Method and system for calibrating position and posture of mechanical arm of double-arm robot

Abstract

The invention provides a two-arm robot mechanical arm pose calibration method and system, and the method comprises the steps: collecting parameters in the collaborative movement process of mechanical arms and the nominal pose of a calibration plate, constructing difference constraint equations of calibration points of the two mechanical arms, combining the difference constraint equations, and calculating the pose of the two mechanical arms according to the difference constraint equations. Establishing a multi-point pose constraint equation of the mechanical arm of the double-arm robot; the multi-point pose constraint equation is subjected to iterative solution through a weighted least square method, and kinematics parameters of the two mechanical arms are calibrated by means of kinematics parameter deviation obtained through iterative solution; and according to the pose constraint relation between the camera and the bases of the two mechanical arms, a mechanical arm relative pose conversion matrix is established, the relative pose relation between the base coordinate systems of the two mechanical arms is iteratively solved through an alternating minimization method in combination with the distance deviation of calibration points on the calibration plates of the two mechanical arms, and the poses of the mechanical arms are calibrated. Through the scheme, the pose calibration cost of the mechanical arm can be reduced, the calibration process is simplified, and the calibration efficiency is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of robots, and in particular relates to a method and system for calibrating the mechanical arm posture of a dual-arm robot. Background Art

[0002] Compared with the traditional single-arm working mode, dual-arm collaboration can expand the working space, increase load capacity, and improve flexibility. The high positioning accuracy of the dual-arm robot is the core foundation for completing high-quality collaborative tasks. The positioning error of the robot mainly comes from the manufacturing and assembly of the robot. Therefore, it is of great significance to develop a high-precision, high-efficiency, and low-cost calibration algorithm to improve the positioning accuracy of the robot.

[0003] At present, the commonly used robot calibration methods are: the calibration method using a laser tracker, which installs a target ball at the end of the robot's arm, uses laser to obtain the end point data of the robot in different postures to establish constraints, and uses the quadratic sequence programming method to solve it, so as to calibrate the kinematic geometric parameters; the dual-arm robot self-calibration method using a ballbar, the ballbar system consists of three parts: a linear sensor and dynamic and static magnetic seats. This method uses the ballbar system to measure the posture of the two robotic arms, and realizes robot self-calibration by identifying the mapping relationship between the ballbar measurement value and the error source.

[0004] However, the use of specific measuring instruments for calibration, such as laser trackers and ballbars, is costly, bulky, and inconvenient to carry, making it difficult to achieve large-scale industrial applications. At the same time, many calibration devices are deployed at the end of the robotic arm, and the operation process is complicated, requiring the operator to have a certain level of professional knowledge. In addition, the existing commonly used dual-arm calibration algorithm generally uses a centralized identification method during the calibration process, that is, the internal parameters and relative postures of the two robotic arms are calculated simultaneously, which will lead to coupling of the dual-arm parameters, resulting in slow actual calculation speed and long calibration time, making it difficult to meet the needs of high production efficiency in industry. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a dual-arm robot manipulator arm posture calibration method and system, which are used to solve the current problems of high cost, complex operation and long calibration time of manipulator arm posture calibration.

[0006] In a first aspect of an embodiment of the present invention, a method for calibrating a dual-arm robot arm posture is provided, comprising: Collect the robot's arm parameters, joint angles and nominal position and posture of the calibration plate during the coordinated motion of the robot's two arms; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving in coordination within the field of view of the camera. Multiple calibration points are set on the calibration plate; According to the robot arm parameters, joint angles and the nominal pose of the calibration plate, the differential constraint equations of the calibration points of the two robot arms are constructed, and the differential constraint equations are combined to establish the multi-point pose constraint equations of the dual-arm robot arm; Iteratively solving the multi-point posture constraint equations by weighted least squares method, and calibrating the kinematic parameters of the two manipulators by using the kinematic parameter deviations obtained by iterative solution; After calibrating the kinematic parameters of the robot, the relative posture transformation matrix of the robot is established according to the posture constraint relationship between the camera and the bases of the two robot arms. Combined with the distance deviation of the calibration points on the calibration plates of the two robot arms, the relative posture relationship between the base coordinate systems of the two robot arms is iteratively solved by the alternating minimization method. According to the relative posture relationship between the two robot base coordinate systems, the robot posture is calibrated.

