CN111013857A - Spraying robot control system and control method - Google Patents
Spraying robot control system and control method Download PDFInfo
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- CN111013857A CN111013857A CN201911267534.XA CN201911267534A CN111013857A CN 111013857 A CN111013857 A CN 111013857A CN 201911267534 A CN201911267534 A CN 201911267534A CN 111013857 A CN111013857 A CN 111013857A
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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
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/12—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus
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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
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
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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
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/085—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to flow or pressure of liquid or other fluent material to be discharged
- B05B12/087—Flow or presssure regulators, i.e. non-electric unitary devices comprising a sensing element, e.g. a piston or a membrane, and a controlling element, e.g. a valve
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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
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/12—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus
- B05B12/122—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus responsive to presence or shape of target
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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
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/12—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus
- B05B12/124—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus responsive to distance between spray apparatus and target
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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
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/12—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus
- B05B12/126—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus responsive to target velocity, e.g. to relative velocity between spray apparatus and target
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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
Abstract
The invention provides a control system and a control method of a spraying robot, belonging to the technical field of spraying robots.A picture acquisition module acquires a spraying picture of a spraying workpiece; analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo; the control module is used for controlling the spraying robot to spray. The invention adopts a method based on machine learning to automatically establish a corresponding spraying area model aiming at a spraying workpiece, can detect the sprayed position in real time and ensure the spraying quality; manual intervention is not needed, and the technical experience requirements of spraying operators are reduced.
Description
Technical Field
The invention relates to the technical field of spraying robots, in particular to a spraying robot control system and a spraying robot control method.
Background
Surface spraying is a vital part in a product processing chain, the quality of manual spraying operation is unstable, a plurality of factors such as spray gun setting and process parameters are determined by manual experience, the quality of the whole product is uneven, in order to ensure that the spraying thickness is uniform and has no dead angle, an operator can repeatedly glaze, a large amount of waste of glaze and low production efficiency are caused, the spraying operation environment is severe, and the long-time work has serious harm to the health of workers.
In recent years, with the popularization of robot application, the requirement on the quality of sprayed products and the continuous improvement of labor cost, a robot automatic spraying system for replacing the traditional manual operation is produced. Spraying is one of the most important applications of robots, and the robot spraying technology is widely applied to hardware, furniture, plastics, war industry, ships and other fields.
The programming mode of the current robot spraying application mainly comprises a teaching programming mode and an off-line programming mode. The existing programming mode of the fixed robot has many limitations such as high site requirement, poor working flexibility, large programming workload and the like in the application of surface spraying, and the spraying quality can not be detected, and the spraying quality meeting the standard can not be ensured.
Along with the development of the machine learning technology, the machine learning technology is applied to the field of spraying robots, so that the spraying quality of a sprayed workpiece is automatically detected in the spraying process, the spraying photos which do not meet the standard are detected and analyzed, and spraying is performed again according to the analysis result, so that the spraying quality can be ensured, and the machine learning technology has a wide application prospect.
Disclosure of Invention
The present invention is directed to a control system and a control method for a painting robot, so as to solve at least one technical problem in the background art.
In order to achieve the purpose, the invention adopts the following technical scheme:
in one aspect, the present invention provides a painting robot control system comprising: the device comprises an image acquisition module, a judgment module and a control module;
the image acquisition module is used for scanning the sprayed workpiece in real time according to a preset scanning path so as to acquire a spraying photo of the sprayed workpiece;
the judging module is used for analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard or not, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo;
the control module is used for optimizing the geometric information to generate a three-dimensional model of a spraying workpiece, generating a position relation between the workpiece and the spraying robot, automatically identifying a spraying area according to the three-dimensional model of the workpiece, calculating a spraying track to form a spraying track file, planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, and controlling the spraying robot to spray.
