CN111486802A - Rotating shaft calibration method based on self-adaptive distance weighting - Google Patents
Rotating shaft calibration method based on self-adaptive distance weighting Download PDFInfo
- Publication number
- CN111486802A CN111486802A CN202010264708.3A CN202010264708A CN111486802A CN 111486802 A CN111486802 A CN 111486802A CN 202010264708 A CN202010264708 A CN 202010264708A CN 111486802 A CN111486802 A CN 111486802A
- Authority
- CN
- China
- Prior art keywords
- coordinate system
- calibration
- calibration plate
- rotating shaft
- camera
- 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
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000006243 chemical reaction Methods 0.000 claims abstract description 17
- 230000000007 visual effect Effects 0.000 claims abstract description 10
- 230000003287 optical effect Effects 0.000 claims description 9
- 230000003044 adaptive effect Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000003384 imaging method Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 3
- 230000001419 dependent effect Effects 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 238000011089 mechanical engineering Methods 0.000 description 1
- 238000013488 ordinary least square regression Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
A rotating shaft calibration method based on self-adaptive distance weighting utilizes a checkerboard calibration plate to calibrate a rotating shaft of a rotary table. Placing the chessboard grid calibration plate on the rotary platform in an inclined manner, positioning the calibration plate in the camera visual field, rotating the rotary platform, collecting the calibration plate image, and establishing a camera coordinate system Ov and a calibration plate coordinate system OBAnd obtaining coordinates under a camera coordinate system of all the chessboard pattern calibration plate angular points at least 3 different rotation positions by utilizing the conversion relation, and then calculating the circle center of a track circle formed by the angular points rotating along with the chessboard pattern calibration plate. And determining a weighting coefficient of the center of the angular point track according to the distance between the front position and the rear position of the angular point, and taking a straight line with the minimum weighted square sum of the distances from the centers of the track circles to the rotating shaft to be calibrated under the camera coordinate as the rotating shaft under the camera coordinate system. By the method, the calibration of the rotating shaft can be quickly and accurately realized, and compared with the traditional calibration method, the error is reduced by 15.6%.
Description
Technical Field
The invention relates to a rotating shaft calibration method based on self-adaptive distance weighting, and belongs to the technical field of optical measurement and mechanical engineering.
Background
When structured light three-dimensional measurement is carried out, due to the problems of camera view field, shooting angle and the like, only point clouds at a certain angle can be measured in one-time measurement, and the point clouds at different viewing angles need to be spliced for realizing complete measurement of a measured object. The current common point cloud splicing method mainly comprises automatic splicing and instrument-dependent splicing. The Point cloud automatic stitching is mainly based on an Iterative Closest Point (ICP) method, which has high precision but requires a superposition portion between two Point clouds, and the selection of an initial value has a large influence on a final stitching result. The instrument-dependent splicing method mainly comprises a marking point utilization method and a rotating platform utilization method. The mark point splicing method is mainly used for measuring large objects, the precision of the mark point splicing method is easily influenced by the deformation of the mark points, and the mark point splicing method is not suitable for measuring objects with larger curvature and complex surfaces; the method of utilizing the rotary platform is that a measured object is placed on the rotary platform, multi-angle measurement is carried out on the measured object, conversion relation among point clouds of different angles is obtained by means of rotary shaft parameters of the rotary platform, and finally point cloud splicing is achieved. The method has the advantages of high speed and high precision, and is widely researched and used, but the precision of the method is greatly influenced by the rotating shaft of the turntable, so that the rotating shaft needs to be accurately calibrated.
The method mainly comprises a rotating shaft calibration method based on a cylindrical calibration block, the method measures more than three pieces of cylindrical surface point clouds with different angles, and calibrates parameters of a rotating shaft by using the axes of the cylindrical surface point clouds, the rotating shaft calibration method based on a calibration ball measures the point clouds of the calibration ball with different rotating positions, the circle center of the point clouds is fitted, and finally the rotating shaft parameters are calibrated by using the circle center, the rotating shaft calibration method based on a cone calibration block uses the vertex coordinates of a cone to calibrate the rotating shaft, the rotating shaft calibration method based on an L type plane calibration object solves a rotating shaft equation by measuring right-angled planes before and after rotation and solving the intersection line of the right-angled planes.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a rotating axis calibration method based on self-adaptive distance weighting so as to improve the precision of rotating axis calibration.
