CN117226858B - Coordinated control method and system for industrial multi-axis robot - Google Patents
Coordinated control method and system for industrial multi-axis robot Download PDFInfo
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Abstract
The invention discloses a coordination control method and a coordination control system for an industrial multi-axis robot, which relate to the technical field of intelligent control, and the method comprises the following steps: acquiring a plurality of degrees of freedom nodes of a first industrial robot, acquiring a first preset control track, and determining a base position coordinate and a secondary axis position coordinate; key node identification is carried out on the plurality of freedom degree nodes, a first key node is output, a first preset control track is segmented, and a first segmented track and a second segmented track are output; and taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate to obtain m gesture control parameters of the first segmented track and n gesture control parameters of the second segmented track, and performing multi-axis segmented control. The invention solves the technical problem of low coordination control precision among the shafts of the industrial multi-shaft robot in the prior art, and achieves the technical effect of improving the coordination control precision among the shafts of the industrial multi-shaft robot.
Description
Technical Field
The invention relates to the technical field of intelligent control, in particular to a coordinated control method and system of an industrial multi-axis robot.
Background
Industrial multiaxial robots, also known as single-axis robots, are multipurpose manipulators capable of achieving automatic control, repeatable programming, multiple degrees of freedom, and spatial orthogonal relationship of freedom of movement, and work in a manner that is mainly achieved by completing linear movement along the X, Y, Z axis. However, since the types, the motion axes and the coordinate systems of the multi-axis robots are many, the control parameter setting is easy to be made mistakes, so that the existing multi-axis robots have the problem of insufficient inter-axis coordination control precision.
Disclosure of Invention
The application provides a coordinated control method and a coordinated control system for an industrial multi-axis robot, which are used for solving the technical problem of low coordinated control accuracy among various axes of the industrial multi-axis robot in the prior art.
In a first aspect of the present application, there is provided a coordinated control method of an industrial multi-axis robot, the method comprising: acquiring a plurality of degrees of freedom nodes of a first industrial robot, and generating a plurality of spatial degrees of freedom according to the degrees of freedom intervals corresponding to the plurality of degrees of freedom nodes, wherein the plurality of spatial degrees of freedom are in one-to-one correspondence with the plurality of degrees of freedom nodes; a first preset control track is sent to a control terminal of the first industrial robot; determining a base position coordinate and a secondary axis position coordinate of the first industrial robot, wherein the secondary axis position coordinate is a degree of freedom node of the first industrial robot for executing the tail end space gesture; performing key node identification on the multiple degrees of freedom nodes, and outputting a first key node; segmenting a first preset control track by the first key node, and outputting a segmented track, wherein the segmented track comprises a first segmented track and a second segmented track; taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate, outputting m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track; and performing multi-axis sectional control on the first industrial robot according to the m gesture control parameters and the n gesture control parameters.
