本論文提出在室內環境中居家保全機器人之障礙物偵測與障礙物規避之即時影像處理方法，同時可透過網際網路監控居家保全機器人以了解家中狀況。整個系統不僅居家保全機器人可以自動導航巡邏而且可以透過VB技術將所探測的影像顯示在遠端使用者之監控網頁上。本論文主要應用影像處理技術，包括邊緣偵測、均值濾波、侵蝕及擴張等影像處理方法，找出環境中實際的障礙物，並求出障礙物相對於居家保全機器人的角度位置。在自動導航過程中，以自我定位的方式做路徑規劃，藉由編碼器回授得知居家保全機器人的位置及角度，並在巡邏過程中閃避環境中的障礙物避免碰撞，以完成室內巡邏的工作。另外，針對以遠端監控居家保全機器人之系統架構，包含VB技術與影像傳輸技術之設計實現均詳述之。最後，我們將藉由電腦模擬及實際實驗之結果，來驗證所提方法之效益及適用性。

This thesis proposes a real-time image processing approach for obstacle detection and avoidance while navigating an e-Home robot in an indoor environment. Moreover, we can monitor the home security condition by internet-based remote control. The whole system not only guides the robot to patrol automatically but also gets the security information and shows the images by VB techniques to the web browser of the remote client. The theorem and application of image processing technique are introduced, where the edge-detect, average filter, erosion and dilation methods. will be utilized to find out the obstacle and compute the angular position of the detected obstacle related to e-Home robot in the corridor. We adopt the self-localization method integrated by encoder data as the posture feedback during the autonomous navigation, and plan a collision-free path to complete the patrol routine. The remote control system developed in the networked vehicle including VB techniques and image transmission will be also described in detail. Finally, both simulations and the practical experiments demonstrate the feasibility and effectiveness of the proposed schemes.

中文摘要Ⅰ
英文摘要Ⅱ
致謝Ⅲ
目錄Ⅳ
圖目錄Ⅵ
第一章 緒論1
1.1前言1
1.2機器人之發展概況2
1.3文獻回顧3
1.4研究動機與目的6
1.5論文規劃7
第二章 居家保全機器人之軟硬體架構8
2.1 硬體系統9
2.2 影像辨識系統11
2.3 驅動系統13
2.4 電力系統14
2.5 遠端監控系統15
2.6 軟體系統介紹15
2.7 本章總結17
第三章 居家保全機器人之影像處理與導航18
3.1 二值化影像分析19
3.2 線性濾波器21
3.3 標記(Labeling)23
3.4 邊緣偵測25
3.4.1 邊緣偵測演算法的基本步驟26
3.4.2 Sobel運算子27
3.5 數學型態學29
3.6 居家保全機器人之影像處理33
3.7 運動方程式(Kinematic Equation)42
3.8 本章總結45
第四章 遠端監控及實驗結果46
4.1 VB網頁程式設計46
4.2 實驗結果53
第五章 居家保全機器人之模擬與實現55
5.1 障礙物規避之路徑模擬55
5.2 居家保全機器人整體實驗結果60
5.3 本章總結65
第六章 結論與未來展望66
6.1 結論 66
6.2 未來展望67
參考文獻68

1.H. Mori, S. Kotani and N.Kiyohiro, “A Robotic Travel Aid “HITOMI”,” Proc. IEEE/RSJ/GI International Conference on Intelligent Robots and System, Vol.3, pp.1716-1723, 1994.
2.S. Hayati, “The Rocky 7 Rover: A Mars Science craft Prototype,” Jet Propulsion Laboratory, California Institute of Technology, International Conference on Robotics and Automation, April 1997.
3.D. Jung and A. Zelinsky, “Whisker Based Mobile Robot Navigation,” IEEE/RSJ International Conference, Vol.2, pp.497-504, 1996.
4.M. Hashima and F. Hasegawa, “Localization and Obstacle Detection for a Robot for Carrying Food Trays,” IRSO 97 0-7803-4119-8/97, IEEE, 1997.
5.E. M. Petriu, “Automated Guided Vehicle with Absolute Encoded Guide-path,” IEEE Transactions on Robotics and Automation, Vol.7, No.4, pp.562-565, 1991.