The invention adopts the following technical scheme:
a rotating shaft calibration method based on adaptive distance weighting comprises the following steps:
step 1: establishing a camera coordinate system Ov and a calibration board coordinate system OBAnd a camera coordinate system Ov and a calibration plate coordinate system OBThe relationship between the two conversion modes is converted,
step 2: placing the chessboard pattern calibration board on the rotary platform in an inclined way and enabling the calibration board to be positioned in a camera visual field, rotating the rotary platform and collecting images of the calibration board to obtain coordinates under a calibration board coordinate system of all chessboard pattern calibration board angular points at least 3 different rotary positions, then obtaining coordinates under the camera coordinate system of all chessboard pattern calibration board angular points at least 3 different rotary positions by utilizing the conversion relation between the camera coordinate system and the calibration board coordinate system,
and step 3: selecting points (a, b, c) with coordinates which are the average value of the coordinates of the centers of the circle centers of the tracks corresponding to the angular points,
(XQi,YQi,ZQi) The method comprises the following steps of taking the coordinates of the center of a track circle corresponding to the ith angular point, wherein i is 1,2 …, m represents the serial number of the angular point, m is the total number of the angular points on a chessboard grid calibration plate, taking points (a, b and c) as points on a rotating shaft, performing space straight line fitting on the center of the track circle formed by the angular points rotating along with the chessboard grid calibration plate to obtain the rotating shaft under the camera coordinate, and finally converting the rotating shaft under the camera coordinate by using the conversion relation between a camera coordinate system and a calibration plate coordinate system to finish the calibration of the rotating shaft, wherein the space straight line fitting adopts the following method:
taking a straight line L with the minimum weighted square sum of the distances from the centers of the track circles to the rotating shaft to be calibrated in the camera coordinate as the rotating shaft in the camera coordinate:
wherein,
di 2＝(XQi-a)2+(YQi-b)2+(ZQi-c)2-[u(XQi-a)+v(YQi-b)+w(ZQi-c)]2，dithe distance between the center of the ith angular point track circle and the rotation axis to be calibrated is [ u, v, w]Is a unit direction vector of a rotating shaft to be calibrated, s.t. represents constraint, min represents minimum value, αiWeighting coefficients corresponding to the centers of the ith angular point track circles, wherein i is an angular point serial number, j is 1,2 …, n represents a calibration plate position serial number, n is the total position number of the calibration plate, and lijAnd p is an integer larger than 1, and is the moving distance of the ith angular point between the jth rotating position and the (j + 1) th rotating position.
Compared with the prior art, the invention has the following beneficial effects:
when the rotating shaft is calibrated, considering that the rotating track centers corresponding to different angular points have different influences on the fitting precision of the rotating shaft, the invention provides a design weighting coefficient based on the moving distance between the front position and the rear position of each angular point, namely:
αiweighting coefficients corresponding to the centers of the ith corner locus circles, wherein i is a corner sequence number, j is 1,2 …, n represents a position sequence number of the calibration plate, n is the total position number of the calibration plate, and lijAnd the distance between the jth rotation position and the (j + 1) th rotation position of the ith angular point is used for enabling the center of a circle of each angular point track to correspond to the weighting coefficient to realize self-adaptive value taking, so that the smaller the center of the circle which contributes to the fitting precision of the rotation shaft is, the smaller the weighting coefficient is, and the larger the center of the circle which contributes to the fitting precision of the rotation shaft is, the larger the weighting coefficient is, and the fitting precision of the rotation shaft is improved. Specifically, the method comprises the following steps:
when the rotating shaft is calibrated, considering that different contribution of track centers of the angular points at different positions to the rotating shaft is different, a weighting coefficient is designed based on the distance between the front position and the rear position of the angular point, and the coefficient is designed according to the moving distance l between all the angular points on the jth position calibration plate and the previous positioni,jThe mean value of (2) is used as a boundary line, so that the weighting coefficient corresponding to the angular point with the movement distance smaller than the mean value is smaller than 1, the weighting coefficient corresponding to the angular point with the movement distance larger than the mean value is larger than 1, and in addition, the difference of the weighting coefficients of different angular points can be further expanded by carrying out calculation of power p, so that the contribution of the circle center with larger error to the fitting rotating shaft is reduced, and the contribution of the circle center with smaller error to the fitting rotating shaft is increased. The design method realizes the self-adaptive value taking of the weighting coefficient according to the moving distance of the front and rear positions of the angular points, thereby ensuring that the trace circle center with smaller error has larger contribution to the rotating shaft, avoiding the error caused by the default of the same contribution of the trace circle centers of the angular points in the traditional method, and effectively improving the calibration precision of the rotating shaft.
Drawings
FIG. 1 is a flow chart of the operation of the present invention.
Fig. 2 is a schematic view of corner positions in a camera coordinate system.
FIG. 3 is a flow chart of rotation axis fitting.
Fig. 4 schematic diagram of a rotating shaft calibration device, wherein 1 vision support, 2 industrial camera, 3 turntable, 4 checkerboard calibration plate.
FIG. 5 is a schematic diagram of a coordinate system transformation relationship, in which a circle is a rotation locus of an angular point, a middle straight line is a fitted rotation axis, and points near the straight line are centers of the rotation locus of the angular point.
FIG. 6 is a graph of results of a spin axis fit.
Fig. 7 error evaluation results.
