CN112766577A - Spraying track transition section optimization system and method based on NURBS curve - Google Patents
Spraying track transition section optimization system and method based on NURBS curve Download PDFInfo
- Publication number
- CN112766577A CN112766577A CN202110087513.0A CN202110087513A CN112766577A CN 112766577 A CN112766577 A CN 112766577A CN 202110087513 A CN202110087513 A CN 202110087513A CN 112766577 A CN112766577 A CN 112766577A
- Authority
- CN
- China
- Prior art keywords
- track
- nurbs curve
- spraying
- control points
- curve
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000005507 spraying Methods 0.000 title claims abstract description 58
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000005457 optimization Methods 0.000 title claims abstract description 40
- 230000007704 transition Effects 0.000 title claims abstract description 34
- 238000003064 k means clustering Methods 0.000 claims abstract description 18
- 239000007921 spray Substances 0.000 claims description 23
- 238000012163 sequencing technique Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 7
- 238000011156 evaluation Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003973 paint Substances 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
- G06F18/232—Non-hierarchical techniques
- G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
- G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Data Mining & Analysis (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Probability & Statistics with Applications (AREA)
- Educational Administration (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Image Generation (AREA)
Abstract
The invention provides a spraying track transition section optimization method based on a NURBS curve, which comprises the following steps: classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces, and respectively performing track planning on the different classification curvature curved surfaces to obtain track point information; obtaining NURBS curve control points according to the track point information, and processing the NURBS curve control points to obtain a smooth block track; the method comprises the steps of sorting the head and tail end points of the block tracks to splice the block tracks, and adding control points and weight factors at the spliced positions of the block tracks to optimize a spraying track curve. The invention can obtain smooth block tracks, so that the overall spraying track is not influenced. Correspondingly, the invention further provides a spraying track transition section optimization system based on the NURBS curve, which comprises a track generation module, a track fitting module and a track optimization module.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a spraying track transition section optimization system and method based on a NURBS curve.
Background
The dominant replacement of manual spraying by industrial robots in the spraying industry has become a necessity, and trajectory planning is a core part of robot spraying. The core problem of the trajectory planning is that the models are various and the appearance curved surface is complex and heterotypic. In order to rapidly plan a spraying track and a process of an industrial robot and solve the core difficulty of the spraying track planning, the existing spraying track planning method comprises the following steps: 1. and (5) acquiring the track fitting by adopting a Bezier curve. 2. And (4) acquiring by adopting a geodesic method and a slicing method. 3. And processing the surface of the workpiece by adopting a triangular block method, and then cutting and obtaining the workpiece through an orthogonal surface.
However, when the existing spraying trajectory planning method carries out concave-convex processing on the trajectory splicing part, the original trajectory is deformed, and an ideal trajectory is difficult to obtain.
Disclosure of Invention
Based on this, in order to solve the problem that the original trajectory is deformed and an ideal trajectory is difficult to obtain when the concave-convex processing is performed on the trajectory splicing part by the existing spraying trajectory planning method, the invention provides a spraying trajectory transition section optimization system and method based on a NURBS curve, and the specific technical scheme is as follows:
a spraying track transition section optimization system based on a NURBS curve comprises a track generation module, a track fitting module and a track optimization module.
The track generation module is used for classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces, and respectively carrying out track planning on the different classification curvature curved surfaces to obtain track point information.
And the track fitting module is used for solving NURBS curve control points according to the track point information and processing the NURBS curve control points to obtain a smooth block track.
The track optimization module is used for splicing the blocked tracks by sequencing the head and tail end points of the blocked tracks and optimizing a spraying track curve by adding control points and weight factors at the splicing positions of the blocked tracks.
The device further comprises a curved surface obtaining module, wherein the curved surface obtaining module is used for obtaining workpiece model data and obtaining a curved surface of the workpiece model according to the workpiece model data.
Further according to the formulaProcessing the NURBS curve control points to obtain a smoothed block trajectory, wherein ω isiAs a weighting factor, DiFor curve control points, u denotes a non-periodic node vector, Ni,m(u) represents the m-degree b-sample basis functions on the corresponding aperiodic node vector u.
Further, the curve of the weight function at the newly added control point is F (D)q,ωi(x, y, z)), wherein DqTo newly add a control point, omegaiFor the weighting factors, (x, y, z) is a formal point expression.