[0007] In a second aspect of an embodiment of the present invention, a dual-arm robot manipulator posture calibration system is provided, comprising: The data acquisition module is used to collect the robot arm parameters, joint angles and nominal position and posture of the calibration plate during the coordinated motion of the two robot arms; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving in coordination within the field of view of the camera. Multiple calibration points are set on the calibration plate; The first calculation module is used to construct the differential constraint equations of the calibration points of the two manipulators according to the manipulator parameters, joint angles and the nominal posture of the calibration plate, combine the differential constraint equations, establish the multi-point posture constraint equations of the dual-arm robot manipulator, and iteratively solve the multi-point posture constraint equations by weighted least squares method; A first calibration module is used to calibrate the kinematic parameters of the two manipulators by using the kinematic parameter deviations obtained by iterative solution; The second calculation module is used to establish the relative posture transformation matrix of the robot arm according to the posture constraint relationship between the camera and the two robot arm bases after calibrating the kinematic parameters of the robot arm. Combined with the distance deviation of the calibration points on the calibration plates of the two robot arms, the relative posture relationship between the two robot arm base coordinate systems is iteratively solved by the alternating minimization method. The second calibration module is used to calibrate the robot arm posture according to the relative posture relationship between the two robot arm base coordinate systems.

[0008] In a third aspect of an embodiment of the present invention, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect of the embodiment of the present invention when executing the computer program.

[0009] In a fourth aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method provided in the first aspect of the embodiment of the present invention are implemented.

[0010] In the embodiment of the present invention, by installing a calibration plate at the end of the mechanical arm and a camera at the head of the robot, the kinematic parameters and relative posture relationship of the mechanical arm are calculated and calibrated by collecting the posture data of the calibration points in the multi-posture coordinated motion of the two mechanical arms. Not only is the equipment small in size, low in cost, and easy to carry, it can meet the needs of industrial applications, but it is also easy to deploy, the operation process is simple, and the calibration efficiency is high. At the same time, the parameter decoupling and relative posture calculation speed are fast, and the calibration accuracy is high, which can meet the needs of high precision and high efficiency in industrial production. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic flow chart of a method for calibrating the mechanical arm posture of a dual-arm robot provided by an embodiment of the present invention; Figure 2 A schematic diagram of the installation of a calibration plate and a camera provided in one embodiment of the present invention; Figure 3 A schematic diagram of a calibration plate provided for an embodiment of the present invention; Figure 4 A schematic structural diagram of a dual-arm robot manipulator posture calibration system provided by one embodiment of the present invention; Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] It should be understood that the term "including" and other similar expressions in the specification or claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions, such as a process, method, system, or device including a series of steps or units is not limited to the listed steps or units. In addition, "first" and "second" are used to distinguish different objects, not to describe a specific order.

[0015] See also Figure 1 , a schematic flow chart of a dual-arm robot mechanical arm posture calibration method provided by an embodiment of the present invention, comprising: S101, collecting robot arm parameters, joint angles, and nominal positions and postures of the calibration plate during the coordinated motion of two robot arms; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving collaboratively within the field of view of the camera. Multiple calibration points are set on the calibration plate.

[0016] like Figure 2 As shown, two calibration plates are respectively installed at the ends of the two mechanical arms of the dual-arm robot, and the camera is installed on the head of the dual-arm robot, and the calibration plates are kept within the field of view of the camera.