In a second aspect of the present application, there is provided a coordinated control system of an industrial multi-axis robot, the system comprising: the degree-of-freedom node acquisition module is used for acquiring a plurality of degree-of-freedom nodes of the first industrial robot and generating a plurality of spatial degrees of freedom according to the degree-of-freedom intervals corresponding to the plurality of degree-of-freedom nodes, wherein the plurality of spatial degrees of freedom are in one-to-one correspondence with the plurality of degree-of-freedom nodes; the first preset control track sending module is used for sending a first preset control track to a control terminal of the first industrial robot; the position coordinate determining module is used for determining a base position coordinate and a secondary axis position coordinate of the first industrial robot, wherein the secondary axis position coordinate is a degree of freedom node of the first industrial robot for executing the tail end space gesture; the first key node output module is used for carrying out key node identification on the plurality of freedom degree nodes and outputting a first key node; the segmented track output module is used for segmenting a first preset control track by the first key node and outputting a segmented track, wherein the segmented track comprises a first segmented track and a second segmented track; the gesture control parameter output module is used for outputting m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track by taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate; the multi-axis sectional control module is used for performing multi-axis sectional control on the first industrial robot according to the m gesture control parameters and the n gesture control parameters.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the application provides a coordination control method of an industrial multi-axis robot, which relates to the technical field of intelligent control, and comprises the steps of obtaining a first preset control track by obtaining a plurality of degrees of freedom nodes of a first industrial robot, and determining a base position coordinate and a secondary axis position coordinate; carrying out key node identification on the multiple degrees of freedom nodes, outputting a first key node, segmenting a first preset control track by the first key node, and outputting a first segmented track and a second segmented track; the base position coordinates are used as initial coordinates, the secondary axis position coordinates are used as target coordinates, m gesture control parameters of a first segmented track and n gesture control parameters of a second segmented track are obtained, multi-axis segmented control is carried out, the technical problem that the coordination control accuracy among the axes of the industrial multi-axis robot is low in the prior art is solved, the coordination control accuracy among the axes of the industrial multi-axis robot is improved, and further the working efficiency and the working quality of the robot are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a coordinated control method of an industrial multi-axis robot according to an embodiment of the present application;
fig. 2 is a schematic flow chart of outputting m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track in the coordinated control method of the industrial multi-axis robot provided in the embodiment of the present application;
fig. 3 is a schematic flow chart of outputting the m attitude control parameters by using the m degree of freedom nodes as control variables in the coordination control method of the industrial multi-axis robot provided in the embodiment of the present application;
fig. 4 is a schematic structural diagram of a coordinated control system of an industrial multi-axis robot according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a degree-of-freedom node acquisition module 11, a first preset control track transmission module 12, a position coordinate determination module 13, a first key node output module 14, a segmented track output module 15, a gesture control parameter output module 16 and a multi-axis segmented control module 17.
Detailed Description
The application provides a coordination control method of an industrial multi-axis robot, which is used for solving the technical problem of low coordination control accuracy among various axes of the industrial multi-axis robot in the prior art.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
As shown in fig. 1, the present application provides a coordinated control method of an industrial multi-axis robot, the method comprising:
s100: acquiring a plurality of degrees of freedom nodes of a first industrial robot, and generating a plurality of spatial degrees of freedom according to the degrees of freedom intervals corresponding to the plurality of degrees of freedom nodes, wherein the plurality of spatial degrees of freedom are in one-to-one correspondence with the plurality of degrees of freedom nodes;
specifically, a plurality of degrees of freedom nodes of a first industrial robot are extracted, the first industrial robot refers to a target robot, the degrees of freedom nodes refer to motion axes of the robot, such as joints of a mechanical arm, and degrees of freedom intervals corresponding to the plurality of degrees of freedom nodes are respectively extracted to generate a plurality of spatial degrees of freedom, wherein the spatial degrees of freedom are degrees of freedom converted in space, such as a rotation angle range and a movable distance, the plurality of spatial degrees of freedom correspond to the plurality of degrees of freedom nodes one by one, and each degree of freedom node has a corresponding spatial degree of freedom.
S200: a first preset control track is sent to a control terminal of the first industrial robot;
optionally, a first preset control track is sent to a control terminal of the first industrial robot, the control terminal controls the first industrial robot to operate according to the first preset control track, the target control terminal is a control system of the target industrial robot, the target industrial robot can be controlled to move according to a specific track to complete a specific work task, the first preset control track is a preset robot moving path in advance, and the control parameter of the first industrial robot is adjusted by controlling the first industrial robot to operate strictly according to the first preset control track, so that coordination precision among all axes of the robot is improved.
S300: determining a base position coordinate and a secondary axis position coordinate of the first industrial robot, wherein the secondary axis position coordinate is a degree of freedom node of the first industrial robot for executing the tail end space gesture;
it should be appreciated that the base position coordinates and the minor axis position coordinates of the first industrial robot, which refer to the position coordinates of the first industrial machine mounting base, are determined by a robot coordinate system, such as an absolute coordinate system, a base coordinate system, a mechanical interface coordinate system, and a tool coordinate system, and the minor axis position coordinates are the degrees of freedom nodes of the first industrial robot for performing the spatial pose of the tip, that is, the coordinates at the joints of the tip, which is the topmost end of the robot arm, such as the gripper of the robot arm, etc., and may be used as references for subsequent adjustments of the robot control parameters.
