CN106813570A - Based on the elongated cylindrical object dimensional identification of line-structured light scanning and localization method - Google Patents

Abstract

Object manipulator automatic charging of the present invention, it is proposed that a kind of based on the elongated cylindrical object dimensional identification of line-structured light scanning and localization method：Using structural light measurement sensor with the elongated cylindrical body surface in m axial scan hopper of fixed step size point, the m structural light measurement data of section are obtained；Structural light measurement data to each section carry out data segmentation respectively so that the data for belonging to same object are segmented in one section of circular arc；Circular fitting is carried out to every section of partition data, central coordinate of circle is obtained；M each circular arc center of circle of section of matching so that belong to the circular arc matching of same object together；The three-dimensional coordinate of object is calculated by linear interpolation algorithm；It is determined that the label of crawl object.The present invention can realize online, real-time, the automatic, non-cpntact measurement of elongated cylindrical object dimensional coordinate, and measuring speed is fast, high precision；Small is constrained to object itself, radius and length can arbitrarily change；Object putting position arbitrarily, can be inclined, intersected in hopper；There is robustness to noise.

Description

Long cylindrical object three-dimensional identification and positioning method based on line structured light scanning

Technical Field

The invention belongs to the field of computer vision, and particularly relates to a three-dimensional identification and positioning method for a long cylindrical object based on line structured light scanning.

Background

With the rapid development of national economy, automation has become the development direction in the future. The robot is used for replacing manual work to realize automatic feeding and discharging, so that the production cost is saved, the production efficiency is improved, the safety factor is improved, the labor intensity of workers is reduced, and the robot becomes an ideal choice for more and more companies.

In order to realize the automatic feeding and discharging of the robot, the position of the material needs to be measured, then the material is transferred to the robot, and the mechanical arm is guided to grab. The structured light measurement method is highly emphasized due to simple equipment and strong real-time performance, and particularly shows the advantages of the structured light measurement method in application occasions with strict requirements on the volume, the weight and the power consumption of the measurement equipment.

The structured light measuring method is an active optical measuring technology, and the basic principle is that a controllable light spot, a light bar or a smooth surface structure is projected to the surface of a measured object through a structured light projector, an image is obtained through an image sensor (such as a camera), and then the three-dimensional coordinates of the object are calculated through the system geometric relationship and by utilizing the trigonometric principle. According to the method, a controllable light spot, a light bar or a smooth surface structure is projected to the surface of a measured object by a structured light projector, and the structured light can be divided into point structured light, line structured light and surface structured light. Because the point structured light measurement method needs to scan an object point by point for measurement, the image shooting and image processing time is increased rapidly along with the increase of the measured object, and real-time measurement is difficult to realize; the amount of three-dimensional coordinate point data obtained by the surface structured light is large, and the calculation amount is increased, so that the application of the line structured light in engineering is more common.

Due to the fact that the production environment is severe and serious in noise pollution, the radius and the length of a long cylindrical object in the material box are changed randomly, and the placement is disordered, the precision of a common measuring method is difficult to achieve the actual requirement.

Disclosure of Invention

The invention provides a method for automatically identifying and positioning a long cylindrical object in real time, which has the advantages of high measurement speed, high precision and strong robustness and can automatically realize the three-dimensional identification and positioning of the long cylindrical object in real time, so as to solve the problem that the measurement precision is influenced by the conditions that the noise pollution in a production environment is serious, the radius and the length of the long cylindrical object in a work bin are randomly changed, the placement is disordered and the like.

The technical scheme adopted by the invention for realizing the purpose is as follows: a three-dimensional identification and positioning method for a long cylindrical object based on line structured light scanning is used for realizing measurement of the position of the long cylindrical object in a material box, and comprises the following steps:

axially scanning a long cylindrical object in the material box m times at a fixed step length by using a linear structured light measuring sensor to obtain structured light measuring data of m sections;

respectively carrying out data segmentation on the structured light measurement data of each section so that the data belonging to the same object are segmented in a section of circular arc;

performing arc fitting on each segment of the segmentation data to obtain a circle center coordinate;

matching the circle centers of the arcs of the m sections according to constraint conditions to be met by the arcs on the same object;

calculating the three-dimensional coordinates of the long cylindrical object by using a linear interpolation algorithm;

the number of objects to grab is determined.

