CN112880562A - Method and system for measuring pose error of tail end of mechanical arm - Google Patents
Method and system for measuring pose error of tail end of mechanical arm Download PDFInfo
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- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
- G01B11/005—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates coordinate measuring machines
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- G06T7/0004—Industrial image inspection
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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Abstract
The invention discloses a method and a system for measuring pose errors of the tail end of a mechanical arm, wherein the system comprises a measuring target device, the mechanical arm, a stripe projection three-dimensional scanning device and a processor; the measuring target device comprises a base, a plurality of standard balls and a plurality of supporting rods, one end of each supporting rod is fixed on the base, the other end of each supporting rod is used for fixing one standard ball, the supporting rods are distributed in an annular mode, and the measuring target device is installed at the tail end of the mechanical arm. The standard pose of the tail end of the mechanical arm is obtained in advance when no external influence exists, and the pose error is directly compared with the actual pose of the tail end of the mechanical arm in actual work to quickly measure the pose error; in addition, a large amount of three-dimensional point cloud data of the surface of the reference sphere are obtained, and the positions of the sphere centers are fitted through the three-dimensional point cloud data.
Description
Technical Field
The invention relates to the field of industrial mechanical arms, in particular to a method and a system for measuring pose errors of a tail end of a mechanical arm.
Background
The industrial mechanical arm has the characteristics of simple structure, convenience in operation and control and the like, can replace manpower to realize automatic and intelligent production, can improve the production efficiency, improve the production environment and reduce the product cost, and is increasingly applied to enterprises. Although the industrial mechanical arm is widely applied to dangerous work such as product transportation or paint spraying, the whole mechanical structure of the industrial mechanical arm belongs to a series structure, the structural rigidity is weak, high positioning precision is difficult to achieve in the working process, the absolute positioning error of the industrial mechanical arm can even reach 2-3 mm, and further application of the industrial mechanical arm in high-precision manufacturing occasions is greatly limited. The absolute positioning accuracy of the industrial mechanical arm can be improved by optimizing the device and the component structure or improving the modeling theory and other modes, but because the overall structure of the industrial mechanical arm is unbalanced, the positioning accuracy improving effect of the methods is limited.
Compared with the prior art, the position and posture error of the industrial mechanical arm is monitored and timely compensated by the aid of the measuring system, so that high-precision positioning of the industrial mechanical arm can be effectively realized, and the control precision requirement of intelligent product manufacturing can be met. The existing industrial mechanical arm tail end pose measuring method can be simply divided into a contact type measuring method and a non-contact type measuring method. The contact measurement mode requires that the measurement equipment must be directly contacted with a measurement target, and equipment such as a ball bar instrument, a pull-wire sensor and the like is usually used. The non-contact measuring method mainly comprises a laser tracking instrument and a visual sensor. Among them, the laser tracker has the advantages of high measurement accuracy, large measurement range, etc., but is not easy to carry and is expensive. By means of the advantages of high measuring efficiency, low cost and the like, visual detection becomes the most common mode for measuring the terminal pose of the industrial mechanical arm. The binocular vision method is based on a parallax principle and achieves three-dimensional pose detection through matching of a plurality of feature points. According to the method, the pose measurement can be realized only by synchronously acquiring images through two cameras, the measurement efficiency is high, and the method is the most common method for measuring the pose of the tail end of the industrial mechanical arm at present. However, the measurement accuracy of the binocular vision method is easily affected by factors such as the measurement distance and the imaging angle, and the nominal measurement accuracy can only be obtained at the optimal measurement position.
Disclosure of Invention
The invention provides a method and a system for measuring pose errors of a tail end of a mechanical arm, which are used for solving one or more technical problems in the prior art and at least providing a beneficial selection or creation condition.
