CN117270537A - Automatic shaving moving path control system and control method - Google Patents
Automatic shaving moving path control system and control method Download PDFInfo
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Abstract
The invention belongs to the technical field of wood shaving path design, and discloses a system and a method for controlling a moving path of automatic wood shaving, wherein a wood shaving design path is matched with wood shaving, an overlapping area of the wood shaving design path and an abnormal wood shaving area is extracted, and the overlapping area is defined as a target area of a moving range of a wood shaving machine; solving a feasible shaving path through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area; and connecting the first moving paths one by one to obtain the wood shaving moving path of the target area.
Description
Technical Field
The invention relates to the technical field of wood shaving path design, in particular to a system and a method for controlling a moving path of automatic wood shavings.
Background
An automatic shaving machine or similar shaving equipment controls long wood shavings by controlling a moving path so as to realize efficient shaving operation to realize control, but because of different textures and states of wood, the moving path needs to be frequently changed, the response speed of the traditional method is slower, and the quick-change shaving design and production requirements are difficult to meet.
The traditional wood shaving machine generally adopts a key point teaching mode or a mode of manually inputting coordinate points to carry out path planning, the method can be suitable for products with simple and regular structures, and for complex and changeable wood shaving section designs, the robot path planning workload is particularly huge, and the production efficiency is severely restricted.
In view of the above, the present invention provides a system and a method for controlling a moving path of automatic shavings.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a system and a method for controlling a movement path of automatic shavings.
In order to achieve the above purpose, the present invention provides the following technical solutions:
according to an aspect of the present invention, there is provided a moving path control method of automatic shavings, comprising the steps of:
firstly, constructing a wood shaving design path based on a wood shaving design diagram, matching the wood shaving design path with wood shaving, extracting an overlapping area of the wood shaving design path and an abnormal wood shaving area, and defining the overlapping area as a target area of a moving range of a wood shaving machine;
solving a feasible shaving path through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area;
and thirdly, connecting the first moving paths one by one based on the wood shaving design paths to obtain wood shaving moving paths of the target area, storing the wood shaving moving paths in a computer numerical control program corresponding to the wood shaving machine, and performing wood shaving operation according to the set wood shaving moving paths.
In a preferred embodiment, the target area acquisition logic is:
creating a wood shaving design path according to the requirements of the wood shaving design drawing, wherein the wood shaving design requirements include, but are not limited to, drawing the track, the cutting depth and the cutting angle of the wood shaving;
generating a numerical control program by using CAM software according to the wood shaving design path, and guiding the wood shaving machine to carry out wood shaving operation based on the numerical control program;
generating a shaving normal area and a shaving abnormal area on the basis of the shaving wood information by an image analysis technology;
according to the design method, a wood shaving design path is arranged on wood shaving wood to be matched according to the exhaustive principle that the normal area of the wood shaving is maximized, and the wood shaving design path is overlapped with an abnormal area of the wood shaving according to the wood shaving design path so as to find an overlapped part of the wood shaving design path and the abnormal area of the wood shaving, wherein the overlapped area is a target area of the moving range of the wood shaving machine.
In a preferred embodiment, the acquisition logic for the normal and abnormal areas of shavings is:
acquiring real-time image data based on the surface of the wood shavings by using an image acquisition device, and preprocessing the real-time image data to acquire wood shavings information, wherein the preprocessing comprises, but is not limited to, denoising, graying and binarization so as to facilitate subsequent processing;
dividing the wood shaving information into n wood areas with different pixel gray values by using image processing and machine learning technologies; the pixel gray value corresponding to the wood areaAnd setting normal wood pixel threshold intervals [ PF1, PF2 ]]PF2 is larger than PF1, wherein PF2 is the maximum value of the pixel gray values corresponding to the normal wood, PF1 is the minimum value of the pixel gray values corresponding to the normal wood,
if the pixel gray value isGreater than or equal to PF1 and +.>If the wood area is smaller than or equal to PF2, the corresponding wood area is marked as a shaving normal area;
if the pixel gray value isLess than PF1, and->And if the wood area is larger than PF2, the corresponding wood area is marked as a shaving abnormal area.
