Swarm based construction of large scale maze-like environments

Raphael Maas; Erik Maehle

doi:10.4108/ICST.ROBOCOMM2009.5831

Swarm based construction of large scale maze-like environments

Raphael Maas, Erik Maehle

Institute of Computer Engineering

Abstract

This paper presents two approaches to pattern based exploration and mapping of large scale, maze-like environments. These approaches fit the needs of single robot as well as multirobot exploration. A further aspect is the subsequent localization of participating robots within previously generated maps. The construction of these maps relies mostly on the extraction and merging of environmental describing patterns. Two different algorithmic solutions are presented within this work. Both solutions were evaluated by either real hardware implementations or exhaustive simulations.

Original language	English
Title of host publication	2009 Second International Conference on Robot Communication and Coordination
Number of pages	6
Publisher	IEEE
Publication date	10.09.2009
Pages	1-6
Article number	4957468
ISBN (Print)	978-963-9799-51-6
DOIs	https://doi.org/10.4108/ICST.ROBOCOMM2009.5831
Publication status	Published - 10.09.2009
Event	2009 2nd International Conference on Robot Communication and Coordination - Odense, Denmark Duration: 31.03.2009 → 02.04.2009 Conference number: 76571

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10.4108/ICST.ROBOCOMM2009.5831

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abstract = "This paper presents two approaches to pattern based exploration and mapping of large scale, maze-like environments. These approaches fit the needs of single robot as well as multirobot exploration. A further aspect is the subsequent localization of participating robots within previously generated maps. The construction of these maps relies mostly on the extraction and merging of environmental describing patterns. Two different algorithmic solutions are presented within this work. Both solutions were evaluated by either real hardware implementations or exhaustive simulations.",

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Swarm based construction of large scale maze-like environments

Abstract

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