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研究生:沈思瑜
研究生(外文):Szu-Yu Shen
論文名稱:改良式的多分類器路面辨識應用於遠端呼叫自走車的導航研究
論文名稱(外文):Study on an Improved Multi-Classifier Road Detection Applied to Navigation of Automatic Land Vehicle through Remote Calling
指導教授:駱榮欽駱榮欽引用關係
指導教授(外文):Rong-Chin Lo
口試委員:林啟芳王振興
口試委員(外文):Chi-Fang LinJenn-Shing Wang
口試日期:2011-07-26
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電腦與通訊研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:52
中文關鍵詞:電腦視覺影像處理自動導航車AdaBoost多分類器
外文關鍵詞:Computer VisionImage ProcessingAutomatic Land VehicleAdaBoostMulti-Classifier
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  • 被引用被引用:1
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本研究提出一種能遠端呼叫自動導航車(ALV)的架構。首先,呼叫端經由無線網路傳送目的地之GPS訊息予ALV,藉由已知的地圖資訊,以迪杰斯特拉演算法進行路徑規劃。行進中所需要的路面資訊,使用AdaBoost演算法來進行路面辨識,對不同的路面種類進行訓練和分類,可找到可行進的路面區域。藉著路面辨識的結果,ALV可決定一個行進方向。由路徑的資訊取得目標子節點的位置以及自動車目前位置的差異,可找到該行進的絕對方向,而與電子羅盤偵測到的車輛行進方向比較,可找到車輛該偏轉的方向。而往目標前進時,以繞道閃避的方式避開AdaBoost找出的非路與立體障礙物。藉由此流程,自動車可到達呼叫端的位置。

This research proposes a technique of calling an ALV remotely. Firstly, the calling side sends the GPS information of the target to the ALV through wireless network, then path planning is completed by prepared map data with Dijkstra algorithm. AdaBoost algorithm is introduced for implementing road detection; different types of classifiers are trained to detect different road surfaces. With the result of road detection, the ALV is able to find the drivable region eliminating the obstacles and not-road region. By determining the difference with the position of the ALV and current sub-goal on the planned path, the forward direction to the sub-goal is decided; with comparing it to the driving direction detect by digital compass, the direction of deflection can be decided. When ALV drives to the sub-goal, obstacles and not-road region is avoided by surpass. In conclusion, ALV can reach the calling side.

ABSTRACT IN CHINESE i
ABSTRACT IN ENGLISH ii
ACKNOWLEDGMENTS iii
TABLE OF CONTENTS iv
LIST OF TABLES vi
LIST OF FIGURES vii
CHAPTER 1 INTRODUCTION 1
1.1 Research Motivation 1
1.2 Survey of Related Research 2
1.2.1 Road Detection 2
1.2.2 Autonomous Vehicle Guidance Methods 2
1.2.3 Wireless Control 2
1.3 Overview of Proposed Approaches 3
1.4 Thesis Organization 6
CHAPTER 2 ALV HARDWARE ARCHITECTURE 7
2.1 Overview of ALV 7
2.2 Camera and GPS Receiver 8
CHAPTER 3 ROAD DETECTION ON ADABOOST ALGORITHM 9
3.1 AdaBoost Algorithm 9
3.2 Weak Classifiers 12
3.2.1 Hue 12
3.2.2 Saturation 13
3.2.3 Entropy 14
3.2.4 Moments 15
3.2.5 Smoothness 16
3.3 Final Strong Classifier 18
CHAPTER 4 NAVIGATION STRATEGY 20
4.1 Wireless Remote Calling 20
4.2 Path Planning 22
CHAPTER 5 DECISION OF DRIVING DIRECTION 27
CHAPTER 6 EXPERIMENTAL RESULTS 30
6.1 Results of Road Detection 30
6.2 Decision of Driving Direction 43
CHAPTER 7 CONCLUSION AND FURTHER RESEARCH 45
7.1 Conclusion 45
7.1.1 Road Detection 45
7.1.2 ALV Navigation 45
7.2 Further Research 46
REFERENCES 47
APPENDIX 49
APPENDIX A.1 Proof of Equation 4.2 50

[1]Jia Liu, Zheying Li, Huan Zhang, Caixia Lv, “A Vision-Based Road Recognition Algorithm,” in 3rd IEEE Conference on Industrial Electronics and Applications, 2008, pp. 284-287.
[2]Hui Kong, Jean-Yves Audibert, and Jean Ponce, “General Road Detection From a Single Image,” in IEEE Transactions on Image Processing, 2008 pp, 2211-2220.
[3]Yaniv Alon, Andras Ferencz and Amnon Shashua, “Off-road Path Following using Region Classification and Geometric Projection Constraints,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, 2006, pp. 689-696.
[4]Sung-Soo Kim and Jong-Hyun Lee, “A study on design of dynamic route guidance system using forecasted travel time based on GPS data and modified shortest path algorithm,” in Proc. IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems, 1999, pp. 44-48.
[5]Bing Liu, Siew-Hwee Choo, Shee-Ling Lok, Sing-Meng Leong, Soo-Chee Lee, Foong-Ping, and Poon Hwee-Har Tan, “Integrating case-based reasoning, knowledge-based approach and Dijkstra algorithm for route finding,” in Proceedings of the Tenth Conference on Artificial Intelligence for Applications, 1994, pp. 149-155.
[6]Wen Cao, Hui Shi, Shulong Zhu, and Baoshan Zhu, “Application of an Improved A* Algorithm in Route Planning,” in WRI Global Congress on Intelligent Systems, 2009, pp. 253-257.
[7]Kar-Keung D. Young, Yong Quan Ou, Jun Tao Feng, Zhi Liang Ou, Lun Hui Cai, Ken Kin Man Cheng, Jason Kam On Ho, Timmy T M Tsang, “Automated navigation and mobile vehicle control using wireless sensor network technology,” in IEEE International Conference on Industrial Technology, 2008.
[8]Yoav Freund and Robert E. Schapire, “Experiments with a New Boosting Algorithm,” in Proc. 13th Int''l Conf. Machine Learning, 1996, pp. 148-156.
[9]Ming-Kuei Hu, “Visual Pattern Recognition by Moment Invariants,” IRE Transactions on Information Theory, 1962, pp. 179-187.
[10]Shuai Yuan and YingLi Tian, “Rotation and Illumination Invariant Texture Analysis,” in International Congress on Image and Signal Processing, 2010, pp. 2643-2647.
[11]Ming-Kuei Hu, “Visual Pattern Recognition by Moment Invariants,” IRE Transactions on Information Theory, 1962, pp. 179-187
[12]DU Yanwei, “Research on Path Planning of Materials Supply of Lean Production Based on the Dijkstra Algorithm,” in 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), 2010, pp. 692-695.
[13]OpenCV: http://www.opencv.org.cn/
[14]RGB to HSV: http://www.shervinemami.co.cc/colorConversion.html
[15]Calculation of GPS: http://en.wikipedia.org/wiki/Great-circle_distance
[16]Calculation of GPS: http://en.wikipedia.org/wiki/Haversine_formula

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