Morphological Neural Networks and Vision Based Mobile Robot Navigation

  • I. Villaverde
  • M. Graña
  • A. d’Anjou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4131)


Morphological Associative Memories (MAM) have been proposed for image denoising and pattern recognition. We have shown that they can be applied to other domains, like image retrieval and hyperspectral image unsupervised segmentation. In both cases the key idea is that Morphological Autoassociative Memories (MAAM) selective sensitivity to erosive and dilative noise can be applied to detect the morphological independence between patterns. The convex coordinates obtained by linear unmixing based on the sets of morphological independent patterns define a feature extraction process. These features may be useful either for pattern classification. We present some results on the task of visual landmark recognition for a mobile robot self-localization task.


Mobile Robot Convex Region Bidirectional Associative Memory Pattern Vector Landmark Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Balkenius, C., Kopp, L.: Robust Self-Localization Using Elastic Templates. In: Lindberg, T. (ed.) Proceedings of Swedish Symposium on Image Analysis (1997)Google Scholar
  2. 2.
    Chatila, R.: Deliberation and Reactivity in Autonomous Mobile Robots. Robotics and Autonomous Systems 16, 197–211 (1995)CrossRefGoogle Scholar
  3. 3.
    DeSouza, G.N., Kak, A.C.: Vision for Mobile Robot Navigation: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(2), 237–267 (2002)CrossRefGoogle Scholar
  4. 4.
    Fox, D.: Markov Localization: A Probabilistic Framework for Mobile Robot Localization and Navigdation, Ph. D. Thesis, University of Bonn, Germany (December 1998)Google Scholar
  5. 5.
    Fukunaga, K.: Introduction to statistical pattern recognition. Academic Press, Boston (1990)MATHGoogle Scholar
  6. 6.
    Graña, M., Gallego, J.: Associative Mophological Memories for endmember induction. In: Proc. IGARSS 2003, Tolouse, FranceGoogle Scholar
  7. 7.
    Graña, M., Sussner, P., Ritter, G.: Associative Morphological Memories for Endmember Determination in Spectral Unmixing. In: Proc. FUZZ-IEEE (2003)Google Scholar
  8. 8.
    Graña, M., d’Anjou, A.: Feature Extraction by Linear Spectral Unmixing. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds.) KES 2004. LNCS (LNAI), vol. 3213, pp. 692–697. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Graña, M., d’Anjou, A., Albizuri, X.: Morphological memories for feature extraction in hyperspectral images. In: Verleysen, M. (ed.) ESANN 2005, pp. 497–502. dFacto press (2005)Google Scholar
  10. 10.
    Gross, H.M., Koening, A., Boehme, H.J., Schroeter, C.: Vision-based Monte Carlo Self-localization for a Mobile Service Robot Acting as Shopping Assistant in a Home Store. In: Proceedings of the IEEE Intl. Conference on Intelligent Robots and Systems (2002)Google Scholar
  11. 11.
    Hopfield, J.J.: Neural networks and physical systems with emergent collective computational abilities. Proc. Nat. Acad. Sciences 79, 2554–2558 (1982)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Keshava, N., Mustard, J.F.: Spectral unimixing. IEEE Signal Proc. Mag. 19(1), 44–57 (2002)CrossRefGoogle Scholar
  13. 13.
    Livatino, S., Madsen, C.: Optimization of Robot Self-Localization Accuracy by Automatic Visual-Landmark Selection. In: Proceedings of 11th Scabdinavian Conference on Image Analysis (SCIA), pp. 501–506 (1999)Google Scholar
  14. 14.
    Livatino, S., Madsen, C.: Autonomous Robot Navigation with Automatic Learning of Visual Landmarks. In: International Symposium of Intelligent Robotic Systems, SIRSÕ 1999 (1999)Google Scholar
  15. 15.
    Manolakis, D., Shaw, G.: Detection algorithms for hyperspectral imaging applications. IEEE Signal Proc. Mag. 19(1), 29–43 (2002)CrossRefGoogle Scholar
  16. 16.
    Marando, F., Piaggio, M., Scalzo, A.: Real Time Self Localization Using a Single Frontal Camera. In: International Symposium of Intelligent Robotic Systems, SIRSÕ 2001 (2001)Google Scholar
