by D. Schröter, M. Beetz and J.-S. Gutmann
Abstract:
In this paper we present Region & Gateway (RG) Mapping, a novel approach to laser-based 2D line mapping of indoor environments. RG Mapping is capable of acquiring very compact, structured, and semantically annotated maps. We present and empirically analyze the method based on map acquisition experiments with autonomous mobile robots. The experiments show that RG mapping drastically compresses the data contained in line scan maps without substantial loss of accuracy.
Reference:
D. Schröter, M. Beetz and J.-S. Gutmann, "RG Mapping: Learning Compact and Structured 2D Line Maps of Indoor Environments", In 11th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN), Berlin/Germany, 2002.
Bibtex Entry:
@InProceedings{ SchroeterRoman02RGML,
author = {D. Schr{\"o}ter and M. Beetz and J.-S. Gutmann},
title = {{RG Mapping: Learning Compact and Structured 2D Line Maps of Indoor Environments}},
booktitle = {11th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN), Berlin/Germany},
year = {2002},
abstract = {{In this paper we present
Region \& Gateway (RG) Mapping,
a novel approach to laser-based 2D line mapping of indoor environments.
RG Mapping is capable of acquiring very compact, structured, and
semantically annotated maps. We present and empirically analyze
the method based on map acquisition experiments with autonomous
mobile robots. The experiments show that RG mapping drastically
compresses the data contained in line scan maps without substantial
loss of accuracy.}},
bib2html_pubtype = {Refereed Workshop Paper},
bib2html_rescat = {Robot Mapping},
bib2html_groups = {IAS,EvI},
bib2html_funding = {EvI},
bib2html_keywords = {Environment Mapping},
}