The invention also provides a spraying track transition section optimization method based on the NURBS curve, which comprises the following steps:
classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces, and respectively performing track planning on the different classification curvature curved surfaces to obtain track point information;
according to the track point information, obtaining NURBS curve control points, and processing the NURBS curve control points to obtain a smooth block track;
and splicing the blocked tracks by sequencing the head and tail end points of the blocked tracks, and optimizing a spraying track curve by adding control points and weight factors at the splicing positions of the blocked tracks.
According to the spraying track transition section optimization method based on the NURBS curve, the workpiece model curved surfaces are classified through a k-means clustering algorithm to obtain different classification curvature curved surfaces, track planning is respectively carried out on the different classification curvature curved surfaces to obtain track point information, and spraying thickness requirement parameters are conveniently set according to different curvature of the workpiece model curved surfaces to obtain a better planned spraying track. And calculating NURBS curve control points according to the track point information and processing the NURBS curve control points, so that the original track is not deformed when concave-convex processing is carried out on the track splicing part, a smooth block track can be obtained, and the whole spraying track is not influenced.
That is to say, the spraying track transition section optimization method based on the NURBS curve solves the problem that the original track is deformed and an ideal track is difficult to obtain when the concave-convex processing is carried out on the track splicing part by the existing spraying track planning method, and can obtain a smooth blocked track, so that the whole spraying track is not influenced.
Further, the specific method for classifying the workpiece model curved surface through the k-means clustering algorithm to obtain the curved surfaces with different classification curvatures comprises the following steps:
setting a curvature threshold value;
classifying the curvature of the workpiece model curved surface according to the curvature threshold;
taking the classification number of the curvature as the initial K point number K in the K-means clustering algorithmn(n=1,2,3.....);
Iterating the workpiece model data through the k-means clustering algorithm to obtain different classification curvature surfaces Cn(n=1,2,3...);
Wherein n is the number of classifications of the curvatures.
Further, the specific method for respectively performing trajectory planning on different classification curvature curved surfaces to acquire trajectory point information comprises the following steps:
making an orthogonal surface at the over-clustering centroid to intersect with the target curved surface so as to obtain an orthogonal line of the over-clustering centroid;
discretizing the orthogonal lines according to the spraying distance to obtain equidistant discrete points;
selecting a plurality of equidistant surfaces according to the equidistant discrete points, and performing orthogonality on the equidistant surfaces to obtain a plurality of equidistant orthogonal lines;
discretizing the equidistant orthogonal lines to obtain a plurality of track points;
sequencing a plurality of the track points to obtain the track point information Cn,j;
Wherein n represents a curved surface and j represents a track point.
Further, the specific method for solving the NURBS curve control points according to the track point information comprises the following steps;
selecting the height according to the spraying to the track point information Cn,jCarrying out offset processing;
and reversely solving the NURBS curve control point by taking the track point information after the offset processing as a model value point.
Further according to the formulaProcessing the NURBS curve control points to obtain a smoothed block trajectory, wherein ω isiAs a weighting factor, DiAre curve control points.
The invention also provides a computer-readable storage medium, which stores a computer program that, when being executed by a processor, carries out the method for NURBS curve-based spray trajectory transition optimization as described above.
Drawings
The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.
FIG. 1 is a schematic overall flow diagram of a NURBS curve-based spray trajectory transition optimization system in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of an overall structure of a spraying trajectory transition section optimization method based on a NURBS curve according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating relationships among the clustered centroids, the orthogonal planes and the target curved surface in a NURBS curve-based spray trajectory transition optimization method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a relationship between a medium range scatter and an equidistant quadrature line in a NURBS curve-based spray trajectory transition optimization method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the relationship between equidistant orthogonal lines and trajectory points in a NURBS curve-based spray trajectory transition optimization method according to an embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating a relationship between a spray gun, a spray selected height, and a spray spacing in a NURBS curve-based spray trajectory transition optimization method according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a transition segment for stitching block trajectories in a spraying trajectory transition segment optimization method based on NURBS curves according to an embodiment of the present invention.
Description of reference numerals:
1. clustering the centroids; 2. equidistant discrete points; 3. equidistant orthogonal lines; 4. tracing points; 5. a spray gun.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to embodiments thereof. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.