The set cross sections of m can basically cover the axial direction of the whole long cylindrical object and are determined according to actual conditions.

The number of rays projected by the line structured light measuring sensor is 1.

In the data segmentation process, the data points of the same arc should simultaneously satisfy the following conditions:

|x_i-x_i-1|+|z_i-z_i-1|＜k₁(1)

|z_i-z_i-5|＜k₂(2)

(z_i-10-z_i≤k₃)||(z_i+10-z_i≤k₃) (3)

wherein (x)_i,z_i) The coordinate values of the structured light measurement data in the x and z directions at the ith point (x)_i-1,z_i-1) The coordinate values of the x and z directions of the i-1 point of the structured light measured data, z_i-5、z_i-10、z_i+10Dividing the coordinate value k of the structured light measurement data in the z direction at the (i-5) th, i-10 th and i +10 th points₁、k₂、k₃Is a preset constant.

And after the data are segmented, eliminating the interference of the structured light measurement data meeting the following conditions:

wherein (x)_i,z_i) The coordinate values of the structured light measurement data in the x and z directions at the ith point,the structured light measurement data, k, for the last point on the arc₄、k₅Is a predetermined constant and k is present₄＜k₅。

The arc fitting requires that the number of points of data on the same arc section simultaneously meet the following conditions:

n＞r/T_sample(6)

n＜2*r/T_sample(7)

wherein n is the number of points of data on the same arc, r is the radius of the arc, and T_sampleIs structured light resolution.

The arc fitting is carried out by adopting a Gaussian-Newton iteration method, and the objective function is as follows:

f(x₀,z₀)＝(x-x₀)²+(z-z₀)²-r²(8)

wherein x and z are data point coordinates on the circular arc, and x₀、z₀The circular arc center coordinates are parameters to be solved, and the solving process is as follows:

the first step is as follows: setting x₀、z₀Initial value of (2)

Wherein x is_kIs the k-th data in the x-direction on the arc, n is the data amount on the arc, z_kIs the maximum value of the data on the arc in the z direction, and r is the radius of the arc;

the second step is that: for function f (x)₀,z₀) Taking the second partial derivative, i.e.

At the same time order

b₁₁Δ₁+b₁₂Δ₂＝B₁(16)

b₂₁Δ₁+b₂₂Δ₂＝B₂(17)

Wherein f is_kThe value of the objective function, Δ, for the k-th data on the arc₁、Δ₂The increments of the center coordinates are obtained from equations (16) and (17):

the third step: updating x₀、z₀Namely:

wherein,respectively are the circular arc center coordinates in the i-1 st iteration,respectively are the circular arc center coordinates in the ith iteration;

the fourth step: calculating the mean square error:

if MS is less than T and T is the maximum mean square error value, stopping iteration to obtain the circular arc center coordinate x₀、z₀(ii) a Otherwise, go to the second step.

The constraint conditions that the arcs on the same object should meet are as follows:

wherein (x)_q,z_q) Is the coordinate of the center of the last matched arc,is the circular arc center coordinate of the unmatched section, k₆、k₇Is a preset constant.

And after the centers of the arcs of the m sections are matched, the object corresponding to the arc section is the candidate grabbed object.

The calculation of the three-dimensional coordinates of the long cylindrical object by using the linear interpolation algorithm specifically comprises the following steps:

knowing the y value of the object at the grabbing position, calculating two sections closest to the y value to obtain the center coordinates (x) of the arc corresponding to the object on the corresponding section₁,z₁)、(x₂,z₂) And calculating by using a linear interpolation method to obtain x and z values corresponding to the y value as follows:

wherein, y₁、y₂The y values corresponding to the two profiles are respectively.

