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A flexible seam detection t echnique. for robotic laser welding. (Shortened English version) Jorg Entzinger. Laser bundel. Seam to Weld. Laser Focus Lens. Camera lens. Video camera. Dichroic mirror. Laser diode. Laser Focus Lens. Presentation Structure. Introduction

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a flexible seam detection t echnique

A flexible seam detection technique

for robotic laser welding

(Shortened English version)

Jorg Entzinger

slide3

Laser bundel

Seam to Weld

slide4

Laser

Focus Lens

slide5

Camera lens

Video camera

Dichroic mirror

Laser diode

slide6

Laser

Focus Lens

presentation structure
Presentation Structure
  • Introduction
  • Lens & camera calibration
  • Image undistortion
  • Seam Detection
functions of the multifunctional welding head
Detect seams

Track & learn seams

Laser weld seams

Process control

Quality control

Functions of the Multifunctional Welding head
s p ecialities of this welding head
Specialities of this welding head
  • Multifunctionality

All needed technology is integrated in one machine

  • Compactness

Flexible in use for complex geometries

  • Lightweight

For higher accuracies with the use of robots

assignment
Assignment
  • Develop a system that can compensate for lens distortions
  • Develop a system to determine the exact position of the workpiece with respect to the welding head from camera images
distortion types
Distortion Types
  • Perspective distortions
  • Camera distortions (skew, non-squareness of pixels)
  • Lens distortions (radial: barrel/pincushion)
  • Noise (dust, bad focussing, CCD measurement noise)

Normal Perspective Skew Barrel Pincushion

program structure
C++

Read parameters

from file

Generate look-op table

of pixel displacements

Aquire camera image

Undistort image

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Parameter estimation

Write Params to File

Program Structure
program structure1
Program Structure

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Parameter estimation

Write Params to File

C++

Read parameters

from file

Generate look-op table

of pixel displacements

Aquire camera image

Undistort image

the calibration pattern
The calibration-pattern

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Estimate parameters

Write params to file

pictures of thecalibration pattern
Pictures of theCalibration-pattern

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Estimate parameters

Write params to file

identified keypoints
Identified Keypoints

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Estimate parameters

Write params to file

sorted keypoints
Sorted Keypoints

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Estimate parameters

Write params to file

parameter estimation 2
Parameter estimation (2)

Barrel Pincushion

or

estimation refinement
Estimation refinement

Homography was calculated without considering radial distortions

 Distortions are calculated from an inaccurate homography

 The estimations must be refined, all parameters are optimized at the same time

program structure2
Program Structure

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Parameter estimation

Write Params to File

C++

Read parameters

from file

Generate look-op table

of pixel displacements

Aquire camera image

Undistort image

program structure3
Program Structure

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Parameter estimation

Write Params to File

C++

Read parameters

from file

Generate look-op table

of pixel displacements

Aquire camera image

Undistort image

test result1
Test Result

Original Undistorted

simulated distortion test
Simulated Distortion Test

Original Undistorted

result
Result

Original Undistorted

amout of distortion
Amout of Distortion

Pixel movement in %

Position on image diagonal

programma structuur
Programma Structuur

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Parameter estimation

Write Params to File

C++

Read parameters

from file

Generate look-op table

of pixel displacements

Aquire camera image

Undistort image

program structure4
Program Structure

MATLAB

Make calibration pattern

Take pictures

Identify keypoints

Sort keypoints

Parameter estimation

Write Params to File

C++

Read parameters

from file

Generate look-op table

of pixel displacements

Aquire camera image

Undistort image

Determine seam location

Move Robot

world co rdinates
World Coördinates
  • How many millimeters in reality

is 10 pixels in the image?

  • If the image moves to the right, in what direction did the robot move?
  • Where is the camera

with respect to the welding spot?

thank you

Thank you

for your attention

Jorg Entzinger

aanbevelingen
Aanbevelingen
  • Pixel-millimeter schaling hoogte afhankelijk maken
  • Bepaling naad-positie minder afhankelijk maken van handmatige instellingen
  • Zorgen voor goede afhandeling als de naad dicht bij de kruising van de lijnen komt
  • Goede gebruikers-interface voor camera & lens calibration maken
camera lens distortions
Camera & Lens distortions
  • Perspective distortion
  • Skew distortion
  • Radial distortions (barrel & pincushion)
  • Noise

Normal Perspective Skew Barrel Pincushion

parameters schatten
Parameters schatten

Er worden subsets gemaakt van

Datapunten uit 4 plaatjes, bijvoorbeeld:

Subset 1 Subset 2 Subset 3 ...

Dataset 1 Dataset 2 Dataset 3

Dataset 2 Dataset 4 Dataset 5

Dataset 3 Dataset 6 Dataset 7

Dataset 4 Dataset 8 Dataset 8

Voor elke subset wordt een calibration

uitgevoerd

MATLAB

calibration patroon

maken

Foto’s nemen

Keypoints identificeren

Keypoints sorteren

Parameters schatten

Parameters naar

bestand schrijven

schatten van de parameters 2
Schatten van de Parameters (2)

Homografie (per plaatje): 8 DOFs

Plaatje afhankelijk: 6 DOFs

(3 rotatie en 3 translatie) -

Over voor schatting camera

parameters: 2 DOFs

Er zijn 5 camera afhankelijke parameters,

dus er is minstens 2½ plaatje nodig

meetfouten
Meetfouten

Y-fout [mm]

X-positie [mm]

Z-fout [mm]

X-positie [mm]

Totaal-fout [mm]

X-positie [mm]

a flexible seam detection t echnique1

A flexible seam detection technique

for robotic laser welding

Jorg Entzinger

dagplanning
Dagplanning

13:00 – 13:45 Presentatie

13:45 – 14:00 Vragen uit de zaal

Jorg & Examencommissie

14:00 – 14:30 Demonstratie in het lab

14:30 – 15:30 Ondervraging

Rest

14:00 – 15:30 Rondleiding door Niels en/of

Koffie/Thee in WB (Horst) kantine

Iedereen

15:30 – 16:00 Diploma-uitreiking & felicitatie (WB-Z109)

16:15 – 18:00 Borrel & Demonstraties in het Lab

(WB-Hal IV = Westhorst)

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