臺灣博碩士論文加值系統

近年來機械手臂逐漸在自動化發展中扮演不可或缺的角色，能依照現場環境需求來選擇機械手臂，目前機械手臂廣泛應用在貨物搬運、裝配、檢測、加工、焊接、毛邊等複雜工作，商用常見的六軸機械手臂多為三個相鄰關節軸相交構型而此種構型無法處理大負荷及較長的水平範圍操作之需求，因此設計出腕部關節偏置之手臂構型來因應。
已有商用機械手臂發展出腕部關節偏置之構型此構型三個相鄰關節軸不相交，其逆向運動學一般沒有封閉解析解，通常採用數值解法求解，其求解收斂速度會與所選取角度初始值有關，因此也比解析解複雜許多。
本論文以YASKAWA MOTOMAN MA1400六軸腕部具偏移型機械手臂為研究對象，利用Denavit-Hartenberg座標系轉換法建立機械手臂運動學數學模型，推導正逆向運動學數學式，透過迭代法與內差法求取機械手臂姿態對應的關節角度，並使用Visual Studio C#撰寫程式，以ModuleWorks與OpenGL函式庫來實現工法編程與加工模擬，最後本文透過SprutCAM軟體進行手臂驗證比對，確認本研究六軸腕部具偏置機械手臂姿態與位置轉換之正確性。

In recent years, robotic arms have gradually played an indispensable role in the development of automation, as they can be selected according to the needs on site. Currently, robotic arms are mostly used in complex tasks such as handling cargo, assembling products, testing, processing, welding, and deburring. Most of the common commercial six-axis robotic arm has the configuration of three intersecting axes, which make it unable to handle large load and long horizontal range operation. Thus, an arm with configuration of an offset wrist joint was designed to accommodate this requirement.
There are commercial robotic arms that have the configuration of offset wrist joint, where the three adjacent joint axes do not intersect. Its inverse kinematics generally does not have an analytical solution and is usually calculated by numerical solution, in which the convergence rate depends on the initial value of the selected angle, so that it is much more complicated than an analytical solution.
In this paper, the YASKAWA MOTOMAN MA1400 six-axis robotic arm with offset wrist joint was the research subject, where the Denavit-Hartenberg coordinate system conversion is used to establish a mathematical kinematic model of the arm. The mathematical equation of its forward and reverse kinematics is derived to find the joint angle corresponding to the robotic arm’s posture by iterative method and interpolation. Then, the Visual Studio C# is employed to write programs and the ModuleWorks and OpenGL libraries are used to implement process programming and machining simulation.
Lastly, the robotic arm was tested and compared by using SprutCAM software to confirm the conversion accuracy of the coordinates of its posture and position.

摘要...i
Abstract...ii
誌謝...iv
目錄...v
表目錄...viii
圖目錄...ix
符號說明...xi
名詞中英對照表...xii
第一章 緒論...1
1.1 研究動機與目的...1
1.2 文獻回顧...2
1.2.1 機械手臂運動學...2
1.2.2 機械手臂路徑規劃...5
1.2.3 ModuleWorks相關文獻...7
1.3 研究方法與步驟...9
1.4 論文架構...12
第二章 相關技術...13
2.1 基本座標轉換矩陣...13
2.2 六軸關節型機械手臂D-H座標轉換法...16
2.3 刀具切削路徑點向量推導...19
2.3.1 平面加工以切線推導...19
2.3.2 曲面加工以接觸點方式之推導...20
2.4 刀軸向量推導...22
2.5 使用軟體介紹...25
2.5.1 Visual Studio 2022 C#[25]...25
2.5.2 Mathematica[26]...26
2.5.3 SprutCAM 10[4]...27
2.5.4 ROBOGUIDE[27]...27
2.6 OpenGL介紹...28
2.6.1 OpenGL繪圖函式庫介紹...29
2.6.2 Opengl常用函式...30
2.7 ModuleWorks介紹...31
第三章 機械手臂相關理論介紹...32
3.1 機械手臂基本介紹...32
3.2 D-H 座標轉換法...33
3.3 腕部具偏移之正運動學...34
3.4 腕部具偏移之逆向運動學...36
3.5 腕部具偏移之迭代法...42
3.6 X-Y-Z 尤拉角轉換...46
3.6.1 正向尤拉角...46
3.6.2 逆向尤拉角...47
第四章 程式介面介紹與驗證...49
4.1 介面之功能介紹...49
4.2 編程零件範例...54
4.3 正向運動學轉換驗證...59
4.4 逆向運動學轉換驗證...61
4.5 尤拉角正逆向轉換驗證...63
4.5.1 尤拉角正向運動學轉換...64
4.5.2 尤拉角逆向運動學轉換...65
4.6 刀軸路徑轉換及模擬介面驗證...66
第五章 結論與未來展望...69
5.1 結論...69
5.2 未來展望...70
參考文獻...71
Extended Abstract...74

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