A method, system and equipment for synchronous calibration of a dual-robot collaborative system

Abstract

This invention discloses a synchronous calibration method, system, and device for a dual-robot collaborative system, relating to the field of robotics. The method involves manipulating the two robots to move and collecting first pose data; constructing a rotation component closed-loop solution model and a translation vector closed-loop solution model based on a set of identities; inputting the first pose data into the rotation closed-loop solution model to obtain an estimated value of the second pose data; inputting the estimated values ​​of the first and second pose data into the translation vector closed-loop solution model to obtain an estimated value of the third pose data; constructing an objective function based on the estimated values ​​of the second and third pose data and the first pose data; iteratively optimizing the objective function until a preset number of iterations is reached to obtain accurate values ​​of the second and third pose data; and calibrating the two robots based on the accurate values ​​of the second and third pose data.

Description

Technical Field

[0001] This invention relates to the field of robotics, and in particular to a method, system, and device for synchronous calibration of a dual-robot collaborative system. Background Technology

[0002] Multi-robot collaborative systems typically refer to swarms of robots designed to accomplish complex tasks or tasks that a single robot cannot perform. Compared to a single robot, multi-robot systems can perform more collective actions in a distributed manner, offering greater efficiency, flexibility, and simplicity in design. Given these advantages, multi-robot systems have been widely applied in agriculture, industry, healthcare, and social services. However, due to the high precision and reliability requirements of multi-robot systems, their application in manufacturing still faces many challenges.

[0003] Multi-robot systems are typically decomposed into multiple dual-robot systems for research. Currently, calibration methods for dual-robot collaborative systems can be categorized into two types: step-by-step calibration methods and synchronous calibration methods. Step-by-step calibration is a non-synchronous calibration method based on the equations AX=XB or AX=YB, which can be further refined into two-step and three-step calibration methods. Although the above calibration process can be completed step-by-step, independently estimating coordinate system relationships leads to uncertainty and inconsistency in the global perspective of the robot collaborative system. Synchronous calibration, on the other hand, is a multi-coordinate system joint estimation method based on the equation AXB=YCZ, which can effectively avoid error propagation and accumulation during step-by-step calibration. Furthermore, compared to one robot remaining static while the other is calibrating, having both robots participate in the calibration process simultaneously improves the utilization of sample data, making the entire calibration process more efficient. However, most existing synchronous calibration theories are designed for binocular vision physical scenarios and are not applicable to monocular vision physical scenarios, such as line laser scanners. Therefore, proposing a more general synchronous calibration method for dual-robot collaborative systems is particularly urgent. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, and device for synchronous calibration of a dual-robot collaborative system, which can be applied to dual-robot calibration in more physical scenarios.

[0005] To achieve the above objectives, the present invention provides the following solution: A synchronous calibration method for a dual-robot collaborative system is applied to a dual-robot collaborative device, which includes: a control system, a measuring robot, a processing robot, a vision measurement system, and a marking device; The control system is connected to the measuring robot, the processing robot, and the vision measurement system respectively; the vision measurement system is located on the end flange of the measuring robot, and the marking device is located on the end flange of the processing robot; the vision measurement system includes two industrial cameras; the marking device includes a calibration plate; The synchronous calibration method for the dual-robot collaborative system includes: The system operates two robots to move and collect first pose data. The two robots include a measuring robot and a machining robot. The measuring robot is equipped with a measuring robot base coordinate system, a measuring robot end flange coordinate system, and a vision measurement system coordinate system. The machining robot is equipped with a machining robot base coordinate system, a machining robot end flange coordinate system, and a marking device coordinate system. Based on a set of identities, a closed-loop solution model for rotational components and a closed-loop solution model for translational vectors are constructed. The first pose data is input into the rotational closed-loop solution model to obtain the estimated value of the second pose data; The estimated values ​​of the first pose data and the second pose data are input into the translation vector closed-loop solution model to obtain the estimated value of the third pose data. Construct an objective function based on the estimated values ​​of the second pose data, the estimated values ​​of the third pose data, and the first pose data; The objective function is iteratively optimized until a preset number of iterations is reached, to obtain the accurate values ​​of the second pose data and the third pose data; The dual robots are calibrated based on the accurate values ​​of the second and third pose data.

