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研究生： Zelalem Abay Abebe
Zelalem - Abay Abebe
論文名稱： Robotized Spray Painting Trajectory Generation and Implementation for Bicycle-frame based on 3D Point Cloud Data
Robotized Spray Painting Trajectory Generation and Implementation for Bicycle-frame based on 3D Point Cloud Data
指導教授： 林其禹
Chyi-Yeu Lin
口試委員: 邱士軒
Shih-Hsuan Chiu
林紀穎
Chi-Ying Lin
學位類別： 碩士
Master
系所名稱： 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年： 2014
畢業學年度： 102
語文別： 英文
論文頁數： 63
中文關鍵詞： 機械手臂(自由度: 6 &自由度: 2) 、噴塗 、追蹤與路徑規劃 、讀取曲線骨架 、KinectFusion 、機械手臂系統
外文關鍵詞： Manipulator (6DOF and 2DOF), Spray Painting, Trajectory and Path Planning, Curve-Skeleton Extraction, KinectFusion, Robot Feeder System
相關次數： 點閱：191  下載：5 
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    • 使用教導盒透過典型的教導方式來設定工業型機器人的運動軌跡是一件繁瑣、耗時且須具備相當技術基礎的任務。本論文提出了基於三維點雲數據的機器人噴塗系統來產生比傳統教學方法更靈活且有效的機器人程序定義和控制方式。使用圖形介面的設計旨在接收系統的輸入參數、顯示模型、並檢查末端效應器(end-effector)的路徑以保證安全。此系統包含了以 KinectFusion 為基礎的 3D 掃描系統、一台噴塗六軸機器手臂、機器人送料系統、路徑規畫和機器人程序產生的部分。此外，本論文亦針對各種機器人系統和機器人送料系統所產生的末端效應器之路徑逐一探討。其軌跡的產生可由兩種模式產生，包括讀取曲線骨架的工件模型或者採用人工選取圖形中的角點方式。本研究成功地透過 YASKAWA MOTOMAN EPX2050 機械手臂與重建腳踏車車架的三維點雲數據，搭配兩種輸送帶系統，來實現兩種噴塗模式。

    Programming an industrial robot by the typical teaching method, through the use of the robot teach pendant, is a tedious and time-consuming task that requires technical expertise. This thesis presents, 3D point cloud data based robotized spray painting system to generate robot motion plan and subsequently control the process in a much flexible and efficient way than the traditional teaching method. A graphical user interface is developed to define system’s input parameters, visualize the model and inspect the end-effector path for safety. Generally the system comprises of a KinectFusion based 3D scanning subsystem, a 6-axis painting robot, robot feeder subsystem and path planning and robot program generation unit. Moreover, we investigated various end-effector trajectories generation methods based on various robot systems and robot feeder subsystems. The trajectory generation has been achieved is in two modes: by extracting the curve-skeleton of the workpiece's 3D model or manually picking a number of critical corner points graphically. This research successfully implemented the two modes of operation of spray painting applications on YASKAWA MOTOMAN EPX2050 painting robot in integration with two conveying systems by using reconstructed 3D point cloud data of various bicycle-frames.

    Abstract…………………………………………………………………………………….....i 中碩摘要…………………………………………………………………………………..…ii Acknowledgment…………………………………………………………….………............iii List of Figures …………………………………………………………………………….…vi List of Tables…………………………………………………………………………….…..ix Chapter 1 Introduction ................................................................................................................ 1 1.1 Background ............................................................................................................. 1 1.2 Literature Review.................................................................................................... 2 1.3 Autonomous Painting.............................................................................................. 3 Chapter 2 Three Dimensional Model Building and Manipulator ............................................... 5 2.1 Bicycle Frames........................................................................................................ 5 2.2 Three Dimensional Modeling ................................................................................. 5 2.2.1 KinectFusion ............................................................................................... 6 2.2.2 Building 3D Model of Bicycle Frame using KinectFusion ........................ 7 2.2.3 Scanned Model Pre-Handling ..................................................................... 8 2.2.4 Calibration of Scanning Subsystem .......................................................... 11 2.3 Manipulators: ........................................................................................................ 12 2.3.1 DENSO VP-G series: VP-6242G ............................................................. 13 2.3.2 YAKSAWA MOTOMAN Robot: EPX2050............................................ 13 Chapter 3 Trajectory Generation to Spray-painting Bicycle-frame using Two Dimensional Robot 17 3.1 Background ........................................................................................................... 17 3.2 System Setup ......................................................................................................... 17 3.3 Simulation ............................................................................................................. 19 3.3.1 Simulation Parameters Description ........................................................... 19 3.3.2 Simulation Results .................................................................................... 20 3.3.3 Discussion ................................................................................................. 23 Chapter 4 Trajectory Generation to Spray-painting Bicycle-frame using 6-DOF Manipulator24 4.1 Introduction ........................................................................................................... 24 4.2 Posture of Workpiece in Space ............................................................................. 24 4.3 Path Planning for Stationary Workpiece ...............................................................26 4.3.1 Curve-Skeleton Extraction from Point Cloud Data .................................. 26 4.3.2 Curve-Skeleton Points Sequencing and Path Definition .......................... 27 4.3.3 Curve-Skeleton Line Points Reduction ..................................................... 29 4.4 Trajectory Generation for Moving Workpeice ..................................................... 31 4.5 Spray Disperse Model ........................................................................................... 33 4.6 Corner Painting: Position and Orientation Determination .................................... 33 4.6.1 Spray-Gun-Tip Position for Corner Painting ............................................ 34 4.6.2 Corner Painting Orientation ...................................................................... 35 4.6.3 Corner Painting Path .................................................................................37 4.7 PC to Robot-Controller Communication .............................................................. 37 4.8 Simulation ............................................................................................................. 38 4.9 Test on DENSO VP-6242G Manipulator ............................................................. 42 Chapter 5 Path Planning for Bicycle Frame Spray Application using YASKAWA Robot and Robot-Feeder Synchronization ................................................................................................. 43 5.1 Introduction ........................................................................................................... 43 5.2 Overall System ...................................................................................................... 43 5.3 Robot Feeder Subsystem....................................................................................... 44 5.4 Frame Model Coordinate System (i.e. Conveyor and Hooked)............................ 46 5.5 Modes of Operations ............................................................................................. 48 5.6 Simulation and Description of the important Parameters of path planning algorithm and their physical meanings ............................................................................. 50 5.6.1 Parameters of Autonomous Mode ............................................................ 50 5.6.2 Parameters of Pick Points Mode: .............................................................. 54 5.7 Experimentation .................................................................................................... 56 5.7.1 YASKAWA MOTOMAN Painting Robot ............................................... 56 5.7.2 Testing....................................................................................................... 57 Chapter 6 Conclusion and Future Work ................................................................................... 61 6.1 Conclusion ............................................................................................................ 61 6.1 Future Works ........................................................................................................ 61

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