A high-precision robot arm intelligent control method and device based on redundant joints

Abstract

The application provides a high-precision robot arm intelligent control method and device based on redundant joints, the method comprising: acquiring a planned path of a robot arm; determining discrete path points and corresponding target poses based on the planned path; analyzing the target poses and determining the joint angles of each joint of the robot arm corresponding to the target poses based on gradient projection; and controlling the robot arm according to the joint angles corresponding to each path point. In the application, the angles of the corresponding joints are uniquely determined by analyzing the target poses corresponding to the discrete path points under the condition of acquiring the planned path, thereby improving the end control precision of the joints of the robot arm and solving the problem of low end control precision of the joint space of the robot arm.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of surgical robots, in particular to a high-precision mechanical arm intelligent control method and device based on redundant joints. BACKGROUND

[0002] In a navigation surgery robot, a surgical robot with a redundant mechanical arm has higher flexibility and self-motion characteristics. However, due to this characteristic, the end control precision of the joint space of the mechanical arm is very low. SUMMARY

[0003] The problem solved by the present application is that the end control precision of the joint space of the mechanical arm is very low.

[0004] To solve the above problems, the first aspect of the present application provides a high-precision mechanical arm intelligent control method based on redundant joints, comprising:

[0005] obtaining a planned path of a mechanical arm;

[0006] determining discrete path points and corresponding target poses based on the planned path;

[0007] analyzing the target pose and determining the joint angles of each joint of the mechanical arm corresponding to the target pose based on gradient projection;

[0008] controlling the path of the mechanical arm according to the joint angles corresponding to each path point.

[0009] The second aspect of the present application provides a high-precision mechanical arm intelligent control device based on redundant joints, comprising:

[0010] a path acquisition module for obtaining a planned path of a mechanical arm;

[0011] a pose determination module for determining discrete path points and corresponding target poses based on the planned path;

[0012] an angle analysis module for analyzing the target pose and determining the joint angles of each joint of the mechanical arm corresponding to the target pose based on gradient projection;

[0013] a mechanical arm control module for controlling the path of the mechanical arm according to the joint angles corresponding to each path point.

[0014] The third aspect of the present application provides an electronic device, comprising a memory and a processor.

[0015] The memory is used to store a program.

[0016] The processor is coupled to the memory and is used to execute the program for:

[0017] obtaining a planned path of the robot arm;

[0018] determining discrete path points and corresponding target poses based on the planned path;

[0019] analyzing the target poses, and determining joint angles of each joint of the robot arm corresponding to the target poses based on gradient projection;

[0020] controlling the robot arm according to the joint angles corresponding to each path point.

[0021] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the intelligent control method of the high-precision robot arm based on redundant joints.

[0022] In the present application, in the case of obtaining a planned path, the angles of the corresponding joints are uniquely determined by analyzing the target poses corresponding to the discrete path points, so as to improve the end control precision of the joints of the robot arm, and solve the problem of low end control precision of the joint space of the robot arm. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 a flowchart of the intelligent control method of the high-precision robot arm based on redundant joints according to an embodiment of the present application;

[0024] Figure 2 a flowchart of the angle analysis of the intelligent control method of the high-precision robot arm based on redundant joints according to an embodiment of the present application;

[0025] Figure 3 a structural block diagram of the intelligent control device of the high-precision robot arm based on redundant joints according to an embodiment of the present application;

[0026] Figure 4 a structural block diagram of the electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the above objectives, features and advantages of the present application more apparent and understandable, specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be accurately conveyed to those skilled in the art.

[0028] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in the present application should be understood as the usual meanings understood by those skilled in the art to which the present application belongs.

[0029] In the navigation surgery robot, the surgery robot with the redundant mechanical arm has higher flexibility and self-motion characteristics. However, due to the characteristics, the joint angle corresponding to the planned path of the mechanical arm can only be determined in an iterative manner. The approximate determination will increase the error sharply with the increase of the joint, resulting in low end control precision of the joint space of the mechanical arm.