[0006] Optionally, the first pose data includes rotation matrices of homogeneous transformation between multiple sets of measurement robot base coordinate systems and measurement robot end flange coordinate systems, translation vectors of homogeneous transformation between multiple sets of measurement robot base coordinate systems and measurement robot end flange coordinate systems, rotation matrices of homogeneous transformation between multiple sets of calibration plate coordinate systems and vision measurement system coordinate systems, translation vectors of homogeneous transformation between multiple sets of calibration plate coordinate systems and vision measurement system coordinate systems, rotation matrices of homogeneous transformation between multiple sets of machining robot base coordinate systems and machining robot end flange coordinate systems, and translation vectors of homogeneous transformation between multiple sets of machining robot base coordinate systems and machining robot end flange coordinate systems. The second pose data includes the rotation matrix of the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system, the rotation matrix of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot, and the rotation matrix of the homogeneous transformation between the coordinate system of the calibration plate and the coordinate system of the end flange of the machining robot. The third pose data includes the translation vector of the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system, the translation vector of the homogeneous transformation between the coordinate system of the calibration plate and the coordinate system of the end flange of the machining robot, and the translation vector of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot.

[0007] Optionally, the two robots are manipulated to move, and the first pose data is collected, specifically including: The operation involves moving the measuring robot and the processing robot while ensuring that the marking device is within the effective field of view of the vision measurement system. This involves changing the relative pose of the vision measurement system and the marking device, and recording multiple sets of first sub-pose data. The first sub-pose data includes the rotation matrix of the homogeneous transformation between the measuring robot's base coordinate system and the measuring robot's end flange coordinate system, the translation vector of the homogeneous transformation between the measuring robot's base coordinate system and the measuring robot's end flange coordinate system, the rotation matrix of the homogeneous transformation between the processing robot's base coordinate system and the processing robot's end flange coordinate system, the translation vector of the homogeneous transformation between the processing robot's base coordinate system and the processing robot's end flange coordinate system, and the translation vector of the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system. The operation of the measuring robot and the processing robot ensures that the marking device is within the effective field of view of the vision measurement system and that the end flange poses of the measuring robot and the processing robot remain unchanged. The relative positions of the vision measurement system and the marking device are changed, and multiple sets of second sub-pose data are recorded. The second sub-pose data includes the translation vector of the homogeneous transformation between the base coordinate system of the measuring robot and the end flange coordinate system of the measuring robot, the translation vector of the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system, and the translation vector of the homogeneous transformation between the base coordinate system of the processing robot and the end flange coordinate system of the processing robot. Pose data is constructed based on multiple sets of first sub-pose data and multiple sets of second sub-pose data.

[0008] Optionally, the set of identities is: ; in, The rotation matrix represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot; The rotation matrix represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The rotation matrix represents the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; The rotation matrix represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The rotation matrix represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; The rotation matrix represents the homogeneous transformation between the calibration plate coordinate system and the end flange coordinate system of the machining robot; The translation vector represents the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; The translation vector represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot. The translation vector represents the homogeneous transformation between the calibration plate coordinate system and the end flange coordinate system of the machining robot. The translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot. The translation vector represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot.

[0009] Optionally, the closed-loop solution model for the rotational component is: ; ; ; in, Indicates the first parameter; Indicates the second parameter; The first step represents the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system. j Group translation vectors; ; A Indicates including j A set; The first homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system represents the first homogeneous transformation. i Group translation vectors; ; B Indicates including i A set; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... Group rotation matrix; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... j Group translation vectors; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... i Group translation vectors; Represents a 3x3 identity matrix; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... i Group translation vectors; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... j Group translation vectors; The estimated value of the rotation matrix represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The estimated value of the rotation matrix representing the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The inverse operator for matrix vectorization.

[0010] Optionally, the closed-loop solution model for the translation vector is: ; ; ; Where J represents the third parameter; c represents the fourth parameter; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... Group rotation matrix; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... k Group translation vectors; ; K express A and B The union of sets; The first homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system represents the first homogeneous transformation. k Group translation vectors; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... k Group translation vectors; This represents an estimate of the translation vector representing the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system. This represents the estimated value of the translation vector for the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot. This represents the estimated translation vector of the homogeneous transformation between the end flange coordinate system and the calibration plate coordinate system of the machining robot.

[0011] Optionally, the objective function is: ; in, The Lie algebraic form corresponding to the estimated value of the rotation matrix representing the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The Lie algebraic form corresponding to the rotation matrix estimate of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The translation vector represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The translation vector represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The translation vector represents the homogeneous transformation between the coordinate system of the end flange of the machining robot and the coordinate system of the calibration plate; Indicates the number of sampled data; This represents the fifth parameter.