In a first aspect, an embodiment of the present invention provides a method for measuring a pose error of an end of a robot arm, including:
designing a measuring target device, wherein the measuring target device comprises a base, a plurality of standard balls and a plurality of supporting rods, one end of each supporting rod is fixed on the base, the other end of each supporting rod is used for fixing one standard ball, the supporting rods are distributed in a ring shape, and the measuring target device is arranged at the tail end of a mechanical arm;
before actual work, when the tail end of the mechanical arm is moved to a target position, a plurality of reference phase shift stripe images of a standard ball are obtained through a stripe projection three-dimensional scanning device, a three-dimensional point cloud data calculation method is used for processing the plurality of reference phase shift stripe images to obtain three-dimensional point cloud data of the surface contour of each standard ball as reference three-dimensional point cloud data, and the three-dimensional coordinates of the center of the sphere of each standard ball are fitted according to the reference three-dimensional point cloud data to serve as standard pose data;
in the actual working process, when the tail end of the mechanical arm moves to the target position, a plurality of actual phase shift stripe images of the standard ball are obtained through a stripe projection three-dimensional scanning device, three-dimensional point cloud data of the surface contour of each standard ball are obtained by processing the actual phase shift stripe images through a three-dimensional point cloud data calculation method and serve as actual three-dimensional point cloud data, and the three-dimensional coordinates of the center of the ball of each standard ball are fitted according to the actual three-dimensional point cloud data and serve as actual pose data;
and when the difference value between the actual pose data and the standard pose data after translation parameter translation and rotation parameter rotation transformation meets a preset condition, taking the translation parameter and the rotation parameter meeting the preset condition as the pose error of the tail end of the mechanical arm.
Further, acquiring a plurality of reference phase shifted fringe images of a standard sphere by a fringe projection three-dimensional scanning device comprises:
using a stripe projection three-dimensional scanning device to project multistep phase shift stripe templates, and simultaneously using a camera to synchronously acquire a phase shift stripe image I corresponding to each phase shift stripe templatei(x, y), i ═ 1,2, …, N are the number of phase shift steps, and x and y are the abscissa and ordinate of the image.
Further, the pose data calculation method includes:
calculating a modulation degree image according to the collected phase shift fringe image;
carrying out binarization conversion on the modulation degree image to obtain a binarization modulation degree image;
determining each standard sphere surface image area from the binarization modulation degree image;
converting the image coordinates of the surface area of each standard sphere into three-dimensional point cloud data of the surface contour of each standard sphere according to a conversion model of the fringe projection three-dimensional scanning device and a phase value at the coordinate position of a phase image, wherein the phase image is obtained by processing a phase shift fringe image through a multi-step phase shift algorithm;
and acquiring three-dimensional coordinates of the center position of each standard sphere as pose data by combining the three-dimensional point cloud data of the surface profile of each standard sphere with a least square fitting algorithm.
Further, the calculating a modulation degree image according to the collected phase shift fringe image is as follows:
where M (x, y) is a modulation degree image.
Further, the obtaining a binary modulation image by performing binary conversion on the modulation image includes:
and calculating a binary image segmentation threshold value of the modulation degree image by Otsu, and performing binarization conversion on the modulation degree image according to the segmentation threshold value to obtain a binarization modulation degree image.
Further, the determining each standard sphere surface image area from the binarized modulation degree image includes:
and searching each disconnected region in the binary modulation degree image, searching a region with circular characteristics according to the variation condition of the distance between the center and each edge, and determining the region as each standard sphere surface image region.
Further, fitting the three-dimensional coordinates of the sphere center of each standard sphere according to the reference three-dimensional point cloud data as standard pose data specifically comprises:
and acquiring the sphere center three-dimensional coordinates of each standard sphere as standard pose data by combining the reference three-dimensional point cloud data with a least square fitting algorithm.
Further, iterating the translation parameters and the rotation parameters by using a particle swarm optimization algorithm until the difference value between the actual pose data and the standard pose data after translation parameter translation and rotation parameter rotation transformation meets a preset condition, wherein the preset condition means that the sum of the absolute values of the difference values between the sphere center three-dimensional coordinates of each standard sphere in the actual pose data and the sphere center three-dimensional coordinates of the corresponding standard sphere in the standard pose data after translation parameter translation and rotation parameter rotation transformation is smaller than a threshold value.
Further, the three-dimensional coordinates of the sphere center of each standard sphere in the actual pose data are translated along the spatial coordinate direction and are subjected to rotation transformation processing around the coordinate direction:
wherein, C'j(x’j,y’j,z’j) Is the sphere center three-dimensional coordinate, C, of the jth standard sphere in the actual pose data "j(x”j,y”j,z”j) J is more than or equal to 3 and less than or equal to M, M is the number of the standard balls, (delta x ', delta y', delta z ') is a translation parameter, (theta'x,θ′y,θ′z) Is a rotation parameter.
