CN109163674A - Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional - Google Patents
Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional Download PDFInfo
- Publication number
- CN109163674A CN109163674A CN201810994182.7A CN201810994182A CN109163674A CN 109163674 A CN109163674 A CN 109163674A CN 201810994182 A CN201810994182 A CN 201810994182A CN 109163674 A CN109163674 A CN 109163674A
- Authority
- CN
- China
- Prior art keywords
- measurement
- viewpoint
- candidate
- volume block
- average
- 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.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
Abstract
The invention belongs to the technical fields of three-dimensional measurement, and disclose sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional.This method includes the following steps: that (a) wraps up the 3 d structure model of object to be measured using multiple cubic volume blocks；(b) six hemisphere faces and candidate measurement viewpoint are constructed in each volume block；(c) it asks friendship to obtain multiple spline surfaces single volume block and 3 d structure model, solves central point, the method for average resultant area of each spline surface；(d) method of average for calculating each spline surface in single volume block swears zenith angle and azimuth in three-dimensional system of coordinate, determines region belonging to each spline surface；(e) the measurement mass parameter of candidate measurement viewpoint is calculated；(f) each candidate corresponding mass parameter of viewpoint that measures is compared the required measurement viewpoint of acquisition with preset threshold.Through the invention, calculating process is simple, high degree of automation, the planning suitable for complex parts measurement viewpoint.
Description
Technical field
The invention belongs to the technical fields of three-dimensional measurement, measure more particularly, to a kind of area-structure light automatized three-dimensional
Middle sensor measurement viewpoint planning method.
Background technique
Area-structure light automatized three-dimensional measurement is mostly by degree of freedom robot positioning surface structural light three-dimensional sensor, from multiple
Measurement viewpoint measures part, to obtain complete three-dimensional data.But many design of part are complicated, since vision hides
Gear, required measurement viewpoint is very more, to increase time of measuring.It is all to rely on to have experience artificial at this stage, to machine
People carries out artificial teaching, completes the editor of measurement viewpoint.This process is very time-consuming, and is difficult to obtain optimal measurement view
Point, to improve measurement efficiency.
In order to fast and accurately cook up measurement viewpoint, domestic and international many units, which begin one's study, to be measured viewpoint and plans automatically
Technology.The measurement viewpoint planning technology of comparative maturity can be divided into three classes mode at present:
1) detection pattern again is generated.The mode firstly generates candidate measurement viewpoint, then by measurement task constraint condition by
The candidate measurement viewpoint of a assessment, finishing screen select optimal measurement viewpoint.The mode is a kind of original measurement viewpoint planning mode,
Thinking is simple and clear, and algorithm design difficulty is small, can introduce a variety of constraint conditions, and small to the dependence of reference model.The disadvantage is that
Need to calculate a large amount of candidate measurement viewpoints, low efficiency, candidate's measurement viewpoint discrete distribution in space, the optimal measurement view of generation
Point may be excessive and inaccurate because of being spaced.
2) synthesis model.The correlation between various constraints in the pattern analysis measurement task is based on these relationships
Directly generate the measurement viewpoint for being best suitable for restrictive condition.The mode focuses on the relationship and survey understood between model various parameters
Mission requirements are measured, purpose is clear in planning process, and calculated result is accurate and can be adjusted according to the difference of mission requirements,
It is a kind of advanced Planning Model.But the difficulty that this mode carrys out algorithm for design is higher, analyzes and closes between various parameters
System is exactly a difficult process；The mode heavy dependence various parameters simultaneously, the requirement to model is high, needs a pretreatment
Process.
3) expert system model.The running basis of the mode includes structural light three-dimensional measurement constraint and reflection model constraint
Expert system, in measurement task information input to system, expert system can provide generate viewpoint needed for parameter suggestion
Value finally generates measurement viewpoint by these recommended values.Expert system is a kind of very high Planning Model of intelligence degree, exploitation
Difficulty is big, leads to show at this stage mature viewpoint planning album system, and existing expert system is not only capable of providing illumination ginseng
Several recommended values, and the recommended value of view point dependent parameters can not be provided.The perfect viewpoint planning expert system of development function also needs
It further to study.
In conclusion need to consider numerous measurement factor and condition in viewpoint generating process, still not no mature technology
Automation best view planning automatically can be carried out to complex parts measurement.