Unless defined otherwise, all 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. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The terms "first" and "second" used herein do not denote any particular order or quantity, but rather are used to distinguish one element from another.
As shown in fig. 2, a spraying trajectory transition optimization system based on NURBS curve in an embodiment of the present invention includes a trajectory generation module, a trajectory fitting module, and a trajectory optimization module.
The track generation module is used for classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces, and respectively carrying out track planning on the different classification curvature curved surfaces to obtain track point information.
And the track fitting module is used for solving NURBS curve control points according to the track point information and processing the NURBS curve control points to obtain a smooth block track.
The track optimization module is used for splicing the blocked tracks by sequencing the head and tail end points of the blocked tracks and optimizing a spraying track curve by adding control points and weight factors at the splicing positions of the blocked tracks.
In one embodiment, the system further comprises a curved surface acquisition module, and the curved surface acquisition module is used for acquiring workpiece model data and acquiring a curved surface of the workpiece model according to the workpiece model data.
In one embodiment, according to a formulaProcessing the NURBS curve control points to obtain a smoothed block trajectory, wherein ω isiAs a weighting factor, DiAre curve control points.
In one embodiment, the curve of the weighting function of the increasing control points and the weighting factors is F (D)q,ωi(x, y, z)), wherein DqTo increaseControl point, ωiFor the weighting factors, (x, y, z) is a formal point expression.
In one embodiment, as shown in fig. 1, the present invention provides a spraying trajectory transition segment optimization method based on NURBS curve, comprising the following steps:
classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces, and respectively performing track planning on the different classification curvature curved surfaces to obtain track point information;
according to the track point information, obtaining NURBS curve control points, and processing the NURBS curve control points to obtain a smooth block track;
and splicing the blocked tracks by sequencing the head and tail end points of the blocked tracks, and optimizing a spraying track curve by adding control points and weight factors at the splicing positions of the blocked tracks.
According to the spraying track transition section optimization method based on the NURBS curve, the workpiece model curved surfaces are classified through a k-means clustering algorithm to obtain different classification curvature curved surfaces, track planning is respectively carried out on the different classification curvature curved surfaces to obtain track point information, and spraying thickness requirement parameters are conveniently set according to different curvature of the workpiece model curved surfaces to obtain a better planned spraying track. And calculating NURBS curve control points according to the track point information and processing the NURBS curve control points, so that the original track is not deformed when concave-convex processing is carried out on the track splicing part, a smooth block track can be obtained, and the whole spraying track is not influenced.
That is to say, the spraying track transition section optimization method based on the NURBS curve solves the problem that the original track is deformed and an ideal track is difficult to obtain when the concave-convex processing is carried out on the track splicing part by the existing spraying track planning method, and can obtain a smooth blocked track, so that the whole spraying track is not influenced.
In one embodiment, the specific method for classifying the workpiece model curved surface by the k-means clustering algorithm to obtain the curved surfaces with different classification curvatures comprises the following steps:
setting a curvature threshold value +/-e;
classifying the curvature of the workpiece model curved surface according to the curvature threshold value +/-e;
taking the classification number of the curvature as the initial K point number K in the K-means clustering algorithmn(n=1,2,3.....);
Iterating the workpiece model data through the k-means clustering algorithm to obtain different classification curvature surfaces Cn(n=1,2,3...);
Wherein n is the number of classifications of the curvatures.
In one embodiment, the specific method for respectively performing trajectory planning on different classification curvature surfaces to obtain trajectory point information includes the following steps:
making an orthogonal plane at the over-clustering centroid to intersect with the target curved surface to obtain an orthogonal line of the over-clustering centroid 1, as shown in fig. 3;
discretizing the orthogonal lines according to the spraying distance to obtain equidistant discrete points 2, as shown in fig. 4;
selecting a plurality of equidistant surfaces according to the equidistant discrete points 2, and performing orthogonality on the equidistant surfaces to obtain a plurality of equidistant orthogonal lines 3;
discretizing a plurality of said equidistant orthogonal lines 3 to obtain a plurality of tracing points 4, as shown in fig. 5;
sequencing a plurality of track points 4 to obtain track point information Cn,j;
Wherein n represents a curved surface and j represents a track point.
Specifically, as shown in fig. 6, the curvature surfaces C for different classificationsn(n ═ 1,2, 3.) for a corresponding spray spacing dkIs d-h tan α, where h is the selected height of the spray and α is equal to half the angular arc of the sector formed by the paint delivered by the spray gun 5.