[0017] For example, an asymmetric dot calibration plate is used as a measurement target. Figure 3 As shown in the figure, the spacing between the calibration points in the same group of the calibration plate is 10mm, and the spacing between different calibration point groups at the same position is 84.8528mm. For example, 0 and 1 are calibration points in the same group, and 2, 3 and 4, 5 are calibration points in different groups. The camera model used can be: MV-CA050-20UC, the fixed focus lens model is: MVL-KF1628M-12MP, the resolution is: 2592×2048, and the field of view is: 20*20cm. The camera internal parameters are calibrated using Zhang's calibration method, and the calibration result is: the measurement accuracy is about 0.015mm under a field of view of 20cm.

[0018] The robotic arm parameters may include the robotic arm connecting rod length, connecting rod torsion angle and connecting rod offset, etc. The joint angle refers to the relative angle between the joints of the robotic arm, and the nominal posture refers to the posture of the reference plate in an ideal state, that is, the target posture.

[0019] S102, constructing differential constraint equations of calibration points of two robotic arms according to robotic arm parameters, joint angles and nominal pose of the calibration plate, combining the differential constraint equations to establish multi-point pose constraint equations of the dual-arm robot robotic arm; Among them, robot parameters, joint angles and visual measurement results are obtained as input, and the initial hand-eye conversion matrix of the two robotic arms is constructed through the hand-eye calibration algorithm, and the initial hand-eye conversion matrix is ​​used as the initial value of the conversion matrix from the camera to the robotic arm.

[0020] Optionally, according to the nominal pose and actual pose of the calibration point in the calibration plate of the robot arm under different collaborative poses, after eliminating the actual pose by the difference method, a differential constraint equation is established, and the differential constraint equation is expressed as:

[0021] In the formula, Indicates The identifiable parameter variation matrix of the robot arm, Indicates The change in the identifiable parameters of the robot arm, Indicates Calibration plate for the robot arm The Jacobian matrix of the point pose change, For the Calibration plate for the robot arm Point The pose Jacobian matrix of the collaborative pose, Indicates Calibration plate for the robot arm The nominal pose change of the point, For the Calibration plate for the robot arm Point The nominal pose of the collaborative pose.

[0022] Calculate the i The deviation between the nominal pose and actual pose of a single calibration point on the calibration plate of a robot arm is expressed as: ; In the formula, represents the position deviation of the calibration point of the robot arm, Indicates i The actual position of the robot arm calibration point, Indicates i The nominal pose of the robot arm calibration points, express Collaborative sports postures, and Respectively represent i The identifiable parameters of a robot arm and their changes.

[0023] No. i The nominal pose of the calibration points on the calibration plate of the manipulator is obtained by forward kinematics calculation: ; ; In the formula, For the i The robot end coordinate system to the i The transformation matrix of the robot base coordinate system, For the i The calibration plate coordinate system of the first robot arm is i The transformation matrix of the robot end coordinate system; From the camera coordinate system to the i The transformation matrix of the calibration plate coordinate system of the robot arm, k is the number of robot arm axes, base=0,end=k .

[0024] No. i The transformation matrix of adjacent links of a robot arm is expressed as ,and , j is less than or equal to k A positive integer, c represents the cosine function, s represents the sine function, a is the connecting rod length, α is the connecting rod torsion angle, d is the offset, θ is the joint angle.

[0025] Since the calibration plate is installed at the end of the robotic arm, is an unknown constant. To ensure the stability of parameter identification, quaternion is used and translation vectors indicates that, and , The robot arm model adopts the DH parameter model, then i The identifiable parameters of the robot arm are: ,in, For the i Each robot arm can correct the joint zero position parameters, , For the i Each robot arm can correct the connecting rod parameters.

[0026] The first-order Taylor expansion is used to expand the calibration point posture deviation: ; The above formula can be simplified as: , For the i The Jacobian matrix of the robot arm pose.

[0027] According to the above formula, we can get: ; Based on the collected data and i The robot arm calibrates the plate in different positions. l The nominal pose data of the calibration points are used to establish the constraint equation:

[0028] In the formula, For the i Calibration plate for the robot arm l Point n The pose Jacobian matrix of the collaborative pose, No. i Calibration plate for the robot arm l The actual position of the point, For the i Calibration plate for the robot arm l Point n The nominal pose of the collaborative pose.

