本論文利用FPGA開發板結合雙CMOS影像感測模組，建立一組立體視覺距離感測系統，輔助自走車進行自動停車。由雙鏡頭輸入成對的影像，經過影像處理偵測出停車格的兩個特徵點，利用立體影像三角成像原理計算出兩特徵點與自走車的距離。在將此兩段距離透過餘弦定理算出自走車與停車格的移動距離，包括轉角、水平距離與垂直距離，接著進行自動停車。將自走車之馬達以閉迴路速度控制方式，讓移動機器人自動駛入停車格內。

This thesis aims to utilize a FPGA development platform with two CMOS image sensors to build a stereo vision distance estimation system to assist mobile robot’s automatic parking task. Two characteristic points of the parking space are detected by a pair of images from two CMOS image sensors. The distances between the two individual characteristic points and the mobile robot are calculated with the triangular perspective theory of the stereo vision respectively. Then, by using cosine theorem, the data of these two distances will be converted to a motion path for the mobile robot to carry out the automatic parking task, including angle, horizontal distance and vertical distance. Furthermore, the wheel of the mobile robot is controlled by close loop speed control. To sum up, with both the necessary path and the motor mentioned above, the mobile robot can automatically park itself into the target space with some success.

[1]J. H. Jean, T. P. Wu, J. H. Lai, and Y. C. Huang, “A Visual Servo System for Object Tracking Applications of Mobile Robots Based on Shape Features,” Proceedings of 2005 CACS Automatic Control Conference Tainan, Taiwan, Nov 18-19, 2005.
[2]A. Lipton, H. Fujiyoshi and R. Patil, “Moving Target Classification and Tracking from Real-time Video,” In Proc. IEEE Workshop on Application of Computer Visio, Princeton, NJ, 1998.
[3]K. P. Hom, B. G. Schunck, “Determining Optical Flow,” Artifical Intelligence, Vol.17, pp. 185-203, 1981.
[4]Marr, D. and Poggio, T. “Cooperative Computation of Stereo Disparity,” Science, Vol. 194, pp. 283-287, 1976.
[5]Barnard, S. T. and Thompson, W. B., “Disparity Analysis of Images,” IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 2, pp. 330-340, 1980.
[6]Tsai, R. Y., “A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the Shelf TV Cameras and Lenses,” IEEE J. of Robotics and Automation, Vol. RA-3, No. 4, pp. 323-344, 1987.
[7]Izaguirre, A., Pu, P., and Summers, J., “A New Development in Camera Calibration: Calibrating a Pair of Mobile Cameras,” Int. J. Robotics Res., Vol. 6, No. 3, pp. 104-116, 1987.
[8]Yau, W. Y. and Wang, H., “Fast Relative Depth Computation for an Active Stereo Vision System,” Real-Time Imaging, Vol. 5, pp. 189-202, 1999.
[9]A. M. Muad, A. Hussain, S. A. Samad, M. Marzuki and B. Y. Majlis, “Implementation of Inverse Perspective Mapping Algorithm for the Development of and Automatic Lane Tracking System,” TENCON 2004, Vol. 1, Nov. 2004, pp. 207-210.
[10]Murray D., Little J., “Using Real-time Stereo Vision for Mobile Robot Navigation,” Autonomus Robots, 8(2):161-171, 2000.
[11]M. Bertozzi, A. Broggi, “GOLD: a Parallel Real-time Stereo Vision System for Generic Obstacle and Lane Detection,” IEEE Transactions on Image Processing, Vol. 7. No. 1, pp. 62-81, 1998.
[12]Kazuhiro Shimizu, Shinichi Hirai, “Implementing Planar Motion Tracking Algorithm on CMOS+FPGA Vision System,” IEEE International on Intelligent Robots and Systems, pp. 1366-1371, 2006.
[13]任紹棟, “具立體視覺測距之移動機器人,” 碩士論文, 國立台灣科技大學電機工程系, 民國96年7月.
[14]周立達, “永磁同步馬達速度控制場效可規劃邏輯陣列硬體電路設計,” 碩士論文, 國立台灣科技大學電機工程系, 民國97年7月.
[15]鐘國亮, “影像處理與電腦視覺,” 東華書局, 台北市, 1999年9 月.
[16]Ming-Bo Lin, “Digital System Design and Practices: Using Verilog HDL and FPGAs,” Wiley, 2008.