CN113554614B - Pipeline measurement system pose calibration method for point cloud splicing - Google Patents
Pipeline measurement system pose calibration method for point cloud splicing Download PDFInfo
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Abstract
The invention discloses a method for calibrating the pose of a pipeline measurement system for point cloud splicing, which can solve the problem of whole-ring point cloud splicing of a pipeline inner surface measurement system. Through a calibration cylinder with a fixed inner diameter processed at high precision, point clouds with different poses are generated through rotary measurement; establishing a calibration coordinate conversion model, and transforming point clouds obtained by the pipeline measurement system at different poses to the same coordinate system through the coordinate conversion model to complete point cloud splicing of the whole ring of the inner wall of the pipeline; meanwhile, an error compensation model is established by combining an optimization algorithm, so that the accurate splicing of point clouds at different poses is realized; the point cloud splicing realized by the method does not need to be spliced through the characteristic points, the pipeline point cloud splicing precision can be optimized, the error is reduced, and the model is simple and clear and is easy to operate.
Description
Technical Field
The invention belongs to the optical pipeline detection technology, and particularly relates to a pipeline measurement system pose calibration method for point cloud splicing.
Background
In the research of the inner surface of the pipeline, due to the limitation of the inner structure, the traditional measuring method has poor precision, only individual parameters in the pipeline can be obtained, the three-dimensional reconstruction of the inner surface cannot be completed, and the optical detection technology is widely applied to the detection process of the inner surface of the pipeline due to the advantages of high precision, high measuring speed, automation and nondestructive detection. The optical detection technology can directly obtain the point cloud characteristics of the inner surface of the pipeline, but the whole circumferential three-dimensional information of the inner surface of the pipeline cannot be obtained during the detection of the inner surface of the pipeline, and the requirement of three-dimensional reconstruction cannot be met. Therefore, how to splice the measurement point clouds of the pipeline measurement system at different poses is an important research direction for realizing the three-dimensional reconstruction of the inner surface of the pipeline.
In the traditional point cloud splicing algorithm, the closest point iterative method (ICP) proposed by Besl in 1992 is most widely applied, but the algorithm needs to use rough matching to obtain an initial value for iterative operation when splicing. In the rough matching algorithm, the preliminary solution is usually performed by a mark point method, a feature point method and a turntable pose method, but the space limitation of the inner surface of the pipeline is difficult to paste mark points on the inner surface to be detected, the turntable pose cannot be calibrated, particularly in the inner surface of a smooth pipeline with a fixed inner diameter, the point cloud obtained by images with different poses has small difference, and enough feature points cannot be extracted for point cloud splicing by an ICP algorithm.
Disclosure of Invention
The invention provides a pipeline measuring system pose calibration method for point cloud splicing, which enables a pipeline inner surface measuring system to finish high-precision point cloud splicing of the whole pipeline inner surface only through a rotation angle of the system under the condition that sufficient point cloud registration characteristic point pairs do not exist.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a pipeline measurement system pose calibration method for point cloud splicing comprises the following steps:
s1, establishing a coordinate conversion mathematical model of a pipeline measurement system;
s2, measuring the whole ring of fixed inner diameter cylinder by using a pipeline measuring system according to preset angle step length to generate point clouds on the inner surface of the pipeline in a camera coordinate system at different angles;
s3, converting the point cloud under the camera coordinate system into a point cloud cylindrical coordinate system through cylindrical fitting;
s4, solving the representation of the point clouds under different angles in a global cylindrical coordinate system, and establishing an error compensation model of the cylindrical coordinate system;
and S5, solving a conversion matrix of the point cloud between the camera coordinate system and the global coordinate system, iteratively solving corresponding error parameters through an optimization algorithm, and completing calibration.
Further, the coordinate conversion mathematical model comprises a camera coordinate system, a point cloud rotating coordinate system, a global rotating coordinate system, a point cloud cylindrical coordinate system and a global cylindrical coordinate system; the coordinate transformation mathematical model is as follows:
wherein, (xCCF, yCCF, zCCF) are coordinate values of the point cloud measured at different angles in the camera coordinate system, (xCyCF, ycyccf, zCyCF) are coordinate values of the point cloud in the global cylindrical coordinate system, r11, r12, \ 8230;, r19 is a position conversion matrix coefficient of the rotational coordinate system and the global cylindrical coordinate system, and r21, r22, \8230;, and r29 is a position conversion matrix coefficient of the camera coordinate system and the point cloud rotational coordinate system.