[0030] In view of the above problems, the application provides a new intelligent control scheme of a high-precision mechanical arm based on a redundant joint, which can effectively implement force guidance and solve the problem that the operator cannot intuitively guide the joint angle to a more appropriate angle in the joint space of the mechanical arm.

[0031] The embodiment of the application provides a high-precision mechanical arm intelligent control method based on a redundant joint. The specific scheme of the method is shown in the method, and the method can be executed by a high-precision mechanical arm intelligent control device based on a redundant joint. The high-precision mechanical arm intelligent control device based on a redundant joint can be integrated in a computer, a server, a computer cluster, a data center and the like. In combination with the flowchart of the high-precision mechanical arm intelligent control method based on a redundant joint according to an embodiment of the application, the high-precision mechanical arm intelligent control method based on a redundant joint comprises the following steps. Figures 1-2 Figure 1 The embodiment of the application provides a high-precision mechanical arm intelligent control method based on a redundant joint. The specific scheme of the method is shown in the method, and the method can be executed by a high-precision mechanical arm intelligent control device based on a redundant joint. The high-precision mechanical arm intelligent control device based on a redundant joint can be integrated in a computer, a server, a computer cluster, a data center and the like. In combination with the flowchart of the high-precision mechanical arm intelligent control method based on a redundant joint according to an embodiment of the application, the high-precision mechanical arm intelligent control method based on a redundant joint comprises the following steps.

[0032] S101, acquiring a planned path of a mechanical arm;

[0033] In the application, the planned path of the mechanical arm is the path passed by the end of the mechanical arm. The specific acquisition method is not limited in the application.

[0034] S102, determining discrete path points and corresponding target poses based on the planned path;

[0035] The planned path of the mechanical arm can be regarded as being composed of continuous discrete points, based on which the planned path can be split into continuous discrete path points.

[0036] In the application, the target pose is the expected pose of the end of the mechanical arm, and the corresponding target pose matrix is usually a 4x4 homogeneous transformation matrix, which contains the position and direction of the end of the mechanical arm in the three-dimensional space.

[0037] S103, analyzing the target pose and determining the joint angle of each joint of the mechanical arm corresponding to the target pose based on gradient projection;

[0038] S104, performing path control on the mechanical arm according to the joint angle corresponding to each path point.

[0039] ​In the present application, the joint angle corresponding to each path point is determined, and the task of path control is to generate a smooth joint angle trajectory between these path points and control the robot arm to reach each path point at the planned speed and time. The specific control method is not described or limited in the present application.

[0040] In the present application, the accuracy of the joint angle corresponding to each path point is determined, thereby improving the accuracy of the entire robot arm control.

[0041] In the present application, in the case of obtaining a planned path, the target pose corresponding to the discrete path point is analyzed, and the angle of the corresponding joint is uniquely determined, thereby realizing the improvement of the end control accuracy of the joint of the robot arm and solving the problem of low end control accuracy in the joint space of the robot arm.

[0042] In one embodiment, in combination with Figure 2 As shown, the S103, analyzing the target pose, determining the joint angle of each joint of the robot arm corresponding to the target pose based on gradient projection, comprises:

[0043] S301, determining a target pose matrix based on the target pose;

[0044] The target pose matrix is a 4x4 homogeneous transformation matrix, which contains the position and direction of the robot arm end in three-dimensional space. The target pose is the desired pose of the robot arm end, and the target pose matrix can be directly determined through the target pose.

[0045] S302, calculating the joint space angle corresponding to the target pose matrix of the robot arm by gradient projection method;

[0046] In the present application, the gradient projection method is used for step-by-step iteration until the joint space angle corresponding to the target pose matrix is obtained. The corresponding joint space angle is an approximate angle with an error.

[0047] S303, fixing the end joint space angle, calculating the end joint target sub-matrix;

[0048] The approximate end joint space angle is obtained by the gradient projection method, and the end joint space angle is set as a known value. Based on the value, the end joint target sub-matrix is calculated.

[0049] The end joint target sub-matrix is the target matrix of the remaining joints (the part of the joint is a non-redundant joint) after removing the end joint.

