CN116786326B - Spraying robot operation control method and system - Google Patents
Spraying robot operation control method and system Download PDFInfo
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- CN116786326B CN116786326B CN202311079355.XA CN202311079355A CN116786326B CN 116786326 B CN116786326 B CN 116786326B CN 202311079355 A CN202311079355 A CN 202311079355A CN 116786326 B CN116786326 B CN 116786326B
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- 238000005507 spraying Methods 0.000 title claims abstract description 138
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000012549 training Methods 0.000 claims abstract description 28
- 238000004458 analytical method Methods 0.000 claims abstract description 20
- 238000013507 mapping Methods 0.000 claims description 15
- 239000007921 spray Substances 0.000 claims description 9
- 238000010422 painting Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000013528 artificial neural network Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000009471 action Effects 0.000 description 2
- 239000011248 coating agent Substances 0.000 description 2
- 238000000576 coating method Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B13/00—Machines or plants for applying liquids or other fluent materials to surfaces of objects or other work by spraying, not covered by groups B05B1/00 - B05B11/00
- B05B13/02—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work
- B05B13/04—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation
- B05B13/0431—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation with spray heads moved by robots or articulated arms, e.g. for applying liquid or other fluent material to 3D-surfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/0075—Manipulators for painting or coating
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/1653—Programme controls characterised by the control loop parameters identification, estimation, stiffness, accuracy, error analysis
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Manipulator (AREA)
- Spray Control Apparatus (AREA)
Abstract
The application relates to the technical field of intelligent control, and provides a spraying robot operation control method and system, wherein the method comprises the following steps: acquiring a plurality of degrees of freedom nodes of the spraying robot; when the spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types; the method comprises the steps of obtaining the operation states of the mechanical arm for marking the nodes with multiple degrees of freedom on multiple path types, respectively performing model training, obtaining multiple degrees of freedom control models corresponding to the multiple path types, performing collaborative analysis, outputting multiple collaborative control parameters, performing spraying operation control, solving the technical problem of insufficient path planning precision in the spraying robot operation control, realizing the flexibility and the movable range of the control spraying robot, performing the spraying robot operation control, and improving the technical effect of the path planning precision in the spraying robot operation control.
Description
Technical Field
The application relates to the technical field of intelligent control, in particular to a spraying robot operation control method and system.
Background
With the continuous development of robot technology, control technology, coating technology and sensor technology, support is provided for realizing the spraying operation of a spraying robot, and currently, the spraying robot is widely concentrated in the field of industrial production, such as automobile manufacturing, aviation manufacturing, building coating, ship manufacturing, furniture manufacturing and the like.
The spraying robot operation control can realize the efficient operation of robot, not only can improve production efficiency and quality by a wide margin, also can reduce simultaneously to artifical reliance, reduce the security risk, but spraying robot operation control still has some problems, for example: the problems of insufficient path planning precision, insufficient control algorithm intelligence and the like.
In summary, the prior art has a technical problem that the path planning accuracy in the operation control of the spraying robot is insufficient.
Disclosure of Invention
The application provides a spraying robot operation control method and a system, and aims to solve the technical problem that the path planning precision in the spraying robot operation control in the prior art is insufficient.
In view of the above problems, the present application provides a method and a system for controlling the operation of a spraying robot.
In a first aspect of the present disclosure, a method for controlling operation of a spraying robot is provided, where the method includes: acquiring a plurality of degrees of freedom nodes of a first spraying robot, wherein each degree of freedom node comprises a node with freely rotatable mechanical arm angle; when the first spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types; acquiring the operation states of the mechanical arm on the multiple path types, wherein the operation states of the mechanical arm are marked by the multiple degrees of freedom nodes; respectively performing model training according to the operation states of the mechanical arm of the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types; outputting a plurality of cooperative control parameters based on the plurality of freedom degree control models under the plurality of path types by performing cooperative analysis on the plurality of freedom degree control models; and performing operation control on the first spraying robot according to the cooperative control parameters.