[0029] Using the difference method, eliminating the actual posture in the constraint equation can obtain the constrained difference equation:

[0030] The first i The corresponding robot arm f By combining the constraint equations of the calibration points, we can get the multi-point pose constraint equation group: .

[0031] S103, iteratively solving the multi-point posture constraint equation by weighted least square method, and calibrating the kinematic parameters of the two manipulators by using the kinematic parameter deviation obtained by iterative solution; The kinematic parameters mainly include DH parameters, which generally refer to parameters used to describe the relative position and direction between each joint and connecting rod of the robot arm, including connecting rod length, connecting rod offset and joint angle, etc. The currently collected kinematic parameters are corrected according to the kinematic parameter deviation solved iteratively.

[0032] Among them, the iteration stopping condition is set to the maximum number of iterations or the terminal winding point error. The terminal winding point error is the average of the average position errors of the calibration points obtained by performing multiple posture measurements on each calibration point.

[0033] The multi-point pose constraint equations are:

[0034] The multi-point pose constraint equations are expressed as: ; In the formula, I is the unit matrix, λ is the weight, and The variable step size optimization is performed based on the changing trend of

[0035] The weighted least square method is used to solve the multi-point pose constraint equations of the manipulator, and the iteration stop condition is set to the maximum number of iterations or the end winding point error. The kinematic parameter deviations obtained by iterative solution are used to calibrate the kinematic parameters of the two manipulators.

[0036] S104, after calibrating the kinematic parameters of the robotic arms, establish a relative posture conversion matrix of the robotic arms according to the posture constraint relationship between the camera and the bases of the two robotic arms, and iterate and solve the relative posture relationship between the base coordinate systems of the two robotic arms by an alternating minimization method in combination with the distance deviation of the calibration points on the calibration plates of the two robotic arms; The pose constraint relationship between the camera and the robot base is determined by eye-to-hand calibration, that is, the camera is installed on the robot head, and the transformation matrix between the camera and the robot base coordinate system is calibrated. The relative pose transformation matrix of the robot refers to the pose transformation relationship between the two robot base coordinate systems.

[0037] The distance deviation of the calibration point refers to the distance deviation between the nominal distance and the actual distance between the calibration points at the same position on the two calibration plates. The alternating minimization method is a process in which some variables are fixed and other variables are optimized in an iterative process, and the process is repeated until convergence.

[0038] Specifically, based on the pose constraint relationship between the camera and the bases of the two robotic arms, a relative pose conversion matrix between the two robotic arms is constructed; The collaborative positioning distance error of the two manipulators is set as the distance deviation between the measured distance and the nominal distance between the corresponding calibration points on the calibration plate at the end of the robot manipulator; According to the collaborative positioning distance error, an index function is constructed, and the index function is iteratively solved through alternating minimization; The indicator function is: ; In the formula, Indicates the indicator value, represents the collaborative posture, n represents the number of collaborative poses, represents the calibration point count variable, q represents the number of calibration point groups, Indicates Collaborative posture The collaborative positioning distance error of the group calibration points, Indicates the second robot calibration board The measured position of the calibration points in the camera coordinate system, Indicates the first robot calibration board The measured position of the calibration points in the camera coordinate system, Represents the transformation matrix from the first robot base coordinate system to the camera, Represents the transpose of the transformation matrix from the second robot base coordinate system to the camera, Indicates the second robot calibration board The position of the calibration point in the second robot base coordinate system, Indicates the first robot calibration board The position of the calibration point in the first robot base coordinate system.