Further, a camera coordinate system is established, wherein the camera coordinate system is CCF, the origin of coordinates is at the center of the lens, and the z axis is the optical axis of the camera and is fixed on the camera.
Further, the point cloud rotation coordinate system is established and is RCF i The origin is established at a certain fixed point on the rotating shaft, the fixed position relation is possessed with the CCF in the rotating measurement process, the z axis of the fixed point is coincident with the rotating shaft, the space position changes along with the rotation of the system measurement attitude, and i is a point cloud rotating coordinate system of different measurement positions.
Further, the global rotating coordinate system is established, the global rotating coordinate system is RCF, the origin is established at RCF i At the origin, the z-axis coincides with the axis of rotation, with the RCF i There is a fixed rotational relationship and the spatial position is fixed and changes during the rotation measurement.
Further, the global cylindrical coordinate system is established, the global cylindrical coordinate system is CyCF, the origin is established at a fixed point on the central axis of the inner surface of the deep-hole part, the z axis of the origin coincides with the central axis of the barrel, and the spatial position is fixed and unchanged in the rotation measurement process.
Furthermore, the camera coordinate system is established on a camera phase plane, the point cloud rotating coordinate system is established on a rotating shaft, the camera coordinate system and the point cloud rotating coordinate system have a fixed position transformation relation, the global rotating coordinate system is established on a coordinate axis, the pose is unchanged relative to the measuring part when the system rotates, the point cloud cylindrical coordinate system is a cylindrical coordinate system established by cylinder fitting of different measuring point clouds, the global cylindrical coordinate system is established on the axis of the measuring part and does not change when the system is measured in a whole circle, and the global rotating coordinate system and the global cylindrical coordinate system have a fixed position transformation relation.
Further, the error compensation model established in step S5 is:
(xCyCF, yCyCF, zCyCF) is a coordinate value of the point cloud in a global cylindrical coordinate system, (xCyCFi, yCyCFi, zCyCFi) is a coordinate of the point cloud obtained by measuring different angles in the point cloud cylindrical coordinate system, theta is a rotation angle measured by an angle converter in the calibration process, and alpha (theta) = theta + A 1 sin(θ+φ 1 )，Δz(θ)＝A 2 sin(θ+φ 2 ) Wherein A is 1 ，A 2 ，φ 1 ，φ 2 The amplitude and phase of the sine function.
Further, in step S5, a coordinate conversion parameter formula obtained by the error compensation model is:
t i (θ)＝a i sin(θ)+b i cos(θ)+c i where i =1,2, \8230, 12 is the rotational-translational matrix from CCF to CyCF, by continually adjusting A 1 ，A 2 ，φ 1 ，φ 2 Different conversion parameters are obtained, the solution is carried out according to the global conversion parameters, and the accumulated least square error is taken as the lossThe lost function is optimized for parameters.
Further, the pipeline measuring system in the step S2 rotationally acquires the point cloud information of the whole circumference of the cylinder with the fixed inner diameter by a fixed step length.
Due to the adoption of the structure, compared with the prior art, the invention has the technical progress that: the method is firstly used for processing the pipeline without the characteristic points inside the attitude calibration most easily without redundant processing steps; secondly, the established rotational translation model can realize high-precision splicing of the inner surface of the pipeline only by using the rotation angle of the measurement system without performing feature extraction on the collected point cloud data; finally, the rotation and translation model is suitable for splicing most of the measured point clouds on the inner surface of the pipeline, and the detection precision of the inner surface of the pipeline can be improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a step diagram of a method for calibrating the pose of a pipeline measurement system to achieve high-precision point cloud splicing according to an embodiment of the present invention;
FIG. 2 is a mathematical model of coordinate transformation of a pipeline measurement system according to an embodiment of the present invention;
FIG. 3 is a point cloud measured by the pipeline measurement system according to the embodiment of the present invention;
FIG. 4 shows a point cloud registration result according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for purposes of illustration and explanation only and are not intended to limit the present invention.
