Exploring information theory for vision-based volumetric mapping

Rui Rocha, Jorge Dias, Adriano Carvalho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

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.

Original languageBritish English
Title of host publication2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
PublisherIEEE Computer Society
Pages1023-1028
Number of pages6
ISBN (Print)0780389123, 9780780389120
DOIs
StatePublished - 2005

Publication series

Name2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

Keywords

  • 3-D volumetric mapping
  • Entropy
  • Mapping and exploration
  • Probabilistic maps
  • Stereo-vision sensors

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