[0050] S304, calculating a plurality of analytical solutions according to the end joint target sub-matrix, each analytical solution being a set of joint angles;

[0051] Wherein, the end joint target sub-matrix is a target matrix corresponding to the non-redundant robot arm, and analysis on the target matrix can obtain corresponding multiple sets of analytical solutions, which are accurate results without errors.

[0052] In the present application, each set of analytical solutions is a set of joint angles, i.e., angles of each joint of the multiple joints.

[0053] In the present application, after the joint angles of the remaining joints after removing the end joint are determined, the joint angle of the end joint can also be re-determined based on the part (under the condition that the whole target pose matrix of the redundant robot arm is known).

[0054] S305, selecting a set closest to the joint space angle from the multiple sets of analytical solutions as the final joint angle.

[0055] In the present application, the joint space angle is an approximate angle obtained by iteration and has a certain error; the analytical solution is an accurate angle, and selecting a set of analytical solutions closest to the joint space angle can obtain an accurate result while keeping the overall data change small.

[0056] In the present application, the final joint angle includes the analytical solution and the re-determined joint angle of the end joint corresponding to the analytical solution.

[0057] In the present application, analytical solution solving can reduce or even eliminate the cumulative error of numerical iteration method, thereby effectively improving the calculation result accuracy. In addition, in the case where the iterative joint space angle is known, by selecting a set of analytical solutions closest to the joint space angle, the singular configuration of the robot arm can also be obviously avoided.

[0058] In an embodiment, the target pose matrix is:

[0059]

[0060]

[0061] Wherein, is a target pose matrix, is a conversion matrix, is a forward kinematics equation of six joints, p x , p y , p z represents the position coordinates of the robot arm end in space, n x , n y , n z , o x , o y , o z , ax , a y , a z is a rotation matrix parameter of the end of the mechanical arm.

[0062] In an embodiment, the formula for calculating the end joint target sub-matrix is:

[0063]

[0064] wherein, is the end joint target sub-matrix, is the target pose matrix, is the conversion matrix.

[0065] In the present application, the conversion matrix is determined according to the end joint space angle.

[0066] In an embodiment, the formula for calculating the analytical solution is:

[0067]

[0068] θ 23 =atan2(t1,t2)

[0069] θ2=θ 23 -θ3

[0070] θ4=atan2(t3,t4)

[0071] θ5=atan2(s5,c5)

[0072] θ6=atan2(s6,c6)

[0073] wherein θ1, θ2, θ3, θ4, θ5, θ6 are joint angles of the analytical solution, atan2 is a tangent function.a i is the link length in the DH parameter, d i is the link offset in the DH parameter, θ i is the joint angle in the DH parameter, s i is sinθ i , c i is cosθ i , k is a general solution constant, t i is a joint variable.

[0074] In an embodiment, the S302 calculates the joint space angle corresponding to the target pose matrix of the mechanical arm by the gradient projection method, comprising:

[0075] obtaining the physical constraints of the mechanical arm, wherein the physical constraints include the range limit of the joint angle;

[0076] constructing a target function in which a difference between a pose matrix corresponding to the joint space angle and a target pose matrix is minimized;

[0077] obtaining initial joint angles, and calculating a gradient of the target function with respect to the joint angles;

[0078] updating the joint angles based on gradient descent and projecting the joint angles into a feasible region;

[0079] returning to perform the gradient calculation of the target function with respect to the joint angles until a convergence condition is met; and finally updating the joint angles as the joint space angles.

[0080] In the present application, the joint angles of the robot arm are calculated by the gradient projection method so that the end pose matrix reaches the target pose, which is an iterative optimization process. The target function is optimized under the constraint condition so that the end effector / endpoint of the robot arm reaches the desired pose.

[0081] In the present application, the specific steps of calculating the joint space angle corresponding to the target pose matrix of the robot arm by the gradient projection method include:

[0082] First, the degrees of freedom of the robot arm are set to n, and the joint angle vector is θ = 9θ1, θ2, …, θ ； ＝ .