In a preferred embodiment, the shaving anomaly area includes pixel position data and shaving data;
the pixel position data comprise a positioning area, a shaving abnormal area and a shaving machine passing path node of the shaving design path;
the shavings data includes a shavings starting node, a shavings ending node, and a shavings time.
In a preferred embodiment, the extraction logic of the viable wood shaving path:
constructing a feasible wood shaving path planning model for the wood shaving abnormal area; solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm;
selecting a corresponding dynamic updating mode to execute a feasible shaving path planning model operation according to a preset K value, comparing the advantages and disadvantages of various dynamic planning updating modes under different conditions, and acquiring the planning of the feasible shaving path under different conditions according to comparison of the advantages and disadvantages;
comprehensively analyzing all the feasible shaving paths, the shaving time and the safety coefficient of the feasible shaving through a feasible shaving path planning model to evaluate the shaving quality of the shaving abnormal area;
and selecting a feasible shaving path, shaving time and a safety coefficient corresponding to the highest shaving quality value of the shaving abnormal region, thereby determining a first moving path of the shaving abnormal region.
In a preferred embodiment, the calculation of the shaving time considers the extra time generated by acceleration and deceleration when shaving in the shaving abnormal area; the safety coefficient is obtained by calculating an average value of the safety degrees of all nodes on the feasible wood shaving path, and the node safety degrees are estimated by combining the distance between each pixel and the wood shaving design path according to the ratio of the number of each pixel in the wood shaving abnormal area to the total pixels.
In a preferred embodiment, the feasibility shaving path planning model is specifically:
building a feasible wood shaving path planning model, and determining constraint conditions of wood shaving path planning based on wood shaving information, wherein the constraint conditions comprise, but are not limited to, minimizing wood shaving waste, maximizing wood shaving quality, shortest wood shaving time, maximum wood shaving depth and minimum wood shaving clearance;
taking the target of the wood shaving path planning as a plurality of target functions, calculating the wood shaving quality of the path according to the target function values, and realizing the basic operation iteration execution genetic operation of the genetic non-dominant sorting algorithm until the termination condition is met;
and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest shaving quality value of the shaving abnormal area.
In a preferred embodiment, k= [0,1,2,3], and the K value corresponds to the selected dynamic update mode:
k=0: the dynamic updating is not performed, and the planning of the shaving path is performed based on static data;
k=1: dynamically updating according to time periods, and planning a shaving path according to time-varying wood conditions;
k=2: dynamically updating according to the key nodes, and dynamically adjusting the planning of the wood shaving path according to the detected key node information;
k=3: updating according to time-space dynamics, and updating the planning of the wood shaving path by combining time and space information;
according to another aspect of the present invention, there is provided a moving path control system of automatic shavings, which is based on the moving path control method of automatic shavings described above, comprising:
the target area identification module is used for constructing a shaving design path based on the shaving design diagram, matching the shaving design path with shaving wood, extracting an overlapping area of the shaving design path and a shaving abnormal area, and defining the overlapping area as a target area of the movement range of the shaving machine;
the local path planning module is used for solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area;
and the path control module is used for connecting the first moving paths one by one based on the shavings design paths to obtain shavings moving paths of the target area, storing the shavings moving paths in a computer numerical control program corresponding to the shavings machine, and carrying out shavings operation according to the set shavings moving paths.
According to still another aspect of the present invention, there is provided an electronic apparatus including: a processor and a memory, wherein the memory stores a computer program for the processor to call;
the processor executes the above-mentioned method for controlling the moving path of the automatic wood shavings by calling the computer program stored in the memory.
The invention relates to a system and a method for controlling a moving path of automatic wood shavings, which have the technical effects and advantages that:
according to the invention, the wood shaving design path is created according to the wood shaving design diagram, so that the wood shaving design path is consistent with the design requirement, and the wood shaving design path is used as a comparison group of the wood shaving movement path, so that the wood shaving process can be optimized, the wood shaving waste can be reduced, the material utilization rate can be improved, and the raw material cost can be reduced; the accurate wood shavings design can ensure the quality and consistency of wood shavings, reduce the defective rate, improve the appearance and performance of products, improve the traceability of products, and also improve the production speed of wood shavings, thereby improving the efficiency of a production line, reducing the production time, reducing the dependence on manual operation, reducing the labor cost and reducing the labor intensity of operators.
