Redundant mechanical arm motion control method, computer equipment and storage medium

Abstract

The invention discloses a motion control method for a redundant mechanical arm, computer equipment and a storage medium, and the motion control method comprises the steps: presetting an expected motion trajectory of an end effector, deducing a trajectory tracking model, and introducing a generalized inverse of a Jacobian matrix of the redundant mechanical arm to rewrite the trajectory tracking model. A joint angular velocity expression of the redundant mechanical arm is obtained, a position error is set, a joint angular velocity model of the redundant mechanical arm is derived, discretization processing is conducted on the joint angular velocity expression of the redundant mechanical arm, generalized inverse of a Jacobian matrix of the redundant mechanical arm is estimated, and therefore a motion control model of the redundant mechanical arm is obtained. And joint angle information and position information when the end effector tracks the expected movement track are obtained and input into a movement control model of the redundant mechanical arm to be processed, the joint angular speed of the redundant mechanical arm is obtained, and therefore the redundant mechanical arm is driven to move, and tracking of a preset target track is completed by the redundant mechanical arm. According to the method, the redundant mechanical arm can be effectively controlled.

Description

Technical Field

[0001] The present invention relates to the technical field of robot arm motion planning and control, and in particular to a redundant robot arm motion control method, computer equipment and storage medium. Background Art

[0002] With the continuous advancement of science and technology, the demand for industrial robots in various industries has increased dramatically. Redundant robotic arms refer to arms whose joints have more degrees of freedom than those required to perform specific tasks. As an important part of industrial automation, such robotic arms have significant advantages such as high precision, high efficiency and flexibility, and are therefore widely used in many fields such as manufacturing, electronics and medical care. In the field of industrial manufacturing, the application of redundant robotic arms has significantly improved production efficiency and effectively reduced production costs. On automated production lines, robotic arms can perform repetitive tasks such as welding, assembly, painting and material handling, greatly reducing the labor intensity of workers. In the electronics industry, redundant robotic arms ensure accurate assembly of parts by achieving precise positioning, thereby improving product quality. In the medical field, redundant robotic arms, with their high-precision operating capabilities, enable doctors to perform difficult operations in remote or minimally invasive environments. In addition, redundant robotic arms also show broad application potential in other fields, and this wide application puts higher requirements on the motion control technology of redundant robotic arms.

[0003] At present, the motion control of redundant manipulators mainly relies on model-driven methods, such as MPC (Model Predictive Control), inverse kinematics control, and adaptive control. These control algorithms are based on known manipulator models to achieve effective motion control. In response to the challenges of multi-input and multi-output systems, the strategy of combining MPC algorithm with adaptive fuzzy control effectively solves the combined control problem between the manipulator and the mobile platform. The introduction of the screw theory also provides a new perspective for manipulator control. The inverse kinematics method for a six-degree-of-freedom manipulator with offset joints proposed based on this theory has been verified to be highly efficient. Although the above methods show good motion control accuracy in simulation or physical experiments, they are highly dependent on the precise model of the manipulator. In actual production applications, factors such as manufacturing errors, factory measurement tolerances, and joint wear during use make it difficult to accurately obtain the kinematic model of the manipulator. Therefore, it is urgent to study a data-driven motion control method independent of the manipulator kinematic model to cope with model uncertainties and external interference in practical applications, thereby improving the adaptability and robustness of control. In recent years, data-driven control methods have become an effective means to deal with model-free or inaccurate model problems because they can learn and adjust system behavior in real time through sensor data. In particular, in redundant robotic arm control, how to effectively estimate the pseudo-inverse (generalized inverse) of the Jacobian matrix has become one of the keys to achieving efficient motion control.