[0083] Secondly, the physical constraints of the robot arm are obtained, so that in each iteration, the joint angles are updated and ensured to meet the physical constraints of the robot arm; the target function is constructed, and the goal in the present application is to find a set of joint angles so that the end pose matrix corresponding to the set of joint angles is as close as possible to the target pose matrix.

[0084] Then, an initial joint angle is selected, which can usually be a default configuration of a robot arm.

[0085] The gradient of the target function with respect to the joint angles is calculated, which is determined based on the Jacobian matrix of the pose matrix with respect to the joint angles, and the difference between the current end pose matrix and the target pose matrix.

[0086] Then, according to the idea of gradient descent method, the joint angles are updated.

[0087] In one embodiment, the update formula of the joint angles is:

[0088]

[0089] where θ 341 is the updated joint angle, θ3 is the joint angle before updating, α3 is the step size, f(θ3) is the target function, is the gradient.​

[0090] Then, the projection operation is performed: a feasible region is constructed based on the physical constraints, and the updated joint angles are projected into the feasible region to ensure that each joint angle is within the allowed range.

[0091] At this time, it is judged: if the gradient of the current iteration is small enough or the change amplitude of the joint angle is small enough, or the value of the objective function is close to zero, it is considered that the algorithm converges, and the final joint angle is returned as the solution; if it has not converged, the gradient of the objective function with respect to the joint angle and the subsequent steps are re-executed, and the next iteration is performed until the convergence condition is reached.

[0092] In this application, through the projection operation, the gradient projection method can handle the constraints of joint angles, and ensure that the solution is always within the physically feasible range.

[0093] In this application, through gradient updating and iteration, the target pose matrix is gradually approximated, and the accuracy of the solution is ensured.

[0094] The embodiment of the application provides a high-precision manipulator intelligent control device based on redundant joints, which is used to execute the high-precision manipulator intelligent control method based on redundant joints described above.

[0095] As shown in Figure 3 The high-precision manipulator intelligent control device based on redundant joints comprises:

[0096] A path acquisition module 101 is configured to acquire a planned path of the manipulator.

[0097] A pose determination module 102 is configured to determine discrete path points and corresponding target poses based on the planned path.

[0098] An angle analysis module 103 is configured to analyze the target pose, and determine joint angles of each joint of the manipulator corresponding to the target pose based on gradient projection.

[0099] A manipulator control module 104 is configured to control the manipulator according to the joint angles corresponding to each path point.

[0100] In an embodiment, the angle analysis module 103 is further configured to:

[0101] Based on the target pose, a target pose matrix is determined; a joint space angle corresponding to the target pose matrix of the robot arm is calculated by a gradient projection method; a target sub-matrix of an end joint is calculated by fixing the end joint space angle; a plurality of analytical solutions are calculated according to the target sub-matrix of the end joint, each analytical solution being a set of joint angles; and a set of joint angles closest to the joint space angle is selected from the plurality of analytical solutions as final joint angles.

[0102] In an embodiment, the target pose matrix is:

[0103]

[0104] wherein, is a target pose matrix, is a conversion matrix, is a forward kinematics equation of six joints, p x , p y , p z represents a position coordinate of the end of the robot arm in space, n x , n y , n z , o x , o y , o z , a x , a y , a z is a rotation matrix parameter of the end of the robot arm.

[0105] In an embodiment, a calculation formula of the target sub-matrix of the end joint is:

[0106]

[0107] wherein, is a target sub-matrix of the end joint, is a target pose matrix, is a conversion matrix.

[0108] In an embodiment, a calculation formula of the analytical solution is:

[0109]

[0110] θ 23 = atan2 (t1, t2)

[0111] θ2= θ 23 - θ3

[0112] θ4= atan2 (t3, t4)

[0113] θ5= atan2 (s5, c5)

[0114] θ6 = atan2(s6, c6)

[0115] wherein θ1, θ2, θ3, θ4, θ5, θ6 are analytical solutions of joint angles, atan2 is a tangent function. i is a link length in DH parameters, d i is a link offset in DH parameters, θ i is a joint angle in DH parameters, s i is sinθ i , c i is cosθ i , k is a general solution constant, t i is a joint variable.