In a second aspect, an embodiment of the present invention provides a robot end pose error system, including: the system comprises a measuring target device, a mechanical arm, a stripe projection three-dimensional scanning device and a processor; wherein the measuring target device comprises a base, a plurality of standard balls and a plurality of supporting rods, one end of each supporting rod is fixed on the base, the other end of each supporting rod is used for fixing one standard ball, the supporting rods are distributed in a ring shape,
the measuring target device is used for being mounted at the tail end of the mechanical arm;
the fringe projection three-dimensional scanning device is used for moving the tail end of the mechanical arm to a target position before actual work to obtain a plurality of reference phase shift fringe images of the standard ball; the system is also used for acquiring a plurality of actual phase shift fringe images of the standard ball when the tail end of the mechanical arm moves to the target position in the actual working process;
and the processor is used for determining standard pose reference data according to the plurality of reference phase shift stripe images, determining actual pose data according to the plurality of actual phase shift stripe images, performing translation and rotation transformation processing on the pose data of each standard ball in the actual pose data along the spatial coordinate direction and around the coordinate direction, and taking the translation parameter and the rotation parameter which meet the preset conditions as the pose error of the tail end of the mechanical arm when the difference value between the actual pose data subjected to translation parameter translation and rotation parameter rotation transformation and the standard pose data meets the preset conditions.
The method and the system for measuring the pose error of the tail end of the mechanical arm have the following beneficial effects: the standard pose of the tail end of the mechanical arm is obtained in advance when no external influence exists, and the pose error is directly compared with the standard pose of the tail end of the mechanical arm in actual work, so that the pose error is quickly measured; in addition, a large amount of three-dimensional point cloud data of the surface of the reference sphere are obtained, and the positions of the sphere centers are fitted through the three-dimensional point cloud data.
Drawings
The accompanying drawings 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 example serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a flowchart of a method for measuring pose errors of an end of a robot according to an embodiment of the present invention;
fig. 2 is a structural diagram of a measurement target apparatus according to an embodiment of the present invention.
FIG. 3(a) is a grayscale image obtained by processing a phase-shifted fringe image according to the prior art;
FIG. 3(b) is a modulation image obtained by processing the phase-shifted fringe image according to the present invention;
fig. 4 is a flowchart for determining an end pose error of a mechanical arm based on a particle swarm optimization algorithm according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that although functional block divisions are provided in the system drawings and logical orders are shown in the flowcharts, in some cases, the steps shown and described may be performed in different orders than the block divisions in the systems or in the flowcharts. The terms first, second and the like in the description and in the claims, and the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Fig. 1 is a method for measuring a pose error of an end of a robot arm, provided by an embodiment of the present invention, including the following steps:
s101, designing a measuring target device, wherein the measuring target device is arranged at the tail end of a mechanical arm;
as shown in fig. 2, the measurement target device 100 includes a base 101, a plurality of standard balls 102, a plurality of support rods 103, and an operating tool 104, wherein one end of each support rod 103 is fixed on the base 101, the other end is used for fixing one standard ball 102, the base 101 is a circular base, and the plurality of support rods are distributed in a ring shape; the measuring target device is mounted at the end of the robot arm 200, and the number of the standard balls is M, 3 ≦ M, for example, in fig. 2, M ≦ 3.
S102, before actual work, when the tail end of the mechanical arm is moved to a target position, obtaining a plurality of reference phase shift stripe images of a standard ball through a stripe projection three-dimensional scanning device, processing the plurality of reference phase shift stripe images by using a three-dimensional point cloud data calculation method to obtain three-dimensional point cloud data of the surface contour of each standard ball as reference three-dimensional point cloud data, and fitting the three-dimensional coordinates of the center of each standard ball according to the reference three-dimensional point cloud data as standard pose data;
s103, in the actual working process, when the tail end of the mechanical arm moves to the target position, obtaining a plurality of actual phase shift stripe images of the standard ball through a stripe projection three-dimensional scanning device, processing the actual phase shift stripe images by using a three-dimensional point cloud data calculation method to obtain three-dimensional point cloud data of the surface contour of each standard ball as actual three-dimensional point cloud data, and fitting the three-dimensional coordinates of the center of each standard ball according to the actual three-dimensional point cloud data as actual pose data;
and S104, translating the three-dimensional coordinates of the sphere center of each standard sphere in the actual pose data along the space coordinate direction and performing rotation transformation around the coordinate direction, and when the difference value between the actual pose data subjected to translation parameter translation and rotation parameter rotation transformation and the standard pose data meets a preset condition, taking the translation parameters and the rotation parameters meeting the preset condition as the pose error of the tail end of the mechanical arm.