[0004] The present invention is proposed in this context, aiming to dynamically estimate the generalized inverse of the Jacobian matrix through a data-driven method in the absence of an accurate mathematical model for redundant manipulators, thereby achieving adaptive and efficient motion control. To simplify the computational complexity, the present invention directly introduces the generalized inverse operation of the Jacobian matrix, combined with discretization processing, to improve computational efficiency and control accuracy, providing a new solution for the control of redundant manipulators. Summary of the invention

[0005] The present invention aims to dynamically estimate the generalized inverse of the Jacobian matrix through a data-driven method in the absence of an accurate mathematical model for a redundant robotic arm, thereby achieving adaptive and efficient motion control of a redundant robotic arm. The present invention proposes a redundant robotic arm motion control method, which includes the following steps: S1, presetting the initial parameters of the redundant manipulator and the expected motion trajectory of the end effector, constructing and derivatizing the motion trajectory tracking model of the end effector, and obtaining the trajectory tracking model of the end effector on the velocity layer, wherein the trajectory tracking model on the velocity layer includes the Jacobian matrix of the redundant manipulator; S2, introducing the generalized inverse of the Jacobian matrix of the redundant manipulator to rewrite the trajectory tracking model of the end effector on the velocity layer, and obtaining the joint angular velocity expression of the redundant manipulator; S3, setting the position error, and setting the joint angular velocity model of the redundant manipulator according to the position error and the joint angular velocity expression of the redundant manipulator; S4, discretizing the joint angular velocity expression of the redundant robotic arm, estimating the generalized inverse of the Jacobian matrix of the redundant robotic arm according to the discretized joint angular velocity expression, and using the estimated generalized inverse of the Jacobian matrix of the redundant robotic arm and the joint angular velocity model of the redundant robotic arm as the motion control model of the redundant robotic arm; S5, obtaining the joint angle information of the redundant manipulator and the position information of the end effector in the process of tracking the expected motion trajectory through the sensor, inputting the joint angle information of the redundant manipulator, the position information of the end effector and the expected position information into the motion control model of the redundant manipulator for processing, and obtaining the joint angular velocity of the redundant manipulator; S6. The lower computer controller receives and drives the redundant robotic arm to move according to the joint angular velocity of the redundant robotic arm, so that the redundant robotic arm completes tracking of the preset expected motion trajectory.

[0006] Preferably, the trajectory tracking model of the end effector in S1 on the velocity layer is specifically expressed as: ; in, ; ; In the formula, represents the Jacobian matrix of the redundant manipulator, is the joint angle of the redundant robot arm, is the real-time joint angular velocity of the redundant manipulator, is the real-time actual speed of the end effector, is the real-time expected velocity of the end effector, is the mapping function.

[0007] Preferably, the joint angular velocity expression of the redundant manipulator in S2 is specifically expressed as: ; In the formula, is the real-time joint angular velocity of the redundant manipulator, is the generalized inverse of the Jacobian matrix of the redundant manipulator, is the real-time actual speed of the end effector.

[0008] Preferably, S3 specifically includes: S31, calculating the position error of the end effector according to the real-time position and the expected position of the end effector; S32. Based on the neurodynamic theory, the velocity error of the end effector is designed according to the position error of the end effector; S33. Setting a joint angular velocity model of the redundant robotic arm according to the joint angular velocity expression, position error, and velocity error of the redundant robotic arm.

[0009] Preferably, the speed error of the end effector in S32 is specifically expressed as: ; in, is the velocity error of the end effector, Design parameters for neural dynamics, is the activation function, is the position error of the end effector.

[0010] Preferably, the joint angular velocity model of the redundant manipulator in S33 is specifically expressed as: ; In the formula, is the real-time joint angular velocity of the redundant manipulator, is the real-time joint angle of the redundant robot arm, is the generalized inverse of the Jacobian matrix of the redundant manipulator, is the real-time expected velocity of the end effector, represents the activation function, is the real-time actual position of the end effector, is the real-time expected position of the end effector.

[0011] Preferably, in S4, the joint angular velocity expression of the redundant manipulator is discretized, and the generalized inverse of the Jacobian matrix of the redundant manipulator is estimated according to the discretized joint angular velocity expression. The estimated generalized inverse of the Jacobian matrix of the redundant manipulator is specifically expressed as: ; in, , , ; In the formula, and Represent the estimated values ​​of the generalized inverse of the Jacobian matrix of the redundant manipulator at the current moment and the previous moment, respectively. and Respectively represent the actual position of the end effector at the current moment and the previous moment, Indicates the difference between the actual position of the end effector at the current moment and the previous moment, and Respectively represent the joint angles of the redundant manipulator at the current moment and the previous moment, Indicates the difference between the joint angles of the redundant robot arm at the current moment and the previous moment.