The label of the object to be grasped is determined as follows:

randomly selecting the top layer of objects that can be grabbed if the following inequality holds:

then the object with the label s is the object to be grabbed; wherein, rand () is a random number,the z values corresponding to the two gripping positions of the object respectively marked s,the z values corresponding to two grabbing positions of the object with the mark number k respectively, and m is the number of candidate grabbing objects.

The invention has the following advantages and beneficial effects:

1. the three-dimensional recognition and positioning of the long cylindrical object are realized by adopting the structured light measuring sensor and the PC, and the method has the characteristics of simple equipment, high measuring precision and strong real-time property.

2. Although the structured light measurement data is seriously polluted by noise and has straight line interference, and the data can accurately divide arc sections under the condition of arc connection, so that the structured light measurement data has good anti-interference performance.

3. The long cylindrical object is small in self-restraint, and the radius and the length of the long cylindrical object can be changed at will.

4. Under various placing conditions of multiple layers, cross-layer placement, intersection and the like of long cylindrical objects in the material box, the objects to be grabbed can be accurately positioned, and the robustness is good.

Drawings

FIG. 1 is an overall flow chart of the present invention;

FIG. 2 is a schematic diagram of line structured light data obtained by scanning a certain cross section;

FIG. 3 is a diagram illustrating the result of arc segmentation;

FIG. 4 is a diagram illustrating the fitting result of the arc.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples.

The invention discloses a long cylindrical object three-dimensional identification and positioning method based on linear structured light scanning. As shown in fig. 1, the method specifically comprises the following steps:

1. structured light measurement data acquisition

Axially scanning a long cylindrical object in a material box for m times at a fixed step length by using a structured light measuring sensor to obtain structured light measuring data of m sections, wherein the data of one section is shown in figure 2, and the abscissa and the ordinate are length data in the X direction and the Z direction respectively; the number of rays projected by the structured light measuring sensor is 1.

2. Data partitioning

By analyzing the data characteristics of the same arc in the structured light measurement data, the following conditions are simultaneously met:

|x_i-x_i-1|+|z_i-z_i-1|＜k₁(1)

|z_i-z_i-5|＜k₂(2)

(z_i-10-z_i≤k₃)||(z_i+10-z_i≤k₃) (3)

wherein (x)_i,z_i) Coordinate values, k, in the x and z directions at the ith point for the structured light measurement data₁、k₂、k₃The constant is constant, and the data on the same arc segment can be ensured to be correctly segmented according to the analysis of sample data and the verification through a large number of experiments under actual conditions. Fig. 3 is a schematic diagram showing the segmentation result of the arc segments on a cross section, wherein the + number indicates the start point and the end point of each segmented arc segment.

However, due to the existence of a large amount of noise in the measured data, a section of circular arc is divided into two or more sections, which affects the following circular arc fitting process. The noise interference suffered by the data segmentation process comprises large noise and small noise, wherein the large noise refers to structured light measurement data (x) at the ith point_i,z_i) If it is compared with the structured light measurement data at the last point on the current circular arcIf the absolute value of the difference value in the z direction is more than a certain number, the position is considered as large noise; small noise refers to the structured light measurement data (x) for the ith point_i,z_i) If it is compared with the structured light measurement data at the last point on the current circular arcAnd if the absolute value of the direction difference is less than a certain number, the point is regarded as a small noise point. The arc segmentation process should therefore be continued with the exclusion of interference from noisy data satisfying the following conditions, namely:

wherein,the coordinate value, k, of the structured light measurement data at the last point on the current circular arc in the z direction₄、k₅The constant is constant, and the data can be analyzed according to the sample data and verified through a large number of experiments under actual conditions, so that the interference of noise is eliminated, and the data segmentation is ensured to be correct. Data satisfying equation (4) is defined as large noise, and data satisfying equation (5) is defined as small noise.

