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研究生: 傅啟文
Chei-Wen Fu
論文名稱: 居家型機器人室內地圖之建構
Design of Indoor Map for Home-based Robot
指導教授: 曾煥雯
Tzeng, Huan-Wen
學位類別: 碩士
Master
系所名稱: 電機工程學系
Department of Electrical Engineering
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 85
中文關鍵詞: 方格地圖地圖建構移動機器人電子羅盤超音波感測器
英文關鍵詞: Grid map, Mobile robot, Ultrasonic sensor, Electronic compass, Direction
論文種類: 學術論文
相關次數: 點閱:134下載:8
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  • 本論文所提出來以方格的方式來建構地圖在此稱方格地圖,本研究之移動機器人搭載超音波感測器在空間上作偵測,將環境中的狀態作記錄,例如:自由空間、障礙物空間、未行走過的空間,以及利用電子羅盤偵測地磁的特性,辨識方向擷取建構地圖之重要資訊,移動機器人在行走時也可以隨時作角度補償。

    本論文所提出方格地圖是利用超音波所擷取特徵點,再將特徵點歸納在特徵點所屬的區域範圍之間,可以有效讓機器人在室內環境之中行動時避免不必要之碰撞及解決解析度高而造成數據龐大之問題,並且可以有效作為引導基準,最後提出準確度與信賴度來做系統評估。

    The paper proposes a method by grid to constructed the map, here we called “Grid Map”. Our mobile robot installation the ultrasonic sensor to detects environment. Here we list some examples for state the environment for record below: Free space, Occupies space, Un-pass Space. Also, use electronic compass to detect magnetic properties and identify the direction. Therefore, the angle will be compensation when the robot is moving.

    The grid map is using feature point for clustering feature. And then, generalize feature point in grid of region. During this research, the “Grid Map” is using to solve the problem of high dip to cause the huge statistics, but also can be basis of guidance. To achieve the robot can move arbitrarily in the indoor environment. Therefore, the paper proposes state accuracy and reliability to evaluate.

    摘 要 ...................................I ABSTRACT ...............................II 謝 誌 .................................. III 目 錄 ................................... IV 圖目錄 .................................. VII 表目錄 .................................. XI 第一章 緒論 ............................. 1 1.1 研究背景與動機 ....................... 1 1.2 研究目的 ............................ 1 1.3 研究方法 ............................ 2 1.4 研究限制 ............................ 2 1.5 研究步驟 ............................ 3 第二章 文獻探討與回顧 ....................5 前言 ................................... 5 2.1 相關研究 ............................ 6 2.2 超音波感測器 ......................... 9 2.2.1 超音波簡介 ......................... 9 2.2.2 超音波原理 ......................... 9 2.2.3 超音波物理模型與測量原理 ............11 2.2.4 超音波檢測方式介紹 ..................14 2.2.5 超音波之應用 ....................... 14 2.3 電子羅盤 ............................ 15 2.3.1 電子羅盤介紹 ....................... 15 2.3.2 電子羅盤原理 ....................... 15 2.4 地圖建立 ............................ 17 第三章 系統架構與分析 .....................23 3.1 機器人系統架構與設計 ..................23 3.1.1 感測器比較 ..........................23 3.1.2 機器人架構 ..........................24 3.1.3 移動機器人運動方程式 ................26 3.1.4 超音波配置 ..........................29 3.1.5 機器人邊尋模式 ......................30 3.1.6 系統架構 ...........................31 3.2 研究方法 .............................32 3.3 超音波偵測 ...........................33 3.3.1 特徵點與閃避障礙物偵測方式 ..........33 3.3.2 環境認知 ..........................34 3.3.3 障礙物閃避法則 .....................34 3.4 機器人方格規劃設計 ....................36 3.4.1 機器人移動方向與座標 .................37 3.4.2 方格地圖 ..........................39 3.4.3 空間狀態記憶 .......................39 第四章 機器人軟硬體環境 ....................44 4.1 電子羅盤 .............................44 4.2 Microcontroller模組 ..................45 4.3 指令脈波產生模組 ......................46 4.4 PV型伺服驅動器 ........................47 4.5 P5 伺服馬達 ..........................48 4.6 減速機 ...............................48 第五章 實驗結果與分析 .....................50 5.1 性能指標評估 ..........................50 5.2 研究實施與環境地圖建構之步驟 ..........51 5.3 環境測試與分析 ........................53 5.4 實驗環境規劃 ..........................55 5.5 實驗環境地圖建構 .......................57 5.5.1 Case1 環境 .........................57 5.5.2 Case2 環境 .........................62 5.5.3 Case3 環境 .........................66 5.5.4 Case4 環境 .........................69 5.6 性能指標評估 .........................72 5.6.1 性能指標評估Case1 與Case2 ..........72 5.6.2 性能指標評估Case3 ..................73 5.6.3 性能指標評估Case4 ..................74 5.6.4 環境建構時間與尺寸飽和區間 .........75 5.7 地圖擴充 .............................77 第六章 結論與後續研究 ....................79 6.1 結論 .................................79 6.2 後續研究 .............................79 參 考 文 獻 ..............................80 自 傳 ....................................85

    [1] P. D. Toledo and J. Silvia, “Telemedicine Experience for Chronic Care in COPD,”IEEE Transactions on information technology in biomedicne,vol.10, no. 3, pp. 567 - 573, july.2006.
    [2] D. Litvak ,“Fall Detection of Elderly through Floor Vibrations and Sound, ” 30th Annual International IEEE EMBS Conference Vancouver,British Columbia, Canada, August. 2008, pp. 4632 – 4635.
    [3] S. Srinivasan, H. Jun, Dhananjay Lal and Aca Gacic, “Towards Automatic Detection of Falls Using Wireless sensors,” Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale, Lyon,
    France August. 2007, pp.1379 - 1382.
    [4] H. Bin, T. Guohui and W. Hao, “A Method for Fast Fall Detection Based on Intelligent Space,” Proceedings of the IEEE International Conference on Automation and Logistics Qingdao, China September 2008, pp. 2260 - 2265.
    [5] P. Sunhong and H. Shuji, “Autonomous Mobile Robot Navigation Using Passive RFID in Indoor Environment,” IEEE Transactions on Industrial Electronics, vol. 56, no.7, pp.2366 – 2373, July 2009.
    [6] F. Atsushi and N. Peter, “Adaptive Navigation of Mobile Robots with Obstacle Avoidance,” IEEE Transactions on Robotics and Automation,vol.13, no.4, pp. 596 – 601, august 1997.
    [7] O. Noureddine, O. Lamine and H. Mustapha, Implementation of an Oriented Positioning on a Car-Like Mobile Robot by Fuzzy Control,”IEEE Industrial Electronics, Iecon 2006, pp. 4076 - 4081.
    [8] A. Balza and K. M. Noh , “Visual-Based Fuzzy Navigation System for Mobile Robot: Wall and Corridor Follower,” International Conference on Lntelligent and Advanced Systems, 2007, pp. 244 - 248.
    [9] N. Nicolas, M. Cesar and F. Wolfgang, ”Acquiring Adaptive Behaviors of Mobile Robots Using Genetic Algorithms and Artificial Neural Network,”Proceedings of the Electronics, Robotics and Automotive Mechanics Conference IEEE, vol.1, 2006, pp. 87 - 91.
    [10] P. Korondi, H. Hashimoto, “Intelligent Space, as an Integrated Intelligent System,” Keynote paper of International Conference on Electrical Drives and Power Electronics, Proceedings, 2003, pp. 24-31.
    [11] P. T. Szemes, “Human Observation-based Motion Control Strategies in Intelligent Space,” PhD Thesis, Tokyo, 2005.
    [12] T. Kamegawa, K. Saikai, S. Suzuki and A. Gofuku, “Development of grouped rescue robot platforms for information collection in damaged buildings,” The University Electro-Communications, Japan, SICE Annual Conference 2008 August 20-22, 2008, pp. 1642 - 1647.
    [13] K. Hayashi, Y. Yokokohji, and T. Yoshikawa, “Tele-existence Vision System with Image Stabilization for Rescue Robots,” Proceedings of the 2005 IEEE International Conference on Robotics and Automation Barcelona, Spain, April 2005, pp. 50 - 55.
    [14] Graduate School, College of Scienceand Technology, “Research on Rescue Robot swith Force Sensors on the Fingertips for Rubble Withdrawal Works,” The University Electro-Communications, Japan, SICE Annual Conference 2008 August 20-22, 2008,pp. 1947 - 1950.
    [15] W. C. Vie and Y. UKAI , “Development of a USAR Robot Considering Camera View Angle and Grouser Shape of Crawler,” Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics Bangkok, Thailand, February 2009, pp. 1991 - 1994.
    [16] 鄭振東,超音波工程,臺北市:全華科技圖書股份有限公司,民92。
    [17] P. N. Wells, Biomedical Ultrasonic. New York: Academic Press, 1977.
    [18] C. B. Chen and J. H Chou, “A Corner Differentiation Algorithm by a Single Sonar Sensor for Mobile Robots,” Asian Journal of Control, 2008,vol. 10, no.4, July 2007, pp.62 - 66.
    [19] L. Yen, C. Y. Lee and S. R. Lee, “Building Map Using Peak Amplitude of Sonar Echoes,” SICE-ICASE international joint Conference , 2006 Oct,pp.1692 - 1696.
    [20] 林永儒,”室內型導覽機器人之系統設計”,國立臺灣師範大學,碩士論文,民98。
    [21] L. Kyoungmin and C. W. Kyun, “Effective Maximum Likelihood Grid Map With Conflict Evaluation Filter Using Sonar Sensors,” IEEE Transactions on Robotics, vol. 25, no. 4, pp.887 – 901, 2009.
    [22] H. Quijano and L. Garrido, “Improving Cooperative Robot Exploration Using an HexagonalWorld Representation,” Electronics Robotics and Automotive Mechanics Conference 2007, Cerma 2007, pp.450 - 455.
    [23] S. M. Jeong, T. H. Song, J. H. Park and J. W. Jeon, “The Local Minimum Escape using The Grid Map,” Proceedings of IEEE International Conference on Multi sensor Fusion and Integration for Intelligent Systems Seoul, Korea, August 2008, pp. 378 - 383.
    [24] B. Barshan and R. Kuc, “Differentiating Sonar Reflections from Corners and Planes by Employing an Intelligent Sensor,” IEEE Transactions on
    83 Pattern Analysis and Machine Intelligence, vol. 12, no.6, pp. 560-569, 1990.
    [25] I. Zoltán and S. Péter, “Robot Navigation Framework Based on Reinforcement Learning for Intelligent Space,” 2008, pp. 761 - 766.
    [26] A. Mohammad ,J. Kareem and L. Reza, “Line Map Construction using a Mobile Robot with a Sonar Sensor,” Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics Monterey,California, USA, July 2005, pp.1251 - 1256.
    [27] M. Tomono, “3-D Object Map Building Using Dense Object Models with SIFT-based Recognition Features,” Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems October 9 - 15, 2006, pp. 1885 - 1890.
    [28] D. F. Wolf and G. S. Sukhatme, Senior Member, “Semantic Mapping Using Mobile Robots,” IEEE Transactions on Robotics, vol. 24, no. 2,pp.245 – 258, 2008.
    [29] V. Harmandas, M. Sanderson, and M. D. Dunlop, “Image Retrieval by Hypertext Links,” in Proc. Int. Conf. Res. Dev. Inf. Retr.,1997,pp.296–303.
    [30] M. D. Klemen, E. R. Weippl, and A. M. Tjoa, “The semantic desktop:A semantic personal information management system based on RDF and topic maps,” in Proc. Workshop Ontol.-Based Tech. DataBases Inf. Syst,2005, pp.135–151.
    [31] N. Rishe, “Efficient Organization of Semantic Databases,” in Proc.Int.Conf. Found. Data Org. Algorithms, 1989, pp.114–127.
    [32] H. Zhuge, “Retrieve Images by understanding Semantic Links and clustering Image Fragments,” J. Syst. Softw. Arch., vol.73, no.3, pp.455–466, 2004.
    [33] 黃信益,“基於行為模式之家用機器人導航設計”,國立交通大學電機與控制工程學系,碩士論文,民92。
    [34] 宋佩栩,“一個使用環境攝影機並結合個人資訊的客製化跌倒偵測系統”,中原大學電子工程學系,碩士論文,民95。
    [35]http://taiwan.cnet.com/crave/0,2000088746,20142980,00.htm
    [36]http://zh.wikipedia.org/zh-tw/File:Hall_effect.png
    [37]http://www.libertytimes.com.tw/2009/new/nov/17/today-t3.htm
    [38]http://chinese.engadget.com/2009/09/13/riba-the-first-robot-nurse-in-japan

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