[0039] According to the constraint relationship between the camera and the robotic arm, the relative posture transformation matrix between the two robotic arms can be obtained as follows:

[0040] In the formula, Represents the transformation relationship between the two robot base coordinate systems. , the above formula is simplified to:

[0041] Transform the above formula into:

[0042] The collaborative positioning error is defined as the distance deviation between the measured distance and the nominal distance between the corresponding calibration points on the calibration plate at the end of the two manipulators of the dual-arm robot:

[0043] In the formula, For two calibration plates The measured distance between the group calibration points, For two calibration plates Nominal distance between group calibration points:

[0044]

[0045] In the formula, Calibrate the second robot on the board The measured position of the calibration points in the camera coordinate system, Calibrate the first robot on the board The measured position of the calibration points in the camera coordinate system, Calibrate the second robot on the board The position of the calibration point in the second robot base coordinate system, Calibrate the first robot on the board The position of the calibration point in the first robot arm base coordinate system.

[0046] According to the distance deviation, the indicator function is defined as: ; In the formula, Indicates kind of posture, Indicates Use step 3 to identify multiple groups of , The value of is solved by alternating minimization method. The value of the smallest group , , and then obtain .

[0047] S105. Calibrate the robot arm posture according to the relative posture relationship between the two robot arm base coordinate systems.

[0048] Based on the relative posture relationship between the base coordinate systems of the two robotic arms, the postures of the two robotic arms are adjusted. The posture of one robotic arm may be adjusted separately or the postures of both robotic arms may be adjusted.

[0049] In this embodiment, there is no need to use expensive calibration equipment. The equipment used only involves calibration plates and common industrial cameras, which are small in size, low in cost, easy to carry, and can meet the needs of large-scale industrial use. The calibration equipment is simple to deploy. It only needs to install calibration plates at the ends of the two robotic arms and industrial cameras on the robot head respectively, and there is no need to measure the actual position of the calibration plate during the calibration process. The operation is simple and the calibration efficiency is high. By first performing kinematic calibration on each robotic arm of the dual-arm robot and completing the kinematic calibration of the two robotic arms, a posture constraint conversion matrix is ​​established through the posture constraint relationship between the camera and the ends of the two robotic arms. Combined with the posture conversion constraint matrix and the single-arm identification result, the relative posture relationship of the base coordinate system between the left arm and the right arm is identified. The whole process has fast calibration speed and high accuracy, and parameter decoupling and relative posture calculation speed are fast, which can meet the needs of high precision and high efficiency in industrial production.

[0050] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0051] Figure 4 A schematic diagram of a dual-arm robot arm posture calibration system provided by an embodiment of the present invention, the system comprising: The data acquisition module 410 is used to collect the robot arm parameters, joint angles and nominal position and posture of the calibration plate during the coordinated movement of the two robot arms of the robot; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving in coordination within the field of view of the camera. Multiple calibration points are set on the calibration plate; A first calculation module 420 is used to construct differential constraint equations of calibration points of two robotic arms according to robotic arm parameters, joint angles and nominal pose of the calibration plate, combine the differential constraint equations, establish multi-point pose constraint equations of the dual-arm robot robotic arm, and iteratively solve the multi-point pose constraint equations by weighted least squares method; Among them, robot parameters, joint angles and visual measurement results are obtained as input, and the initial hand-eye conversion matrix of the two robotic arms is constructed through the hand-eye calibration algorithm, and the initial hand-eye conversion matrix is ​​used as the initial value of the conversion matrix from the camera to the robotic arm.

[0052] Specifically, the differential constraint equations for constructing the calibration points of the two robotic arms according to the robotic arm parameters, joint angles and the nominal position and posture of the calibration plate include: According to the nominal pose and actual pose of the calibration point in the calibration plate under different collaborative poses of the robot arm, the differential constraint equation is established after eliminating the actual pose by the differential method. The differential constraint equation is expressed as:

[0053] In the formula, Indicates The identifiable parameter variation matrix of the robot arm, Indicates The change in the identifiable parameters of the robot arm, Indicates Calibration plate for the robot arm The Jacobian matrix of the point pose change, For the Calibration plate for the robot arm Point The pose Jacobian matrix of the collaborative pose, Indicates Calibration plate for the robot arm The nominal pose change of the point, For the Calibration plate for the robot arm Point The nominal pose of the collaborative pose.