S400: performing key node identification on the multiple degrees of freedom nodes, and outputting a first key node;
the method includes the steps of identifying key nodes of the plurality of degrees of freedom nodes, searching nodes with larger control force, such as nodes with larger rotation angle and larger displacement, and outputting the nodes as first key nodes, wherein the first key nodes can be used as references for control track segmentation.
Further, step S400 in the embodiment of the present application further includes:
s410: the degree-of-freedom control data acquisition is carried out on the plurality of degree-of-freedom nodes, and a control sample data set is output, wherein the control sample data set comprises control parameters of all nodes and the corresponding controlled attitude change degree of all nodes;
s420: performing attitude change influence evaluation according to the control sample data set, and outputting a plurality of change influence degrees corresponding to the plurality of degree of freedom nodes one by one;
s430: and carrying out key node identification from the plurality of degrees of freedom nodes according to the plurality of variation influence degrees, and outputting a first key node.
The degree-of-freedom control data of the plurality of degree-of-freedom nodes are respectively collected and output as a control sample data set, wherein the control sample data set comprises control parameters of each node, including rotation angles and displacement values, and the corresponding controlled attitude change degree of each node, including angle change and displacement change. And carrying out attitude change influence assessment according to the data in the control sample data set, namely attitude change degree assessment, outputting a plurality of change influence degrees corresponding to the plurality of degree-of-freedom nodes one by one according to the change degrees of angles and displacement, carrying out key node identification on the plurality of degree-of-freedom nodes according to the plurality of change influence degrees, wherein the larger the rotation angle range is, the larger the displacement range is, the larger the change influence degree is, the more key the corresponding degree-of-freedom node is, and selecting the node with the largest change influence degree from the plurality of degree-of-freedom nodes to be output as a first key node, so that the node can be used as a reference for controlling track segmentation.
S500: segmenting the first preset control track by the first key node, and outputting a segmented track, wherein the segmented track comprises a first segmented track and a second segmented track;
in a possible embodiment of the present application, with the first key node as a reference, the first preset control track is segmented to obtain a segmented track, where the segmented track includes a first segmented track and a second segmented track, the first segmented track may be a mechanical arm motion track from the robot base to the first key node portion, the second segmented track may be a mechanical arm motion track from the first key node to the execution end portion of the robot, the first preset control track is segmented into the first segmented track and the second segmented track, and the robot may be subjected to parameter adjustment according to different portions, so as to improve overall control accuracy of the robot.
S600: taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate, outputting m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track;
further, as shown in fig. 2, step S600 in the embodiment of the present application further includes:
s610: determining m degrees of freedom nodes according to the first key nodes and the base of the first industrial robot, wherein the m degrees of freedom nodes comprise the first key nodes;
s620: determining n degrees of freedom nodes according to the first key node and the execution tail end of the first industrial robot;
s630: outputting the m attitude control parameters by taking the first segmented track as a target and the m degrees of freedom nodes as control variables;
s640: and outputting the n attitude control parameters by taking the second segmented track as a target and the n degrees of freedom nodes as control variables.
Optionally, m degrees of freedom nodes are determined according to the first key node and the base of the first industrial robot, that is, the plurality of degrees of freedom nodes of the section of mechanical arm are extracted from the base of the first industrial robot to the mechanical arm part of the first key node, here, m degrees of freedom nodes are assumed, and the m degrees of freedom nodes include the first key node. Similarly, n degrees of freedom nodes are extracted from the first key node to the mechanical arm portion of the execution end of the first industrial robot.