Drawings
FIG. 1 is a schematic diagram of a system for controlling the path of travel of automatic shavings according to the present invention;
FIG. 2 is a flow chart of a method for controlling the moving path of the automatic wood shavings according to the present invention;
FIG. 3 is a schematic view of the connection of the design path of the wood shavings of the present invention to the target zone;
FIG. 4 is a schematic diagram of an electronic device according to the present invention;
in the figure: 1. a target area identification module; 2. a local path planning module; 3. and a path control module.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, a system for controlling a moving path of automatic shavings according to the present embodiment includes: a target area identification module 1, a local path planning module 2 and a path control module 3; the modules are connected in a wired and/or wireless connection mode, so that data transmission among the modules is realized;
the target area identification module 1 is used for constructing a wood shaving design path based on a wood shaving design diagram, matching the wood shaving design path with wood shaving, extracting an overlapping area of the wood shaving design path and an abnormal wood shaving area, and defining the overlapping area as a target area of a moving range of the wood shaving machine;
what needs to be explained here is: the target area is a safe shaving range on the shaving wood based on the shaving design path, i.e. a safe shaving machine movement range. The wood shaving design path is a final wood shaving path diagram of automatic wood shaving through a wood shaving machine;
in addition, it should be noted that: the condition of the wood shavings is not fixed, the areas with normal wood lines of the wood shavings are marked as wood shavings normal areas, but the areas with larger differences from the wood lines of the wood shavings are marked as wood shavings abnormal areas, so that in the process of controlling a moving path, the designed path of the wood shavings needs to be covered on the wood shavings normal areas as far as possible, and the wood shavings machine can move normally according to the designed path of the wood shavings; however, the design path of the shavings inevitably contacts more or less abnormal areas of the shavings, see fig. 3; therefore, the shaving machine needs to analyze the abnormal shaving areas to re-plan the shaving paths, so that the damage of the shaving wood caused by direct shaving is avoided.
The acquisition logic of the target area is as follows:
creating a wood shaving design path according to the requirements of the wood shaving design drawing, wherein the wood shaving design requirements include, but are not limited to, drawing the track, the cutting depth and the cutting angle of the wood shaving;
generating a numerical control program by using CAM software according to the wood shaving design path, and guiding the wood shaving machine to carry out wood shaving operation based on the numerical control program;
generating a shaving normal area and a shaving abnormal area on the basis of the shaving wood information by an image analysis technology; the shaving normal area and the shaving abnormal area are areas defined by technicians according to the actual situation of the shaving wood, and the shaving abnormal area is an obstacle area where the shaving machine cannot normally shave the shaving; the colors that are present on the wood surface are also differentiated, and are represented by pixel gray values, for specific examples; the pixel gray threshold is set to distinguish between normal and abnormal areas of shavings.
The acquisition logic of the normal wood shaving area and the abnormal wood shaving area is as follows:
acquiring real-time image data based on the surface of the wood shavings by using an image acquisition device, and preprocessing the real-time image data to acquire wood shavings information, wherein the preprocessing comprises, but is not limited to, denoising, graying and binarization so as to facilitate subsequent processing;
dividing the wood shaving information into n wood areas with different pixel gray values by using image processing and machine learning technologies; the pixel gray value corresponding to the wood areaAnd setting normal wood pixel threshold intervals [ PF1, PF2 ]]PF2 is larger than PF1, wherein PF2 is the maximum value of the pixel gray values corresponding to the normal wood, PF1 is the minimum value of the pixel gray values corresponding to the normal wood,
if the pixel gray value isGreater than or equal to PF1 and +.>If the wood area is smaller than or equal to PF2, the corresponding wood area is marked as a shaving normal area;
if the pixel gray value isLess than PF1, and->And if the wood area is larger than PF2, the corresponding wood area is marked as a shaving abnormal area. The wood shavings anomaly areas include, but are not limited to, areas of blemish, cracks, or non-uniformity on the wood surface.
