A multi-parameter monocular vision synchronous measurement method for load motion in a drop tower test

Abstract

The application belongs to the technical field of measurement, and relates to a kind of tower test load movement multi-parameter monocular vision synchronous measurement method, uses measurement camera to collect calibration image, and calibrates measurement camera internal parameter and distortion coefficient;Design cooperation mark point array on the plane of target load, as measurement feature point;Target load is unlocked when test cabin is free fall, and measurement camera collects the image containing cooperation mark point array information, and pre-processes the collected image, and extracts measurement feature point;The rotation matrix and translation vector of target coordinate system to camera coordinate system at different time are calculated using PnP algorithm;The three-dimensional coordinates of target load centroid in camera coordinate system at different time are calculated using rotation matrix and translation vector, and then the translation direction and translation velocity of target load are calculated;The unit direction vector of reference vector in camera coordinate system at different time under target coordinate system is calculated using rotation matrix, and rotation feature point is generated;The rotation trajectory plane is fitted using rotation feature point, the space circle fitting optimization function is constructed, the trajectory circle equation is calculated, and the coordinates of rotation feature point are reduced in dimension, and the rotation angle and rotation angular velocity of target load are calculated using reduced dimension coordinates.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of visual measurement, and particularly relates to a kind of tower test load movement multi-parameter monocular vision synchronous measurement method. BACKGROUND

[0002] In recent years, China's aerospace technology has developed rapidly, and the diversification of aerospace functional requirements has put forward new requirements for spacecraft structures. Separation and unlocking device is an important part of spacecraft system, which has been applied to the separation of satellite and rocket, the separation of loading equipment, etc., and plays an important role in the launch, flight and on-orbit operation of spacecraft. The impact vibration generated during the launch of spacecraft can easily damage the high-precision instruments carried by the spacecraft. The separation and unlocking device is closely connected with the instruments, providing rigid support for the instruments during the launch phase, and fixing and protecting the instruments. After the spacecraft reaches the specified orbit, the constraints between the load and the spacecraft platform are safely and reliably released, and the freedom of the instrument load is released. In some cases, there are clear restrictions on the motion parameters of the instrument load, such as separation speed, separation direction and separation speed, etc. Therefore, tower tests are generally carried out on the ground to measure the motion parameters of the separated load and verify the separation performance of the separation and unlocking device.

[0003] Visual measurement technology is a non-contact measurement technology with high precision, strong adaptability and high reliability, which has been widely used in aerospace industry. According to the number of cameras, it can be divided into monocular vision technology and binocular stereo vision technology. Binocular stereo vision technology can solve the three-dimensional coordinates of the target through the parallax between different viewing angles, but its measurement system structure is complex, and the high-precision matching of the same points under dynamic conditions is relatively difficult, which often causes matching errors, non-synchronous errors and double target positioning errors, etc. The measurement system structure of monocular vision measurement technology is simple, and there is no synchronous error and matching error, but it cannot obtain the stereo information of the target.

[0004] Therefore, in order to overcome the shortcomings of binocular vision technology system structure and monocular vision technology cannot obtain stereo information, and realize the measurement of the parameters such as translation direction, translation speed, self-rotation direction and self-rotation angular velocity of the target load, the present application provides an effective tower test load movement multi-parameter synchronous measurement method based on monocular vision system. SUMMARY

[0005] The technical problem to be solved by the present application is to overcome the shortcomings of existing monocular vision technology and binocular stereo vision technology in tower test, and to provide an effective separation load movement multi-parameter synchronous measurement method based on monocular vision system, including the translation direction, translation speed, self-rotation direction and self-rotation angular velocity of the load target. This method not only helps to simplify the measurement system structure, but also avoids the difficulty of matching algorithm, reduces the source of measurement error, and realizes the synchronous measurement of the movement multi-parameters of the measured load target.