Further, the first segmented track is used as a control target, the m degree-of-freedom nodes are used as control variables, the m degree-of-freedom nodes are controlled to change angles and displacements, the first segmented track is completed, and the angle and displacement control parameters of the m degree-of-freedom nodes are used as m attitude control parameters to be output. And similarly, the second segmented track is completed by taking the second segmented track as a target and the n degrees of freedom nodes as control variables and controlling the n degrees of freedom nodes to change angles and displacements, and the angles and displacement control parameters of the n degrees of freedom nodes are output as n gesture control parameters to obtain m gesture control parameters and n gesture control parameters which can be used as multiaxial segmented control parameters of the first industrial robot.
Further, as shown in fig. 3, step S630 in the embodiment of the present application further includes:
s631: building a posture control model, wherein the posture control model comprises a rotary posture control model and a displacement posture control model, and the rotary posture control model is connected with the displacement posture control model;
s632: inputting the first segmented track and the m degrees of freedom nodes into the gesture control model, outputting angle control vectors and displacement control vectors respectively corresponding to the m degrees of freedom nodes, and outputting the angle control vectors and the displacement control vectors as m gesture control parameters;
s633: the gesture control model sequentially carries out iterative control on the m degrees of freedom nodes, and when the sum of deviation between the previous degree of freedom node and the next degree of freedom node is minimized, the gesture control model converges.
The method comprises the steps of building an attitude control model based on a BP neural network by combining attitude change data of the first industrial robot, wherein the BP neural network is a multi-layer feedforward network trained according to error back propagation, and can adapt to environment, summarize rules, complete certain operation, identification or process control, and enable errors of actual output values and expected output values of the network to be minimized. The gesture control model comprises a rotation gesture control model and a displacement gesture control model, the rotation gesture control model is connected with the displacement gesture control model, the rotation gesture control model is used for optimizing the rotation angle of the robot, and the displacement gesture control model is used for optimizing the displacement of the robot to complete the first preset control track.
Further, the calculating process of the m degrees of freedom node control parameters of the first segmented track may be: inputting the first segmented track and the m degrees of freedom nodes into the gesture control model, respectively calculating the angles and displacements of the degrees of freedom nodes by a rotation gesture control model and a displacement gesture control model of the gesture control model, and outputting angle control vectors and displacement control vectors corresponding to the m degrees of freedom nodes respectively, wherein the angle control vectors and the displacement control vectors are used as the m gesture control parameters. The method comprises the steps that a gesture control model is needed to be used for sequentially carrying out iterative control on m degrees of freedom nodes, namely, control parameter calculation is needed to be carried out on the m degrees of freedom nodes in sequence, when the deviation of motion trajectories at the joint of every two adjacent degrees of freedom nodes is minimum, namely, when the deviation sum of a previous degree of freedom node and a next degree of freedom node is minimum, the gesture control model converges, and the m gesture control parameters of the m degrees of freedom nodes output reach the optimal.
Further, step S640 in the embodiment of the present application further includes:
s641: acquiring real-time position coordinates of the first key node when the gesture execution of the m degrees of freedom nodes in the first segmented track is completed;
s642: and inputting the real-time position coordinates, the second segmented track and the m degrees of freedom nodes into the gesture control model, and outputting angle control vectors and displacement control vectors respectively corresponding to the n degrees of freedom nodes as n gesture control parameters.
When the execution of the first segmented track by the m degree-of-freedom nodes is completed, acquiring real-time position coordinates of the first key node, inputting the real-time position coordinates, the second segmented track and the m degree-of-freedom nodes into the gesture control model, taking the second segmented track as a track target, taking the real-time position coordinates of the first key node as a reference, sequentially carrying out iterative control on the n degree-of-freedom nodes by using the gesture control model, and outputting angle control vectors and displacement control vectors corresponding to the n degree-of-freedom nodes respectively as n gesture control parameters.
S700: and performing multi-axis sectional control on the first industrial robot according to the m gesture control parameters and the n gesture control parameters.