[0012] A computer system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described synchronous calibration method for a dual-robot cooperative system.

[0013] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the synchronous calibration method for a dual-robot collaborative system as described above.

[0014] Optionally, the memory is a non-transitory computer-readable storage medium.

[0015] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects: This invention discloses a method, system, and device for synchronous calibration of a dual-robot collaborative system. The method involves manipulating the two robots to move and collecting first pose data. Based on the first pose data, estimated values ​​for the second and third pose data are determined. An objective function is then constructed based on these estimated values ​​and the first pose data. The objective function is iteratively optimized to obtain precise values ​​for the second and third pose data, and the dual robots are calibrated accordingly. This invention is applicable to dual-robot calibration in a wider range of physical scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of the synchronous calibration method for a dual-robot collaborative system provided by the present invention; Figure 2 This is a schematic diagram of the dual-robot collaborative device provided by the present invention; Figure 3A first schematic diagram of the visual measurement system and marking device provided by the present invention; Figure 4 A second schematic diagram of the visual measurement system and marking device provided by the present invention; Figure 5 This is a schematic diagram of the synchronous calibration method for a dual-robot collaborative system provided by the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] The purpose of this invention is to provide a synchronous calibration method, system and equipment for a dual-robot collaborative system, which solves the inherent drawbacks of error propagation, accumulation and low efficiency in the existing step-by-step calibration process. On the other hand, the proposed calibration theory directly addresses the challenges of poor interoperability and compatibility of existing synchronous calibration theories, taking into account accuracy while pursuing universality in more physical scenarios.

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] This invention discloses a synchronous calibration method for a dual-robot collaborative system, applicable to a dual-robot collaborative device. The dual-robot collaborative device includes: a control system, a measuring robot 1, a processing robot 4, a vision measurement system 2, and a marking device 3. Figure 2 As shown.

[0022] like Figure 2 As shown, the control system is connected to the measuring robot 1, the processing robot 4 and the vision measurement system 2 respectively; the vision measurement system 2 is set on the end flange of the measuring robot 1 and the marking device 3 is set on the end flange of the processing robot 4.

[0023] The measuring robot 1 has a vision measurement system 2 fixed to its end flange, which drives the sensor to move.

[0024] The processing robot 4 has a marking device 3 fixed to its end flange and moves the marking device.

[0025] The control system is communicatively connected to the measuring robot 1, the processing robot 4, and the vision measurement system 2, respectively.

[0026] like Figure 4As shown, the vision measurement system includes two industrial cameras 12; the marking device includes a calibration plate 14. The focal points of the two industrial cameras 12 are located at a point on the calibration plate 14. The calibration plate 14 is a checkerboard calibration plate, but as a variation, other types of calibration plates with checkerboard texture information can also be used.

[0027] like Figure 3 As shown, the present invention also provides another combination of a vision measurement system and a marking device, wherein the vision measurement system includes a line laser sensor 11 and an industrial camera 12; and the marking device includes a standard ball 13, both of which remain stationary in spatial orientation.

[0028] like Figure 1 As shown, the synchronous calibration method for the dual-robot collaborative system includes: Step 101: Operate the dual-robot motion to collect the first pose data. The dual robots include a measuring robot and a processing robot; for example... Figure 1 As shown, the measuring robot is equipped with a measuring robot base coordinate system 5, a measuring robot end flange coordinate system 6, and a vision measurement system coordinate system 9; the machining robot is equipped with a machining robot base coordinate system 7, a machining robot end flange coordinate system 8, and a marking device coordinate system 10; the pose data includes the end flange pose information of the measuring robot, the end flange pose information of the machining robot, and the pose information of the marking device coordinate system in the vision measurement system coordinate system.

[0029] The first pose data includes rotation matrices for homogeneous transformations between multiple sets of measurement robot base coordinate systems and measurement robot end flange coordinate systems, translation vectors for homogeneous transformations between multiple sets of measurement robot base coordinate systems and measurement robot end flange coordinate systems, rotation matrices for homogeneous transformations between multiple sets of calibration plate coordinate systems and vision measurement system coordinate systems, translation vectors for homogeneous transformations between multiple sets of calibration plate coordinate systems and vision measurement system coordinate systems, rotation matrices for homogeneous transformations between multiple sets of machining robot base coordinate systems and machining robot end flange coordinate systems, and translation vectors for homogeneous transformations between multiple sets of machining robot base coordinate systems and machining robot end flange coordinate systems.

