CN111735487A - Sensor, sensor calibration method and device, and storage medium - Google Patents

Sensor, sensor calibration method and device, and storage medium Download PDF

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CN111735487A
CN111735487A CN202010420953.9A CN202010420953A CN111735487A CN 111735487 A CN111735487 A CN 111735487A CN 202010420953 A CN202010420953 A CN 202010420953A CN 111735487 A CN111735487 A CN 111735487A
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sensor
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calibration
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CN111735487B (en
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李星辉
陈瑞铭
王晓浩
周倩
倪凯
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Shenzhen International Graduate School of Tsinghua University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/497—Means for monitoring or calibrating

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Abstract

The application discloses a sensor, a sensor calibration method and device and a storage medium. The method comprises the steps of obtaining initial parameters of a calibration model of the sensor, calculating calibration parameters of the calibration model according to the initial parameters, and calibrating the sensor according to the calibration parameters. By establishing a calibration model calibrated by the sensor and selecting initial parameters of the calibration model, under the condition of meeting the parameter constraint range of optical parameters, proper calibration parameters can be obtained according to the initial parameters to calibrate and design the sensor, so that the measurement precision of a sensor measurement system is improved, and the application range of the sensor is expanded.

Description

Sensor, sensor calibration method and device, and storage medium
Technical Field
The present application relates to the field of measurement, and in particular, to a sensor, a sensor calibration method and apparatus, and a storage medium.
Background
The optical parameters of the sensor affect the measurement parameters of the sensor, such as sensitivity, measurement range and resolution, and the measurement parameters of the sensor cannot be adjusted and controlled by the variation of a single optical variable because the coupling relationship between the optical parameters and the measurement parameters is a nonlinear relationship. In the related art, in the process of designing a sensor, researchers mostly determine the optical structure of the sensor through a large number of experimental groceries and empirical laws, a theoretical mathematical model for calibrating the sensor cannot be established, and the influence of certain optical parameters on the measured parameters can be accurately obtained through a simulation process.
In the related technology, parameter calibration of the sensor is carried out through a particle swarm optimization, local extremum, premature convergence or stagnation easily occur in the method, and as all particles are only gathered to the self and the historical optimal positions of the neighborhood without referring to the constraint relation among other parameters, the parameter design of the laser triangulation distance measuring sensor is influenced, and higher convergence speed and convergence accuracy cannot be obtained. Or in the related technology, a two-dimensional plane is used for calibrating the target, local world coordinates of the sensor characteristic points under respective target coordinate systems are established through cross ratio invariance, world coordinates of all calibrated characteristic points under the world coordinate systems are solved through a camera coordinate system as a medium, a lens plane of the sensor calibrated by the method is parallel to an imaging plane, a large depth of field range cannot be obtained, the imaging magnification is small, and the resolution of the imaging system is not high.
Disclosure of Invention
The present application is directed to solving at least one of the problems in the prior art. Therefore, the sensor calibration method is provided, a theoretical mathematical calibration model for sensor calibration is established, calibration parameters are obtained through the calibration model, the sensor is calibrated, and the influence of certain optical parameters on the measurement parameters is accurately obtained through a simulation process.
In a first aspect, an embodiment of the present application provides: the sensor calibration method comprises the following steps:
acquiring initial parameters of a calibration model of the sensor;
calculating calibration parameters of the calibration model according to the initial parameters;
and calibrating the sensor according to the calibration parameters.
Further, the acquiring initial parameters of the calibration model of the sensor includes:
obtaining a target function of the sensitivity value of the calibration model;
and optimizing the objective function by selecting the maximum sensitivity value, and obtaining the initial parameter according to the optimization result.
Further, the optimizing the objective function by selecting a maximum sensitivity value and obtaining the initial parameter according to an optimization result includes:
generating a plurality of groups of random parameters of the target function within a parameter constraint range according to a Monte Carlo method;
calculating the current sensitivity value of the target function according to the plurality of groups of random parameters;
and performing loop iteration, and selecting a random parameter corresponding to the maximum value of the current sensitivity value as the initial parameter.
