Topological SLAM Using Fast Vision Techniques

Werner, Felix, Maire, Frederic, & Sitte, Joaquin (2009) Topological SLAM Using Fast Vision Techniques. In Advances in Robotics. Springer, Berlin ; New York, pp. 187-196.

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Abstract

In this paper we propose a method for vision only topological simultaneous localisation and mapping (SLAM). Our approach does not use motion or odometric information but a sequence of colour histograms from visited places. In particular, we address the perceptual aliasing problem which occurs using external observations only in topological navigation.

We propose a Bayesian inference method to incrementally build a topological map by inferring spatial relations from the sequence of observations while simultaneously estimating the robot's location. The algorithm aims to build a small map which is consistent with local adjacency information extracted from the sequence measurements. Local adjacency information is incorporated to disambiguate places which otherwise would appear to be the same.

Experiments in an indoor environment show that the proposed technique is capable of dealing with perceptual aliasing using visual observations only and successfully performs topological SLAM.

Impact and interest:

3 citations in Scopus
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6 citations in Web of Science®

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ID Code: 26448
Item Type: Book Chapter
Additional Information: FIRA RoboWorld Congress 2009, Incheon, Korea, August 16-20, 2009, Proceedings
Additional URLs:
Keywords: Robot Navigation, SLAM, Colour Histogram, Neighbourhood Information, Topological Mapping
DOI: 10.1007/978-3-642-03983-6_23
ISBN: 9783642039829
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2009 Springer-Verlag Berlin Heidelberg
Deposited On: 23 Jul 2009 04:43
Last Modified: 07 Nov 2013 01:51

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