6.J. Borenstein and Y. Koren, “Histogramic In-motion Mapping for Mobile Robot Obstacle Avoidance,” IEEE Transactions on Robotics and Automation, Vol.7, No.4, pp.535-539, 1991.
7.A. P. Tirumalai, B. G. Schunck and R. C. Jain, “Evidential Reasoning for Building Environment Maps,” IEEE Transactions on Systems, Man, and Cybernetics, Vol.25, No.1, pp.10-20, 1995.
8.D. Pagac, E. M. Nebot and D. W. Hugh, “An Evidential Approach to Map-building for Autonomous Vehicles,” IEEE Transactions on Robotics and Automation, Vol.14, No.4, pp.623-629, 1998.
9.G. Beccari, S. Caselli, F. Zanichelli and A. Calafiore, “Vision-based Line Tracking and Navigation in Structured Environments,” IEEE Computational Intelligence in Robotics and Automation, pp.406-411, 1997.
10.F. M. Pan and W. H. Tsai, “Automatic Environment Learning and Path Generation for Indoor Autonomous Land Vehicle Guidance Using Computer Vision Techniques,” Proc. of Nat. Comput. Symp. ’93, Chiayi, Taiwan, pp.311-321, 1993.
11.W. H. Lee, K. S. Roh and I. S. Kweon, “Self-localization of Mobile Robot without Camera Calibration Using Projective Invariants,” pattern recognition letters Vol.21, pp.45-60, 1999.
12.Y. Yagi, H. Nagai, K.Yamazawa and M. Yachida, “Reactive Visual Navigation Based on Omnidirectional Sensing-path Following and Collision Avoidance,” Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol.1, pp.58-63, 1999.
13.Y. Yagi, S. Kawato and S. Tsuji, “Real-Time Omnidirectional Image Sensor (COPIS) for Vision-Guided Navigation,” IEEE Trans. Robotics and Automation, Vol.10, No.1, pp.11-22, 1994.
14.C. Roman and C. Reinholtz, “Robust Course-boundary Extraction Algorithms for Autonomous Vehicles,” IEEE Intelligent Systems, pp.32-38, Nov. 1998.
15.R. R. Murphy, “Sensor and Information Fusion for Improved Vision-based Vehicle Guidance,” IEEE Intelligent Systems, pp.49-56, Nov. 1998.
16.A. Ohya, A. Kosaka and A. Kak, “Vision-based Navigation by a Mobile Robot with Obstacle Avoidance using Single-Camera Vision and Ultrasonic sensing,” IEEE Transactions on Robotics and Automatic, Vol.14, No.6, pp969-978, 1998.
17.S. R. Kyoung and H. L. Wang, “Obstacle Detection and Self-localization without Camera Calibration using Projective Invariant,” Proc IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol.2, pp.1030-1035, 1997.
18.G. S. Young, T. H. Hong, M. Herman and J. C. S. Yang, “New Visual Invariant for Obstacle Detection Using Optical Flow Induced from General Motion,” Proc IEEE Workshop on Applications of Computer Vision, pp.100-109, 1992.
19.T. Suzuki and T. Kanada, “Measurement of Vehicle Motion and Orientation Using Optical Flow,” Proc IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems, pp.25-30, 1999.
20.A. Giachetti, M. Campani and V. Torre, “The use of Optical Flow for Road Navigation,” IEEE Trans. on Robotics and Automation, Vol.141, pp.34-48, 1998.
21.X. Yuan, Z. Hu, J. Chen, R. Chen and P. Liu, “Online Learning and Object Recognition for AUV Optical Vision,” Proc. IEEE International Conference on System, Vol.6, pp.857-862, 1999.
22.Y. K. Hwang and N. Ahuja, “A potential field approach to path planning,” IEEE Transactions on Robotics and Automation, Vol.8, No.1, pp.23-32, Feb. 1992.
23.Y. H. Liu and Suguru Arimoto, “Path planning using a tangent graph for mobile robots among polygonal and curved obstacles,” Int. J. Robotics Research, Vol.11, No.4, pp.376-382, Aug. 1992.
24.J. C. Latmobe, Robot Motion Planning, Kluwer Academic Publishers, 1991.