The invention discloses a method for calibrating the position and pose of a pipeline measurement system for point cloud splicing, which comprises the following steps as shown in figure 1:
s1, establishing a coordinate conversion mathematical model of a pipeline measurement system;
s2, measuring the whole fixed inner diameter cylinder by using a pipeline measuring system according to preset angle step length to generate point clouds of the inner surface of the pipeline in a camera coordinate system at different angles;
s3, converting the point cloud under the camera coordinate system into a point cloud cylindrical coordinate system through cylindrical fitting;
s4, solving the representation of the point clouds under different angles in a global cylindrical coordinate system, namely solving a coordinate conversion matrix of the point clouds from a camera coordinate system to a unified coordinate system, calibrating parameters related to system design and assembly according to the coordinate conversion matrix, and establishing an error compensation model of the cylindrical coordinate system;
and S5, solving a conversion matrix of the point cloud between the camera coordinate system and the global coordinate system, iteratively solving corresponding error parameters through an optimization algorithm, and completing calibration.
Specifically, a smooth cylinder with a fixed radius is processed according to an application scene, and the cylinder is required to have an inner surface with a fixed radius and to have clear imaging. Acquiring a whole-circle image of the smooth cylinder by using a pipeline inner wall measuring device according to a fixed step length delta theta, and solving a measuring point cloud corresponding to each angle; fitting a cylindrical equation by using the point cloud corresponding to each measuring angle, carrying out coordinate transformation, and obtaining the point cloud
A coordinate representation of (a); establishing
To
The initial value is set to be both amplitude and phase
And find and
of the rotational-translation matrix
Coefficient, to manySolving the rotation and translation matrix of each angle; will be provided with
When the accumulated least square error of coefficient solution is used as loss function to continuously obtain minimum value
And find
And the coefficient is used as a calibration pose result of point cloud splicing.
As shown in fig. 3, the point cloud model obtained in step S2 is a coordinate point describing three-dimensional characteristics of the inner surface of the pipeline, and due to the limitation of the field of view of the measurement system, all three-dimensional information of the inner surface of the pipeline cannot be obtained by one measurement, and the point cloud data collected from different angles are converted into a coordinate system through coordinate conversion, so that the point cloud splicing of the measurement data of the inner surface of the pipeline can be completed.
As shown in fig. 4, the result of acquiring the point cloud at different angles is obtained in step S5. According to the pose calibration result, coordinate conversion relations under different angles are obtained, and finally point cloud data of the inner surface of the pipeline, which are obtained at different angles, are converted into the same coordinate system through coordinate conversion.
The invention has the advantages that: the method is firstly used for processing the pipeline without characteristic points in the posture calibration most easily, and has no redundant processing steps; secondly, the established rotational translation model can realize high-precision splicing of the inner surface of the pipeline only by using the rotation angle of the measurement system without performing feature extraction on the collected point cloud data; finally, the rotational translation model is suitable for splicing most of the measured point clouds on the inner surface of the pipeline, and the detection precision of the inner surface of the pipeline can be improved.
As a preferred embodiment of the present invention, as shown in fig. 2, the coordinate transformation mathematical model includes a camera coordinate system, a point cloud rotating coordinate system, a global rotating coordinate system, a point cloud cylindrical coordinate system, and a global cylindrical coordinate system. Rotation of detection systemThe axis and the central line axis of the inner surface of the pipeline to be measured are spatial straight lines at common positions, a camera coordinate system (CCF) is established on a camera phase plane, and a point cloud rotating coordinate system (RCF) i ) Built on a rotating shaft, CCF and RCF i The system has a fixed position transformation relation, a global rotating coordinate system (RCF) is established on a coordinate axis, and is unchanged relative to a measuring part when the system rotates, and a point cloud cylindrical coordinate system (CyCF) i ) The system is characterized in that a cylindrical coordinate system is established for different measuring point clouds through cylindrical fitting, a global cylindrical coordinate system (CyCF) is established on the axis of a measuring part, the system does not change during measurement, and the RCF and the CyCF have a fixed position transformation relation.
