CN110722554A - Manipulator track editing and correcting method based on laser point cloud data - Google Patents
Manipulator track editing and correcting method based on laser point cloud data Download PDFInfo
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- CN110722554A CN110722554A CN201910824138.6A CN201910824138A CN110722554A CN 110722554 A CN110722554 A CN 110722554A CN 201910824138 A CN201910824138 A CN 201910824138A CN 110722554 A CN110722554 A CN 110722554A
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- track
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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Abstract
The invention provides a manipulator track editing and correcting method based on laser point cloud data, which comprises the following steps: s1: calculating a conversion relation matrix T between a coordinate system of a laser 3D contourgraph sensor and a manipulator coordinate system by using an arbitrary 3D calibration method; s2: scanning a workpiece by using a laser 3D contourgraph sensor to obtain 3D contour laser point cloud data of the workpiece; s3: converting the 3D contour laser point cloud data of the workpiece into a visual operation background, editing 8D track nodes in the visual operation background, and sequentially connecting a plurality of 8D track nodes to form an 8D track; s4: calculating the pose information of the workpiece from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose amount of the 8D track node to the pose information of the workpiece S5: and converting the 8D track into a manipulator 8D track under a manipulator coordinate system through a conversion relation matrix T.
Description
Technical Field
The invention relates to the field of machine automation, in particular to a manipulator track editing and correcting method based on laser point cloud data.
Background
At present, the programming modes commonly used by the manipulator are two types:
"robot off-line trajectory programming" is abbreviated as "off-line programming" which can extract contour features from an existing 3D model as a robot machining path, and the following disadvantages exist in the technology:
A. modeling software is required to be matched, and the offset, the attitude, the speed and the tool state of a specific position of a track cannot be flexibly adjusted;
B. the model is often different from the real object;
C. the real object can not be adjusted quickly when changed.
The 'teaching' is 'for short' for manipulator teaching ', and the specific teaching' method is that a manipulator operator moves a manipulator tool tip to a specific point by using a 'demonstrator' and then records the point in the manipulator, and a real object is used as a reference in the technology, so that the technology has the following defects:
A. the obtained track is taught to be a fixed track, secondary editing is not facilitated, and the method is only suitable for simple and repeated processing scenes;
B. the machining accuracy depends on the clamping accuracy of the clamp and brings additional clamp-related costs.
Disclosure of Invention
In order to solve the problems, the invention provides a manipulator track editing and correcting method based on laser point cloud data.
The invention is realized by the following technical scheme:
the invention provides a manipulator track editing and correcting method based on laser point cloud data, which comprises the following steps:
s1: calculating a conversion relation matrix T between a coordinate system of a laser 3D contourgraph sensor and a manipulator coordinate system by using an arbitrary 3D calibration method;
s2: scanning a workpiece by using a laser 3D contourgraph sensor to obtain 3D contour laser point cloud data of the workpiece;
s3: converting 3D contour laser point cloud data of a workpiece into a visual operation background, and editing 8D track nodes in the visual operation background, wherein each 8D track node contains 8 scalars of x, y, z, psi, theta, phi, spd and radius, wherein the x, y, z, psi, theta and phi are the pose quantities of the 8D track nodes, and a plurality of 8D track nodes are sequentially connected to form an 8D track;
s4: calculating the pose information of the workpiece from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose quantity of the 8D track node to the pose information of the workpiece; if the workpiece can be divided into a plurality of areas, calculating the pose information of each area from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose quantity corresponding to the 8D track nodes to the pose information of each area;
s5: converting the 8D track into a manipulator 8D track under a manipulator coordinate system through a conversion relation matrix T;
s6: the robot 8D trajectory is transferred into the robot.
Further, the pose information of the workpiece contains x1、y1、z1、ψ1、θ1And phi16 scalars.
Further, in step S4, if the pose information of the workpiece has anchor information, the pose amount of each 8D trajectory node in the 8D trajectory is updated by using a trajectory anchor algorithm.