Further, step S700 in the embodiment of the present application further includes:
s710: acquiring initial position coordinates of the second segmented track;
s720: comparing the initial position coordinate with the real-time position coordinate, and outputting a first optimization instruction when the deviation degree of the initial position coordinate and the real-time position coordinate is larger than a preset deviation degree;
s730: and optimizing the m gesture control parameters and the n gesture control parameters by adopting a segmentation optimization algorithm according to the first optimization instruction, and performing multi-axis segmentation control on the first industrial robot according to the optimized parameters.
It should be understood that, the initial position coordinate of the second segment track, that is, the position coordinate of the first key node is obtained, the real-time position coordinate is the real-time position coordinate of the first key node when the execution of the first segment track is completed, the initial position coordinate is compared with the real-time position coordinate, when the deviation degree of the initial position coordinate and the real-time position coordinate is greater than the preset deviation degree, it is indicated that the position deviation of the second segment track and the first segment track at the connection point is greater, and it is necessary to optimize the control parameters of the second segment track and the first segment track respectively, so as to reduce the position deviation of the connection point and achieve the coordinated control of the two parts.
Further, a first optimization instruction is generated, the m gesture control parameters and the n gesture control parameters are optimized according to the first optimization instruction by adopting a segmentation optimization algorithm, the segmentation optimization algorithm is to divide the first industrial robot into two parts according to a first key node, an exemplary method is to fix a base to a mechanical part of the first key node, the second segmentation track is used as a target, the n gesture control parameters are optimized, then fix the first key node to a mechanical part of an execution end, the first segmentation track is used as a target, the m gesture control parameters are optimized, and so on, iteration is continuously performed until the deviation degree of the initial position coordinate and the real-time position coordinate meets a preset deviation degree, multi-axis segmentation control is performed on the first industrial robot according to the optimized parameters, and therefore the coordination control precision among all axes of the industrial multi-axis robot can be improved, and the working efficiency and the working quality of the industrial multi-axis robot are further improved.
Further, the embodiment of the present application further includes step S800, where step S800 further includes:
s810: comparing every two change influences in the plurality of change influences, and judging whether two degrees of freedom nodes with influence differences smaller than a preset influence difference exist or not;
s820: if two degrees of freedom nodes with influence degree differences smaller than the preset influence degree differences exist, outputting a first key node and a second key node;
s830: and segmenting the first preset control track by the first key node and the second key node to output a segmented track, wherein the segmented track comprises a first segmented track, a second segmented track and a third segmented track.
Optionally, the two degrees of freedom nodes with the influence degree difference value smaller than the preset influence degree difference value and the largest influence degree are screened out by comparing every two of the plurality of the change influence degrees, the two degrees of freedom nodes are used as a first key node and a second key node, the first key node and the second key node are used as references, the first preset control track is segmented, three segmented tracks including a first segmented track, a second segmented track and a third segmented track are output, and the robot can be subjected to parameter adjustment according to different parts so as to improve the overall control precision of the robot.
In summary, the embodiments of the present application have at least the following technical effects:
according to the method, a plurality of degrees of freedom nodes of a first industrial robot are obtained, a first preset control track is obtained, and a base position coordinate and a secondary axis position coordinate are determined; carrying out key node identification on the multiple degrees of freedom nodes, outputting a first key node, segmenting a first preset control track by the first key node, and outputting a first segmented track and a second segmented track; and taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate to obtain m gesture control parameters of the first segmented track and n gesture control parameters of the second segmented track, and performing multi-axis segmented control.
The technical effects of improving the coordination control precision among the shafts of the industrial multi-shaft robot and further improving the working efficiency and the working quality of the robot are achieved.
