CN109373898B - Complex part pose estimation system and method based on three-dimensional measurement point cloud - Google Patents
Complex part pose estimation system and method based on three-dimensional measurement point cloud Download PDFInfo
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Abstract
The invention belongs to the field of automatic measurement, and particularly discloses a complex part pose estimation system and method based on three-dimensional measurement point cloud, which realize complex part pose estimation through the following steps: calibrating a conversion matrix between a tail end flange plate of the six-degree-of-freedom industrial robot and a measurement coordinate system of a grating type area array scanner; the six-degree-of-freedom industrial robot drives the grating type area array scanner to move so as to scan the workpiece to be measured, and then three-dimensional point cloud data of the workpiece to be measured are obtained; converting the three-dimensional point cloud data of the workpiece to be detected to a robot base coordinate system to obtain converted three-dimensional point cloud data; and matching the converted three-dimensional point cloud data with the three-dimensional design model of the workpiece to be detected to obtain the pose of the workpiece to be detected relative to the robot base coordinate system, thereby finishing the estimation of the pose of the complex part. The invention has wide measurement range, can realize the accurate measurement of multiple areas and complete appearance of the workpiece to be measured, and can accurately acquire the pose of the workpiece to be measured.
Description
Technical Field
The invention belongs to the field of automatic measurement, and particularly relates to a complex part pose estimation system and method based on three-dimensional measurement point cloud.
Background
Robot three-dimensional automatic measurement requires planning a complete collision-free path, and the planned path requires knowing the pose of the workpiece with respect to the robot base coordinate system. The traditional workpiece attitude estimation method comprises a manual alignment method, which depends on manual operation, has great randomness and inaccurate estimation; the method for acquiring the pose of the workpiece by using visual positioning is also applicable to workpieces with unobvious features and is complex in calculation.
The traditional measuring modes are complex, accurate workpiece poses are difficult to acquire, and subsequent path planning is deviated, especially when workpieces are huge, a workpiece coordinate system is difficult to acquire, so that large-amplitude deviation occurs in subsequent robot measuring point planning, and unexpected collision between a robot measuring system and the external environment is possibly caused.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a complex part pose estimation system and method based on three-dimensional measurement point cloud, which utilize a six-degree-of-freedom industrial robot to drive a grating type area array scanner to carry out local characteristic scanning on a measured workpiece, acquire point cloud data of key parts, convert the point cloud data into a robot base coordinate system through a matrix calibrated by hands and eyes to obtain new point cloud data, and then utilize a design model of the measured workpiece to be matched with the point cloud to acquire a conversion matrix from the design model to the point cloud data, wherein the conversion matrix is the pose of the measured workpiece relative to the robot base coordinate system.
In order to achieve the above object, according to one aspect of the present invention, a complex part pose estimation system based on three-dimensional measurement point cloud is provided, which includes a six-degree-of-freedom industrial robot, a grating type area array scanner, a measured workpiece, a marker point support frame, and a data processing upper computer, wherein:
the tail end of the six-degree-of-freedom industrial robot clamps the grating type area array scanner and is used for driving the grating type area array scanner to move so as to scan and measure a workpiece to be measured placed on the mark point support frame, blue light emitted by the grating type area array scanner covers the surface of the workpiece to be measured and mark points on the mark point support frame during measurement, and at least 3 public mark points which are not on the same straight line exist in the two-time measurement; the six-degree-of-freedom industrial robot is connected with the data processing upper computer so as to transmit the motion parameters of the six-degree-of-freedom industrial robot to the data processing upper computer in real time;
the grating type area array scanner is arranged at the tail end of the six-degree-of-freedom industrial robot and used for scanning and measuring a workpiece to be measured to obtain three-dimensional point cloud data of the workpiece to be measured, and the grating type area array scanner is connected with the data processing upper computer to transmit the measured data to the processing upper computer in real time;
the data processing upper computer is used for receiving the motion parameters of the six-degree-of-freedom industrial robot and the measurement data of the grating type area array scanner, and calculating to obtain the pose of the measured workpiece under the robot base coordinate system, so that the estimation of the pose of the complex part is completed.
