RG Mapping: Learning Compact and Structured 2D Line Maps of Indoor Environments (bibtex)
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.},
}
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RG Mapping: Learning Compact and Structured 2D Line Maps of Indoor Environments (bibtex)
RG Mapping: Learning Compact and Structured 2D Line Maps of Indoor Environments (bibtex)
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.},
}
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