Detailed Description
A rotating shaft calibration method based on adaptive distance weighting comprises the following steps:
step 1: establishing a camera coordinate system Ov and a calibration board coordinate system OBAnd a camera coordinate system Ov and a calibration plate coordinate system OBThe relationship between the two conversion modes is converted,
step 2: placing the chessboard pattern calibration board on the rotary platform in an inclined way and enabling the calibration board to be positioned in a camera visual field, rotating the rotary platform and collecting images of the calibration board to obtain coordinates under a calibration board coordinate system of all chessboard pattern calibration board angular points at least 3 different rotary positions, then obtaining coordinates under the camera coordinate system of all chessboard pattern calibration board angular points at least 3 different rotary positions by utilizing a conversion relation system between the camera coordinate system and the calibration board coordinate system,
and step 3: selecting points (a, b, c) with coordinates which are the average value of the coordinates of the centers of the circle centers of the tracks corresponding to the angular points,
(XQi,YQi,ZQi) The method comprises the following steps of taking the coordinates of the center of a track circle corresponding to the ith angular point, wherein i is 1,2 …, m represents the serial number of the angular point, m is the total number of the angular points on a chessboard grid calibration plate, taking points (a, b and c) as points on a rotating shaft, performing space straight line fitting on the center of the track circle formed by the angular points rotating along with the chessboard grid calibration plate to obtain the rotating shaft under the camera coordinate, and finally converting the rotating shaft under the camera coordinate by using the conversion relation between a camera coordinate system and a calibration plate coordinate system to finish the calibration of the rotating shaft, wherein the space straight line fitting adopts the following method:
taking a straight line L with the minimum weighted square sum of the distances from the centers of the track circles to the rotating shaft to be calibrated in the camera coordinate as the rotating shaft in the camera coordinate:
wherein,
di 2＝(XQi-a)2+(YQi-b)2+(ZQi-c)2-[u(XQi-a)+v(YQi-b)+w(ZQi-c)]2，dithe distance between the center of the ith angular point track circle and the rotation axis to be calibrated is [ u, v, w]Is a unit direction vector of a rotating shaft to be calibrated, s.t. represents constraint, min represents minimum value, αiWeighting coefficients corresponding to the centers of the ith angular point track circles, wherein i is an angular point serial number, j is 1,2 …, n represents a calibration plate position serial number, n is the total position number of the calibration plate, and lijThe moving distance of the ith corner point between the jth rotation position and the (j + 1) th rotation position is defined, p is an integer greater than 1, and p can be set to be 7 in this embodiment. In the present embodiment, it is preferred that,
the origin of the camera coordinate system is arranged at the optical center of the camera, the z axis of the camera coordinate system passes through the optical center and is vertical to the imaging plane of the camera, the direction facing the object to be shot is positive direction, the x axis passes through the optical center and is vertical to the z axis, the camera coordinate system is positioned in the horizontal direction of the imaging plane, the horizontal right direction facing the object is positive direction, the y axis passes through the optical center and is vertical to the x axis and the z axis, and the upward direction facing the object is positive direction; the origin of the coordinate system of the calibration board is arranged at the corner point of the lower right corner of the calibration board, the z axis of the coordinate system of the calibration board passes through the corner point and is vertical to the plane of the calibration board, the direction facing the camera is the positive direction, the x axis passes through the corner point and is vertical to the z axis, the coordinate system of the calibration board is positioned in the horizontal direction of the plane of the calibration board, the left direction faces the calibration board is the positive direction, the y axis passes through the corner point and is vertical to the x axis and the z axis, and the upward direction faces the; the camera coordinate system Ov and the calibration plate coordinate system OBThe inter-conversion relation is [ X ]VYVZV]T＝R[XBYBZB]T+t，XB，YB，ZBCalibration plate coordinate system O for any angle point on calibration plateBCoordinates of the lower part, coordinate values Z in the calibration plate coordinate system OBBDefault is 0, XV，YV， ZVIs the coordinate value of the corresponding point under the camera coordinate system Ov of any angular point on the calibration board and the corresponding point (X)V，YV，ZV) The coordinate value of (A) is obtained by camera shooting and using a coordinate system O of a calibration plateBAny corner point below (X)B， YB，ZB) And the corresponding point (X) of any one of the corner points under the camera coordinate system OvV，YV，ZV) And (5) calculating coordinates to obtain external parameter matrixes R and t.
The rotary platform comprises a visual support 2 and a rotary platform 3, a camera 1 is arranged on the visual support 2, a chessboard pattern calibration plate 4 is placed on the rotary platform 3, and the chessboard pattern calibration plate 4 is positioned in a camera field of view.
And rotating the platform at every rotation of 4-10 degrees and collecting the image of the calibration plate, specifically, rotating the platform at every rotation of 5 degrees and collecting the image of the calibration plate.
The movement distance l of the ith angular point between the jth rotation position and the (j + 1) th rotation positionijComprises the following steps: li，j＝||Pi，j+1-Pi，jL, wherein Pi,jThe ith angle point on the jth position calibration plate is represented by i, i is 1,2 …, m represents the serial number of the angle point, m is the total number of the angle points, the serial number of the angle point increases in an s-shaped manner from right to left and from bottom to top, j is 1,2 …, n represents the position serial number of the calibration plate, n is the total position number of the calibration plate, and | | represents the norm calculation.
The reason why the points (a, b, c) are points on the rotation axis is as follows: let (x)0,y0,z0) Is a point on line L:
x0＝a+x
y0＝b+y
z0＝a+z
x is to be0,y0,z0Substitution formula
And (4) obtaining:
wherein:
f(u,v,w)＝(1-u2)B11+(1-v2)B22+(1-w2)B33-2uvB12-2uwB13-2vwB23
thus, for any (u, v, w), there is:
when in usex＝y＝zWhen equal to 0
At this time, the process of the present invention,
the minimum value may be taken, i.e., the straight line L passes through points (a, b, c).
The design idea of the weighting coefficient is as follows: the relative movement distance l between all the angular points on the jth position calibration plate and the previous position is calibrated by the jth positioni,jThe mean value of (a) is used as a boundary, so that the weighting coefficient corresponding to the angular point with the moving distance smaller than the mean value is smaller than 1, and the weighting coefficient corresponding to the angular point larger than the mean value is larger than 1, thus, the center of a circle of each angular point track corresponds to the weighting coefficient to realize self-adaptive value taking. The purpose of taking p as the power of 7 is to further expand the difference between the weight coefficients of different angle points, thereby reducing the contribution of the circle center with larger error to the fitting rotating shaft and increasing the contribution of the circle center with smaller error to the fitting rotating shaft.