Further, the initial parameters include: and calculating calibration parameters of the calibration model according to the lens focal length and the Samm angle.
Further, the calibrating the sensor according to the calibration parameters includes:
obtaining a first maximum likelihood function according to the calibration parameters;
and calibrating the sensor according to the parameters corresponding to the first maximum likelihood function.
Further, the sensor calibration method further comprises the following steps:
carrying out distortion compensation according to the distortion parameter of the sensor to obtain an optimized parameter;
and calibrating the sensor according to the optimized parameters.
Further, the sensor distortion parameters include: the method comprises the following steps of obtaining optimized parameters by distortion compensation according to sensor distortion parameters, wherein the optimized parameters comprise the following steps:
obtaining a second maximum likelihood function according to the first maximum likelihood function, the radial distortion parameter and the tangential distortion parameter;
and obtaining an optimization parameter according to the second maximum likelihood function.
The embodiment of the application has at least the following beneficial effects: the measurement precision of the sensor measurement system is improved, and the application range of the sensor is expanded.
In a second aspect, an embodiment of the present application provides: a sensor calibrated using the sensor calibration method of any one of the first aspect.
In a third aspect, an embodiment of the present application provides: a sensor calibration method and device comprises the following steps:
at least one processor, and a memory communicatively coupled to the at least one processor;
wherein the processor is configured to execute the sensor calibration method according to any one of the first aspect by calling a computer program stored in the memory.
In a fourth aspect, an embodiment of the present application provides: a computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform a method of sensor calibration as defined in any one of the first aspects.
The beneficial effects of the embodiment of the application are that:
according to the embodiment of the application, the initial parameters of the calibration model of the sensor are obtained, the calibration parameters of the calibration model are calculated according to the initial parameters, and the calibration of the sensor is carried out according to the calibration parameters. By establishing a calibration model calibrated by the sensor and selecting initial parameters of the calibration model, under the condition of meeting the parameter constraint range of optical parameters, proper calibration parameters can be obtained according to the initial parameters to calibrate and design the sensor, so that the measurement precision of a sensor measurement system is improved, and the application range of the sensor is expanded.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
FIG. 1 is a schematic diagram of an imaging structure of a laser triangulation ranging sensor according to an embodiment of a sensor calibration method in the embodiment of the present application;
FIG. 2 is a schematic view of an imaging model of an embodiment of a sensor calibration method according to the present application;
FIG. 3 is a schematic flow chart diagram illustrating an embodiment of a sensor calibration method according to the present disclosure;
fig. 4 is a schematic flowchart of step S1 of an embodiment of the sensor calibration method in the embodiment of the present application.
Detailed Description
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the present application, and that for a person skilled in the art, other drawings and other embodiments can be obtained from these drawings without inventive effort.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The laser triangulation distance measurement method is mainly characterized in that a laser beam irradiates a measured target at a certain incident angle, the laser beam is reflected and scattered on the surface of the target, the reflected laser beam is converged and imaged by a lens at another angle, and a light spot is imaged on a CCD (Charge-coupled Device) position sensor. When the measured object moves along the laser direction (or called forward displacement), the light spot on the sensor moves, and the displacement corresponds to the moving distance of the measured object, so that the distance value between the measured object and the base line can be calculated according to the displacement distance of the light spot, and the distance measurement is realized. Since the incident light and the reflected light form a triangle, geometric trigonometric theorem is applied when calculating the displacement of the light spot, and therefore the measuring method is called laser triangulation.
The sensor applying the laser triangulation ranging method in the related technology is called as a laser triangulation ranging sensor, which is a commonly used optical ranging sensor and generally comprises two types, one type is a common line structured light laser triangulation sensor, the imaging surface of the sensor is parallel to the central plane of a lens, the imaging depth of field of a sensor system is small, and the clear image of a target in a large range cannot be obtained due to the limitation of the depth of field, so that the clear imaging of the whole object plane cannot be ensured. The other type of the optical distance measuring sensor meets the Scheimflux law structure, a perfectly focused picture can be shot on an inclined image surface, the structure meeting the Scheimflux law can increase the imaging depth of field, and provide larger magnification and visual angle range, and the optical distance measuring sensor is matched with a structural light source to construct a more accurate 3D imaging system.
