Workpiece adaptive positioning compensation method for multi-robot cooperative grinding and polishing

Abstract

The present invention provides a workpiece adaptive positioning compensation method for multi-robot collaborative grinding and polishing, relating to the fields of intelligent processing and grinding and polishing technology. The method first performs eye-in-hand and eye-out-hand calibration on the handling and measuring robot, multiple grinding robots, and scanning equipment in the grinding and polishing system, obtaining eye-in-hand and eye-out-hand calibration result matrices. The workpiece's base coordinate system is then calibrated within the grinding robot to obtain a base coordinate system matrix within the grinding robot's coordinate system. During the actual machining process, actual workpiece point cloud data and the corresponding handling and measuring robot poses are acquired, and the workpiece base coordinate system matrices, using visual calibration, are calculated within the coordinate systems of multiple grinding robots to achieve workpiece positioning. This method can improve system positioning accuracy and efficiency, ensuring stable and consistent machining quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent machining and polishing, and particularly relates to a workpiece adaptive positioning compensation method for multi-robot collaborative grinding and polishing. BACKGROUND

[0002] At present, the positioning function of the robot used in the automatic polishing of the surface of a complex structural component such as an aero-engine assembly mainly adopts the traditional teach-to-point method, which is low in efficiency, poor in repeatability and low in degree of automation, and seriously affects the beat, efficiency and yield in automatic production.

[0003] Since the accuracy of the teach-to-point method is determined by the proficiency and operation skills of the operator, the method itself has uncertainty, and each workpiece for batch production needs to be positioned independently and repeatedly, which consumes a large amount of manpower, material resources and time, so it is necessary to study the automatic calibration technology.

[0004] In addition, there are research progresses in the positioning of workpieces for single-robot automatic machining systems, but there are still deficiencies in the positioning method for collaborative machining of multi-robot systems. The single-robot automatic machining system can perform well in positioning the workpieces that are small in size, light in weight and easy to clamp, but it is difficult to simultaneously satisfy the positioning and machining processes for the workpieces that are large in size, heavy in weight and difficult to clamp. Therefore, there is an urgent need for a workpiece positioning method for multi-robot collaborative grinding and polishing. SUMMARY

[0005] The technical problem to be solved by the present application is to provide a workpiece adaptive positioning compensation method for multi-robot collaborative grinding and polishing to solve the problems of the prior art.

[0006] To solve the above technical problems, the technical solution adopted by the present application is: a workpiece adaptive positioning compensation method for multi-robot collaborative grinding and polishing, which is based on a scanning device connected to a carrying and measuring robot in a grinding and polishing system to complete the acquisition of workpiece point cloud for positioning compensation calculation, and specifically includes the following steps:

[0007] Step 1: The carrying and measuring robot in the grinding and polishing system and the multiple polishing robots and the scanning device are calibrated in eye-in-hand and eye-in-space to obtain a calibration result matrix in eye-in-hand and a calibration result matrix in eye-in-space;

[0008] Step 2: The base coordinate system of the workpiece is calibrated under the polishing robot to obtain a base coordinate system matrix of the workpiece under the polishing robot coordinate system;

[0009] Step 3: Based on the multiple calibration result matrices obtained in step 1 and the base coordinate system matrix of the workpiece in the grinding robot coordinate system obtained by calibration in step 2, the actual workpiece point cloud data and the corresponding handling and measurement robot posture are acquired, and the base coordinate system matrix of the workpiece using visual calibration in multiple grinding robot coordinate systems is calculated to achieve workpiece positioning.

[0010] Preferably, the step 3 includes:

[0011] Step 3.1: Based on the multiple calibration result matrices obtained in step 1 and the base coordinate system matrix of the workpiece in the grinding robot coordinate system obtained by calibration in step 2, calculate the position transfer matrix from the transport measurement robot to the grinding robot during calibration;

[0012] During the actual processing, the relative position relationship between the handling and measuring robot and the multiple polishing robots remains unchanged. Therefore, at any time, the position transfer moment from the handling and measuring robot to the polishing robot is equal to the position transfer matrix from the handling and measuring robot to the polishing robot during calibration.

[0013] Step 3.2: Obtain the workpiece point cloud data and the corresponding handling and measurement robot pose during the actual processing process, and convert the workpiece point cloud data from the scanning device coordinate system to the polishing robot coordinate system;

[0014] Step 3.2.1: Ensure that the workpiece clamping method during the actual machining process is consistent with that during calibration, and that the worktables in the grinding and polishing system are at the same initial angle. Ensure that all grinding robots are moved to a safe position so that the handling and measuring robot does not interfere with the grinding robot during movement.