Further, the specific process of step S5 is:
A. respectively converting the pose quantities x, y, z, psi, theta and phi of each 8D track node in the 8D track into matrixes;
B. the transformation relation matrix T is respectively multiplied by the matrix of the pose quantities of all the 8D track nodes;
C. and sequentially resolving the pose quantity of each matrix obtained in the step, and adding the pose quantity obtained by the resolution and the spd and radius of the original 8D track node to obtain the 8D track of the manipulator under the manipulator coordinate system.
The invention has the beneficial effects that:
1. the method for editing and correcting the manipulator track based on the laser point cloud data unifies the track editing of the manipulator to a platform, an editor of the track does not need to be familiar with the operation and control of the manipulator, the visual track editing greatly reduces the entry threshold of the manipulator track editing, and the real object characteristic anchoring function of track points enables the edited track to be directly applied to production.
2. The method for editing and correcting the manipulator track based on the laser point cloud data can be flexibly applied to various fields needing complicated manual track editing and can play a role in simplifying the problem and improving the efficiency.
Detailed Description
In order to more clearly and completely illustrate the technical solution of the present invention, the present invention is further described below.
The invention provides a manipulator track editing and correcting method based on laser point cloud data, which comprises the following steps:
s1: calculating a conversion relation matrix T between a coordinate system of a laser 3D contourgraph sensor and a manipulator coordinate system by using an arbitrary 3D calibration method;
s2: scanning a workpiece by using a laser 3D contourgraph sensor to obtain 3D contour laser point cloud data of the workpiece;
s3: converting 3D contour laser point cloud data of a workpiece into a visual operation background, and editing 8D track nodes in the visual operation background, wherein each 8D track node contains 8 scalars of x, y, z, psi, theta, phi, spd and radius, wherein the x, y, z, psi, theta and phi are the pose quantities of the 8D track nodes, and a plurality of 8D track nodes are sequentially connected to form an 8D track;
s4: calculating the pose information of the workpiece from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose quantity of the 8D track node to the pose information of the workpiece; if the workpiece can be divided into a plurality of areas, calculating the pose information of each area from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose quantity corresponding to the 8D track nodes to the pose information of each area;
s5: converting the 8D track into a manipulator 8D track under a manipulator coordinate system through a conversion relation matrix T;
s6: the robot 8D trajectory is transferred into the robot.
In the present embodiment, spd is the speed amount of 8D trajectory node switching; radius is expressed as a radius in 8D track node editing in a visual operation background and can be actually used for setting the state quantity of a manipulator carrying tool; when the pose information of the workpiece is subjected to any rigid body transformation, the pose quantity of the anchored 8D track node is also subjected to the same transformation, so that the spatial relationship between the pose of the 8D track node and the pose of the workpiece is kept unchanged; the manipulator track editing and correcting method based on the laser point cloud data enables tracks of manipulators to be edited and unified to a platform, an editor of the tracks does not need to be familiar with the operation and control of the manipulators, the entry threshold of the manipulator track editing is greatly reduced through visual track editing, and the real object characteristic anchoring function of track points enables the edited tracks to be directly applied to production; the manipulator track editing and correcting method based on the laser point cloud data can be flexibly applied to various fields needing complicated manual editing tracks, and can play a role in well simplifying problems and improving efficiency.
In the present embodiment, in step S1, the conversion relationship matrix T can be calculated according to the icp (iterative closed point) algorithm; in step S3, the 3D contour laser point cloud data of the workpiece is converted into a visual operation background in the form of a three-dimensional space point set or a polygon mesh.
Further, the pose information of the workpiece contains x1、y1、z1、ψ1、θ1And phi16 scalars.
In the present embodiment, in performing step S4, the attitude amounts x, y, z, ψ, θ, and Φ of the 8D locus node are respectively associated with the attitude information x of the workpiece1、y1、z1、ψ1、θ1And phi1Anchoring, i.e. determining a unique relationship; when the pose information of the workpiece is calculated from the 3D contour laser point cloud data, solving the translation amount of the pose information of the workpiece by using a median algorithm, wherein the median center of the workpiece is used as the center of the pose information of the workpiece: x is the number of1、y1And z1(ii) a And (3) jointly solving the rotation amount of the pose information of the workpiece by using a plane fitting algorithm, an edge extraction algorithm and a straight line fitting algorithm: psi1、θ1And phi1。
Further, in step S4, if the pose information of the workpiece has anchor information, the pose amount of each 8D trajectory node in the 8D trajectory is updated by using a trajectory anchor algorithm.