[0006] The technical solution of the present invention is: a method for synchronously measuring multi-parameter monocular vision of load motion in a drop tower test, characterized by:

[0007] S1: Calibrate the internal parameter matrix A and distortion coefficient vector d of the measurement camera; calculate the center of mass position of the target payload; use the calibrated monocular camera to capture N frames of measurement images of the target payload in motion, extract visual feature points in the measurement images, and sort and match the visual feature points;

[0008] S2: Take the center of mass of the target load as the coordinate origin and establish the target coordinate system Ox on the target load o y o z o , according to the visual feature points extracted in step S1, calculate the coordinate system of the target to the camera coordinate system at different times c -x c y c z c The rotation matrix and translation vectors i=1,2,···,N;

[0009] S3: By rotation matrix and translation vectors The target load center of mass is converted to the camera coordinate system, and the center of mass coordinate is used to fit the center of mass trajectory line L to obtain the translation direction n of the target load; the center of mass coordinate is projected onto the line L, and the translation velocity v of the target load is calculated using the center of mass projection point; through the rotation matrix Obtain the rotation characteristic point P of the target load at different times i , using the rotation feature point P i Fit the target load rotation trajectory plane π; according to the perpendicular constraint and the center coplanar constraint, fit the target load rotation trajectory circle in the plane π, calculate the coordinate of the center C of the rotation trajectory circle; i After projecting the center C onto the plane π, the coordinates of the feature projection point and the center projection point are reduced in dimension, and the reduced-dimensional coordinates are used to calculate the rotation angle θ and rotation speed ω of the target load.

[0010] Furthermore, the specific operation steps of step S1 include:

[0011] S101: Fix the camera and place a dot target in front of the camera. Adjust the position and orientation of the dot target. Use the measurement camera to collect 10 to 15 images of the target in different poses. Calibrate the internal parameter matrix A and distortion coefficient vector d of the measurement camera using the Zhang Zhengyou camera calibration method.

[0012] S102: Calculating the center of mass position of the target payload based on the structure and density information of the target payload;

[0013] S103: Designing a cooperative marker dot array on a certain plane of the target load, and using a calibrated measurement camera to collect N frames of measurement images containing the cooperative marker dot array when the target load moves;

[0014] S104: Extracting the ellipse corresponding to the cooperative marker point in the measurement image, and calculating the common tangent point coordinates of the ellipse as the measurement feature point of the target load;

[0015] S105: Sorting the feature points in each extracted frame of image, and matching the feature points in different frames of image according to the sorting result.

[0016] Further, the specific operation steps of step S3 include:

[0017] S301: According to the rotation matrix and the translation vector , the coordinates of the target load mass center O i at different time are converted into the coordinates in the camera coordinate system

[0018] S302: Fitting a space straight line L using the mass center points O i at different time, and obtaining the direction vector n of the straight line L in the camera coordinate system, then the translation direction of the target load is n;

[0019] S303: Projecting the mass center points O i at different time onto the straight line L to obtain the projection point , and the coordinate vector of the projection point is , and the translation speed v of the target load is calculated according to the coordinates of the projection point and the time difference:

[0020]

[0021] Wherein, ΔT represents the time interval between adjacent frames of the measurement camera, and m and n represent the frame number.

[0022] S304: According to the rotation matrix , the unit reference vector i -x o,i y o,i z o,i in the i-th frame of target coordinate system O is converted into the unit vector in the camera coordinate system, and the end point of the vector is taken as a rotation feature point P i , and a rotation feature point set S={P i |i=1,2,···,N} is constructed.

[0023] S305: Let the set S ′ =S, use set S ′ Fit the equation of plane π and calculate P i Distance d to plane π i ,like Make d i >d0, then from the set S ′ Eliminate P i , and refit the plane until it satisfies

[0024] d i ≤d0;

[0025] S306: Based on the perpendicular bisector constraint and the circle center coplanarity constraint, a spatial circle fitting optimization function is constructed, and the extreme value points of the optimization function are calculated to obtain the three-dimensional coordinates of the center C of the fitting circle trajectory and the linear equation of the self-rotation axis, where the perpendicular bisector constraint is defined as the set S ′ The perpendicular bisector of the line connecting any two points in the circle must pass through the center of the circle; the center coplanarity constraint is defined as the center of the circle being inside the fitting plane π;