[0015] Step 3.2.2: The transport measurement robot moves to a certain position p, and the scanning device collects point cloud data of the workpiece at this position, ensuring that the point cloud data can cover a local plane or curved surface of the workpiece. Where each point in the point cloud data is V = (x, y, z), then there is a corresponding point cloud P = {V};

[0016] Step 3.2.3: Repeat step 3.2.2 until N point cloud data are obtained The corresponding transport measurement robot position p n , n = 1, ..., N, and record the pose matrix of the handling and measuring robot at the corresponding position; ensure that the point cloud at these N positions can basically cover all the spatial information in the processing flow channel of several workpieces;

[0017] Step 3.2.4: Summarize the actual scanning process obtained in step 3.2.3, during which the transport measurement robot is located at point p n The pose matrix and the workpiece point cloud in the corresponding scanning device coordinate system A position transfer matrix of the polishing robot to the scanning device in the actual scanning process is calculated; a workpiece point cloud in the polishing robot coordinate system in the actual scanning process is further calculated;

[0018] Step 3.3: Obtain the workpiece base coordinate system matrix calibrated by vision of the polishing robot, to realize the positioning of the workpiece;

[0019] Step 3.3.1: Merge the workpiece point clouds in the polishing robot coordinate system obtained in N actual scanning processes after filtering and cutting, to obtain the point cloud of the local workpiece in the polishing robot coordinate system;

[0020] Step 3.3.2: Obtain the workpiece digital model point cloud, and calculate the calibration workpiece digital model point cloud in the polishing robot coordinate system in combination with the calibrated workpiece base coordinate system in the polishing robot coordinate system;

[0021] Step 3.3.3: Apply the ICP algorithm to calculate the transfer matrix of the point cloud of the local workpiece in the polishing robot coordinate system to the calibration workpiece digital model point cloud in the polishing robot coordinate system;

[0022] Step 3.3.4: Based on the transfer matrix of the point cloud of the local workpiece in the polishing robot coordinate system to the calibration workpiece digital model point cloud in the polishing robot coordinate system and the workpiece base coordinate system matrix calibrated by the digital model in the polishing robot coordinate system, the workpiece base coordinate system matrix calibrated by vision in the polishing robot coordinate system is calculated; the workpiece base coordinate system matrix calibrated by vision of the polishing robot is used to realize the positioning of the workpiece.

[0023] Preferably, the method further compensates for errors of the workpiece base coordinate system matrix calibrated by vision obtained in step 3 to improve the positioning accuracy, so as to achieve a required workpiece positioning result, comprising:

[0024] 1) When the base coordinate system of the workpiece is calibrated in the polishing robot coordinate system in step 2, ensure that the workpiece is in the initial position, and obtain the actual workpiece point cloud data and the corresponding handling measurement robot pose;

[0025] 2) Perform the operations of steps 3.2 to 3.3 on the actual workpiece point cloud data and the corresponding handling measurement robot pose obtained in 1) to obtain the transfer matrix of the point cloud of the local workpiece in the polishing robot to the calibration workpiece digital model point cloud in the polishing robot at the calibration position; and further calculate the comprehensive error of the workpiece base coordinate system matrix calibrated by vision in the polishing robot and the workpiece base coordinate system matrix calibrated by the digital model in the polishing robot;

[0026] 3) Correct the workpiece base coordinate system matrix calibrated by vision in the polishing robot calculated in step 3.3 by using the comprehensive error.

[0027] Preferably, the method further introduces turntable control to perform approximate compensation of the workpiece base coordinate system, including:

[0028] (1) Based on the comprehensive error between the workpiece base coordinate system matrix calibrated by vision in the polishing robot coordinate system at the calibrated position and the workpiece base coordinate system matrix calibrated by digital model in the polishing robot coordinate system, and the transfer matrix of the point cloud of the local workpiece in the polishing robot coordinate system offset to the digital model point cloud of the calibrated workpiece in the polishing robot coordinate system during the actual processing process, the correction matrix in the polishing robot coordinate system is calculated;

[0029] (2) Converting the calculated correction matrix in the polishing robot coordinate system into Cartesian correction coordinates that can be recognized by the robot;

[0030] (3) The turntable in the polishing system is rotated for compensation according to the Cartesian correction coordinates in the polishing robot coordinate system and then the workpiece is processed, that is, the compensation rotation angle of the turntable is calculated.

[0031] The beneficial effects of the above technical solution are as follows: the adaptive workpiece positioning compensation method provided by the present invention for multi-robot collaborative grinding and polishing can improve system positioning accuracy and efficiency, ensuring stable and consistent machining quality. It is also suitable for overall positioning calibration during coordinated machining processes between multiple robots, demonstrating its advanced and referenceable nature. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic structural diagram of a grinding and polishing system provided in an embodiment of the present invention;

[0033] Figure 2 A schematic diagram of the structure of a polishing workbench provided in an embodiment of the present invention;

[0034] Figure 3 A schematic structural diagram of a polishing robot provided in an embodiment of the present invention;

[0035] Figure 4 A schematic diagram of the tool rack structure provided by an embodiment of the present invention;

[0036] Figure 5 This is a process flow chart of the grinding and polishing system provided in an embodiment of the present invention.