According to the design method, a shaving design path is arranged on shaving wood to be matched according to an exhaustion principle of maximization of a shaving normal area, and overlapped parts of the shaving design path and the abnormal shaving area are found according to superposition of the shaving design path and the shaving abnormal area, wherein the overlapped areas are target areas of the movement range of a shaving machine; ensuring that the shaving machine does not collide or go beyond a predetermined range during operation.
The local path planning module 2 solves the feasible wood shaving paths through an improved non-dominant multi-objective genetic algorithm in the wood shaving abnormal region; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the target area, thereby determining a first moving path of the shaving abnormal area;
what needs to be explained here is: and comprehensively analyzing at least one feasible shaving path generated based on the shaving difficulty level of the shaving abnormal area, shaving time corresponding to all the feasible shaving paths and the safety coefficient of the feasible shaving path so as to more comprehensively evaluate the shaving quality of the shaving abnormal area, and adjusting parameters of the shaving machine or providing operator feedback according to the result of the comprehensive analysis so as to ensure that the shaving operation is properly performed on the complex wood surface.
Reading pixel position data and shaving data of a shaving abnormal region, wherein the pixel position data comprises a positioning region of a shaving design path, a shaving abnormal partition and a shaving machine passing path node; the shaving data comprise a shaving starting node, a shaving ending node and a shaving time;
extraction logic of viable wood shaving paths:
constructing a feasible wood shaving path planning model for the wood shaving abnormal area; solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm;
selecting a corresponding dynamic updating mode to execute a feasible shaving path planning model operation according to a preset K value, comparing the advantages and disadvantages of various dynamic planning updating modes under different conditions, and acquiring the planning of the feasible shaving path under different conditions according to comparison of the advantages and disadvantages;
the feasibility wood shaving path planning model specifically comprises the following steps:
building a feasible wood shaving path planning model, and determining constraint conditions of wood shaving path planning based on wood shaving information, wherein the constraint conditions comprise, but are not limited to, minimizing wood shaving waste, maximizing wood shaving quality, shortest wood shaving time, maximum wood shaving depth and minimum wood shaving clearance;
taking the target of the wood shaving path planning as a plurality of target functions, calculating the wood shaving quality of the path according to the target function values, and realizing the basic operation iteration execution genetic operation of the genetic non-dominant sorting algorithm until the termination condition is met;
and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest shaving quality value of the shaving abnormal area.
K= [0,1,2,3], and the dynamic update mode is selected corresponding to the K value:
k=0: and (5) carrying out the planning of the shavings path based on static data by the model without dynamic updating.
K=1: and dynamically updating according to the time period, and planning a path according to the wood condition of time change.
K=2: and dynamically updating according to the key nodes, and dynamically adjusting the paths according to the detected key node information.
K=3: and updating the path planning by time-space dynamic updating and combining time and space information.
And selecting a corresponding dynamic updating mode to execute the operation of the path planning model of the feasibility shavings according to the preset K value, and selecting a proper path representation method, wherein the path representation method comprises but is not limited to a continuous curve and a discrete point set.
What needs to be explained here is: based on different updating modes, different data input and algorithm strategies need to be adapted to meet specific demands of the shavings, the embodiment mainly optimizes path control of the automatic shavings from planning of abnormal areas of the shavings, and in fact, other requirements exist in the automatic shavings, and the requirements of the shavings wood are met through various dynamic updating modes.
Comprehensively analyzing all the feasible shaving paths, the shaving time and the safety coefficient of the feasible shaving through a feasible shaving path planning model to evaluate the shaving quality of the shaving abnormal area;
and selecting a feasible shaving path, shaving time and a safety coefficient corresponding to the highest shaving quality value of the shaving abnormal region, thereby determining a first moving path of the shaving abnormal region.