As a further preferred, before measurement, the position relationship between the end flange of the six-degree-of-freedom industrial robot and the measurement coordinate system of the grating type area array scanner is obtained through hand-eye calibration.
More preferably, the distance between adjacent marking points on the marking point support is preferably 3cm to 4 cm.
Preferably, the six-degree-of-freedom industrial robot is connected with the data processing upper computer through a six-degree-of-freedom industrial robot controller.
Preferably, the grating type area array scanner is connected with a six-degree-of-freedom industrial robot controller to achieve synchronization of signal triggering and data acquisition.
According to another aspect of the invention, a complex part pose estimation method based on three-dimensional measurement point cloud is provided, which comprises the following steps:
s1 calibration conversion matrix between six-freedom-degree industrial robot tail end flange plate and grating type area array scanner measurement coordinate system
S2, the six-degree-of-freedom industrial robot drives the grating type area array scanner to move so as to scan the workpiece to be measured, and then three-dimensional point cloud data p of the workpiece to be measured is obtainedi(i＝1,2,...,s)；
S3, converting the three-dimensional point cloud data of the workpiece to be detected to a robot base coordinate system to obtain the converted three-dimensional point cloud data:
wherein the content of the first and second substances,
the pose of the robot is measured for the first time;
and S4, matching the converted three-dimensional point cloud data with the three-dimensional design model of the workpiece to be measured to obtain the pose of the workpiece to be measured relative to the robot base coordinate system, thereby finishing the estimation of the pose of the complex part.
Further preferably, in step S4, the pose of the workpiece to be measured with respect to the robot base coordinate system is obtained by the following method:
firstly, calculating a transformation matrix from point cloud to three-dimensional design model coordinate system after each matching is finished
Wherein the matching times are n;
then according to the conversion matrix T corresponding to each matchingkCalculating the pose of the measured workpiece under the robot base coordinate system
The result is obtained.
Generally, compared with the prior art, the above technical solution conceived by the present invention mainly has the following technical advantages:
1. the invention overcomes the defect that the traditional pose estimation method needs manual measurement, can utilize a six-degree-of-freedom industrial robot to drive a scanner to realize remote operation, acquire point cloud data and calculate the pose of a workpiece, is safe and reliable, cannot cause threat to operators, has wide measurement range, and can realize the accurate measurement of multiple regions and complete appearance of the workpiece to be measured.
2. The grating type area array scanner has an automatic splicing function based on the mark points, can avoid the splicing error of the point cloud measured by the scanner caused by the absolute positioning error of the robot, improves the precision of the measured point cloud, and realizes the splicing of the mark points by pasting the mark points on the periphery of the measured area of the workpiece to be measured and ensuring that at least three repeated mark points are observed under two adjacent visual angles in the measuring process, thereby ensuring that complete measured point cloud data are spliced.
3. The invention can solve the problem that manual measurement is difficult to obtain more accurate position parameters, particularly the acquisition of the rotation matrix R, and can more accurately acquire the pose of the workpiece to be measured by utilizing an accurate hand-eye matrix and a point cloud matching algorithm.
4. The invention has simple structure, can well solve the problem of the pose of the randomly placed workpiece relative to the pose of the robot base coordinate system, is applicable to pose estimation of the same type and has strong universality.
Drawings
Fig. 1 is a schematic structural diagram of a complex part pose estimation system based on a three-dimensional measurement point cloud according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a three-dimensional feature of an exemplary workpiece;
FIG. 3 is a schematic diagram of the pose relationship between the scanner and the end flange of the robot and the acquisition of a three-dimensional point cloud, where OBXYZ is the robot-based coordinate system { B }, OEXYZ is the robot end flange coordinate system { E }, OSXYZ is the scanner measurement coordinate system S;
FIG. 4 is a schematic diagram of a point cloud matching process, where xyz is the coordinate system of the three-dimensional measurement point cloud, x0y0z0T is a transformation matrix from a coordinate system of the three-dimensional measurement point cloud to the model coordinate system.