Example two
Based on the same inventive concept as the coordination control method of an industrial multi-axis robot in the foregoing embodiments, as shown in fig. 4, the present application provides a coordination control system of an industrial multi-axis robot, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. Wherein the system comprises:
the degree-of-freedom node obtaining module 11 is configured to obtain a plurality of degree-of-freedom nodes of a first industrial robot, and generate a plurality of spatial degrees of freedom according to degree-of-freedom intervals corresponding to the plurality of degree-of-freedom nodes, where the plurality of spatial degrees of freedom are in one-to-one correspondence with the plurality of degree-of-freedom nodes;
a first preset control track sending module 12, where the first preset control track sending module 12 is configured to send a first preset control track to a control terminal of the first industrial robot;
a position coordinate determining module 13, wherein the position coordinate determining module 13 is configured to determine a base position coordinate and a minor axis position coordinate of the first industrial robot, where the minor axis position coordinate is a degree of freedom node of the first industrial robot for performing a terminal spatial gesture;
the first key node output module 14, where the first key node output module 14 is configured to identify key nodes of the multiple degrees of freedom nodes, and output a first key node;
the segmented track output module 15 is configured to segment a first preset control track with the first key node, and output a segmented track, where the segmented track includes a first segmented track and a second segmented track;
the gesture control parameter output module 16 is configured to output m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track, where the gesture control parameter output module 16 uses the base position coordinate as a start coordinate and the minor axis position coordinate as a target coordinate;
the multi-axis segment control module 17, wherein the multi-axis segment control module 17 is configured to perform multi-axis segment control on the first industrial robot according to the m gesture control parameters and the n gesture control parameters.
Further, the first key node output module 14 is further configured to perform the following steps:
the degree-of-freedom control data acquisition is carried out on the plurality of degree-of-freedom nodes, and a control sample data set is output, wherein the control sample data set comprises control parameters of all nodes and the corresponding controlled attitude change degree of all nodes;
performing attitude change influence evaluation according to the control sample data set, and outputting a plurality of change influence degrees corresponding to the plurality of degree of freedom nodes one by one;
and carrying out key node identification from the plurality of degrees of freedom nodes according to the plurality of variation influence degrees, and outputting a first key node.
Further, the attitude control parameter output module 16 is further configured to perform the following steps:
determining m degrees of freedom nodes according to the first key nodes and the base of the first industrial robot, wherein the m degrees of freedom nodes comprise the first key nodes;
determining n degrees of freedom nodes according to the first key node and the execution tail end of the first industrial robot;
outputting the m attitude control parameters by taking the first segmented track as a target and the m degrees of freedom nodes as control variables;
and outputting the n attitude control parameters by taking the second segmented track as a target and the n degrees of freedom nodes as control variables.
Further, the attitude control parameter output module 16 is further configured to perform the following steps:
building a posture control model, wherein the posture control model comprises a rotary posture control model and a displacement posture control model, and the rotary posture control model is connected with the displacement posture control model;
inputting the first segmented track and the m degrees of freedom nodes into the gesture control model, outputting angle control vectors and displacement control vectors respectively corresponding to the m degrees of freedom nodes, and outputting the angle control vectors and the displacement control vectors as m gesture control parameters;
the gesture control model sequentially carries out iterative control on the m degrees of freedom nodes, and when the sum of deviation between the previous degree of freedom node and the next degree of freedom node is minimized, the gesture control model converges.
Further, the attitude control parameter output module 16 is further configured to perform the following steps:
acquiring real-time position coordinates of the first key node when the gesture execution of the m degrees of freedom nodes in the first segmented track is completed;
and inputting the real-time position coordinates, the second segmented track and the m degrees of freedom nodes into the gesture control model, and outputting angle control vectors and displacement control vectors respectively corresponding to the n degrees of freedom nodes as n gesture control parameters.
Further, the multi-axis segment control module 17 is further configured to perform the following steps:
acquiring initial position coordinates of the second segmented track;
comparing the initial position coordinate with the real-time position coordinate, and outputting a first optimization instruction when the deviation degree of the initial position coordinate and the real-time position coordinate is larger than a preset deviation degree;
and optimizing the m gesture control parameters and the n gesture control parameters by adopting a segmentation optimization algorithm according to the first optimization instruction, and performing multi-axis segmentation control on the first industrial robot according to the optimized parameters.