[0012] Preferably, the expected motion trajectory of the end effector in S1 is specifically a three-dimensional closed figure.

[0013] The present invention also provides a computer device, including 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 above-mentioned redundant robotic arm motion control method when executing the computer program.

[0014] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned redundant robot arm motion control method are implemented.

[0015] The above-mentioned redundant manipulator motion control method, computer device and storage medium, wherein the motion control method introduces the generalized inverse of the Jacobian matrix, tracks the desired motion trajectory in real time through the redundant manipulator, obtains real-time data during the tracking process, and dynamically estimates the generalized inverse of the Jacobian matrix, which can effectively control the redundant manipulator in the absence of an accurate mathematical model or an inaccurate model. This method not only avoids the complex analytical solution process, but also improves the real-time response capability of the control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of a redundant mechanical arm motion control method in one embodiment of the present invention; Figure 2 is a three-dimensional model diagram of a redundant mechanical arm in one embodiment of the present invention; Figure 3 is a schematic diagram of the moving trajectory of a redundant mechanical arm in one embodiment of the present invention; Figure 4 is a schematic diagram of the error between the actual motion trajectory and the expected trajectory of the redundant robot arm in the x, y, and z directions in one embodiment of the present invention; Figure 5 is a schematic diagram of the overall error between the actual motion trajectory and the expected motion trajectory of the redundant robotic arm in one embodiment of the present invention; Figure 6 is a schematic diagram of joint angles of a redundant mechanical arm in one embodiment of the present invention; Figure 7 Schematic diagram of a generalized inverse estimate of the Jacobian matrix of a redundant manipulator in one embodiment of the present invention; Figure 8 is a schematic diagram of the generalized inverse ideal value of the Jacobian matrix of a redundant manipulator in one embodiment of the present invention; Fig. 9 It is a schematic block diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings.

[0018] See also Figure 1 , Figure 2 and Figure 3 , a redundant robot arm motion control method, the control method comprising the following steps: S1. Preset the initial parameters of the redundant robotic arm and the expected motion trajectory of the end effector, construct the motion trajectory tracking model of the end effector and derive it to obtain the trajectory tracking model of the end effector on the velocity layer, wherein the trajectory tracking model on the velocity layer includes the Jacobian matrix of the redundant robotic arm.

[0019] Figure 2 The UR5 robot arm is specifically shown in FIG. The redundant robot arm includes 6 connecting rods (connecting rod 1 to connecting rod 6) and 6 joints (joint 1 to joint 6) connected in sequence. The 6 connecting rods are connected in sequence through 6 joints. The end effector is installed at the end of connecting rod 6, and its working space is a three-dimensional space. Among them, and represents the robot base coordinate system, and ( ) represents the joint coordinate system of 6 joints (joint 1 to joint 6).

[0020] Trajectory tracking is an important issue in the field of robot control. Its core purpose is to make the end effector of redundant robot arms dimensional task space along the desired trajectory Motion, the expected motion trajectory can be a straight line, a two-dimensional figure or a three-dimensional closed figure. Figure 3 The desired motion trajectory shown in is a three-dimensional closed figure. The posture of the redundant manipulator is determined by the Joint angles Therefore, the real-time position of the end effector of the redundant robot arm can be described by the following expression: (1) in, The end effector is Real-time position in dimensional space, , express Dimensional task space, is a mapping function determined by the mathematical model of the redundant manipulator, is the real-time joint angle of the redundant robot arm.

[0021] In order to enable the end effector to complete the desired trajectory Tracking, that is, satisfying: , taking the derivative of both sides of equation (1) at the same time, we get the trajectory tracking model of the end effector on the velocity layer: (2) In the formula, (2) -1 in, is the Jacobian matrix of the redundant manipulator, , express Dimensional task space, is the real-time joint angular velocity of the redundant manipulator, is the real-time speed of the end effector.

[0022] The trajectory tracking task of the above end effector on the velocity layer is: (2) -2 In the formula, is the preset expected motion trajectory About time The derivative of , which is the desired velocity of the end effector.

[0023] S2. The generalized inverse of the Jacobian matrix of the redundant manipulator is introduced to rewrite the trajectory tracking model of the end effector on the velocity layer to obtain the joint angular velocity expression of the redundant manipulator.

