CN110722554B - 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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- CN110722554B CN110722554B CN201910824138.6A CN201910824138A CN110722554B CN 110722554 B CN110722554 B CN 110722554B CN 201910824138 A CN201910824138 A CN 201910824138A CN 110722554 B CN110722554 B CN 110722554B
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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 profiler sensor and a manipulator coordinate system by using an arbitrary 3D calibration method; s2: scanning the workpiece by using a laser 3D profiler sensor to obtain 3D profile 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 pose information of the workpiece from the 3D profile laser point cloud data using an arbitrary machine vision algorithm, anchoring the pose amount of the 8D trajectory 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
There are two common programming modes for manipulators:
the technology has the following defects that the offline track programming of the manipulator is abbreviated as offline programming, and the offline programming can extract outline features from the existing 3D model to serve as a manipulator processing path:
A. tool states of offset, gesture, speed and specific positions of tracks can not be flexibly adjusted due to cooperation of modeling software;
B. the model is often different from the real object;
C. the real object can not be quickly adjusted when being changed.
The specific method of the teaching of the manipulator is that a manipulator operator moves the tip of a manipulator tool to a specific point position by using a demonstrator and then records the point position into the manipulator, and the technology uses a real object as a reference and has the following defects:
A. the track obtained by teaching is a fixed track and is not beneficial to secondary editing, and is only suitable for simple 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 above problems, the present 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 profiler sensor and a manipulator coordinate system by using an arbitrary 3D calibration method;
s2: scanning the workpiece by using a laser 3D profiler sensor to obtain 3D profile laser point cloud data of the workpiece;
s3: converting 3D profile laser point cloud data of a workpiece into a visual operation background, editing 8D track nodes in the visual operation background, wherein each 8D track node contains 8 scalar quantities of x, y, z, psi, theta, phi, spd and radius, wherein x, y, z, psi, theta and phi are pose quantities of the 8D track nodes, and the 8D track nodes are sequentially connected to form an 8D track;
s4: calculating 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 split into a plurality of areas, calculating pose information of each area from 3D contour laser point cloud data by using any machine vision algorithm, and anchoring pose quantity of a corresponding 8D track node 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 manipulator 8D trajectory is transferred into the manipulator.
Further, the pose information of the workpiece contains x 1 、y 1 、z 1 、ψ 1 、θ 1 And phi 1 6 scalar quantities.
Further, in step S4, if the pose information of the workpiece already has the anchor information, the pose amount of each 8D track node in the 8D track is updated by using the track anchor algorithm.
Further, the specific process of step S5 is as follows:
A. respectively converting pose quantities x, y, z, psi, theta and phi of all 8D track nodes in the 8D track into matrixes;
B. multiplying the transformation relation matrix T by the matrix of the pose quantity of all 8D track nodes respectively;
C. and sequentially resolving the pose quantity of each matrix obtained in the step, and adding spd and radius of the original 8D track node to the pose quantity obtained by resolving to obtain the 8D track of the manipulator in the manipulator coordinate system.
The invention has the beneficial effects that:
1. according to the manipulator track editing and correcting method based on the laser point cloud data, track editing of the manipulator is unified to one platform, a track editor does not need to be familiar with operation of the manipulator, visual track editing greatly reduces entrance thresholds of the track editing of the manipulator, and the physical characteristic anchoring function of the track points enables the edited track to be directly applied to production.
2. The manipulator track editing and correcting method based on the laser point cloud data can be flexibly applied to various occasions needing complex manual track editing, and can play a role in well simplifying problems and improving efficiency.
Detailed Description
The present invention will be further described in the following for a more clear and complete description of the technical solution of the present invention.
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 profiler sensor and a manipulator coordinate system by using an arbitrary 3D calibration method;
s2: scanning the workpiece by using a laser 3D profiler sensor to obtain 3D profile laser point cloud data of the workpiece;
s3: converting 3D profile laser point cloud data of a workpiece into a visual operation background, editing 8D track nodes in the visual operation background, wherein each 8D track node contains 8 scalar quantities of x, y, z, psi, theta, phi, spd and radius, wherein x, y, z, psi, theta and phi are pose quantities of the 8D track nodes, and the 8D track nodes are sequentially connected to form an 8D track;
s4: calculating 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 split into a plurality of areas, calculating pose information of each area from 3D contour laser point cloud data by using any machine vision algorithm, and anchoring pose quantity of a corresponding 8D track node 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 manipulator 8D trajectory is transferred into the manipulator.