The design can give corresponding weight to the center of the corner locus according to the moving distance of the corner, namely the error of the center of the circle, so that the self-adaption of the weighting coefficient is realized, and the contribution of the center of the circle with smaller error to the fitting precision of the rotating shaft is larger.
The above di can be calculated by the following formula:
where | | represents the norm, then,
di 2＝(XQi-a)2+(YQi-b)2+(ZQi-c)2-[u(XQi-a)+v(YQi-b)+w(ZQi-c)]2。
the following description is given with reference to specific examples and embodiments of the present invention.
As shown in FIG. 3, the experimental apparatus of the present invention comprises 1 vision support, 2 industrial cameras, and 3 turntables. The visual support is provided with a mounting hole, and the camera is fixedly connected with the visual support through a bolt.
Establishing a camera coordinate system Ov and a calibration board coordinate system OBIn which the camera coordinate system Ov is fixed, calibrating the board coordinate systemOBIs varied with the rotation of the turntable. The determination of the rotation axis of the turntable can be converted into a representation of the rotation axis in the camera coordinate system.
The coordinates of the corner points in the coordinate system of the calibration plate are known, and the coordinates of the corner points in the coordinate system of the camera can be obtained according to the conversion relation.
And converting all corner point coordinates into a camera coordinate system, and performing subsequent processes in the camera coordinate system. The equation of the plane where the angular point trajectory circle is located is as follows:
Ax+By+Cz+D＝0
a, B and C respectively represent parameters of the plane normal vector, and can be calculated by using coordinates of three positions of any angular point. Taking three positions q of the same angular point1(x1,y1,z1)，q2(x2,y2,z2)，q3(x3,y3,z3) Relative amount of
Sum vector
The cross product is performed to obtain the normal vector of the plane space, i.e.
The distance from different positions of the same angular point on a track circle to the center of a circle is known to be equal to the radius, and the center of the circle and the angular point are on the same plane, so that the relation satisfies the equation:
||Pi，j-Qi||＝r2
AXQi+BYQi+CZQi+D＝0
where | | represents a norm, point Pi,j(XP,YP,ZP) For the ith position on the calibration plate, the ith corner point, Qi(XQi,YQi,ZQi) And f, setting the center of a track circle corresponding to the ith angle point, wherein i is 1,2 …, m represents the number of the angle points, m represents the total number of the angle points, j is 1,2 …, n represents the position number of the calibration plate, n represents the total position number of the calibration plate, and r represents the radius of the track circle. And substituting the coordinates of more than three positions of any angular point into the calculation to obtain the circular center coordinate of the rotation track corresponding to the angular point. Substituting different angular points for calculation, and finally obtaining the centers of the rotation track circles corresponding to all the angular points.
Before the measurement is started, the vision bracket is adjusted to be at a proper position and angle, and a camera is ensured to have a proper view field; placing the calibration plate on a proper position on a 3-degree rotary table, and collecting a corresponding calibration image every 5 degrees of rotation of the rotary table;
calibrating the internal and external parameters of the camera, and converting the coordinates of the corner points from a coordinate system of a calibration board to a coordinate system of the camera by using a calibration result, wherein a schematic diagram of a conversion relation is shown in FIG. 4;
and calculating the centers of the circles of the rotation tracks of the angular points, and fitting a linear equation where the rotation axes are located by using all the centers of the circles, wherein the result is shown in FIG. 5.
The error is calculated by the error evaluation method, and the error comparison result of the ordinary least square method and the weighted least square method is shown in fig. 6.
The implementation result of the specific example proves that the method provided by the invention effectively reduces the calibration error of the rotating shaft, the total error sum is reduced by 2.52mm, and the error sum is about 15.6%, so that the reduction of the method can obviously improve the calibration precision of the rotating shaft. The invention can evaluate the error by the following model, namely: and establishing an error evaluation model and evaluating the calibration precision of the rotating shaft. Knowing any angular point P after rotationi,j(j>1) Relative initial position corner point Pi,1And the relative rotation of the theta angle exists, a corresponding conversion matrix H can be obtained by combining the parameters of the fitting rotating shaft and the value of the theta angle, and the rotated angular point can be restored to the initial position through the conversion matrix. Considering that the fitting rotation axis has an error with the actual rotation axis, the rotated corner point Pi,jAfter the initial position is restored, the two positions are not completely overlapped, but have a certain offset, and the size of the offset distance can be easily known to represent the size of the calibration error of the rotating shaft. Calculating the ith angle of all position calibration platesThe offset distance after the point is restored to the initial position is taken as the mean value M of the offset distances corresponding to all the positions of the angular pointi，MiCan be expressed as follows:
Mican be used for representing the error corresponding to each corner point, and further solving the M corresponding to all corner pointsiSum of (S):
the evaluation method can ensure that the smaller the S value is, the smaller the calibration error of the rotating shaft is. S can effectively evaluate the calibration error of the rotating shaft.