An embodiment of the application provides a sensor calibration method, which is used for setting and calibrating a calibration model of a laser triangulation ranging sensor based on a Schlemm's law structure.
Fig. 1 is a schematic diagram of an imaging structure of a laser triangulation distance measuring sensor according to an embodiment of the present application.
From the figure can be seen a laser100 laser is applied to the surface of the object to be measured, and the measuring range is located in the depth of field range L3I.e. the object to be measured is located in the depth of field range L3L of3Is represented by a line segment BC, point A is the center point of the working distance, and the depth of field range L3A, B, C three points are projected on the photosensitive device 200 to form three points A ', B' and C ', a dotted line passing through the points A and A' represents the optical axis of the convex lens 300, the included angle between the optical axis and the laser emitted by the laser 100 is called a scattering angle, which is designated as α, the included angle between the straight line where the photosensitive device 200 is located and the optical axis is a Sammy angle, which is designated as β, the center of the convex lens 300 is O, OA is an object distance, and the size is designated as L1OA' is the image distance and the size is recorded as L2。
The imaging structure of the laser triangulation in fig. 1 satisfies the schem's law. Its imaging plane a1, laser plane a2, and lens principal plane A3 intersect in a straight line, referred to as the schlemm line a 4. A mathematical model of oblique imaging can be obtained according to the model of the imaging of the convex lens 300, and then a calibration model in the embodiment of the application is obtained.
As shown in fig. 2, which is a schematic diagram of an imaging model in an embodiment of the present application, in a camera coordinate system with O point as a coordinate origin, a straight line r represents a normal of an actual inclined image plane Π s, and a normal direction vector is
Figure BDA0002496855200000041
The normal r respectively intersects with an ideal vertical image surface Π and an actual inclined image surface Π s at Pc、PsPoint, the origin of coordinates of an ideal vertical image surface Π and an actual inclined image surface Π s is recorded as O',
Figure BDA0002496855200000051
and
Figure BDA0002496855200000052
the direction vector of the x and y axes of the actual inclined image plane Π s is shown as the normal direction vector
Figure BDA0002496855200000053
Is composed of
Figure BDA0002496855200000054
Is a vector product of
Figure BDA0002496855200000055
f is the focal length of the lens, τxAnd τyAnd the rotation angles of the ideal vertical image plane Π around the x and y axes of the actual inclined image plane Π s in a camera coordinate system are respectively shown.
As shown in fig. 3, which is a schematic flow chart of a sensor calibration method provided in an embodiment of the present application, as shown in fig. 3, the method includes the following steps:
s1: and acquiring initial parameters of a calibration model of the sensor.
S2: and calculating calibration parameters of the calibration model according to the initial parameters.
S3: and calibrating the sensor according to the calibration parameters.
In one embodiment, step S1 obtains initial parameters of a calibration model of the sensor, including:
obtaining a target function of a sensitivity value of a calibration model;
and optimizing the objective function by selecting the maximum sensitivity value, and obtaining initial parameters according to the optimization result.
For example, the objective function is set according to the optical parameters of the sensor as:
Figure BDA0002496855200000056
where K denotes the sensitivity value, f denotes the lens focal length, H denotes the working distance, α denotes the scattering angle, β denotes the Samm angle, y denotes the valuemaxRepresents the farthest distance of movement of the sensor in the forward direction, where ymaxI.e. the farthest moving distance of the object to be measured moving along the laser direction.
Referring to fig. 3, in an embodiment, optimizing the objective function according to the maximum sensitivity value principle, and obtaining the initial parameter according to the optimization result specifically includes:
several sets of random parameters of the objective function are generated within the parameter constraints according to the monte carlo method.
And obtaining the current sensitivity value of the target function according to the random parameters.
And performing loop iteration, and selecting a random parameter corresponding to the maximum value of the current sensitivity value as an initial parameter.