[0030] In a collaborative dual-robot system, pose transformation relationships exist between the coordinate frames, including: hand-eye pose transformation relationship (R... X and t X Pose transformation between the end flange and the base coordinate system in a machining robot (R) B and t B ), pose transformation between the end flange and the base coordinate system in a measuring robot (R) A and t A ), pose transformation between frames in dual robot base coordinate systems (R) Y and t Y) and pose transformation between the end flange-marker coordinate system frame of the machining robot (R Z and t Z ).

[0031] The pose transformation between the end flange and base coordinate system in both the measuring robot and the machining robot can be directly obtained from the robot control system, with the calibration model being a known constant matrix.

[0032] The pose transformations between the hand-eye coordinate system frames, the pose transformations between the dual-robot base coordinate system frames, and the pose transformations between the end flange-marker coordinate system frames of the machining robot are all unknown constant matrices to be calibrated.

[0033] When using a matte-finish standard sphere as the marking device, and selecting the center spatial coordinates as the origin of the marker coordinate system frame, the pose information of the marking device coordinate system in the visual measurement system coordinate system is obtained as follows: The coordinates of the center of the circle intercepted by the laser line can be calculated from the pixel coordinates of the laser line in the image captured by the tool camera. The spatial position of the center of the sphere in the coordinate system of the visual measurement system. The calculation formula is as follows: in, This represents the radius of a standard sphere.

[0034] The operation involves moving the measuring robot and the processing robot while ensuring that the marking device is within the effective field of view of the vision measurement system. This involves changing the relative pose of the vision measurement system and the marking device, and recording multiple sets of first sub-pose data. The first sub-pose data includes the rotation matrix of the homogeneous transformation between the measuring robot's base coordinate system and the measuring robot's end flange coordinate system, the translation vector of the homogeneous transformation between the measuring robot's base coordinate system and the measuring robot's end flange coordinate system, the rotation matrix of the homogeneous transformation between the processing robot's base coordinate system and the processing robot's end flange coordinate system, the translation vector of the homogeneous transformation between the processing robot's base coordinate system and the processing robot's end flange coordinate system, and the translation vector of the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system.

[0035] Manipulate the dual-robot motion to change the relative pose of the vision sensor and the marking device, ensuring the marking device remains within the effective field of view of the vision sensor, and record the pose information R of the dual-robot end flange. A[i] R B[i] t A[i] t B[i] And the representation of the calibration device coordinate frame in the vision sensor coordinate system R C[i] t C[i] .

[0036] The operation of the measuring robot and the processing robot ensures that the marking device is within the effective field of view of the vision measurement system and that the end flange poses of the measuring robot and the processing robot remain unchanged. The relative positions of the vision measurement system and the marking device are changed, and multiple sets of second sub-pose data are recorded. The second sub-pose data includes the translation vector of the homogeneous transformation between the base coordinate system of the measuring robot and the end flange coordinate system of the measuring robot, the translation vector of the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system, and the translation vector of the homogeneous transformation between the base coordinate system of the processing robot and the end flange coordinate system of the processing robot.

[0037] Keeping the dual robot end flanges in the same orientation, only changing their relative positions, the pose information t is recorded again. A[j] t B[j] and t C[j] This completes the collection of a set of sample data.

[0038] Repeat the above process to collect several sets of pose data.

[0039] Pose data is constructed based on multiple sets of first sub-pose data and multiple sets of second sub-pose data.

[0040] like Figure 5 As shown, firstly, the end positions and orientations of the measuring robot and the processing machine are changed simultaneously. Secondly, only the end positions of the two robots are changed (with the orientation unchanged). The poses of the end flanges of the two robots after the two changes and the pose description of the marking module in the vision sensor are recorded respectively. The above process is repeated to collect several sets of sample data.

[0041] like Figure 1 As shown, step 102: Construct a closed-loop solution model for the rotation component and a closed-loop solution model for the translation component based on the set of identities.

[0042] The set of identities is as follows: ; in, The rotation matrix represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot; The rotation matrix represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The rotation matrix represents the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; The rotation matrix represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The rotation matrix represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; The rotation matrix represents the homogeneous transformation between the calibration plate coordinate system and the end flange coordinate system of the machining robot; The translation vector represents the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; The translation vector represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot. The translation vector represents the homogeneous transformation between the calibration plate coordinate system and the end flange coordinate system of the machining robot. The translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot. The translation vector represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot.