In another aspect of the present disclosure, a spray robot job control system is provided, wherein the system includes: the free degree node acquisition module is used for acquiring a plurality of free degree nodes of the first spraying robot, wherein each free degree node comprises a node with a freely rotatable mechanical arm angle; the path splitting module is used for splitting the preset spraying path when the first spraying robot receives the preset spraying path to obtain multiple path types; the operation state acquisition module is used for acquiring the operation states of the mechanical arm, which are marked with the plurality of degrees of freedom nodes, on the plurality of path types; the model training module is used for respectively carrying out model training according to the operation states of the mechanical arm of the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types; the collaborative analysis module is used for outputting a plurality of collaborative control parameters based on the plurality of freedom degree control models under the plurality of path types by collaborative analysis of the plurality of freedom degree control models; and the operation control module is used for controlling the operation of the first spraying robot according to the plurality of cooperative control parameters.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
due to the adoption of the plurality of degrees of freedom nodes for acquiring the first spraying robot; when the first spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types; acquiring the operation states of the mechanical arm, which are marked with a plurality of degrees of freedom nodes, on a plurality of path types; model training is respectively carried out according to the operation states of the mechanical arm of the nodes with multiple degrees of freedom, multiple degrees of freedom control models corresponding to multiple path types are obtained, collaborative analysis is carried out, multiple collaborative control parameters are output, spraying operation control is carried out, the flexibility and the movable range of the spraying robot are compared, the spraying robot operation control is carried out, and the technical effect of path planning precision in the spraying robot operation control is improved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
Fig. 1 is a schematic diagram of a possible flow chart of a method for controlling operation of a spraying robot according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a possible generation of multiple path types in a spraying robot operation control method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a possible flow of obtaining multiple degrees of freedom control models in a spraying robot operation control method according to an embodiment of the present application;
fig. 4 is a schematic diagram of a possible configuration of a painting robot operation control system according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a degree-of-freedom node acquisition module 100, a path splitting module 200, a job status acquisition module 300, a model training module 400, a collaborative analysis module 500 and a job control module 600.
Detailed Description
The embodiment of the application provides a spray robot operation control method and a system, which solve the technical problem of insufficient path planning precision in spray robot operation control, realize the control of the spray robot operation by contrasting the flexibility and the movable range of the spray robot, and improve the technical effect of the path planning precision in the spray robot operation control.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides a method for controlling an operation of a spraying robot, where the method includes:
s10: acquiring a plurality of degrees of freedom nodes of a first spraying robot, wherein each degree of freedom node comprises a node with freely rotatable mechanical arm angle;
s20: when the first spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types;
as shown in fig. 2, step S20 includes the steps of:
s21: radial identification is carried out on the preset spraying path to obtain a radial horizontal angle;
s22: splitting according to the radial horizontal angle to obtain a unidirectional horizontal path, a unidirectional vertical path, a reciprocating horizontal path and a reciprocating vertical path;
s23: and generating a plurality of path types based on the preset spraying path according to the unidirectional horizontal path, the unidirectional vertical path, the reciprocating horizontal path and the reciprocating vertical path.
Specifically, the control technology is used for realizing control and adjustment of parameters such as a motion track and a motion range of the spraying robot, so that the spraying robot is used for spraying operation and generally comprises a mechanical arm, spraying equipment and a corresponding spraying robot operation control system, the actual motion of the mechanical arm can be used as a side gravity direction by contrast to the spraying robot operation control, and a plurality of mechanical arm rotating points are designed on the mechanical arm in the first spraying robot; the degree of freedom node reflects the flexibility of the robot action and can be represented by the number of linear movement, swinging or rotating actions on the axis of the mechanical arm; and acquiring a plurality of degrees of freedom nodes corresponding to a plurality of movable points of the first spraying robot, wherein each degree of freedom node comprises a node with freely rotatable mechanical arm angle, and the degree of freedom node is a joint or node which can independently move in the mechanical arm. The mechanical arm generally has a plurality of degrees of freedom, and each degree of freedom node controls the motion of the mechanical arm in a specific direction and is a basic unit for the motion of the robot;
the preset spraying paths are set by related technicians in the field, the preset spraying paths are robot motion paths planned in advance before the spraying tasks are started, the track to be followed by the spraying robot in the working process is determined, and the path types are used for distinguishing different spraying tasks; when the first spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types, including: the method comprises the steps that a complex preset path can be converted into a plurality of simple paths, the radial direction of the mechanical arm, namely the direction of an axial lead corresponding to an axis between every two movable points of the mechanical arm, is subjected to radial identification, and a radial horizontal angle is obtained, and is a radial horizontal angle relative to the mechanical arm, so that the preset spraying path is split into different types of paths;
the path types obtained after splitting comprise a unidirectional horizontal path, a unidirectional vertical path, a reciprocating horizontal path and a reciprocating vertical path, wherein the unidirectional horizontal path is used for representing a path moving along the horizontal direction; the unidirectional vertical path is used to characterize the path of movement in the vertical direction; the reciprocating horizontal path is used for representing a path for moving back and forth, and the spraying robot returns to the starting point after advancing a certain distance in the horizontal direction and then advances again; the reciprocating vertical path is used for representing a path for moving back and forth, and the spraying robot returns to the starting point after advancing a certain distance in the vertical direction and then advances again;
according to the unidirectional horizontal path, the unidirectional vertical path, the reciprocating horizontal path and the reciprocating vertical path which are obtained by splitting the preset spraying path, a plurality of different types of paths are generated, which means that the spraying robot can select a proper path type to finish a spraying task according to the characteristics of the preset spraying path, the different types of paths can be suitable for various different spraying scenes, and the complex preset spraying path is split into a plurality of simple paths so as to facilitate the operation of the spraying robot.