Further, the system further comprises:
the change influence degree judging module is used for comparing every two change influence degrees in the plurality of change influence degrees and judging whether two degrees of freedom nodes with influence degree difference values smaller than a preset influence degree difference value exist or not;
the key node output module is used for outputting a first key node and a second key node if two degrees of freedom nodes with influence degree differences smaller than the preset influence degree differences exist;
the segmented track output module is used for segmenting the first preset control track by the first key node and the second key node and outputting a segmented track, and the segmented track comprises a first segmented track, a second segmented track and a third segmented track.
It should be noted that the sequence of the embodiments of the present application is merely for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing description of the preferred embodiments of the present application is not intended to limit the invention to the particular embodiments of the present application, but to limit the scope of the invention to the particular embodiments of the present application.
The specification and drawings are merely exemplary of the application and are to be regarded as covering any and all modifications, variations, combinations, or equivalents that are within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (6)
1. A method for coordinated control of an industrial multi-axis robot, the method comprising:
acquiring a plurality of degrees of freedom nodes of a first industrial multi-axis robot, and generating a plurality of spatial degrees of freedom according to the degrees of freedom intervals corresponding to the plurality of degrees of freedom nodes, wherein the plurality of spatial degrees of freedom are in one-to-one correspondence with the plurality of degrees of freedom nodes;
a first preset control track is sent to a control terminal of the first industrial multi-axis robot;
determining a base position coordinate and a secondary axis position coordinate of the first industrial multi-axis robot, wherein the secondary axis position coordinate is a degree of freedom node of the first industrial multi-axis robot for executing the tail end space gesture;
performing key node identification on the multiple degrees of freedom nodes, and outputting a first key node;
segmenting a first preset control track by the first key node, and outputting a segmented track, wherein the segmented track comprises a first segmented track and a second segmented track, the first segmented track is a mechanical arm motion track from a robot base to the first key node part, and the second segmented track is a mechanical arm motion track from the first key node to an execution tail end part of the robot;
taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate, outputting m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track;
performing multi-axis sectional control on the first industrial multi-axis robot according to the m gesture control parameters and the n gesture control parameters;
wherein outputting the m gesture control parameters of the first segmented track and the n gesture control parameters based on the second segmented track, comprises:
determining m degrees of freedom nodes according to the first key nodes and the base of the first industrial multi-axis robot, wherein the m degrees of freedom nodes comprise the first key nodes;
determining n degrees of freedom nodes according to the first key node and the execution tail end of the first industrial multi-axis robot;
outputting the m attitude control parameters by taking the first segmented track as a target and the m degrees of freedom nodes as control variables;
outputting the n attitude control parameters by taking the second segmented track as a target and the n degrees of freedom nodes as control variables;
performing key node identification on the plurality of freedom degree nodes, and outputting a first key node, wherein the method comprises the following steps:
the degree-of-freedom control data acquisition is carried out on the plurality of degree-of-freedom nodes, and a control sample data set is output, wherein the control sample data set comprises control parameters of all nodes and the corresponding controlled attitude change degree of all nodes;
performing attitude change influence evaluation according to the control sample data set, and outputting a plurality of change influence degrees corresponding to the plurality of degree of freedom nodes one by one;
and carrying out key node identification from the plurality of degrees of freedom nodes according to the plurality of variation influence degrees, and outputting a first key node.
2. The method of claim 1, wherein the method further comprises:
comparing every two change influences in the plurality of change influences, and judging whether two degrees of freedom nodes with influence differences smaller than a preset influence difference exist or not;
if two degrees of freedom nodes with influence degree differences smaller than the preset influence degree differences exist, outputting a first key node and a second key node;
and segmenting the first preset control track by the first key node and the second key node to output a segmented track, wherein the segmented track comprises a first segmented track, a second segmented track and a third segmented track.