In one embodiment, random parameters of several groups of laser triangulation distance measuring sensors are generated according to the monte carlo method under the condition that parameter constraint ranges of optical parameters are met, and the random parameters include but are not limited to: and optical parameters such as a lens focal length f, a working distance H, a scattering angle alpha, a Schlemm angle beta and the like.
In one embodiment, the parameter constraint range is a value range of a parameter variable, and the value range generally has various limitations, which may be static or a function of an independent variable, specifically determined by the actual use design requirements of the laser triangulation distance measuring sensor.
In one embodiment, the random parameter is set according to practical engineering application experience, for example, the scattering angle cannot be too large according to design experience, and the constraint range of the scattering angle is set to be 30 ≦ α ≦ 50 in a specific embodiment; the focal length f of the lens is set according to the focal length of the fixed-focus industrial lens commonly used in industry, and the selectable value range comprises the following steps: 16mm, 25mm, 35mm, 50mm and the like, and taking the focal lengths as random parameters corresponding to the focal length f of the lens; the measuring range is located between the depth of field ranges BC, i.e. the working distance H is obtained within the measuring range, which is selected according to the size of the object to be measured, for example, the measuring range may be selected to be 16 mm.
In addition, in actual use, parameters such as the resolution μ and the range L of the convex lens can be set, for example, the large and constant image model is selected as follows: the industrial camera of MER-2000-19U3M is used as an optical sensor, and the resolution is as follows: 5496 (H). times.3672 (V), and the pixel size is 2.4 μm. times.2.4 μm, and the industrial camera has high resolution, low noise and other imaging characteristics.
In one embodiment, the current sensitivity value of the objective function is obtained according to the random parameters, specifically, the number of cycles is set according to the number of sets of random parameters, and a set of random parameters is selected and substituted into the objective function to obtain the current sensitivity value corresponding to the set of random parameters.
In one embodiment, a parameter corresponding to the maximum value of the current sensitivity value is iteratively selected as an initial parameter, and the iterative process is represented as:
and comparing the current sensitivity value with the set maximum sensitivity value, if the current sensitivity value is greater than the maximum sensitivity value, assigning the current sensitivity value to the maximum sensitivity value, recording the current corresponding random parameter, and entering the next cycle. And if the current sensitivity value is smaller than the maximum sensitivity value, directly entering the next cycle until the cycle is ended. Namely, the parameter corresponding to the maximum value of the current sensitivity value is selected as the initial parameter.
In one embodiment, the initial parameters include: and calculating calibration parameters of the calibration model according to the lens focal length and the Samm angle.
In one embodiment, the resulting set of initial parameters is represented as: the scattering angle α is 42 °, the schemer angle β is 53.9 °, the working distance H is 75mm, the lens focal length f is 40mm, the resolution μ is 0.003mm, the range L is 16.34mm, and the sensitivity K is 1.86.
It will be appreciated that the initial parameters are not exclusive and the above embodiment is only an optimal solution within one of the parameter constraints. This is called the optimal solution for two reasons: 1) for the monte carlo method, repeated iteration experiments tend to converge finally, but optimization processes in each iteration are different, so that in limited experiments, one solution which is most fit with practical constraints is selected as an optimal solution, namely the initial parameters. 2) In the above embodiments, some parameter constraint ranges are exemplified (for example, the scattering angle α cannot be too large, the focal length of the fixed-focus industrial lens commonly used in the industry is fixed, the measurement range can be determined according to the size of the measured object, the model of the industrial camera selected, etc.), but in practice, the parameter constraint ranges corresponding to different application scenarios may change, so that the above set of initial parameters is only one of the preferred initial parameters for the laser triangulation distance measuring sensor system with high precision, small range and short working distance, and does not represent that the initial parameters of the present application can only be the above values.
In one embodiment, as shown in fig. 4, the step S1 includes the following steps:
s11: and obtaining an objective function of the calibration model, and optimizing the objective function according to the maximum sensitivity value principle.
