Robot machining optimization method and machining system based on functional redundancy characteristics

Abstract

The invention relates to the technical field of robot machining, and discloses a robot machining optimization method and system based on functional redundancy characteristics, and the robot machining optimization method comprises the following steps: obtaining a rigidity performance evaluation index # imgabs0 # through formula derivation; and establishing a robot rigidity performance attitude optimization model based on the function redundancy characteristic and the rigidity performance evaluation index # imgabs1 # of the robot. The rigidity performance evaluation index can visually display and evaluate the rigidity performance of the robot in the main shaft direction in real time, and represents the deformation resistance of the tail end of the robot. The method has the advantages that the whole machining system is simple in structure, convenient to operate and easy to program, the calculation speed of the rigidity of the robot machining system is remarkably improved, proposed rigidity performance evaluation indexes have directivity, the precision of the robot machining system is remarkably improved, visualization of the tail end rigidity of the robot machining system is achieved, and the working efficiency of the robot machining system is improved. And the rigidity performance of the robot can be accurately and intuitively evaluated.

Description

Technical Field

[0001] The invention relates to the technical field of robot processing, and in particular to a robot processing optimization method and a processing system based on functional redundancy characteristics. Background Art

[0002] Six-degree-of-freedom industrial robots are increasingly widely used in the fields of optical processing and mechanical processing. Compared with traditional CNC machine tools, they have the advantages of low cost-performance ratio, large workspace, good dexterity, high degree of integration, and multiple degrees of freedom. However, they also inevitably have some disadvantages. For example, regarding the problem of stiffness: the robot has low stiffness, which will produce stress deformation under the action of processing force, significantly reducing the processing accuracy; the robot configuration changes continuously along the processing path, resulting in continuous changes in the stiffness of the robot processing system, making the stress deformation of the workpiece along the processing path inconsistent; the low stiffness feature makes the dynamic characteristics of the robot processing system worse, and the variable stiffness feature causes the dynamics of the robot processing system to be time-varying, making it very difficult to suppress the chatter between the tool and the workpiece.

[0003] In order to compensate for the low rigidity of the robot in the processing system, the robot configuration can be changed through the functional redundancy characteristics of the robot, thereby improving the rigidity of the robot processing system. The robot rigidity performance index can evaluate the rigidity performance of the robot in the spindle direction before processing. If the processing requirements are met, the robot processing can be carried out; if the requirements are not met, the robot redundant axis angle can be adjusted in time to optimize the robot processing plan.

[0004] However, the current indicators for evaluating the stiffness performance of robots include: translational compliance index, ellipsoid volume, processing plane ellipse area and Rayleigh entropy, which are generally not directional and cannot accurately evaluate the stiffness performance in a specific direction under the current posture of the robot. In addition, there are problems such as fuzzy, inaccurate or lost indicator values ​​near the robot's singular posture. The translational compliance index and the processing plane ellipse area index are not smooth, which limits their application in mechanical and optical processing processes, resulting in the above indicators being unable to meet the basic needs of robot processing.

[0005] Based on this, those skilled in the art urgently need to propose a robot processing optimization method based on functional redundancy characteristics to solve the above technical problems. Summary of the invention

[0006] Therefore, the technical problem to be solved by the present invention is to overcome the defects in the above-mentioned prior art, thereby providing a robot processing optimization method and processing system based on functional redundancy characteristics.

[0007] A robot processing optimization method based on functional redundancy characteristics comprises the following steps: The formula is derived to obtain the stiffness performance evaluation index used to represent the stiffness performance in the main axis direction of the robot end ; Evaluation index of functional redundancy characteristics and stiffness performance based on robots , establish the robot stiffness performance posture optimization model; Robot stiffness performance posture optimization model: (12); In the formula, represents the joint angles of the robot, represents the posture of the robot's maximum stiffness performance index, represents the inverse kinematics of the robot, represents the redundant axis angle of the robot machining system, represents the robot posture after inverse kinematics solution, Indicates the robot The angle of the joints, represents the forward kinematics of the robot.

[0008] Preferably, the formula is derived to obtain the stiffness performance evaluation index , specifically including the following steps: The robot Cartesian stiffness matrix is ​​inverted to obtain the flexibility matrix form; Based on the fact that rotation displacement << linear displacement, the coupling submatrix and rotation submatrix in the flexibility matrix are ignored, and the formula for linear displacement is obtained; Substituting the linear displacement formula into the linear displacement formula of the robot end, we get: (7); where is the terminal external force, is the translation submatrix; Will Merge into a new matrix ,get (8), after expansion, it becomes: (10); In the formula, , and Both are matrices Elements of , and For the matrix elements.

[0009] Preferably, the stiffness performance index expression is: (11).

[0010] Preferably, based on the rotation displacement << linear displacement, the coupling submatrix and the rotation submatrix in the flexibility matrix are ignored, and the formula for obtaining the linear displacement specifically includes: Since rotational displacement <<linear displacement, The coupling submatrix and The rotation submatrix is ​​ignored, and the linear displacement is obtained The expression is as follows: (4); Further expansion to: (5).