3. The method of claim 1, wherein the m attitude control parameters are output with the m degree of freedom nodes as control variables, the method comprising:
building a posture control model, wherein the posture control model comprises a rotary posture control model and a displacement posture control model, and the rotary posture control model is connected with the displacement posture control model;
inputting the first segmented track and the m degrees of freedom nodes into the gesture control model, outputting angle control vectors and displacement control vectors respectively corresponding to the m degrees of freedom nodes, and outputting the angle control vectors and the displacement control vectors as m gesture control parameters;
the gesture control model sequentially carries out iterative control on the m degrees of freedom nodes, and when the sum of deviation between the previous degree of freedom node and the next degree of freedom node is minimized, the gesture control model converges.
4. A method as claimed in claim 3, wherein the method further comprises:
acquiring real-time position coordinates of the first key node when the gesture execution of the m degrees of freedom nodes in the first segmented track is completed;
and inputting the real-time position coordinates, the second segmented track and the m degrees of freedom nodes into the gesture control model, and outputting angle control vectors and displacement control vectors respectively corresponding to the n degrees of freedom nodes as n gesture control parameters.
5. The method of claim 4, wherein the method further comprises:
acquiring initial position coordinates of the second segmented track;
comparing the initial position coordinate with the real-time position coordinate, and outputting a first optimization instruction when the deviation degree of the initial position coordinate and the real-time position coordinate is larger than a preset deviation degree;
and optimizing the m gesture control parameters and the n gesture control parameters by adopting a segmentation optimization algorithm according to the first optimization instruction, and performing multi-axis segmentation control on the first industrial multi-axis robot according to the optimized parameters.
6. A coordinated control system of an industrial multi-axis robot, the system comprising:
the degree-of-freedom node acquisition module is used for acquiring a plurality of degree-of-freedom nodes of the first industrial multi-axis robot and generating a plurality of spatial degrees of freedom according to the degree-of-freedom intervals corresponding to the plurality of degree-of-freedom nodes, wherein the plurality of spatial degrees of freedom are in one-to-one correspondence with the plurality of degree-of-freedom nodes;
the first preset control track sending module is used for sending a first preset control track to a control terminal of the first industrial multi-axis robot;
the position coordinate determining module is used for determining a base position coordinate and a secondary axis position coordinate of the first industrial multi-axis robot, wherein the secondary axis position coordinate is a degree of freedom node of the first industrial multi-axis robot for executing the tail end space gesture;
the first key node output module is used for carrying out key node identification on the plurality of freedom degree nodes and outputting a first key node;
the segmented track output module is used for segmenting a first preset control track by the first key node and outputting a segmented track, wherein the segmented track comprises a first segmented track and a second segmented track, the first segmented track is a mechanical arm motion track from a robot base to the first key node part, and the second segmented track is a mechanical arm motion track from the first key node to an execution tail end part of the robot;
the gesture control parameter output module is used for outputting m gesture control parameters of the first segmented track and n gesture control parameters based on the second segmented track by taking the base position coordinate as an initial coordinate and the secondary axis position coordinate as a target coordinate;
the multi-axis sectional control module is used for performing multi-axis sectional control on the first industrial multi-axis robot according to the m gesture control parameters and the n gesture control parameters;
the attitude control parameter output module is further configured to perform the following steps:
determining m degrees of freedom nodes according to the first key nodes and the base of the first industrial multi-axis robot, wherein the m degrees of freedom nodes comprise the first key nodes;
determining n degrees of freedom nodes according to the first key node and the execution tail end of the first industrial multi-axis robot;
outputting the m attitude control parameters by taking the first segmented track as a target and the m degrees of freedom nodes as control variables;
outputting the n attitude control parameters by taking the second segmented track as a target and the n degrees of freedom nodes as control variables;
the first key node output module is further configured to perform the following steps:
the degree-of-freedom control data acquisition is carried out on the plurality of degree-of-freedom nodes, and a control sample data set is output, wherein the control sample data set comprises control parameters of all nodes and the corresponding controlled attitude change degree of all nodes;
performing attitude change influence evaluation according to the control sample data set, and outputting a plurality of change influence degrees corresponding to the plurality of degree of freedom nodes one by one;
and carrying out key node identification from the plurality of degrees of freedom nodes according to the plurality of variation influence degrees, and outputting a first key node.
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