[0037] In the figure: 1. Handling and measuring robot; 2. Loading and unloading table; 3. Turning table; 4. Grinding workbench; 5. Grinding robot; 6. Tool holder; 7. Turntable; 8. Three-jaw chuck; 9. Workpiece; 10. Quick change; 11. Grinding tool; 12. Spindle; 13. Belt sander; 14. Grinding wheel. DETAILED DESCRIPTION

[0038] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0039] In this embodiment, a workpiece adaptive positioning compensation method for multi-robot collaborative grinding and polishing is implemented based on the grinding and polishing system;

[0040] Grinding and polishing system Figure 1 As shown, it includes a loading and unloading measurement system, a grinding table 4, multiple grinding robots, a tool rack 6 and an electrical control system;

[0041] The loading and unloading measurement system consists of a handling and measurement robot 1 (a 300kg six-axis KUKA industrial robot), a loading and unloading platform 2, and a turning platform 3. It performs loading, unloading, and turning of workpieces on a polishing table 4. Simultaneously, the handling and measurement robot is rigidly connected to a scanning device via a tooling assembly to collect workpiece point clouds for positioning calculations.

[0042] like Figure 2 As shown, the polishing table 4 is a rotary mechanism, which is composed of a turntable 7, a three-jaw chuck 8, and a workpiece 9. For workpieces 9 with cylindrical or conical structures, the three-jaw chuck 8 is used to position the workpiece from the inside.

[0043] like Figure 3 As shown, the grinding robot 5 is a KUKA 70kg six-axis industrial robot. The end of the robot flange is connected to the grinding tool 11 through a quick change 10, which can realize rapid switching of different tools and grinding processing of different areas of the workpiece.

[0044] like Figure 4 As shown, the tool holder 6 includes a spindle 12, a belt sander 13, and a grinding wheel 14 connected in sequence, which can complete automated processing of different areas.

[0045] In this embodiment, the grinding and polishing system includes grinding robots R1 and R2 carrying grinding tools, and a handling and measuring robot R3 integrating handling and measuring functions. Each robot performs handling, measurement and positioning, grinding and polishing on the workpiece on the grinding workbench, and collaborates to complete the grinding and polishing of the workpiece; the handling and measuring robot R3 completes loading by clamping the workpiece from the loading and unloading table to the grinding workbench through the tooling, completes flipping by clamping the workpiece from the grinding workbench to the flipping table through the tooling, and completes unloading by clamping the workpiece from the flipping table to the loading and unloading table through the tooling; at the same time, the handling and measuring robot R3 completes the acquisition of the workpiece point cloud through the scanner C rigidly connected to the tooling for positioning calculation; the grinding workbench is a rotating platform, on which is provided a three-jaw chuck and a turntable for fixing and clamping the workpiece to be ground; the grinding robots R1 and R2 are industrial robots, and the end flange of the robot is connected to the grinding tool for grinding the workpiece.

[0046] The method is as follows Figure 5 As shown, the following steps are included:

[0047] Step 1: In the preparation stage, the handling measurement robot R3 and scanner C in the polishing system are calibrated with eyes in the hand to obtain the eye-in-hand calibration result matrix, that is, the hand-eye calibration matrix. The hand-eye calibration matrix represents the positional relationship between the flange of robot R3 and the scanner; the eye-out-hand calibration of robots R1, R2 and scanner C is performed to obtain the eye-out-hand calibration result matrix. The hand-eye calibration matrix represents the positional relationship between the robots R1 and R2 and the scanner.

[0048] In this embodiment, a calibration ball with an accuracy test report is prepared, the detection radius of the calibration ball is obtained, and a tooling connector that can fix the calibration ball to the end of the robot flange and a connector that can place the calibration ball on a horizontal plane are prepared.

[0049] Step 1.1: Calibrate the eyes of the handling measurement robot R3 and scanner C on the hand. The process is as follows:

[0050] Step 1.1.1: Fix the calibration ball on a horizontal plane in a certain posture to ensure that it is aligned with the base coordinate system of the robot R3 during the subsequent acquisition of the workpiece point cloud. The relative position relationship does not change and will not be affected by occlusion, interference and other conditions.

[0051] Step 1.1.2: Move the robot R3 so that the calibration ball is within the field of view of the scanner C and collect the workpiece point cloud data P C , and record the robot R3 in its base coordinate system and tool coordinate system The coordinate value of in, For robot R3 in its base coordinate system The three-dimensional coordinate values ​​under For robot R3 in its base coordinate system The three-dimensional coordinate values ​​​​under .

[0052] Generally, the subsequent The default coordinate value is R m The robot's base coordinate system and tool coordinate system Next (m=1,2,3).