[0116] In an embodiment, the angle analysis module 103 is further configured to:

[0117] obtain physical constraints of the robot arm, the physical constraints including range limits of joint angles; construct an objective function in which a pose matrix corresponding to the joint space angles is closest to a target pose matrix; obtain initial joint angles, calculate a gradient of the objective function with respect to the joint angles; update the joint angles based on gradient descent and project the joint angles into a feasible region; return to perform the gradient calculation of the objective function with respect to the joint angles until a convergence condition is met; and finally update the joint angles as the joint space angles.

[0118] In an embodiment, the update formula of the joint angles is:

[0119]

[0120] wherein θ 341 is an updated joint angle, θ3 is a joint angle before updating, α3 is a step size, f(θ3) is the objective function, is a gradient.

[0121] The above embodiments of the present application provide a high-precision robot arm intelligent control device based on redundant joints, and the high-precision robot arm intelligent control method based on redundant joints provided by the embodiments of the present application has a corresponding relationship, so the specific contents in the device have a corresponding relationship with the high-precision robot arm intelligent control method based on redundant joints, and the specific contents can be referred to in the high-precision robot arm intelligent control method based on redundant joints. This will not be repeated here.

[0122] The high-precision robot arm intelligent control device based on redundant joints provided by the above embodiments of the present application and the high-precision robot arm intelligent control method based on redundant joints provided by the embodiments of the present application have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0123] The internal functions and structures of the intelligent control device of the high-precision redundant-joint robot are described above, such as Figure 4 As shown in the figure, the intelligent control device of the high-precision redundant-joint robot can be implemented as an electronic device, including a memory 301 and a processor 303.

[0124] The memory 301 can be configured to store programs.

[0125] In addition, the memory 301 can also be configured to store other various data to support operations on the electronic device. Examples of these data include instructions for any application or method operating on the electronic device, contact data, phonebook data, messages, pictures, videos, etc.

[0126] The memory 301 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0127] The processor 303 is coupled to the memory 301 and is configured to execute programs in the memory 301 for:

[0128] Obtaining a planned path of the robot arm;

[0129] Determining discrete path points and corresponding target poses based on the planned path;

[0130] Analyzing the target pose and determining the joint angles of each joint of the robot arm corresponding to the target pose based on gradient projection;

[0131] Controlling the robot arm according to the joint angles corresponding to each path point.

[0132] In an embodiment, the processor 303 is further configured to:

[0133] Determine a target pose matrix based on the target pose; calculate the joint space angles of the robot arm corresponding to the target pose matrix by gradient projection method; fix the end joint space angle, calculate the end joint target sub-matrix; calculate a plurality of analytical solutions according to the end joint target sub-matrix, each analytical solution being a set of joint angles; select a set of joint angles closest to the joint space angles from the plurality of analytical solutions as the final joint angles.

[0134] In an embodiment, the target pose matrix is:

[0135]

[0136] wherein, is a target pose matrix, is a transformation matrix, is a forward kinematics equation of six joints, p x , p y , p z denotes the position coordinates of the end of the robot arm in space, n x , n y , n z , o x , o y , o z , a x , a y , a z is a rotation matrix parameter of the end of the robot arm.

[0137] In an embodiment, the calculation formula of the end joint target sub-matrix is:

[0138]

[0139] wherein, is an end joint target sub-matrix, is a target pose matrix, is a transformation matrix.

[0140] In an embodiment, the calculation formula of the analytical solution is:

[0141]

[0142] θ 23 =atan2(t1,t2)

[0143] θ2=θ 23 -θ3

[0144] θ4=atan2(t3,t4)

[0145] θ5=atan2(s5,c5)

[0146] θ6=atan2(s6,c6)

[0147] wherein, θ1, θ2, θ3, θ4, θ5, θ6 are joint angles of the analytical solution, atan2 is a tangent function.a i is a link length in DH parameters, d i is a link offset in DH parameters, θ i is a joint angle in DH parameters, s i is sinθ i , c i is cosθ i , k is a general solution constant, ti is a joint variable.