Claims (5)
1. A rotating shaft calibration method based on self-adaptive distance weighting is characterized by comprising the following steps:
step 1: establishing a camera coordinate system Ov and a calibration board coordinate system OBAnd a camera coordinate system Ov and a calibration plate coordinate system OBThe relationship between the two conversion modes is converted,
step 2: placing the chessboard pattern calibration board on the rotary platform in an inclined way and enabling the calibration board to be positioned in a camera visual field, rotating the rotary platform and collecting images of the calibration board to obtain coordinates under a calibration board coordinate system of all chessboard pattern calibration board angular points at least 3 different rotary positions, then obtaining coordinates under the camera coordinate system of all chessboard pattern calibration board angular points at least 3 different rotary positions by utilizing the conversion relation between the camera coordinate system and the calibration board coordinate system,
and step 3: selecting points (a, b, c) with coordinates which are the average value of the coordinates of the centers of the circle centers of the tracks corresponding to the angular points,
(XQi,YQi,ZQi) The center coordinates of a track circle corresponding to the ith corner point are set as 1,2 …, m represents the serial number of the corner point, m is the total number of the corner points on the chessboard calibration board, and the points are processed(a, b, c) as points on the rotating shaft, performing space straight line fitting on the center of a circle of a track formed by the angular points rotating along with the chessboard pattern calibration plate to obtain the rotating shaft under the camera coordinate, and finally converting the rotating shaft under the camera coordinate by using the conversion relation between the camera coordinate system and the calibration plate coordinate system to finish the calibration of the rotating shaft, wherein the space straight line fitting adopts the following method:
taking a straight line L with the minimum weighted square sum of the distances from the centers of the track circles to the rotating shaft to be calibrated in the camera coordinate as the rotating shaft in the camera coordinate:
wherein,
di 2＝(XQi-a)2+(YQi-b)2+(ZQi-c)2-[u(XQi-a)+v(YQi-b)+w(ZQi-c)]2，dithe distance between the center of the ith angular point track circle and the rotating shaft to be calibrated is [ u, v, w]Is a unit direction vector of a rotating shaft to be calibrated, s.t. represents constraint, min represents minimum value, αiWeighting coefficients corresponding to the centers of the ith angular point track circles, wherein i is an angular point serial number, j is 1,2 …, n represents a calibration plate position serial number, n is the total position number of the calibration plate, and lijAnd p is an integer larger than 1, and is the moving distance of the ith angular point between the jth rotating position and the (j + 1) th rotating position.
2. The method for calibrating a rotating shaft based on adaptive distance weighting according to claim 1, wherein the origin of the camera coordinate system is located at the optical center of the camera, the z-axis of the camera coordinate system passes through the optical center and is perpendicular to the imaging plane of the camera, the direction toward the object to be photographed is positive, the x-axis passes through the optical center and is perpendicular to the z-axis, the camera coordinate system is located in the horizontal direction of the imaging plane, the direction toward the object is positive, the y-axis passes through the optical center and is perpendicular to the x-axis and the z-axis, and the direction toward the object is positive; the origin of the coordinate system of the calibration plate is arranged at the corner of the lower right corner of the calibration plate, and the z axis of the coordinate system of the calibration plate isPassing through the angular point and being vertical to the plane of the calibration plate, the direction facing the camera is the positive direction, the x axis passes through the angular point and is vertical to the z axis, the x axis is located in the horizontal direction of the plane of the calibration plate, the left direction is the positive direction when facing the calibration plate, the y axis passes through the angular point and is vertical to the x axis and the z axis, and the upward direction is the positive direction when facing the calibration plate; the camera coordinate system Ov and the calibration plate coordinate system OBThe inter-conversion relation is [ X ]VYVZV]T＝R[XBYBZB]T+t，XB，YB，ZBCalibration plate coordinate system O for any angle point on calibration plateBCoordinates of the lower part, coordinate values Z in the calibration plate coordinate system OBBDefault is 0, XV，YV，ZVIs the coordinate value of the corresponding point under the camera coordinate system Ov of any angular point on the calibration board and the corresponding point (X)V，YV，ZV) The coordinate value of (A) is obtained by camera shooting and using a coordinate system O of a calibration plateBAny corner point below (X)B，YB，ZB) And the corresponding point (X) of any one of the corner points under the camera coordinate system OvV，YV，ZV) And (5) calculating coordinates to obtain external parameter matrixes R and t.
3. The method for calibrating a rotating shaft based on adaptive distance weighting according to claim 1, wherein the rotating platform comprises a visual support (2) and a rotating platform (3), the visual support (2) is provided with a camera (1), a checkerboard calibration plate (4) is placed on the rotating platform (3), and the checkerboard calibration plate (4) is located in a camera field of view.
4. The adaptive distance weighting-based rotating shaft calibration method as claimed in claim 1, wherein the platform is rotated and calibration plate images are collected every 4-10 ° of rotation.
