最近幾年以來，機器人定位、以及導引系統的運用領域十分廣泛，如:無人駕駛汽車、自動倒車系統…等新穎的技術。空間定位有分為室內定位與室外定位，室外定位多數都是利用GPS系統進行定位，而室內定位則因GPS的衛星訊號無法在室內環境中取得，而產生各種相異的感測器定位系統，如:Wi-Fi感測器、RFID感測器、ZigBee感測器，以及近幾年最常使用的雷射測距儀(Laser Range Finder)。但這些利用感測器所進行的定位系統，價錢十分昂貴。故此，本研究主要目的為開發新的定位方式，利用QR code與2D平面地圖做結合。將2D平面地圖儲存資訊，如:座標點、位置名稱、環境比例尺、北極方向，再利用攝影機拍上環境中擺放的QR code，取得QR code的資訊並與2D平面地圖比對，判斷機器人目前位置。
由於機器人在進行導航移動時，常會因為地面傾斜等問題，造成移動偏離的現象，本研究機器人移動方式是利用Basic Stamp2微處理器與馬達控制器進行馬達轉速控制，並利用HM5883L電子羅盤校正機器人移動時所產生的偏離問題，使機器人就算遇到地面傾斜的狀況，也能適時修正馬達轉速，解決行走偏離問題。

In recent years, the robot localization and navigation system is widely used, like unmanned car, automatic reversing car system…etc. There are indoor localization and outdoor localization in space positioning, and some of people use GPS system to locate in the outdoor environment. The GPS satellite data couldn’t be received in the indoor environment, so people use different sensors to locate the positions, like Wi-Fi sensor, RFID sensor, ZigBee sensor, and the Laser Range Finder which is popularly used in recent year. But it cost much when using these kind of sensors to build the localization system. Therefore, the main purpose is to build a novel localization method in this research. The method is combined with QR code and 2D plane map and store the some information in the map. For example, coordinates, position, scaling factor for the environment, and the direction of North. We use the camera to capture QR code which is pasted in the environment. When receiving the information of QR code, we use them to compare with the map to get the current location of the robot.
When navigation in the tile floor, the robot would cause displacement moving. We use Basic Stamp2 microcontroller and motor controllers to control the motors rotation in the research. The HM5883L electrical compass is used to calibrate the displacement moving when the robot moving. After that, the robot would revise the speed of motors to solve the displacement moving problem in the tile floor.

[1] A. Ohya, et al., "Vision-based navigation by a mobile robot with obstacle avoidance using single-camera vision and ultrasonic sensing," IEEE Transactions on Robotics and Automation, vol. 14, pp. 969-978, Dec 1998.
[2] D. Herrero-Pérez, et al., "Fuzzy uncertainty modeling for grid based localization of mobile robots," International Journal of Approximate Reasoning, vol. 51, pp. 912-932, 2010.
[3] F. Michaud, et al., "Exploratory design and evaluation of a homecare teleassistive mobile robotic system," Mechatronics, vol. 20, pp. 751-766, 2010.
[4] G. Benet, et al., "Using infrared sensors for distance measurement in mobile robots," Robotics and Autonomous Systems, vol. 40, pp. 255-266, Sep 2002.
[5] H. B. Wang, et al., "Self-localization and obstacle avoidance for a mobile robot," Neural Computing & Applications, vol. 18, pp. 495-506, Jun 2009.
[6] I. A. R. Ashokaraj, et al., "Robust Sensor-Based Navigation for Mobile Robots," IEEE Transactions on Instrumentation and Measurement, vol. 58, pp. 551-556, Mar 2009.
[7] J. Borenstein and L. Feng, "UMBmark —A Method for Measuring, Comparing, and Correcting Dead-reckoning Errors in Mobile Robots", The University of Michigan,Technical Report UM-MEAM-94-22, December 1994.
[8] J. Broekens, et al., "Assistive social robots in elderly care: a review," Gerontechnology, vol. 8, pp. 94-103, 2009.
[9] J. Correa and A. Soto, "Active Visual Perception for Mobile Robot Localization," Journal of Intelligent and Robotic Systems, vol. 58, pp. 339-354, 2009.
[10] J. Leonard, H. Durrant-Whyte, Mobile robot localization by tracking geometric beacons, IEEE Transactions on Robotics and Automation 7 (3) (1991)
376–382.
[11] M. Luimula, et al., "Remote navigation of a mobile robot in an RFID-augmented environment," Personal and Ubiquitous Computing, vol. 14, pp. 125-136, Feb 2010.
[12] P. Boissy, et al., "A qualitative study of in-home robotic telepresence for home care of community-living elderly subjects," Journal of Telemedicine and Telecare, vol. 13, pp. 79-84, 2007.
[13] Prince TR, Croghan JE, Sheridan Jr PH, Weatherly JD, "Enhancing efficiency and quality of ambulatory care through telehealth technology, " J Ambul Care Manage 2005,28(3):222–9.
[14] Prinz L, Cramer M, Englund A, "Telehealth: a policy analysis for quality, impact on patient outcomes, and political feasibility.” Nurs Outlook 2008;56(4):152–8.
[15] S. K. Pradhan, et al., "Fuzzy logic techniques for navigation of several mobile robots," Applied Soft Computing, vol. 9, pp. 290-304, Jan 2009.
[16] W. Gueaieb and M. S. Miah, "An intelligent mobile robot navigation technique using RFID technology," IEEE Transactions on Instrumentation and Measurement, vol. 57, pp. 1908-1917, Sep 2008.
[17] Play Robot 飆機器人/普特企業有限公司http://www.playrobot.com/cart/index.php
[18] http://www.jethobby.com.sg/cgi-bin/ezsite/prod/manager.cgi?action=show&pid=1895&cid=111&idx=11&gid=24
[19] http://www.qrcode.com/zh/index.html