In this embodiment, the trajectory anchoring algorithm is detailed as follows: let the initial pose of the workpiece be expressed as a matrix A08D locusThe initial pose of the last 8D track node can be represented as a matrix B0Now, the position and attitude matrix of the workpiece is changed from A0Change is AtIf the matrix corresponding to the variation is M, then
MA0＝At
Equality two-sided simultaneous right-hand multiplication by A0 -Can obtain the product
M＝AtA0 -
According to the anchoring rule, it is known
Bt＝MB0
Namely, it is
Bt＝AtA0 -B0＝At(A0 -B0)
Thus, only the current A needs to be obtained when anchoring0 -B0That is, the position matrix of the workpiece can be changed to AtThe pose matrix B of the 8D track node is solved by applying the formulatTo further derive from the pose matrix BtAnd solving the pose quantity of the node.
Further, the specific process of step S5 is:
A. respectively converting the pose quantities x, y, z, psi, theta and phi of each 8D track node in the 8D track into matrixes;
B. the transformation relation matrix T is respectively multiplied by the matrix of the pose quantities of all the 8D track nodes;
C. and sequentially resolving the pose quantity of each matrix obtained in the step, and adding the pose quantity obtained by the resolution and the spd and radius of the original 8D track node to obtain the 8D track of the manipulator under the manipulator coordinate system.
In the present embodiment, after step S6, the robot executes the trajectory of the robot 8D.
Of course, the present invention may have other embodiments, and based on the embodiments, those skilled in the art can obtain other embodiments without any creative effort, and all of them are within the protection scope of the present invention.
Claims (4)
1. A manipulator track editing and correcting method based on laser point cloud data is characterized by comprising the following steps:
s1: calculating a conversion relation matrix T between a coordinate system of a laser 3D contourgraph sensor and a manipulator coordinate system by using an arbitrary 3D calibration method;
s2: scanning a workpiece by using a laser 3D contourgraph sensor to obtain 3D contour laser point cloud data of the workpiece;
s3: converting 3D contour laser point cloud data of a workpiece into a visual operation background, and editing 8D track nodes in the visual operation background, wherein each 8D track node contains 8 scalars of x, y, z, psi, theta, phi, spd and radius, wherein the x, y, z, psi, theta and phi are the pose quantities of the 8D track nodes, and a plurality of 8D track nodes are sequentially connected to form an 8D track;
s4: calculating the pose information of the workpiece from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose quantity of the 8D track node to the pose information of the workpiece; if the workpiece can be divided into a plurality of areas, calculating the pose information of each area from the 3D contour laser point cloud data by using any machine vision algorithm, and anchoring the pose quantity corresponding to the 8D track nodes to the pose information of each area;
s5: converting the 8D track into a manipulator 8D track under a manipulator coordinate system through a conversion relation matrix T;
s6: the robot 8D trajectory is transferred into the robot.
2. The method of claim 1, wherein the pose information of the workpiece comprises x1、y1、z1、ψ1、θ1And phi16 scalars.
3. The method for editing and correcting the trajectory of the manipulator based on the laser point cloud data of claim 1, wherein in step S4, if the pose information of the workpiece has anchor information, the pose amount of each 8D trajectory node in the 8D trajectory is updated by using a trajectory anchor algorithm.
4. The method for editing and correcting the trajectory of the manipulator based on the laser point cloud data of claim 1, wherein the specific process of step S5 is as follows:
A. respectively converting the pose quantities x, y, z, psi, theta and phi of each 8D track node in the 8D track into matrixes;
B. the transformation relation matrix T is respectively multiplied by the matrix of the pose quantities of all the 8D track nodes;
C. and sequentially resolving the pose quantity of each matrix obtained in the step, and adding the pose quantity obtained by the resolution and the spd and radius of the original 8D track node to obtain the 8D track of the manipulator under the manipulator coordinate system.
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