The pose collected in the actual working process is influenced by dynamic loads, and the error is large, and the standard pose of the tail end of the mechanical arm is obtained in advance when no external influence exists, and is directly compared with the standard pose of the tail end of the mechanical arm in actual working to quickly measure the pose error.
Further, in step S102, acquiring a plurality of reference phase-shifted fringe images of the standard sphere by the fringe projection three-dimensional scanning device includes:
using a stripe projection three-dimensional scanning device to project multistep phase shift stripe templates, and simultaneously using a camera to synchronously acquire a phase shift stripe image I corresponding to each phase shift stripe templatei(x, y), i is 1,2, …, N is the phase shift step number, x and y are the abscissa and ordinate of the image, the multi-step phase shift fringe template refers to the phase shift fringe template with different initial phases, the initial phase difference of the adjacent phase shift fringe templates is 360 degrees/N, and the phase shift fringe template is input to the fringe projection three-dimensional scanning device, so that the projected light scans the target object, and the phase shift fringe image of the target object is acquired. For example, three-step phase shift corresponds to three phase shift fringe templates, so as to obtain 3 phase shift fringe images, and the phase difference between each image is 120 degrees.
In one embodiment, the method for acquiring a plurality of actual phase-shifted fringe images of the standard sphere by the fringe projection three-dimensional scanning device in step S103 is the same as the method for acquiring a plurality of reference phase-shifted fringe images of the standard sphere by the fringe projection three-dimensional scanning device in step S102.
Further, the three-dimensional point cloud data calculation method in step S102 and step S103 includes:
s201, calculating a modulation degree image according to the collected phase shift fringe image;
s202, carrying out binarization conversion on the modulation degree image to obtain a binarization modulation degree image;
s203, determining each standard ball surface image area from the binary modulation degree image;
and S204, converting the image coordinates of the surface area of each standard sphere into three-dimensional point cloud data of the surface contour of each standard sphere according to the conversion model of the fringe projection three-dimensional scanning device and the phase value at the phase image coordinate.
The conversion model adopts a phase-height conversion model in the prior art, the coordinate of a phase distribution diagram and the numerical value at the coordinate, namely the phase are input, the three-dimensional coordinate corresponding to the coordinate of a phase image can be directly calculated by adopting the phase-height conversion model, namely the three-dimensional coordinate of each point on the surface of each standard sphere is calculated, and the phase image is obtained by processing the acquired phase shift fringe image through a multi-step phase shift algorithm.
Further, the step S102 of fitting the three-dimensional coordinates of the sphere center of each standard sphere according to the reference three-dimensional point cloud data as standard pose data specifically includes:
and acquiring the sphere center three-dimensional coordinates of each standard sphere as standard pose data by combining the reference three-dimensional point cloud data with a least square fitting algorithm.
Further, the step S103 of fitting the three-dimensional coordinates of the sphere center of each standard sphere according to the actual three-dimensional point cloud data as actual pose data specifically includes:
and acquiring the sphere center three-dimensional coordinates of each standard sphere as actual pose data by combining actual three-dimensional point cloud data with a least square fitting algorithm.
The pose error measurement method of the invention is used for obtaining the three-dimensional point cloud data of the surface of the reference sphere, and the three-dimensional point cloud data is used for fitting the positions of all sphere centers, and because a large amount of point cloud data is used in the calculation process, a small amount of data with larger errors has little influence on the measurement result, so that the measurement precision of the pose error measurement method is higher than that of a binocular vision measurement system, and the pose error measurement of the tail end of the industrial mechanical arm with higher precision can be realized.