Summary of the invention
Aiming at the above defects or improvement requirements of the prior art, the present invention provides a kind of surveys of area-structure light automatized three-dimensional
Sensor measurement viewpoint planning method in amount, by being constructed using the characteristic parameter of area-structure light automatized three-dimensional measurement sensor
Multiple cubic volume blocks, and the 3 d structure model of object to be measured is wrapped up using multiple volume blocks, then according to each volume
The intersection of block and threedimensional model cooks up the optimal measurement viewpoint in each volume block, is obtained in all volume blocks with this
Optimal measurement viewpoint, this method calculating process is simple, high degree of automation, the planning suitable for complex parts measurement viewpoint.
To achieve the above object, it is proposed, according to the invention, provide sensor in a kind of measurement of area-structure light automatized three-dimensional and survey
Measure viewpoint planning method, which is characterized in that this method includes the following steps:
(a) the area-structure light automatized three-dimensional sensor for measuring object to be measured is chosen, and the single width for obtaining the sensor is surveyed
Range, the measurement depth of field and optimum measurement distance are measured, for the 3 d structure model of object to be measured, using multiple cubic volume blocks
Wrap up the 3 d structure model, wherein using the single width measurement range and measure the depth of field as the bottom of the volume block
Face and height；
(b) for single volume block, three-dimensional system of coordinate is established using the center of the volume block as origin, and to each volume
Block constructs six hemisphere faces, and the corresponding region of each hemisphere face makees a plurality of uniform point by starting point of each hemispherical centre of sphere
The ray of cloth, the ray and the hemispherical intersection point are candidate measurement viewpoint, wherein the hemisphere face is with the volume block
Center is the centre of sphere, and the vertical direction at center to each face of volume block is radial direction, and the optimum measurement distance is half path length
Degree；
(c) single volume block and the 3 d structure model are asked into friendship, the 3 d structure model is obtained in the body with this
Multiple spline surfaces in block solve central point, the method for average resultant area of each spline surface,；
(d) method of average for calculating each spline surface in single volume block swears the zenith in the three-dimensional system of coordinate
Angle and azimuth, according to the zenith angle and azimuth determine every spline surface belonging to region；
(e) candidate in the central point of every spline surface, each region of method of average resultant areal calculation is utilized
The measurement mass parameter of viewpoint is measured, it is corresponding to obtain each candidate measurement viewpoint in six regions in single volume block with this
Measure mass parameter；
(f) step (b)~(e) is repeated, the measurement mass parameter of the candidate measurement viewpoint in all volume blocks is obtained with this,
The corresponding mass parameter of each candidate's measurement viewpoint is compared with preset threshold, the conduct greater than the preset threshold is optimal
Measure viewpoint, i.e., required measurement viewpoint.
It is further preferred that the measurement mass parameter is preferably calculated according to following expression formula in step (d):
Cfmq=aCfvis+b·Cfθ
Wherein, wherein a and b is the weight rule of thumb set, CfvisAnd CfθRespectively visual parameter and molding matter
Parameter is measured, is obtained by the central point of spline surface, method of average resultant areal calculation.
It is further preferred that the visuality parameter CfvisIt is preferred that being calculated according to the following steps:
S1 connects candidate's measurement point and the candidate measures in viewpoint region and owns using candidate's measurement viewpoint as starting point
The central point of spline surface obtains a plurality of straight line with this；
S2 detects whether every straight line interferes with the 3 d structure model, by all there is no interference
The area of spline surface corresponding to straight line obtains the visual parameter respectively multiplied by summing after preset ratio coefficient
Cfvis。
It is further preferred that the Forming Quality parameter CfθIt is preferred that being calculated according to the following steps:
S1 calculates the method for average arrow in each region
For S2 using the central point of each volume block as starting point, candidate's measurement point is terminal, and connection source and terminal obtain
Vector
S3 calculates method of average arrowWith the vectorBetween angle, assigned according to the size of angle different pre-
If value, which is the Forming Quality parameter.
It is further preferred that the method for average in each region is swearedIt is preferred that calculating as follows: to each area
The product that all respective areas of spline surface are sweared with the method for average in domain is summed, the method for average arrow in as each region
In general, through the invention it is contemplated above technical scheme is compared with the prior art, can obtain down and show
Beneficial effect:
1, the present invention generates six groups of candidates in each single width measurement volume block and measures viewpoint, and every group of candidate measures viewpoint point
It is not corresponding with spline surface subregion, when calculating measurement mass parameter, only calculate candidate measurement viewpoint and corresponding spline surface subregion
Visual parameter and image quality parameter between interior spline surface, on the one hand reduce calculation amount, on the other hand avoid
The calculating mistake that extreme spline surface may cause；
2, the present invention is constituted measurement mass parameter with visual parameter and image quality parameter, is regarded as optimal measurement is screened
The standard of point, has taken into account the image quality of three-dimensional data quantity and three-dimensional data, and it is practical to be more in line with production；
3, method provided by the invention by object to be measured the automatic planning survey viewpoint of 3 d structure model, planning process without
Human intervention, high degree of automation are needed, and plans that speed is fast, after obtaining optimal measurement viewpoint using the present invention, is greatly improved certainly
The measurement efficiency of area-structure light three-dimension sensor when dynamicization measures.