  17. 17.
    Ohya, A., Kosaka, A., Kak, A.C.: Vision-Based Navigation by a Mobile Robot with Obstacle Avoidance Using Single-Camera Vision and Ultrasonic Sensing. IEEE Journal of Robotics and Automation 14(6), 969–978 (1998)CrossRefGoogle Scholar
  18. 18.
    Olson, C.F.: Landmark Selection for Terrain Matching. In: Proceedings ICRA 2000 (2000)Google Scholar
  19. 19.
    Raducanu, B., Graa, M., Sussner, P.: Morphological Neural Networks for vision based self-localization. In: Proc. ICRA 2001Google Scholar
  20. 20.
    Raducanu, B., Graa, M., Sussner, P.: Steps towards one-shot vision-based self-localization. In: Duro, R., Santos, J., Graa, M. (eds.) Biologically inspired robot behavior engineering, pp. 265–294. Springer, Heidelberg (2002)Google Scholar
  21. 21.
    Raducanu, B., Graña, M., Albizuri, X.: Morphological scale spaces and associative morphological memories: results on robustness and practical applications. J. Math. Imaging and Vision 19(2), 113–122 (2003)MATHCrossRefMathSciNetGoogle Scholar
  22. 22.
    Reuter, J.: Mobile Robot Self-Localization Using PDAB. In: Proceedings of International Conference on Robotics and Automation, ICRA (2000)Google Scholar
  23. 23.
    Ritter, G.X., Diaz-de-Leon, J.L., Sussner, P.: Morphological bidirectional associative memories. Neural Networks 12, 851–867 (1999)CrossRefGoogle Scholar
  24. 24.
    Ritter, G.X., Sussner, P., Diaz-de-Leon, J.L.: Morphological associative memories. IEEE Trans. on Neural Networks 9(2), 281–292 (1998)CrossRefGoogle Scholar
  25. 25.
    Ritter, G.X., Urcid, G., Iancu, L.: Reconstruction of patterns from moisy inputs using morphological associative memories. J. Math. Imaging and Vision 19(2), 95–112 (2003)MATHCrossRefMathSciNetGoogle Scholar
  26. 26.
    Ritter, G.X., Urcid, G.: Lattice algebra approach to single-neuron computation. IEEE Trans Neural Networks 14(2), 282–295 (2003)CrossRefMathSciNetGoogle Scholar
  27. 27.
    Rizzi, A., Duina, D., Inelli, S., Cassinis, R.: Unsupervised Matching of Visual Landmarks for Robotic Homing using Fourier-Mellin Transform. Robotics and Autonomous Systems 40, 131–138 (2002)CrossRefGoogle Scholar
  28. 28.
    Saffiotti, A., Wesley, L.P.: Perception-Based Self-Localization Using Fuzzy Location. In: Dorst, L., Voorbraak, F., van Lambalgen, M. (eds.) RUR 1995. LNCS, vol. 1093, pp. 368–385. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  29. 29.
    Sekimori, D., Usui, T., Masutani, Y., Miyazaki, F.: High-Speed Obstacle Avoidance and Self-Localization for Mobile Robots Based on Omni-Directional Imaging of Floor Region. IPSJ Transactions on Computer Vision and Image Media, 42 NoSIG13-012 (2002)Google Scholar
  30. 30.
    Sussner, P.: Observations on Morphological Associative Memories and the Kernel Method. In: Proc. IJCNN 2001, Washington DC (July 2001)Google Scholar
  31. 31.
    Sussner, P.: Generalizing operations of binary autoassociative morphological memories using fuzzy set theory. J. Math. Imaging and Vision 19(2), 81–94 (2003)MATHCrossRefMathSciNetGoogle Scholar
  32. 32.
    Villaverde, I., Ibañez, S., Albizuri, F.X., Graña, M.: Morphological neural networks for real-time vision based self-localization. In: Abrham, A., Dote, Y., Furuhashi, T., Köpen, M., Ohuchi, A., Ohsawa, Y. (eds.) Soft Computing as transdisciplinary Science and Techonology, Proc. WSTST 2005. Advances in Soft Computing, pp. 70–79. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  33. 33.
    Villaverde, I., Graña, M., D’Anjou, A.: Morphological Neural Networks for Localization and Mapping. In: Proceedings of the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA 2006), La Coruña (Spain), July 12-14 (2006) (On Print)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • I. Villaverde
    • 1
  • M. Graña
    • 1
  • A. d’Anjou
    • 1
  1. 1.Dept. CCIAUPV/EHUSan SebastianSpain

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