Large hydraulic mechanical arm tail end position control method and system, computer equipment and storage medium

Abstract

A method for controlling the tail end position of a large hydraulic mechanical arm comprises the following steps that the joint value of the hydraulic mechanical arm is obtained and recorded as the current joint value # imgabs0 #, and n is the number of joints of the hydraulic mechanical arm; determining a first tail end target parameter of the hydraulic mechanical arm; based on the current joint value # imgabs1 # and the first tail end target parameter, a second tail end target parameter is obtained through first Jacobian iteration and first error compensation in sequence; updating a joint value of the hydraulic mechanical arm, recording the joint value as a dynamic joint value # imgabs2 #, and sequentially performing second Jacobian iteration and second error compensation on the basis of a second tail end target parameter and the dynamic joint value # imgabs3 # to obtain a tail end position error; and optimal control parameters are generated based on the tail end position errors, and the hydraulic mechanical arm is controlled based on the optimal control parameters. According to the method, the tail end position of the hydraulic mechanical arm is corrected twice on the basis of double Jacobian iterations, so that the control precision of the tail end position of the hydraulic mechanical arm is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hydraulic mechanical arm control, in particular to a method, system, computer equipment and storage medium for controlling the end position of a large hydraulic mechanical arm. Background Art

[0002] A hydraulic robotic arm is a type of robotic arm driven by hydraulic principles, capable of high-precision, high-speed, and highly flexible movement. Its working principle is to utilize the pressure of a hydraulic engine to move each joint of the robotic arm through the action of hydraulic cylinders, hydraulic pipes, and hydraulic valves, thereby achieving the purpose of moving the robotic arm. A hydraulic robotic arm primarily consists of multiple joints. In the process of driving the end of the hydraulic robotic arm to move, all joints need to participate. However, due to factors such as its own gravity and material strength, the position of the end of the hydraulic robotic arm is difficult to accurately reach the target position. Especially for large hydraulic robotic arms, which have more joints and are larger in size, the negative effects of various factors will be amplified, especially due to different deformations occurring at different joints, making it more difficult to control the end position.

[0003] Existing techniques primarily use forward error compensation to calculate the actual position of the hydraulic manipulator's end point based on the combined joint values ​​of the arm. However, this method cannot completely resolve the positioning error between the hydraulic manipulator's end point and the desired target point. This known but uncompensated forward kinematic positioning error becomes a major factor affecting inverse kinematics accuracy. Summary of the Invention

[0004] In order to address the deficiencies in the prior art, the present invention provides a method, system, computer equipment and storage medium for controlling the end position of a large hydraulic robotic arm. The end position of the hydraulic robotic arm is corrected twice based on double Jacobi iteration, and then the position of the hydraulic robotic arm is made sufficiently close to the target position through two error compensations, thereby effectively improving the control accuracy of the end position of the hydraulic robotic arm.

[0005] In order to achieve the above object, the specific solution adopted by the present invention is: a large hydraulic manipulator end position control method, comprising the following steps: Get the joint value of the hydraulic manipulator and record it as the current joint value Where n is the number of joints of the hydraulic manipulator; determining a first end target parameter of the hydraulic manipulator arm; Based on the current joint values The first terminal target parameter and the first terminal target parameter are sequentially subjected to the first Jacobian iteration and the first error compensation to obtain the second terminal target parameter; Update the joint values ​​of the hydraulic manipulator and record them as dynamic joint values Based on the second end target parameters and dynamic joint values The end position error is obtained through the second Jacobi iteration and the second error compensation; Optimized control parameters are generated based on the end position error, and the hydraulic manipulator arm is controlled based on the optimized control parameters.

[0006] As a further optimization of the above-mentioned large hydraulic manipulator end position control method: the first end target parameter includes the first end target position and the first terminal target pose Based on the current joint values The method of obtaining the second terminal target parameter by sequentially performing the first Jacobian iteration and the first error compensation on the first terminal target parameter includes: For the first end target pose and the current joint values Perform the first Jacobi iteration to obtain the first inverse solution joint value For the first inverse solution joint value Perform DH forward solution to obtain the theoretical position of the first end The first terminal theoretical position is corrected using the pre-trained error compensation model Compensation is performed to obtain the first error compensation amount And based on the first error compensation amount and the first end theoretical position Calculate the second end target position For the current joint value Update to get dynamic joint values And for the first end target pose Update to get the second end target pose Second end target position and the second end target pose Makes up the second terminal target parameter.

