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Visual Topological Mapping and Localisation using Colour Histograms

Werner, Felix, Sitte, Joaquin, & Maire, Frederic D. (2008) Visual Topological Mapping and Localisation using Colour Histograms. In International Conference on Control, Automation, Robotics and Vision (ICARCV08), 17 - 20 December 2008, Hanoi, Vietnam.

Abstract

In this paper we present a system for appearance-based topological mapping and localisation using vision data. The algorithms are designed for robots which are equipped with FPGA~cameras. Such cameras do not provide the entire image to the robot but simple image features like colour histograms.

Our mapping approach exploits the continuity of the visual appearance of consecutive images from the robots exploration traversal. For topologically mapping the environment colour histograms are clustered whereby each cluster represents a place.

We use a Monte-Carlo localisation strategy combined with the topological map to localise the robot. For a robot equipped with a panoramic camera the proposed strategy works reasonably well, and is capable of overcoming the challenges of severe perceptual aliasing which occurs because of using simple image features and a sparse environment representation through the topological map.

Impact and interest:

1 citations in Scopus
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2 citations in Web of Science®

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Full-text downloads:

179 since deposited on 20 Aug 2008
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ID Code: 14438
Item Type: Conference Paper
Additional URLs:
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2008 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 20 Aug 2008
Last Modified: 29 Feb 2012 23:49

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