S30: acquiring the operation states of the mechanical arm on the multiple path types, wherein the operation states of the mechanical arm are marked by the multiple degrees of freedom nodes;
s40: respectively performing model training according to the operation states of the mechanical arm of the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types;
as shown in fig. 3, step S40 includes the steps of:
s41: data acquisition is carried out on the states of the corresponding mechanical arm under the conditions of the multiple path types, so that a mechanical arm rotation data set is obtained;
s42: acquiring real-time rotation characteristics corresponding to the plurality of degrees of freedom nodes according to the mechanical arm rotation data set;
s43: and performing mapping model training according to the rotation characteristics corresponding to the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types.
Specifically, the mechanical arm operation state is used for representing position, posture and motion information of the mechanical arm during one spraying operation, acquiring the mechanical arm operation state of marking the nodes with the plurality of degrees of freedom on the plurality of path types, wherein a spraying path during one spraying operation is any spraying path in the plurality of path types;
respectively performing model training according to the mechanical arm operation states of the multiple degrees of freedom nodes to obtain multiple degrees of freedom control models corresponding to the multiple path types, wherein the degrees of freedom control models are mathematical models for controlling the mechanical arm to move and are commonly used for predicting and guiding the movement of the rotating points of the mechanical arm according to the mechanical arm operation states and the path types;
based on a data storage unit of a spraying robot operation control system, carrying out data acquisition on the corresponding mechanical arm states under the conditions of the multiple path types to obtain a mechanical arm rotation data set, wherein the mechanical arm rotation data set comprises speeds, accelerations and rotation angular speeds of mechanical arm rotation points defined by the corresponding mechanical arm states under the conditions of the multiple path types;
decomposing in all directions through the mechanical arm rotation data set to obtain real-time rotation characteristics corresponding to the plurality of degrees of freedom nodes, wherein the real-time rotation characteristics comprise real-time rotation angular velocity of a mechanical arm rotation point in the X axis direction, real-time rotation angular velocity of the mechanical arm rotation point in the Y axis direction and real-time rotation angular velocity of the mechanical arm rotation point in the Z axis direction, and meanwhile, the real-time rotation angular velocity in the X axis direction is a component of the rotation angular velocity of the mechanical arm rotation point in the X axis direction, the real-time rotation angular velocity in the Y axis direction is a component of the rotation angular velocity of the mechanical arm rotation point in the Y axis direction and the real-time rotation angular velocity in the Z axis direction is a component of the rotation angular velocity of the mechanical arm rotation point in the Z axis direction;
because one path type corresponds to one free point distribution, a plurality of freedom degree control models are determined according to the rotation characteristics corresponding to a plurality of freedom degree nodes, the freedom degree control models are in one-to-one correspondence with the path types, the feedforward neural network is used as a model basis, the rotation characteristics corresponding to the plurality of freedom degree nodes are used as construction data for carrying out mapping model training, new combination characteristics are constructed through the rotation characteristics corresponding to the plurality of freedom degree nodes and the corresponding time identifiers thereof, the new combination characteristics are transmitted into the feedforward neural network for model convergence learning, a plurality of freedom degree control models corresponding to the plurality of path types are obtained, and model support is provided for predicting and guiding the movement of the rotation points of the mechanical arm.