Further, in step S201, the modulation degree image is calculated according to the collected phase shift fringe image as follows:
where M (x, y) is a modulation degree image. As shown in fig. 3(a) and fig. 3(b), fig. 3(a) is a grayscale image obtained by processing a phase-shifted fringe image according to the prior art, and fig. 3(b) is a modulation image according to the present invention, in which the brightness of the edge region of the spherical target in the modulation image is reduced compared with the grayscale image, which is beneficial to accurately segmenting and identifying the standard spherical image region in the subsequent process. The lower left corners of fig. 3(a) and 3(b) are enlarged views of the joint of the standard ball and the support rod, and it can be seen that the modulation degree image has higher image resolution than the gray scale image.
Further, the step S202 of performing binarization conversion on the modulation degree image to obtain a binarized modulation degree image includes:
and calculating a binary image segmentation threshold value of the modulation degree image by Otsu, and performing binarization conversion on the modulation degree image according to the segmentation threshold value to obtain a binarization modulation degree image.
Further, the determining each standard sphere surface image area from the binarized modulation degree image in step S203 includes:
and searching each disconnected region in the binary modulation degree image, searching a region with circular characteristics according to the variation condition of the distance between the center and each edge, and determining the region as each standard sphere surface image region.
Further, iterating the translation parameters and the rotation parameters by using a particle swarm optimization algorithm until the difference value between the actual pose data and the standard pose data after translation parameter translation and rotation parameter rotation transformation meets a preset condition, wherein the preset condition means that the sum of the absolute values of the difference values between the sphere center three-dimensional coordinates of each standard sphere in the actual pose data and the sphere center three-dimensional coordinates of the corresponding standard sphere in the standard pose data after translation parameter translation and rotation parameter rotation transformation is smaller than a threshold value.
Further, in step S104, the process of translating the three-dimensional coordinates of the center of sphere of each standard sphere along the spatial coordinate direction and performing rotational transformation around the coordinate direction includes:
wherein, C'j(x’j,y’j,z’j) Is the sphere center three-dimensional coordinate, C, of the jth standard sphere in the actual pose data "j(x”j,y”j,z”j) J is more than or equal to 3 and less than or equal to M, M is the number of the standard balls, (delta x ', delta y', delta z ') is the translation parameter of the standard balls, (theta'x,θ′y,θ′z) Is the rotation parameter of a standard ball.
In order to quickly determine the pose error value, the invention uses a particle swarm algorithm to carry out parameter optimization. The algorithm continuously iterates the translation (Δ x ', Δ y', Δ z ') and rotation transformations (θ'x,θ′y,θ′z) And (4) parameters.
The end pose error of the industrial mechanical arm can be decomposed into a translation parameter (delta x, delta y, delta z) along the spatial coordinate direction and a rotation parameter (theta) around the coordinate directionx,θy,θz) When the three-dimensional coordinates C of the centers of the standard spheres are converted "j(x”j,y”j,z”j) Reference coordinate C with the center of the standard spherej(xj,yj,zj) The translation parameter (Deltax ', Deltay ', Deltaz ') and the rotation transformation (theta ') at the time when the sum of absolute values of the differences satisfies a condition of being less than a preset value 'x,θ′y,θ′z) As a translation parameter (Δ x, Δ y, Δ z) in the spatial coordinate direction and a rotation parameter (θ) around the coordinate direction of each standard spherex,θy,θz) Namely, as an accurate measurement result of the pose error of the end of the industrial mechanical arm, the calculation flow chart is as shown in fig. 4:
s301, translating the pose data of the standard ball in the actual pose data along the spatial coordinate direction and performing rotation transformation around the coordinate direction;
s302, judging whether the sum of the absolute values of the difference values of the actual pose data and the standard pose data after the actual pose data are subjected to translation parameter translation and rotation parameter rotation transformation meets the condition that the sum is smaller than a threshold value;
if yes, executing step S303;
when the judgment result is no, executing step S304;
s303, taking the translation parameter and the rotation parameter as the pose error of the tail end of the mechanical arm;
s304, iterating the translation parameter and the rotation parameter by using a particle swarm optimization algorithm, and executing the step S302.
