose in turn to take a photo, records the shooting data A, and at the same time reads the pose parameters B from the robot controller for recording, inputs the A group of parameters and the B group of parameters into the calibration software, calculates X, and outputs the corresponding error result. According to the error result, the hand-eye calibration accuracy is judged. Since the calibration board does not move during the entire robot calibration process, the positional relationship between the calibration board and the robot base coordinate system is fixed, and after the robot takes a photo at position 1 and position 2, the following equation can be constructed:

[0061] ;

[0062] After the coordinate change of , the position of the calibration board in the robot base coordinate system is obtained, which is fixed, so the two sides of the equation are equal.

[0063] The two sides of the equation can be transformed as:

[0064] ;

[0065] Among them, let , , it can be simplified as:

[0066] At this time, a typical AX=XB problem is formed, and the least square method can usually be used to estimate the value of X.

[0067] However, 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 obtain a relatively accurate parameter X value using any optimization algorithm.

[0068] Among them, the accuracy of parameter A depends on the measurement accuracy of the camera body, and to improve the accuracy of parameter A, a camera with higher measurement accuracy needs to be used. In general use scenarios, the accuracy of the camera body is much higher than that of the robot body. Parameter B, i.e. the transformation relationship from the robot flange origin coordinate system to the robot base coordinate system. If B directly reads the parameters in the robot controller, the absolute accuracy error of the robot will be introduced, and there may be a large error.

[0069] Therefore, if the accuracy of parameter B can be improved, the accuracy of the whole hand-eye calibration can be greatly improved. If the robot pose error is detected and corrected, the corrected parameters can be obtained, which can greatly reduce the error of parameter B. After the compensation of parameter B, the parameters closer to the true measurement values can be obtained, and the accuracy of solving parameter X is also improved, and the hand-eye calibration result with higher accuracy can be obtained.

[0070] If the robot pose error can be measured and corrected, the accuracy of the robot hand-eye calibration can be improved. Therefore, the embodiment provides a high-precision hand-eye calibration method of a robot system, a 3D camera is installed at the end of the wrist of the robot, a calibration board is arranged on one side of the camera 3D camera, a plurality of target ball mounting positions are arranged on the end effector of the robot, and the target ball seat and the target ball are conveniently installed, as shown in Figure 5 The error caused by the deformation of the tool under force is not in the same order of magnitude as the robot pose error. We assume that the whole tool is rigid, the camera and the spindle are fixed together through the tool, and the transformation relationship is fixed, which can be directly calculated by digital-analog calculation, or the transformation relationship can be obtained by hand-eye calibration using a laser tracker. And the target ball mounting position is processed by a numerical control machine tool to ensure the position accuracy. The laser tracker measures at least three target balls of the end effector to establish the coordinate system of the end effector, and the actual pose parameters of the origin coordinate system of the robot flange plate can be determined through the transformation relationship.

[0071] Referring to Figure 8 The hand-eye calibration method comprises the following steps:

[0072] S1, planning a plurality of random robot poses; comprising:

[0073] A plurality of (such as 10) translational pose points and a plurality of (such as 10) pose change points are planned, so that each robot pose can shoot the calibration board; wherein the translational pose points are arranged in a pyramid method, and the robot is arranged around the initial shooting pose; the pose change point adopts a satellite arrangement method, and the pose of the robot is adjusted around the initial shooting pose;

[0074] 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 and the far field of its field of view. The line condition is normal indoor light, and the light is insufficient. The light supplement lamp can be used.

[0075] S2, using a laser tracker to perform hand-eye calibration to 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 plate origin coordinate system and the end effector tool coordinate system , with reference to Figure 7 , as shown,

[0076] wherein the coordinate parameters are calculated as follows:

[0077] .

