Mechanical arm control zero point calibration method and related apparatus

Abstract

A mechanical arm control zero point calibration method and a related apparatus. The mechanical arm control zero point calibration method comprises: adding a zero point deviation of each joint of a robot to a first forward kinematic model of a mechanical arm of the robot, so as to form a second forward kinematic model, and combining the second forward kinematic model with the first forward kinematic model to obtain a tail end deviation function; when the mechanical arm is at the current zero point, sending a target tail end pose instruction and acquiring the spatial deviation of the actual position of a tail end; substituting into the tail end deviation function the position information and the spatial deviation of each joint angle after the tail end stops moving each time, and shifting the phase to obtain an objective optimization function; and solving the objective optimization function to obtain a zero point deviation value.

Description

A method and related device for zero point calibration of robotic arm control Technical Field

[0001] The present application relates to the field of robot control technology, and in particular to a robot arm control zero point calibration method and related devices. Background Art

[0002] With the development of robotics, the trend is to attach serial robots to the end-end of traditional construction machinery or machine tools. Leveraging the robot's flexibility and high precision with the construction machinery's high payload and wide-range capabilities, these robots are used to perform precision operations within large mobile spaces, such as aircraft fuselage machining, high-speed rail body polishing, and ship hull exterior welding. In addition to machining within workshop environments, these devices can also be used for outdoor, high-altitude operations in high-risk industries, such as live overhead line repairs and explosive filling for blasting.

[0003] High-precision target tracking is key to the functionality of this type of robot. Visual perception is used to determine the relative position of the target relative to the robot, and the coordinated motion control of the two manipulator arms enables high-precision interaction between the end-arm and the work point. Due to assembly errors in the manipulator arms, the zero points of the encoders on each arm are physically inconsistent. This prevents the two arms from achieving high-precision physical interaction within the same coordinate system. This means that both arms cannot track the spatial position of the same target with the same accuracy, hindering dual-arm collaboration. Therefore, solving the manipulator homing problem is particularly important for dual-arm collaborative robots that rely on visual positioning and absolute positioning accuracy.

[0004] However, the calibration methods commonly used in the industry are mostly for single-arm robots, and common methods include hardware and software methods. The hardware method is to create scales or marks with a certain degree of precision on the robot's outer shell, and to achieve zero calibration by aligning the scales or marks during the assembly of the robotic arm. This method is suitable for large-scale, high-profit robotic arm production lines to ensure that the processed scales or marks achieve high precision. Otherwise, the assembly error is too large to meet the needs of dual-arm coordination. The software method is to control the end of the robotic arm to touch a fixed theoretical position point in different postures, measure the difference between the theoretical position and the actual position, and construct a nonlinear equation system to obtain the deviation angle of each joint through Gaussian elimination. This method is difficult to implement and difficult to implement, which is not conducive to widespread use.

[0005] Summary of the Invention

[0006] The present application provides a method and related device for zero point calibration of a robotic arm control, which is used to solve the technical problems in the prior art that the algorithm is difficult to implement, difficult to implement, and not conducive to widespread use.

[0007] In view of this, the first aspect of the present application provides a method for calibrating a zero point of a robotic arm control, the method comprising:

[0008] Based on the first forward kinematics model of the robot's manipulator, the zero-point deviations of the robot's joints are added to form a second forward kinematics model, and the second forward kinematics model is combined with the kinematic model to obtain an end deviation function;

[0009] When the robot arm is at the current zero point, it sends the target end position command and collects the spatial deviation of the actual end position;

[0010] Substituting the position information of each joint angle and the spatial deviation after each end stops moving into the end deviation function, and performing phase shifting to obtain the target optimization function;

[0011] The target optimization function is solved to obtain a zero-point deviation value.

[0012] Optionally, the sending of the target end position command and the acquisition of the spatial deviation of the actual position of the end for the robot arm at the current zero point specifically include:

[0013] When the robot arm is at the current zero point, it sends m target end position instructions, and collects the spatial deviation between the end position and the actual position after the first target end position instruction is issued after the second to mth target end position instructions are issued and the robot arm stops moving.

