Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/9160
標題: 全方位移動雙手臂機器人之全域定位與地圖建立
Global Localization and Mapping of a Two-Armed Robot with Omnidirectional Mecanum Wheels
作者: 王育晟
Wang, Yu-Cheng
關鍵字: 擴張型卡爾曼濾波
Extended Kalman filtering (EKF)
全域定位
地圖建立
體感控制器
Global localization
Mapping
KINECT
出版社: 電機工程學系所
引用: [1] T. Fukao, H. Nakagawa, and N. Adachi, “Adaptive tracking control of a nonholonomic mobile robot,” IEEE Trans. Robot. Autom., vol. 16, no. 5, pp. 609–615, 2000. [2] D. Maksarov and H. Durrant-Whyte, “Mobile vehicle navigation in unknown environments: A multiple hypothesis approach,” Proc. Inst. Electr. Eng.—Control Application Theory, vol. 142, no. 4, pp. 385–400, 1995. [3] B. Triggs, “Model-based sonar localisation for mobile robots,” Robot., Auton. Syst., vol. 12, no. 3/4, pp. 173–186, 1994. [4] S. Thrun , M. Bennewitz, W. Burgard, A. B. Cremers, F. Dellaert, D. Fox, D. Hahnel, C. Rosenberg, N. Roy, J. Schulte, D. Schulte, “MINERVA: A second-generation museum tour-guide robot,” IEEE International Conference on Robotics and Automation, pp. 1999-2005,1999. [5] B. Graf, M. Hans, and R. D. Schraft, “Mobile robot assistants,” IEEE Robotics and Automation Magzine, vol. 11, no.2, pp.67-77, 2004. [6] B. Jensen, G. Froidevaux, X. Greppin, A. Lorotte, L. Mayor, M. Meisser, G. Ramel, R. Siegwart, “The Interactive Autonomous Mobile System Robox,” IEEE/RSJ International Conference on Intelligent Robots and System, pp. 1221-1227, 2002. [7] G. Kim, W. Chung, K.R. Kim, M. Kim, S. Han, R. H. Shinn, “The autonomous tour-guide robot Jinny,” IEEE/RSJ International Conference on Intelligent Robots and System, pp. 3450-3455, 2004. [8] P. S. Maybeck, Stochastic Models, Estimation, and Control, vol.1, New York, Academic Press, 1979. [9] F. Dellaert, D. Fox, W. Burgard, and S. Thrun, “Monte Carlo Localization for Mobile Robots,” in Proc. IEEE Int. Conf. Robotics and Automation, vol. 2, pp. 1322 –1328, 1999. [10] E. Kiriy and M. Buehler, “Three-State Extended Kalman Filter for Mobile Robot Localization,” Tech. Rep., McGill University, Montreal, Canada, 2002. [11] C. C. Tsai, H. S. Lin, and J. C. Hsu, “Ultrasonic Localization and Pose Tracking of an Autonomous Mobile Robot via Fuzzy Adaptive Extended Information Filtering,” IEEE Trans. Instrum. Meas., vol. 57, no. 9, 2008 [12] R. Siegwart and I. R. Nourbakhsh, Introduction to Autonomous Mobile Robots. The MIT Press. [13] N. Ganganath and H. Leung, “Mobile Robot Localization Using Odometry and Kinect Sensor.” IEEE Int. Conf. ESPA, pp. 91 –94, 2012 [14] PrimeSense Ltd., Palo Alto, CA 94301, USA, The Prime-Sensor Reference Design, 1.08 edition, 2010. [15] N. Karlsson, E. Di Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M.E. Munich, “The vSLAM Algorithm for Robust Localization and Mapping, ” IEEE International Conference on Robotics and Automation, 2005. [16] A.J. Davison, I.D. Reid, N.D. Molton, and O. Stasse, “MonoSLAM Real Time Single Camera SLAM, ” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, no.6, pp.1052-1067, 2007. [17] F. Tungadi, L. Kleeman, “Discovering and restoring changes in object positions using an autonomous robot with laser rangefinders,” Robotics and Autonomous Systems, Vol. 59, No.2 pp. 428-443, 2011. [18] M. Paz Lina, P. Pedro, D.T. Juan, and N. Jos′e, “Large-Scale 6-DOF SLAM With Stereo-in-Hand,” IEEE TRANSACTIONS ON ROBOTICS, VOL. 24, NO. 5, 2008. [19] K.S. Chong and L. Kleeman, “Feature-based mapping in real, large scale environments using an ultrasonic array,” International Journal of Robotics Research, Vol. 18, No. 2, pp. 3-19, 1999 [20] D.G. Lowe, “Object recognition from local scale-invariant features,” Proceedings of International Conference on Computer Vision, pp.1150-1157, 1999. [21] Bay, H., A. Ess, T. Tuytelaars, L. Van Gool, “SURF: speeded up robust features,” Computer Vision and Image Understanding, vol.110, pp.346-359, 2008. [22] H. Durrant-Whyte, and T. Bailey, “Simultaneous Localization and Mapping: Part 1,” IEEE Robotics and Automation Magazine, 2006. [23] H. Durrant-Whyte, and T. Bailey, “Simultaneous Localization and Mapping: Part 2,” IEEE Robotics and Automation Magazine, 2006. [24] Y. R. Lee, System Design, Intelligent Adaptive Motion Control for Mecanum Wheeled Omnidirectional Robots, Master thesis, Department of Electrical Engineering, National Chung-Hsing University, 2011. [25] T. T. Liang, System Design, Autonomous Task Execution of a Two-Armed Robot with Stereo Vision Camera, Master thesis, Department of Electrical Engineering, National Chung-Hsing University, 2011.
摘要: 本篇論文主旨在發展配備KINECT感測器與麥卡輪全方位移動平台的雙手臂人形機器人之全域定位及地圖建立技術。首先,本文採用擴張型卡爾曼濾波方法,利用數個已知位置的人工地標融合四輪全方位移動平台上的編碼器來進行全域定位。其次,採用加速強健特徵演算法偵測及匹配部份位置未知的自然影像地標,再結合擴張型卡爾曼濾波器,進行移動式雙手臂人形機器人之全域定位及地圖建立。為了執行相關的實驗,本文建立一個以KINECT視覺感測器、以SoPC實現的四輪麥卡輪全方位移動平台及具備雙手臂之類人形行動機器人系統。利用此系統進行相關的模擬和實驗,其結果驗證了本文所提出的兩個方法的精度及性能。最後,希望本文所發展的技術對智慧機器人領域的研究有所貢獻。
This thesis presents techniques for global localization and mapping of a mobile anthropomorphous two-armed robot (ATAR) with the KINECT sensor and Mecanum four-wheeled omnidirectional base. An EKF-based global localization of the mobile ATAR is presented by using several artificial landmarks with given positions and four encoders mounted on four-wheeled omnidirectional base. An EKF-based approach using SURF is proposed for global localization and mapping of the mobile ATAR based on partially unknown natural landmarks. To conduct required experimentation, this thesis constructs an experimental, mobile, anthropomorphous two-armed robotic system with two anthropomorphous dual arms, a SoPC-based controlled Mecanum four-wheeled omnidirectional base and a KINECT sensor. Several simulations and experimental results are conducted to show the accuracy and performance of both proposed methods. The proposed techniques might be of interests to professionals working in the field of intelligent robots.
URI: http://hdl.handle.net/11455/9160
其他識別: U0005-2208201219052900
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2208201219052900
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