S12: several sets of random parameters of the objective function are generated within the parameter constraint range according to the monte carlo method, i.e. random parameters are generated within the parameter constraint range, including but not limited to: and optical parameters such as a lens focal length f, a working distance H, a scattering angle alpha, a Schlemm angle beta and the like.
S13: obtaining the current sensitivity value K of the target function according to the random parameteri；
S14: judging the current sensitivity value KiWhether or not to be greater than or equal to the maximum sensitivity value KmaxIf K isi≥KmaxStep S15 is entered, otherwise step S16 is entered.
S15: the current sensitivity value K is measurediIs assigned to the maximum sensitivity value Kmax。
S16: and judging whether the random parameter loop is ended, if not, entering the step S12, otherwise, entering the step S17.
S17: the current maximum sensitivity value KmaxThe corresponding parameter is used as the initial parameter.
After the initial parameters are obtained in step S17, the process proceeds to step S2, where the calibration parameters of the calibration model are calculated.
In one embodiment, the calibration model set is represented as:
Figure BDA0002496855200000071
wherein s represents a scale factor for representing the relation of size transformation of the left side and the right side of the equation,
Figure BDA0002496855200000072
representing a coordinate point, P, on a pixel coordinate systemWRepresenting coordinate points on a world coordinate system, A representing an internal reference matrix, S representing a rotation matrix change relation matrix from an ideal vertical image surface to an actual inclined image surface, RτA rotation matrix representing the ideal vertical image plane to the actual tilted image plane, [ RT]An external reference matrix is represented.
The parameters of the calibration model are described in detail below.
In one embodiment of the method of the present invention,
Figure BDA0002496855200000073
representing a coordinate point, P, on a pixel coordinate systemWAnd coordinate points on the world coordinate system are represented as follows:
Figure BDA0002496855200000081
in one embodiment, the reference matrix a is represented as:
Figure BDA0002496855200000082
Figure BDA0002496855200000083
wherein (u)0,v0) And the pixel coordinate value representing the center of the camera, namely the x and y coordinates of the central point of the ideal vertical image plane pi in a pixel coordinate system.
In one embodiment, dX and dY represent the actual physical dimensions of a single pixel in the x and y directions of the pixel coordinate system, respectively, in mm, f represents the lens focal length, and f represents the lens focal lengthx、fyRespectively representing the conversion relation between the x-axis direction and the y-axis direction of a pixel coordinate system and the actual object size, namely the conversion relation of units between a world coordinate system and the pixel coordinate system, wherein the unit of a coordinate axis in the pixel coordinate system is pixel(s), and the unit of the coordinate axis in the world coordinate system is mm.
In one embodiment, γ represents a tilt factor between the ideal vertical image plane Π and the pixel coordinate system, that is, represents a tilt relationship between the pixel coordinate system and the ideal vertical image plane Π, and the tilt factor has an initial value of 0.
In one embodiment, a rotation matrix R from an ideal vertical image plane Π to an actual inclined image plane Π s is obtained according to the theory that a free rigid body rotates around x and y axesτExpressed as:
Figure BDA0002496855200000084
wherein, taux、τyAnd respectively representing the rotation angles of the ideal vertical image plane pi around the x axis and the y axis in the camera coordinate system.
In one embodiment, as can be seen from FIG. 2, r represents the normal of the actual tilted image plane Π s, and the normal vector is
Figure BDA0002496855200000085
The normal r respectively intersects with an ideal vertical image surface Π and an actual inclined image surface Π s at Pc、PsAnd (4) point. Let λ denote
Figure BDA0002496855200000086
The third row product of the matrix, (X)C,YC,ZC) Representing a point P on the ideal vertical image plane Πc，PsThe points satisfy the following relationships:
Figure BDA0002496855200000091
due to psHas the coordinates of (x)s,ys) Thus is a straight line
Figure BDA0002496855200000092
The projection on the ideal vertical image plane Π is represented as:
Figure BDA0002496855200000093
the combined vertical type (8) and the formula (9) can obtain a rotation matrix change relation matrix from an ideal vertical image surface Π to an actual inclined image surface Π, namely S, which is expressed as:
Figure BDA0002496855200000094
in one embodiment, τ isx＝β，τyThe initial value of (2) is 0, that is, the calibration parameter can be calculated according to the obtained initial parameter.