[0007] As a further optimization of the above-mentioned large hydraulic manipulator end position control method: based on the first error compensation and the first end theoretical position Calculate the second end target position The methods include: Based on the first error compensation amount and the first end theoretical position Calculate the actual position of the first end Based on the actual position of the first end and the first end target position Calculate the first end position error Based on the first end target position and the first end position error Calculate the second end target position

[0008] As a further optimization of the above-mentioned large hydraulic manipulator end position control method: based on the second end target parameters and dynamic joint values Methods for obtaining the end position error through the second Jacobi iteration and the second error compensation include: For the second end target pose and dynamic joint values Perform the second Jacobi iteration to obtain the second inverse solution joint value For the second inverse solution of joint values Perform DH neatly to get the second end theoretical position The second terminal theoretical position is calculated using the pre-trained error compensation model Compensation is performed to obtain the second error compensation amount And based on the second error compensation amount and the second terminal theoretical position Calculate the actual position of the second end Based on the first end target position and the actual position of the second end Calculate the end position error

[0009] As a further optimization of the above-mentioned large hydraulic manipulator end position control method: the method of training the error compensation model includes: Obtain the joint values ​​and end position errors of the hydraulic manipulator and construct a data set; Divide the dataset into training and validation sets; Use the neural network model as the basis and train it using the training set; After the training is completed, the trained neural network model is verified using the validation set. If the verification is passed, the error compensation model is output, otherwise the training is repeated.

[0010] A large hydraulic manipulator end position control system, comprising: A data acquisition module, used to obtain joint values ​​and first end target parameters of the hydraulic manipulator; Data processing module, used to process data based on the current joint value The first terminal target parameters and the first Jacobian iteration and the first error compensation are sequentially performed based on the second terminal target parameters and the dynamic joint values. After the second Jacobi iteration and the second error compensation; Data output module, used to output optimized control parameters.

[0011] Computer equipment, including: a memory storing a computer program; The processor is used to read the computer program to implement the above-mentioned large hydraulic mechanical arm end position control method.

[0012] The storage medium is used to store a computer program, which, when executed, implements the above-mentioned method for controlling the end position of a large hydraulic mechanical arm.

[0013] Beneficial Effects: This invention uses a double Jacobi iteration to correct the end position of the hydraulic manipulator twice. This double error compensation allows the position of the hydraulic manipulator to be sufficiently close to the target position, effectively improving the control accuracy of the hydraulic manipulator's end position. This can effectively address end position errors caused by material deformation, particularly for large hydraulic manipulators. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flow chart of the present invention; Figure 2 is a comparison diagram of control results in the X-axis direction in an experiment of a specific implementation method; Figure 3 is a comparison diagram of control results in the Y-axis direction in an experiment of a specific implementation method; Figure 4 It is a comparison diagram of control results in the Z-axis direction in the experiment of the specific implementation method. DETAILED DESCRIPTION

[0015] 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 ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0016] like Figure 1 As shown, a large hydraulic manipulator end position control method includes S1 to S6.

[0017] S1. Get the joint value of the hydraulic manipulator and record it as the current joint value Where n is the number of joints of the hydraulic manipulator.

[0018] S2, determine the first end target parameters of the hydraulic manipulator. The first end target parameters include the first end target position and the first terminal target pose

[0019] S3, based on the current joint value The first end target parameter and the first end target parameter are obtained through the first Jacobi iteration and the first error compensation. The method of obtaining the second terminal target parameter by sequentially performing the first Jacobian iteration and the first error compensation on the first terminal target parameter includes:

[0020] S31, the first end target posture and the current joint values Perform the first Jacobi iteration to obtain the first inverse solution joint value

[0021] S32, solve the first inverse joint value Perform DH forward solution to obtain the theoretical position of the first end The DH model of the hydraulic manipulator is as follows Figure 2 shown.