In one embodiment, the specific method for obtaining the NURBS curve control point according to the track point information includes the following steps;
height selected according to sprayingFor the track point information Cn,jPerforming offset processing on the track point information C after the offset processingn,jFrom C'n,j;
Track point information C 'after offset processing'n,jNURBS curve control points are solved reversely for the model value points.
In one embodiment, according to a formulaProcessing the NURBS curve control points to obtain a smoothed block trajectory, wherein ω isiAs a weighting factor, DiAre curve control points.
In one embodiment, the specific method for splicing the blocked tracks by sorting the head and tail end points of the blocked tracks and optimizing the spraying track curve by adding a control point and a weight factor at the spliced position of the blocked tracks comprises the following steps:
a line segment of the block track with the tail end connected with the head end is used as a diameter to make a circle, and then a vertical bisector is made at the diameter to obtain two intersection points with the circle, as shown in fig. 7;
and selecting the newly added upper control point or the lower control point. Specifically, based on the two intersection points and according to the influence of the concave-convex degree of the curvature of the curved surface on the uniformity of the spraying thickness, selecting a newly added upper control point or a newly added lower control point;
setting a weight factor omegaiIn combination with said weight factor omegaiAnd the newly added control point DqCurve F (D) of the selected weighting functionq,ωi(x, y, z)), wherein (x, y, z) is a formal point expression.
Specifically, due to the fact that the distances of the curves close to the newly added control points are different due to different weight factors, the requirement for the uniformity of the spraying thickness can be met by adjusting the height of the spray gun 5 from the surface of the workpiece. The distance from the highest point of the spray gun 5 to the splicing part is set as hpWeight factor ωi<ωmax,ωmaxIs the maximum weight factor, the spraying thickness uniformity coefficient is beta, and the spraying thickness is PiThen adding a control pointDqThe lower weight function curve is F (D)q,ωi(x, y, z)). Wherein, (x, y, z) is a type point expression form. M (P)i,β,hp) Is hpEvaluation function of spray thickness under change.
Due to hp=Fh=F(Dq,ωi,(0,0,zp)),(0,0,zp) Represents the highest point position of the curve, so M (P)i,β,Fh). That is, based on the spraying thickness evaluation function, and by adopting an adaptive algorithm to obtain a suitable weight factor, a spraying trajectory curve can be optimized.
In one embodiment, the present invention provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the NURBS curve-based spray trajectory transition optimization method as described above.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A NURBS curve-based spray trajectory transition optimization system, comprising:
the trajectory generation module is used for classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces and respectively carrying out trajectory planning on the different classification curvature curved surfaces to obtain trajectory point information;
the track fitting module is used for solving NURBS curve control points according to the track point information and processing the NURBS curve control points to obtain a smooth block track;
and the track optimization module is used for splicing the blocked tracks by sequencing the head and tail end points of the blocked tracks and optimizing the spraying track curve by adding control points and weight factors at the splicing positions of the blocked tracks.
2. The NURBS curve-based spray trajectory transition optimization system of claim 1, further comprising a curved surface acquisition module configured to acquire workpiece model data and to acquire a workpiece model curved surface based on the workpiece model data.
4. The NURBS curve-based spray trajectory transition optimization system of claim 3, wherein the weighting function curve at the newly added control points is F (D)q,ωi(x, y, z)), wherein DqTo newly add a control point, omegaiFor the weighting factors, (x, y, z) is a formal point expression.
5. A spraying track transition section optimization method based on a NURBS curve is characterized by comprising the following steps:
classifying the workpiece model curved surface through a k-means clustering algorithm to obtain different classification curvature curved surfaces, and respectively performing track planning on the different classification curvature curved surfaces to obtain track point information;
according to the track point information, obtaining NURBS curve control points, and processing the NURBS curve control points to obtain a smooth block track;
and splicing the blocked tracks by sequencing the head and tail end points of the blocked tracks, and optimizing a spraying track curve by adding control points and weight factors at the splicing positions of the blocked tracks.