[0148] In an embodiment, the processor 303 is further configured to:

[0149] obtain physical constraints of the robot arm, the physical constraints comprising range limits of joint angles; construct an objective function in which a difference between a pose matrix corresponding to the joint space angles and a target pose matrix is minimized; obtain initial joint angles, calculate a gradient of the objective function with respect to the joint angles; update the joint angles based on gradient descent and project the joint angles into a feasible region; return to perform the gradient calculation of the objective function with respect to the joint angles until a convergence condition is met; and finally update the joint angles as the joint space angles.

[0150] In an embodiment, the update formula of the joint angles is:

[0151]

[0152] wherein θ 341 is an updated joint angle, θ3 is a joint angle before being updated, α3 is a step size, f(θ3) is the objective function, is a gradient.

[0153] In the present application, the processor is further configured to perform all the processes and steps of the above-mentioned intelligent control method for high-precision robot arm based on redundant joints, and the specific content can be referred to the record in the intelligent control method for high-precision robot arm based on redundant joints, which will not be repeated here.

[0154] In the present application, Figure 4 only some components are shown schematically, and it does not mean that the electronic device only includes Figure 4 the components shown.

[0155] The electronic device provided by the embodiment of the present application has the same beneficial effects as the method adopted, run or implemented by the application program stored therein, based on the same inventive concept as the intelligent control method for high-precision robot arm based on redundant joints provided by the embodiment of the present application.

[0156] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer readable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer usable program code.

[0157] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0158] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0159] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.

[0160] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0161] The memory can include non-persistent memory, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or Flash memory, among others. The memory is an example of computer-readable media.

[0162] The application also provides a computer readable storage medium corresponding to the intelligent control method of high-precision redundant joint-based mechanical arm provided by the foregoing embodiments, and a computer program (i.e., a program product) is stored on the computer readable storage medium. When the computer program is executed by a processor, the intelligent control method of high-precision redundant joint-based mechanical arm provided by any of the foregoing embodiments is executed.

[0163] Computer-readable media includes permanent and non-permanent, movable and non-movable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0164] The computer-readable storage medium provided by the above embodiments of the application has the same beneficial effects as the method adopted, run or implemented by the application program stored therein, based on the same inventive concept.

[0165] It should be noted that in the specification provided herein, a large number of specific details are explained. However, it can be understood that the embodiments of the application can be practiced without these specific details. In some examples, well-known structures and techniques are not shown in detail in order not to obscure the understanding of the present specification.

[0166] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that processes, methods, articles or devices including a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or devices. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0167] The above only describes the embodiments of the application and is not intended to limit the application. The application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the application shall be included in the scope of claims of the application.

Claims

1. A high-precision intelligent control method for a robotic arm based on redundant joints, characterized in that: include: Get the planned path of the robotic arm; Determine discrete path points and corresponding target poses based on the planned path; Analyze the target pose and determine the joint angles of each joint of the robotic arm corresponding to the target pose based on gradient projection; The path of the robotic arm is controlled according to the joint angles corresponding to each path point; The analyzing target pose and determining the joint angles of each joint of the robotic arm corresponding to the target pose based on the gradient projection include: Based on the target pose, determine the target pose matrix; Calculate the joint space angles between the manipulator and the target pose matrix using the gradient projection method; Fix the end joint space angle and calculate the end joint target sub-matrix; According to the terminal joint target sub-matrix, multiple sets of analytical solutions are calculated, each set of analytical solutions is a set of joint angles; Selecting a set of analytical solutions that is closest to the joint space angle from multiple sets of analytical solutions as the final joint angle; The method of calculating the joint space angle corresponding to the manipulator and the target pose matrix by the gradient projection method includes: Acquire physical constraints of the robotic arm, wherein the physical constraints include range limits of joint angles; Constructing an objective function in which the difference between the pose matrix corresponding to the joint space angle and the target pose matrix is ​​minimized; Get the initial joint angle and calculate the gradient of the objective function with respect to the joint angle; Based on gradient descent, the joint angles are updated and projected into the feasible region; Return to execute the gradient calculation of the objective function on the joint angle until the convergence condition is met; the last updated joint angle is the joint space angle.