[0022] S33, using the pre-trained error compensation model to calculate the theoretical position of the first terminal Compensation is performed to obtain the first error compensation amount And based on the first error compensation amount and the first end theoretical position Calculate the second end target position

[0023] S34, current joint value Update to get dynamic joint values And for the first end target pose Update to get the second end target pose

[0024] S35, second end target position and the second end target pose The second terminal target parameter is formed. Based on the first error compensation and the first end theoretical position Calculate the second end target position The method includes S351 to S353.

[0025] S351, based on the first error compensation amount and the first end theoretical position Calculate the actual position of the first end

[0026] S352, based on the actual position of the first terminal and the first end target position Calculate the first end position error

[0027] S353, based on the first terminal target position and the first end position error Calculate the second end target position

[0028] S4. Update the joint value of the hydraulic manipulator and record it as the dynamic joint value

[0029] S5, based on the second end target parameters and dynamic joint values The end position error is obtained after the second Jacobi iteration and the second error compensation. Based on the second end target parameters and dynamic joint values Methods for obtaining the end position error through the second Jacobi iteration and the second error compensation include:

[0030] S51, the second end target posture and dynamic joint values Perform the second Jacobi iteration to obtain the second inverse solution joint value

[0031] S52, the second inverse solution joint value Perform DH neatly to get the second end theoretical position

[0032] S53, using the pre-trained error compensation model to calculate the theoretical position of the second terminal Compensation is performed to obtain the second error compensation amount And based on the second error compensation amount and the second terminal theoretical position Calculate the actual position of the second end

[0033] S54, based on the first end target position and the actual position of the second end Calculate the end position error

[0034] S6. Generate optimized control parameters based on the end position error, and control the hydraulic manipulator arm based on the optimized control parameters.

[0035] This invention uses a double Jacobi iteration to correct the end position of the hydraulic manipulator twice. This double error compensation allows the arm to be positioned sufficiently close to the target position, effectively improving the control accuracy of the end position. This can effectively address end position errors caused by material deformation, particularly for large hydraulic manipulators.

[0036] In order to verify the effect of the invention, an experiment was conducted using the rock drilling arm of a rock drilling rig model G3Zi produced by Henan Gengli Engineering Equipment Co., Ltd. as the control object. The experimental results are as follows: Figure 2-4 As shown, in Figure 2-4 In the figure, the present invention is marked as target-corrected double Jacobian iteration, and compared with the traditional single Jacobian iteration technology, it can be seen that the present invention achieves more precise control of the end position of the hydraulic manipulator in the XYZ directions.

[0037] In the present invention, the error compensation model adopts a neural network model, such as a BP neural network model, which belongs to the prior art and its structure and specific operating principle are not described here. On this basis, the method for training the error compensation model is as follows.

[0038] First, the joint values ​​and end position errors of the hydraulic manipulator are obtained, and a dataset is constructed.

[0039] Second, the dataset is divided into training and validation sets.

[0040] Afterwards, the neural network model is used as a basis for training using the training set.

[0041] Finally, after the training is completed, the trained neural network model is verified using the validation set. If the verification passes, the error compensation model is output, otherwise retraining is performed.

[0042] The present invention also provides a large hydraulic mechanical arm end position control system, which includes a data acquisition module, a data processing module and a data output module.

[0043] A data acquisition module, used to obtain joint values ​​and first end target parameters of the hydraulic manipulator;

[0044] Data processing module, used to process data based on the current joint value The first terminal target parameters and the first Jacobian iteration and the first error compensation are sequentially performed based on the second terminal target parameters and the dynamic joint values. After the second Jacobi iteration and the second error compensation;

[0045] Data output module, used to output optimized control parameters.

[0001] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules 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 through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0046] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of the present embodiment according to actual needs.

[0047] The present invention further provides a computer device comprising a memory and a processor.

[0048] A memory storing a computer program.

[0049] The processor is used to read the computer program to implement the above-mentioned large hydraulic mechanical arm end position control method.

[0050] Finally, the present invention provides a storage medium for storing a computer program, which, when executed, implements the above-mentioned method for controlling the end position of a large hydraulic mechanical arm.

