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Flies Open a Door to SLAM

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Applications of Evolutionary Computing (EvoWorkshops 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5484))

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Abstract

The “fly algorithm” is a real-time evolutionary strategy designed for stereovision. Previous work has shown how to process stereo image sequences and use an evolving population of “flies” as a continuously updated representation of the scene for obstacle avoidance in a mobile robot, and the support to collect information about the environment from different sensors. In this paper, we move a step forward and show a way the fly representation may be used by a mobile robot for its own localisation and build a map of its environment (‘Simultaneous Localisation And Mapping’).

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References

  1. Bäck, T., Schwefel, H.P.: An overview of evolutionary algorithms for parameter optimisation, technical report, University of Dortmund (1992)

    Google Scholar 

  2. Boumaza, A., Louchet, J.: Using Real-time evolution in Robotics. In: Boumaza, A., Louchet, J. (eds.) EVOIASP 2001, Artificial Evolution in Image Analysis and Signal Processing, Como, Italy (April 2001)

    Google Scholar 

  3. Collet, P., Lutton, E., Raynal, F., Schoenauer, M.: Individual GP: an Alternative Viewpoint for the Resolution of Complex Problems. In: Banzhaf, W., Daida, J., Eiben, A.E., Garzon, M.H., Honovar, V., Jakiela, M., Smith, R.E. (eds.) Genetic and Evolutionary Computation Conference GECCO 1999. Morgan Kaufmann, San Francisco (1999)

    Google Scholar 

  4. Connolly, C.I., Burns, J.B., Weiss, R.: Path planning using Laplace’s equation. In: Proceedings of the IEEE Conference on Robotics and Automation ICRA 1990, pp. 2102–2106 (May 1990)

    Google Scholar 

  5. Davison, A.J.: Real-time Simultaneous Localisation and Mapping with a Single Camera. In: Proceedings of the Ninth IEEE International Conference on Computer Vision, vol. 2, pp. 1403–1410 (2003)

    Google Scholar 

  6. Dissanayake, M., Newman, P., Clark, S., Durrant-Whyte, H.F., Csorba, M.: A Solution to the Simultaneous Localization and Map Building (SLAM) Problem. IEEE Transactions on Robotics and Automation 17(3), 229–241 (2001)

    Article  Google Scholar 

  7. Fogel, D.B.: Handbook of Evolutionary Computation. IEEE Press, Los Alamitos (1997)

    Book  MATH  Google Scholar 

  8. Haralick, R.M.: Using Perspective Transformations in Scene Analysis. Computer Graphics and Image Processing 13, 191–221 (1980)

    Article  Google Scholar 

  9. Horn, B.H.: Robot Vision. McGraw-Hill, New York (1986)

    Google Scholar 

  10. Louchet, J.: From Hough to Darwin: an Individual Evolutionary Strategy applied to Artificial Vision. In: Fonlupt, C., Hao, J.-K., Lutton, E., Schoenauer, M., Ronald, E. (eds.) AE 1999. LNCS, vol. 1829. Springer, Heidelberg (1999)

    Google Scholar 

  11. Louchet, J.: Using an Individual Evolution Strategy for Stereovision. Genetic Programming and Evolvable Machines 2(2), 101–109 (2001)

    Article  MATH  Google Scholar 

  12. Perez-Garcia, A., Ayala-Ramirez, V., Sanchez-Yanez, R.E., Avina-Cervantes, J.G.: Monte carlo evaluation of the hausdorff distance for shape matching. In: Martínez-Trinidad, J.F., Carrasco Ochoa, J.A., Kittler, J. (eds.) CIARP 2006. LNCS, vol. 4225, pp. 686–695. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Louchet, J., Sapin, E. (2009). Flies Open a Door to SLAM. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_43

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  • DOI: https://doi.org/10.1007/978-3-642-01129-0_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01128-3

  • Online ISBN: 978-3-642-01129-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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