Preferably, the control module comprises a graph reconstruction unit, a track programming unit, a code generation unit and a spraying unit;
the graphic reconstruction unit is used for optimizing the geometric information to generate a three-dimensional model of the workpiece, generating a position relation between the workpiece and the robot, and performing meshing processing on point cloud data of a certain position of the workpiece sprayed on the spraying picture to obtain a three-dimensional model of a partial area of the workpiece to be sprayed;
the track programming unit is used for automatically identifying a spraying area according to the three-dimensional model and calculating a spraying track to form a spraying track file, selecting a point on the three-dimensional model, planning a scanning plane and a scanning distance, and calculating a scanning track;
the code generating unit is used for planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, automatically planning a scanning path according to a scanning track, and converting the scanning path into a code file which can be executed by a robot;
the spraying unit is used for controlling the spraying robot to execute the spraying action according to the code file corresponding to the spraying path generated by the code generating unit.
Preferably, the trajectory programming unit includes a spraying area recognition module and a spraying trajectory calculation module;
the spraying area identification module is used for optimizing the boundary of a spraying area and removing the noise of the spraying area according to the three-dimensional model by selecting the color characteristics of the spraying area to obtain a three-dimensional model of the workpiece spraying area;
the spraying track calculation module is used for setting spraying process parameters according to the three-dimensional model of the workpiece spraying area generated by the spraying area identification module, and automatically calculating a spraying track strategy meeting process requirements according to the process parameters to obtain a spraying track file.
Preferably, the code generation unit is further configured to collect pose information of the robot in the spraying process, and perform real-time simulation on the whole spraying process; the code generation unit comprises a simulation module and a post-processing module;
the simulation module is used for configuring the position relation between the workpiece and the spraying robot, acquiring a spraying track file generated by the spraying track calculation module, performing interpolation calculation, automatically planning the action path of the robot and simulating the spraying process;
and the post-processing module is used for converting the action path generated by the simulation module into a code file which can be executed by the robot.
Preferably, the spraying track includes a distance relationship between the spray gun and the spraying area, a position, a direction and a speed of the spray gun entering and exiting the spraying area, a starting point and an ending point of the spray gun, a running speed and a spraying amount of the spray gun during the spraying process, and a spraying path of the spray gun.
Preferably, the image acquisition module is an industrial camera.
In another aspect, the present invention also provides a painting robot control method using the control system as described above, including:
acquiring a spraying photo of a spraying workpiece;
analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo;
and optimizing the geometric information to generate a three-dimensional model of the spraying workpiece, generating a position relation between the workpiece and the spraying robot, automatically identifying a spraying area according to the three-dimensional model of the workpiece, calculating a spraying track to form a spraying track file, planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, and controlling the spraying robot to spray.
Preferably, the training of the model using the plurality of sets of training data includes:
taking the workpiece spraying image marked with the spraying standard as a training set;
cutting the training set with corresponding size, and converting the training set into tfrecord format;
extracting detail characteristic information from the training set through continuous hole convolution calculation to obtain a prediction characteristic diagram;
taking the predicted feature map as an input of an ASPP structure, and reducing feature dimensions through a convolution layer;
performing a plurality of groups of cavity convolutions with different sampling rates on the prediction feature map with the reduced feature dimension to extract multi-scale feature information of the image;
fusing the detail characteristic information and the multi-scale characteristic information to obtain more accurate characteristic information as the input of a decoding part;
an improved Xprediction network structure is used as a network backbone of a decoding part, and the feature graph fusing detail feature information and multi-scale feature information is sampled upwards and restored to the size of an original graph;
and deriving the model obtained by training.
Preferably, obtaining the file of the spraying track includes: acquiring the three-dimensional model, optimizing the boundary of the spraying area by picking up the color characteristics of the spraying area, and removing the noise of the spraying area to obtain the three-dimensional model of the workpiece spraying area;
and setting spraying process parameters according to the three-dimensional model of the workpiece spraying area, and automatically calculating a spraying track strategy which meets the process requirements according to the process parameters and a track planning algorithm based on the spraying thickness to obtain a spraying track file.
Preferably, the acquiring the executable code file includes: acquiring the position relation between a workpiece and a robot, and automatically building a virtual working platform; the virtual working platform comprises key information of a real working platform, including a robot model, the position relation between the spray gun and the robot, the position relation between the visual identification unit and the robot and a user coordinate system;
acquiring the spraying track file, calculating the posture of the robot, automatically planning the action path of the robot, and simulating the spraying process;
and converting the action path into a code file which can be executed by the robot.