In this embodiment, spd is the speed amount of 8D trace node switching; radius is expressed as a radius in 8D track node editing in a visual operation background, and can be practically 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 amount of the anchored 8D track node is subjected to the same transformation, so that the spatial relationship between the 8D track node pose and the workpiece pose is kept unchanged; according to the manipulator track editing and correcting method based on the laser point cloud data, track editing of the manipulator is unified to one platform, a track editor does not need to be familiar with the operation of the manipulator, the visual track editing greatly reduces the entrance threshold of the manipulator track editing, and the physical characteristic anchoring function of the track points enables the edited track 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 occasions requiring complex manual track editing, and can play a role in well simplifying problems and improving efficiency.
In the present embodiment, in step S1, the conversion relation matrix T can be calculated according to the ICP (Iterative Closest 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 spatial point set, a polygonal mesh.
Further, the pose information of the workpiece contains x 1 、y 1 、z 1 、ψ 1 、θ 1 And phi 1 6 scalar quantities.
In the present embodiment, in the step S4, the pose amounts x, y, z, ψ, θ, and Φ of the 8D trajectory nodes are respectively equal to the pose information x of the workpiece 1 、y 1 、z 1 、ψ 1 、θ 1 And phi 1 Anchoring, i.e. determining a unique relationship; when pose information of a workpiece is calculated from 3D contour laser point cloud data, a median center of the workpiece is solved by using a median algorithm to serve as translation amount of the pose information of the workpiece: x is x 1 、y 1 And z 1 The method comprises the steps of carrying out a first treatment on the surface of the And (3) jointly solving the rotation quantity of the pose information of the workpiece by using a plane fitting algorithm, an edge extraction algorithm and a linear fitting algorithm: psi phi type 1 、θ 1 And phi 1 。
Further, in step S4, if the pose information of the workpiece already has the anchor information, the pose amount of each 8D track node in the 8D track is updated by using the track anchor algorithm.
In this embodiment, the trajectory anchoring algorithm is described in detail as: let the initial pose of the workpiece be represented as matrix A 0 The initial pose of an 8D track node on an 8D track can be represented as a matrix B 0 Now, as the pose of the workpiece is changed, the pose matrix of the workpiece is represented by A 0 Change to A t Assuming that the matrix corresponding to the change is M
MA 0 ＝A t
Equality of both sides simultaneously right multiply A 0 - Is available in the form of
M＝A t A 0 -
According to the anchoring rule, it can be known that
B t ＝MB 0
I.e.
B t ＝A t A 0 - B 0 ＝A t (A 0 - B 0 )
Thus, only the current A is needed for anchoring 0 - B 0 Can change the pose matrix of the workpiece to A t Solving pose matrix B of 8D track node by using the formula t Thereby further from the pose matrix B t Solution calculationThe pose of the node.
Further, the specific process of step S5 is as follows:
A. respectively converting pose quantities x, y, z, psi, theta and phi of all 8D track nodes in the 8D track into matrixes;
B. multiplying the transformation relation matrix T by the matrix of the pose quantity of all 8D track nodes respectively;
C. and sequentially resolving the pose quantity of each matrix obtained in the step, and adding spd and radius of the original 8D track node to the pose quantity obtained by resolving to obtain the 8D track of the manipulator in the manipulator coordinate system.
In the present embodiment, after step S6, the robot performs the robot 8D trajectory.
Of course, the present invention can be implemented in various other embodiments, and based on this embodiment, those skilled in the art can obtain other embodiments without any inventive effort, which fall within the scope of the present invention.