[0011] Preferably, the linear displacement formula is substituted into the linear displacement formula of the robot end to obtain: (7) Specifically include: is the end external force, assuming that the linear displacement of the robot end is: (6); Substituting formula (4) into formula (6), we get: (7).

[0012] A robot processing system based on functional redundancy characteristics, which uses a robot processing optimization method based on functional redundancy characteristics to realize the visualization of the end stiffness of the robot processing system during operation; The robot processing system comprises: a robot body, an end effector and a workbench, wherein the end effector is fixed to the end flange of the robot body by bolts, and the workpiece is fixed to the workbench by a pressing plate; the end effector processes the workpiece along a preset processing path.

[0013] Preferably, the physical meaning of the stiffness performance evaluation index is the length of the section segment where the center point of the stiffness ellipsoid at the end of the robot intersects the vector in the normal direction of the workpiece on the worktable with the stiffness ellipsoid, expressed as the force required to produce a unit linear displacement in the vector direction.

[0014] The technical solution of the present invention has the following advantages: 1. The processing optimization method provided by the present invention can significantly improve the calculation speed of the stiffness of the robot processing system. The proposed stiffness performance evaluation index is directional, which can significantly improve the accuracy of the robot processing system, realize the visualization of the stiffness of the end of the robot processing system, and can accurately and intuitively evaluate the stiffness performance of the robot.

[0015] 2. The processing system provided by the present invention has a simple structure. The stiffness of the processing system can be optimized by simply changing the angle of the robot's redundant axis. It is easy to operate and easy to program, and can significantly improve the calculation speed of the stiffness of the robot processing system.

[0016] 3. The stiffness performance evaluation index provided by the present invention realizes the solution of robot stiffness in a specific direction, so that the proposed stiffness performance evaluation index has directionality, improves efficiency, eliminates the influence of errors such as the uneven changes of existing indicators and the loss, inaccuracy or ambiguity of indicator values ​​near the singular posture of the robot, and can significantly improve the accuracy of the robot processing system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the robot processing optimization method based on functional redundancy characteristics of the present invention; Figure 2 It is a front axonometric view of the robot processing system of the present invention; Figure 3 This is a rear axonometric view of the robot processing system of the present invention.

[0019] Description of reference numerals: 1-Robot body; 2-End effector; 3-Tool spindle; 4-Motor; 5-Workbench; 6-Flange connector. DETAILED DESCRIPTION

[0020] The technical solution of the present invention will be described clearly and completely below 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 creative work are within the scope of protection of the present invention.

[0021] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0022] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0023] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0024] Example 1 In this embodiment, the robot controller is connected to the industrial computer data through the Ethernet / IP bus; the current position of the robot is obtained, the stiffness ellipsoid of the robot end is solved, and the length of the section segment perpendicular to the workpiece surface direction of the center of the stiffness ellipsoid of the robot end is the force required to produce a unit linear displacement in this direction as the robot stiffness performance evaluation index.

[0025] To this end, this embodiment further discloses a robot processing optimization method based on functional redundancy characteristics, comprising the following steps: The formula is derived to obtain the stiffness performance evaluation index used to represent the stiffness performance in the main axis direction of the robot end ;like Figure 1 As shown, it is a schematic diagram of the robot stiffness performance evaluation index, in which X1, Y1, and Z1 are coordinate axes.

[0026] Evaluation index of functional redundancy characteristics and stiffness performance based on robots , establish the robot stiffness performance posture optimization model; Robot stiffness performance posture optimization model: (12); In the formula, represents the joint angles of the robot, represents the posture of the robot's maximum stiffness performance index, represents the inverse kinematics of the robot, represents the redundant axis angle of the robot machining system, represents the robot posture after inverse kinematics solution, Indicates the robot The angle of the joints, represents the forward kinematics of the robot.

[0027] Specifically: In this embodiment, the formula is derived to obtain the stiffness performance evaluation index , specifically including the following steps: The robot Cartesian stiffness matrix is ​​inverted to obtain the flexibility matrix: The robot Cartesian stiffness matrix is ​​expressed as: (1); is the robot Cartesian stiffness matrix, is the robot Jacobian matrix, is the robot joint stiffness matrix; Formula (1) is expressed in the form of flexibility matrix: (2); is the flexibility matrix of the robot, The inverse matrix of . Decomposed from four flexibility sub-matrices: (3); is the translation submatrix, is the coupling submatrix, is the rotation matrix.

[0028] Based on the rotation displacement << linear displacement, the coupling submatrix and rotation submatrix in the flexibility matrix are ignored, and the linear displacement is obtained The expression is as follows: (4); Further expansion to: (5).

[0029] Substituting the linear displacement formula into the linear displacement formula of the robot end, we get: (7): is the end external force, assuming that the linear displacement of the robot end is: (6); Substituting formula (4) into formula (6), we get: (7).

[0030] Will Merge into a new matrix ,get (8) can be rewritten as: (9); After further expansion: (10); In the formula, , and Both are matrices Elements of , and For the matrix elements.

