整合視覺、力量感測與模糊控制技術之新穎機械手臂組裝系統

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姓名

李家銘(Jia-Ming Li) 查詢紙本館藏

畢業系所

光機電工程研究所

論文名稱

整合視覺、力量感測與模糊控制技術之新穎機械手臂組裝系統
(A Novel Robotic Assembly System Integrating Vision, Force Sensing, and Fuzzy Control Technologies)

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至系統瀏覽論文 ( 永不開放)

摘要(中)

本研究在Linux系統的Ubuntu 20.04版本上，利用機器人作業系統(Robot Operating System, ROS)開發控制軟體。透過ROS的點對點網路和分散式架構，整合了所有的資訊，並實現了工業電腦(Industrial PC)、六軸工業機械手臂、立體相機、六軸力量/力矩感測器以及自適應夾爪等硬體設備與軟體系統的協同運作。
本研究針對機械手臂在齒輪箱組裝任務中的挑戰，提出了一種結合視覺與力量控制的模糊控制系統。傳統的順應性控制方法往往需要手動調整多個參數，以應對手臂初始校正、視覺定位誤差以及每次零件夾取時的變異，這導致了自動化組裝過程繁瑣且效率不高。為了解決這些問題，本研究設計並實現了一套多輸入多輸出(Multiple-Input Multiple-Output, MIMO)的模糊力量控制系統，使機械手臂能夠根據即時的組裝情況、力量反饋和視覺定位等感測資訊進行動態調整控制參數，從而提高手臂控制系統的自適應性。經過一系列的實驗驗證結果顯示，所提出之新系統在機車齒輪箱組裝過程，相較於先前本研究室所開發之前系統，減少34%的組裝時間，平均降低30%的最大組裝力量及27%的組裝力量標準差，顯著提升組裝效率和組裝穩定度。此外，也再以行星齒輪系統進行組裝驗證實驗，再次證明了模糊控制在此類複雜干涉與定位的自動化齒輪系統組裝任務中的創新性和實務應用性。

摘要(英)

This research developed control software on the Ubuntu 20.04 version of the Linux system, using the Robot Operating System (ROS). Through ROS′s peer-to-peer network and distributed architecture, all information was integrated, facilitating the coordinated operation of industrial PC, a six-axis industrial robot arm, a stereo camera, a six-axis force/torque sensor, and adaptive grippers.
Addressing the challenges in gearbox assembly tasks for robotic arms, this research proposed a fuzzy control system that combined vision and force control. Traditional compliance control methods often required manual adjustment of multiple parameters to accommodate initial arm calibration, visual positioning errors, and variations in each part-grabbing process, leading to a tedious and inefficient automated assembly process. To overcome these limitations, this study designed and implemented a Multiple-Input Multiple-Output (MIMO) fuzzy control system that dynamically adjusted control parameters based on real-time assembly conditions, force feedback, and visual positioning sensor data, thus enhancing the adaptability of the robotic arm control system.
A series of experimental results demonstrated that the proposed new system significantly improved assembly efficiency and stability in motorcycle gearbox assembly tasks compared to the previously developed system, showing a 34% reduction in assembly time, an average 30% decrease in maximum assembly force, and a 27% reduction in force standard deviation. Furthermore, additional validation through planetary gear system assembly experiments confirmed the innovative and practical application of fuzzy control in complex, interference-sensitive, and precision-demanding automated gear system assembly tasks.

關鍵字(中)

★ 模糊控制
★ 力量控制
★ 機器視覺
★ 機械手臂組裝
★ 伺服運動控制
★ Robot Operating System (ROS)

關鍵字(英)

★ Fuzzy Control
★ Force Control
★ Machine Vision
★ Robotic Assembly
★ Servo Motion Control
★ Robot Operating System (ROS)

論文目次

摘要 2
Abstract 4
誌謝 5
目錄 6
圖目錄 9
表目錄 13
一、緒論 1
1-1 研究背景 1
1-2 文獻回顧 1
1-2-1 力量控制 1
1-2-2 模糊控制 5
1-3 研究動機和目的 7
1-4 論文架構 8
二、系統架構 9
2-1 硬體架構 9
2-1-1 六軸工業機械手臂 9
2-1-2 相機 11
2-1-3 力量感測器 12
2-1-4 自適應夾爪與指夾設計 14
2-1-5 工業電腦 16
2-2 軟體架構 17
2-2-1 機器人作業系統(Robot Operating System, ROS) 17
2-2-2 Moveit套件介紹 20
2-2-3 ABB EGM系統介紹 21
2-2-4 Scikit-Fuzzy模組 22
三、研究方法 23
3-1 機械手臂運動學與運動控制 23
3-1-1 D-H法 23
3-1-2 正向運動學 24
3-1-3 逆向運動學 26
3-1-4 點到點運動控制 27
3-1-5 伺服運動控制 28
3-2 機器視覺及影像處理 29
3-2-1 OpenCV環境介紹 29
3-2-2 灰階化 30
3-2-3 高斯濾波與二次高斯濾波 31
3-2-4 二值化與自適應二值化 31
3-2-5 邊緣檢測 33
3-2-6 輪廓提取 34
3-3 機械手臂手眼校正 35
3-3-1 由世界座標系到相機座標系 37
3-3-2 從相機座標系到圖像座標系 37
3-3-3 從圖像座標系到像素座標系 38
3-4 順應性控制 40
3-4-1 阻抗控制 41
3-4-2 位置順應性控制 44
3-5 模糊控制 46
3-5-1 模糊控制理論 46
3-5-2 歸屬度函數 47
3-5-3 模糊規則 47
3-5-4 模糊推理 48
3-5-5 解模糊化 49
3-6 機器人作業系統整合應用 50
3-6-1 機械手臂控制節點 51
3-6-2 力量感測器節點 52
3-6-3 影像辨識節點 52
3-6-4 模糊控制節點 53
四、實驗結果 54
4-1 實驗工作環境及優化齒輪裝配 54
4-2 模糊控制器設計 55
4-2-1 定義系統的輸入輸出變數 55
4-2-2 模糊化 56
4-2-3 定義模糊規則 61
4-2-4 模糊推理和解模糊化 62
4-3 機車齒輪箱裝配實驗 63
4-4 機車齒輪箱裝配實驗結果分析與模糊控制系統評估 68
4-4-1 副齒輪裝配實驗 69
4-4-2 驅動齒輪裝配實驗 75
4-4-3 驅動軸裝配實驗 81
4-5 組裝系統驗證-行星齒輪裝配實驗 87
五、結論及未來展望 93
5-1 論文結論 93
5-2 未來展望 94
參考文獻 95

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指導教授

陳怡呈(Yi-Cheng Chen)

審核日期

2024-11-25

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