Abstract
A hybrid mapping framework is presented in this work. The goal is to obtain better computational efficiency than pure metrical mapping techniques and better accuracy as well as usability for robot guidance and navigation compared to the topological mapping. Image sequences acquired in an environment by manually driving a robot are used to build a hierarchical map representation by using an image sequence partitioning (ISP) technique that uses local image features. The hierarchical map built can be understood as a topological map with nodes corresponding to certain regions in the environment. Each node in turn is made up of a set of images acquired in that region. These maps are further augmented with metrical information at those nodes which correspond to image subsequences acquired while the robot is turning as a part of its trajectory. Metrical information becomes invaluable during autonomous robot navigation through these places. Hence, we call the resulting maps hybrid since they primarily contain topological information and metrical information at places that are important for navigation. Experimental results obtained on a sequence acquired in an outdoor environment are provided to demonstrate our approach.
Keywords
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The IP datasets website is: http://ipds.univ-bpclermont.fr/.
References
Andrew J. Davison and David W. Murray. Simultaneous localization and map-building using active vision. IEEE Trans. Pattern Anal. Mach. Intell., 24(7):865–880, 2002.
A. Angeli, D. Filliat, S. Doncieux, and J.-A. Meyer. A fast and incremental method for loop-closure detection using bags of visual words. IEEE Transactions On Robotics, Special Issue on Visual SLAM, 24(5):1027–1037, October 2008.
S. Bazeille and D. Filliat. Incremental topo-metric SLAM using vision and robot odometry. In Robotics and Automation (ICRA), 2011 IEEE International Conference on, page 4067–4073, may 2011.
Bill Triggs, Philip F. McLauchlan, Richard I. Hartley, and Andrew W. Fitzgibbon. Bundle Adjustment - A Modern Synthesis. In Proceedings of the International Workshop on Vision Algorithms: Theory and Practice, ICCV ’99, page 298–372, London, UK, UK, 2000. Springer-Verlag.
M. Cummins and P. Newman. FAB-MAP: Probabilistic localization and mapping in the space of appearance. The International Journal of Robotics Research, 27(6):647–665, 2008.
David Nister, Oleg Naroditsky, and James Bergen. Visual odometry for ground vehicle applications. Journal of Field Robotics, 23:2006, 2006.
David Nister. An efficient solution to the five-point relative pose problem. IEEE Trans. Pattern Anal. Mach. Intell., 26(6):756–777, 2004.
David G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91–110, November 2004.
A. Diosi, A. Remazeilles, S. Segvic, and François Chaumette. Outdoor visual path following experiments. In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS’07, pages 4265–4270, San Diego, California, France, 2007.
Eric Royer, Maxime Lhuillier, Michel Dhome, and Jean-Marc Lavest. Monocular Vision for Mobile Robot Localization and Autonomous Navigation. Int. J. Comput. Vision, 74(3):237–260, September 2007.
F. Fraundorfer, C. Engels, and D. Níster. Topological mapping, localization and navigation using image collections. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS’07, pages 3872–3877, San Diego, USA, October 2007.
Giorgio Grisetti, Cyrill Stachniss, and Wolfram Burgard. Non-linear constraint network optimization for efficient map learning. IEEE Transactions on Intelligent Transportation Systems, 10, 2009.
Herbert Bay, Andreas Ess, Tinne Tuytelaars, and Luc Van Gool. Speeded-up robust features (surf). Comput. Vis. Image Underst., 110(3):346–359, June 2008.
E. Johns and Guang-Zhong Yang. Global localization in a dense continuous topological map. In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages 1032–1037, 2011.
Jongwoo Lim, Jan-Michael Frahm, and Marc Pollefeys. Online environment mapping using metric-topological maps. I. J. Robotic Res., 31(12):1394–1408, 2012.
Jose-Luis Blanco, Juan-Antonio Fernandez-Madrigal, and Javier Gonzalez. Toward a unified bayesian approach to hybrid metric-topological slam. IEEE Transactions on Robotics, 24(2):259–270, 2008.
Kai Ni and F. Dellaert. Multi-level submap based slam using nested dissection. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pages 2558–2565, 2010.
H. Korrapati, J. Courbon, Y. Mezouar, and P. Martinet. Image Sequence Partitioning for Outdoor Mapping. In IEEE International Conference on Robotics and Automation, ICRA’12, pages 13–18, Pasadena, CA, USA, 2012.
H. Korrapati, F. Uzer, and Y. Mezouar. Hierarchical visual mapping with omnidirectional images. In Intelligent Robots and Systems, 2013. IROS 2013. IEEE/RSJ International Conference on, 2013.
B. Kuipers, J. Modayil, P. Beeson, M. MacMahon, and F. Savelli. Local metrical and global topological maps in the hybrid spatial semantic hierarchy. In in IEEE Int. Conf. on Robotics & Automation (ICRA-04, pages 4845–4851, 2004.
Michael Bosse, Paul Newman, John Leonard, Martin Soika, Wendelin Feiten, and Seth Teller. An atlas framework for scalable mapping. In in IEEE International Conference on Robotics and Automation, pages 1899–1906, 2003.
E. Mouragnon, M. Lhuillier, M. Dhome, F. Dekeyser, and P. Sayd. Generic and real-time structure from motion using local bundle adjustment. Image Vision Comput., 27(8):1178–1193, July 2009.
A.C. Murillo, G. Singh, J. Kosecka, and J.J. Guerrero. Localization in urban environments using a panoramic gist descriptor. Robotics, IEEE Transactions on, 29(1):146–160, Feb 2013.
Nicola Tomatis, Hybrid, Metric-Topological Representation for Localization and Mapping. In MargaretE. Jefferies and Wai-Kiang Yeap, editors, Robotics and Cognitive Approaches to Spatial Mapping, volume 38 of Springer Tracts in Advanced Robotics, pages 43–63, Springer, Berlin Heidelberg, 2008
R. Paul and P. Newman. Fab-map 3d: Topological mapping with spatial and visual appearance. In IEEE International Conference on Robotics and Automation (ICRA), pages 2649–2656, Anchorage, Alaska, USA, May 2010.
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Lost in quantization: Improving particular object retrieval in large scale image databases. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pages 1–8, June 2008.
N. Sunderhauf and P. Protzel. Towards a robust back-end for pose graph slam. In Robotics and Automation (ICRA), 2012 IEEE International Conference on, pages 1254–1261, 2012.
S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series. The MIT Press, 2005.
C. Valgren and A.J. Lilienthal. Incremental spectral clustering and seasons: Appearance-based localization in outdoor environments. In IEEE International Conference on Robotics and Automation (ICRA), pages 1856–1861, May 2008.
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Üzer, F., Korrapati, H., Royer, E., Mezouar, Y., Lee, S. (2016). Vision-Based Hybrid Map Building for Mobile Robot Navigation. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_11
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