[0053] In addition, define the eye-on-hand calibration result matrix for the R3 robot flange and scanner C for:

[0054]

[0055] Step 1.1.3: Repeat step 1.1.2 until four sets of robot R3 poses are obtained. And the point cloud collected by scanner C in the corresponding posture And ensure that the following requirements are met:

[0056] ① The R3 postures of these four groups of robots The quantities vary, and The quantities are the same, that is

[0057]

[0058] ② The R3 postures of these four groups of robots The weight difference between the two weights should be as large as possible and not less than 5mm, that is,

[0059]

[0060] ③ Workpiece point cloud collected by scanner C It should be ensured that: each point cloud contains half a complete and independent spherical point cloud without interference, that is, it can be finally cropped into an independent hemispherical point cloud; the spherical point cloud is uniform and smooth, without large noise data.

[0061] Step 1.1.4: Repeat step 1.1.2 until six sets of robot R3 poses are obtained. And the point cloud collected by scanner C in the corresponding posture And ensure that the following requirements are met:

[0062] ① The six groups of robot R3 postures The quantities vary, i.e.

[0063]

[0064] ② These six groups of robot postures The weight difference between the two weights should be as large as possible and not less than 5mm; the six groups of robot postures The difference between the two components should be as large as possible and not less than 5°, that is,

[0065]

[0066] ③Point cloud collected by scanner C It should be ensured that: each point cloud contains half a complete and independent spherical point cloud without interference, that is, it can be finally cropped into an independent hemispherical point cloud; the spherical point cloud is uniform and smooth, without large noise data.

[0067] Step 1.1.5: Point cloud collected by scanner C Filtering, cropping, and additional downsampling if the number of points in the point cloud exceeds a set value, to obtain a post-processed point cloud containing only the calibration sphere point cloud

[0068] Step 1.1.6: Use the four sets of robot R3 poses and the post-processed point cloud to calculate the hand-eye calibration matrix component; and use component and the six sets of robot R3 poses and the post-processed point cloud to calculate the hand-eye calibration matrix component, obtaining the hand-eye calibration matrix

[0069] Step 1.1.7: Use the obtained hand-eye calibration matrix and and the point cloud to calculate 10 half-sphere point clouds in the scanner C coordinate system, which are merged into a complete sphere point cloud in the robot R3 coordinate system, i.e.

[0070]

[0071] wherein is the complete sphere point cloud in the robot R3 coordinate system;

[0072] Step 1.1.8: Perform sphere fitting on the complete sphere point cloud to obtain the fitted radius and the root mean square error According to the measured radius of the calibration sphere in the given calibration sphere detection report obtain the fitted radius error which is:

[0073]

[0074] To eliminate accidental errors, multiple fittings are taken to obtain the average fitted radius error and the average root mean square error The qualified calibration result should meet the following requirements:

[0075]

[0076] If not, repeat steps 1.1.1-1.1.7 until the requirements are met.

[0077] Step 1.2: Perform the hand-out eye calibration of the grinding robot R1 and the scanner C, the process is as follows:

[0078] Step 1.2.1: Fix the calibration ball to the end of the flange of the polishing robot R1 in a certain posture to ensure that it is consistent with the tool coordinate system of the polishing robot R1 during the subsequent point cloud collection process. The relative position relationship does not change and will not be affected by occlusion, interference, etc. The mobile robot R3 makes the scanner C in a position convenient for scanning the calibration ball, and records the position of the R3 robot in its base coordinate system at this time. and tool coordinate system The position matrix under In addition, the eye-outside-hand calibration result matrix of the R1 robot and scanner C is defined as for:

[0079]

[0080] Step 1.2.2: Move the polishing robot R1 so that the calibration ball is within the field of view of the scanner C and collect the point cloud data P C’ , and record the grinding robot R1 in its base coordinate system and tool coordinate system The coordinate value of

[0081] Step 1.2.3: Repeat step 1.2.2 until four sets of polishing robot R1 poses are obtained. And the point cloud collected by scanner C in the corresponding posture And ensure that the following requirements are met:

[0082] ① These four groups of grinding robot postures The quantities vary, and The quantities are the same, that is

[0083]

[0084] ②These four groups of grinding robot postures The weight difference between the two weights should be as large as possible and not less than 5mm, that is,

[0085]

[0086] ③Point cloud collected by scanner C It should be ensured that: each point cloud contains half a complete and independent spherical point cloud without interference, that is, it can be finally cropped into an independent hemispherical point cloud; the spherical point cloud is uniform and smooth, without large noise data.

[0087] Step 1.2.4: Repeat step 1.2.3 until six sets of polishing robot poses are obtained. And the point cloud collected by scanner C in the corresponding posture And ensure that the following requirements are met:

[0088] ① These six groups of robot postures The quantities vary, i.e.

[0089]

[0090] ②These four groups of robot postures The difference between the weights should be as large as possible and not less than 5mm; the four groups of robot postures The difference between the two components should be as large as possible and not less than 5°, that is,

[0091]

[0092] ③Point cloud collected by scanner C It should be ensured that: each point cloud contains half a complete and independent spherical point cloud without interference, that is, it can be finally cropped into an independent hemispherical point cloud; the spherical point cloud is uniform and smooth, without large noise data.

