本研究主要目的在使用即時影像處理技術應用於物體辨識與追蹤，並設計製作一無線遙控自走車測試本研究的影像處理技術。自走車分為五個次系統，分別為結構及動力驅動次系統、環境感測次系統、無線傳輸次系統、影像處理次系統、微控制器數據處理次系統，結合五個次系統與基地台電腦端，透過無線傳輸的方式，做物體判別與控制命令的判斷。在追蹤的過程之中，為了快速處理大量的影像資料，自走車CCD將獲得的環境影像資訊，經由無線傳輸回基地台做影像處理，如此將每一張的影像圖片經過計算之後便能得知追蹤物體與自走車之間的相對位置關係。自走車控制器的設計是以模糊邏輯為基礎的控制器，在電腦端運算之後透過無線傳輸的方式傳送至自走上車的微控制器處理晶片來執行計算行動。從Matlab軟體的模擬與硬體實驗，均能成功的追蹤到目標物，顯示所提出的概念有助於工程上的應用。

The main purpose of this research is to investigate the use of a real-time image processing technique applied in tracking a specified object. A remotely controlled robot-car is also designed and implemented to test the technique. Five subsystems, structure and drive transmission, environmental detection, wireless communication, image processing, and micro-controller and data handling subsystem are integrated on the robot-car, which links to a desktop personal computer through FM radio equipment for object identification and control command determination. To start the tracking, the robot-car on-board CCD acquires enviromental images and transfer them back to PC in order to evaluate large quantity of data as fast as possible. Then each image frame is processed to identify the tracking object and the relative motion between the robot-car and the object. The robot-car drive controller formulated with fuzzy logic is also placed on PC and its command is transfered back to robot-car with wireless transmittor and direct the robot-car through a micro-processor to execute computed motion. Successful tracking results from simulation with Matlab software and hardware experiment show that the proposed concept can be useful in engineering application.

參考文獻
[1] Kai-Tai Song and Liang-Hwang Sheen,”Fuzzy-nero control design for
obstacle avoidance of a mobile robot”,IEEE Int. Conf. On Fuzzy System,
Vol.12. No.4 pp447-465, August 2004
[2] 許哲源，”自走車之驅動控制與避障規劃，”國立成功大學工程科學系碩士論文，
2003
[3] 陳巧音，”小型自走車以超音波避障之研究，” 國立成功大學工程科學系碩士論文，
2002
[4] Iluminada Baturone, Francisco J. Moreno-Velo, Santiago Sanchez-Solano, and
Anibal Ollero,”Automatic Design of Fuzzy Controller for Car-Like
Autonomous Robots”,IEEE Trans. On Fuzzy System, Vol. 12.No.4 pp447-
465,August 2004
[5] Tzuu-Hseng S.Li, and Shih-Jie Chang, ”Autonomous Fuzzy Parking Control of
a Car-Like Mobile Robot”, IEEE Trans. On Fuzzy System,Vol.33,No.4,pp451-
465,July 2003.
[6] Akira Ohata , and Masahiro Mio,”Parking Control Based On Nonlinear
Trajectory Control For Low Speed Vechicles”, IECON Int . Conf.,
Vol.1,pp107-112,October 1991.
[7] 蘇裕記，”以FPGA晶片實現智慧型車庫停車控制系統，”國立成功大學電機工程系碩
士論文，1999
[8] 簡卓建，”應用模糊控制於自走車路徑導引避障之整合設計，”國立成功大學航空太
空工程研究所碩士論文，2003
[9] 王建清，”無線遙控智慧型自走車之設計製作應用於平行泊車實驗”， 國立成功大學
航空太空工程研究所碩士論文，2005
[10] G.G Rigatos, S.G. Tzafestas and G.J. Evangelidis, “Reactive Parking
Control of Nonholonomic Vehicles Via a Fuzzy Learning Automaton,” IEEE
Proc.-Control Theory Apply, Vol.48, No.2,pp169-179,March 2001.
[11] Ching-Wen Cheng, Shih-Jie Chang, and Tzuu-Hseng S. Li, ”Parallel-Parking
Control of Autonomous Mobile Robot” ,IECON Int.Conf., Vol1.3,pp1305-
1310,Nov.1997.
[12] Y.K. Lo, A.B. Rad,C.W. Wong and M.L. Ho ”Automatic Parallel Parking,
“Intelligent Trans. System, Vol.2,pp12-15,October 2003.
[13] 李宗勳，”應用FPGA晶片實現車型機器人之智慧型路邊停車控制之研究，”國立成功
大學電機工程學系碩士論文，1999
[14] 陳意翔，”具智慧型停車功能車型機器人之設計與研究，” 國立成功大學電機工
學系碩士論文，2001
[15] 張世傑，”用於車型機器人之模糊停車控制法的設計與實現，” 國立成功大學電機
工程學系碩士論文，2002
[16] Simon X. Yang, Ho Li, Max Q.-H. Meng, and Peter X. Liu “An Embedded
Fuzzy Cintroller for a Behavior-Based Mobile Robot With Guaranteed
Performance,” IEEE Trans. On Fuzzy System, Vol.12, No.4,pp436-446,August
2004.
[17] Tzuu-Hseng S. Li, Member, IEEE,Shih-Jie Chang, and Wei Tong, “Fuzzy
Target Tracking Control of Autonomous Mobile Robots by Using Infrared
Sensors,” IEEE Trans. On Fuzzy System, Vol.12,No.4,August 2004
[18] 魏光群，”無線導引微晶片控制巡蹤自走車之研製”， 國立成功大學航空太空工程
研究所碩士論文，2003
[19] 江正偉，”智慧型避障追蹤電動車控制系統之設計與研究”， 國立成功大學航空太
空工程研究所碩士論文，2000
[20] Leese, J. A., Novak, C. S., and Taylor, V. R. “The Determination of
Cloud Motion Patterns from Geosynchronous Satellite Image Data”, Patter
Recognition, Clustering, Statistic, Grammars, Learning, Vol.2 pp272-
292,1970
[21] Horn, K. P. and B. G.. Schunck,”Determining optical flow”, Artificial
Intelligence, Vol.17,pp185-203,1981
[22] Fuh, C. S. and Maragos P.,”Region-Based Optical Flow
Estimation”,Proceedings of IEEE Conference on Computer Vision and attern
Recognition, San Diego, CA, pp130-133,1989
[23] O. Masoud, and N.P. Papanikolopoulos, “ A Novel Method for Tracking and
Counting Pedestrians in Real-Time Using a Single Camera,” IEEE Trans. On
Vehicukar Technology, Vol. 50, no. 5, pp1267-1278, Set. 2001
[24] S. Birchfield, “Elliptical Head Tracking Using Intensity Gradients and
Color Histograms, “ IEEE Computer Society Conference on Computer Vision
and Pattern Recognition, pp232-237,June 1998.
[25] Zedeh,L.A.,”Fuzzy Sets”, Inform. Control, Vol.8,pp338-353,1965.
[26] Mamdani,E.H”,An Experiment in Linguistic Synthesis with a Fuzzy Logic
Control,”Int.Journal of Human-Computer Studies,Vol.51,pp135-
147,August 1999.
[27] 陳熹隸, 全華科技圖書股份有限公司, “步進馬達應用技術”, 1989
[28] 逸塵,艾倫 , 金禾資訊股份有限公司,”8051單晶片教學範本,2003
[29] 繆紹綱, 全華科技圖書股份有限公司, “數位影像處理 活用Matlab”,2004
[30] 繆紹綱 編譯, 普林斯頓國際有限公司,”Digital Image Processing 2/e