[0026] S307: Project the set S and the center C onto the plane π to obtain the set S π and the center C π , establish a plane coordinate system O in plane π d -x d y d , the set S π and the center C π Perform coordinate dimensionality reduction to obtain its d -x d y d Two-dimensional coordinates in the coordinate system and X C,d , the rotation angle θ and rotation angular velocity ω of the target load are calculated by the following formula:

[0027]

[0028] The advantages of the present invention over existing technologies are as follows: This invention addresses the problem of multi-parameter measurement of target load motion in drop tower separation tests and proposes a method for synchronous multi-parameter measurement of target load motion based on a monocular vision system. This method, which enables multi-parameter measurement of target load motion based on monocular vision technology, not only overcomes the inability of monocular vision technology to obtain stereoscopic target information but also avoids the complex structure and algorithmic difficulties of binocular stereo vision technology. This method enables synchronous measurement of the translational direction, translational velocity, self-rotational direction, and self-rotational angular velocity of the target load separation motion in drop tower tests, providing guidance for the measurement of motion parameters of complex motions. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The above advantages of the present application will become apparent and easy to understand from the following description of embodiments taken in conjunction with the accompanying drawings. The drawings are only intended to illustrate embodiments of the present application and not to limit the present application.

[0030] Figure 1 Flow chart of the method for measuring multiple parameters of target motion based on monocular vision in the present application;

[0031] Figure 2 Schematic diagram of the array of cooperative markers in the present application;

[0032] Figure 3 Schematic diagram of the dynamics analysis of the target load in the present application;

[0033] Figure 4 Schematic diagram of the measurement process in the present application;

[0034] Figure 5 Flow chart of the method for measuring rotation parameters in the present application. DETAILED DESCRIPTION

[0035] The specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0036] The measurement camera is fixed, a circular dot target is placed in front of the measurement camera, the posture and position of the circular dot target are adjusted, and 10-15 calibration images with different target postures are collected by using the measurement camera; the image target feature points are extracted by pre-processing the above calibration images; and the internal parameter matrix A and the distortion coefficient vector d of the measurement camera are calculated according to the paper “A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence [J]. 2000, 22(11): 1330-1334” by Zhang Zhengyou.

[0037] As Figure 2 , the array of cooperative markers is designed on one face of the target load, and taken as an example of 2×2 array, marker point diameter of 20 mm, and adjacent point spacing of 40 mm.

[0038] As Figure 3 , taken as an example of a uniform rectangular target load, the centroid is located at the center of the rectangle, in the tower drop test, under the action of a certain instantaneous impact force F, the target load moves in translation with a velocity of v along the direction of the force F, while accompanied by a self-rotation motion with a rotation axis of l r , and an angular velocity of ω, wherein v has three degrees of freedom, and l r has three degrees of freedom.

[0039] As Figure 4 During the separation process of the target load, the measuring camera collects multiple frames of images. With the target load center of mass O as the origin, the target coordinate system Ox is established. o y o z o , the target coordinate system is synchronized with the target load.

[0040] like Figure 1 , the target load translation parameter measurement method, the specific steps are as follows:

[0041] (1) Extract the imaging ellipse of the cooperative marker point in the measurement image. Specifically, the extraction method is the EDCircles method in the paper "EDCircles:Areal-time circledetector with a false detection control.2013,46(3),725-740", and sort the extracted image ellipses; calculate the common tangent point between any two ellipses. The extraction algorithm refers to the paper "UAV landing position and posture visual measurement method based on double circle features. Acta Aeronautica Sinica, 2005(03):344-348", and sort the extracted common tangent points. Calculate the target coordinate system of the i-th frame using the PnP algorithm and the common tangent point coordinates To the camera coordinate system O c -x c y c z c The rotation matrix and translation vectors

[0042] (2) The target load mass center point O is transformed by the rigid body transformation of the coordinate system. i (i.e. the origin of the target coordinate system) coordinates are converted to coordinates in the camera coordinate system

[0043]

[0044] (3) Using coordinates Fitting, we get the centroid fitting line L in the sense of least squares, which can be expressed as:

[0045] (2)

[0046] Among them, the unit vector n L =(m1,n1,p1) T represents the direction of the line L, and (x0, y0, z0) is the coordinate of any point on the line L. Therefore, the translation direction of the target load is n L =(m1,n1,p1) T .