Step S43 further includes the steps of:
s431: the method for acquiring the degree of freedom control model corresponding to the path type comprises the following steps: obtaining a first rotation characteristic corresponding to a first degree of freedom node in the plurality of degree of freedom nodes and a second rotation characteristic corresponding to a second degree of freedom node;
s432: performing mapping training once based on the first rotation feature and the second rotation feature, outputting control parameters output based on a first degree of freedom node and the second degree of freedom node, fixing the first degree of freedom node, and obtaining a third rotation feature of a third degree of freedom node;
s433: and performing secondary mapping training based on the second rotation characteristic and the third rotation characteristic, and the like until the final degree of freedom node of the plurality of degree of freedom nodes is trained, and outputting a degree of freedom control model corresponding to the path type.
Specifically, the degree of freedom control model corresponds to the path types one by one, and the obtaining of the degree of freedom control model corresponding to the path type comprises the following steps: the method comprises the steps that the mechanical arm motion characteristics of the spraying robot and the degree of freedom control process are sequenced, so that a first rotation characteristic corresponding to a first degree of freedom node in a plurality of degree of freedom nodes and a second rotation characteristic corresponding to a second degree of freedom node are obtained, the data types of the first rotation characteristic and the second rotation characteristic are consistent with real-time rotation characteristics, the first rotation characteristic is the rotation characteristic of the first degree of freedom node under a first path type, the second rotation characteristic is the rotation characteristic of the second degree of freedom node under the first path type, the first degree of freedom node and the second degree of freedom node belong to adjacent degree of freedom nodes, and the first path type is any path type in the plurality of path types;
based on the feedforward neural network as a model, performing primary mapping training based on the first rotation feature and the second rotation feature, outputting control parameters output based on a first degree of freedom node and the second degree of freedom node, taking the first degree of freedom node as a fixed point, determining a second rotation feature corresponding to the second degree of freedom node and a third rotation feature of a third degree of freedom node, and performing secondary mapping training based on the second rotation feature and the third rotation feature; and mapping training is performed by using the sequence of the first degree of freedom node and the second degree of freedom node, the second degree of freedom node and the third degree of freedom node, the third degree of freedom node and the fourth degree of freedom node, the fourth degree of freedom node and the fifth degree of freedom node, and the like until the final degree of freedom node of the plurality of degree of freedom nodes is trained, outputting a degree of freedom control model corresponding to a path type, and disclosing the construction step of the degree of freedom control model.
S50: outputting a plurality of cooperative control parameters based on the plurality of freedom degree control models under the plurality of path types by performing cooperative analysis on the plurality of freedom degree control models;
s60: and performing operation control on the first spraying robot according to the cooperative control parameters.
Step S50 includes the steps of:
s51: analyzing various path types on the preset spraying path, and identifying nodes for switching the path types;
s52: when the node is in path type switching, acquiring real-time control parameters corresponding to a plurality of degree-of-freedom nodes under the real-time path type;
s53: and connecting the degree of freedom control model under the real-time path type with the degree of freedom control model under the switching path type, and carrying out cooperative analysis according to the real-time control parameters to obtain cooperative control parameters.
Specifically, by performing collaborative analysis on the multiple degrees of freedom control models, outputting multiple collaborative control parameters based on the multiple degrees of freedom control models under the multiple path types, where the path type switching node is used for representing a specific position where the path type on a preset spraying path may change, analyzing the multiple path types on the preset spraying path, and identifying the path type switching node, such as switching from a horizontal radial direction to a vertical radial direction;
when the nodes are in path type switching, real-time control parameters corresponding to the plurality of degree-of-freedom nodes under the real-time path type are obtained, wherein the real-time control parameters refer to parameters used for controlling the movement of the mechanical arm in real-time operation, the real-time control parameters comprise, but are not limited to, force and rotational angular velocity applied by the rotation of the rotating point of the mechanical arm in a specific direction, the degree-of-freedom control model under the real-time path type and the degree-of-freedom control model under the path type switching are connected, collaborative analysis is carried out according to the real-time control parameters, collaborative control parameters are obtained, and the collaborative control parameters are used for guiding the coordinated movement of the mechanical arm during path type switching, so that the path switching is performed smoothly.