Detailed description of the invention
Fig. 1 is planing method flow chart constructed by preferred embodiment according to the invention；
Fig. 2 is the package 3 d structure model of volume block constructed by preferred embodiment according to the invention；
Fig. 3 is six hemisphere faces of each volume block building constructed by preferred embodiment according to the invention；
Fig. 4 is the signal that candidate measurement viewpoint is generated in single volume block constructed by preferred embodiment according to the invention
Figure；
Fig. 5 is spline surface subregion schematic diagram in single volume block constructed by preferred embodiment according to the invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below
Not constituting a conflict with each other can be combined with each other.
Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional, this method have following steps real
It is existing:
Step 1: the biography of cubic shaped is determined with the single width measurement range of area-structure light three-dimension sensor and the measurement depth of field
Sensor single width measures volume block, wherein single width measurement range is the bottom surface of the cube, measures the span conduct cube of the depth of field
The height of body；Several single width are measured into volume block close-packed arrays, wrap up measured object with comprising minimum number single width measurement volume block
Body CAD model；
Step 2: for each measurement volume block, using the center of single width measurement volume block as the centre of sphere, area-structure light three-dimensional is passed
The optimum measurement distance of sensor is radius, determines six hemisphere faces.Zenith angle and azimuth are respectively with 15 ° on each hemisphere face
Interval, uniform to generate candidate measurement viewpoint, symbiosis measures candidate viewpoints at six groups of candidates, and to it by 1-6 number.Each
Single width measures the corresponding six groups of candidate's viewpoints of volume block and constitutes a candidate viewpoint collection.Body is measured for each single width in step 1
Block generates a candidate viewpoint collection；
Step 3: single single width measurement volume block and testee CAD model being asked into friendship, is obtained and is asked in intersection with this
Central point (the P of all spline surfacesp), the method for average arrowWith area (Sp).Central point method for solving is as follows, sampling bar
All vertex on curved surface profile line, obtain the coordinate value on all vertex under basis coordinates system, then by the coordinate value on all vertex
Its average value is taken, this average value is the central point for being used as the curved surface.The method of average swears that method for solving is as follows, sampling bar curved surface profile
The method that all vertex obtain all vertex on line is lost, then these methods are lost and are summed, and result is just used as the method for average of the curved surface
It loses.Aforesaid operations are carried out to each single width measurement volume block in step 1；
Step 4: in single single width measurement volume block, calculating separately each spline surface method of average and lose and single width measurement body
Zenith angle θ and azimuth between block coordinate systemThe corresponding zenith angle of each hemisphere face and azimuth coverage, are dividing
When which area spline surface belong to, by the zenith angle of spline surface and azimuth zenith angle corresponding with each hemisphere face and orientation
The range at angle is compared, and determines which area spline surface belongs to this, is specifically divided according to following rule spline surface
Area:
1) 45 ° of θ < are divided into subregion 1；
2) 135 ° of θ > are divided into subregion 2；
3)It is divided into subregion 3；
4)It is divided into subregion 4；
5)It is divided into subregion 5；
6)It is divided into subregion 6.
Aforesaid operations are carried out to single width each in step 1 measurement volume block；
Step 5: in single single width measurement volume block, calculating the measurement quality ginseng that every group of candidate measures each viewpoint of viewpoint
Number Cfmq:
Cfmq=aCfvis+bCfθ
Wherein, a and b is the weight rule of thumb set, for example, a=5, b=3, CfvisAnd CfθRespectively visual ginseng
Several and Forming Quality parameter.
