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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/74666


    Title: 自走車追跡系統之灰預測模糊控制研究
    Other Titles: Research of grey-fuzzy control for autonomous mobile robot lane tracking system
    Authors: 江承祐;Jiang, Cheng-You
    Contributors: 淡江大學機械與機電工程學系碩士班
    孫崇訓
    Keywords: 灰色預測;模糊控制;Grey Prediction;fuzzy controller
    Date: 2011
    Issue Date: 2011-12-28 19:14:49 (UTC+8)
    Abstract: 本研究是發展一套自走車車道追蹤,並且可變換車速的系統 ,使用攝影機作為感測器架設於自走車上,拍攝前方行進道路即時影像,利用影像處理的方法,將影像中車道線的資訊留下。由車子與車道的相關資訊與車輪與車身夾角二項資訊做為控制輸入,設計模糊控制器,作為控制前輪轉向以保持在車道內行進。應用灰色理論進行預測,使用四點滾動式GM(1, 1)灰預測,預測車道位置後判斷車道線是否將要轉彎,降低自走車轉彎之車速。最後以實驗來驗證,此車道追跡與變換車速的系統是可行的。
    This paper performs a vision-based lane tracking system for a variable-speed autonomous mobile robot. A camera is set on the mobile robot as the sensor to get real-time road images. The lane marks in images are extracted by real-time image processing algorithm. We design fuzzy controller according to the information of the lane marks and steering angle. Then the autonomous mobile robot moves following the lane marks. We apply the four-point rolling grey modeling GM(1, 1) to prediction of the lane position and confirm whether the autonomous mobile robot is in the sharp curve of a road. Afterward we slow down car speed in the curve road. Finally experimental results show the effectiveness of the proposed lane tracking and different car speed system.
    Appears in Collections:[機械與機電工程學系暨研究所] 學位論文

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