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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/6358

Title: 應用影像處理與智慧型避障策略於自走車之控制
Application of Image Process and Intelligent Obstacle Avoidance Strategy to Wheeled Mobile Robot Control
Authors: Yen-Sheng Chen
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: 模糊;自走車;影像
fuzzy;mobile robot;image processing
Date: 2009
Issue Date: 2011-06-22T08:47:40Z
Abstract: 本篇論文主要提出一個藉由不同的感測器作為輸入,可良好避障且達到目標點的自走車模糊控制器。這篇論文提出了兩種主要的感測器,CCD攝影機和超音波感測器。以這兩種感測器為基礎,加上人類的經驗判斷,不需要非常複雜的數學方程式,就可以設計出一個效果不錯的控制器。本論文第一部分是利用超音波感測器作為自走車的輸入源,再以模糊理論設計模糊控制法則,並以距離的遠近提出不同的避障策略,由MATLAB模擬看出控制器設計可以被實現。第二部分主要是藉由CCD攝影機捕捉的影像,用影像處理的方法去擷取障礙物的邊緣且計算出障礙物距離車子的距離,由影像處理後的障礙物距離取代第一部分中三個超音波感測器所量測的距離,再以模糊法則進行避障控制。硬體部分使用LabView 8.5來撰寫人機介面,將感測器資料傳回電腦運算產生輸出轉速,藉由WiFi (802.11b)無線網路將運算數值與車體回授做為自走車與電腦間數值的傳遞,影像處理用C語言編寫並結合LabView 8.5來控制自走車。經由實驗證實,本論文所設計的模糊控制器運行良好。
This thesis presents a well-performed obstacle avoidance fuzzy controller for a wheeled mobile robot (WMR) via different kinds of input sensors. Two types of sensors, CCD camera and ultrasonic sensors, are utilized in this thesis. In the controller design, complex mathematic formula is not needed. Control strategies are based on human experiences, fuzzy rules, and sensor information. Simulations show that the controller can be realized by MATLAB. We use CCD camera to capture objects and edge of obstacles via image processing method which calculates the distance between the obstacle and the WMR. Hardware implementation uses LABVIEW 8.5 to realize interface between human and machine. Command signals are transferred through WiFi (802.11b) wireless to communicate data between the WMR and computer. Image processing is handled by C code and then is integrated by LABVIEW 8.5 to control the WMR. The proposed controller works well in field tests.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M96670010
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