CfvisCalculation method it is as follows:
1) viewpoint is measured with the candidate and makees terminal；
2) P of a spline surface in the corresponding spline surface subregion of the affiliated group number of viewpoint is measured with the candidatepMake
Starting point, connection source terminal is in line；
3) detect whether the straight line can interfere with reference model；
If 4) do not interfere, the S of the spline surfacepIt is multiplied by a proportionality coefficient m and obtains mSp；
5) it participates in without any processing if interfering；
6) it repeats above operation, calculates all spline surfaces and the candidate in corresponding spline surface subregion and measure viewpoint m
SpIt is worth (if present)；
7) by all mSpIt is added, and as Cfvis。
Wherein CFθCalculation method it is as follows:
1) it is measured in the corresponding spline surface subregion of the affiliated group number of viewpoint in the candidate, calculates the method for average and lose
A) spline surface is taken in the spline surface subregion to seek vector using its area as weight
B) by the vector of all spline surfacesIt is added, and is
2) starting point is made with the central point of single width measurement volume block, candidate's measurement viewpoint makees terminal, does vector
3) it asksWithBetween angle theta；
A) 0 15 ° of < θ <；Cfθ=1.00a；
B) 15 ° of 30 ° of < θ <；Cfθ=0.75a；
C) 30 ° of 45 ° of < θ <；Cfθ=0.50a；
D) 45 ° of < θ；Cfθ=0.1a
A is proportionality coefficient in formula, can use arbitrary value, is only so that CfvisAnd CfθIt is in the same order of magnitude.
Aforesaid operations are carried out to each single width measurement volume block in space is measured in step 1；
Step 6: in single single width measurement volume block, the highest candidate viewpoint of measurement mass parameter is filtered out, as most
Excellent measurement viewpoint.Aforesaid operations are carried out to each single width measurement volume block in space is measured in step 1, are finally obtained several optimal
Measure viewpoint.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all include
Within protection scope of the present invention.
Claims (5)
1. a kind of sensor measurement viewpoint planning method in area-structure light automatized three-dimensional measurement, which is characterized in that this method packet
Include the following steps:
(a) the area-structure light three-dimension sensor for measuring object to be measured is chosen, and obtains the single width measurement range of the sensor, measurement
The depth of field and optimum measurement distance, for the 3 d structure model of object to be measured, using multiple cubic volume blocks package described three
Tie up structural model, wherein bottom surface and height using the single width measurement range and the measurement depth of field as the volume block；
(b) for single volume block, three-dimensional system of coordinate is established using the center of the volume block as origin, and to each volume block structure
Six hemisphere faces are built, the corresponding region of each hemisphere face is made a plurality of equally distributed using each hemispherical centre of sphere as starting point
Ray, the ray and the hemispherical intersection point are candidate measurement viewpoint, wherein the hemisphere face is with the center of the volume block
For the centre of sphere, the vertical direction at center to each face of volume block is radial direction, and the optimum measurement distance is radius length；
(c) single volume block and the 3 d structure model are asked into friendship, the 3 d structure model is obtained in the volume block with this
In multiple spline surfaces, solve central point, the method for average resultant area of each spline surface；
(d) calculate each spline surface in single volume block the method for average swear zenith angle in the three-dimensional system of coordinate and
Azimuth, according to the zenith angle and azimuth determine each spline surface corresponding to hemisphere face region；
(e) candidate measurement described in the central point of each spline surface, each region of method of average resultant areal calculation is utilized
The measurement mass parameter of viewpoint obtains each candidate in six regions in single volume block with this and measures the corresponding measurement of viewpoint
Mass parameter；
(f) step (b)~(e) is repeated, the measurement mass parameter of the candidate measurement viewpoint in all volume blocks is obtained with this, it will be every
A candidate corresponding mass parameter of viewpoint that measures is compared with preset threshold, the optimal measurement of the conduct greater than the preset threshold
Viewpoint, i.e., required measurement viewpoint.
2. planing method as described in claim 1, which is characterized in that in step (d), the measurement mass parameter is preferably pressed
It is calculated according to following expression formula:
Cfmq=aCfvis+b·Cfθ
Wherein, wherein a and b is the weight rule of thumb set, CfvisAnd CfθRespectively visual parameter and Forming Quality ginseng
Number is obtained by the central point of spline surface, method of average resultant areal calculation.
3. planing method as claimed in claim 2, which is characterized in that the visuality parameter CfvisIt is preferred that according to the following steps
It calculates:
S1 connects candidate's measurement point and the candidate measures all battens in viewpoint region using candidate's measurement viewpoint as starting point
The central point of curved surface obtains a plurality of straight line with this；
S2 detects whether every straight line interferes with the 3 d structure model, and there is no the straight lines of interference by all
The area of corresponding spline surface obtains the visual parameter Cf respectively multiplied by summing after preset ratio coefficientvis。
4. planing method as claimed in claim 2, which is characterized in that the Forming Quality parameter CfθIt is preferred that according to the following steps
It calculates:
S1 calculates the method for average arrow in each region
For S2 using the central point of each volume block as starting point, candidate's measurement point is terminal, and connection source and terminal obtain vector
S3 calculates method of average arrowWith the vectorBetween angle, assigned according to the size of angle different default
Value, which is the Forming Quality parameter.
