臺灣博碩士論文加值系統

隨著時代在進步，科技日新月異的發展，自動化成為許多現代企業努力的方向，而自動導引車(Automated Guided Vehicle, AGV)則是自動化中及為重要的一環。AGV有著安全、效率高和能長時間運轉等優點，使用在自動化生產中是個不錯的選擇，甚至在觀光、旅館等產業也有許多使用AGV的案例。
為了因應各種環境與需求，AGV也有許多不同的導航依據，例如磁帶導航、電磁導航、雷射導航或二維條碼等等，但這些導航方式普遍都需要增設軌道或對環境有一定的要求，而本論文中介紹了一種利用電腦視覺做為導航方式的自動導引車，其對環境的要求相對來說較低一些，其工作原理是利用裝載在車上的攝影鏡頭拍攝位於地面的標線，透過影像處理得到標線與車體間的相關資訊，進而達到導航的目地，期望以一般工廠地面现有的標線進行導航。
然而電腦視覺容易受到環境中的干擾進而影響系統的穩定性，因此本論文提出了兩種方法來對AGV的路徑偏移校正進行改良，透過軌跡預測補足車輛遺失的路徑校正依據，同時利用模糊控制器提高車輛控制的效能，以此提高路徑偏移校正的效率與系統的穩定性。

With the advancement of the times and the rapid development of science and technology, automation has become the direction of many modern enterprises, and automated guided vehicle (AGV) is an important part of automation. AGV has the advantages of safety, high efficiency and long-term operation. It is a good choice for automated production. It has many cases of using AGV even in tourism and hotel industries.
In order to respond to various environments and needs, AGV also has many different navigational basis, such as tape navigation, electromagnetic navigation, laser navigation or 2D barcodes, etc., but these navigation methods generally require additional orbital or environmental requirements. In this paper, an automatic guided vehicle using computer vision as a navigation method is introduced, which has relatively low environmental requirements. The working principle is to use the camera mounted on the vehicle to shoot the marking line of the ground, and through the image processing to obtain the relevant information between the marking line and the vehicle, thereby achieving the navigation purpose. It is hoped that the existing markings on the ground of the general factory will be used as the basis for navigation.
However, computer vision is susceptible to interference in the environment and thus affects the stability of the system. Therefore, this paper proposes two methods to improve the path offset correction of AGV. The trajectory prediction is used to complement the missing path correction basis, and the fuzzy controller is used to improve the efficiency of vehicle control, thereby improving the efficiency of path offset correction and system stability.

摘要......i
Abstract......ii
誌謝......iii
目錄......iv
表目錄......vi
圖目錄......vii
第一章 緒論......1
1.1 前言......1
1.2 研究背景與動機......2
1.3 研究方法......3
1.4 論文章節架構......4
第二章 相關背景知識......5
2.1 AGV導航方式......5
2.2 模糊理論......8
第三章 系統設計......10
3.1 影像處理......11
3.1.1 影像辨識......12
3.1.2 標線資訊計算......20
3.2 軌跡預測......27
3.2.1 AGV車體架構......27
3.2.2 距離與角度資訊補償......28
3.3 模糊控制......32
3.3.1 定義輸入與輸出變數......32
3.3.2 模糊集合與隸屬函數......33
3.3.3 模糊控制規則......35
3.3.4 模糊推論......36
3.3.5 解模糊化......38
第四章 實作結果......39
4.1 影像處理結果......39
4.1.1 影像辨識結果......39
4.1.2 標線資訊計算結果......42
4.2 軌跡預測資訊補償結果......42
4.3 模糊控制改善結果......47
第五章 結論與未來展望......49
參考文獻......50
Extended Abstract......52

[1]When were automatic guided vehicles first developed?
Available：http://www.agvsystems.com/faqs/
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