Calculating the shaving time by considering extra time generated by acceleration and deceleration when shaving in the shaving abnormal area; the safety coefficient is obtained by calculating an average value of the safety degrees of all nodes on the feasible wood shaving path, and the node safety degrees are evaluated by combining the distance between each pixel and the wood shaving design path according to the ratio of the number of each pixel in the wood shaving abnormal area to the total pixels;
one possibility scheme is as follows:
；
wherein: the pixel shaving difficulty of shaving is different in the areas where different pixels correspond to the shaving abnormality, wherein the pixel shaving difficulty is determined by shaving force used in the shaving process of a large number of shaving machines, the pixel number corresponding to the gray value of the current pixel is counted, and the ratio of the pixel number to the total pixels of the areas is the occupation space of the pixels corresponding to the areas where the current shaving abnormality;
the pixel distance is the linear distance of the specific wood shaving design path of the current pixel, and the farther the distance is, the safer the corresponding pixel is, and the smaller the threat to the wood shaving design path is; the shaving is preferably carried out in the area with high safety in the shaving process;
a higher degree of node safety indicates a safer area of the current shaving area, may help determine the accuracy and stability of the shaving operation so that an operator can intuitively understand the characteristics of the target area, may make decisions such as adjusting parameters of the shaving apparatus, stopping the shaving operation, or taking other safety measures.
The path control module 3 is connected with each first moving path one by one based on the shavings design path to obtain shavings moving paths of the target area, stores the shavings moving paths in a computer numerical control program corresponding to the shavings machine, and performs shavings operation according to the set shavings moving paths.
Example 2
Referring to fig. 2, the embodiment is not described in detail in the first description of the embodiment, and the embodiment provides a method for controlling a moving path of automatic wood shavings, comprising the following steps: firstly, constructing a wood shaving design path based on a wood shaving design diagram, matching the wood shaving design path with wood shaving, extracting an overlapping area of the wood shaving design path and an abnormal wood shaving area, and defining the overlapping area as a target area of a moving range of a wood shaving machine;
solving a feasible shaving path through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area;
and thirdly, connecting the first moving paths one by one based on the wood shaving design paths to obtain wood shaving moving paths of the target area, storing the wood shaving moving paths in a computer numerical control program corresponding to the wood shaving machine, and performing wood shaving operation according to the set wood shaving moving paths.
The acquisition logic of the target area is as follows:
creating a wood shaving design path according to the requirements of the wood shaving design drawing, wherein the wood shaving design requirements include, but are not limited to, drawing the track, the cutting depth and the cutting angle of the wood shaving;
generating a numerical control program by using CAM software according to the wood shaving design path, and guiding the wood shaving machine to carry out wood shaving operation based on the numerical control program;
generating a shaving normal area and a shaving abnormal area on the basis of the shaving wood information by an image analysis technology;
according to the design method, a wood shaving design path is arranged on wood shaving wood to be matched according to the exhaustive principle that the normal area of the wood shaving is maximized, and the wood shaving design path is overlapped with an abnormal area of the wood shaving according to the wood shaving design path so as to find an overlapped part of the wood shaving design path and the abnormal area of the wood shaving, wherein the overlapped area is a target area of the moving range of the wood shaving machine.
The acquisition logic of the normal wood shaving area and the abnormal wood shaving area is as follows:
acquiring real-time image data based on the surface of the wood shavings by using an image acquisition device, and preprocessing the real-time image data to acquire wood shavings information, wherein the preprocessing comprises, but is not limited to, denoising, graying and binarization so as to facilitate subsequent processing;
dividing the wood shaving information into n wood areas with different pixel gray values by using image processing and machine learning technologies; the pixel gray value corresponding to the wood areaAnd setting normal wood pixel threshold intervals [ PF1, PF2 ]]PF2 is greater than PF1, where PF2 is the maximum value of the pixel gray values corresponding to normal wood and PF1 is the minimum value of the pixel gray values corresponding to normal woodThe value of the sum of the values,
if the pixel gray value isGreater than or equal to PF1 and +.>If the wood area is smaller than or equal to PF2, the corresponding wood area is marked as a shaving normal area;
if the pixel gray value isLess than PF1, and->And if the wood area is larger than PF2, the corresponding wood area is marked as a shaving abnormal area.
