Creating Metric-topological Maps for Large-scale Monocular SLAM

Eduardo Fernández-Moral, Javier Gonzalez-Jimenez, Vicente Arévalo

Abstract

In the last very few years, monocular SLAM approaches based on bundle adjustment are achieving amazing results in terms of accuracy, computational efficiency, and density of the map. When such solutions are applied on large scenarios it is crucial for the system scalability to maintain a map representation that permits efficient map optimization and augmentation. In order to cope with such large maps, we present an on-the-fly partitioning technique which allows abstraction from the metric map to operate more efficiently. The result is a metric-topological arrangement where the areas with highly-connected observations are grouped in submaps weakly interconnected to each other. This is accomplished by progressively cutting a graph representation of the map, where the nodes are keyframes and the arcs between them represent their shared observations. The experimental results indicate that the proposed approach improves the efficiency of monocular SLAM and provides a metric-topological world representation suitable for other robotic tasks.

References

  1. Angeli, A., Doncieux, S., Meyer, J.-A., Filliat, D., 2009. "Visual Topological SLAM and Global Localization", In IEEE International Conference on Robotics and Automation.
  2. Blanco, J. L., Fernández-Madrigal, J. A., González, J., 2008. Toward a unified bayesian approach to hybrid metric-topological SLAM. IEEE Transactions on Robotics and Automation, 24(2):259-270.
  3. Blanco, J. L., González, J., Fernández-Madrigal, J. A., 2006. “Consistent observation grouping for generating metric-topological maps that improves robot localization”. In IEEE International Conference on Robotics and Automation, pp. 818-823.
  4. Blanco, J. L., González-Jiménez, J., Fernández-Madrigal, J. A., 2013. "Sparser Relative Bundle Adjustment (SRBA): constant-time maintenance and local optimization of arbitrarily large maps", In IEEE International Conference on Robotics and Automation.
  5. Davison, A. J, 2003. “Real-time simultaneous localisation and mapping with a single camera,” In Proceedings of the International Conference on Computer Vision.
  6. Eade, E., Drummond, T., 2007. “Monocular slam as a graph of coalesced observations”. In Proceedings of the International Conference on Computer Vision.
  7. Estrada, C., Neira, J., Tardos, J., 2005. “Hierarchical slam: Real-time accurate mapping of large environments”. IEEE Transactions on Robotics, vol. 21, no. 4, p. 588- 596.
  8. Fernández-Moral, E., Mayol-Cuevas, W., Arévalo, V., González-Jiménez, J., 2013. "Fast place recognition with plane-based maps", In Proceedings of the IEEE International Conference on Robotics and Automation.
  9. Galindo, C., Saffiotti, A., Coradeschi, S., Buschka, P., Fernández-Madrigal, J. A., J. González, 2005. “Multihierarchical semantic maps for mobile robotics,” In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2278-2283.
  10. Holmes, S. A., Sibley, G., Klein, G., Murray, D. W., 2009. ”A relative frame representation for fixed-time bundle adjustment in monocular SFM”. In Proceedings IEEE International Conference on Robotics and Automation.
  11. Klein, G., Murray, D. W, 2007. “Parallel tracking and mapping for small AR workspaces”. In Proceedings of the International Symposium on Mixed and Augmented Reality.
  12. Konolige, K., 2010. “Sparse sparse bundle adjustment”. In Proceedings of the British Machine Vision Conference.
  13. Lim, J., Frahm, J. M., Pollefeys, M., 2011. Online environment mapping. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
  14. Newman, P., Leonard, J., Soika, M., Feiten, W., Teller, S., 2003. “An atlas framework for scalable mapping”. In Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2, pp. 1899-1906.
  15. Ni, K., Dellaert, F., 2010. “Multi-level submap based slam using nested dissection”. In IEEE/RSJ International Conference on Intelligent Robots and Systems.
  16. Ni, K., Steedly, D., Dellaert, F., 2007. “Tectonic SAM: Exact, out-of-core, submap-based SLAM,” in IEEE International Conference on Robotics and Automation.
  17. Nistér, D., Naroditsky, O., Bergen, J.R, 2005. “Visual odometry”. In Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pages 652- 659.
  18. Rogers, J. G., Christensen, H. I., 2009. “Normalized graph cuts for visual slam”. In IEEE/RSJ International Conference on Intelligent Robots and Systems.
  19. Savelli, F., Kuipers, B., 2004. “Loop-Closing and Planarity in Topological Map-Building,” In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 1511-1517.
  20. Segvic, S., Remazeilles, A., Diosi, A. and Chaumette, F., 2009. "A mapping and localization framework for scalable appearance-based navigation". Computer Vision and Image Understanding 113(2): 172-187.
  21. Shi, J., Malik, J., 2000. “Normalized cuts and image segmentation”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, p. 888-905.
  22. Sibley, G., Mei, C., Reid, I., Newman, P., 2009. “Adaptive relative bundle adjustment”. In Robotics Science and Systems.
  23. Strasdat, H., Davison, A. J., Montiel, J. M. M., Konolige, K., 2011. “Double Window Optimisation for Constant Time Visual SLAM”. In IEEE International Conference on Computer Vision.
  24. Strasdat, H., Montiel, J. M. M., Davison, A. J., 2010. “Real-time monocular slam: Why filter?”. In IEEE International Conference on Robotics and Automation.
  25. Thrun, S., 1998. “Learning Metric-Topological Maps for Indoor Mobile Robot Navigation,” Artificial Intelligence, v.99, no.1, pp. 21-71.
  26. Zivkovic, Z., Bakker, B., Krose, B., 2005. “Hierarchical map building using visual landmarks and geometric constraints”. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p. 2480-2485.
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Paper Citation


in Harvard Style

Fernández-Moral E., Gonzalez-Jimenez J. and Arévalo V. (2013). Creating Metric-topological Maps for Large-scale Monocular SLAM . In Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8565-71-6, pages 39-47. DOI: 10.5220/0004438900390047


in Bibtex Style

@conference{icinco13,
author={Eduardo Fernández-Moral and Javier Gonzalez-Jimenez and Vicente Arévalo},
title={Creating Metric-topological Maps for Large-scale Monocular SLAM},
booktitle={Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2013},
pages={39-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004438900390047},
isbn={978-989-8565-71-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Creating Metric-topological Maps for Large-scale Monocular SLAM
SN - 978-989-8565-71-6
AU - Fernández-Moral E.
AU - Gonzalez-Jimenez J.
AU - Arévalo V.
PY - 2013
SP - 39
EP - 47
DO - 10.5220/0004438900390047