In one embodiment, [ RT ] represents an extrinsic reference matrix, which is a4 × 4 roto-translating transformation matrix, and thus is also referred to as an extrinsic roto-translating transformation matrix, with an initial value of 0.
In one embodiment, step S3 includes the following steps:
and obtaining a first maximum likelihood function according to the calibration parameters, and carrying out nonlinear calibration parameter optimization according to the first maximum likelihood function.
And calibrating the sensor according to the parameters corresponding to the first maximum likelihood function.
For example, a first maximum likelihood function corresponding to the internal and external parameters of the sensor is determined from the initial parameters, and is expressed as:
Figure BDA0002496855200000095
wherein the content of the first and second substances,
Figure BDA0002496855200000096
which represents the initial pixel coordinates, is,
Figure BDA0002496855200000097
representing the reprojected pixel coordinates.
In one embodiment, the first maximum likelihood function in the embodiment of the present application is designed based on the criterion that the reprojection error is minimum, where the reprojection error refers to that, in the pixel coordinate system, the initial pixel coordinates (i.e., the image acquired by the sensor) and the coordinates of the calibration target in the world coordinate system are reprojected (for example, by substituting the world coordinate system into an imaging mathematical model, i.e., the calibration model in the present application), the pixel difference between the two is compared, and the calibration parameter with the smallest pixel difference between the two is selected.
In one embodiment, the sensor calibration method further comprises: and carrying out distortion compensation according to the calibration parameters to obtain optimized parameters. For example:
carrying out distortion compensation according to the sensor distortion parameter to obtain an optimized parameter, wherein the distortion compensation comprises the following steps: lens distortion compensation;
and calibrating the sensor according to the optimized parameters.
In one embodiment, the sensor distortion parameter comprises: the method specifically comprises the following steps of carrying out distortion compensation on the radial distortion parameter and the tangential distortion parameter according to the distortion parameter of the sensor to obtain optimized parameters:
obtaining a second maximum likelihood function according to the first maximum likelihood function, the radial distortion parameter and the tangential distortion parameter;
and obtaining an optimized parameter according to the second maximum likelihood function.
Wherein the second maximum likelihood function is represented as:
Figure BDA0002496855200000101
wherein D isjx、DjyRepresenting the radial distortion parameter, Dqx、DqyRepresenting the tangential distortion parameter.
In one embodiment, the radial distortion parameter and the tangential distortion parameter are expressed as:
Figure BDA0002496855200000102
wherein k is1,k2Representing a radial distortion polynomial coefficient, and the initial value is 0; p is a radical of1,p2The tangential distortion polynomial coefficient is 0 at the initial value.
In one embodiment, the second maximum likelihood function is solved by an L-M optimization algorithm (Levenberg-Marquardt, Levenberg-Marquardt method) to perform nonlinear optimization, so as to obtain optimized parameters, and the calibration of the sensor is performed according to the optimized parameters.
In one implementation, a sensor calibration method according to an embodiment of the present application includes the following steps:
obtaining calibration parameters according to initial parameters of the sensor;
obtaining a first maximum likelihood function according to the calibration parameters, and carrying out nonlinear optimization on the internal and external parameters;
establishing a second maximum likelihood function according to the nonlinear optimization result, and performing distortion compensation to obtain an optimized parameter;
and calibrating the sensor according to the optimized parameters corresponding to the second maximum likelihood function.
With reference to fig. 1 to 4, the embodiment of the present application describes how to obtain optimal optical parameters under actual parameter constraints, and a calibration model of a laser triangulation ranging sensor is established according to the optical parameters to describe the ranging performance of the laser triangulation ranging sensor. The laser triangulation ranging sensor can meet the actual use requirement by utilizing the actual parameter constraint condition, and the sensitivity performance of the sensor is ensured by establishing an objective function according to the maximum sensitivity principle.
