自走車追跡系統之灰預測模糊控制研究

Research of Grey-Fuzzy Control for Autonomous Mobile Robot Lane Tracking System

江承祐(Cheng -You Jiang)

指導教授 ： 孫崇訓

淡江大學/工學院/機械與機電工程學系碩士班/碩士(2011年)

https://doi.org/10.6846/TKU.2011.00078

摘要

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。

關鍵字

灰色預測 ； 模糊控制

並列摘要

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.

並列關鍵字

Grey Prediction ； Fuzzy Controller

參考文獻

[6] 林伯彥，以機器視覺為基礎實現自走車車道追跡系統，淡江大學機械與機電工程學系碩士論文，民國99年。

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