[0047] (4) The target centroid point O i Project it onto the fitting line L to get the centroid projection point Its coordinates are The projection formula is as follows:

[0048]

[0049] (5) Calculate the target load's velocity v based on the center of mass projection point coordinates:

[0050]

[0051] Where ΔT represents the time interval between adjacent frames of the measurement camera, and m and n represent the number of frames.

[0052] Define the reference vector in the target coordinate system Through the rotation matrix Get the direction vector of the reference vector in the target coordinate system of the i-th frame in the camera coordinate system The calculation formula is as follows:

[0053]

[0054] Take the origin as the starting point of the vector and The end point of the rotation feature point is recorded as P i , whose coordinates are

[0055]

[0056] like Figure 1 , the target load rotation parameter measurement method is shown as follows Figure 5 As shown, let N0 = N, the specific steps are as follows:

[0057] (1) Construct a set S = {P i |i=1,2,···,N0}, and let S ′ =S;

[0058] (2) Through the set S ′ Points within the fitting space plane π: ax+by+cz-1=0;

[0059] (3) Calculate the set S ′ Point P inside i Distance d to plane π i ;

[0060] (4) Determine the distance d i With a certain value d0, if Make d i >d0, then from the set S ′ Eliminate Pi and let N0=N0-1, return to step (1);

[0061] (5) If d i ≤d0, use the set S ′ to fit the optimal equation of the plane π;

[0062] (6) Let the coordinates of the center C of the spatial trajectory circle in the target coordinate system be X C =(x0,y0,z0), according to the “median constraint - the median of the line connecting any two points in the set S ′ must pass through the center of the circle”, the following formula can be obtained:

[0063]

[0064] wherein,

[0065] The formula (6) can be obtained:

[0066]

[0067] wherein, and Similarly,

[0068] The formula (7) is written as a matrix form B·X C =L2, as follows:

[0069]

[0070] Let w=(a,b,c) T , according to the “center coplanar constraint - the center is located in the fitting plane π”, the following formula can be obtained:

[0071] w T ·X C -1=0

[0072] The spatial circle fitting optimization function is constructed as follows:

[0073] f(X C ,λ=B·X C -L2 2 +λ·(w T X C -1

[0074] Wherein, λ is the Lagrange multiplier.

[0075] Let f(X C ,λ be derived with respect to X C and λ, and let the derivative be 0, which can be obtained by arranging:

[0076]

[0077] Solving formula (9) we can get the three-dimensional coordinates of the center C, and the equation of the rotation axis is:

[0078] (7) Project the points in the set S onto the fitting plane π, P i The projection point on plane π is Its coordinates are Building a Collection Furthermore, project the center of the circle C to point C on plane π π , coordinate is X C,π ;

[0079] (8) Establish a plane coordinate system O in plane π d -x d y d , origin O d with C π Coincidence, O d x d Direction and Consistent, O d y d Direction and O d x d vertical and located in plane π, O d x d and O d y d The unit vector in the target coordinate system is denoted as n x and n y ;

[0080] (9) Set S π Points inside and point C π Dimensionality reduction, from three-dimensional spatial coordinates to two-dimensional coordinates in plane π and X C,d , where X C,d =(0,0) T , The conversion formula is as follows:

[0081]

[0082] (10) According to and X C,d Calculate the rotation angle θ and rotation speed ω of the target load:

[0083]

[0084] The above examples are provided only to describe processes of the present application and are not meant to limit the scope of the present application. The scope of the present application is defined by the appended claims. Various equivalent alterations and modifications which are thus within the spirit and scope of the present application will become apparent to those skilled in the art from the foregoing description.