[0093] Step 1.2.5: Point cloud collected by scanner C Perform filtering and cropping. If the number of points in the point cloud exceeds the set value, additional downsampling is performed to obtain a post-processed point cloud containing only the calibration sphere point cloud.

[0094] Step 1.2.6: Exploit and point cloud Calculate the hand-eye calibration matrix Quantity; and use Quantity and and point cloud Calculate the hand-eye calibration matrix Component, that is, the hand-eye calibration matrix

[0095] Step 1.2.7: Use the obtained hand-eye calibration matrix to and point cloud The 10 hemispherical point clouds in the scanner C coordinate system are calculated and merged into the complete spherical point cloud in the robot R1 coordinate system, that is,

[0096]

[0097] in, It is the complete spherical point cloud in the robot R1 coordinate system;

[0098] Step 1.2.8: Complete sphere point cloud in the robot R1 coordinate system Do spherical fitting and get the fitting radius RMS error According to the given calibration ball detection report, the measured radius of the calibration ball Get the fitting radius error For:

[0099]

[0100] To eliminate accidental errors, take the average of multiple fittings, and ensure that the evaluation unit is mm, to get the final average fitting radius error And the average root mean square error The qualified calibration result should meet the following requirements:

[0101]

[0102] If not, repeat steps 1.2.1-1.2.7 until the requirements are met, and get the final R1 robot and scanner C eye-to-hand calibration result matrix

[0103] Step 1.3: Perform the eye-to-hand calibration of the polishing robot R2 and the scanner C, the process is the same as the eye-to-hand calibration of the polishing robot R1 and the scanner C in step 1.2, where the robot R3 is in the same position as in step 1.2.1, which is The eye-to-hand calibration result matrix of the polishing robot R2 and the scanner C is

[0104] Step 2: Perform the calibration of the workpiece base coordinate system in robots R1, R2, and get the workpiece base coordinate system matrix in robots R1, R2

[0105] Step 2.1: Calibrate the workpiece base coordinate system in the polishing robot R1, and the calibration process is carried out according to the standard process specified by the robot used, and the calibration result is the workpiece base coordinate system matrix in the polishing robot R1

[0106] Step 2.2: Calibrate the workpiece base coordinate system in the polishing robot R2, and the calibration process is carried out according to the standard process specified by the robot used, and the calibration result is the workpiece base coordinate system matrix in the polishing robot R2

[0107] Step 3: Perform the basic application phase. Based on the multiple calibration result matrices obtained from the calibration of the grinding and polishing system in the preparation phase of step 1, obtain the actual workpiece point cloud data and the corresponding robot R3 pose, and calculate the workpiece base coordinate system matrix using visual calibration under robots R1 and R2. If the grinding and polishing system does not require high accuracy for visual calibration, or the accuracy of the scanner and hand-eye calibration is high enough, then only the operating procedures of the "basic application phase" need to be used to obtain workpiece positioning results that meet the requirements.

[0108] Step 3.1: Summarize the data of the grinding and polishing system calibration phase: It is known that the calibration result matrix of the robot R3 and scanner C is It is known that the calibration matrix of robot R1 and scanner C with eyes outside the hand is It is known that the calibration matrix of robot R2 and scanner C with eyes outside the hand is It is known that when robots R1 and R2 perform eye-in-hand external calibration with scanner C, the pose matrix of robot R3 is It is known that the workpiece base coordinate system matrix calibrated by digital model under robot R1 is The workpiece base coordinate system matrix calibrated by digital model under robot R2 is:

[0109] Step 3.2: Based on the data collected in step 3.1, calculate the position transfer matrix from robot R3 to robot R1 during calibration for:

[0110]

[0111] Similarly, the position transfer matrix from robot R3 to robot R2 during calibration is for:

[0112]

[0113] Obviously, the relative position relationship between robots R1, R2, and R3 remains unchanged. Therefore, at any time, the position transfer moment from the transport and measurement robot to the polishing robot is equal to the position transfer matrix from the transport and measurement robot to the polishing robot during calibration, that is:

[0114]

[0115] in, is the position transfer moment from robot R3 to robot R1 at any time, is the position transfer moment from robot R3 to robot R2 at any time;

[0116] Step 3.3: Acquire the actual workpiece point cloud data and the corresponding robot R3 pose, convert the workpiece point cloud data from the scanner coordinate system to the robot coordinate system, obtain the workpiece base coordinate system matrix using visual calibration under robots R1 and R2, and realize the positioning of the workpiece. The process is as follows:

[0117] Step 3.3.1: Maintain the same clamping method for the workpiece during actual machining as during calibration, and keep the worktable at the same initial angle. Ensure that both robots R1 and R2 are moved to a safe position so that robot R3 does not interfere with either robot R1 or R2 during movement.

