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A flexible seam detection technique for robotic laser welding (Shortened English version) Jorg Entzinger.

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Presentation on theme: "A flexible seam detection technique for robotic laser welding (Shortened English version) Jorg Entzinger."— Presentation transcript:

1 A flexible seam detection technique for robotic laser welding (Shortened English version) Jorg Entzinger

2 2

3 3 Seam to Weld Laser bundel

4 4 Laser Focus Lens

5 5 Laser diode Dichroic mirror Video camera Camera lens

6 6 Laser Focus Lens

7 7 Presentation Structure Introduction Lens & camera calibration Image undistortion Seam Detection

8 8 Functions of the Multifunctional Welding head Detect seams Track & learn seams Laser weld seams Process control Quality control Introduction Why Camera Calibration? How it is doneResultsPlanning Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

9 9 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 Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

10 10 Assignment 1.Develop a system that can compensate for lens distortions 2.Develop a system to determine the exact position of the workpiece with respect to the welding head from camera images Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

11 11 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 Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

12 12 C++ Read parameters from file Generate look-op table of pixel displacements Aquire camera image Undistort image Program Structure MATLAB Make calibration pattern Take pictures Identify keypoints Sort keypoints Parameter estimation Write Params to File Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

13 13 Program Structure Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies 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

14 14 The calibration-pattern MATLAB Make calibration pattern Take pictures Identify keypoints Sort keypoints Estimate parameters Write params to file Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

15 15 Pictures of theCalibration-pattern Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies MATLAB Make calibration pattern Take pictures Identify keypoints Sort keypoints Estimate parameters Write params to file

16 16 Identified Keypoints Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies MATLAB Make calibration pattern Take pictures Identify keypoints Sort keypoints Estimate parameters Write params to file

17 17 Sorted Keypoints Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies MATLAB Make calibration pattern Take pictures Identify keypoints Sort keypoints Estimate parameters Write params to file

18 18 Parameter estimation (1) Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies Perspective Camera

19 19 Parameter estimation (2) Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies Barrel Pincushion or

20 20 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 Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

21 21 Program Structure Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies 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

22 22 Program Structure Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies 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

23 23 Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies Undistortion

24 24 An Original (Distorted) Picture Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

25 25 Test Result Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

26 26 Test Result Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies Original Undistorted

27 27 Simulated Distortion Test Original Undistorted Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

28 28 Result Original Undistorted Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

29 29 Amout of Distortion Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies Pixel movement in % Position on image diagonal

30 30 Programma Structuur Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies 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

31 31 Program Structure Introduction Lens Distortions Calibration Procedure ProgramPlanning Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies C++ Read parameters from file Generate look-op table of pixel displacements Aquire camera image Undistort image Determine seam location Move Robot MATLAB Make calibration pattern Take pictures Identify keypoints Sort keypoints Parameter estimation Write Params to File

32 32 Changes in camera image due to a change of relative position Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

33 33 Changes in camera image due to a change of relative position Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

34 34 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? Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

35 35 Test objects Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

36 36 Following a seam Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

37 Thank you for your attention Jorg Entzinger

38 38

39 39 Rotatie Matrix

40 40 Rodrigues Parameters

41 41 Rotatie Matrix  Rodrigues Parameters

42 42 Schatten van de Parameters (1) Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies met

43 43 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 Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

44 44 Camera & Lens distortions Perspective distortion Skew distortion Radial distortions (barrel & pincushion) Noise Normal Perspective Skew Barrel Pincushion

45 45 Why Camera Calibration?

46 46 Detectie van Lijnen

47 47 Scheiden van Lijnen in het Kruis

48 48 Detectie van de Lasnaad

49 49 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

50 50 Parameter Schattingen Op Basis Van Meerdere Subsets RMS alfa f

51 51 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

52 52 Verstorings-gebied fotocamera

53 53 Experiment Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

54 54 Experiment Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies

55 55 Meetfouten Introduction Camera & lens calibration Image undistortion Seam detection & world coord. ResultsConclusies X-positie [mm] Y-fout [mm] Z-fout [mm] Totaal-fout [mm]

56 56

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59 A flexible seam detection technique for robotic laser welding Jorg Entzinger

60 60 Dagplanning 13:00 – 13:45Presentatie 13:45 – 14:00Vragen uit de zaal Jorg & Examencommissie 14:00 – 14:30Demonstratie in het lab 14:30 – 15:30Ondervraging Rest 14:00 – 15:30Rondleiding door Niels en/of Koffie/Thee in WB (Horst) kantine Iedereen 15:30 – 16:00Diploma-uitreiking & felicitatie (WB-Z109) 16:15 – 18:00Borrel & Demonstraties in het Lab (WB-Hal IV = Westhorst)

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