The shaving abnormal region comprises pixel position data and shaving data;
the pixel position data comprise a positioning area, a shaving abnormal area and a shaving machine passing path node of the shaving design path;
the shavings data includes a shavings starting node, a shavings ending node, and a shavings time.
Extraction logic of viable wood shaving paths:
constructing a feasible wood shaving path planning model for the wood shaving abnormal area; solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm;
selecting a corresponding dynamic updating mode to execute a feasible shaving path planning model operation according to a preset K value, comparing the advantages and disadvantages of various dynamic planning updating modes under different conditions, and acquiring the planning of the feasible shaving path under different conditions according to comparison of the advantages and disadvantages;
comprehensively analyzing all the feasible shaving paths, the shaving time and the safety coefficient of the feasible shaving through a feasible shaving path planning model to evaluate the shaving quality of the shaving abnormal area;
and selecting a feasible shaving path, shaving time and a safety coefficient corresponding to the highest shaving quality value of the shaving abnormal region, thereby determining a first moving path of the shaving abnormal region.
Calculating the shaving time by considering extra time generated by acceleration and deceleration when shaving in the shaving abnormal area; the safety coefficient is obtained by calculating an average value of the safety degrees of all nodes on the feasible wood shaving path, and the node safety degrees are estimated by combining the distance between each pixel and the wood shaving design path according to the ratio of the number of each pixel in the wood shaving abnormal area to the total pixels.
The feasibility wood shaving path planning model specifically comprises the following steps:
building a feasible wood shaving path planning model, and determining constraint conditions of wood shaving path planning based on wood shaving information, wherein the constraint conditions comprise, but are not limited to, minimizing wood shaving waste, maximizing wood shaving quality, shortest wood shaving time, maximum wood shaving depth and minimum wood shaving clearance;
taking the target of the wood shaving path planning as a plurality of target functions, calculating the wood shaving quality of the path according to the target function values, and realizing the basic operation iteration execution genetic operation of the genetic non-dominant sorting algorithm until the termination condition is met;
and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest shaving quality value of the shaving abnormal area.
K= [0,1,2,3], and the dynamic update mode is selected corresponding to the K value:
k=0: the dynamic updating is not performed, and the planning of the shaving path is performed based on static data;
k=1: dynamically updating according to time periods, and planning a shaving path according to time-varying wood conditions;
k=2: dynamically updating according to the key nodes, and dynamically adjusting the planning of the wood shaving path according to the detected key node information;
k=3: updating according to time-space dynamics, and updating the planning of the wood shaving path by combining time and space information;
according to another aspect of the present invention, there is provided a moving path control system of automatic shavings, which is based on the moving path control method of automatic shavings described above, comprising:
the target area identification module is used for constructing a shaving design path based on the shaving design diagram, matching the shaving design path with shaving wood, extracting an overlapping area of the shaving design path and a shaving abnormal area, and defining the overlapping area as a target area of the movement range of the shaving machine;
the local path planning module is used for solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area;
and the path control module is used for connecting the first moving paths one by one based on the shavings design paths to obtain shavings moving paths of the target area, storing the shavings moving paths in a computer numerical control program corresponding to the shavings machine, and carrying out shavings operation according to the set shavings moving paths.
Example 3
As shown in fig. 4, this embodiment is not described in detail in the first description of the embodiment, and this embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program for the processor to call;
the processor executes the above-mentioned method for controlling the moving path of the automatic wood shavings by calling the computer program stored in the memory.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A method for controlling a moving path of automatic shavings, comprising the steps of:
firstly, constructing a wood shaving design path based on a wood shaving design diagram, matching the wood shaving design path with wood shaving, extracting an overlapping area of the wood shaving design path and an abnormal wood shaving area, and defining the overlapping area as a target area of a moving range of a wood shaving machine;
solving a feasible shaving path through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area;
and thirdly, connecting the first moving paths one by one based on the wood shaving design paths to obtain wood shaving moving paths of the target area, storing the wood shaving moving paths in a computer numerical control program corresponding to the wood shaving machine, and performing wood shaving operation according to the set wood shaving moving paths.