[0118] Step 3.3.2: Move robot R3 to a certain position p, and scanner C collects point cloud data at this position, ensuring that the point cloud data can cover a local plane or curved surface of the workpiece. Where each point in the point cloud data is V = (x, y, z), then there is a corresponding point cloud P = {V};

[0119] Step 3.3.3: Repeat step 3.3.2 until N point cloud data are obtained The corresponding robot R3 position p n , n=1,…,N, and record the robot R3 pose matrix of the corresponding position Ensure that the point cloud at these N positions can basically cover all the spatial information within the machining flow channels of several workpieces;

[0120] Step 3.3.4: Summarize the actual scanning process obtained in step 3.3.3, during which the robot R3 is located at point p n The pose matrix The workpiece point cloud corresponding to the scanner C coordinate system Calculate the position transfer matrix from robot R1 to scanner C during the actual scanning process for:

[0121]

[0122] Similarly, the position transfer matrix from robot R2 to scanner C during the actual scanning process is for:

[0123]

[0124] Further calculation shows that the workpiece point cloud under robot R1 during the actual scanning process is:

[0125]

[0126] Similarly, the workpiece point cloud under robot R2 during the actual scanning process is:

[0127]

[0128] Step 3.3.5: The point cloud of the local workpiece under robot R1 is obtained by filtering and cutting the point cloud of the workpiece under robot R1 acquired in the actual scanning process, and is represented as

[0129]

[0130] Similarly, the point cloud of the local workpiece under robot R2 is represented as

[0131]

[0132] wherein, represents the result of filtering and cutting the original point cloud V, and the cutting method is to retain only the effective matching point cloud and delete the noise points and external interference.

[0133] Step 3.3.6: Obtain the point cloud of the workpiece model Combine the workpiece base coordinate system calibrated under robot R1 The calibrated workpiece model point cloud under robot R1 is calculated as:

[0134]

[0135] Similarly, the calibrated workpiece model point cloud under robot R2 is:

[0136]

[0137] Step 3.3.7: Apply the ICP algorithm to calculate the transfer matrix of the point cloud of the local workpiece under robot R1 offset to the calibrated workpiece model point cloud under robot R1, which is represented as

[0138]

[0139] Similarly, the transfer matrix of the point cloud of the local workpiece under robot R2 offset to the calibrated workpiece model point cloud under robot R2 is represented as

[0140]

[0141] Step 3.3.8: Finally, the workpiece base coordinate system matrix calibrated by vision under robot R1 is calculated as

[0142]

[0143] Similarly, the workpiece base coordinate system matrix calibrated by vision under robot R2 is represented as

[0144]

[0145] The workpiece base coordinate system matrix calibrated by vision under robot R1 and robot R2, respectively Positioning of the workpiece is realized.

[0146] In this embodiment, if the accuracy required by the vision calibration of the grinding and polishing system is very high, or the accuracy of the scanner and the hand-eye calibration is not high, the operation process of "extended application stage 1" is still needed to compensate for the error of the workpiece base coordinate system matrix obtained by the vision calibration in step 2, so as to improve the positioning accuracy and achieve the required workpiece positioning result. This is an optional function after step 1-3 is completed.

[0147] 1) In the preparation stage, when the base coordinate system of the workpiece is calibrated under the robots R1 and R2 in step 1.6, the workpiece is ensured to be in the initial position, and the actual workpiece point cloud data and the corresponding robot R3 pose are obtained in step 3.3 of the basic application stage;

[0148] 2) The results in 1) are operated in steps 3.4 to 3.7 of the basic application stage to obtain the transfer matrix of the local workpiece point cloud of the workpiece at the calibration position under the robot R1 to the calibration workpiece digital model point cloud under the robot R1 and the transfer matrix of the local workpiece point cloud of the workpiece at the calibration position under the robot R2 to the calibration workpiece digital model point cloud under the robot R2; and the comprehensive error of the workpiece base coordinate system matrix of the workpiece at the calibration position under the robot R1 by vision calibration and the workpiece base coordinate system matrix of the workpiece at the calibration position under the robot R1 by digital model calibration is:

[0149]

[0150] Similarly, the comprehensive error of the workpiece base coordinate system matrix of the workpiece at the calibration position under the robot R2 by vision calibration and the workpiece base coordinate system matrix of the workpiece at the calibration position under the robot R2 by digital model calibration is:

[0151]

[0152] Wherein, the subscript calib represents that the data is only valid for the data of the workpiece at the calibration position;

[0153] 3) In the actual application process, the step 3.2 is defaulted as a known quantity. After completing the entire process of the grinding and polishing system calibration to step 3.7, the workpiece base coordinate system matrix of the workpiece at the calibration position under the robot R1 by vision calibration is calculated as:

[0154]

[0155] Similarly, the workpiece base coordinate system matrix of the workpiece at the calibration position under the robot R2 by vision calibration is calculated as:

[0156]

[0157] In this embodiment, when the bias of the workpiece is too large, the influence of the change of the workpiece coordinate system and the interference between the tool and the workpiece need to be considered. When the tool movement path is complex or the internal allowance of the workpiece is small, the correction amount of part of the matrix can be discarded, and the turntable control can be introduced to perform approximate compensation of the workpiece coordinate system. This is an optional function after the completion of the calibration of the grinding and polishing system, the basic application stage and the first extended application stage, and is for the second extended application stage.