3. Fitting of circular arcs

And if the number of points of the data on the same arc section meets the following conditions, performing arc fitting:

n＞r/T_sample(6)

n＜2*r/T_sample(7)

wherein n is the number of points of data on the same arc, r is the radius of the arc, and T_sampleIs the axial scan step size. The center of the circular arc is fitted by adopting a Gaussian-Newton iteration method. The expression of the standard circle is:

(x-x₀)²+(z-z₀)²＝r²(30)

where x and z are coordinates of points on a circle, x₀、z₀As the coordinates of the center of the circle. Order to

f(x₀,z₀)＝(x-x₀)²+(z-z₀)²(31)

Then the gaussian-newton iteration method obtains the center coordinates (x) by taking the minimum value of the following expression₀,z₀) I.e. by

The method comprises the following specific steps:

the first step is as follows: setting x₀、z₀At an initial value of (2), wherein x₀Is the average value of the data on the circular arc in the x direction, z₀The maximum value of the data on the arc in the z-direction minus the radius of the arc, i.e.

The second step is that: for function f (x)₀,z₀) With respect to x₀、z₀The second-order partial derivative is calculated,

at the same time order

b₁₁Δ₁+b₁₂Δ₂＝B₁(16)

b₂₁Δ₁+b₂₂Δ₂＝B₂(17)

Wherein, Delta₁、Δ₂The increment of the circle center coordinate is obtained according to the two formulas (16) and (17):

the third step: updating x₀、z₀Namely:

the fourth step: calculating the mean square error:

if MS is less than T, stopping iteration to obtain circular arc center coordinate x₀、z₀(ii) a Otherwise, go to the second step. Wherein T is the maximum mean square error value. Fig. 4 is a schematic diagram showing the fitting result of the arc, in which the circle represents the circle obtained by the arc segment segmentation fitting, and the + number represents the center of the circle obtained by the fitting.

4. Circular arc matching

Setting the center coordinates of all circular arcs of the first unmatched section asThe coordinates of the centers of all circular arcs used for matching are (x)₁,z₁),(x₂,z₂),...,(x_q,z_q),...,(x_m,z_m). Therefore, two arcs belonging to the same object should satisfy the following conditions simultaneously:

wherein k is₆、k₇The constant is obtained by analyzing the sample data and verifying the sample data through a large number of experiments under actual conditions. After the two formulas are satisfied, the circular arc center coordinates for matching are updated, namely:

5. calculating three-dimensional coordinates of an object

And if the matching times of a certain section of circular arc are equal to the scanning times m, the long cylindrical object corresponding to the section of circular arc is the candidate grabbed object. Knowing the y value of the object at the grabbing position, calculating two sections closest to the y value to obtain the center coordinates (x) of the arc corresponding to the object on the corresponding section₁,z₁)、(x₂,z₂) Then the following linear relationship exists:

the x and z values corresponding to the finally obtained y values are respectively as follows:

wherein, y₁、y₂The y values corresponding to the two profiles are respectively.

6. Determining a gripping object label

If the way of determining the object to be grabbed from the candidate long cylindrical objects is fixed, and the object cannot be grabbed for some reasons, the system repeats the above process and falls into paralysis. A random method is therefore chosen herein to determine the object to be grasped. If the following inequality holds:

the long cylindrical object with the reference number s is the object to be grasped. Wherein rand () is a random number, z₁、z₂Respectively corresponding z values at two grabbing positions, and m is the number of candidate grabbing objects.

Claims (11)

1. A three-dimensional identification and positioning method for a long cylindrical object based on line structured light scanning is used for realizing measurement of the position of the long cylindrical object in a material box, and is characterized by comprising the following steps:

axially scanning a long cylindrical object in the material box m times at a fixed step length by using a linear structured light measuring sensor to obtain structured light measuring data of m sections;

respectively carrying out data segmentation on the structured light measurement data of each section so that the data belonging to the same object are segmented in a section of circular arc;

performing arc fitting on each segment of the segmentation data to obtain a circle center coordinate;

matching the circle centers of the arcs of the m sections according to constraint conditions to be met by the arcs on the same object;

calculating the three-dimensional coordinates of the long cylindrical object by using a linear interpolation algorithm;

the number of objects to grab is determined.