The embodiment of the application also comprises the following steps:
s541: when the node is in a path type switching node, judging whether the switching path type is a reciprocating path, and if the switching path type is the reciprocating path, calling the cooperative control parameter;
s542: and the cooperative control parameters are reciprocally positioned according to the first positioning module, so that the cooperative control parameters based on the reciprocal paths are obtained.
The embodiment of the application also comprises the following steps:
s543: judging whether the first spraying robot moves along a sliding rail, and if so, connecting a sliding rail control module of the first spraying robot;
s544: and connecting the sliding rail control module with the plurality of freedom degree control models, and outputting optimized cooperative control parameters.
Specifically, the first spraying robot is subjected to operation control according to the plurality of cooperative control parameters: in the first case of the embodiment of the application, when the node is in the path type switching, judging whether the switching path type is a reciprocating path, if the switching path type is judged to be the reciprocating path, the spraying robot operation control system can call the cooperative control parameters obtained before, the reciprocating in the reciprocating path refers to the spraying robot to brush back, the first time is required to be the same as the position of the reciprocating path, the reciprocating path is symmetrical to the mechanical arm operation state in the reciprocating path, the first positioning module is a functional module in the spraying robot operation control system, an embedded positioning sensor is used for positioning the spraying equipment of the spraying robot in real time, and the spraying robot operation control system can carry out reciprocating positioning on the cooperative control parameters according to the information about the current position of the mechanical arm provided by the first positioning module, namely, the mechanical arm is positioned according to the characteristics of the reciprocating path so as to obtain the scene that the spraying robot needs to be repeatedly operated in a specific area based on the reciprocating path;
and performing operation control on the first spraying robot according to the plurality of cooperative control parameters: in the second case of the embodiment of the present application, the motion of the sliding rail refers to the motion of the mechanical arm through the sliding rail, the sliding rail is a linear guide rail motion system, so that the mechanical arm translates on a specific track, whether the first spraying robot moves on the sliding rail is determined, if the first spraying robot moves on the sliding rail, the sliding rail control module of the first spraying robot is connected, the sliding rail control module is used for controlling the motion of the mechanical arm on the sliding rail, the sliding rail control module is connected with the plurality of degrees of freedom control models, and the sliding rail control module is connected to cooperate with the plurality of degrees of freedom control models to output optimized cooperative control parameters when the first spraying robot moves on the sliding rail, so as to optimize the overall performance of the mechanical arm, realize more accurate and efficient mechanical arm motion, and adjust according to specific application and working scenarios, so as to achieve optimal motion performance and task completion quality.
In summary, the method and system for controlling the operation of the spraying robot provided by the embodiment of the application have the following technical effects:
1. due to the adoption of the plurality of degrees of freedom nodes for acquiring the first spraying robot; when the first spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types; acquiring the operation states of the mechanical arm, which are marked with a plurality of degrees of freedom nodes, on a plurality of path types; according to the method and the system for controlling the operation of the spraying robot, the flexibility and the movable range of the spraying robot are compared, the operation control of the spraying robot is carried out, and the technical effect of path planning precision in the operation control of the spraying robot is improved.
2. Because the analysis is carried out on various path types on the preset spraying path, the nodes for switching the path types are identified; when the node is in path type switching, acquiring real-time control parameters corresponding to a plurality of degree-of-freedom nodes under the real-time path type; and connecting the degree of freedom control model under the real-time path type with the degree of freedom control model under the switching path type, and carrying out cooperative analysis according to the real-time control parameters to obtain cooperative control parameters so as to enable the switching path to be carried out smoothly.