[0024] Specifically, in order to further realize the trajectory tracking task of the end effector in the velocity layer, it is necessary to obtain the real-time joint angular velocity of the redundant manipulator In order to simplify the computational complexity, the generalized inverse (pseudo-inverse matrix) of the Jacobian matrix of the robot is directly introduced for calculation, and the joint angular velocity expression of the redundant robot is obtained: (3) in, (3) -1 In the formula, is the generalized inverse of the Jacobian matrix of the redundant manipulator, is the pseudo-inverse symbol, It is the generalized inverse of the Jacobian matrix of the redundant manipulator that must be calculated in the traditional motion control method. In this application, the generalized inverse of the Jacobian matrix of the redundant manipulator is used. Generalized inverse of the Jacobian matrix in traditional algorithms Make accurate estimates.

[0025] S3. Setting the position error, and setting the joint angular velocity model of the redundant robotic arm according to the position error and the joint angular velocity expression of the redundant robotic arm.

[0026] Furthermore, S3 specifically includes: S31, calculating the position error of the end effector according to the real-time position and the expected position of the end effector. The position error is specifically expressed as follows: (4) In the formula, represents the actual position of the end effector, represents the desired position of the end effector, Represents the position error of the end effector.

[0027] S32. Based on the neurodynamics theory, the velocity error of the end effector is designed according to the position error of the end effector.

[0028] Specifically, the following speed error is designed based on the neurodynamic theory: (5) In the formula, is the derivative of the position error, i.e. the velocity error, Design parameters for neural dynamics, is the activation function.

[0029] S33. Setting a joint angular velocity model of the redundant robotic arm according to the joint angular velocity expression, position error, and velocity error of the redundant robotic arm.

[0030] Specifically, according to the above formulas (3), (4) and (5), the joint angular velocity model of the redundant manipulator can be obtained: (6) In the formula, is the real-time joint angular velocity of the redundant manipulator, is the real-time joint angle of the redundant robot arm, is the generalized inverse of the Jacobian matrix of the redundant manipulator, is the real-time expected velocity of the end effector, represents the activation function, is the real-time actual position of the end effector, is the real-time expected position of the end effector.

[0031] S4. Discretize the joint angular velocity expressions of the redundant robotic arm, estimate the generalized inverse of the Jacobian matrix of the redundant robotic arm based on the discretized joint angular velocity expressions, and use the estimated generalized inverse of the Jacobian matrix of the redundant robotic arm and the joint angular velocity model of the redundant robotic arm as the motion control model of the redundant robotic arm.

[0032] Specifically, in order to facilitate numerical calculation and real-time control, the joint angular velocity expression of the redundant manipulator (corresponding to formula (3)) will be discretized and derived. The process is described as follows: 1) Preset discrete sampling time interval and sampling times ,use and Respectively represent the current moment and the previous moment; 2) According to the current time and the previous moment The actual position of the end effector is calculated at the current moment End effector speed: (7) -1 In the formula, Indicates the end effector at the current moment speed, and They represent the end effector at the current moment. and the previous moment actual location.

[0033] 3) According to the current time and the previous moment The joint angle calculation of the redundant robot arm at the current moment Joint angular velocity of redundant manipulator: (7) -2 In the formula, Indicates the redundant robot arm at the current moment The joint angular velocity, and Respectively represent the redundant robotic arms at the current moment and the previous moment The joint angle.

[0034] 4) According to formulas (7)-1 and (7)-2, the joint angular velocity expression of the redundant manipulator (corresponding to formula (3)) is discretized to obtain the expression of the joint angular velocity change after discretization: (7) The generalized inverse of the Jacobian matrix of the redundant manipulator in the expression of the discretized joint angular velocity change is Make an estimate: (8) in, , , , ; In the formula, and They represent the estimated values ​​of the generalized inverse of the Jacobian matrix of the redundant manipulator at the current moment and the previous moment, respectively, in discrete form. and Respectively represent the actual position of the end effector at the current moment and the previous moment, Indicates the difference between the actual position of the end effector at the current moment and the previous moment, and Respectively represent the joint angles of the redundant manipulator at the current moment and the previous moment, Indicates the difference between the joint angles of the redundant robot arm at the current moment and the previous moment.

