臺灣博碩士論文加值系統

本論文之主旨在設計機器人以沿牆走行為模式之模糊控制系統，在未知環境下執行機器人沿牆走行為模式，並使機器人能依照各種環境變化來以各種相關的行為模式替換，例如：閃避障礙物、轉彎規劃、牆搜尋。行為架構為基礎的機器人能夠在環境平面繞牆行走。

本論文除了利用模糊控制器外，更提出了改善的方法，加入類神經網路的觀念，以倒傳遞演算法設計出可適應性的模糊控制器，以感測器收集周圍環境參數的資訊，依照這資訊來計算機器人的控制變數，並且用迴授的方式以增加錯誤函數藉著倒傳遞演算來增進整體系統的穩定度，並且探討此種適應性模糊控制器的各種變化。

最後，經由電腦模擬與實際導航操作，驗證本論文的設計具有更加改善的穩定效果。

The aim of this thesis is to design a fuzzy controller for a robot system, which is capable of executing the wall-following behavior and the adaptation under varying conditions, such as obstacle avoidance, making turns, and wall-searching. With these capabilities, the proposed robot is competent to walk along the walls in any environment. Furthermore, with the concept of neural network, an adaptive fuzzy controller is designed based on the back-propagation algorithm. Using the information obtained from the infrared sensor, the control output is computed. To improve the performance of the system, the error of the system is utilized to modify the parameters of the adaptive fuzzy controller according to the gradient descent updating rule. Through the simulation and experiments, the proposed robot system has been proved to be reliable and effective.

Through the simulation and experiments, the robot system proposed has been proved to be reliable and effective.

目錄 iii
第一章 序論 1
1.1 前言 1
1.2 研究動機與目的 1
1.3 相關研究回顧 2
1.4 研究方向與問題描述 6
1.5 章節說明 7
第二章 機器人之系統與硬體介紹 9
2.1 實驗機器人 9
2.1.1 機器人結構系統 9
2.1.2 實驗器材和設備 11
2.1.3 機器人之基本構造 11
2.2 機器人硬體模組 11
2.2.1 PMS5005 Sensor and Motion Controller 12
2.2.2 PMB5010 Multimedia Controller 13
2.3 機器人感測器模組 13
2.3.1 DUR5200 超音波感測器 15
2.3.2 GP2Y0A21YK紅外線感測器 16
2.4 機器人通訊與多媒體 20
2.5 機器人控制平台 24
2.5.1 機器人電池能量 26
2.5.2 機器人聲音播放與影像擷取 26
2.6 機器人控制流程 26
第三章 機器人之自我行為模式控制器 28
3.1 機器人感測器存取 28
3.2 模糊控制器設計之應用於機器人沿牆行走 29
3.3 模糊控制器設計之應用於機器人閃避障礙物 38
3.4 機器人轉彎狀態機制 44
3.5 機器人選擇左右牆機制 46
3.6 機器人行為模式融合 48
第四章 適應性學習應用於沿牆行走 50
4.1 模糊化類神經網路 50
4.2 結合適應性之機器人控制器設計 51
4.2.1 倒傳遞演算法 52
4.2.2 應用倒傳遞學習機制於沿牆走行為模式 53
4.3 適應性沿牆走行為控制器 59
4.3.1 適應性的再訓練 60
第五章 實驗與模擬結果 61
5.1 車體運動方程式 61
5.2 車體初始定位 64
5.3 實驗結果 68
5.3.1 穩態響應 68
5.3.2 角度與距離輸出值 69
5.4 模擬結果 81
5.4.1 車行模擬圖 82
5.4.2 模擬角度與距離輸出值 90
5.4.3 重複訓練函數 101
5.4.4 調整Gradient係數 103
5.5 GUI模擬器介面設計 106
第六章 結論與未來展望 108
6.1 實驗結論 108
6.2 未來展望 109

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