本研究主要設計與研製一套不需辨別停車空間之車型機器人自主停車控制系統。本論文中，車型機器人依靠四個超音波感測器與一個電子羅盤感測器量測環境資訊，由模糊控制器來預測車子停車時之前輪轉向角度，以達成路邊停車之任務。其控制器設計過程中，以三條五階多項式為參考路徑來產生訓練資料，透過減法聚類法（Subtractive Clustering）獲得控制器之前提部與推論部之組合，再運用適應性網路模糊推論系統（Adaptive Network-Based Fuzzy Inference System，ANFIS）理論，使得所有參數獲得適當的優化調整。此車型機器人之設計分為兩大單元，分別為控制單元與運算單元，控制單元主要介紹步進馬達轉動控制、RC伺服馬達轉向控制、超音波感測器與電子羅盤感測器量測控制、RS-232通訊介面控制。運算單元由LabVIEW圖控式軟體來完成控制器的即時演算，以得到車型機器人的前輪轉向角度。文中在硬體測試前先經由Matlab/Simulink軟體模擬測試，以驗證該理論之可行性。而硬體實作結果顯示車型機器人在不同的牆面距離初始條件下，完成路邊停車之任務。

The thesis presents an autonomous parallel parking fuzzy controller for a car-like mobile robot (CLMR) which the parking space dimensions cannot be identified. Four ultrasonic sensors are mounted in the front right corner of the car to obtain the parking environmental information and a compass sensor is mounted at the centre position of the car to measure the posture of the car. Through the proposed mechanism, one of the four ultrasonic sensors and the compass sensor are used to decide on the turning angle. Fifth-order polynomial reference paths starting from three different parking widths to the same goal point have been used to generate the training data set. The controllers have been identified by the subtractive clustering algorithm and been trained by the adaptive network-based fuzzy inference systems (ANFIS) to obtain the optimal parameters of the controllers. The hardware design of the CLMR can be classified into two units which are the control unit and operation unit. The control unit includes the stepper motor rotation control, RC servo motor steering control, ultrasonic sensors and compass sensor measurement control, and RS-232 communication interface control. The operation unit utilizes the LabVIEW software to implement real-time computations of the front wheel steering angle of the CLMR. Before the hardware testing, the Matlab/Simulink software is first used to simulate and verify the feasibility of the proposed approach. The experiment results show that the proposed approach enable the CLMR to intelligently and successfully perform the parallel parking for a variety of parking widths.

摘 要 i
Abstract ii
致 謝 iii
目 錄 iv
圖 目 錄 vi
表 目 錄 ix
第1章 緒論 1
1-1研究目地與動機 1
1-2文獻回顧 2
1-3論文架構 2
第2章 系統架構與硬體元件 4
2-1整體系統架構 4
2-2車型機器人車體結構 5
2-3微控制器ATmega162簡介 7
2-4步進馬達 9
2-4.1步進馬達簡介 9
2-4.2步進馬達驅動與控制方法 11
2-5 RC伺服馬達 12
2-5.1 RC伺服馬達簡介 12
2-5.2 RC伺服馬達控制方法 13
2-6超音波感測器 14
2-6.1超音波感測器特性與簡介 14
2-6.2超音波量測距離計算 14
2-6.3多個超音波感測器量測電路之設計 15
2-7電子羅盤感測器 17
2-8串列埠通訊界面設計 18
第3章 運動方程式介紹與停車控制器設計 22
3-1運動方程式推導 22
3-2路邊停車參考路徑－五階多項式 25
3-3減法聚類演算法 27
3-4適應性網路模糊推演系統（ANFIS） 32
3-4.1 Sugeno模糊模式 33
3-4.2適應性網路模糊推論系統之架構 35
3-4.3適應性網路模糊推論系統之學習演算法 38
3-5停車控制器設計 40
3-5.1感測器位置配置設計與分析 40
3-5.2超音波感測器訓練資料之產生 42
3-5.3電子羅盤感測器訓練資料之產生 44
3-5.4前輪轉向角訓練資料之產生 45
3-5.5控制器設計 46
3-5.6模擬結果 61
第4章 軟韌體設計與實現結果 64
4-1軟體與韌體架構簡介 64
4-2串列傳輸系統設計與分析 64
4-2.1轉向角度量化與通訊編碼 65
4-2.2串列通訊協定 66
4-3人機介面設計 68
4-3.1 LabVIEW圖控式軟體簡介 69
4-3.2虛擬儀表的組成 69
4-3.3軟體程式設計 70
4-4 AVR微控制器韌體設計與流程 73
4-5實驗結果 78
第5章 總結與未來展望 81
5-1 總結 81
5-2 未來展望 81
參考文獻 82

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