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. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, a complex part pose estimation system based on three-dimensional measurement point cloud according to an embodiment of the present invention includes a six-degree-of-freedom industrial robot 100, a workpiece 200 to be measured, a grating type area array scanner 300, a marker point support 400, and a data processing upper computer 500.
The end of the six-degree-of-freedom industrial robot 100 clamps the grating type area array scanner 300, the six-degree-of-freedom industrial robot 100 moves in a working space according to a certain track to drive the grating type area array scanner 300 to move, the grating type area array scanner 300 scans and measures a measured workpiece 200 placed on a mark point support frame 400, during measurement, blue light emitted by the grating type area array scanner 300 needs to be ensured to cover the surface of the measured workpiece and a part of mark points on the mark point support frame, and at least 3 public mark points which are not on the same straight line need to be ensured to exist during two times of measurement, so as to be used for splicing point clouds; the six-degree-of-freedom industrial robot 100 is connected to the data processing upper computer 500, so that the motion parameters (including the position, attitude, motion state, and other parameters) of the six-degree-of-freedom industrial robot 100 are transmitted to the data processing upper computer 500 in real time.
The grating type area array scanner 300 is installed at the end of the six-degree-of-freedom industrial robot 100, scans and measures a region to be measured of a workpiece to be measured under the driving of the six-degree-of-freedom industrial robot 100 to obtain the appearance point cloud of the workpiece, and the grating type area array scanner 300 is also connected with the data processing upper computer 500 to transmit three-dimensional point cloud data obtained through measurement to the processing upper computer 500 in real time. The testing principle of the grating type area array scanner 300 is that a binocular stereo vision three-dimensional measurement technology based on a triangulation principle is adopted, a reference grating with different phase differences is projected to a measured object through the scanner, a dual camera is used for collecting deformed grating images modulated by the surface of the object from two visual angles, then the phase value of each pixel point is calculated by using the deformed grating, the three-dimensional point cloud coordinate of the object is calculated according to the phase value, and the grating type area array scanner is adopted for obtaining the three-dimensional point cloud data of the measured workpiece. Specifically, the grating type area array scanner communicates with the upper computer data processing software through the switch 700 to complete the collection and transmission of point cloud data, and the grating type area array scanner may adopt, for example, ato Compact Scan of germany Gom company, and PowerScan of the world's view-only technology.
The data processing upper computer 500 is used for receiving the motion parameters of the six-degree-of-freedom industrial robot 100 and the measurement data of the grating type area array scanner 300, and calculating to obtain the pose of the measured workpiece under the robot base coordinate system, so as to complete the estimation of the pose of the complex part. The upper computer data processing software in the data processing upper computer 500 has the functions of point cloud data acquisition, point cloud splicing, point cloud simplification, point cloud position conversion, point cloud-design model matching and the like, and can realize coordinate conversion (conversion to a six-degree-of-freedom industrial robot base coordinate system) and point cloud matching functions based on measured point cloud, so that the relative pose of the measured workpiece relative to the six-degree-of-freedom industrial robot base coordinate system is output, namely the pose of the measured workpiece under the robot base coordinate system is calculated according to the received motion parameters of the six-degree-of-freedom industrial robot 100 and the measurement data of the grating type area array scanner 300, and the pose is obtained.
