Abstract
In this paper, we propose a robust method for the process of localization of a mobile robotthrough a vision system. The mobile robot is a compact system consisting of an embedded board and a fish-eye camera. The fish-eye camera looks upward to capture ceiling images. The camera provides a sequence of images for the process of detection and tracking ceiling features. These features are used like natural landmarks to detect the state of translation and rotation of the robot. Our method requires less computational power and resources for a robot, and thus can be used at home. The results produced in this study showed the advantages of our method in terms of both speed and accuracy.
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References
Blanc, G., Aït Aïder, O., Mezouar, Y., Chateau, T., Martinet, P.: Indoor Navigation of Mobile Robot: An Image Based Approach. In: ISR 2004. Proceedings of the 35th International Symposium on Robotics, Paris, France, March 23-26, 2004, p. 010 (2004)
Aït Aïder, O., Chateau, T., Lapresté, J.T.: Indoor autonomous navigation using visual memory and pattern tracking. In: British Machine Vision Conference, Kingston, England, September 2004, vol. 2, pp. 657–665 (2004)
Brady, M., Wang, H.: Vision for mobile robots. Phil. Trans. R. Soc. Lond. B 337, 341–350 (1992)
Se, S., Lowe, D.G., Little, J.J.: Vision-Based Global Localization and Mapping for Mobile Robots. IEEE Transaction on Robotics, vol. 21(3) (June 2005)
Se, S., Lowe, D.G., Little, J.J.: Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks. The International Journal of Robotics Research 21(8), 735–758 (2002)
Thrun, S., Bennewitz, M., Burgard, W., Cremers, A.B., Dellaert, F., Hähnel, D.F.D., Rosenbeg, C., Roy, N., Schulte, J., Schulz, D.: MINERVA: A Second – Generation Museum Tour- Guide Robot. In: Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference, May 10-15, 1999, vol. 3, pp. 1999–2005 (1999)
Dellaert, F., Burgard, W., Thrun, S.: Using the CONDENSATION Algorithm for Robust, Vision-based Mobile Robot Localization. In: Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 23-25, 1999, vol. 2, Pages: Digital Object Identifier 10.1109/CVPR.1999.784976 (1999)
Jeong, W.Y., Lee, K.M.: CV-SLAM: A new Ceiling Vision-based SLAM technique. In: IEEE/RSJ International Conference on Intelligent Robots and Systems 2005, pp. 3195–3200 (2005)
Smith, S.M., Brady, J.M.: SUSAN - a new approach to low level image processing. Int. Journal of Computer Vision 23(1), 45–78 (1997)
Harris, C., Stephens, M.: A combined edge and corner detector. Proceedings of the 4th Alvey Vision Conference 1998 15, 147–151 (1998)
Tomasi, C., Kanade, T.: Detection and Tracking of Point Features. Tech Report CMU-CS-91-132 Carnegie-Mellon University, Pittsburgh, PA (1991)
Shi, J., Tomasi, C.: Good Features to Track. In: 9th IEEE Conference on Computer Vision and Pattern Recognition, June 1994, pp. 593–600. IEEE Computer Society Press, Los Alamitos (1994)
Trajkovic, M., Hedley, M.: Fast corner detection. Image and Vision Computing 16(2), 75–87 (1998)
Zitová, B., Flusser, J., Kautsky, J., Peters, G.: Feature point detection in multiframe images. In: Svoboda, T. (ed.) Czech Pattern Recognition Workshop, Peršlák, Czech Republic, February 2-4, 2000, pp. 117–122 (2000)
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Nguyen, V.T., Jeong, M.S., Ahn, S.M., Moon, S.B., Baik, S.W. (2007). A Robust Localization Method for Mobile Robots Based on Ceiling Landmarks. In: Torra, V., Narukawa, Y., Yoshida, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2007. Lecture Notes in Computer Science(), vol 4617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73729-2_40
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DOI: https://doi.org/10.1007/978-3-540-73729-2_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73728-5
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