2. The linear structured light scanning-based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein the set m cross sections can substantially cover the axial direction of the whole long cylindrical object and need to be determined according to actual conditions.

3. The method for three-dimensionally identifying and positioning the long cylindrical object based on the line-structured light scanning as claimed in claim 1, wherein the number of rays projected by the line-structured light measuring sensor is 1.

4. The three-dimensional identification and positioning method for the long cylindrical object based on the line structured light scanning as claimed in claim 1, wherein during the data segmentation process, the data points of the same arc should simultaneously satisfy the following conditions:

|x_i-x_i-1|+|z_i-z_i-1|＜k₁(1)

|z_i-z_i-5|＜k₂(2)

(z_i-10-z_i≤k₃)||(z_i+10-z_i≤k₃) (3)

wherein (x)_i,z_i) The coordinate values of the structured light measurement data in the x and z directions at the ith point (x)_i-1,z_i-1) The coordinate values of the x and z directions of the i-1 point of the structured light measured data, z_i-5、z_i-10、z_i+10Dividing the coordinate value k of the structured light measurement data in the z direction at the (i-5) th, i-10 th and i +10 th points₁、k₂、k₃Is a preset constant.

5. The three-dimensional identification and positioning method for the long cylindrical object based on the line structured light scanning as claimed in claim 4, wherein the data segmentation excludes the interference of structured light measurement data satisfying the following conditions:

$|z_i-z_m^{*}|>k_4---\left(4\right)$

$|z_i-z_n^{*}|<k_5---\left(5\right)$

wherein (x)_i,z_i) The coordinate values of the structured light measurement data in the x and z directions at the ith point,the structured light measurement data, k, for the last point on the arc₄、k₅Is a predetermined constant and k is present₄＜k₅。

6. The linear structured light scanning-based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein the arc fitting requires that the number of points of data on the same arc satisfy the following conditions:

n＞r/T_sample(6)

n＜2*r/T_sample(7) wherein n is the number of points of data on the same arc, r is the radius of the arc, and T_sampleIs structured light resolution.

7. The linear structured light scanning-based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein the arc fitting is performed by using a gaussian-newton iteration method, and the objective function is as follows:

f(x₀,z₀)＝(x-x₀)²+(z-z₀)²-r²(8)

wherein x and z are data point coordinates on the circular arc, and x₀、z₀The circular arc center coordinates are parameters to be solved, and the solving process is as follows:

the first step is as follows: setting x₀、z₀Initial value of (2)

$x_0^{\left(0\right)}=\frac{1}{n}\underset{k=1}{\overset{n}{\&Sigma;}}{x}_k---\left(9\right)$

$z_0^{\left(0\right)}=\underset{max}{\&Sigma;}{z}_k-r---\left(10\right)$

Wherein x is_kIs the k-th data in the x-direction on the arc, n is the data amount on the arc, z_kIs the maximum value of the data on the arc in the z direction, and r is the radius of the arc;

the second step is that: for function f (x)₀,z₀) Taking the second partial derivative, i.e.