Wherein, the point cloud data acquisition is to acquire the coordinate p of the point on the measured workpiece under the measurement coordinate system of the grating type area array scanner by utilizing the stereo vision three-dimensional measurement technologyi(i 1, 2.., r.., s); the point cloud splicing is to splice the point clouds of 2 nd, 3 rd, … th and s th into the point cloud of 1 st by utilizing two point clouds before and after the mark point splicing measurement, and the total point cloud coordinate obtained in the way represents the position of a measurement coordinate system of the grating type area array scanner when the six-degree-of-freedom industrial robot measures the point clouds for the first time; point cloud simplification is to uniformly sample large-scale measurement point cloud initially measured by a robot optical measurement system, reduce the data scale and improve the data processing and calculating efficiency; the point cloud position conversion is carried out according to the relative pose between the grating type area array scanner and the end flange plate of the six-degree-of-freedom industrial robot
Pose of robot tail end flange plate relative to robot base coordinate system when robot measures point for the first time
And measuring the obtained point cloud pi(i＝1,2,...,r,...,s) By means of a calculation formula
Converting the coordinate system into a six-degree-of-freedom industrial robot base coordinate system; the point cloud-design model matching is to match and align the point cloud converted into the six-degree-of-freedom industrial robot base coordinate system and the design model to the same coordinate system so as to obtain a conversion matrix, wherein the conversion matrix is the pose of the workpiece to be measured in the robot base coordinate system.
The positional relationship between the end flange of the six-degree-of-freedom industrial robot 100 and the measurement coordinate system of the grating type area array scanner 300 before measurement is obtained by hand-eye calibration, which is the prior art and is not described herein again. In the process of acquiring the point cloud of the workpiece to be measured 200, the blue light of the grating type area array scanner 300 covers the workpiece and part of the mark points, so that the subsequent point cloud can be spliced.
Specifically, the six-degree-of-freedom industrial robot 100 is connected with the data processing upper computer 500 through the six-degree-of-freedom industrial robot controller 600, the grating type area array scanner 300 is connected with the six-degree-of-freedom industrial robot controller 600, and signal triggering of upper computer software and synchronization of part point cloud data acquisition are achieved through control of the six-degree-of-freedom industrial robot controller 600.
The six-degree-of-freedom industrial robot 100 and the grating type area array scanner 300 are connected to the same data processing upper computer 500, pose parameters including angles of six axes and end positions of the robot during first measurement are recorded in the measurement process, and measurement data are synchronized to the data processing upper computer 500.
The height of the mark point support frame cannot be larger than the lowest height of the measured workpiece 200 during assembly, so that the point cloud of the measured workpiece is not influenced, the subsequent point cloud matching process is not interfered, meanwhile, the distance between the mark points is required to be 3 cm-4 cm, and the requirements that the point clouds measured in two times can be spliced and the mark points cannot be too many in one measuring range are met.
In actual work, firstly, the six-degree-of-freedom industrial robot, the area array scanner and the upper computer processing software need to be ensured to be in an open state, and the robot is controlledThe demonstrator controls the actual measurement posture of the robot, the measurement points are required to meet the measurement requirements, and the two images are required to contain at least 3 mark points which are not on the same straight line by the two-time measurement, so that the point cloud splicing is completed. After the acquisition of the measured point cloud data is finished, the measured point cloud is simplified by utilizing upper computer data processing software for improving the point cloud quality and reducing the data volume, hand-eye calibration parameters and the measurement pose of a first robot are input, the measured point cloud is converted into a robot base coordinate system, then point cloud-design model matching can be carried out, the point cloud model is matched into a design model coordinate system, and simultaneously, a conversion matrix T during each time of point cloud matching is recordedkAfter matching is completed, calculation is performed
The pose of the measured part to be solved relative to the six-degree-of-freedom industrial robot coordinate system is obtained.