5. planing method as claimed in claim 4, which is characterized in that the method for average in each region is swearedIt is preferred that according to
Following manner calculates: the product sweared to the respective area of spline surfaces all in each region with the method for average is summed, as
The method of average in each region is sweared
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810994182.7A CN109163674B (en) | 2018-08-29 | 2018-08-29 | Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810994182.7A CN109163674B (en) | 2018-08-29 | 2018-08-29 | Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109163674A true CN109163674A (en) | 2019-01-08 |
| CN109163674B CN109163674B (en) | 2019-08-13 |
Family
ID=64893381
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810994182.7A Active CN109163674B (en) | 2018-08-29 | 2018-08-29 | Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109163674B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111462330A (en) * | 2020-03-30 | 2020-07-28 | 成都飞机工业（集团）有限责任公司 | Measuring viewpoint planning method based on plane normal projection |
| CN111907727A (en) * | 2020-06-17 | 2020-11-10 | 成都飞机工业（集团）有限责任公司 | Method for selecting outline measurement points of airplane wing framework |
| CN113551613A (en) * | 2021-06-24 | 2021-10-26 | 储信(北京)科技发展有限公司 | Method for specifying optimal placement position of article in area |
-
2018
- 2018-08-29 CN CN201810994182.7A patent/CN109163674B/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111462330A (en) * | 2020-03-30 | 2020-07-28 | 成都飞机工业（集团）有限责任公司 | Measuring viewpoint planning method based on plane normal projection |
| CN111907727A (en) * | 2020-06-17 | 2020-11-10 | 成都飞机工业（集团）有限责任公司 | Method for selecting outline measurement points of airplane wing framework |
| CN113551613A (en) * | 2021-06-24 | 2021-10-26 | 储信(北京)科技发展有限公司 | Method for specifying optimal placement position of article in area |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109163674B (en) | 2019-08-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109163674B (en) | Sensor measurement viewpoint planning method in a kind of measurement of area-structure light automatized three-dimensional | |
| CN104142514B (en) | Three-dimensional earthquake observing system quantitative designing method | |
| CN104102845B (en) | The interpolation method of dimension self-adaption and the interplotation system of dimension self-adaption | |
| CN105787281B (en) | Fusion inversion method and device for sea wave significant wave height field | |
| CN103136393B (en) | A kind of areal coverage computing method based on stress and strain model | |
| CN101424520B (en) | Method for detecting partial contour outline of object curved surface | |
| CN109685848A (en) | A kind of neural network coordinate transformation method of three-dimensional point cloud and three-dimension sensor | |
| CN105093299B (en) | A kind of method and device based on geophone offset slice of vector technical optimization observation system | |
| CN109444813A (en) | A kind of RFID indoor orientation method based on BP and DNN amphineura network | |
| CN105973246A (en) | Drawing method and apparatus of geomagnetic map, and robot | |
| CN103106632B (en) | A kind of fusion method of the different accuracy three dimensional point cloud based on average drifting | |
| CN108459298A (en) | A kind of outdoor positioning method based on LoRa technologies | |
| CN102914795B (en) | Method for detecting illuminance of offset pair | |
| CN104053129A (en) | Wireless sensor network indoor positioning method and device based on sparse RF fingerprint interpolations | |
| CN110009667A (en) | Multi-viewpoint cloud global registration method based on Douglas Rodríguez transformation | |
| CN107862712A (en) | Sized data determines method, apparatus, storage medium and processor | |
| CN108305277A (en) | A kind of heterologous image matching method based on straightway | |
| CN104463970A (en) | Method for determining three-dimensional gravity center of city based on remote-sensing image and application thereof | |
| CN108537361A (en) | A kind of addressing appraisal procedure of mobile radar and communication station | |
| CN208780164U (en) | Full depth array inclinometer | |
| CN106815577A (en) | A kind of recognition methods of ocean mesoscale eddy and device | |
| CN104050660A (en) | Method for measuring workpiece round edges | |
| CN103364833A (en) | High-precision dip estimation method | |
| CN106403818A (en) | System and method for on-line detection of size parameters of large square tubes of multiple specifications | |
| CN109884698B (en) | Quantitative evaluation method of seismic exploration observation system based on target layer |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |