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Parallel and Distributed Map Merging and LocalizationReal Experiments

Parallel and Distributed Map Merging and Localization: Real Experiments [We show some experiments of the methods studied in this book with real data under different communication schemes. We have carried out experiments using a data set from Frese and Kurlbaum, a data set for data association, 2008, [1] with bearing-only information extracted from conventional images. Additionally, we have analyzed the performance of the data association method and the localization and map merging algorithms under real data acquired with an RGB-D sensor, which provides both visual and depth information.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Parallel and Distributed Map Merging and LocalizationReal Experiments

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Publisher
Springer International Publishing
Copyright
© The Author(s) 2015
ISBN
978-3-319-25884-3
Pages
89 –105
DOI
10.1007/978-3-319-25886-7_5
Publisher site
See Chapter on Publisher Site

Abstract

[We show some experiments of the methods studied in this book with real data under different communication schemes. We have carried out experiments using a data set from Frese and Kurlbaum, a data set for data association, 2008, [1] with bearing-only information extracted from conventional images. Additionally, we have analyzed the performance of the data association method and the localization and map merging algorithms under real data acquired with an RGB-D sensor, which provides both visual and depth information.]

Published: Oct 30, 2015

Keywords: RGB-D data; Visual data; Distributed and parallel algorithms; Localization; Data association; Map merging

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