6. The NURBS curve-based spraying track transition section optimization method as claimed in claim 5, wherein the specific method for classifying the workpiece model curved surface through the k-means clustering algorithm to obtain the curved surfaces with different classification curvatures comprises the following steps:
setting a curvature threshold value;
classifying the curvature of the workpiece model curved surface according to the curvature threshold;
taking the classification number of the curvature as the initial K point number K in the K-means clustering algorithmn(n=1,2,3.....);
Iterating the workpiece model data through the k-means clustering algorithm to obtain different classification curvature surfaces Cn(n=1,2,3...);
Wherein n is the number of classifications of the curvatures.
7. The NURBS curve-based spraying track transition section optimization method as claimed in claim 6, wherein the specific method for respectively performing track planning on different classification curvature curved surfaces to obtain track point information comprises the following steps:
making an orthogonal surface at the over-clustering centroid to intersect with the target curved surface so as to obtain an orthogonal line of the over-clustering centroid;
discretizing the orthogonal lines according to the spraying distance to obtain equidistant discrete points;
selecting a plurality of equidistant surfaces according to the equidistant discrete points, and performing orthogonality on the equidistant surfaces to obtain a plurality of equidistant orthogonal lines;
discretizing the equidistant orthogonal lines to obtain a plurality of track points;
sequencing a plurality of the track points to obtain the track point information Cn,j;
Wherein n represents a curved surface and j represents a track point.
8. The method for optimizing the transition section of the spraying track based on the NURBS curve as claimed in claim 7, wherein the specific method for obtaining the control points of the NURBS curve according to the track point information comprises the following steps;
selecting the height according to the spraying to the track point information Cn,jCarrying out offset processing;
and reversely solving the NURBS curve control point by taking the track point information after the offset processing as a model value point.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when being executed by a processor, carries out the NURBS curve-based spray trajectory transition optimization method according to any one of the preceding claims 5 to 9.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110087513.0A CN112766577A (en) | 2021-01-22 | 2021-01-22 | Spraying track transition section optimization system and method based on NURBS curve |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110087513.0A CN112766577A (en) | 2021-01-22 | 2021-01-22 | Spraying track transition section optimization system and method based on NURBS curve |
Publications (1)
Publication Number | Publication Date |
---|---|
CN112766577A true CN112766577A (en) | 2021-05-07 |
Family
ID=75705672
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110087513.0A Pending CN112766577A (en) | 2021-01-22 | 2021-01-22 | Spraying track transition section optimization system and method based on NURBS curve |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112766577A (en) |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104820744A (en) * | 2015-04-30 | 2015-08-05 | 柳州宏开汽车科技有限公司 | Generation method for NURBS tool path in curved surface numerical control machining |
US20170018118A1 (en) * | 2015-07-17 | 2017-01-19 | Board Of Trustees Of Michigan State University | Electromagnetic Scattering Analysis Module Using Subdivision Based Isogeometric Analysis |
CN106354098A (en) * | 2016-11-04 | 2017-01-25 | 大连理工大学 | Method for forming cutter machining tracks on NURBS combined curved surface |
US10520600B1 (en) * | 2017-03-23 | 2019-12-31 | United States Of America As Represented By The Secretary Of The Navy | Methods and systems for automated mission area segmentation |
CN110750830A (en) * | 2019-10-18 | 2020-02-04 | 北京申信达成科技有限公司 | Wood structure ancient building health state assessment method based on normal cloud model |
US20200151286A1 (en) * | 2018-11-09 | 2020-05-14 | Autodesk, Inc. | Conversion of geometry to boundary representation with facilitated editing for computer aided design and 2.5-axis subtractive manufacturing |
CN111490489A (en) * | 2020-04-16 | 2020-08-04 | 北京天下宏图空间信息技术有限公司 | Unmanned aerial vehicle trajectory planning method and device for power transmission line inspection |
CN111496789A (en) * | 2020-04-23 | 2020-08-07 | 佛山科学技术学院 | Offline complex curved surface spraying track planning system and control method |
CN114943130A (en) * | 2021-02-16 | 2022-08-26 | 达索系统公司 | Segmenting a 3D modeled object representing a mechanical component |
-