The invention has the beneficial effects that: by adopting a machine learning-based method, a corresponding spraying area model is automatically established for a spraying workpiece, the sprayed position can be detected in real time, and the spraying quality is ensured; manual intervention is not needed, and the technical experience requirements of spraying operators are reduced.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic block diagram of a control system of a painting robot according to an embodiment of the present invention.
Detailed Description
The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or modules, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, modules, and/or groups thereof.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the convenience of understanding of the embodiments of the present invention, the following description will be further explained by taking specific embodiments as examples with reference to the drawings, and the embodiments are not to be construed as limiting the embodiments of the present invention.
It will be understood by those of ordinary skill in the art that the figures are merely schematic representations of one embodiment and that the elements or devices in the figures are not necessarily required to practice the present invention.
Example 1
As shown in fig. 1, embodiment 1 of the present invention provides a painting robot control system including: the device comprises an image acquisition module, a judgment module and a control module;
the image acquisition module is used for scanning the sprayed workpiece in real time according to a preset scanning path so as to acquire a spraying photo of the sprayed workpiece; in embodiment 1 of the present invention, the image capturing module may use an industrial camera.
The judging module is used for analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard or not, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo;
the control module is used for optimizing the geometric information to generate a three-dimensional model of a spraying workpiece, generating a position relation between the workpiece and the spraying robot, automatically identifying a spraying area according to the three-dimensional model of the workpiece, calculating a spraying track to form a spraying track file, planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, and controlling the spraying robot to spray.
In the embodiment of the invention, the control module comprises a graph reconstruction unit, a track programming unit, a code generation unit and a spraying unit;
the graphic reconstruction unit is used for optimizing the geometric information to generate a three-dimensional model of the workpiece, generating a position relation between the workpiece and the robot, and performing meshing processing on point cloud data of a certain position of the workpiece sprayed on the spraying picture to obtain a three-dimensional model of a partial area of the workpiece to be sprayed;
the track programming unit is used for automatically identifying a spraying area according to the three-dimensional model and calculating a spraying track to form a spraying track file, selecting a point on the three-dimensional model, planning a scanning plane and a scanning distance, and calculating a scanning track;
the code generating unit is used for planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, automatically planning a scanning path according to a scanning track, and converting the scanning path into a code file which can be executed by a robot;
the spraying unit is used for controlling the spraying robot to execute the spraying action according to the code file corresponding to the spraying path generated by the code generating unit.
In a specific embodiment 1 of the present invention, the trajectory programming unit includes a spraying area recognition module and a spraying trajectory calculation module;
the spraying area identification module is used for optimizing the boundary of a spraying area and removing the noise of the spraying area according to the three-dimensional model by selecting the color characteristics of the spraying area to obtain a three-dimensional model of the workpiece spraying area;
the spraying track calculation module is used for setting spraying process parameters according to the three-dimensional model of the workpiece spraying area generated by the spraying area identification module, and automatically calculating a spraying track strategy meeting process requirements according to the process parameters to obtain a spraying track file.
In a specific embodiment 1 of the present invention, the code generating unit is further configured to collect pose information of the robot during a spraying process, and perform real-time simulation on the entire spraying process; the code generation unit comprises a simulation module and a post-processing module;
the simulation module is used for configuring the position relation between the workpiece and the spraying robot, acquiring a spraying track file generated by the spraying track calculation module, performing interpolation calculation, automatically planning the action path of the robot and simulating the spraying process;
and the post-processing module is used for converting the action path generated by the simulation module into a code file which can be executed by the robot.
In an embodiment 1 of the present invention, the spraying track includes a distance relationship between the spray gun and the spraying area, a position, a direction and a speed of the spray gun entering and exiting the spraying area, a starting point and an ending point of the spray gun, a running speed and a spraying amount of the spray gun during the spraying process, and a spraying path of the spray gun.
Example 2
An embodiment 2 of the present invention provides a method for controlling a spray robot, including:
acquiring a spraying photo of a spraying workpiece;
analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo;
and optimizing the geometric information to generate a three-dimensional model of the spraying workpiece, generating a position relation between the workpiece and the spraying robot, automatically identifying a spraying area according to the three-dimensional model of the workpiece, calculating a spraying track to form a spraying track file, planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, and controlling the spraying robot to spray.