[0014] Optionally, the terminal deviation function is specifically: Δp=p′-p=f(q+Δq)-f(q);

[0015] Where f is the forward kinematic model of the manipulator, q is an n-dimensional vector representing the angles of each joint; p is a three-dimensional vector representing the spatial position of the end based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

[0016] Optionally, the target optimization function is specifically: i =Δp i -(f(q i +Δq)-f(q i ));

[0017] Where i = 1, 2, ..., m, f is the forward kinematic model of the robot arm, q is an n-dimensional vector representing the angle of each joint; p is a 3-dimensional vector representing the spatial position of the end based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

[0018] A second aspect of the present application provides a robot arm control zero point calibration system, the system comprising:

[0019] a modeling unit configured to form a second forward kinematic model based on a first forward kinematic model of the robot's manipulator arm by adding zero-point deviations of the robot's joints, and to combine the second forward kinematic model with the kinematic model to obtain an end deviation function;

[0020] The acquisition unit is used to send the target end position command to the robot arm at the current zero point and collect the spatial deviation of the actual position of the end;

[0021] a transformation unit, configured to substitute the position information of each joint angle and the spatial deviation after each end stops moving into the end deviation function, and perform phase shifting to obtain a target optimization function;

[0022] The calculation unit is used to solve the target optimization function to obtain a zero-point deviation value.

[0023] Optionally, the acquisition unit is specifically configured to:

[0024] When the robot arm is at the current zero point, it sends m target end position instructions, and collects the spatial deviation between the end position and the actual position after the first target end position instruction is issued after the second to mth target end position instructions are issued and the robot arm stops moving.

[0025] Optionally, the terminal deviation function is specifically: Δp=p′-p=f(q+Δq)-f(q);

[0026] Where f is the forward kinematic model of the manipulator, q is an n-dimensional vector representing the angles of each joint; p is a three-dimensional vector representing the spatial position of the end based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

[0027] Optionally, the target optimization function is specifically: i =Δp i -(f(q i +Δq)-f(q i ));

[0028] Where i = 1, 2, ..., m, f is the forward kinematic model of the robot arm, q is an n-dimensional vector representing the angle of each joint; p is a 3-dimensional vector representing the spatial position of the end based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

[0029] A third aspect of the present application provides a robot arm control zero point calibration device, the device comprising a processor and a memory:

[0030] The memory is used to store program code and transmit the program code to the processor;

[0031] The processor is used to execute the steps of the robot arm control zero point calibration method as described in the first aspect according to the instructions in the program code.

[0032] In a fourth aspect, the present application provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute the robot arm control zero point calibration method described in the first aspect above.

[0033] It can be seen from the above technical solutions that this application has the following advantages:

[0034] The present application provides a method for zero-point calibration of a robotic arm control, comprising: forming a second positive kinematic model based on a first positive kinematic model of the robot's robotic arm, adding the zero-point deviations of the robot's joints, and combining the second positive kinematic model with the kinematic model to obtain an end-point deviation function; for the robotic arm at the current zero point, sending a target end-point posture instruction, and collecting the spatial deviation of the actual end-point position; substituting the position information and spatial deviation of each joint angle after each end stops moving into the end-point deviation function, and performing phase shifting to obtain a target optimization function; and solving the target optimization function to obtain a zero-point deviation value.

[0035] Compared with the prior art, this application:

[0036] 1. The solution method is simple and is not limited by the number of joints of the robotic arm. It is applicable to common robotic arms with 3 degrees of freedom, 6 degrees of freedom, and 7 degrees of freedom.

[0037] 2. It is not limited by the processing accuracy of the robot arm joints, and zero calibration can be achieved even if the scale or mark cannot be processed. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] FIG1 is a schematic flow chart of a method for zero point calibration of a robotic arm control provided in an embodiment of the present application;

[0039] FIG2 is a schematic structural diagram of a robot arm control zero point calibration system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to help those skilled in the art better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments 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 those skilled in the art without creative work are within the scope of protection of this application.