[0035] The above formula (6) and formula (8) together constitute the motion control model of the redundant manipulator. In the case of no accurate mathematical model or uncertain model, the generalized inverse of the Jacobian matrix of the manipulator is unknown. Therefore, by processing the historical data and real-time data of the redundant manipulator and the end effector during the motion process through formula (8), the generalized inverse of the Jacobian matrix of the redundant manipulator at the current moment can be accurately estimated. .

[0036] S5. Obtain the joint angle information and position information of the redundant robotic arm during the process of the end effector tracking the expected motion trajectory through sensors, input the joint angle information, position information of the end effector and expected position information of the redundant robotic arm into the motion control model of the redundant robotic arm for processing, and obtain the joint angular velocity of the redundant robotic arm.

[0037] Specifically, the sensors on the redundant manipulators are used to obtain the joint angle information of the redundant manipulators and the position information of the end effector during the process of tracking the desired motion trajectory, including the joint angles of the redundant manipulators at the current moment and the previous moment, and the actual positions of the end effector at the current moment and the previous moment. Referring to formula (8), the difference in joint angles is calculated when the joint angles of the redundant manipulators at the current moment and the previous moment are known. , the actual position of the end effector at the current moment and the previous moment is calculated as the difference between the actual position ,according to , And the generalized inverse of the Jacobian matrix of the redundant manipulator at the previous moment Calculate the generalized inverse of the Jacobian matrix of the redundant manipulator at the current time , where the initial value of the generalized inverse of the Jacobian matrix can be set randomly. Referring to formula (6), according to the generalized inverse of the Jacobian matrix of the redundant manipulator at the current moment , the real-time actual position of the end effector and the real-time desired position of the end effector The real-time joint angular velocity of the redundant robotic arm can be calculated .

[0038] S6. The lower computer controller receives and drives the redundant robotic arm to move according to the joint angular velocity of the redundant robotic arm, so that the redundant robotic arm completes tracking of the preset expected motion trajectory.

[0039] In the present invention application, the real-time position information of the end effector can be obtained only through the sensors on the redundant robotic arm, without calculating or reading the real-time speed of the end effector, thereby effectively reducing the interference effect of speed-level noise.

[0040] Furthermore, a redundant robot arm motion control method in the present invention is simulated and verified.

[0041] Select the UR5 robot and preset the expected trajectory of the UR5 robot as a three-dimensional closed figure (see Figure 3 ), specifically expressed as follows: ; in, Seconds is the task execution time, and the sampling interval is milliseconds, set the initial angles of joints 1 to 6 of the UR5 robot arm to , setting the neural dynamics design parameters to .

[0042] The connecting rod parameters of the UR5 robot are shown in Table 1, which are used to construct the mathematical model of the redundant robot. The mathematical model can be used to determine the mapping function in formula (1) The accurate mathematical model of the redundant manipulator is introduced here to facilitate the generalized inverse of the Jacobian matrix of the redundant manipulator obtained by the technical solution of the present invention (corresponding to Figure 7 ) and the generalized inverse of the Jacobian matrix of the redundant manipulator obtained by the mathematical model (corresponding to Figure 8 ) for comparison.

[0043] Table 1 UR5 robot arm connecting rod parameters ; In Table 1, , , , They respectively represent the joint angle of the redundant robot arm, the length of the common perpendicular line of two adjacent joint axes, the distance along the common axis direction of two adjacent links, and the angle between two adjacent joint axes.

[0044] For relevant experimental data, see Figures 4 to 8 . Figure 4 The actual position of the end effector is shown in Figure 1. , and Position error in direction , and ,from Figure 4 It can be seen that the position error is , and The steady-state errors in the three directions are The order of meters, with high accuracy; Figure 5 The actual motion trajectory of the end effector is shown in Figure 2. , and Overall error in three directions ,from Figure 5 It can be seen that the overall error in the steady state is The order of meters, with high accuracy; Figure 6 is a schematic diagram of the joint angles of the six joints of the robotic arm, where the angles of joint 1, joint 2, joint 3, joint 4, joint 5, and joint 6 are , , , , and ; Figure 7 It is the generalized inverse estimate of the Jacobian matrix that is dynamically updated based on the historical data of the robot and the real-time feedback data, and contains 18 elements of the generalized inverse of the Jacobian matrix; Figure 8 It is the ideal value of the generalized inverse of the Jacobian matrix obtained based on the precise mathematical model of the robot arm. It also contains 18 elements in the generalized inverse of the Jacobian matrix, which is used to represent the benchmark for ideal control.