[0043] like Figure 5 As shown, the estimated values ​​of the rotation matrix between each coordinate system frame are calculated based on the closed-loop solution model of the rotation component.

[0044] like Figure 1 As shown, step 103: Input the first pose data into the rotational closed-loop solution model to obtain the estimated value of the second pose data.

[0045] The second pose data includes the rotation matrix of the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system, the rotation matrix of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot, and the rotation matrix of the homogeneous transformation between the coordinate system of the calibration plate and the coordinate system of the end flange of the machining robot.

[0046] By simultaneously establishing the equations representing the translation components in the system of identities, a closed-loop solution model for the rotational components can be established. This closed-loop solution model for the rotational components is as follows: in, Indicates the first parameter; Indicates the second parameter; The first homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system represents the first homogeneous transformation. j Group translation vectors; ; A Indicates including j A set; The first homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system represents the first homogeneous transformation. i Group translation vectors; ; B Indicates including i A set; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... Group rotation matrix; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... j Group translation vectors; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... i Group translation vectors; Represents a 3x3 identity matrix; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... i Group translation vectors; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... j Group translation vectors; The estimated value of the rotation matrix represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The estimated value of the rotation matrix representing the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The inverse operator for matrix vectorization.

[0047] The closed-loop solution model for the rotational component is a constrained linear model, and its solution... For matrix The eigenvector corresponding to the smallest eigenvalue times.

[0048] like Figure 1 As shown, step 104: Input the estimated values ​​of the first pose data and the second pose data into the translation vector closed-loop solution model to obtain the estimated value of the third pose data.

[0049] like Figure 5 As shown, based on the closed-loop solution model of the translation components and by importing the estimated value of the rotation matrix, the estimated values ​​of the translation components between the coordinate system frames are calculated.

[0050] The closed-loop solution model for the translation vector is as follows: ; ; ; Where J represents the third parameter; c represents the fourth parameter; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... Group rotation matrix; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot represents the... k Group translation vectors; ; K express A and B The union of sets; The first homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system represents the first homogeneous transformation. k Group translation vectors; The first homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot represents the... k Group translation vectors; This represents an estimate of the translation vector representing the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system. This represents the estimated value of the translation vector for the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot. This represents the estimated translation vector of the homogeneous transformation between the end flange coordinate system and the calibration plate coordinate system of the machining robot.

[0051] like Figure 1 As shown, step 105: Construct an objective function based on the estimated values ​​of the second pose data, the estimated values ​​of the third pose data, and the first pose data.

[0052] The Lie algebra corresponding to the estimate of the rotation matrix : in, n and These are the direction vector and rotation angle corresponding to the rotation axis of the rotation matrix, respectively. tr ( ) is the trace operator.

[0053] The objective function is constructed based on the Lie algebra corresponding to the estimated values ​​of the rotation matrices between the coordinate systems in the dual-robot collaborative system, the estimated values ​​of the translation matrices between the coordinate systems in the dual-robot collaborative system, and the pose data.

[0054] in, The Lie algebraic form corresponding to the estimated value of the rotation matrix representing the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The Lie algebraic form corresponding to the rotation matrix estimate of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The translation vector represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The translation vector represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; The translation vector represents the homogeneous transformation between the coordinate system of the end flange of the machining robot and the coordinate system of the calibration plate; Indicates the number of sampled data; This represents the fifth parameter.

[0055] Step 106: Iteratively optimize the objective function until a preset number of iterations is reached to obtain the accurate values ​​of the second pose data and the third pose data.

[0056] like Figure 5 As shown, an optimization objective function for the calibration system is established, and the sample data and estimated initial values ​​are substituted into the optimization model to iterate its corresponding exact solution.

[0057] like Figure 1 As shown, step 107: calibrate the dual robots based on the accurate values ​​of the second pose data and the third pose data.

[0058] Example 2 A computer system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the synchronous calibration method for a dual-robot cooperative system as described in Embodiment 1.

[0059] Example 3 An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the synchronous calibration method for a dual-robot collaborative system as described in Embodiment 1.

[0060] The memory is a non-transitory computer-readable storage medium.