[0078] S3, running the current robot pose, a measured pose acquisition step, the step includes:

[0079] S31, running the robot program, so that the robot runs to the set pose in the program, to obtain the current controller theory rotation matrix and get the current controller theory displacement vector , get the current robot controller theory pose ;

[0080] S32, using a laser tracker to obtain the coordinate values (X, Y, Z) of a plurality of (at least three) target ball points, establishing an end effector tool coordinate system according to the coordinate values of a plurality of target ball points, based on the end effector tool coordinate system, get the coordinate parameters of the end effector tool coordinate system under the laser tracker measurement coordinate system, based on the transformation matrix , convert the coordinate parameters to the robot base coordinate system to get the coordinate parameters of the end effector tool coordinate system under the robot base coordinate system: ;

[0081] S33, according to the conversion relationship and the coordinate parameters , get the measured rotation matrix and the measured displacement vector ; including:

[0082] Calculate the parameters of the robot flange origin under the robot base coordinate system: :

[0083] ;

[0084] wherein, is a 4x4 matrix, represented as , the measured rotation matrix is a 3x3 matrix, and the measured displacement vector is a 3x1 matrix.

[0085] S4, a pose compensation step, the step includes:

[0086] S41, according to the theory rotation matrix and the measured rotation matrix , to obtain a fine-adjusted rotation operator ΔR according to the theoretical displacement vector and the measured displacement vector , to obtain a fine-adjusted translation operator ΔP; the fine-adjusted rotation operator ΔR is calculated as follows:

[0087] ;

[0088] ;

[0089] S42, the robot end effector is to reach the theoretical pose , the current measured pose needs to be adjusted, so that the robot measured pose approaches the target pose , it is necessary to calculate , according to the fine-adjusted rotation operator ΔR and the current controller theoretical rotation matrix , to obtain the adjusted target pose :

[0090] ;

[0091] The updated target rotation matrix of the robot can be converted into Euler angles or quaternions again and input into the robot controller, and the robot is run to reach the new pose, and actual measurement is performed to measure the new measured rotation matrix ,

[0092] Similarly, according to the fine-adjusted translation operator ΔP and the current controller theoretical displacement vector , to obtain the adjusted displacement vector ; wherein:

[0093] ;

[0094] ;

[0095] S43, according to the adjusted target pose and the adjusted displacement vector , a homogeneous transformation matrix is composed:

[0096] ;

[0097] Adjust the current robot pose, and the robot is run to the new theoretical target pose according to , and then the laser tracker measurement is used again to obtain the new measured rotation matrix​ and position vector , and get the adjusted measured pose .

[0098] S5, performing an iterative correction step, including:

[0099] S51, according to the current robot controller theoretical posture and the measured pose after adjustment , and the residual error is obtained , 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. Based on experience, it can be set between 0.05mm and 0.15mm. If the iteration termination requirement is not met, continue 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, and the measured posture at this time is used as the robot theoretical posture, and the 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 picture with a 3D camera and obtain the pose (parameter A) of the calibration plate in the 3D camera coordinate system at this time.

[0100] It should be noted that the principle of robot iterative correction is as follows Figure 6 As shown in the figure, the robot's pose transformation can be achieved using a homogeneous transformation matrix, a 4×4 matrix consisting of rotation and translation operators. According to the theory of spatial similarity of robot errors, when the inputs to each robot joint are similar, the corresponding errors are also similar. The error between the robot's theoretical pose and the measured pose is typically less than 1 mm. Since the distance between the theoretical and measured poses is relatively small, according to the theory of spatial similarity, the inputs to each robot joint are also similar, and the corresponding errors are also similar. When controlling the robot's motion to make small adjustments to the robot's theoretical pose, the measured pose will also undergo corresponding small changes.