The invention discloses a complex part pose estimation system based on three-dimensional measurement point cloud, which is used for estimating the pose of a complex part, and the basic idea is to obtain a conversion matrix of a grating type area array scanner and a six-degree-of-freedom industrial robot through hand-eye calibration, convert the workpiece measurement point cloud below a base coordinate system of the six-degree-of-freedom industrial robot, and match the point cloud with a workpiece three-dimensional design model through three-dimensional point cloud matching to obtain the conversion matrix, wherein the method specifically comprises the following steps:
s1 calibration conversion matrix between six-freedom-degree industrial robot tail end flange plate and grating type area array scanner measurement coordinate system
Wherein, R is a rotation matrix of the measurement coordinate system of the grating type area array scanner relative to the end flange of the six-degree-of-freedom industrial robot, t is a translation matrix of the measurement coordinate system of the grating type area array scanner relative to the end flange of the six-degree-of-freedom industrial robot, and the calibration is specifically performed by adopting hand-eye calibration, which is the prior art and is not repeated herein;
s2 driving grating by six-degree-of-freedom industrial robotThe surface array scanner moves to scan the workpiece to be measured, and then three-dimensional point cloud data p of the workpiece to be measured is obtainedi(i 1, 2., r., s), that is, three-dimensional point cloud data of the workpiece to be measured is obtained by a grating type area array scanner, which is the prior art and is not described herein again;
s3, converting the three-dimensional point cloud data of the workpiece to be detected to a robot base coordinate system to obtain the converted three-dimensional point cloud data:
wherein the content of the first and second substances,
the pose of the robot during the first measurement, namely the conversion pose from a flange plate at the tail end of the robot to a robot base coordinate system during the first measurement, can be obtained by calculation according to the motion parameters of the robot, and T is a conversion matrix from a connecting rod j-1 of the robot to a connecting rod j;
s4, matching the converted three-dimensional point cloud data with the three-dimensional design model of the workpiece to be measured to obtain the pose of the workpiece to be measured relative to the robot base coordinate system, thereby completing the estimation of the pose of the complex part, specifically, calculating the conversion matrix from the point cloud to the three-dimensional design model coordinate system after each matching is completed through the ICP matching algorithm
Setting the matching times as n, and then matching the corresponding transformation matrix T according to each timekCalculating the pose of the measured workpiece under the robot base coordinate system
The result is obtained.
The point cloud of the three-dimensional design model of the workpiece to be measured is assumed to be Q, and comprises the point cloud Qi(i 1, 2.. a., l.) P represents the converted three-dimensional point cloud data, including the point cloudBpi(i＝1,2,...,r,...,s)，TkThe solution of (c) is as follows:
s41 pairs all points in PBpiSearching the closest point Q corresponding to each point from QiCalculating the centroid muP、μQAnd difference of coordinates
S42 calculates a 3 × 3 order covariance matrix H from the set of points P, Q:
wherein HijRepresents the ith row and jth column elements of the matrix H;
s43 constructs a 4 × 4 order symmetric matrix W from H:
s44, calculating the eigenvalue of matrix W, and extracting the eigenvector corresponding to the maximum eigenvalue
And further solving a rotation matrix R and a translation matrix t:
t＝μQ-R×μP
further, the following is obtained:
obtaining a transformation matrix TkThen, using TkSolving for pi(i 1, 2.. r.. s.) matched position pi′，pi′＝Tk×piUpdating p at next matchi＝pi', then repeating the steps S41-S44 to match n times, thereby improving the matching precision, and then converting the matrix T according to each timekCalculating the pose of the measured workpiece under the robot base coordinate system
Is obtained, wherein T is1I.e. the transformation matrix, T, obtained in the first matching2I.e. the transformation matrix obtained in the second matching, and so on, TnI.e. the transformation matrix obtained at the n-th matching.