[0051] The memory, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon can include an operating system, a computer program, etc., and the storage method can be temporary storage or permanent storage. The operating system is used to manage and control the various hardware devices and computer programs on the electronic device, which can be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program that can be used to complete the adaptive emotion regulation method based on personalized reconfigurable music performed by the electronic device disclosed in any of the aforementioned embodiments, the computer program can further include a computer program that can be used to complete other specific tasks. The processor can adopt a general-purpose processor product based on X86, IA64, RISC, MIPS and ARM architectures.

[0052] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling the end position of a large hydraulic mechanical arm, characterized in that: The steps include: Get the joint value of the hydraulic manipulator and record it as the current joint value Where n is the number of joints of the hydraulic manipulator; determining a first end target parameter of the hydraulic manipulator arm; Based on the current joint values The first terminal target parameter and the first terminal target parameter are successively subjected to the first Jacobi iteration and the first error compensation to obtain the second terminal target parameter; Update the joint values ​​of the hydraulic manipulator and record them as dynamic joint values Based on the second end target parameters and dynamic joint values The end position error is obtained through the second Jacobi iteration and the second error compensation; An optimized control parameter is generated based on the end position error, and the hydraulic robot arm is controlled based on the optimized control parameter.

2. A large hydraulic mechanical arm end position control method as claimed in claim 1, characterized in that: The first end target parameter includes a first end target position and the first terminal target pose Based on the current joint values The method of obtaining the second terminal target parameter by sequentially performing the first Jacobi iteration and the first error compensation with the first terminal target parameter includes: For the first end target pose and the current joint values Perform the first Jacobi iteration to obtain the first inverse solution joint value For the first inverse solution joint value Perform DH positive solution to obtain the theoretical position of the first end The first terminal theoretical position is calculated using the pre-trained error compensation model. Compensation is performed to obtain the first error compensation amount And based on the first error compensation amount and the first terminal theoretical position Calculate the second end target position For the current joint value Update to get dynamic joint values And for the first terminal target pose Update to get the second end target pose Second end target position and the second end target pose Makes up the second terminal target parameter.

3. A large hydraulic mechanical arm end position control method as claimed in claim 2, characterized in that: Based on the first error compensation amount and the first terminal theoretical position Calculate the second end target position The methods include: Based on the first error compensation amount and the first terminal theoretical position Calculate the actual position of the first end Based on the actual position of the first end and the first end target position Calculate the first end position error Based on the first end target position and the first end position error Calculate the second end target position 4. A large hydraulic mechanical arm end position control method as claimed in claim 3, characterized in that: Based on the second end target parameters and dynamic joint values Methods for obtaining the end position error through the second Jacobi iteration and the second error compensation include: For the second end target pose and dynamic joint values Perform the second Jacobi iteration to obtain the second inverse solution joint value For the second inverse solution of joint values Perform DH neatly to get the second end theoretical position The second terminal theoretical position is calculated using the pre-trained error compensation model Compensation is performed to obtain the second error compensation amount And based on the second error compensation amount and the second terminal theoretical position Calculate the actual position of the second end Based on the first end target position and the actual position of the second end Calculate the end position error 5. A large hydraulic mechanical arm end position control method as claimed in any one of claims 2 and 4, characterized in that: The method of training the error compensation model includes: Obtain the joint values ​​and end position errors of the hydraulic manipulator and construct a data set; Divide the dataset into training and validation sets; Take the neural network model as the basis and use the training set for training; After the training is completed, the trained neural network model is verified using the verification set. If the verification passes, the error compensation model is output, otherwise the training is performed again.

6. A large hydraulic mechanical arm end position control system, characterized in that: include: A data acquisition module, used to acquire joint values ​​and first end target parameters of the hydraulic mechanical arm; Data processing module, used to calculate the current joint value The first terminal target parameters and the first terminal target parameters are successively subjected to the first Jacobian iteration and the first error compensation, and based on the second terminal target parameters and dynamic joint values After the second Jacobi iteration and the second error compensation in sequence; Data output module, used to output optimized control parameters.

7. Computer device, characterized in that include: a memory storing a computer program; A processor is used to read the computer program to implement a large hydraulic mechanical arm end position control method as described in any one of claims 1-5.

8. A storage medium, characterized in that Used to store a computer program, which, when executed, implements a large hydraulic mechanical arm end position control method as described in any one of claims 1-5.

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