[0101] The current posture of the robot can be compensated using the rotation operator as the compensation amount. The posture compensation can be performed using quaternions, Euler angles or rotation matrices. Taking the rotation matrix method as an example, the current theoretical posture of the robot controller is To make the measured pose reach the target pose, the target pose 2 is input into the robot controller, which is the target pose 1 transformed by the rotation operator ΔT. At this time, the robot measured pose also moves to the measured pose 2. In the ideal state, the measured pose also undergoes transformation based on the rotation operator ΔT, so at this time the measured pose 2 becomes the target pose, and the pose compensation is completed. However, in the actual compensation process, when the robot is compensated by using the rotation operator ΔT as the compensation amount, due to the deviation of the theoretical kinematics parameters and non-kinematics parameters, there is still deviation when the joint variables corresponding to the compensation amount are solved by the inverse kinematics of the robot. The end pose of the robot driven by the joint variables after compensation can only reach the measured pose 2, and the compensation amount still causes residual error . This method ignores the nonlinear relationship between the compensation value and the positioning error, and cannot complete the compensation of all error amounts. The residual error between the measured position 2 and the target pose can be used as the next iteration compensation value by the method of the present application, and the next iteration compensation is performed. This iterative compensation method is based on the direct compensation method and performs error compensation multiple times. The residual error of the last iteration is compensated, and the iteration stops when the residual error is less than the precision threshold or the number of iterations is reached.

[0102] S6, run to the rest of the robot pose, repeat the measured pose acquisition step, pose compensation step and pose compensation step, and after obtaining the corresponding pose of the calibration plate in the 3D camera coordinate system and the theoretical pose of the robot at each robot pose, the robot hand-eye calibration process is performed.

[0103] The value of X is estimated by the least square method according to the following formula:

[0104] Where X represents the pose transformation relationship of 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 of the robot flange origin coordinate system to the robot base coordinate system.

[0105] Finally, X is the final robot hand-eye calibration data, which is saved to the vision software for subsequent workpiece photographing positioning work, greatly improving the vision guidance accuracy of the workpiece.

[0106] Each pose of the robot is measured by the laser tracker, and then corrected by the iterative compensation method. After correction, photographing is performed, and photographing data A is recorded, and pose parameters B are recorded. A group of parameters and B group of parameters are input into the calibration software, X is calculated, and the corresponding error result is output. According to the error result, the hand-eye calibration accuracy is judged. In theory, the hand-eye calibration accuracy should be less than 0.3mm, which can meet the actual hole making demand.

[0107] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0108] The present application is described in reference to the flowchart and / or block diagrams of the method, apparatus (system) and computer program product according to embodiments of the present application. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processing device 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 and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 means for carrying out each of the one or more functions specified in the flowchart and / or block diagram block or blocks.

[0109] These computer program instructions can 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 instructions which implement the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 means for carrying out each of the one or more functions specified in the flowchart and / or block diagram block or blocks.

[0110] These computer program instructions can 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 flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 means for carrying out each of the one or more functions specified in the flowchart and / or block diagram block or blocks.

[0111] Finally, it should be noted that the detailed description of the specific embodiments of the present application is not intended to limit the scope of the present application. Although the present application has been described with reference to the example embodiments thereof, it is to be understood that the present application is not limited to the example embodiments described above but is intended to cover modifications and equivalents thereof falling within the spirit and scope of the present application.

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, and multiple target points are set on the robot end effector. 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 robot controller theoretical pose ; The coordinate values ​​of the target points are obtained by using a laser tracker, and an end effector tooling coordinate system is established according to the coordinate values ​​of the 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 and the measured rotation matrix , we get the slightly adjusted rotation operator ΔR, according to the theoretical displacement vector and the measured displacement vector , we get 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 , 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 obtained , 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 at this time is obtained; 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 calibration plate corresponding to each robot posture in the 3D camera coordinate system and the robot theoretical 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 be photographed with a calibration plate; wherein the translation pose points are arranged in a pyramidal manner around the initial photographic pose, and the pose change pose points are arranged in a satellite manner to adjust the robot's pose around the initial photographic 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. The 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. The 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. The 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. The 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. The high-precision hand-eye calibration method for a robot system according to claim 1, characterized in that: There are at least three target points.

9. The 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 Where X represents the pose transformation 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; and B represents the transformation from the robot flange origin coordinate system to the robot base coordinate system.

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