The method can estimate the pose of a sealing surface flange sample of a certain model, skillfully acquire the pose of a workpiece in a robot base coordinate system after a series of coordinate transformation is carried out on measured three-dimensional point cloud data, and can carry out subsequent path planning and simulation on the robot after the pose is acquired.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (4)
1. The utility model provides a complicated part position appearance estimation system based on three-dimensional measurement point cloud, its characterized in that includes six degree of freedom industrial robot (100), grating formula area array scanner (300), by survey work piece (200), mark point support frame (400) and data processing host computer (500), wherein:
the tail end of the six-degree-of-freedom industrial robot (100) clamps the grating type area array scanner (300) and is used for driving the grating type area array scanner (300) to move to scan and measure a workpiece (200) to be measured placed on the mark point support frame (400), blue light emitted by the grating type area array scanner (300) covers the surface of the workpiece to be measured and mark points on the mark point support frame during measurement, at least 3 public mark points which are not on the same straight line exist in the two previous and later measurements, and the distance between adjacent mark points on the mark point support frame (400) is 3-4 cm; the six-degree-of-freedom industrial robot (100) is connected with a data processing upper computer (500) through a six-degree-of-freedom industrial robot controller (600) so as to transmit the motion parameters of the six-degree-of-freedom industrial robot (100) to the data processing upper computer (500) in real time;
the grating type area array scanner (300) is arranged at the tail end of the six-degree-of-freedom industrial robot (100) and used for scanning and measuring a workpiece to be measured (200) to obtain three-dimensional point cloud data of the workpiece to be measured, and the grating type area array scanner (300) is connected with the data processing upper computer (500) to transmit the measurement data to the processing upper computer (500) in real time; the grating type area array scanner (300) is connected with a six-degree-of-freedom industrial robot controller (600) so as to realize the synchronization of the signal triggering of a data processing upper computer and the data acquisition of the grating type area array scanner;
the data processing upper computer (500) is used for receiving the motion parameters of the six-degree-of-freedom industrial robot (100) and the measurement data of the grating type area array scanner (300), and calculating to obtain the pose of the measured workpiece under the robot base coordinate system, so that the estimation of the pose of the complex part is completed.
2. The complex part pose estimation system based on three-dimensional measurement point cloud as claimed in claim 1, characterized in that the position relation between the end flange of the six-degree-of-freedom industrial robot (100) and the measurement coordinate system of the grating type area array scanner (300) is obtained by hand-eye calibration before measurement.
3. A complex part pose estimation method based on three-dimensional measurement point cloud is characterized by being carried out by the system of claim 1 or 2, and comprising the following steps:
s1 calibration conversion matrix between six-freedom-degree industrial robot tail end flange plate and grating type area array scanner measurement coordinate system
Wherein R is a rotation matrix of a measurement coordinate system of the grating type area array scanner relative to a tail end flange plate of the six-degree-of-freedom industrial robot, and t is a translation matrix of the measurement coordinate system of the grating type area array scanner relative to the tail end flange plate of the six-degree-of-freedom industrial robot;
s2, the six-degree-of-freedom industrial robot drives the grating type area array scanner to move so as to scan the workpiece to be measured, and then three-dimensional point cloud data p of the workpiece to be measured is obtainedi，i＝1,2,...,s；
S3, converting the three-dimensional point cloud data of the workpiece to be detected to a robot base coordinate system to obtain the converted three-dimensional point cloud data:
wherein the content of the first and second substances,
the pose of the robot is measured for the first time;
and S4, matching the converted three-dimensional point cloud data with the three-dimensional design model of the workpiece to be measured to obtain the pose of the workpiece to be measured relative to the robot base coordinate system, thereby finishing the estimation of the pose of the complex part.
4. The method for estimating the pose of a complex part based on three-dimensional measurement point cloud according to claim 3, wherein the pose of the measured workpiece relative to the robot base coordinate system is obtained in step S4 by adopting the following method:
firstly, calculating a transformation matrix from point cloud to three-dimensional design model coordinate system after each matching is finished
Wherein the matching times are n;
then according to the conversion matrix T corresponding to each matchingkCalculating the pose of the measured workpiece under the robot base coordinate system
The result is obtained.
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Application publication date: 20190222 Assignee: WUHAN POWER3D TECHNOLOGY Ltd. Assignor: HUAZHONG University OF SCIENCE AND TECHNOLOGY Contract record no.: X2022420000110 Denomination of invention: A pose estimation system and method for complex parts based on 3d measurement point cloud Granted publication date: 20200710 License type: Common License Record date: 20220930 |