In an embodiment, an end pose error measurement apparatus of a robot provided in an embodiment of the present invention includes:
an end-of-arm pose error system, comprising: the system comprises a measurement target device 100, a mechanical arm 200, a stripe projection three-dimensional scanning device and a processor; the measuring target device 100 comprises a base 101, a plurality of standard balls 102, a plurality of support rods 103 and an operating tool 104, wherein one end of each support rod 103 is fixed on the base 101, the other end of each support rod 103 is used for fixing one standard ball 102, the base 101 is a circular base, the operating tool 104 comprises an operating support rod and an operating end, the operating support rod is fixed in the center of the circular base, the length of the operating support rod is longer than that of the support rods 103, and the support rods are distributed in a ring shape; the measurement target device is mounted at the end of the robot arm 200.
The measurement target device 100 is used for being mounted at the tail end of the mechanical arm 200;
the fringe projection three-dimensional scanning device is used for acquiring a plurality of reference phase shift fringe images of the standard ball when the tail end of the mechanical arm moves to a target position; the system is also used for acquiring a plurality of actual phase shift fringe images of the standard ball when the tail end of the mechanical arm moves to the target position in the actual working process;
and the processor is used for determining standard pose reference data according to the plurality of reference phase shift stripe images, determining actual pose data according to the plurality of actual phase shift stripe images, performing translation and rotation transformation processing on the actual pose data along the spatial coordinate direction and around the coordinate direction, performing translation and rotation transformation processing on the pose data of each standard ball in the actual pose data along the spatial coordinate direction and around the coordinate direction, and taking the translation parameters and the rotation parameters which meet the preset conditions as the pose error of the tail end of the mechanical arm when the difference value between the actual pose data subjected to translation and rotation parameter transformation and the standard pose data meets the preset conditions.
The processing process of the processor is similar to the processing process of the robot arm end pose error measurement method, and is not described again here.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and 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.
While the preferred embodiments of the present invention have been described in detail, it will be understood by those skilled in the art that the foregoing and various other changes, omissions and deviations in the form and detail thereof may be made without departing from the scope of this invention.
Claims (10)
1. A method for measuring pose errors of the tail end of a mechanical arm is characterized by comprising the following steps:
designing a measuring target device, wherein the measuring target device comprises a base, a plurality of standard balls and a plurality of supporting rods, one end of each supporting rod is fixed on the base, the other end of each supporting rod is used for fixing one standard ball, the supporting rods are distributed in a ring shape, and the measuring target device is arranged at the tail end of a mechanical arm;
before actual work, moving the tail end of the mechanical arm to a target position, acquiring a plurality of reference phase shift stripe images of a standard ball through a stripe projection three-dimensional scanning device, processing the plurality of reference phase shift stripe images by using a three-dimensional point cloud data calculation method to obtain surface contour three-dimensional point cloud data of each standard ball as reference three-dimensional point cloud data, and fitting the sphere center three-dimensional coordinates of each standard ball according to the reference three-dimensional point cloud data as standard pose data;
in the actual working process, when the tail end of the mechanical arm moves to the target position, a plurality of actual phase shift stripe images of the standard ball are obtained through a stripe projection three-dimensional scanning device, three-dimensional point cloud data of the surface contour of each standard ball are obtained by processing the actual phase shift stripe images through a three-dimensional point cloud data calculation method and serve as actual three-dimensional point cloud data, and the three-dimensional coordinates of the center of the ball of each standard ball are fitted according to the actual three-dimensional point cloud data and serve as actual pose data;
and when the difference value between the actual pose data and the standard pose data after translation parameter translation and rotation parameter rotation transformation meets a preset condition, taking the translation parameter and the rotation parameter meeting the preset condition as the pose error of the tail end of the mechanical arm.
2. The robot arm tip pose error measurement method of claim 1, wherein acquiring a plurality of reference phase shifted fringe images of a standard sphere by a fringe projection three-dimensional scanning device comprises:
using a stripe projection three-dimensional scanning device to project multistep phase shift stripe templates, and simultaneously using a camera to synchronously acquire a phase shift stripe image I corresponding to each phase shift stripe templatei(x, y), i ═ 1,2, …, N are the number of phase shift steps, and x and y are the abscissa and ordinate of the image.
3. The robot arm end pose error measurement method according to claim 2, wherein the three-dimensional point cloud data calculation method comprises:
calculating a modulation degree image according to the collected phase shift fringe image;
carrying out binarization conversion on the modulation degree image to obtain a binarization modulation degree image;
determining each standard sphere surface image area from the binarization modulation degree image;
and converting the image coordinates of the surface area of each standard sphere into three-dimensional point cloud data of the surface contour of each standard sphere according to the conversion model of the fringe projection three-dimensional scanning device and the phase value at the phase image coordinate, wherein the phase image is obtained by processing the phase shift fringe image through a multi-step phase shift algorithm.
