臺灣博碩士論文加值系統

本論文提出一套結合相機與雷射投影之非接觸3D測量系統，藉由追蹤以點雷射和線雷射在平面影像中的雷射投影，來獲取3D空間中的資訊，並利用手眼校正將相機的座標系轉為機械手臂座標系，供工業六軸機械手臂使用。本論文將系統運用在需要高精準度的電腦主機板記憶體插入任務上。測試結果顯示系統精準度 ±0.35mm，適用於現今大多數機械手臂的組裝任務。

This thesis presents a 3D measurement system combining webcam camera and laser projectors as a non-contacting method for fast robot operations. Two types of laser projector comprising the pointer laser and the line laser are used to obtain 3D information by tracking laser projection on image plane and then calculating its 3D positions in camera coordinate. The system is integrated to an industrial 6-axis robot arm with implementing the hand-eye calibration method so that the scanned 3D points from the camera coordinate can be transformed to the robot coordinate. The whole integration system has been tested on the socket insertion task that demands a high precision requirement. The result from exemplification indicated that system’s precision is and can satisfy many robot arm operated assembly tasks.

Abstract i
List of Figures v
List of Tables vii
CHAPTER ONE INTRODUCTION 1
1.1 Background 1
1.2 Motivation 1
1.3 Background Knowledge 2
1.3.1 3D Scanner 2
1.3.2 Introduction to Laser Scanner System 3
CHAPTER TWO DENSO ROBOT 5
2.1 Transformation Matrix 5
2.2 DENSO Robot’s DH Table 6
2.3 Direct Kinematics 7
2.4 Inverse Kinematics 9
2.5 End-Effector Kinematics-Screw Transformation 11
2.6 Velocity Jacobian 12
CHAPTER THREE NON-CONTACTING 3D MEASUREMENT SYSTEM 14
3.1 Camera Pinhole Model 14
3.2 Non-Contacting 3D Measurement System 15
3.2.1 System Setup 15
3.2.2 Laser Scanner System Using Line Laser 16
3.2.3 Range Finder System Using Pointer Laser 19
CHAPTER FOUR IMAGE PROCESSING 26
4.1 Camera Calibration 26
4.1.1 Zhang’s Method for Camera Calibration 26
4.1.2 Camera Intrinsic 27
4.1.3 Camera Extrinsic 28
4.1.4 Back Projecting 29
4.2 Hand-Eye Calibration 30
4.3 Laser Segmentation 32
4.3.1 Laser Projector and Laser Filter 32
4.3.2 Laser Segmentation by Adaptive Threshold 33
4.3.3 Thinning Operation 35
4.4 Edge Detection 38
4.5 Halconn 2D Shape-Based Matching 40
CHAPTER FIVE GUI SYSTEM 42
5.1 QT Creator 42
5.2 GUI System Using Qt Creator 42
CHAPTER SIX EXPERIMENT AND RESULTS 45
CHAPTER SEVEN CONCLUSION AND FUTURE WORKS 50
7.1 Conclusion 51
7.2 Applications 52
7.3 Future Works 52
References 54

[1]Marani, Roberto, Massimiliano Nitti, Grazia Cicirelli, Tiziana D'Orazio, and Ettore Stella. "High-Resolution Laser Scanning for Three-Dimensional Inspection of Drilling Tools." Advances in Mechanical Engineering 5 (2013): 620786.
[2] Lopez-Escogido, Daniel, and Adriano De Luca. "2-D high precision laser sensor for detecting small defects in PCBs." Electrical Engineering, Computing Science and Automatic Control (CCE), 2012 9th International Conference on. IEEE, 2012.
[3] Daniilidis, Konstantinos. "Hand-eye calibration using dual quaternions." The International Journal of Robotics Research 18.3 (1999): 286-298. [4] R. Gonzalez and R. Woods, “Digital Image Processing”, in Addison-Wesley Publishing Company, 1992, pp. 518 – 548.
[5] Shapiro, Linda, and R. Haralick. "Computer and robot vision." Reading: Addison Wesley 8 (1992).
[6] Davis, James, and Xing Chen. "A laser range scanner designed for minimum calibration complexity." 3-D Digital Imaging and Modeling, 2001. Proceedings. Third International Conference on. IEEE, 2001.
[7] Fernandez, J. C., et al. "An overview of lidar point cloud processing software." GEM Center Report No. Rep_2007-12-001, University of Florida(2007).
[8]Hiremagalur, Jagannath, et al. Creating standards and specifications for the use of laser scanning in caltrans projects. No. CA07-0964. 2007.
[9]Abdelmajid, Yezeed. "Investigation and comparison of 3D laser scanning software packages." (2012).
[10] Jean-Yves Bouguet, “Camera calibration toolbox for Matlab”:
http://www.vision.caltech.edu/bouguetj/calib_doc/
[11] Camera calibration OpenCV:
http://docs.opencv.org/2.4/doc/tutorials/calib3d/camera_calibration/camera_calibration.html
[12] Halconn Shape-Based Matching:
http://download.mvtec.com/halcon-9.0-solution-guide-ii-b-shape-based-matching.pdf