In embodiment 2 of the present invention, the obtaining the model by training using multiple sets of training data includes:
taking the workpiece spraying image marked with the spraying standard as a training set;
cutting the training set with corresponding size, and converting the training set into tfrecord format;
extracting detail characteristic information from the training set through continuous hole convolution calculation to obtain a prediction characteristic diagram;
taking the predicted feature map as an input of an ASPP structure, and reducing feature dimensions through a convolution layer;
performing a plurality of groups of cavity convolutions with different sampling rates on the prediction feature map with the reduced feature dimension to extract multi-scale feature information of the image;
fusing the detail characteristic information and the multi-scale characteristic information to obtain more accurate characteristic information as the input of a decoding part;
an improved Xprediction network structure is used as a network backbone of a decoding part, and the feature graph fusing detail feature information and multi-scale feature information is sampled upwards and restored to the size of an original graph;
and deriving the model obtained by training.
In embodiment 2, obtaining the file of the spraying trajectory includes: acquiring the three-dimensional model, optimizing the boundary of the spraying area by picking up the color characteristics of the spraying area, and removing the noise of the spraying area to obtain the three-dimensional model of the workpiece spraying area;
and setting spraying process parameters according to the three-dimensional model of the workpiece spraying area, and automatically calculating a spraying track strategy which meets the process requirements according to the process parameters and a track planning algorithm based on the spraying thickness to obtain a spraying track file.
In embodiment 2 of the present invention, acquiring an executable code file includes: acquiring the position relation between a workpiece and a robot, and automatically building a virtual working platform; the virtual working platform comprises key information of a real working platform, including a robot model, the position relation between the spray gun and the robot, the position relation between the visual identification unit and the robot and a user coordinate system;
acquiring the spraying track file, calculating the posture of the robot, automatically planning the action path of the robot, and simulating the spraying process;
and converting the action path into a code file which can be executed by the robot.
In summary, the control system of the painting robot according to the embodiment of the present invention includes: the device comprises an image acquisition module, a judgment module and a control module; the image acquisition module is used for scanning the sprayed workpiece in real time according to a preset scanning path so as to acquire a spraying photo of the sprayed workpiece; the judging module is used for analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard or not, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information used for identifying the spraying photo. By adopting a machine learning-based method, a corresponding spraying area model is automatically established for a spraying workpiece, the sprayed position can be detected in real time, and the spraying quality is ensured; manual intervention is not needed, and the technical experience requirements of spraying operators are reduced.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A painting robot control system, comprising: the device comprises an image acquisition module, a judgment module and a control module;
the image acquisition module is used for scanning the sprayed workpiece in real time according to a preset scanning path so as to acquire a spraying photo of the sprayed workpiece;
the judging module is used for analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard or not, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo;
the control module is used for optimizing the geometric information to generate a three-dimensional model of a spraying workpiece, generating a position relation between the workpiece and the spraying robot, automatically identifying a spraying area according to the three-dimensional model of the workpiece, calculating a spraying track to form a spraying track file, planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, and controlling the spraying robot to spray.
2. The painting robot control system of claim 1, wherein: the control module comprises a graph reconstruction unit, a track programming unit, a code generation unit and a spraying unit;
the graphic reconstruction unit is used for optimizing the geometric information to generate a three-dimensional model of the workpiece, generating a position relation between the workpiece and the robot, and performing meshing processing on point cloud data of a certain position of the workpiece sprayed on the spraying picture to obtain a three-dimensional model of a partial area of the workpiece to be sprayed;
the track programming unit is used for automatically identifying a spraying area according to the three-dimensional model and calculating a spraying track to form a spraying track file, selecting a point on the three-dimensional model, planning a scanning plane and a scanning distance, and calculating a scanning track;
the code generating unit is used for planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, automatically planning a scanning path according to a scanning track, and converting the scanning path into a code file which can be executed by a robot;
the spraying unit is used for controlling the spraying robot to execute the spraying action according to the code file corresponding to the spraying path generated by the code generating unit.