4. The method for measuring the pose error of the end of the mechanical arm according to claim 3, wherein the calculating the modulation degree image according to the collected phase shift fringe image comprises:
where M (x, y) is a modulation degree image.
5. The method for measuring the pose error of the tail end of the mechanical arm according to claim 3, wherein the step of performing binarization conversion on the modulation degree image to obtain a binarization modulation degree image comprises the following steps:
and calculating a binary image segmentation threshold value of the modulation degree image by Otsu, and performing binarization conversion on the modulation degree image according to the segmentation threshold value to obtain a binarization modulation degree image.
6. The robot arm tip pose error measurement method according to claim 5, wherein the determining each standard sphere surface image area from the binarized modulation degree image comprises:
and searching each disconnected region in the binary modulation degree image, searching a region with circular characteristics according to the variation condition of the distance between the center and each edge, and determining the region as each standard sphere surface image region.
7. The method for measuring the pose error of the tail end of the mechanical arm according to claim 1, wherein fitting the three-dimensional coordinates of the sphere center of each standard sphere according to the reference three-dimensional point cloud data as standard pose data specifically comprises:
and acquiring the sphere center three-dimensional coordinates of each standard sphere as standard pose data by combining the reference three-dimensional point cloud data with a least square fitting algorithm.
8. The method for measuring the pose error of the tail end of the mechanical arm according to claim 1, characterized in that a particle swarm optimization algorithm is used for iterating the translation parameter and the rotation parameter until the difference value between the actual pose data and the standard pose data after the translation parameter translation and the rotation parameter rotation transformation meets a preset condition, wherein the preset condition means that the sum of the absolute values of the difference values between the sphere center three-dimensional coordinates of each standard sphere in the actual pose data and the sphere center three-dimensional coordinates of the corresponding standard sphere in the standard pose data after the translation parameter translation and the rotation parameter rotation transformation is smaller than a threshold value.
9. The robot arm end pose error measurement method according to claim 8, wherein the three-dimensional coordinates of the sphere center of each standard sphere in the actual pose data are translated along the spatial coordinate direction and rotationally transformed around the coordinate direction by:
wherein, C'j(x’j,y’j,z’j) Is the sphere center three-dimensional coordinate, C, of the jth standard sphere in the actual pose data "j(x”j,y”j,z”j) J is more than or equal to 3 and less than or equal to M, M is the number of the standard balls in the actual pose data, (delta x ', delta y', delta z ') is a translation parameter, (theta'x,θ′y,θ′z) Is a rotation parameter.
10. The utility model provides a terminal position appearance error measurement system of arm, its characterized in that includes: the system comprises a measuring target device, a mechanical arm, a stripe projection three-dimensional scanning device and a processor; wherein the measuring target device comprises a base, a plurality of standard balls and a plurality of supporting rods, one end of each supporting rod is fixed on the base, the other end of each supporting rod is used for fixing one standard ball, the supporting rods are distributed in a ring shape,
the measuring target device is used for being mounted at the tail end of the mechanical arm;
the fringe projection three-dimensional scanning device is used for moving the tail end of the mechanical arm to a target position before actual work to obtain a plurality of reference phase shift fringe images of the standard ball; the system is also used for acquiring a plurality of actual phase shift fringe images of the standard ball when the tail end of the mechanical arm moves to the target position in the actual working process;
