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A “Thermodynamic” Approach to Multi-robot Cooperative Localization with Noisy Sensors

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7461)

Abstract

In a previous paper [1], we proposed a new approach to the simultaneous cooperative localization of a very large group of simple robots capable of performing dead-reckoning and sensing the relative position of nearby robots. The idea behind the proposed averaging process is the following: every time two robots meet, they simply average their location estimates. This paper extends the results of [1] by considering noisy relative location measurements and by presenting a novel analysis based on the Well Mixing Movement Pattern assumption. The results of this paper are more precise than what was previously reported. Nevertheless, when considering the limit of a large group of robots, and after a long “stabilization” time, the final results turn out to be identical.

Keywords

  • Localization Error
  • Relative Location
  • Main Diagonal
  • Constant Component
  • Cooperative Localization

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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References

  1. Elor, Y., Bruckstein, A.M.: A Thermodynamic Approach to the Analysis of Multi-robot Cooperative Localization under Independent Errors. In: Dorigo, M., Birattari, M., Di Caro, G.A., Doursat, R., Engelbrecht, A.P., Floreano, D., Gambardella, L.M., Groß, R., Şahin, E., Sayama, H., Stützle, T. (eds.) ANTS 2010. LNCS, vol. 6234, pp. 36–47. Springer, Heidelberg (2010)

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Elor, Y., Bruckstein, A.M. (2012). A “Thermodynamic” Approach to Multi-robot Cooperative Localization with Noisy Sensors. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2012. Lecture Notes in Computer Science, vol 7461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32650-9_18

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  • DOI: https://doi.org/10.1007/978-3-642-32650-9_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32649-3

  • Online ISBN: 978-3-642-32650-9

  • eBook Packages: Computer ScienceComputer Science (R0)