[0061] The technical solution proposed in this invention can achieve the following beneficial effects: On the one hand, compared with existing step-by-step calibration techniques, the proposed scheme can achieve synchronous calibration of multiple coordinate system frames such as basis-basis transformation, hand-eye transformation, and marker-flange transformation, effectively avoiding the propagation and accumulation of calculation errors, and realizing the unification of each coordinate frame of the system from a global perspective.

[0062] On the other hand, the synchronous calibration theory established based on the translation equation in the AXB=YCZ equation has higher interoperability and universality, and can be compatible with various physical scenarios such as binocular / monocular vision.

[0063] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0064] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for synchronous calibration of a dual-robot collaborative system, characterized in that, The synchronous calibration method for the dual-robot collaborative system is applied to a dual-robot collaborative device, which includes: a control system, a measuring robot, a processing robot, a vision measurement system, and a marking device. The control system is connected to the measuring robot, the processing robot, and the vision measurement system respectively; the vision measurement system is located on the end flange of the measuring robot, and the marking device is located on the end flange of the processing robot; the vision measurement system includes two industrial cameras; the marking device includes a calibration plate; The synchronous calibration method for the dual-robot collaborative system includes: The system operates two robots to move and collect first pose data. The two robots include a measuring robot and a machining robot. The measuring robot is equipped with a measuring robot base coordinate system, a measuring robot end flange coordinate system, and a vision measurement system coordinate system. The machining robot is equipped with a machining robot base coordinate system, a machining robot end flange coordinate system, and a marking device coordinate system. Based on a set of identities, a closed-loop solution model for rotational components and a closed-loop solution model for translational vectors are constructed. The first pose data is input into the rotational closed-loop solution model to obtain the estimated value of the second pose data; The estimated values ​​of the first pose data and the second pose data are input into the translation vector closed-loop solution model to obtain the estimated value of the third pose data. Construct an objective function based on the estimated values ​​of the second pose data, the estimated values ​​of the third pose data, and the first pose data; The objective function is iteratively optimized until a preset number of iterations is reached, to obtain the accurate values ​​of the second pose data and the third pose data; The dual robots are calibrated based on the accurate values ​​of the second and third pose data.

2. The synchronous calibration method for a dual-robot collaborative system according to claim 1, characterized in that, The first pose data includes rotation matrices of homogeneous transformation between multiple sets of measurement robot base coordinate systems and measurement robot end flange coordinate systems, translation vectors of homogeneous transformation between multiple sets of measurement robot base coordinate systems and measurement robot end flange coordinate systems, rotation matrices of homogeneous transformation between multiple sets of calibration plate coordinate systems and vision measurement system coordinate systems, translation vectors of homogeneous transformation between multiple sets of calibration plate coordinate systems and vision measurement system coordinate systems, rotation matrices of homogeneous transformation between multiple sets of machining robot base coordinate systems and machining robot end flange coordinate systems, and translation vectors of homogeneous transformation between multiple sets of machining robot base coordinate systems and machining robot end flange coordinate systems. The second pose data includes the rotation matrix of the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system, the rotation matrix of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot, and the rotation matrix of the homogeneous transformation between the coordinate system of the calibration plate and the coordinate system of the end flange of the machining robot. The third pose data includes the translation vector of the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system, the translation vector of the homogeneous transformation between the coordinate system of the calibration plate and the coordinate system of the end flange of the machining robot, and the translation vector of the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot.

3. The synchronous calibration method for a dual-robot collaborative system according to claim 2, characterized in that, The operation involves manipulating the two robots to move and collecting the first pose data, specifically including: The operation involves moving the measuring robot and the processing robot while ensuring that the marking device is within the effective field of view of the vision measurement system. This involves changing the relative pose of the vision measurement system and the marking device, and recording multiple sets of first sub-pose data. The first sub-pose data includes the rotation matrix of the homogeneous transformation between the measuring robot's base coordinate system and the measuring robot's end flange coordinate system, the translation vector of the homogeneous transformation between the measuring robot's base coordinate system and the measuring robot's end flange coordinate system, the rotation matrix of the homogeneous transformation between the processing robot's base coordinate system and the processing robot's end flange coordinate system, the translation vector of the homogeneous transformation between the processing robot's base coordinate system and the processing robot's end flange coordinate system, and the translation vector of the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system. The operation of the measuring robot and the processing robot ensures that the marking device is within the effective field of view of the vision measurement system and that the end flange poses of the measuring robot and the processing robot remain unchanged. The relative positions of the vision measurement system and the marking device are changed, and multiple sets of second sub-pose data are recorded. The second sub-pose data includes the translation vector of the homogeneous transformation between the base coordinate system of the measuring robot and the end flange coordinate system of the measuring robot, the translation vector of the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system, and the translation vector of the homogeneous transformation between the base coordinate system of the processing robot and the end flange coordinate system of the processing robot. Pose data is constructed based on multiple sets of first sub-pose data and multiple sets of second sub-pose data.