and the processor is used for determining standard pose reference data according to the plurality of reference phase shift stripe images, determining actual pose data according to the plurality of actual phase shift stripe images, performing translation and rotation transformation processing on the pose data of each standard ball in the actual pose data along the spatial coordinate direction and around the coordinate direction, and taking the translation parameter and the rotation parameter which meet the preset conditions as the pose error of the tail end of the mechanical arm when the difference value between the actual pose data subjected to translation parameter translation and rotation parameter rotation transformation and the standard pose data meets the preset conditions.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113639634A (en) * | 2021-08-09 | 2021-11-12 | 重庆市计量质量检测研究院 | Three-dimensional optical scanning measuring instrument and error analysis method thereof |
| CN113701798A (en) * | 2021-08-29 | 2021-11-26 | 孙恺欣 | Calibration device and method for two-dimensional grid standard plate |
| CN113974834A (en) * | 2021-09-14 | 2022-01-28 | 武汉联影智融医疗科技有限公司 | Casing pose determination method and device of surgical robot system |
| WO2023072086A1 (en) * | 2021-11-01 | 2023-05-04 | 北京卫星制造厂有限公司 | Workpiece end face attitude assessment method |
| CN116236278A (en) * | 2023-05-08 | 2023-06-09 | 江苏省人民医院（南京医科大学第一附属医院） | Bone tunnel establishment system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651752A (en) * | 2016-09-27 | 2017-05-10 | 深圳市速腾聚创科技有限公司 | Three-dimensional point cloud data registration method and stitching method |
| CN109443206A (en) * | 2018-11-09 | 2019-03-08 | 山东大学 | Mechanical arm tail end pose measurement system and method based on color spherical fishing light source target |
| CN109544599A (en) * | 2018-11-22 | 2019-03-29 | 四川大学 | A kind of three-dimensional point cloud method for registering based on the estimation of camera pose |
| JP2020069549A (en) * | 2018-10-30 | 2020-05-07 | Thk株式会社 | Calibration method and gripping system |
| CN111355894A (en) * | 2020-04-14 | 2020-06-30 | 长春理工大学 | Novel self-calibration laser scanning projection system |
| CN111775146A (en) * | 2020-06-08 | 2020-10-16 | 南京航空航天大学 | Visual alignment method under industrial mechanical arm multi-station operation |
-
2021
- 2021-01-19 CN CN202110070623.6A patent/CN112880562A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651752A (en) * | 2016-09-27 | 2017-05-10 | 深圳市速腾聚创科技有限公司 | Three-dimensional point cloud data registration method and stitching method |
| JP2020069549A (en) * | 2018-10-30 | 2020-05-07 | Thk株式会社 | Calibration method and gripping system |
| CN109443206A (en) * | 2018-11-09 | 2019-03-08 | 山东大学 | Mechanical arm tail end pose measurement system and method based on color spherical fishing light source target |
| CN109544599A (en) * | 2018-11-22 | 2019-03-29 | 四川大学 | A kind of three-dimensional point cloud method for registering based on the estimation of camera pose |
| CN111355894A (en) * | 2020-04-14 | 2020-06-30 | 长春理工大学 | Novel self-calibration laser scanning projection system |
| CN111775146A (en) * | 2020-06-08 | 2020-10-16 | 南京航空航天大学 | Visual alignment method under industrial mechanical arm multi-station operation |
Non-Patent Citations (1)
| Title |
|---|
| 殷永凯: "相位辅助光学三维测量系统的标定方法", 《中国博士学位论文全文数据库 信息科技辑》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113639634A (en) * | 2021-08-09 | 2021-11-12 | 重庆市计量质量检测研究院 | Three-dimensional optical scanning measuring instrument and error analysis method thereof |
| CN113701798A (en) * | 2021-08-29 | 2021-11-26 | 孙恺欣 | Calibration device and method for two-dimensional grid standard plate |
| CN113701798B (en) * | 2021-08-29 | 2024-01-19 | 孙恺欣 | Calibrating device and method for two-dimensional grid standard plate |
| CN113974834A (en) * | 2021-09-14 | 2022-01-28 | 武汉联影智融医疗科技有限公司 | Casing pose determination method and device of surgical robot system |
| CN113974834B (en) * | 2021-09-14 | 2023-10-31 | 武汉联影智融医疗科技有限公司 | Method and device for determining sleeve pose of surgical robot system |
| WO2023072086A1 (en) * | 2021-11-01 | 2023-05-04 | 北京卫星制造厂有限公司 | Workpiece end face attitude assessment method |
| CN116236278A (en) * | 2023-05-08 | 2023-06-09 | 江苏省人民医院（南京医科大学第一附属医院） | Bone tunnel establishment system |
| CN116236278B (en) * | 2023-05-08 | 2023-07-18 | 江苏省人民医院（南京医科大学第一附属医院） | Bone tunnel establishment system |
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