The method comprises the steps of establishing a calibration model, simplifying the physical process of laser triangulation imaging by using a mathematical model, obtaining calibration parameters more fitting the constraint condition of actual parameters according to optimal optical parameters, designing initial parameters of a laser triangulation ranging sensor according to a Monte Carlo method under the condition of meeting the constraint range of the optical parameters, obtaining the initial parameters of the corresponding calibration model under the condition of maximum sensitivity, substituting the initial parameters according to the calibration model to obtain internal and external parameter information of the sensor, compensating lens distortion according to a sensor distortion parameter model, and optimizing the calibration parameters to obtain optimized internal and external parameter information, namely optimized parameters. When the optimization process of the internal parameter, the external parameter and the distortion parameter of the calibration model is more accurate, the calibration model of the sensor conforms to the actual use requirement, the measurement precision of the sensor measurement system is improved, the output error is smaller, and the application range of the sensor is expanded.
Another embodiment of the present application discloses a sensor calibrated by the sensor calibration method as described in any of the above embodiments, which may be a laser triangulation ranging sensor.
In addition, this application still provides sensor calibration equipment, includes:
at least one processor, and a memory communicatively coupled to the at least one processor;
wherein the processor is configured to perform the method according to embodiment one by calling the computer program stored in the memory. A computer program, i.e. a program code, for causing a sensor calibration apparatus to perform the steps of the sensor calibration method as described in the previous embodiment section of this specification, when the program code is run on the sensor calibration apparatus.
In addition, the present application also provides a computer-readable storage medium, which stores computer-executable instructions for causing a computer to execute the method according to the above embodiment.
It should be noted that: the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods disclosed above may be implemented as software, firmware, hardware, or suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same, although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present disclosure, and the present disclosure should be construed as being covered by the claims and the specification.

Claims (10)

1. The sensor calibration method is characterized by comprising the following steps:
acquiring initial parameters of a calibration model of the sensor;
calculating calibration parameters of the calibration model according to the initial parameters;
and calibrating the sensor according to the calibration parameters.
2. The sensor calibration method according to claim 1, wherein said obtaining initial parameters of a calibration model of said sensor comprises:
obtaining a target function of the sensitivity value of the calibration model;
and optimizing the objective function by selecting the maximum sensitivity value, and obtaining the initial parameter according to the optimization result.
3. The sensor calibration method according to claim 2, wherein the optimizing the objective function by selecting a maximum sensitivity value and obtaining the initial parameter according to an optimization result comprises:
generating a plurality of groups of random parameters of the target function within a parameter constraint range according to a Monte Carlo method;
calculating the current sensitivity value of the target function according to the random parameters;
and performing loop iteration, and selecting a random parameter corresponding to the maximum value of the current sensitivity value as the initial parameter.
4. A method for sensor calibration as claimed in claim 3, wherein said initial parameters comprise: and calculating calibration parameters of the calibration model according to the lens focal length and the Samm angle.
5. A method for calibrating a sensor according to claim 1, wherein said calibrating the sensor according to the calibration parameters comprises:
obtaining a first maximum likelihood function according to the calibration parameters;
and calibrating the sensor according to the parameters corresponding to the first maximum likelihood function.
6. The sensor calibration method according to claim 5, further comprising:
carrying out distortion compensation according to the distortion parameter of the sensor to obtain an optimized parameter;
and calibrating the sensor according to the optimized parameters.
7. The sensor calibration method according to claim 6, wherein the sensor distortion parameter comprises: the method comprises the following steps of obtaining optimized parameters by distortion compensation according to sensor distortion parameters, wherein the optimized parameters comprise the following steps:
obtaining a second maximum likelihood function according to the first maximum likelihood function, the radial distortion parameter and the tangential distortion parameter;
and obtaining an optimization parameter according to the second maximum likelihood function.
8. Sensor, characterized in that it is calibrated using the sensor calibration method according to any one of claims 1 to 7.
9. A sensor calibration apparatus, comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a sensor calibration method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon computer-executable instructions for causing a computer to perform a method of calibrating a sensor as claimed in any one of claims 1 to 7.
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