[0041] Referring to FIG1 , a method for calibrating a zero point of a robotic arm control provided in an embodiment of the present application includes:

[0042] Step 101: Based on a first forward kinematics model of the robot's manipulator, zero-point deviations of the robot's joints are added to form a second forward kinematics model, and the second forward kinematics model is combined with the kinematic model to obtain an end deviation function;

[0043] It should be noted that based on the forward kinematics model p of the manipulator, the zero-point deviations of each joint are added to form a new forward kinematics model p′. This is combined with the original kinematics model p to obtain the end deviation function. That is: p = f(q) (1) p′ = f(q + Δq) (2) Δp = p′ - p = f(q + Δq) - f(q) (3)

[0044] Where f is the forward kinematic model of the manipulator, q is an n-dimensional vector representing the angles of each joint; p is a three-dimensional vector representing the spatial position of the end based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

[0045] Step 102: When the robot arm is at the current zero point, send the target end position command and collect the spatial deviation of the actual position of the end;

[0046] It should be noted that when the robot arm is at the current zero point, the target end position and posture instructions are sent multiple times; the target end position and posture instructions must ensure that the position remains unchanged and the posture is variable.

[0047] If m instructions are issued, the measurement system is used to collect the spatial deviation between the end position after each target end posture is issued from the second to the mth time and the end position after the robot arm stops moving and the actual position after the first issuance.

[0048] Step 103: Substitute the position information and spatial deviation of each joint angle after each end stops moving into the end deviation function, and perform phase shifting to obtain the target optimization function;

[0049] It should be noted that the position of each joint angle after each end stops moving is substituted into the rightmost side of Equation (3), and the end space deviation is substituted into the leftmost side of Equation (3), and the target optimization function is obtained by phase shifting, that is: i =Δp i -(f(q i +Δq)-f(q i )) i=1,2,……,m (4)

[0050] Step 104: Solve the target optimization function to obtain a zero-point deviation value.

[0051] It should be noted that the target optimization function is:

[0052] Then solving the joint angle zero point deviation can be transformed into solving the problem of the size of △q when g is minimum.

[0053] At this point, the Global Optimization Toolbox of Matlab software can be used to solve the problem and obtain the zero-point deviation size.

[0054] The robot arm control zero point calibration method provided in this embodiment is a method for solving the zero point offset of the joint angle based on the evolutionary algorithm to solve the problem of robot arm zeroing; the robot joint zeroing process is equivalent to a global optimization problem of a constrained multivariable function, and the deviation between the current zero point and the ideal zero point is determined by finding the optimal solution.

[0055] The above is a robot arm control zero point calibration method provided in an embodiment of the present application, and the following is a robot arm control zero point calibration system provided in an embodiment of the present application.

[0056] Referring to FIG. 2 , a robot arm control zero point calibration system provided in an embodiment of the present application includes:

[0057] A modeling unit 201 is configured to form a second forward kinematic model based on a first forward kinematic model of the robot's manipulator arm by adding zero-point deviations of the robot's joints, and to combine the second forward kinematic model with the kinematic model to obtain an end deviation function;

[0058] The acquisition unit 202 is used to send a target end position command to the robot arm at the current zero point and to acquire the spatial deviation of the actual position of the end;

[0059] The transformation unit 203 is used to substitute the position information and spatial deviation of each joint angle after each end stops moving into the end deviation function, and perform phase shifting to obtain the target optimization function;

[0060] The calculation unit 204 is used to solve the target optimization function to obtain a zero-point deviation value.

[0061] Furthermore, an embodiment of the present application also provides a robotic arm control zero point calibration device, the device comprising a processor and a memory:

[0062] The memory is used to store program code and transmit the program code to the processor;

[0063] The processor is used to execute the steps of the robot arm control zero point calibration method as described in the above method embodiment according to the instructions in the program code.

[0064] Furthermore, a computer-readable storage medium is provided in an embodiment of the present application, and the computer-readable storage medium is used to store program code, and the program code is used to execute the robot arm control zero point calibration method described in the above method embodiment.

