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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Carpin, S., Birk, A. (2005). Stochastic Map Merging in Rescue Environments. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds) RoboCup 2004: Robot Soccer World Cup VIII. RoboCup 2004. Lecture Notes in Computer Science(), vol 3276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32256-6_43
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DOI: https://doi.org/10.1007/978-3-540-32256-6_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25046-3
Online ISBN: 978-3-540-32256-6
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