3. The painting robot control system according to claim 2, wherein the trajectory programming unit includes a painting area recognition module and a painting trajectory calculation module;
the spraying area identification module is used for optimizing the boundary of a spraying area and removing the noise of the spraying area according to the three-dimensional model by selecting the color characteristics of the spraying area to obtain a three-dimensional model of the workpiece spraying area;
the spraying track calculation module is used for setting spraying process parameters according to the three-dimensional model of the workpiece spraying area generated by the spraying area identification module, and automatically calculating a spraying track strategy meeting process requirements according to the process parameters to obtain a spraying track file.
4. The painting robot control system of claim 3, wherein the code generation unit is further configured to collect pose information of the robot during the painting process, and perform real-time simulation on the entire painting process; the code generation unit comprises a simulation module and a post-processing module;
the simulation module is used for configuring the position relation between the workpiece and the spraying robot, acquiring a spraying track file generated by the spraying track calculation module, performing interpolation calculation, automatically planning the action path of the robot and simulating the spraying process;
and the post-processing module is used for converting the action path generated by the simulation module into a code file which can be executed by the robot.
5. The painting robot control system of claim 4, wherein the painting trajectory includes a distance relationship of the spray gun from the painting area, a position, a direction, and a speed of the spray gun as it enters and exits the painting area, a start point and an end point of the spray gun, a travel speed and a magnitude of a painting quantity of the spray gun during the painting process, and a painting path of the spray gun.
6. The painting robot control system of any of claims 1-5, wherein the image acquisition module is an industrial camera.
7. A painting robot control method using the control system according to any one of claims 1 to 6, characterized by comprising:
acquiring a spraying photo of a spraying workpiece;
analyzing the spraying photos through the model, determining whether the spraying photos meet the spraying standard, and acquiring the geometric information of the spraying photos which do not meet the spraying standard; the model is obtained through a plurality of groups of data by using machine learning training, and each group of data in the plurality of groups of data comprises a spraying photo of a spraying workpiece and standard identification information for identifying the spraying photo;
and optimizing the geometric information to generate a three-dimensional model of the spraying workpiece, generating a position relation between the workpiece and the spraying robot, automatically identifying a spraying area according to the three-dimensional model of the workpiece, calculating a spraying track to form a spraying track file, planning a spraying path according to the position relation and the spraying track file, converting the spraying path into an executable code file, and controlling the spraying robot to spray.
8. The control method of claim 7, wherein the training the model using the plurality of sets of training data comprises:
taking the workpiece spraying image marked with the spraying standard as a training set;
cutting the training set with corresponding size, and converting the training set into tfrecord format;
extracting detail characteristic information from the training set through continuous hole convolution calculation to obtain a prediction characteristic diagram;
taking the predicted feature map as an input of an ASPP structure, and reducing feature dimensions through a convolution layer;
performing a plurality of groups of cavity convolutions with different sampling rates on the prediction feature map with the reduced feature dimension to extract multi-scale feature information of the image;
fusing the detail characteristic information and the multi-scale characteristic information to obtain more accurate characteristic information as the input of a decoding part;
an improved Xprediction network structure is used as a network backbone of a decoding part, and the feature graph fusing detail feature information and multi-scale feature information is sampled upwards and restored to the size of an original graph;
and deriving the model obtained by training.
9. The control method of claim 7, wherein obtaining a paint trajectory file comprises: acquiring the three-dimensional model, optimizing the boundary of the spraying area by picking up the color characteristics of the spraying area, and removing the noise of the spraying area to obtain the three-dimensional model of the workpiece spraying area;
and setting spraying process parameters according to the three-dimensional model of the workpiece spraying area, and automatically calculating a spraying track strategy which meets the process requirements according to the process parameters and a track planning algorithm based on the spraying thickness to obtain a spraying track file.
10. The control method of claim 9, wherein obtaining an executable code file comprises: acquiring the position relation between a workpiece and a robot, and automatically building a virtual working platform; the virtual working platform comprises key information of a real working platform, including a robot model, the position relation between the spray gun and the robot, the position relation between the visual identification unit and the robot and a user coordinate system;
acquiring the spraying track file, calculating the posture of the robot, automatically planning the action path of the robot, and simulating the spraying process;
and converting the action path into a code file which can be executed by the robot.
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