[0065] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0066] The terms "first," "second," "third," "fourth," etc., in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or apparatus.

[0067] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0068] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0069] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0070] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0071] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (English full name: Read-Only Memory, English abbreviation: ROM), random access memory (English full name: RandomAccess Memory, English abbreviation: RAM), disk or optical disk and other media that can store program code.

[0072] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. 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 application.

Claims

1. A method for zero point calibration of a robot arm control, characterized in that: include: Based on the first forward kinematics model of the robot's mechanical arm, the zero-point deviations of the robot's joints are added to form a second forward kinematics model, and the second forward kinematics model is combined with the kinematics model to obtain an end deviation function; When the robot arm is at the current zero point, send the target end position command and collect the spatial deviation of the actual end position; Substituting the position information of each joint angle and the spatial deviation after each end stops moving into the end deviation function, and performing phase shifting to obtain the target optimization function; The target optimization function is solved to obtain a zero-point deviation value.

2. The method for zero point calibration of a robot arm control according to claim 1, characterized in that: The method of sending the target end position command to the robot arm at the current zero point and collecting the spatial deviation of the actual end position specifically includes: When the robot arm is at the current zero point, m target end position and posture instructions are sent, and the spatial deviation between the end position and the actual position of the end after the first target end position and posture instruction is issued is collected after the second to mth target end position and posture instructions are issued and the robot arm stops moving.

3. The method for zero point calibration of a robot arm control according to claim 1, characterized in that: The terminal deviation function is specifically: Δp=p′-p=f(q+Δq)-f(q); Where f is the forward kinematics model of the robot, q is an n-dimensional vector representing the angles of each joint; p is a three-dimensional vector representing the end spatial posture based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

4. The method for zero point calibration of a robot arm control according to claim 1, characterized in that: The target optimization function is specifically: i =Δp i -(f(q i +Δq)-f(q i )); Wherein, i=1,2,…,m, f is the forward kinematics model of the robot, q is an n-dimensional vector representing each joint angle; p is a three-dimensional vector representing the end spatial posture based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

5. A robot arm control zero point calibration system, characterized in that: include: Modeling unit for the first forward kinematic model of the robot arm based on the addition of the various joints The zero-point deviation forms a second forward kinematics model, and the second forward kinematics model is combined with the kinematics model to obtain a terminal deviation function; The acquisition unit is used to send the target end position command to the robot arm at the current zero point and collect the spatial deviation of the actual position of the end; A transformation unit, used for substituting the position information of each joint angle and the spatial deviation into the terminal deviation function after each end stops moving, and performing phase shifting to obtain a target optimization function; The calculation unit is used to solve the target optimization function to obtain a zero-point deviation value.

6. The robot arm control zero point calibration system according to claim 5, characterized in that: The acquisition unit is specifically used for: When the robot arm is at the current zero point, m target end position and posture instructions are sent, and the spatial deviation between the end position and the actual position of the end after the first target end position and posture instruction is issued is collected after the second to mth target end position and posture instructions are issued and the robot arm stops moving.

7. The robot arm control zero point calibration system according to claim 5, characterized in that: The terminal deviation function is specifically: Δp=p′-p=f(q+Δq)-f(q); Where f is the forward kinematics model of the robot, q is an n-dimensional vector representing the angles of each joint; p is a three-dimensional vector representing the end spatial posture based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

8. The robot arm control zero point calibration system according to claim 5, characterized in that: The target optimization function is specifically: e i =Δp i -(f(q i +Δq)-f(q i )); Wherein, i=1,2,…,m, f is the forward kinematics model of the robot, q is an n-dimensional vector representing each joint angle; p is a three-dimensional vector representing the end spatial posture based on f, and △q is an n-dimensional vector representing the deviation between the current zero point and the ideal zero point of each joint angle.

9. A robot arm control zero point calibration device, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the robot arm control zero point calibration method described in any one of claims 1-4 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program code, and the program code is used to execute the robot arm control zero point calibration method described in any one of claims 1-4.

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