2. The method for controlling a moving path of automatic shavings as claimed in claim 1, wherein said target zone acquisition logic comprises:
creating a wood shaving design path according to the requirements of the wood shaving design drawing, wherein the wood shaving design requirements include, but are not limited to, drawing the track, the cutting depth and the cutting angle of the wood shaving;
generating a numerical control program by using CAM software according to the wood shaving design path, and guiding the wood shaving machine to carry out wood shaving operation based on the numerical control program;
generating a shaving normal area and a shaving abnormal area on the basis of the shaving wood information by an image analysis technology;
according to the design method, a wood shaving design path is arranged on wood shaving wood to be matched according to the exhaustive principle that the normal area of the wood shaving is maximized, and the wood shaving design path is overlapped with an abnormal area of the wood shaving according to the wood shaving design path so as to find an overlapped part of the wood shaving design path and the abnormal area of the wood shaving, wherein the overlapped area is a target area of the moving range of the wood shaving machine.
3. The method for controlling a moving path of automatic shavings as claimed in claim 2, wherein the logic for acquiring the normal area and the abnormal area of shavings is:
acquiring real-time image data based on the surface of the wood shavings by using an image acquisition device, and preprocessing the real-time image data to acquire wood shavings information, wherein the preprocessing comprises, but is not limited to, denoising, graying and binarization so as to facilitate subsequent processing;
dividing the wood shaving information into n wood areas with different pixel gray values by using image processing and machine learning technologies; the pixel gray value corresponding to the wood areaAnd setting normal wood pixel threshold intervals [ PF1, PF2 ]]PF2 is larger than PF1, wherein PF2 is the maximum value of the pixel gray values corresponding to the normal wood, PF1 is the minimum value of the pixel gray values corresponding to the normal wood,
if the pixel gray value isGreater than or equal to PF1 and +.>If the wood area is smaller than or equal to PF2, the corresponding wood area is marked as a shaving normal area;
if the pixel gray value isLess than PF1, and->And if the wood area is larger than PF2, the corresponding wood area is marked as a shaving abnormal area.
4. A method of controlling a moving path of automatic shavings according to claim 3, wherein the shavings abnormal area includes pixel position data and shavings data;
the pixel position data comprise a positioning area, a shaving abnormal area and a shaving machine passing path node of the shaving design path;
the shavings data includes a shavings starting node, a shavings ending node, and a shavings time.
5. A method of controlling a travel path for automatic shavings as in claim 4 wherein the feasibility shavings path extraction logic:
constructing a feasible wood shaving path planning model for the wood shaving abnormal area; solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm;
selecting a corresponding dynamic updating mode to execute a feasible shaving path planning model operation according to a preset K value, comparing the advantages and disadvantages of various dynamic planning updating modes under different conditions, and acquiring the planning of the feasible shaving path under different conditions according to comparison of the advantages and disadvantages;
comprehensively analyzing all the feasible shaving paths, the shaving time and the safety coefficient of the feasible shaving through a feasible shaving path planning model to evaluate the shaving quality of the shaving abnormal area;
and selecting a feasible shaving path, shaving time and a safety coefficient corresponding to the highest shaving quality value of the shaving abnormal region, thereby determining a first moving path of the shaving abnormal region.
6. The method according to claim 5, wherein the calculation of the shaving time considers an extra time generated by acceleration and deceleration when shaving in an abnormal area of the shaving; the safety coefficient is obtained by calculating an average value of the safety degrees of all nodes on the feasible wood shaving path, and the node safety degrees are estimated by combining the distance between each pixel and the wood shaving design path according to the ratio of the number of each pixel in the wood shaving abnormal area to the total pixels.