[0158] (1) The comprehensive error of the workpiece coordinate system matrix calibrated by vision under robot R1 and the workpiece coordinate system matrix calibrated by numerical model under robot R1 and the transfer matrix of the point cloud of the local workpiece under robot R1 to the numerical model point cloud of the calibration workpiece under R1 in step 3.7 of the basic application stage in the actual application process The correction matrix under robot R1 is calculated as :

[0159]

[0160] Similarly, the correction matrix under robot R2 is calculated as :

[0161]

[0162] (2) The correction matrix under robot R1 is converted into a Cartesian coordinate recognizable by the robot as

[0163]

[0164] Similarly, the correction matrix under robot R2 is converted into a Cartesian coordinate recognizable by the robot as

[0165]

[0166] Wherein, a, b, c are the rotation components around z, y, x directions respectively.

[0167] (3) The turntable is compensated and rotated according to the correction coordinates under robot R1 and robot R2, that is, the compensation rotation angle of the turntable is calculated as

[0168]

[0169] Wherein, is(up) = 1 indicates that the workpiece is in the front surface during processing, and is(up) = 0 indicates that the workpiece is in the back surface during processing.

[0170] In this embodiment, based on the workpiece adaptive positioning compensation method for multi-robot cooperative grinding and polishing of the application, the grinding and polishing system process is as shown in the figure, specifically: Figure 5

[0171] S1: Complete the hand-eye calibration of robots R1, R2, R3 and scanner c, and complete the base coordinate system calibration of robots R1 and R2 using the workpiece numerical model.

[0172] S2: When the workpiece is at the calibration position, move robot R3 to collect a number of point clouds and save the corresponding positions. Using the calibration results of S1, the comprehensive error matrix of R1 and R2 is calculated.

[0173] S3: When the workpiece is in the production state, i.e., after secondary clamping, move R3 robot according to the position in S2 to collect point clouds. Using the results of S1 and S2, the compensation angle of the corrected base coordinate system and the rotary table in the coordinate system of robots R1 and R2 is calculated.

[0174] S4: If there is no interference phenomenon, the corrected base coordinate system of robots R1 and R2 can be transmitted to the robot program, and the saved base coordinate system is modified by the robot program. If there is an interference phenomenon, the compensation angle is transmitted to the robot program, the rotary table is rotated to complete the compensation correction by the robot program, and then the polishing process is performed.

[0175] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the application, and not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent substitutions for part or all of the technical features; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the scope defined by the claims of the application.​

Claims

1. A workpiece adaptive positioning compensation method for multi-robot collaborative grinding and polishing, characterized by: The scanning device connected to the handling and measuring robot in the grinding and polishing system completes the acquisition of the workpiece point cloud for positioning compensation calculation, which specifically includes the following steps: Step 1: Perform eye-on-hand and eye-off-hand calibration on the handling and measurement robot, multiple polishing robots, and scanning devices in the polishing system to obtain the eye-on-hand calibration result matrix and the eye-off-hand calibration result matrix; Step 2: Calibrate the base coordinate system of the workpiece under the grinding robot to obtain the base coordinate system matrix of the workpiece in the grinding robot coordinate system; Step 3: Based on the multiple calibration result matrices obtained in step 1 and the base coordinate system matrix of the workpiece in the grinding robot coordinate system obtained by calibration in step 2, the actual workpiece point cloud data and the corresponding handling and measurement robot posture are acquired, and the base coordinate system matrix of the workpiece using visual calibration in multiple grinding robot coordinate systems is calculated to achieve workpiece positioning; Step 3.1: Based on the multiple calibration result matrices obtained in step 1 and the base coordinate system matrix of the workpiece in the grinding robot coordinate system obtained by calibration in step 2, calculate the position transfer matrix from the transport measurement robot to the grinding robot during calibration; Step 3.2: Obtain the workpiece point cloud data and the corresponding handling and measurement robot pose during the actual processing process, and convert the workpiece point cloud data from the scanning device coordinate system to the polishing robot coordinate system; Step 3.3: Obtain the workpiece base coordinate system matrix using visual calibration under the grinding robot to achieve workpiece positioning; The method further performs error compensation on the workpiece base coordinate system matrix obtained by visual calibration in step 3, including: 1) When calibrating the base coordinate system of the workpiece in the polishing robot coordinate system in step 2, ensure that the workpiece is in the initial position, obtain the actual workpiece point cloud data and the corresponding handling and measurement robot posture; 2) Perform the calculations from steps 3.2 to 3.3 on the actual workpiece point cloud data obtained in 1) and the corresponding handling and measurement robot posture to obtain the transfer matrix from the point cloud of the local workpiece under the grinding robot at the calibrated position to the digital model point cloud of the calibrated workpiece under the grinding robot; then calculate the combined error between the workpiece base coordinate system matrix calibrated by visual calibration under the grinding robot at the calibrated position and the workpiece base coordinate system matrix calibrated by digital model under the grinding robot; 3) Use the workpiece base coordinate system matrix calculated in step 3.3 of the comprehensive error correction step to calibrate the workpiece using vision under the grinding robot; The method also introduces turntable control to perform approximate compensation of the workpiece base coordinate system, including: (1) Based on the comprehensive error between the workpiece base coordinate system matrix calibrated by vision in the grinding robot coordinate system at the calibrated position and the workpiece base coordinate system matrix calibrated by digital model in the grinding robot coordinate system, and the transfer matrix of the local workpiece point cloud in the grinding robot coordinate system offset to the digital model point cloud of the calibrated workpiece in the grinding robot coordinate system during the actual processing process, the correction matrix in the grinding robot coordinate system is calculated; (2) Convert the calculated correction matrix in the grinding robot coordinate system into a Cartesian correction coordinate that can be recognized by the robot; (3) The turntable in the polishing system is rotated according to the Cartesian correction coordinates in the polishing robot coordinate system to process the workpiece, that is, the compensation rotation angle of the turntable is calculated.

