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研究生：	陳威任 Chen, Wei-Jen
論文名稱：	輪型移動機器人之路徑規劃與學習演算法應用於路徑追蹤之模糊控制器設計 Path planning for a wheeled mobile robot and learning algorithms applied to tracking fuzzy controller design.
指導教授：	陳美勇 Chen, Mei-Yung
學位類別：	碩士 Master
系所名稱：	機電工程學系 Department of Mechatronic Engineering
論文出版年：	2016
畢業學年度：	104
語文別：	中文
論文頁數：	104
中文關鍵詞：	A*演算法、B-Spline曲線、模糊控制、學習演算法
英文關鍵詞：	A* algorithm, B-Spline Curve, Fuzzy Control, Learning algorithms
DOI URL：	https://doi.org/10.6345/NTNU202203668
論文種類：	學術論文
相關次數：	點閱：70 下載：28
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本研究主要是輪型機器人的路徑規劃與路徑追蹤。在路徑規劃方面，採A*演算法具有最小花費函數搜尋結果之特色生成輪型移動機器人之最短路徑，然而，此種設計方法應用於路徑規劃之結果將會產生大量轉折點以及過於靠近障礙物之路徑，因此，採用了具有局部改變調整特性的B-Spline 曲線來調整A*演算法不適用於輪型移動機器人追跡之區段路徑。在路徑生成之後，接下來即是考慮路徑追蹤的課題。為設計路徑追蹤的控制器，我們必須先了解輪型移動機器人的運動模型才可進行下一步之路徑追蹤控制器設計。路徑追蹤方面採用輪型移動機器人之兩輪速度控制方法來完成目的，本論文採用了模糊控制系統結合類神經網路之適應性模糊類神經網路技術，以此方式可結合模糊控制之定性分析與類神經網路定量分析能力之特色，並具備自我學習調整之能力，最後再加入遺傳演算法進行最佳化設計提高理想之結果。

The primary search in this content are path planning and path tracking of wheel mobile robot. For path planning, adopting A * algorithm with the feature of minimum cost function results to design the shortest path of wheeled mobile robots. However, the result of path planning with this method will generate a lot of turning points and too close to the obstacle on the path. Under this situation, then use B-Spline curve which has local change adjustment feature can adjust the segments of A * algorithm where are not suitable for wheeled mobile robot to track. After the path is generated, the next consideration is path tracking. To design tracking controller, we must know kinematics model of wheeled mobile robot, therefore it is required to derived of kinematics model beforehand. For path tracking, it is accomplished the purpose by adjusting the speed of two wheels of the mobile robot, this paper uses adaptive network-based fuzzy inference system technology which combines with fuzzy and neural network, it contains the feature of qualitative analysis capabilities of fuzzy control and quantitative analysis capabilities of neural network, and has ability of self-learning adjustment , then add genetic algorithm to optimize the ideal result.

論文目錄
      摘要..............................................i
      Abstract.........................................ii
      致謝............................................iii
      目錄.............................................iv
      圖目錄.........................................viii
      表目錄.........................................xiii
    
第一章 緒論..............................................1
      1.1 前言..........................................1
      1.2 文獻回顧.......................................2
      1.3 研究動機.......................................7
      1.4 本論文之貢獻..................................11
      1.5 論文架構......................................11
第二章 輪型移動機器人之路徑規劃...........................13
      2.1 路徑規劃......................................13
      2.2 最短路經搜尋法................................13
      2.3 B-Spline曲線.................................19
      2.3.1 B-Spline 曲線定義.......................20
          2.3.2 B-Spline曲線模型特性....................20
      2.3.3 B-Spline曲線的凸多邊形特性...............27
          2.3.4 B-Spline曲線的局部控制特性...............29           
第三章 輪型移動機器人之運動模型建立........................32
      3.1 輪型機器人之結構分析並以約束條件推導運動模型......34
          3.1.1 輪型移動機器人完整約束之分析..............35
      3.1.2 非完整約束條件推導.......................36
      3.2 離散型輪型機器人運動模型........................37
      3.3 軌跡追蹤模型之建立.............................39
第四章 模糊理論與控制應用.................................41
      4.1 模糊理論......................................42
          4.1.1 模糊集合................................42
      4.1.2 模糊邏輯................................44
          4.1.3 模糊集合運算............................45
      4.2 模糊邏輯控制(Fuzzy Logic Control，FLC)........45
          4.2.1 模糊推論系統............................46
      4.2.2 模糊化.................................46
          4.2.3 模糊規則庫..............................48
          4.2.4 歸屬函數資料庫..........................50
      4.2.5 推論引擎................................52
          4.2.6 解模糊化機構............................53
          4.2.7 解模糊化之模糊模式.......................55
      4.3 智慧型模糊控制................................57
第五章 智慧型學習法應用於模糊控制器之改良..................58
      5.1 類神經網路....................................58
      5.2 適應性網路模糊推論系統.........................60
      5.3 基因演算法....................................64
      5.3.1 基因演算法之設定.........................65
      5.3.2 基因演算法之程序.........................67
      5.3.3 基因演算法之使用時機.................... 70
第六章 實驗設計與結果討論.................................71
      6.1 實驗設備介紹..................................71
          6.1.1 程式設計軟體............................71
      6.1.2 實驗硬體設備............................74
          6.1.3 模型分析與控制器參數定義..................75
      6.2 路徑追蹤控制規則...............................75
          6.2.1 控制規則設計之概念...................... 75
          6.2.2 歸屬函數與模糊規則.......................76
      6.3 模糊控制之參數學習調整.........................79
      6.4 輪型移動機器人之路徑規劃與追蹤實例分析...........80
          6.4.1 模擬驗證................................80
          6.4.2 實驗測試................................86
第七章 結論與未來展望....................................98
參考文獻...............................................100
                                

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