7. The method for controlling a moving path of automatic shavings as claimed in claim 6, wherein said feasibility shavings path planning model comprises:
building a feasible wood shaving path planning model, and determining constraint conditions of wood shaving path planning based on wood shaving information, wherein the constraint conditions comprise, but are not limited to, minimizing wood shaving waste, maximizing wood shaving quality, shortest wood shaving time, maximum wood shaving depth and minimum wood shaving clearance;
taking the target of the wood shaving path planning as a plurality of target functions, calculating the wood shaving quality of the path according to the target function values, and realizing the basic operation iteration execution genetic operation of the genetic non-dominant sorting algorithm until the termination condition is met;
and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest shaving quality value of the shaving abnormal area.
8. The method of claim 7, wherein the dynamic update mode is selected by the k= [0,1,2,3], and the K value is:
k=0: the dynamic updating is not performed, and the planning of the shaving path is performed based on static data;
k=1: dynamically updating according to time periods, and planning a shaving path according to time-varying wood conditions;
k=2: dynamically updating according to the key nodes, and dynamically adjusting the planning of the wood shaving path according to the detected key node information;
k=3: updating according to the time-space dynamic state, and updating the wood shaving path planning by combining the time and space information.
9. A system for controlling the movement path of automatic shavings, characterized in that it is based on a method for controlling the movement path of automatic shavings according to any of the claims 1-8, comprising:
the target area identification module is used for constructing a shaving design path based on the shaving design diagram, matching the shaving design path with shaving wood, extracting an overlapping area of the shaving design path and a shaving abnormal area, and defining the overlapping area as a target area of the movement range of the shaving machine;
the local path planning module is used for solving the feasible shaving paths through an improved non-dominant multi-objective genetic algorithm in the shaving abnormal area; constructing a feasible shaving path planning model to evaluate the shaving quality of the current shaving abnormal area, and selecting a feasible shaving path, the shaving time and the safety coefficient corresponding to the highest value of the shaving quality of the shaving abnormal area, thereby determining a first moving path of the shaving abnormal area;
and the path control module is used for connecting the first moving paths one by one based on the shavings design paths to obtain shavings moving paths of the target area, storing the shavings moving paths in a computer numerical control program corresponding to the shavings machine, and carrying out shavings operation according to the set shavings moving paths.
10. An electronic device, comprising: a processor and a memory, wherein the memory stores a computer program for the processor to call;
the processor performs a method of controlling a movement path of automatic wood shavings according to any one of claims 1-8 by invoking a computer program stored in said memory.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112434849A (en) * | 2020-11-19 | 2021-03-02 | 上海交通大学 | Dangerous goods transportation path dynamic planning method based on improved multi-objective algorithm |
| CN114219794A (en) * | 2021-12-17 | 2022-03-22 | 沭阳县桐盛木业制品厂(普通合伙) | Method and system for evaluating surface quality of shaving board based on machine vision |
| CN216992300U (en) * | 2022-03-17 | 2022-07-19 | 广西志光家具集团有限责任公司 | Wood shaving machine capable of improving surface flatness of furniture wood |
| CN218947158U (en) * | 2022-10-23 | 2023-05-02 | 洛宁三环华兰木业有限公司 | Shaving board sander |
| CN116740449A (en) * | 2023-06-19 | 2023-09-12 | 昆明飞林人造板集团有限公司 | Shaving form detection method and system based on AI (advanced technology attachment) computer vision technology |
-
2023
- 2023-09-28 CN CN202311265524.9A patent/CN117270537B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112434849A (en) * | 2020-11-19 | 2021-03-02 | 上海交通大学 | Dangerous goods transportation path dynamic planning method based on improved multi-objective algorithm |
| CN114219794A (en) * | 2021-12-17 | 2022-03-22 | 沭阳县桐盛木业制品厂(普通合伙) | Method and system for evaluating surface quality of shaving board based on machine vision |
| CN216992300U (en) * | 2022-03-17 | 2022-07-19 | 广西志光家具集团有限责任公司 | Wood shaving machine capable of improving surface flatness of furniture wood |
| CN218947158U (en) * | 2022-10-23 | 2023-05-02 | 洛宁三环华兰木业有限公司 | Shaving board sander |
| CN116740449A (en) * | 2023-06-19 | 2023-09-12 | 昆明飞林人造板集团有限公司 | Shaving form detection method and system based on AI (advanced technology attachment) computer vision technology |
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