[0031] Therefore, the stiffness performance index represents the stiffness performance in the main axis direction of the robot end, which is expressed as the length of the section segment perpendicular to the workpiece surface from the center of the stiffness ellipsoid of the robot end, and the force required to produce a unit linear displacement in this direction: (11); As a real-time stiffness performance evaluation index of the robot processing system, it represents the resistance of the robot end to deformation. The larger the value, the smaller the deformation of the robot end and the stronger the stiffness performance. This stiffness performance evaluation index not only quantifies the stiffness performance of the robot end in the spindle direction in real time, but also provides a visual display, providing an evaluation standard for the robot's mechanical and optical processing optimization.

[0032] Example 2 This embodiment further discloses a robot processing system based on functional redundancy characteristics on the basis of embodiment 1. During operation, the robot processing optimization method based on functional redundancy characteristics of embodiment 1 is applied to realize visualization of the end stiffness of the robot processing system. The robot processing system includes: a robot body 1, an end effector 2 and a workbench 5, wherein the end effector 2 is fixed to the end flange of the robot body 1 by bolts, and the workpiece is fixed to the workbench 5 by a pressure plate; the end effector 2 processes the workpiece along a preset processing path.

[0033] In this embodiment, combined with the robot processing system, the physical meaning of the stiffness performance evaluation index is the length of the cross-section segment of the intersection of the center point of the robot end stiffness ellipsoid with the vector in the normal direction of the workpiece on the workbench 5 and the stiffness ellipsoid, expressed as the force required to produce a unit linear displacement in the vector direction.

[0034] Further Figure 2-3 The end effector 2 includes: a motor 4, a flange connector 6 and a tool spindle 3, wherein the flange connector 6 is fixed to the end flange of the robot body 1 by bolts, the motor 4 is installed on the flange connector 6 by bolts, and the tool spindle 3 is connected to the spindle of the motor 4.

[0035] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A robot processing optimization method based on functional redundancy characteristics, characterized in that: The following steps are involved: The formula is derived to obtain the stiffness performance evaluation index used to represent the stiffness performance in the main axis direction of the robot end ; Evaluation index of functional redundancy characteristics and stiffness performance based on robots , establish the robot stiffness performance posture optimization model; Robot stiffness performance posture optimization model: (12)； In the formula, represents the joint angles of the robot, represents the posture of the robot's maximum stiffness performance index, represents the inverse kinematics of the robot, represents the redundant axis angle of the robot machining system, represents the robot posture after inverse kinematics solution, Indicates the robot The angle of the joints, represents the forward kinematics of the robot.

2. The robot processing optimization method based on functional redundancy characteristics according to claim 1 is characterized in that: Formula derivation to obtain stiffness performance evaluation index , specifically including the following steps: The robot Cartesian stiffness matrix is ​​inverted to obtain the flexibility matrix form; Based on the fact that rotation displacement << linear displacement, the coupling submatrix and rotation submatrix in the flexibility matrix are ignored, and the formula for linear displacement is obtained; Substituting the linear displacement formula into the linear displacement formula of the robot end, we get: (7); where is the terminal external force, is the translation submatrix; Will Merge into a new matrix ,get (8), after expansion, it becomes: （10）； In the formula, , and Both are matrices Elements of , and For the matrix elements.

3. The robot processing optimization method based on functional redundancy characteristics according to claim 2 is characterized in that: The stiffness performance index expression is: (11)。 4. The robot processing optimization method based on functional redundancy characteristics according to claim 2 is characterized in that: Based on the rotation displacement << linear displacement, the coupling submatrix and the rotation submatrix in the flexibility matrix are ignored, and the formula for linear displacement is obtained, which includes: Since rotational displacement <<linear displacement, The coupling submatrix and The rotation submatrix is ​​ignored, and the linear displacement is obtained The expression is as follows: (4)； Further expansion to: (5)。 5. The robot processing optimization method based on functional redundancy characteristics according to claim 4 is characterized in that: Substituting the linear displacement formula into the linear displacement formula of the robot end, we get: (7) Specifically include: is the end external force, assuming that the linear displacement of the robot end is: (6)； Substituting formula (4) into formula (6), we get: (7)。 6. A robot processing system based on functional redundancy characteristics, characterized in that: When working, the robot processing optimization method based on functional redundancy characteristics described in claims 1 to 5 is applied to realize the visualization of the end stiffness of the robot processing system; The robot processing system comprises: a robot body (1), an end effector (2) and a workbench (5), wherein the end effector (2) is fixed to an end flange of the robot body (1) by means of bolts, and a workpiece is fixed to the workbench (5) by means of a pressing plate; the end effector (2) processes the workpiece along a preset processing path.

7. The robot processing system based on functional redundancy characteristics according to claim 6 is characterized in that: The physical meaning of the stiffness performance evaluation index is the length of the intersection of the center point of the robot end stiffness ellipsoid with the vector in the normal direction of the workpiece on the worktable (5) and the stiffness ellipsoid, expressed as the force required to produce a unit linear displacement in the vector direction.

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