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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/52428


    Title: 以機器視覺為基礎實現自走車車道追跡系統
    Other Titles: Vision-based lane tracking system for autonomous mobile robot
    Authors: 林伯彥;Lin, Po-yen
    Contributors: 淡江大學機械與機電工程學系碩士班
    孫崇訓
    Keywords: 車道追跡;機器視覺;階層式模糊系統;Lane tracking;Machine vision;hierarchical fuzzy system
    Date: 2010
    Issue Date: 2010-09-23 17:40:16 (UTC+8)
    Abstract: 本論文的主要研究方向就是把即時影像處理技術應用在車道線的偵測,並將車道與車子的相關資訊回授給系統控制器以控制前輪的轉向,進而實現自走車車道保持與追跡的功能。
    我們將攝影機架設在自走車上做為感測器拍攝前方道路影像,並以邊緣偵測、霍夫轉換等影像處理方法來獲得即時的車道線資訊。如此自走車便可以根據得到的車道資訊透過模糊控制的方式做出正確轉向動作完成車道追跡。因為自走車使用的前輪轉向伺服機並不具有回授與編碼的功能,無法直接得知前輪在每一時刻的轉向角,因此我們的模糊系統完全靠影像回授的車道線資訊,包含車子與車道之間的側偏差、側偏差隨時間變化率以及車道中心線方向隨時間變化率這三項資訊做為控制輸入。設計三輸入的模糊系統,可能會產生大量的模糊規則,因此這邊又加入了階層式模糊系統的概念,來達到模糊規則數的降低。最後,我們以實驗來驗證此車道追跡系統在自走車上的應用是可行且穩定的。
    This paper performs a vision-based lane tracking system for the autonomous mobile robot. We take the camera on mobile robot as the sensor to get real-time road images. The lane markings in images are extracted by specifying ROI (Region of Interest), Sobel edge detection, Hough transform and real-time image processing algorithm. Then the autonomous mobile robot will move following the lane markings using fuzzy control. In this fuzzy controller, the input variables are the derivative of lane direction, the deviation between lane center and mobile robot, and its change rate, since the sensor-less steering motor is adopted. For the traditional fuzzy control system, three input variables will lead to a large number of fuzzy rules. The hierarchical fuzzy system is utilized to reduce the fuzzy rules and the computing burden. Experimental results show the effectiveness of the proposed lane tracking system.
    Appears in Collections:[Graduate Institute & Department of Mechanical and Electro-Mechanical Engineering] Thesis

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