In particular, o-x CCF y CCF z CCF : and a camera coordinate system (CCF), wherein the coordinate origin is at the center of the lens, and the z axis is the optical axis of the camera and is fixed on the camera.
o-x RCFi y RCFi z RCFi : point cloud rotating coordinate system (RCF) i ) The original point is established at a certain fixed point on the rotating shaft, and has a fixed position relation with the CCF in the rotating measurement process, the z axis of the original point is superposed with the rotating shaft, the spatial position changes along with the rotation of the measuring attitude of the system, and i is a point cloud rotating coordinate system of different measuring positions.
o-x RCF y RCF z RCF : global rotating coordinate system (RCF), with origin established at RCF i At the origin, the z-axis coincides with the axis of rotation, with the RCF i There is a fixed rotational relationship and the spatial position is fixed and changes during the rotation measurement.
o-x CyCF y CyCF z CyCF : and a global cylindrical coordinate system (CyCF), wherein the origin is established at a fixed point on the central axis of the inner surface of the deep-hole part, the z axis of the CyCF coincides with the central axis of the barrel, and the spatial position is fixed in the rotation measurement process.
The above-mentioned coordinate transformation mathematical model is:
wherein, (xCCF, yCCF, zCCF) are coordinate values of the point cloud measured at different angles in the camera coordinate system, (xCyCF, ycyccf, zCyCF) are coordinate values of the point cloud in the global cylindrical coordinate system, r11, r12, \ 8230;, r19 is a position conversion matrix coefficient of the rotational coordinate system and the global cylindrical coordinate system, and r21, r22, \8230;, and r29 is a position conversion matrix coefficient of the camera coordinate system and the point cloud rotational coordinate system.
As a preferred embodiment of the present invention, the error compensation model established in step S5 is:
(xCyCF, yCyCF, zCyCF) is a coordinate value of the point cloud in a global cylindrical coordinate system, (xCyCFi, yCyCFi, zCyCFi) is a coordinate of the point cloud obtained by measuring different angles in the point cloud cylindrical coordinate system, theta is a rotation angle measured by an angle converter in the calibration process, and alpha (theta) = theta + A 1 sin(θ+φ 1 )，Δz(θ)＝A 2 sin(θ+φ 2 ) Wherein A is 1 ，A 2 ，φ 1 ，φ 2 The amplitude and phase of the sine function. In the step S5, the formula of the coordinate conversion parameter obtained by the error compensation model is as follows:
t i (θ)＝a i sin(θ)+b i cos(θ)+c i where i =1,2, \8230, 12 is the rotation-translation matrix from CCF to CyCF, by continually adjusting A 1 ，A 2 ，φ 1 ，φ 2 And solving different conversion parameters, and performing parameter optimization by taking the accumulated least square error as a loss function according to the global conversion parameters.
As a preferred embodiment of the present invention, in step S2, the pipeline measurement system rotationally acquires the point cloud information of the whole circumference of the cylinder with a fixed inner diameter by a fixed step length.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (8)
1. A pipeline measurement system pose calibration method for point cloud splicing is characterized by comprising the following steps:
s1, establishing a coordinate conversion mathematical model of a pipeline measurement system;
s2, measuring the whole ring of fixed inner diameter cylinder by using a pipeline measuring system according to preset angle step length to generate point clouds on the inner surface of the pipeline in a camera coordinate system at different angles;
s3, converting the point cloud under the camera coordinate system into a point cloud cylindrical coordinate system through cylindrical fitting;
s4, solving the representation of the point clouds under different angles in a global cylindrical coordinate system, and establishing an error compensation model of the point cloud cylindrical coordinate system and the global cylindrical coordinate system;
s5, solving a conversion matrix of the point cloud between a camera coordinate system and a global cylindrical coordinate system, iteratively solving corresponding coordinate conversion parameters through an optimization algorithm, and completing calibration;
the coordinate conversion mathematical model comprises a camera coordinate system, a point cloud rotating coordinate system, a global rotating coordinate system, a point cloud cylindrical coordinate system and a global cylindrical coordinate system; the original coordinates acquired by the measured point cloud are coordinate values under a camera coordinate system, and all the measured point clouds are converted into a unified global cylindrical coordinate system through a coordinate conversion mathematical model, wherein the coordinate conversion mathematical model is as follows:
wherein, (xCCF, yCCF, zCCF) are coordinate values of point clouds measured at different angles in a camera coordinate system, (xCyCF, yCyCF, zCyCF) are coordinate values of the point clouds in a global cylindrical coordinate system, r11, r12, \ 8230, r19 is a position conversion matrix coefficient of a rotating coordinate system and the global cylindrical coordinate system, r21, r22, \8230, r29 is a position conversion matrix coefficient of the camera coordinate system and the point cloud rotating coordinate system, and theta is a rotation angle measured by an angle converter in the calibration process;
the system comprises a camera coordinate system, a point cloud rotating coordinate system, a rotating shaft, a point cloud cylindrical coordinate system, a measuring part, a measuring point cloud measuring system and a measuring part, wherein the camera coordinate system is established on a camera phase plane, the point cloud rotating coordinate system is established on the rotating shaft, the camera coordinate system and the point cloud rotating coordinate system have a fixed position conversion relationship, the global rotating coordinate system is established on a coordinate axis, the pose is unchanged relative to the measuring part when the system rotates, the point cloud cylindrical coordinate system is a cylindrical coordinate system established by cylinder fitting of different measuring point clouds, the global cylindrical coordinate system is established on the axis of the measuring part and does not change when the system is measured in a whole circle, and the global rotating coordinate system and the global cylindrical coordinate system have a fixed position conversion relationship.