5. The method for calibrating a rotating shaft based on adaptive distance weighting as claimed in claim 1, wherein the moving distance l of the ith corner point between the jth rotating position and the j +1 th rotating positionijComprises the following steps: li，j＝||Pi，j+1-Pi，jL, wherein Pi,jThe ith angle point on the jth position calibration plate is represented by i, i is 1,2 …, m represents the angle point serial number, m is the total number of the angle points, the angle point serial number increases in an s-shaped manner from right to left and from bottom to top, j is 1,2 …, n represents the position serial number of the calibration plate, n is the total position number of the calibration plate, and | | represents the norm calculation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010264708.3A CN111486802B (en) | 2020-04-07 | 2020-04-07 | Rotating shaft calibration method based on self-adaptive distance weighting |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010264708.3A CN111486802B (en) | 2020-04-07 | 2020-04-07 | Rotating shaft calibration method based on self-adaptive distance weighting |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111486802A true CN111486802A (en) | 2020-08-04 |
| CN111486802B CN111486802B (en) | 2021-04-06 |
Family
ID=71791537
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010264708.3A Active CN111486802B (en) | 2020-04-07 | 2020-04-07 | Rotating shaft calibration method based on self-adaptive distance weighting |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111486802B (en) |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111981984A (en) * | 2020-08-28 | 2020-11-24 | 南昌航空大学 | Rotating shaft calibration method based on binocular vision |
| CN112284272A (en) * | 2020-09-16 | 2021-01-29 | 江苏大学 | Monocular machine vision-based vehicle turning radius measuring method |
| CN112288824A (en) * | 2020-10-27 | 2021-01-29 | 中国科学院上海微系统与信息技术研究所 | Long-focus camera calibration device and calibration method based on real scene |
| CN112611325A (en) * | 2020-12-07 | 2021-04-06 | 东莞市兆丰精密仪器有限公司 | Calibration method of laser center and image center synchronously |
| CN112631200A (en) * | 2020-12-02 | 2021-04-09 | 深圳数马电子技术有限公司 | Machine tool axis measuring method and device |
| CN112907683A (en) * | 2021-04-07 | 2021-06-04 | 歌尔光学科技有限公司 | Camera calibration method and device for dispensing platform and related equipment |
| CN113108716A (en) * | 2021-04-30 | 2021-07-13 | 上海汇像信息技术有限公司 | Calibration template for calibrating rotating shaft of rotary table |
| CN113146073A (en) * | 2021-06-24 | 2021-07-23 | 浙江华睿科技有限公司 | Vision-based laser cutting method and device, electronic equipment and storage medium |
| CN113706632A (en) * | 2021-08-31 | 2021-11-26 | 上海景吾智能科技有限公司 | Calibration method and system based on three-dimensional visual calibration plate |
| CN114166144A (en) * | 2021-11-22 | 2022-03-11 | 天津科技大学 | Method for calibrating machined profile after gear chamfering machining and clamping |
| CN114216395A (en) * | 2021-12-14 | 2022-03-22 | 众致盛视智能科技(苏州)有限公司 | Space rotation axis solving method based on calibration plate |
| CN114236513A (en) * | 2021-12-17 | 2022-03-25 | 昆山丘钛微电子科技股份有限公司 | Module error calibration method, device and system |
| CN114485386A (en) * | 2020-10-23 | 2022-05-13 | 广东天机工业智能系统有限公司 | Method, device and system for calibrating workpiece coordinate system |
| CN114894116A (en) * | 2022-04-08 | 2022-08-12 | 苏州瀚华智造智能技术有限公司 | Measurement data fusion method and non-contact measurement equipment |
| CN115711589A (en) * | 2022-11-22 | 2023-02-24 | 哈尔滨工业大学 | Method for measuring rotor spherical surface profile of large-scale high-speed rotation equipment based on integration of multidimensional great circle projection centers |
| CN116739898A (en) * | 2023-06-03 | 2023-09-12 | 广州市西克传感器有限公司 | Multi-camera point cloud splicing method and device based on cylindrical characteristics |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE3425662A1 (en) * | 1984-07-12 | 1986-01-23 | Siemens AG, 1000 Berlin und 8000 München | Circuit arrangement for the temperature compensation of crystal oscillators |
| CN1529286A (en) * | 2003-10-14 | 2004-09-15 | 哈尔滨工业大学 | Spray deposited blank dynamic size visual dtecting method and data acquisition device |
| CN101032408A (en) * | 2006-03-09 | 2007-09-12 | Ge医疗系统环球技术有限公司 | X-ray CT apparatus |
| CN101033958A (en) * | 2007-02-01 | 2007-09-12 | 华中科技大学 | Mechanical vision locating method |
| CN101915580A (en) * | 2010-07-14 | 2010-12-15 | 中国科学院自动化研究所 | Self-adaptation three-dimensional attitude positioning method based on microinertia and geomagnetic technology |
| CN103150724A (en) * | 2013-02-06 | 2013-06-12 | 长春工业大学 | Segmented model-based camera calibration method |
| CN103674189A (en) * | 2013-11-21 | 2014-03-26 | 清华大学 | Method for monitoring flow meter faults of turbine system |
| CN104504688A (en) * | 2014-12-10 | 2015-04-08 | 上海大学 | Method and system based on binocular stereoscopic vision for passenger flow density estimation |
| CN104634248A (en) * | 2015-02-04 | 2015-05-20 | 西安理工大学 | Revolving shaft calibration method under binocular vision |