Example 2
Based on the same inventive concept as one of the spray robot operation control methods in the foregoing embodiments, as shown in fig. 4, an embodiment of the present application provides a spray robot operation control system, wherein the system includes:
a degree-of-freedom node obtaining module 100, configured to obtain a plurality of degree-of-freedom nodes of the first spraying robot, where each degree-of-freedom node includes a node at which a mechanical arm angle can freely rotate;
the path splitting module 200 is configured to split the preset spraying path when the first spraying robot receives the preset spraying path, so as to obtain multiple path types;
a working state obtaining module 300, configured to obtain a working state of the mechanical arm on the multiple path types, where the working state is identified by the multiple degrees of freedom nodes;
the model training module 400 is configured to perform model training according to the operation states of the mechanical arm of the plurality of degrees of freedom nodes, so as to obtain a plurality of degrees of freedom control models corresponding to the plurality of path types;
the collaborative analysis module 500 is configured to output a plurality of collaborative control parameters based on the plurality of degrees of freedom control models under the plurality of path types by performing collaborative analysis on the plurality of degrees of freedom control models;
the operation control module 600 is configured to perform operation control on the first spraying robot according to the plurality of cooperative control parameters.
Further, the system includes:
the radial horizontal angle obtaining module is used for carrying out radial identification on the preset spraying path to obtain a radial horizontal angle;
the splitting module is used for splitting according to the radial horizontal angle to obtain a unidirectional horizontal path, a unidirectional vertical path, a reciprocating horizontal path and a reciprocating vertical path;
the path type determining module is used for generating multiple path types based on the preset spraying path according to the unidirectional horizontal path, the unidirectional vertical path, the reciprocating horizontal path and the reciprocating vertical path.
Further, the system includes:
the mechanical arm rotation data set obtaining module is used for collecting data of the corresponding mechanical arm states under the conditions of the multiple path types to obtain a mechanical arm rotation data set;
the real-time rotation characteristic acquisition module is used for acquiring real-time rotation characteristics corresponding to the plurality of degrees of freedom nodes according to the mechanical arm rotation data set;
the freedom degree control model obtaining module is used for carrying out mapping model training according to the rotation characteristics corresponding to the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types.
Further, the system includes:
the first rotation characteristic determining module and the second rotation characteristic determining module are used for obtaining a first rotation characteristic corresponding to a first degree of freedom node and a second rotation characteristic corresponding to a second degree of freedom node in the plurality of degree of freedom nodes;
the primary mapping training module is used for carrying out primary mapping training based on the first rotation feature and the second rotation feature, outputting control parameters output based on the first degree of freedom node and the second degree of freedom node, fixing the first degree of freedom node and obtaining a third rotation feature of a third degree of freedom node;
and the secondary mapping training module is used for carrying out secondary mapping training based on the second rotation characteristic and the third rotation characteristic, and the like until the final degree of freedom node of the plurality of degree of freedom nodes is trained, and outputting a degree of freedom control model corresponding to the path type.
Further, the system includes:
the node identification module is used for analyzing various path types on the preset spraying path and identifying nodes for switching the path types;
the real-time control parameter acquisition module is used for acquiring real-time control parameters corresponding to a plurality of degrees of freedom nodes under the real-time path type when the nodes are in path type switching;
and the cooperative control parameter obtaining module is used for connecting the degree of freedom control model under the real-time path type and the degree of freedom control model under the switching path type, and carrying out cooperative analysis according to the real-time control parameters to obtain cooperative control parameters.
Further, the system includes:
the first judging module is used for judging whether the switching path type is a reciprocating path or not when the switching path type is at a node for switching the path type, and calling the cooperative control parameter if the switching path type is the reciprocating path;
and the reciprocating positioning module is used for carrying out reciprocating positioning on the cooperative control parameters according to the first positioning module to obtain the cooperative control parameters based on the reciprocating path.
Further, the system includes:
the second judging module is used for judging whether the first spraying robot moves in a sliding rail mode or not, and if the first spraying robot moves in the sliding rail mode, the second judging module is connected with a sliding rail control module of the first spraying robot;
and the optimized cooperative control parameter output module is used for connecting the slide rail control module with the plurality of degrees of freedom control models and outputting optimized cooperative control parameters.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any method for implementing an embodiment of the present application, without unnecessary limitations.