[0045] Figure 7 and Figure 8Shown are the change curves of each element of the 3×6 Jacobian matrix (this 3×6 Jacobian matrix can map the velocities of the six joints to the linear velocity of the end effector in three-dimensional space) in the task time seconds (a total of 18 elements, represented by J11~J16, J21~J26, and J31~J36 with subscript numbers in the figure).

[0046] The experimental results show that the end effector on the UR5 robot arm successfully completes the tracking of the three-dimensional closed figure and its position is precisely controlled, which verifies the effectiveness and accuracy of the motion control model (Formula (6) and Formula (8)) of the redundant robot arm proposed in this application.

[0047] Compared with the prior art, the above redundant manipulator motion control method proposed in the present invention introduces the generalized inverse of the Jacobian matrix, tracks the desired motion trajectory in real time through the redundant manipulator, obtains real-time data during the tracking process, and dynamically estimates the generalized inverse (pseudo-inverse matrix) of the Jacobian matrix, thereby realizing efficient control of the redundant manipulator. This method can effectively control the redundant manipulator in the absence of an accurate mathematical model or an inaccurate model, not only avoiding the complex analytical solution process, but also improving the real-time response capability of the control system, and improving the control accuracy and anti-noise interference capability of the redundant manipulator, which has important practical significance and broad application prospects in practical applications.

[0048] In one embodiment, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned redundant robotic arm motion control method are implemented. The computer device can be a mobile phone, a tablet, a mobile computer, or any other computer device that can implement a redundant robotic arm motion control.

[0049] In one embodiment, a computer-readable storage medium stores a computer program, which implements the steps of the above-mentioned redundant robot arm motion control method when executed by a processor.

[0050] Specifically, see Fig. 9 , Fig. 9 The figure is a schematic block diagram of a computer device in one embodiment of the present invention.

[0051] The computer device 3 may be a smart phone, tablet computer, laptop computer, desktop computer, etc. that executes a program. The computer device 3 of this embodiment includes at least but is not limited to: a memory 31, a processor 32, and a computer program 33 stored in the memory 31 and executable on the processor 32, which can be connected to each other through a system bus, such as a program corresponding to the above-mentioned redundant robot arm motion control method. It can be understood by those skilled in the art that the schematic diagram is only an example of the computer device 3 and does not constitute a limitation on the computer device 3.

[0052] The memory 31 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 31 may be an internal storage unit of the computer device 1, such as a mobile hard disk of the computer device 3, or an external storage device of the computer device 3, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the computer device 3. The memory 31 may not only be used to store application software and various types of data installed in the computer device 3, such as the program code corresponding to the above-mentioned redundant robot arm motion control method, but also be used to temporarily store data that has been output or is to be output.

[0053] The processor 32 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips. The processor 32 executes the operating system of the computer device 3 and various installed application programs. In this embodiment, the processor 32 executes the computer program 33 stored in the memory 31 to implement a redundant manipulator motion control method disclosed in an embodiment of the present invention.

[0054] Since the aforementioned computer device and computer-readable storage medium both include the aforementioned redundant robotic arm motion control method, they also have the beneficial effects of the control method, which will not be described in detail here.