[0054] Among them, the iteration stopping condition is set to the maximum number of iterations or the terminal winding point error, and the terminal winding point error is the average of the average position errors of the calibration points obtained by performing multiple posture measurements on multiple calibration points respectively.

[0055] A first calibration module 430 is used to calibrate the kinematic parameters of the two manipulators by using the kinematic parameter deviations obtained by iterative solution; The second calculation module 440 is used to establish the relative posture transformation matrix of the robot arm according to the posture constraint relationship between the camera and the two robot arm bases after calibrating the kinematic parameters of the robot arm, and iteratively solve the relative posture relationship between the two robot arm base coordinate systems by the alternating minimization method in combination with the distance deviation of the calibration points on the calibration plates of the two robot arms; Specifically, based on the pose constraint relationship between the camera and the bases of the two robotic arms, a relative pose conversion matrix between the two robotic arms is constructed; The collaborative positioning distance error of the two manipulators is set as the distance deviation between the measured distance and the nominal distance between the corresponding calibration points on the calibration plate at the end of the robot manipulator; According to the collaborative positioning error, an indicator function is constructed, and the indicator function is iteratively solved through alternating minimization; The indicator function is: ; In the formula, Indicates the indicator value, Indicates Collaborative postures, n represents the number of collaborative poses, Indicates group calibration point, q represents the number of calibration point groups, Indicates Collaborative posture The collaborative positioning distance error of the group calibration points, Indicates the second robot calibration board The measured position of the calibration points in the camera coordinate system, Indicates the first robot calibration board The measured position of the calibration points in the camera coordinate system, Represents the transformation matrix from the first robot base coordinate system to the camera, Represents the transpose of the transformation matrix from the second robot base coordinate system to the camera, Indicates the second robot calibration board The position of the calibration point in the second robot base coordinate system, Indicates the first robot calibration board The second calibration module 450 is used to calibrate the posture of the robot arm according to the relative posture relationship between the two robot arm base coordinate systems.

[0056] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and modules can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0057] Figure 5 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device is used for calibrating the position and posture of a dual-arm robot. Figure 5 As shown, the electronic device 5 of this embodiment includes: a memory 510, a processor 520 and a system bus 530, wherein the memory 510 includes an executable program 5101 stored thereon, and those skilled in the art can understand that Figure 5 The electronic device structure shown in the figure does not constitute a limitation of the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0058] Combine the following Figure 5 A detailed introduction to the various components of electronic equipment: The memory 510 can be used to store software programs and modules. The processor 320 executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory 510. The memory 510 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as cache data), etc. In addition, the memory 510 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0059] The memory 510 includes an executable program 5101 of the network request method, and the executable program 5101 can be divided into one or more modules / units, which are stored in the memory 510 and executed by the processor 520 to implement the calibration of the robot arm posture, etc. The one or more modules / units can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program 5101 in the electronic device 5. For example, the computer program 5101 can be divided into functional modules such as a data acquisition module, a first calculation module, a first calibration module, a second calculation module, and a second calibration module.

[0060] The processor 520 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 510, and calling data stored in the memory 510, it performs various functions of the electronic device and processes data, thereby monitoring the overall status of the electronic device. Optionally, the processor 520 may include one or more processing units; preferably, the processor 520 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 520.

[0061] The system bus 530 is used to connect the various functional components inside the computer, and can transmit data information, address information, and control information. Its types can be, for example, PCI bus, ISA bus, CAN bus, etc. The instructions of the processor 520 are transmitted to the memory 510 through the bus, and the memory 510 feeds back data to the processor 520. The system bus 530 is responsible for the data and instruction exchange between the processor 520 and the memory 510. Of course, the system bus 530 can also be connected to other devices, such as network interfaces, display devices, etc.