| JP2016066909A (en) * | 2014-09-25 | 2016-04-28 | 株式会社アルバック | Crystal oscillator, sensor head including the same, film formation control apparatus, and manufacturing method of the same |
| CN105551039A (en) * | 2015-12-14 | 2016-05-04 | 深圳先进技术研究院 | Calibration method and calibration device for structured light 3D scanning system |
| CN106228534A (en) * | 2016-07-08 | 2016-12-14 | 众趣（北京）科技有限公司 | Relation scaling method between a kind of rotating shaft based on constrained global optimization and camera |
| CN109556633A (en) * | 2018-11-26 | 2019-04-02 | 北方工业大学 | Bionic polarization sensor multi-source error calibration method based on adaptive EKF |
| CN110596593A (en) * | 2019-08-26 | 2019-12-20 | 浙江大学 | Lithium ion battery SOC estimation method based on intelligent adaptive extended Kalman filtering |
| CN110766677A (en) * | 2019-10-24 | 2020-02-07 | 吉林大学 | Automatic detection method for parameters and abnormity of air bag detonation process based on machine vision |
-
2020
- 2020-04-07 CN CN202010264708.3A patent/CN111486802B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE3425662A1 (en) * | 1984-07-12 | 1986-01-23 | Siemens AG, 1000 Berlin und 8000 München | Circuit arrangement for the temperature compensation of crystal oscillators |
| CN1529286A (en) * | 2003-10-14 | 2004-09-15 | 哈尔滨工业大学 | Spray deposited blank dynamic size visual dtecting method and data acquisition device |
| CN101032408A (en) * | 2006-03-09 | 2007-09-12 | Ge医疗系统环球技术有限公司 | X-ray CT apparatus |
| CN101033958A (en) * | 2007-02-01 | 2007-09-12 | 华中科技大学 | Mechanical vision locating method |
| CN101915580A (en) * | 2010-07-14 | 2010-12-15 | 中国科学院自动化研究所 | Self-adaptation three-dimensional attitude positioning method based on microinertia and geomagnetic technology |
| CN103150724A (en) * | 2013-02-06 | 2013-06-12 | 长春工业大学 | Segmented model-based camera calibration method |
| CN103674189A (en) * | 2013-11-21 | 2014-03-26 | 清华大学 | Method for monitoring flow meter faults of turbine system |
| JP2016066909A (en) * | 2014-09-25 | 2016-04-28 | 株式会社アルバック | Crystal oscillator, sensor head including the same, film formation control apparatus, and manufacturing method of the same |
| CN104504688A (en) * | 2014-12-10 | 2015-04-08 | 上海大学 | Method and system based on binocular stereoscopic vision for passenger flow density estimation |
| CN104634248A (en) * | 2015-02-04 | 2015-05-20 | 西安理工大学 | Revolving shaft calibration method under binocular vision |
| CN105551039A (en) * | 2015-12-14 | 2016-05-04 | 深圳先进技术研究院 | Calibration method and calibration device for structured light 3D scanning system |
| CN106228534A (en) * | 2016-07-08 | 2016-12-14 | 众趣（北京）科技有限公司 | Relation scaling method between a kind of rotating shaft based on constrained global optimization and camera |
| CN109556633A (en) * | 2018-11-26 | 2019-04-02 | 北方工业大学 | Bionic polarization sensor multi-source error calibration method based on adaptive EKF |
| CN110596593A (en) * | 2019-08-26 | 2019-12-20 | 浙江大学 | Lithium ion battery SOC estimation method based on intelligent adaptive extended Kalman filtering |
| CN110766677A (en) * | 2019-10-24 | 2020-02-07 | 吉林大学 | Automatic detection method for parameters and abnormity of air bag detonation process based on machine vision |
Non-Patent Citations (2)
| Title |
|---|
| OMAR KHALDOON等: "A Novel Self-Calibration Technique for Linear Array Based on Modified MVDR Adaptive Beamformer", 《2019 DEVELOPMENTS IN ESYSTEMS ENGINEERING》 * |
| 樊子德等: "顾及多因素影响的自适应反距离加权插值方法", 《武汉大学学报· 信息科学版》 * |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111981984A (en) * | 2020-08-28 | 2020-11-24 | 南昌航空大学 | Rotating shaft calibration method based on binocular vision |
| CN111981984B (en) * | 2020-08-28 | 2022-05-17 | 南昌航空大学 | Rotating shaft calibration method based on binocular vision |
| CN112284272A (en) * | 2020-09-16 | 2021-01-29 | 江苏大学 | Monocular machine vision-based vehicle turning radius measuring method |
| CN112284272B (en) * | 2020-09-16 | 2022-02-15 | 江苏大学 | Monocular machine vision-based vehicle turning radius measuring method |
| CN114485386B (en) * | 2020-10-23 | 2023-11-07 | 广东天机工业智能系统有限公司 | Workpiece coordinate system calibration method, device and system |
| CN114485386A (en) * | 2020-10-23 | 2022-05-13 | 广东天机工业智能系统有限公司 | Method, device and system for calibrating workpiece coordinate system |
| CN112288824A (en) * | 2020-10-27 | 2021-01-29 | 中国科学院上海微系统与信息技术研究所 | Long-focus camera calibration device and calibration method based on real scene |
| CN112288824B (en) * | 2020-10-27 | 2024-04-12 | 中国科学院上海微系统与信息技术研究所 | Device and method for calibrating tele camera based on real scene |
| CN112631200A (en) * | 2020-12-02 | 2021-04-09 | 深圳数马电子技术有限公司 | Machine tool axis measuring method and device |
| CN112611325A (en) * | 2020-12-07 | 2021-04-06 | 东莞市兆丰精密仪器有限公司 | Calibration method of laser center and image center synchronously |
| CN112907683A (en) * | 2021-04-07 | 2021-06-04 | 歌尔光学科技有限公司 | Camera calibration method and device for dispensing platform and related equipment |
| CN112907683B (en) * | 2021-04-07 | 2022-11-25 | 歌尔光学科技有限公司 | Camera calibration method and device for dispensing platform and related equipment |
