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Stochastic Map Merging in Rescue Environments

  • Stefano Carpin
  • Andreas Birk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

We address the problem of merging multiple noisy maps in the rescue environment. The problem is tackled by performing a stochastic search in the space of possible map transformations, i.e. rotations and translations. The proposed technique, which performs a time variant Gaussian random walk, turns out to be a generalization of other search techniques like hill-climbing or simulated annealing. Numerical examples of its performance while merging partial maps built by our rescue robots are provided.

Keywords

Simulated Annealing Motion Planning Acceptance Function Optimal Transformation Dissimilarity Function 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Stefano Carpin
    • 1
  • Andreas Birk
    • 1
  1. 1.School of Engineering and ScienceInternational University of BremenGermany

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