2. The method for adaptive positioning compensation of a workpiece for multi-robot collaborative grinding and polishing according to claim 1, characterized in that: During the actual machining process, the relative position relationship between the transport and measurement robot and the multiple polishing robots remains unchanged. Therefore, at any time, the position transfer moment from the transport and measurement robot to the polishing robot is equal to the position transfer matrix from the transport and measurement robot to the polishing robot during calibration.

3. The method for adaptive positioning compensation of a workpiece for multi-robot collaborative grinding and polishing according to claim 1, characterized in that: The step 3.2 includes: Step 3.2.1: Ensure that the workpiece clamping method during the actual machining process is consistent with that during calibration, and that the worktables in the grinding and polishing system are at the same initial angle. Ensure that all grinding robots are moved to a safe position so that the handling and measuring robot does not interfere with the grinding robot during movement. Step 3.2.2: Move the measurement robot to a certain location , the scanning device collects the point cloud data of the workpiece at that position, ensuring that the point cloud data can cover a certain plane or curved surface of the workpiece; wherein each point of the point cloud data is , then there is a corresponding point cloud ; Step 3.2.3: Repeat step 3.2.2 until you get Point cloud data collected by scanning equipment Corresponding transport measurement robot position , point cloud data The superscript C in the figure indicates the scanning device, and records the position matrix of the handling measurement robot at the corresponding position; The point cloud at each position can basically cover all the spatial information in the processing flow channel of several workpieces; Step 3.2.4: Summarize the actual position of the transport measurement robot during the scanning process of the scanning device obtained in step 3.2.3 The pose matrix and the workpiece point cloud data in the corresponding scanning device coordinate system , In order to transfer the position of the nth point cloud data collected by the scanning device at position p of the handling measurement robot, the position transfer matrix from the polishing robot to the scanning device during the actual scanning process is calculated; further, the workpiece point cloud in the polishing robot coordinate system during the actual scanning process is calculated.

4. The method for adaptive positioning compensation of a workpiece for multi-robot collaborative grinding and polishing according to claim 3, characterized in that: The step 3.3 includes: Step 3.3.1: Filter and crop the N workpiece point clouds acquired in the actual scanning process in the polishing robot coordinate system and then merge them to obtain a point cloud of the local workpiece in the polishing robot coordinate system; Step 3.3.2: Obtain the workpiece digital model point cloud, and calculate the calibrated workpiece digital model point cloud in the polishing robot coordinate system by combining it with the workpiece base coordinate system calibrated in the polishing robot coordinate system; Step 3.3.3: Apply the ICP algorithm to calculate the transfer matrix from the point cloud of the local workpiece in the grinding robot coordinate system to the digital model point cloud of the calibrated workpiece in the grinding robot coordinate system; Step 3.3.4: Based on the transfer matrix of the point cloud of the local workpiece in the polishing robot coordinate system offset to the digital model point cloud of the calibrated workpiece in the polishing robot coordinate system and the workpiece base coordinate system matrix calibrated by the digital model in the polishing robot coordinate system, the workpiece base coordinate system matrix calibrated by vision in the polishing robot coordinate system is calculated; the polishing robot uses the workpiece base coordinate system matrix calibrated by vision to realize the positioning of the workpiece.

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