$b_{11}=\underset{k=1}{\overset{n}{\&Sigma;}}\frac{\&part;f_k}{\&part;x_0}\&CenterDot;\frac{\&part;f_k}{\&part;x_0}---\left(11\right)$

$b_{21}=b_{12}=\underset{k=1}{\overset{n}{\&Sigma;}}\frac{\&part;f_k}{\&part;x_0}\&CenterDot;\frac{\&part;f_k}{\&part;z_0}---\left(12\right)$

$b_{21}=\underset{k=1}{\overset{n}{\&Sigma;}}\frac{\&part;f_k}{\&part;z_0}\&CenterDot;\frac{\&part;f_k}{\&part;z_0}---\left(13\right)$

At the same time order

$B_1=\underset{k=1}{\overset{n}{\&Sigma;}}\frac{\&part;f_k}{\&part;x_0}(r^2-f_k)---\left(14\right)$

$B_2=\underset{k=1}{\overset{n}{\&Sigma;}}\frac{\&part;f_k}{\&part;z_0}(r^2-f_k)---\left(15\right)$

b₁₁Δ₁+b₁₂Δ₂＝B₁(16)

b₂₁Δ₁+b₂₂Δ₂＝B₂(17)

Wherein f is_kThe value of the objective function for the k-th data on the arc，Δ₁、Δ₂The increments of the center coordinates are obtained from equations (16) and (17):

${\mathrm{\&Delta;}}_1=\frac{B_1\&CenterDot;b_{22}-B_2\&CenterDot;b_{12}}{b_{11}\&CenterDot;b_{22}-b_{21}\&CenterDot;b_{12}}---\left(18\right)$

${\mathrm{\&Delta;}}_2=\frac{B_1\&CenterDot;b_{21}-B_2\&CenterDot;b_{11}}{b_{12}\&CenterDot;b_{21}-b_{22}\&CenterDot;b_{11}}---\left(19\right)$

the third step: updating x₀、z₀Namely:

$x_0^i=x_0^{i-1}+{\mathrm{\&Delta;}}_1---\left(20\right)$

$z_0^i=z_0^{i-1}+{\mathrm{\&Delta;}}_2---\left(21\right)$

wherein,respectively are the circular arc center coordinates in the i-1 st iteration,respectively are the circular arc center coordinates in the ith iteration;

the fourth step: calculating the mean square error:

$MS=\frac{1}{n}\underset{k=1}{\overset{n}{\&Sigma;}}{\left(f_k\right(x_0,z_0)-r^2)}^2---\left(22\right)$

if MS is less than T and T is the maximum mean square error value, stopping iteration to obtain the circular arc center coordinate x₀、z₀(ii) a Otherwise, go to the second step.

8. The linear structured light scanning-based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein the constraint conditions that the arcs on the same object should satisfy are as follows:

$|x_q-x_p^0|<k_6---\left(23\right)$

$|z_q-z_p^0|<k_7---\left(24\right)$

wherein (x)_q,z_q) Is the coordinate of the center of the last matched arc,is the circular arc center coordinate of the unmatched section, k₆、k₇Is a preset constant.

9. The linear structured light scanning-based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein after the centers of the arcs of the m cross sections are matched, the object corresponding to the arc is the candidate grasped object.

10. The linear interpolation algorithm based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein the linear interpolation algorithm is used to calculate the three-dimensional coordinates of the long cylindrical object, specifically:

knowing the y value of the object at the grabbing position, calculating two sections closest to the y value to obtain the center coordinates (x) of the arc corresponding to the object on the corresponding section₁,z₁)、(x₂,z₂) And calculating by using a linear interpolation method to obtain x and z values corresponding to the y value as follows:

$x=\frac{y-y_1}{y_2-y_1}\&CenterDot;(x_2-x_1)+x_1---\left(27\right)$

$z=\frac{y-y_1}{y_2-y_1}\&CenterDot;(z_2-z_1)+z_1---\left(28\right)$

wherein, y₁、y₂The y values corresponding to the two profiles are respectively.

11. The linear structured light scanning-based three-dimensional identification and positioning method for the long cylindrical object according to claim 1, wherein the determination of the captured object label is specifically as follows:

randomly selecting the top layer of objects that can be grabbed if the following inequality holds:

then the object with the label s is the object to be grabbed; wherein, rand () is a random number,the z values corresponding to the two gripping positions of the object respectively marked s,the z values corresponding to two grabbing positions of the object with the mark number k respectively, and m is the number of candidate grabbing objects.