2. The high-precision robotic arm intelligent control method based on redundant joints according to claim 1 is characterized in that: The calculation formula of the end joint target sub-matrix is: in, is the end joint target sub-matrix, is the target pose matrix, is the transformation matrix.

3. The high-precision robotic arm intelligent control method based on redundant joints according to claim 1 is characterized in that: The update formula of the joint angle is: in, is the updated joint angle, is the joint angle before updating, is the step length, is the objective function, is the gradient.

4. A high-precision intelligent control device for a robotic arm based on redundant joints, characterized in that: include: A path acquisition module is used to obtain the planned path of the robotic arm; A pose determination module is used to determine discrete path points and corresponding target poses based on the planned path; Angle parsing module, which is used to parse the target pose and determine the joint angles of each joint of the robotic arm corresponding to the target pose based on gradient projection; The robot arm control module is used to control the path of the robot arm according to the joint angles corresponding to each path point; The analyzing target pose and determining the joint angles of each joint of the robotic arm corresponding to the target pose based on the gradient projection include: Based on the target pose, determine the target pose matrix; Calculate the joint space angles between the manipulator and the target pose matrix using the gradient projection method; Fix the end joint space angle and calculate the end joint target sub-matrix; According to the terminal joint target sub-matrix, multiple sets of analytical solutions are calculated, each set of analytical solutions is a set of joint angles; Selecting a set of analytical solutions that is closest to the joint space angle from multiple sets of analytical solutions as the final joint angle; The method of calculating the joint space angle corresponding to the manipulator and the target pose matrix by the gradient projection method includes: Acquire physical constraints of the robotic arm, wherein the physical constraints include range limits of joint angles; Constructing an objective function in which the difference between the pose matrix corresponding to the joint space angle and the target pose matrix is ​​minimized; Get the initial joint angle and calculate the gradient of the objective function with respect to the joint angle; Based on gradient descent, the joint angles are updated and projected into the feasible region; Return to execute the gradient calculation of the objective function on the joint angle until the convergence condition is met; the last updated joint angle is the joint space angle.

5. An electronic device, characterized in that: include: memory and processor; The memory is used to store programs; The processor, coupled to the memory, is configured to execute the program to: Get the planned path of the robotic arm; Determine discrete path points and corresponding target poses based on the planned path; Analyze the target pose and determine the joint angles of each joint of the robotic arm corresponding to the target pose based on gradient projection; The path of the robotic arm is controlled according to the joint angles corresponding to each path point; The analyzing target pose and determining the joint angles of each joint of the robotic arm corresponding to the target pose based on the gradient projection include: Based on the target pose, determine the target pose matrix; Calculate the joint space angles between the manipulator and the target pose matrix using the gradient projection method; Fix the end joint space angle and calculate the end joint target sub-matrix; According to the terminal joint target sub-matrix, multiple sets of analytical solutions are calculated, each set of analytical solutions is a set of joint angles; Selecting a set of analytical solutions that is closest to the joint space angle from multiple sets of analytical solutions as the final joint angle; The method of calculating the joint space angle corresponding to the manipulator and the target pose matrix by the gradient projection method includes: Acquire physical constraints of the robotic arm, wherein the physical constraints include range limits of joint angles; Constructing an objective function in which the difference between the pose matrix corresponding to the joint space angle and the target pose matrix is ​​minimized; Get the initial joint angle and calculate the gradient of the objective function with respect to the joint angle; Based on gradient descent, the joint angles are updated and projected into the feasible region; Return to execute the gradient calculation of the objective function on the joint angle until the convergence condition is met; the last updated joint angle is the joint space angle.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the high-precision intelligent control method of a robotic arm based on redundant joints as described in any one of claims 1 to 3.

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