Exploring Information Theory for Vision-Based Volumetric Mapping

Rui Rocha, Jorge Dias, Adriano Carvalho

In Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS’2005)
Edmonton, Canada, pages 2409-2414, Aug. 2-6, 2005.

Abstract

This article presents an innovative probabilistic approach for building volumetric maps of unknown environments with autonomous mobile robots, which is based on information theory. Each mobile robot uses an entropy gradient-based exploration strategy, with the aim of maximizing information gain when building and improving a 3-D map upon measurements yielded by an on-board stereo-vision sensor. The proposed framework was validated through experiments with a real mobile robot equipped with stereo-vision, in order to be further used on cooperative volumetric mapping with teams of mobile robots.

Index Terms — 3-D volumetric mapping, entropy, probabilistic maps, mapping and exploration, stereo-vision sensors.

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BibTeX

@INPROCEEDINGS(Rocha_et_al_05b,

AUTHOR = "Rocha, R. and Dias, J. and Carvalho, A.",

TITLE = "Exploring Information Theory for Vision-Based Volumetric Mapping",

BOOKTITLE = "Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS’2005)",

ADDRESS = "Edmonton, Canada",

YEAR = "2005",

MONTH = "Aug.",

PAGES = "2409-2414"

)

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Last update: 14/06/2006