Claims

1. A method for multi-parameter monocular vision synchronous measurement of load motion in a drop tower test, characterized in that, The method comprises the following steps: S1: calibrating the internal parameter matrix A and the distortion coefficient vector d of the measurement camera; calculating the center of mass position of the target load; using the calibrated monocular camera to collect N frames of measurement images during the movement of the target load, extracting visual feature points in the measurement images, and sorting and matching the visual feature points; S2: Establish a target coordinate system O-x on the target load with the target load centroid as the coordinate origin o y o z o , according to the visual feature points extracted in step S1, calculate the rotation matrix c -x c y c z c and translation vector of the target coordinate system to the camera coordinate system O S3: through a rotation matrix and a translation vector Convert the target load centroid to the camera coordinate system, fit the centroid trajectory straight line L using the centroid coordinates, and get the translation direction n of the target load; project the centroid coordinates onto the straight line L, and calculate the translation speed v of the target load using the centroid projection point; S4: By rotation matrix Obtain the rotation characteristic point P of the target load at different times i , using the rotation feature point P i Fit the target load rotation trajectory plane π; according to the perpendicular constraint and the center coplanar constraint, fit the target load rotation trajectory circle in the plane π, calculate the coordinate of the center C of the rotation trajectory circle; i After projecting the center C onto the plane π, the coordinates of the feature projection point and the center projection point are reduced in dimension, and the rotation angle θ and rotation speed ω of the target load are calculated using the reduced-dimensional coordinates; The step S4 comprises the following specific steps: S401: According to the rotation matrix The unit reference vector in the i-th frame target coordinate system O i -x o,i y o,i z o,i under Convert the unit vector in the camera coordinate system The end point of the vector as a rotation feature point P i , construct a rotation feature point set S = {P i |i = 1, 2, ···, N}. S402: Let the set S ′ =S, use set S ′ Fit the equation of plane π and calculate P i Distance d to plane π i ,like Make d i >d0, then from the set S ′ Eliminate P i , and refit the plane until it satisfies d i ≤d0; S403: According to the median line constraint and the circle center coplanar constraint, a space circle fitting optimization function is constructed, the extreme point of the optimization function is calculated, and the three-dimensional coordinates of the fitting circle center C and the spin rotation axis straight line equation are obtained, wherein: the median line constraint is defined as a set S ′ The median line of any two points in the set S passes through the circle center, and the circle center coplanar constraint is defined as the circle center being located in the fitting plane π. S404: Project the set S and the center C onto the plane π to obtain the set S π and the center C π , establish a plane coordinate system O in plane π d -x d y d , the set S π and the center C π Perform coordinate dimensionality reduction to obtain its d -x d y d Two-dimensional coordinates in the coordinate system and X C,d , the rotation angle θ and rotation angular velocity ω of the target load are calculated by the following formula: 。 2. The tower drop test load motion multi-parameter monocular vision synchronous measurement method according to claim 1, characterized in that: The step S1 comprises the following specific operation steps: S101: fixing the camera, placing a circular dot target in front of the camera, adjusting the position and direction of the circular dot target, collecting 10-15 target images with different poses using the measurement camera, and calibrating the internal parameter matrix A and the distortion coefficient vector d of the measurement camera; S102: calculating the center of mass position of the target load according to the structure and density information of the target load; S103: designing an array of cooperative marker dots on a certain plane of the target load, and collecting N frames of measurement images containing the array of cooperative marker dots using the calibrated measurement camera when the target load moves; S104: extracting the ellipses corresponding to the cooperative marker dots in the measurement images, calculating the common tangent point coordinates of the ellipses as the measurement feature points of the target load; S105: sorting the feature points in each extracted image, and matching the feature points in different frames of images according to the sorting results.

3. The tower drop test load motion multi-parameter monocular vision synchronous measurement method according to claim 1, characterized in that: The step S3 comprises the following specific operation steps: S301: According to the rotation matrix and the translation vector The target load centroid O i Convert the coordinates into the camera coordinate system S302: utilize the mass center point O of different time i fitting the space straight line L, obtaining the direction vector n of the straight line L under the camera coordinate system, and then the translation direction of the target load is n; S303: Project the centroid point O i Projecting onto the straight line L, get the projection point The coordinate vector is The coordinate of the projection point Calculate the translation speed v of the target load through the coordinate and time difference Wherein, ΔT represents the time interval between adjacent frames of the measurement camera, and m and n represent the frame numbers.

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