| CN113108716A (en) * | 2021-04-30 | 2021-07-13 | 上海汇像信息技术有限公司 | Calibration template for calibrating rotating shaft of rotary table |
| CN113146073A (en) * | 2021-06-24 | 2021-07-23 | 浙江华睿科技有限公司 | Vision-based laser cutting method and device, electronic equipment and storage medium |
| CN113706632A (en) * | 2021-08-31 | 2021-11-26 | 上海景吾智能科技有限公司 | Calibration method and system based on three-dimensional visual calibration plate |
| CN113706632B (en) * | 2021-08-31 | 2024-01-16 | 上海景吾智能科技有限公司 | Calibration method and system based on three-dimensional vision calibration plate |
| CN114166144A (en) * | 2021-11-22 | 2022-03-11 | 天津科技大学 | Method for calibrating machined profile after gear chamfering machining and clamping |
| CN114166144B (en) * | 2021-11-22 | 2023-09-22 | 天津科技大学 | Calibration method for machining profile after gear chamfering machining and clamping |
| CN114216395A (en) * | 2021-12-14 | 2022-03-22 | 众致盛视智能科技(苏州)有限公司 | Space rotation axis solving method based on calibration plate |
| CN114216395B (en) * | 2021-12-14 | 2023-10-24 | 众致盛视智能科技(苏州)有限公司 | Space rotation axis solving method based on calibration plate |
| CN114236513A (en) * | 2021-12-17 | 2022-03-25 | 昆山丘钛微电子科技股份有限公司 | Module error calibration method, device and system |
| CN114894116B (en) * | 2022-04-08 | 2024-02-23 | 苏州瀚华智造智能技术有限公司 | Measurement data fusion method and non-contact measurement equipment |
| CN114894116A (en) * | 2022-04-08 | 2022-08-12 | 苏州瀚华智造智能技术有限公司 | Measurement data fusion method and non-contact measurement equipment |
| CN115711589B (en) * | 2022-11-22 | 2023-12-22 | 哈尔滨工业大学 | Method for measuring spherical profile of rotor of large-sized high-speed rotary equipment based on multi-dimensional large-circle projection center integration |
| CN115711589A (en) * | 2022-11-22 | 2023-02-24 | 哈尔滨工业大学 | Method for measuring rotor spherical surface profile of large-scale high-speed rotation equipment based on integration of multidimensional great circle projection centers |
| CN116739898A (en) * | 2023-06-03 | 2023-09-12 | 广州市西克传感器有限公司 | Multi-camera point cloud splicing method and device based on cylindrical characteristics |
| CN116739898B (en) * | 2023-06-03 | 2024-04-30 | 广东西克智能科技有限公司 | Multi-camera point cloud splicing method and device based on cylindrical characteristics |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111486802B (en) | 2021-04-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111486802B (en) | Rotating shaft calibration method based on self-adaptive distance weighting | |
| CN109029299B (en) | Dual-camera measuring device and method for butt joint corner of cabin pin hole | |
| CN108340211B (en) | Numerically-controlled machine tool profile errors method for three-dimensional measurement based on monocular vision | |
| CN112223285B (en) | Robot hand-eye calibration method based on combined measurement | |
| CN109297436B (en) | Binocular line laser stereo measurement reference calibration method | |
| CN111981984B (en) | Rotating shaft calibration method based on binocular vision | |
| CN109272555B (en) | External parameter obtaining and calibrating method for RGB-D camera | |
| CN111862238B (en) | Full-space monocular light pen type vision measurement method | |
| CN113820070B (en) | Rigid body moment of inertia measuring method and system based on machine vision and torsion pendulum method | |
| CN110470320B (en) | Calibration method of swinging scanning type line structured light measurement system and terminal equipment | |
| CN114359405A (en) | Calibration method of off-axis Samm 3D line laser camera | |
| CN113724337B (en) | Camera dynamic external parameter calibration method and device without depending on tripod head angle | |
| CN113119129A (en) | Monocular distance measurement positioning method based on standard ball | |
| CN113240749B (en) | Remote binocular calibration and ranging method for recovery of unmanned aerial vehicle facing offshore ship platform | |
| CN104167001B (en) | Large-visual-field camera calibration method based on orthogonal compensation | |
| CN113702384A (en) | Surface defect detection device, detection method and calibration method for rotary component | |
| CN108871190B (en) | Handheld spherical target for binocular stereo vision measurement and measurement method | |
| CN110428471B (en) | Accurate self-positioning method for optical free-form surface sub-aperture deflection measurement | |
| CN115187612A (en) | Plane area measuring method, device and system based on machine vision | |
| JP2007533963A (en) | Non-contact optical measuring method and measuring apparatus for 3D position of object | |
| CN115179323A (en) | Machine end pose measuring device based on telecentric vision constraint and precision improving method | |
| JP2007533963A5 (en) | ||
| CN109342008B (en) | Wind tunnel test model attack angle single-camera video measuring method based on homography matrix | |
| CN110595374A (en) | Large structural part real-time deformation monitoring method based on image transmission machine | |
| CN108537748B (en) | Far field image distortion correction method and system based on angle |
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 |