[0055] The above is a detailed introduction to a redundant robotic arm motion control method, computer device and storage medium provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the core idea of ​​the present invention. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A redundant robotic arm motion control method, characterized in that: The control method comprises: S1, presetting the initial parameters of the redundant manipulator and the expected motion trajectory of the end effector, constructing and derivatizing the motion trajectory tracking model of the end effector, and obtaining the trajectory tracking model of the end effector on the velocity layer, wherein the trajectory tracking model on the velocity layer includes the Jacobian matrix of the redundant manipulator; S2, introducing the generalized inverse of the Jacobian matrix of the redundant manipulator to rewrite the trajectory tracking model of the end effector on the velocity layer, and obtaining the joint angular velocity expression of the redundant manipulator; S3, setting the position error, and setting the joint angular velocity model of the redundant manipulator according to the position error and the joint angular velocity expression of the redundant manipulator; S4, discretizing the joint angular velocity expression of the redundant robotic arm, estimating the generalized inverse of the Jacobian matrix of the redundant robotic arm according to the discretized joint angular velocity expression, and using the estimated generalized inverse of the Jacobian matrix of the redundant robotic arm and the joint angular velocity model of the redundant robotic arm as the motion control model of the redundant robotic arm; S5, obtaining the joint angle information of the redundant manipulator and the position information of the end effector in the process of tracking the expected motion trajectory through the sensor, inputting the joint angle information of the redundant manipulator, the position information of the end effector and the expected position information into the motion control model of the redundant manipulator for processing, and obtaining the joint angular velocity of the redundant manipulator; S6. The lower computer controller receives and drives the redundant robotic arm to move according to the joint angular velocity of the redundant robotic arm, so that the redundant robotic arm completes tracking of the preset expected motion trajectory.

2. The redundant robot arm motion control method according to claim 1, characterized in that: The trajectory tracking model of the end effector in S1 on the velocity layer is specifically expressed as: ； in, ; ； In the formula, represents the Jacobian matrix of the redundant manipulator, is the joint angle of the redundant robot arm, is the real-time joint angular velocity of the redundant manipulator, is the real-time actual speed of the end effector, is the real-time expected velocity of the end effector, is the mapping function.

3. The redundant robot arm motion control method according to claim 2, characterized in that: The joint angular velocity expression of the redundant manipulator in S2 is specifically expressed as: ； In the formula, is the real-time joint angular velocity of the redundant manipulator, is the generalized inverse of the Jacobian matrix of the redundant manipulator, is the real-time actual speed of the end effector.

4. The redundant robot arm motion control method according to claim 3, characterized in that: S3 specifically includes: S31, calculating the position error of the end effector according to the real-time position and the expected position of the end effector; S32. Based on the neurodynamic theory, the velocity error of the end effector is designed according to the position error of the end effector; S33. Setting a joint angular velocity model of the redundant robotic arm according to the joint angular velocity expression, position error, and velocity error of the redundant robotic arm.

5. The redundant robot arm motion control method according to claim 4, characterized in that: The speed error of the end effector in S32 is specifically expressed as: ； in, is the velocity error of the end effector, Design parameters for neural dynamics, is the activation function, is the position error of the end effector.

6. The redundant robot arm motion control method according to claim 5, characterized in that: The joint angular velocity model of the redundant manipulator in S33 is specifically expressed as: ； In the formula, is the real-time joint angular velocity of the redundant manipulator, is the real-time joint angle of the redundant robot arm, is the generalized inverse of the Jacobian matrix of the redundant manipulator, is the real-time expected velocity of the end effector, represents the activation function, is the real-time actual position of the end effector, is the real-time expected position of the end effector.

7. The redundant robot arm motion control method according to claim 6, characterized in that: In S4, the joint angular velocity expression of the redundant manipulator is discretized, and the generalized inverse of the Jacobian matrix of the redundant manipulator is estimated according to the discretized joint angular velocity expression. The estimated generalized inverse of the Jacobian matrix of the redundant manipulator is specifically expressed as: ； in, , , ； In the formula, and Represent the estimated values ​​of the generalized inverse of the Jacobian matrix of the redundant manipulator at the current moment and the previous moment, respectively. and Respectively represent the actual position of the end effector at the current moment and the previous moment, Indicates the difference between the actual position of the end effector at the current moment and the previous moment, and Respectively represent the joint angles of the redundant manipulator at the current moment and the previous moment, Indicates the difference between the joint angles of the redundant robot arm at the current moment and the previous moment.

8. The redundant robot arm motion control method according to claim 7, characterized in that: The desired motion trajectory of the end effector in S1 is specifically a three-dimensional closed figure.

9. A computer 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 redundant robot arm motion control method as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a redundant robot arm motion control method as described in any one of claims 1 to 8 are implemented.

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