[0062] In the embodiment of the present invention, the executable program executed by the processor 520 included in the electronic device includes: Collect the robot's arm parameters, joint angles and nominal position and posture of the calibration plate during the coordinated motion of the robot's two arms; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving in coordination within the field of view of the camera. Multiple calibration points are set on the calibration plate; According to the robot arm parameters, joint angles and the nominal pose of the calibration plate, the differential constraint equations of the calibration points of the two robot arms are constructed, and the differential constraint equations are combined to establish the multi-point pose constraint equations of the dual-arm robot arm; Iteratively solving the multi-point posture constraint equations by weighted least squares method, and calibrating the kinematic parameters of the two manipulators by using the kinematic parameter deviations obtained by iterative solution; After calibrating the kinematic parameters of the robot, the relative posture transformation matrix of the robot is established according to the posture constraint relationship between the camera and the bases of the two robot arms. Combined with the distance deviation of the calibration points on the calibration plates of the two robot arms, the relative posture relationship between the base coordinate systems of the two robot arms is iteratively solved by the alternating minimization method. According to the relative posture relationship between the two robot base coordinate systems, the robot posture is calibrated.

[0063] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0064] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0065] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dual-arm robot arm posture calibration method, characterized in that: include: Collect the robot's arm parameters, joint angles and nominal position and posture of the calibration plate during the coordinated motion of the robot's two arms; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving in coordination within the field of view of the camera. Multiple calibration points are set on the calibration plate; According to the robot arm parameters, joint angles and the nominal pose of the calibration plate, the differential constraint equations of the calibration points of the two robot arms are constructed, and the differential constraint equations are combined to establish the multi-point pose constraint equations of the dual-arm robot arm; Iteratively solving the multi-point posture constraint equations by weighted least squares method, and calibrating the kinematic parameters of the two manipulators by using the kinematic parameter deviations obtained by iterative solution; After calibrating the kinematic parameters of the robot, the relative posture transformation matrix of the robot is established according to the posture constraint relationship between the camera and the bases of the two robot arms. Combined with the distance deviation of the calibration points on the calibration plates of the two robot arms, the relative posture relationship between the base coordinate systems of the two robot arms is iteratively solved by the alternating minimization method. According to the relative posture relationship between the two robot base coordinate systems, the robot posture is calibrated.

2. The method according to claim 1, characterized in that The differential constraint equations for constructing the calibration points of the two robotic arms according to the robotic arm parameters, joint angles and the nominal position and posture of the calibration plate include: The robot arm parameters, joint angles and camera vision measurement results are obtained as input, and the initial hand-eye conversion matrix of the two robot arms is constructed through the hand-eye calibration algorithm, and the initial hand-eye conversion matrix is ​​used as the initial value of the conversion matrix from the camera to the robot arm.

3. The method according to claim 1, characterized in that: The differential constraint equations for constructing the calibration points of the two robotic arms according to the robotic arm parameters, joint angles and the nominal position and posture of the calibration plate include: According to the nominal pose and actual pose of the calibration point in the calibration plate of the manipulator under different collaborative poses, the differential constraint equation is established after eliminating the actual pose by the differential method. The differential constraint equation is expressed as: ； In the formula, Indicates The identifiable parameter variation matrix of the robot arm, Indicates The change in the identifiable parameters of the robot arm, Indicates Calibration plate for the robot arm The Jacobian matrix of the point pose change, For the Calibration plate for the robot arm Point The pose Jacobian matrix of the collaborative pose, Indicates Calibration plate for the robot arm The nominal pose change of the point, For the Calibration plate for the robot arm Point The nominal pose of the collaborative pose.

4. The method according to claim 1, characterized in that The iterative solution of the multi-point posture constraint equation by weighted least square method comprises: The iteration stopping condition is set to the maximum number of iterations or the terminal winding point error, where the terminal winding point error is the average of the average position errors of the postures obtained from each measurement relative to the calibration points after multiple posture measurements are performed on each calibration point.

