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系統識別號 U0026-0812200912134539
論文名稱(中文) 應用類神經網路與超音波感測器於車型機器人之路徑追蹤與避障
論文名稱(英文) Path tracking and obstacles avoidance using neural networks and ultrasonic sensors for car-like robots
校院名稱 成功大學
系所名稱(中) 電機工程學系碩博士班
系所名稱(英) Department of Electrical Engineering
學年度 94
學期 2
出版年 95
研究生(中文) 黃國和
研究生(英文) Guo-He Huang
電子信箱 n2693127@ccmail.ncku.edu.tw
學號 n2693127
學位類別 碩士
語文別 中文
論文頁數 72頁
口試委員 指導教授-王振興
口試委員-蔣榮先
口試委員-鄭銘揚
中文關鍵字 車型機器人  避障  路徑追蹤 
英文關鍵字 car-like robot  path tracking  obstacle avoidance 
學科別分類
中文摘要 本論文主旨在實現全域路徑追蹤與閃避障礙物於實體車型機器人。論文中提出一種可追蹤可閃避全域環境障礙物之最短路徑,並可即時偵測並閃避障礙物之機器人動作規劃(motion planning)演算法。此演算法利用模式切換的觀念,針對不同的情況進行適當的控制與動作規劃,增加車型機器人之環境適應能力與自主性。動作規劃方法中主要分為兩種模式:追蹤模式(tracking mode)與緊急模式(emergency mode)。追蹤模式使用Neural dynamic model路徑追蹤演算法令車型機器人行走於由若干離散點所組成之離散化全域路徑。在行進過程中同時利用超音波感測器偵測行進路徑是否存在障礙物,一旦感測器測得障礙物隨即切換為緊急模式。此模式利用類神經分類器辨別障礙物位置與其可能的形狀後,控制車型機器人進行閃避動作,再令其返回全域路徑,完成障礙物閃避目標。待演算法軟體驗證無誤後,利用Parallax公司生產之感測器與車型機器人原型實行實體驗證工作,證明本論文中所提之控制機制於實體應用之可行性。
英文摘要 This thesis focuses on the implementation of a car-like robot navigation hybrid control strategy characterized by global path tracking and obstacle avoidance based on neural network and ultrasonic sensors. The proposed car-like robot navigation control algorithm is capable of tracking a planned global path and avoiding the obstacle instantaneously. In order to enhance the adaptability and autonomy of the car-like robot, the algorithm adopts the concept of mode switching to provide a suitable control strategy in different situations. The control strategy consists of two modes: a tracking mode and an emergency mode. Most of the time, we set the robot in the tracking mode whose neural dynamic path-tracking algorithm enables the robot to follow a discretized planned path. In addition, we use ultrasonic sensors to detect whether there is any obstacle on the path during the navigation. Once these sensors detect the existence of the obstacles, the control strategy will switch to the emergency mode immediately. The emergency mode utilizes a neural classifier to judge the positions and possible shapes of the obstacles. Based on different positions and shapes of the objects determined by the classifier, we proceed to the obstacle avoidance control. The robot will go back to trace the global planned path after avoiding the obstacle. After software validation of the proposed algorithm, we use the ultrasonic sensors and a car-like robot developed by Parallax to verify the effectiveness and feasibility of the proposed control strategy.
論文目次 中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第 1 章 緒論 1-1
1.1 研究背景與動機 1-1
1.2 文獻探討 1-2
1.2.1 車型機器人之路徑規劃 1-5
1.2.2 車型機器人之路徑追蹤 1-6
1.2.3 其他車型機器人自主式行為 1-7
1.3 研究目的 1-8
1.4 論文架構 1-8
第 2 章 類神經網路與局部路徑規劃 2-1
2.1 前言 2-1
2.2 類神經網路簡介 2-1
2.2.1 類神經網路模型 2-1
2.2.2 倒傳遞演算法 2-4
2.3 類神經障礙物幾何形狀分類器 2-5
2.3.1 基本障礙幾何物形狀簡介 2-5
2.3.2 類神經障礙物幾何形狀分類器 2-7
2.4 局域路徑規劃與控制 2-14
第 3 章 全域路徑規劃與路徑追蹤 3-1
3.1 前言 3-1
3.2 全域路徑規劃方法 3-1
3.3 路徑追蹤控制機制 3-4
3.4 全域路徑追蹤結合即時障礙物閃避 3-9
3.5 超音波感測器與傳輸介面 3-11
第 4 章 模擬結果 4-1
4.1 規劃路徑上無障礙物之模擬結果 4-1
4.2 規劃路徑上存在障礙物之模擬結果 4-4
第 5 章 結論與未來工作 5-1
5.1 結論 5-1
5.2 未來工作 5-2
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