Further, the first or second may represent not only the order relationship but also a specific concept. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
Claims (8)
1. A method of controlling operation of a painting robot, the method comprising:
acquiring a plurality of degrees of freedom nodes of a first spraying robot, wherein each degree of freedom node comprises a node with freely rotatable mechanical arm angle;
when the first spraying robot receives a preset spraying path, splitting the preset spraying path to obtain multiple path types;
acquiring the operation states of the mechanical arm on the multiple path types, wherein the operation states of the mechanical arm are marked by the multiple degrees of freedom nodes;
respectively performing model training according to the operation states of the mechanical arm of the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types;
outputting a plurality of cooperative control parameters based on the plurality of freedom degree control models under the plurality of path types by performing cooperative analysis on the plurality of freedom degree control models;
and performing operation control on the first spraying robot according to the cooperative control parameters.
2. The method of claim 1, wherein the predetermined spray path is split, the method comprising:
radial identification is carried out on the preset spraying path to obtain a radial horizontal angle;
splitting according to the radial horizontal angle to obtain a unidirectional horizontal path, a unidirectional vertical path, a reciprocating horizontal path and a reciprocating vertical path;
and generating a plurality of path types based on the preset spraying path according to the unidirectional horizontal path, the unidirectional vertical path, the reciprocating horizontal path and the reciprocating vertical path.
3. The method of claim 2, wherein a plurality of degrees of freedom control models corresponding to the plurality of path types are obtained, the method comprising:
data acquisition is carried out on the states of the corresponding mechanical arm under the conditions of the multiple path types, so that a mechanical arm rotation data set is obtained;
acquiring real-time rotation characteristics corresponding to the plurality of degrees of freedom nodes according to the mechanical arm rotation data set;
and performing mapping model training according to the rotation characteristics corresponding to the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types.
4. The method of claim 3, wherein obtaining a degree of freedom control model corresponding to a path type comprises:
obtaining a first rotation characteristic corresponding to a first degree of freedom node in the plurality of degree of freedom nodes and a second rotation characteristic corresponding to a second degree of freedom node;
performing mapping training once based on the first rotation feature and the second rotation feature, outputting control parameters output based on a first degree of freedom node and the second degree of freedom node, fixing the first degree of freedom node, and obtaining a third rotation feature of a third degree of freedom node;
and performing secondary mapping training based on the second rotation characteristic and the third rotation characteristic, and the like until the final degree of freedom node of the plurality of degree of freedom nodes is trained, and outputting a degree of freedom control model corresponding to the path type.
5. The method of claim 1, wherein by collaborative analysis of the plurality of degrees of freedom control models, the method further comprises:
analyzing various path types on the preset spraying path, and identifying nodes for switching the path types;
when the node is in path type switching, acquiring real-time control parameters corresponding to a plurality of degree-of-freedom nodes under the real-time path type;
and connecting the degree of freedom control model under the real-time path type with the degree of freedom control model under the switching path type, and carrying out cooperative analysis according to the real-time control parameters to obtain cooperative control parameters.
6. The method of claim 5, wherein the method further comprises:
when the node is in a path type switching node, judging whether the switching path type is a reciprocating path, and if the switching path type is the reciprocating path, calling the cooperative control parameter;
and the cooperative control parameters are reciprocally positioned according to the first positioning module, so that the cooperative control parameters based on the reciprocal paths are obtained.
7. The method of claim 1, wherein the method further comprises:
judging whether the first spraying robot moves along a sliding rail, and if so, connecting a sliding rail control module of the first spraying robot;
and connecting the sliding rail control module with the plurality of freedom degree control models, and outputting optimized cooperative control parameters.
8. A painting robot job control system for implementing a painting robot job control method as claimed in any one of claims 1 to 7, comprising:
the free degree node acquisition module is used for acquiring a plurality of free degree nodes of the first spraying robot, wherein each free degree node comprises a node with a freely rotatable mechanical arm angle;
the path splitting module is used for splitting the preset spraying path when the first spraying robot receives the preset spraying path to obtain multiple path types;
the operation state acquisition module is used for acquiring the operation states of the mechanical arm, which are marked with the plurality of degrees of freedom nodes, on the plurality of path types;
the model training module is used for respectively carrying out model training according to the operation states of the mechanical arm of the plurality of freedom degree nodes to obtain a plurality of freedom degree control models corresponding to the plurality of path types;
the collaborative analysis module is used for outputting a plurality of collaborative control parameters based on the plurality of freedom degree control models under the plurality of path types by collaborative analysis of the plurality of freedom degree control models;
and the operation control module is used for controlling the operation of the first spraying robot according to the plurality of cooperative control parameters.
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