5. The method according to claim 1, characterized in that The method of establishing a relative posture transformation matrix of the robotic arms according to the posture constraint relationship between the camera and the two robotic arm bases, and iteratively solving the relative posture relationship between the two robotic arm base coordinate systems by an alternating minimization method in combination with the distance deviation of the two robotic arms includes: Based on the pose constraint relationship between the camera and the bases of the two robotic arms, the relative pose transformation matrix between the two robotic arms is constructed; The collaborative positioning distance error of the two manipulators is set as the distance deviation between the measured distance and the nominal distance between the corresponding calibration points on the calibration plate at the end of the robot manipulator; According to the collaborative positioning distance error, an index function is constructed, and the index function is iteratively solved through alternating minimization; The indicator function is: ； In the formula, Indicates the indicator value, represents the collaborative posture, n represents the number of collaborative poses, represents the calibration point count variable, q represents the number of calibration point groups, Indicates Collaborative posture The collaborative positioning distance error of the group calibration points, Indicates the second robot calibration board The measured position of the calibration points in the camera coordinate system, Indicates the first robot calibration board The measured position of the calibration points in the camera coordinate system, Represents the transformation matrix from the first robot base coordinate system to the camera, Represents the transpose of the transformation matrix from the second robot base coordinate system to the camera, Indicates the second robot calibration board The position of the calibration point in the second robot base coordinate system, Indicates the first robot calibration board The position of the calibration point in the first robot base coordinate system.

6. A dual-arm robot arm posture calibration system, characterized in that: include: The data acquisition module is used to collect the robot arm parameters, joint angles and nominal position and posture of the calibration plate during the coordinated motion of the two robot arms; Among them, two calibration plates are respectively installed at the ends of the two mechanical arms of the robot, and the camera is installed on the head of the dual-arm robot, and the two mechanical arms are kept moving in coordination within the field of view of the camera. Multiple calibration points are set on the calibration plate; The first calculation module is used to construct the differential constraint equations of the calibration points of the two manipulators according to the manipulator parameters, joint angles and the nominal posture of the calibration plate, combine the differential constraint equations, establish the multi-point posture constraint equations of the dual-arm robot manipulator, and iteratively solve the multi-point posture constraint equations by weighted least squares method; A first calibration module is used to calibrate the kinematic parameters of the two manipulators by using the kinematic parameter deviations obtained by iterative solution; The second calculation module is used to establish the relative posture transformation matrix of the robot arm according to the posture constraint relationship between the camera and the two robot arm bases after calibrating the kinematic parameters of the robot arm. Combined with the distance deviation of the calibration points on the calibration plates of the two robot arms, the relative posture relationship between the two robot arm base coordinate systems is iteratively solved by the alternating minimization method. The second calibration module is used to calibrate the robot arm posture according to the relative posture relationship between the two robot arm base coordinate systems.

7. The system according to claim 6, characterized in that The differential constraint equations for multiple calibration points of the two robotic arms are constructed according to the robotic arm parameters, joint angles and nominal pose data of the calibration plate, including: The robot parameters, joint angles and visual measurement results are obtained as input, and the initial hand-eye conversion matrix of the two robotic arms is constructed through the hand-eye calibration algorithm, and the initial hand-eye conversion matrix is ​​used as the initial value of the conversion matrix from the camera to the robotic arm.

8. The system according to claim 6, characterized in that The differential constraint equations for constructing the calibration points of the two robotic arms according to the robotic arm parameters, joint angles and the nominal position and posture of the calibration plate include: According to the nominal pose and actual pose of the calibration point in the calibration plate under different collaborative poses of the robot arm, the differential constraint equation is established after eliminating the actual pose by the differential method. The differential constraint equation is expressed as: ； In the formula, Indicates The identifiable parameter variation matrix of the robot arm, Indicates The change in the identifiable parameters of the robot arm, Indicates Calibration plate for the robot arm The Jacobian matrix of the point pose change, For the Calibration plate for the robot arm Point The pose Jacobian matrix of the collaborative pose, Indicates Calibration plate for the robot arm The nominal pose change of the point, For the Calibration plate for the robot arm Point The nominal pose of the collaborative pose.

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, the steps of a dual-arm robot manipulator arm posture calibration method are implemented as described in any one of claims 1 to 5.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed, the steps of a dual-arm robot manipulator arm posture calibration method as described in any one of claims 1 to 5 are implemented.

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