25.C. J. Taylor and D. J. Kriegman, “Vision-based Motion Planning and Exploration Algorithms for Mobile Robots,” IEEE Trans. on Robotics and Automation, Vol.14, No.3, pp.417-426, June 1998.
26.A. Kosaka, M. Meng and A. C. Kak, “Vision-guided Mobile Robot Navigation Using Retroactive Updating of Position Uncertainty,” Proc. IEEE International Conference on Robotics and Automation, Vol.2 pp.1-7, 1993.
27.S. Maeyama, A. Ohya and S. Yuta, “Non-stop Outdoor Navigation of a Mobile Robot-retroactive Positioning Data Fusion with a Time Consuming Sensor System,” Proc. IEEE/RSJ International Conference on Intelligent Robots and System,Vol.1, pp.130-135,1995.
28.W. L. Xu and S. K. Tso, “Sensor-based Fuzzy Reactive Navigation of a Mobile Robot through Local Target Switching,” IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, Vol.29, No.3, pp.451-459, 1999.
29.K. C. Ng and M. M. Trivedi, “A Neuro-fuzzy Controller for Mobile Robot Navigation and Multirobot Convoying,” IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetic, Vol.28, No.6, pp.829-840, Dec. 1998.
30.D. Silva, I. N. Gomide and D. Amaral, “Navigation of Mobile Robots Using Fuzzy Logic Controllers,” IEEE International Workshop on Advanced Motion Control, pp.346-349, July 1998.
31.B. Y. Chee, Y. T. Lang and W. T. Tse, “Fuzzy Mobile Robot Navigation and Sensor Integration,” IEEE International Conference on Fuzzy Systems, Vol.1, pp.7-12, 1996.
32.L. G. Shapior and G. C. Stockman, Computer Vision, 1st Edition, 2001.
33.E. R. Dougherty and C. R. Giardina, Mathematical Methods for Artificial Intelligence and Autonomous Systems, Prentice-Hall, New Jersey, 1988.
34.R. M. Haralick and L. G. Shapiro, “Computer and Robot Vision,” Addison-Wesley, Reading, Massachusetts, Vol. 1, 1992, Vol. 2, 1993.
35.B. T. Mitchel and A. M. Gillies, A model-based computer vision system for recognizing handwritten ZIP codes, Machine Vision and Applications, 2(4):231-243, 1989.
36.http://www.irobot.com/
37.http://www.pioneernet.net/johnc/actuallydo.htm
38.林毅勳，“基於即時影像系統之自動導航車控制設計”，國立交通大學控制工程研究所，碩士論文，一九九七年，六月。
39.簡志昌，“在室內環境使用特殊號誌辨識技術作自動導航”，國立交通大學資訊科學研究所，碩士論文，一九九五年，六月。
40.王信義，“非規則性道路邊界偵測之彩色電腦視覺研究”，國立中正大學電機工程研究所，碩士論文，一九九七年，六月。
41.楊家俊，“以影像處理為基礎之看門狗機器人之設計與研製”，國立成功大學電機工程研究所，碩士論文，二零零二年，六月。
42.蔡昆華，“以電力線傳送之資訊家電控制系統之設計與實現”，國立成功大學電機工程研究所，碩士論文，二零零二年，六月。
43.蔡寶賢，“以DSP實現具室內導航控制功能之機器人及其居家保全之應用”，國立成功大學電機工程研究所，碩士論文，二零零二年，六月。
44.鄭吉泰，“居家型機器人之研製”，淡江大學電機工程學系，碩士論文，二零零二年，六月。
45.沈伸鴻，“遠端行動式保全系統之研發應用於多重感測保全機器人”，國立中正大學電機工程研究所，碩士論文，二零零二年，六月。
46.蕭賢德，“電腦視覺系統應用於自走車系統障礙物檢測之研究”，國立成功大學工程科學研究所，碩士論文，二零零零年，六月。
47.張正東，“結合影像及紅外線感測於自動導航車避障策略之設計”，國立台北科技大學電機工程學系，碩士論文，二零零一年，六月。
48.王志陽，“基於模糊類神經網路之自動導航車反應行為融合策略”，國立台北科技大學機電整合研究所，碩士論文，二零零零年，六月。
49.梁朝琪，“事件驅動式多代理者自走車導航系統”，國立成功大學工程科學研究所，碩士論文，二零零零年，六月。