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Vision-based Biped Robot Localization and Target Seeking
|關鍵字:||Biped Robot;雙足機器人;Localization;Target Seeking;定位;尋標||出版社:||電機工程學系所||引用:|| S. Makrogiannis, Ch. Theoharatos, G. Economau, S. Fotopoulos, “Color image segmentation using multiscale fuzzy C-means and graph theoretic merging,” in Proceedings 2003 International Conference on Image Processing, vol. 1, pp. 14-17, Sep. 2003.  H. D. Cheng, X. H. Jiang, Y. Sun, and J. Wang, “Color Image Segmentation: Advances and Prospects,” International Journal on Pattern Recognition, vol. 34, no. 12, pp. 2259-2281, Sep. 2000.  R.C. Gonzalez and R.E. Wooks, “Digital image processing,” 2002.  H.D. Cheng and Y. Sun, “A hierarchical approach to color image segmentation using homogeneity,” IEEE Transactions on Image Processing, vol. 9, pp. 2071-2082, Dec. 2000.  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, Jan. 1999.  S. Thrun, D. Fox and W. Burgard, “A probabilistic approach to concurrent mapping and localization for mobile robots,” in Machine Learning and Autonomous Robots, vol. 31, pp. 29-53, 1998.  http://www.skilligent.com/products/computer-vision.shtml  J. F. Li, K. Q. Wang, and Z. D., “A new equation of saturation in RGB-to-HSI conversion for more rapidity of computing,” in Proceedings of the International Conference on Machine Learning and Cybernetics, pp. 1493-1497, 2002.  T. Kawanishi, T. Kurozumi, K. Kashino, S. Takagi, “A fast template matching algorithm with adaptive skipping using inner-subtemplate's distance,” in Proceedings of the IEEE Internation Conference on Pattern Recognition, pp. 654-657, 2004.  T. Kawanishi, T. Kurozumi, K. Kashino, S. Takagi, “Dynamic active search for quick object detection with pan-tilt-zoom camera,” in Proceedings of the IEEE International Conference on Image Processing, pp. 716-719, 2001.||摘要:||
In the early stages of industry, sequential control is used to be the main application of automation robotics; however, the current trend of advanced applications in this field is intelligent control. This thesis aims to develop vision-based human biped robot control capable of navigating a robot to reach target accurately by taking advantage of the proposed vision-based object recognition and robot localization algorithm. The proposed method can recognize the target object from an image captured by camera and calculate the right angle and distance for robot navigation. The proposed method includes two phases: First, the non-uniform HSV-based region segmentation method is used to match the target object. Second, a simple RGB-based method is utilized to determine the angle and the distance between the target object and the robot for localization. Through the vision-based object recognition and localization method, we can control the biped robot to reach the target successfully. The proposed technique can be further applied to other fields such as target tracking, obstacle avoidance and dangerous object detection/removal.
|Appears in Collections:||電機工程學系所|
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