Abstract
This paper describes the design and implementation of a basic architecture for view-based autonomous navigation of a mobile robot platform. Our system is composed by an interface module which communicates a robotic platform with a decisions module. The system tries to follow a original trained path by calculating a rotation angle using a scene comparison. We implemented this comparison by performing a matching between the current view of the robot and a memorized panoramic image. The matching process is carried out by two methods: NCC-based template matching and SURF-based marching. Our results demonstrate an acceptable performance of the autonomous navigation for both methods when no changes in the environment are present, and a superior performance of the SURF-based method even in the presence of new objects which were not present during the training stage.
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References
Matsumoto, Y., Inaba, M., Inoue, H.: Visual navigation using view-sequenced route representation. In: Proceedings of the 1996 IEEE International Conference on Robotics and Automation, vol. 1, pp. 83–88. IEEE (1996)
Gaspar, J., Winters, N., Santos-Victor, J.: Vision-based navigation and environmental representations with an omnidirectional camera. IEEE Trans. Robot. Autom. 16, 890–898 (2000)
Matsumoto, Y., Sakai, K., Inaba, M., Inoue, H.: View-based approach to robot navigation. In: Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS 2000), vol. 3, pp. 1702–1708. IEEE (2000)
Zhang, Y., Cao, J., Lou, L., Su, B.: Appearance-based mobile robot navigation using omnidirectional camera. In: 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 2357–2361. IEEE (2012)
Tabuse, M., Nakai, D.: Mobile robot navigation using surf features. ACS 10, 276–279 (2010)
Murillo, A.C., Guerrero, J.J., Sagues, C.: Surf features for efficient robot localization with omnidirectional images. In: 2007 IEEE International Conference on Robotics and Automation, pp. 3901–3907. IEEE (2007)
Sharma, K., Jeong, K.y., Kim, S.G.: Vision based autonomous vehicle navigation with self-organizing map feature matching technique. In: 2011 11th International Conference on Control, Automation and Systems (ICCAS), pp. 946–949. IEEE (2011)
Wang, H., Mou, W., Ly, M.H., Lau, M.W.S., Seet, G., Wang, D.: Mobile robot ego motion estimation using ransac-based ceiling vision. In: 2012 24th Chinese Control and Decision Conference (CCDC), pp. 1939–1943. IEEE (2012)
Booij, O., Terwijn, B., Zivkovic, Z., Krose, B.: Navigation using an appearance based topological map. In: 2007 IEEE International Conference on Robotics and Automation, pp. 3927–3932. IEEE (2007)
Tabuse, M., Kitaoka, T., Nakai, D.: Outdoor autonomous navigation using surf features. Artif. Life Robot. 16, 356–360 (2011)
Goedeme, T., Tuytelaars, T., Van Gool, L., Vanacker, G., Nuttin, M.: Feature based omnidirectional sparse visual path following. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), pp. 1806–1811 (2005)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91–110 (2004)
Bay, H., Tuytelaars, T., Van Gool, L.: SURF: speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Roland, S., Reza, N.I., Davide, S.: Introduction to autonomous mobile robots. Volume Intelligent robotics and autonomous agents series. MIT Press (2011)
Mitchell, T., Labrosse, F.: Visual homing: a purely appearance-based approach. In: University of Essex, pp. 101–108 (2006)
Dr Robot Inc.: User manual (2013). http://www.drrobot.com/products/item_downloads/x80sv_1.pdf
Dr Robot Inc.: Data sheet (2013). http://www.robotshop.com/media/files/pdf/x80sv-datasheet-x80sv.pdf
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24, 381–395 (1981)
Ross, A.: Procrustes analysis (2005). http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.2686
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Ayala-Raggi, S.E., González, P.d.J., Sánchez-Urrieta, S., Barreto-Flores, A. (2015). A Simple View-Based Software Architecture for an Autonomous Robot Navigation System. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2015. Lecture Notes in Computer Science(), vol 9164. Springer, Cham. https://doi.org/10.1007/978-3-319-20801-5_31
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DOI: https://doi.org/10.1007/978-3-319-20801-5_31
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