4. The synchronous calibration method for a dual-robot collaborative system according to claim 1, characterized in that, The set of identities is as follows: ； Among them, R A R represents the rotation matrix representing the homogeneous transformation between the base coordinate system and the end effector flange coordinate system of the measuring robot; X R represents the rotation matrix representing the homogeneous transformation between the coordinate system of the robot's end effector flange and the coordinate system of the vision measurement system; B R represents the rotation matrix representing the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; Y R represents the rotation matrix representing the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; C R represents the rotation matrix representing the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; Z The rotation matrix representing the homogeneous transformation between the calibration plate coordinate system and the end flange coordinate system of the machining robot; t B The translation vector representing the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; t X The translation vector t represents the homogeneous transformation between the coordinate system of the end effector flange of the measuring robot and the coordinate system of the vision measurement system. A The translation vector t represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot; Z The translation vector t represents the homogeneous transformation between the calibration plate coordinate system and the end flange coordinate system of the machining robot; C The translation vector t represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; Y The translation vector represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot.

5. The synchronous calibration method for a dual-robot collaborative system according to claim 1, characterized in that, The closed-loop solution model for the rotational component is as follows: ； ； ； ； Among them, M ABC Indicates the first parameter; m RXY Indicates the second parameter; t B[j] Let represent the j-th translation vector of the homogeneous transformation between the calibration board coordinate system and the vision measurement system coordinate system; j∈A; A represents the set including j; t B[i] Let represent the i-th translation vector of the homogeneous transformation between the calibration board coordinate system and the vision measurement system coordinate system; i ∈ B; B represents the set including i; R A[i'] The i'-th rotation matrix represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot; t C[j] The j-th translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; t C[i] Ii represents the i-th translation vector of the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; I3 represents the 3x3 identity matrix; t A[i] The t represents the i-th translation vector representing the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot; A[j] The j-th translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot. The estimated value of the rotation matrix represents the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; This represents the estimated value of the rotation matrix for the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot; unvec() represents the inverse operator for matrix vectorization.

6. The synchronous calibration method for a dual-robot collaborative system according to claim 5, characterized in that, The closed-loop solution model for the translation vector is as follows: ； ； ； Where J represents the third parameter; c represents the fourth parameter; R C[i'] The i'-th rotation matrix represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; t C[k] The k-th translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the machining robot; k∈K; K represents the union of A and B; t B[k] The k-th translation vector represents the homogeneous transformation between the calibration plate coordinate system and the vision measurement system coordinate system; t A[k] The k-th translation vector represents the homogeneous transformation between the base coordinate system and the end flange coordinate system of the measuring robot. This represents an estimate of the translation vector representing the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system. This represents the estimated value of the translation vector for the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot. This represents the estimated translation vector of the homogeneous transformation between the end flange coordinate system and the calibration plate coordinate system of the machining robot.

7. The synchronous calibration method for a dual-robot collaborative system according to claim 6, characterized in that, The objective function is: in, The Lie algebraic form corresponding to the estimated value of the rotation matrix representing the homogeneous transformation between the coordinate system of the end flange of the measuring robot and the coordinate system of the vision measurement system; The Lie algebraic form corresponding to the rotation matrix estimate of the homogeneous transformation between the coordinate systems of the measuring robot and the machining robot; t X The translation vector t represents the homogeneous transformation between the coordinate system of the end effector flange of the measuring robot and the coordinate system of the vision measurement system. Y The translation vector t represents the homogeneous transformation between the coordinate system of the measuring robot and the coordinate system of the machining robot. Z n' represents the translation vector of the homogeneous transformation between the coordinate system of the end flange of the machining robot and the coordinate system of the calibration plate; n' represents the number of sampled data. This represents the fifth parameter.

8. A computer system, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the synchronous calibration method for a dual-robot collaborative system as described in any one of claims 1-7.

10. The electronic device according to claim 9, characterized in that, The memory is a non-transitory computer-readable storage medium.

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