臺灣博碩士論文加值系統

本研究是探討以類神經網路應用於水下機械臂定位精確度校正之相關問題。水下機械臂之定位由於洋流與水下載具之動態效應影響，使其極不易達成高精確度；在本先期研究中，我們將暫不考慮洋流等外在負載影響，主要著力於解決機械臂因加工、組裝、傳動等誤差所造成之定位誤差問題。我們首先進行機械臂精確度及重現性實驗，探討誤差產生之因素，再將機械臂各種誤差所形成的誤差量視為一系統誤差，針對此系統誤差進行線性回歸分析，最後利用此線性回歸建立資料庫並以類神經網路─倒傳遞演算法則進行校正工作。由驗證實驗顯示，經類神經網路構成校正後之機械臂定位精確度比未校正前有顯著提昇。

In this thesis, we investigated the related problems of the application of the neural network to the positioning calibration of an underwater manipulator. Due to the influence of the ocean current and the dynamic effects of the underwater vehicle, high level of positioning accuracy of an underwater manipulator is generally unattainable. In this preliminary study, we did not consider the external loads such as the effects of the current, but focused on the inaccuracy induced by the process of fabrication, assembling, and the errors from the transmission systems of the underwater manipulator. First, we performed the positioning accuracy tests and repeatability tests to find out the factors of inaccuracy. Then, we regarded the manipulator’s inaccuracy as a system error, and performed the linear regression analysis to the system output. A database was resulted from the linear regression analysis. Finally, we proceeded the positioning calibration using the back-propagation algorithm of the neural network. The results from the calibration using neural network showed that, the positioning accuracy of the manipulator was greatly enhanced than that before calibration.

第一章 緒論
1.1 前言．．．．．．．．．．．．．．．．．．．．．．．1
1.2 文獻回顧．．．．．．．．．．．．．．．．．．．．．4
1.3 研究動機．．．．．．．．．．．．．．．．．．．．．6
1.4 論文架構．．．．．．．．．．．．．．．．．．．．．7
第二章 理論背景
2.1 機械臂運動方式．．．．．．．．．．．．．．．．．．9
　2.1.1 迪納維特-哈登伯格矩陣．．．．．．．．．．．．．9
2.1.2 前向運動學．．．．．．．．．．．．．．．．．．13
2.1.3 迴路方程式．．．．．．．．．．．．．．．．．．16
2.1.4 逆向運動學．．．．．．．．．．．．．．．．．．18
2.2類神經網路．．．．．．．．．．．．．．．．．．．．．20
2.2.1 倒傳遞演算法則．．．．．．．．．．．．．．．．．20
第三章 實驗設備
3.1受控模組．．．．．．．．．．．．．．．．．．．．．24
3.2控制模組．．．．．．．．．．．．．．．．．．．．．30
3.3控制介面模組．．．．．．．．．．．．．．．．．．．32
3.4誤差來源．．．．．．．．．．．．．．．．．．．．．33
第四章 實驗及模擬
4.1實驗方法．．．．．．．．．．．．．．．．．．．．．36
4.2實驗程序．．．．．．．．．．．．．．．．．．．．．37
實驗一：無負載下馬達精確度測試．．．．．．．．．．．．．37
實驗二：轉軸角位移精確度實驗．．．．．．．．．．．．．．40
實驗三：重現性實驗．．．．．．．．．．．．．．．．．．．45
4.3類神經網路模擬．．．．．．．．．．．．．．．．．．54
4.3.1資料庫前置處理作業．．．．．．．．．．．．．．．．55
4.3.2利用倒傳遞演算法進行模擬．．．．．．．．．．．．．58
第五章 結果驗證及討論
5.1模擬結果．．．．．．．．．．．．．．．．．．．．．．．68
5.1.1關節轉角驗證．．．．．．．．．．．．．．．．．．．69
5.1.2座標位置驗證．．．．．．．．．．．．．．．．．．．71
5.2結果討論．．．．．．．．．．．．．．．．．．．．．74
第六章 結論與未來展望
6.1結論．．．．．．．．．．．．．．．．．．．．．．．76
6.2未來展望．．．．．．．．．．．．．．．．．．．．．77

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