2. The pipeline measurement system pose calibration method for point cloud registration according to claim 1, characterized in that: and establishing a camera coordinate system, wherein the camera coordinate system is CCF, the origin of coordinates is at the center of the lens, and the z axis is the optical axis of the camera and is fixed on the camera.
3. The pipeline measurement system pose calibration method for point cloud registration according to claim 1, characterized in that: establishing a point cloud rotating coordinate system which is RCF i The original point is established at a certain fixed point on the rotating shaft, and has a fixed position relation with the CCF in the rotating measurement process, the z axis of the original point is superposed with the rotating shaft, the spatial position changes along with the rotation of the measuring attitude of the system, and i is a point cloud rotating coordinate system of different measuring positions.
4. The pipeline measurement system pose calibration method for point cloud registration according to claim 1, characterized in that: and establishing a global rotation coordinate system (RCF), wherein the origin is established at the RCF i At the origin, the z-axis coincides with the axis of rotation, with the RCF i There is a fixed rotational relationship and the spatial position is fixed during the rotation measurement.
5. The pipeline measurement system pose calibration method for point cloud registration according to claim 1, characterized in that: and establishing a global cylindrical coordinate system, wherein the global cylindrical coordinate system is CyCF, the origin is established at a fixed point on the central axis of the inner surface of the deep-hole part, the z axis of the origin is superposed with the central axis of the barrel, and the spatial position is fixed in the rotation measurement process.
6. The pipeline measurement system pose calibration method for point cloud registration according to claim 1, characterized in that: the error compensation model established in step S4 is:
(xCyCF, yCyCF, zCyCF) are coordinate values of the point cloud in a global cylindrical coordinate system, (xCyCFi, yCyCFi, zCyCFi) are coordinates of the point cloud obtained by measuring different angles in a point cloud cylindrical coordinate system, theta is a rotation angle measured by an angle converter in a calibration process, alpha is an angle difference between the point cloud cylindrical coordinate system and the global cylindrical coordinate system under different rotation angles, and alpha (theta) = theta + A 1 sin(θ+φ 1 )，Δz(θ)＝A 2 sin(θ+φ 2 ) Wherein A is 1 ，A 2 ，φ 1 ，φ 2 Is the magnitude and phase of the function.
7. The pipeline measurement system pose calibration method for point cloud registration according to claim 6, characterized in that: in step S5, a coordinate conversion parameter formula obtained by the error compensation model is:
t i (theta) is a rotation-translation matrix parameter from CCF to CyCF, and t is set i (θ)＝a i sin(θ)+b i cos(θ)+c i Wherein i =1,2, \ 8230, 12, by continuously adjusting A 1 ，A 2 ，φ 1 ，φ 2 And solving different coordinate conversion parameters.
8. The pipeline measurement system pose calibration method for point cloud registration according to claim 1, characterized in that: and in the step S2, the pipeline measuring system rotationally collects point cloud information of the whole circle of the cylinder with the fixed inner diameter by a fixed step length.
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