Claims (4)
1. The manipulator track editing and correcting method based on the laser point cloud data is characterized by comprising the following steps of:
s1: calculating a conversion relation matrix T between a coordinate system of a laser 3D profiler sensor and a manipulator coordinate system by using an arbitrary 3D calibration method;
s2: scanning the workpiece by using a laser 3D profiler sensor to obtain 3D profile laser point cloud data of the workpiece;
s3: converting 3D profile laser point cloud data of a workpiece into a visual operation background, editing 8D track nodes in the visual operation background, wherein each 8D track node contains 8 scalar quantities of x, y, z, psi, theta, phi, spd and radius, wherein x, y, z, psi, theta and phi are pose quantities of the 8D track nodes, and the 8D track nodes are sequentially connected to form an 8D track;
s4: calculating 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 split into a plurality of areas, calculating pose information of each area from 3D contour laser point cloud data by using any machine vision algorithm, and anchoring pose quantity of a corresponding 8D track node 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: transmitting the 8D track of the manipulator into the manipulator;
in step S3, converting the 3D contour laser point cloud data of the workpiece into a visual operation background in the form of a three-dimensional space point set and a polygonal grid;
in the step S4, the pose amounts x, y, z, psi, theta and phi of the 8D track nodes are respectively matched with the pose information x of the workpiece 1 、y 1 、z 1 、ψ 1 、θ 1 And phi 1 Anchoring, i.e. determining a unique relationship; when pose information of a workpiece is calculated from 3D contour laser point cloud data, a median center of the workpiece is solved by using a median algorithm to serve as translation amount of the pose information of the workpiece: x is x 1 、y 1 And z 1 The method comprises the steps of carrying out a first treatment on the surface of the And (3) jointly solving the rotation quantity of the pose information of the workpiece by using a plane fitting algorithm, an edge extraction algorithm and a linear fitting algorithm: psi phi type 1 、θ 1 And phi 1 。
2. The method for editing and correcting a trajectory of a robot based on laser point cloud data as claimed in claim 1, wherein the pose information of the workpiece contains x 1 、y 1 、z 1 、ψ 1 、θ 1 And phi 1 6 scalar quantities.
3. The method for editing and correcting a manipulator track based on laser point cloud data according to claim 1, wherein in step S4, if the pose information of the workpiece has anchor information, the pose amount of each 8D track node in the 8D track is updated by using a track anchor algorithm.
4. The method for editing and correcting the track of the manipulator based on the laser point cloud data according to claim 1, wherein the specific process of step S5 is as follows:
A. respectively converting pose quantities x, y, z, psi, theta and phi of all 8D track nodes in the 8D track into matrixes;
B. multiplying the transformation relation matrix T by the matrix of the pose quantity of all 8D track nodes respectively;
C. and sequentially resolving the pose quantity of each matrix obtained in the step, and adding spd and radius of the original 8D track node to the pose quantity obtained by resolving to obtain the 8D track of the manipulator in the manipulator coordinate system.
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| CN101791801B (en) * | 2010-01-15 | 2012-06-06 | 广东工业大学 | Industrial robot motion planning and performance testing system and implementation method thereof |
| CN103085072B (en) * | 2013-03-11 | 2014-10-29 | 南京埃斯顿机器人工程有限公司 | Method for achieving industrial robot off-line programming based on three-dimensional modeling software |
| CN104841593B (en) * | 2015-05-29 | 2017-04-19 | 希美埃（芜湖）机器人技术有限公司 | Control method of robot automatic spraying system |
| CN107127755B (en) * | 2017-05-12 | 2023-12-08 | 华南理工大学 | Real-time acquisition device of three-dimensional point cloud and robot polishing track planning method |
| CN107901039B (en) * | 2017-11-13 | 2020-11-13 | 浙江工业大学 | Python-based desktop-level robot offline programming simulation system |
| CN108161936B (en) * | 2017-12-26 | 2020-06-30 | 中科新松有限公司 | Optimized robot calibration method and device |
| CN108582071B (en) * | 2018-04-26 | 2020-09-08 | 华中科技大学 | Industrial robot programming track diagnosis and speed optimization method |
| CN109605157B (en) * | 2018-11-30 | 2019-11-12 | 华中科技大学 | A kind of robot deburred method based on 3D laser scanner |
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