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:
RG Mapping: Learning Compact and Structured 2D Line Maps of Indoor Environments (D Schröter, M Beetz and J.-S. Gutmann), In 11th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN), Berlin/Germany, 2002.
Bibtex Entry:
@inproceedings{schroter_rg_2002,
author = {D Schröter 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.},
}