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System Design and Implementation of a Home-Service Robot
|關鍵字:||home-service;居家服務;omni-directional robot;全方位機器人||出版社:||電機工程學系所||引用:||M. Pollack, S. Engberg, J.T. Matthews, S. Thrun, L. Brown, D. Colbry, C. Orosz, B. Peintner, S. Ramakrishnan, J. Dunbar-Jacob, C. McCarthy, M. Montemerlo, J. Pineau and N. Roy, “Pearl: A Mobile Robotic Assistant for the Elderly,” Workshop on Automation as Caregiver :the Role of Intelligent Technology in Elderly Care (AAAI), August,2002. B.Graf , M. Hans and R. Schraft “Care-O-bot II—Development of a Next Generation Robotic Home Assistant,” Autonomous Robots, vol. 16, pp.193-205, 2004. H. Kobayashi, M. Yanagida, “Moving Object Detection by an Autonomous Guard Robot,” Proceedings of the 4th IEEE International Workshop on Robot and Human Communication, Tokyo, Japan, pp.323-326, 1995. Y. Shimosasa, J. Kanemoto, K. Hakamada, H. Horii, T. Ariki, Y. Sugawara, F. Kojio, A. Kimura, S. 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Barat, “Matching Segments in Stereoscopic Vision,” IEEE Instrumentation & Measurement Magazine, vol. 4, no. 1, pp. 37-42, March 2001. H. Issa, Y. Ruichek and J. G. Postaire, “Extracting Depth Information from Stereo Linear Images Using a Genetic Approach,” Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium, vol. 1, pp.185-189, Sept, 10-12.2002. Y. Ogawa, K. Ishimura and M. Wada, “Stereo Vision Using Pulse-Coupled Neural Network,” SICE 2002. Proceedings of the 41st SICE Annual Conference, vol. 2, pp 719-724, Aug 5-7. 2002. P. Khosla and R. Volpe. “Superquadric Artificial Potentials for Obstacle Avoidance and Approach,” in Proc. of IEEE Intl. Conf. on Robotics and Automation, Vol. 3, Philadelphia, PA, USA, pp.1778-1784, April 1988. J. H. Chuang and N. Ahuja, “An Analytically Tractable Potential Field Model of Free Space and Its Application in Obstacle Avoidance,” IEEE Transactions on systems, Man, and Cybernetics-Part B : Cybernetics, vol. 28, no. 5, pp.729-736, October 1998. W. Tang, L. Lam, and J. Wang, “Kinematic Control and Obstacle Avoidance for Redundant Manipulators using a Recurrent Neural Network,” in Proc. Int. Conf. Artificial Neural Networks, pp. 922-929, 2001. S. X. Yang and M. Meng, “An Efficient Neural Network Approach to Dynamic Robot Motion Planning,” Nerual Nerworks, vol. 13, pp. 143-148, 2000. K. Sugihara and J. Smith, “Genetic Algorithms for Adaptive Motion Planning of an Autonomous Mobile Robot,” in Proceedings of IEEE Intl. Symposium on Computational Intelligence in Robotics and Automation, pp. 138-143, 1997.. C. L. Lin, Optimal Path Planning for Dynamic Platforms, M.S. Thesis, Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, June 2004. J. G. Kang and J. M. Lee, “A Study on Optimal Configuration for the Mobile Manipulator Considering the Minimal Movement,” Proceedings of IEEE International Symposium on Industrial Electronics, vol.2, pp.546-551, Dec. 2000. L. B. Jiang, Point-to-Point Optimal Configuration Planning and Control of an Omnidirectional Mobile Manipulator, M.S. Thesis, Department of Electrical Engineering, National Chung-Hsing University, Taichung, Taiwan, July 2005. D. S. Wang, System Design, Trajectory planning and Control of an Omni-directional Mobile Robot, M.S. Thesis, Department of Electrical Engineering, National Chung-Hsing University, Taichung, Taiwan, July 2006. http://savannah.nongnu.org http://www.roboken.esys.tsukuba.ac.jp||摘要:||
本論文的目的在針對ㄧ機器手臂結合全方位運動平台的居家服務機器人，研製該機器人之全方位自我定位、安全巡航及運動規劃方法學及其可程式化系統晶片實現技術。自我定位演算法是結合全方位影像系統擷取之資訊與三角定位方法來進行位置及角度估測。全域路徑規劃配合區域路徑規劃完成機器人在居家環境之安全巡航；全域路徑由一新編碼格式之基因演算法來規劃靜態環境之路徑最佳解，而藉由雷射掃瞄器做偵測結合所提出之權重選擇方法提供機器人即時避障之區域路徑來達到安全巡航之目的。在居家服務機器人火源撲滅之功能方面，火源之3-D位置座標由雙視覺系統運算得到，再應用精英式基因演算法負責搜尋移動機械手臂之點對點最佳姿態，用以控制整體機器人，完成撲滅火源任務。本論文實驗中之全方位影像、雙視覺影像處理及雷射掃瞄環境估測等處理法則是以小型個人電腦式準系統完成所需的計算，機器手臂之運動控制及行動平台控制分別由Straix II 和Stratix 版本之Nios 發展板進行運算。模擬結果及實驗數據驗證本論文所提出之方法的有效性。
This thesis presents methodologies and techniques for self-localization, safe patrolling, motion planning and system-on-programmable-chip (SOPC) implementation of a home-service robot with a manipulator equipped on the omni-directional mobile platform. A self-localization algorithm based on the triangular approach is proposed using the omni-directional vision system. Safe patrolling in house environment is achieved by two kinds of path planning, including global path planning and local path planning. The global optimal path is determined using a novel encoded genetic algorithm which provides the home-service robot with a static obstacle-free path. With the global optimal path, a weight decision method based on the laser measurement system is presented to steer the robot follow the local path with obstacle avoidance. Being a home-service robot, it is designed to have two functions, object fetch-and-carry, and fire extinguishment. The 3-D position of the fire is estimated by binocular webcams, and a proposed elite genetic algorithm is developed to find the optimal configuration of the mobile manipulator moving from one point to another when executing the fire extinguishment. A small-scale personal computer is employed to deal with environment estimation from the laser scanner, and image processing from the omni-directional vision system and the binocular vision system. Both kinematic control of the manipulator and the omni-directional mobile platform are respectively performed by a Stratix II Nios development board, and a Stratix Nios development board. Numerous simulations and experimental results are conducted to verify the effectiveness and merits of the proposed methods.
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