2021
- 2021-01-22 CN CN202110087513.0A patent/CN112766577A/en active Pending
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104820744A (en) * | 2015-04-30 | 2015-08-05 | 柳州宏开汽车科技有限公司 | Generation method for NURBS tool path in curved surface numerical control machining |
US20170018118A1 (en) * | 2015-07-17 | 2017-01-19 | Board Of Trustees Of Michigan State University | Electromagnetic Scattering Analysis Module Using Subdivision Based Isogeometric Analysis |
CN106354098A (en) * | 2016-11-04 | 2017-01-25 | 大连理工大学 | Method for forming cutter machining tracks on NURBS combined curved surface |
US10520600B1 (en) * | 2017-03-23 | 2019-12-31 | United States Of America As Represented By The Secretary Of The Navy | Methods and systems for automated mission area segmentation |
US20200151286A1 (en) * | 2018-11-09 | 2020-05-14 | Autodesk, Inc. | Conversion of geometry to boundary representation with facilitated editing for computer aided design and 2.5-axis subtractive manufacturing |
CN110750830A (en) * | 2019-10-18 | 2020-02-04 | 北京申信达成科技有限公司 | Wood structure ancient building health state assessment method based on normal cloud model |
CN111490489A (en) * | 2020-04-16 | 2020-08-04 | 北京天下宏图空间信息技术有限公司 | Unmanned aerial vehicle trajectory planning method and device for power transmission line inspection |
CN111496789A (en) * | 2020-04-23 | 2020-08-07 | 佛山科学技术学院 | Offline complex curved surface spraying track planning system and control method |
CN114943130A (en) * | 2021-02-16 | 2022-08-26 | 达索系统公司 | Segmenting a 3D modeled object representing a mechanical component |
Non-Patent Citations (3)
Title |
---|
HAICHU CHEN ET AL.,: "The trajectory planning system for spraying robot based on k-means clustering and NURBS curve optimization", IEEE, pages 5356 - 5361 * |
HAICHU CHEN ET AL.: "The trajectory planning system for spraying robot based on k-means clustering and NURBS curve", 《 IECON 2020 THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY》, pages 5357 * |
李文龙;李中伟;毛金城;: "iPoint3D曲面检测软件开发与工程应用综述", 机械工程学报, no. 07 * |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105741355B (en) | A kind of block dividing method of triangle grid model | |
CN110039538B (en) | Robot track planning method based on large complex component point cloud information | |
CN112284290B (en) | Autonomous measurement method and system for aero-engine blade robot | |
CN111283686B (en) | Grabbing pose calculation method for live working robot in grabbing branch line scene | |
CN110458174B (en) | Precise extraction method for key feature points of unordered point cloud | |
CN109976262B (en) | Global curvature continuous fairing method for micro-line segment processing | |
CN110866934B (en) | Normative coding-based complex point cloud segmentation method and system | |
CN112396690B (en) | Curved surface high-precision reconstruction method based on improved centripetal parameterization method | |
CN109683552A (en) | A kind of Machining Path generation method on the complicated point cloud model of basal plane curve orientation | |
CN112364442A (en) | Bidirectional intelligent selection fluid-solid coupling analysis method | |
Xie et al. | A robotic belt grinding approach based on easy-to-grind region partitioning | |
Wang et al. | A new point cloud slicing based path planning algorithm for robotic spray painting | |
CN104331933A (en) | Slicing direction self-adaptive rapid selection method | |
CN108038259B (en) | Method for generating pneumatic component appearance based on curvature | |
CN108594764B (en) | Equal-residual-height tool contact point track generation method for triangular mesh model | |
CN114227685A (en) | Mechanical arm control method and device, computer readable storage medium and mechanical arm | |
Van Dang et al. | Enhanced vector flow of significant directions for five-axis machining of STL surfaces | |
CN108508847A (en) | A method of the high small line segment of error is bent based on approximation etc. and approaches Nurbs curves | |
CN113171913B (en) | Spraying path generation method based on three-dimensional point cloud of seat furniture | |
CN112766577A (en) | Spraying track transition section optimization system and method based on NURBS curve | |
CN112085837B (en) | Three-dimensional model classification method based on geometric shape and LSTM neural network | |
CN110928326A (en) | Measuring point difference planning method for aircraft appearance | |
Wang et al. | A deep learning based automatic surface segmentation algorithm for painting large-size aircraft with 6-DOF robot | |
CN111610751A (en) | Iterative calculation method for repeatedly subdividing interpolation errors of NURBS (non-uniform rational B-spline) interpolation curve of over-point set | |
CN110207618B (en) | Surface line data extraction method of three-dimensional scanning measurement data |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |