Combining multiple sensor modalities for a localisation robust to smoke

Brunner, Christopher, Peynot, Thierry, & Vidal-Calleja, Teresa (2011) Combining multiple sensor modalities for a localisation robust to smoke. In Proceedings of 2011 IEEE/RSJ International Conference on Robots and Intelligent Systems, IEEE, San Francisco, CA, pp. 2489-2496.

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This paper proposes an approach to obtain a localisation that is robust to smoke by exploiting multiple sensing modalities: visual and infrared (IR) cameras. This localisation is based on a state-of-the-art visual SLAM algorithm. First, we show that a reasonably accurate localisation can be obtained in the presence of smoke by using only an IR camera, a sensor that is hardly affected by smoke, contrary to a visual camera (operating in the visible spectrum). Second, we demonstrate that improved results can be obtained by combining the information from the two sensor modalities (visual and IR cameras). Third, we show that by detecting the impact of smoke on the visual images using a data quality metric, we can anticipate and mitigate the degradation in performance of the localisation by discarding the most affected data. The experimental validation presents multiple trajectories estimated by the various methods considered, all thoroughly compared to an accurate dGPS/INS reference.

Impact and interest:

4 citations in Scopus
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ID Code: 67658
Item Type: Conference Paper
Refereed: Yes
Additional Information: 12318048
sensor modalities
sensing modality
visual camera
infrared camera
visual SLAM algorithm
IR camera
visible spectrum
visual image
data quality metric
Keywords: cameras, infrared imaging, robot vision, sensor fusion, SLAM (robots), reliable perception
DOI: 10.1109/IROS.2011.6094614
ISBN: 9781612844541
ISSN: 2153-0858
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2011 IEEE
Copyright Statement: Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Deposited On: 06 Mar 2014 01:47
Last Modified: 06 Apr 2014 13:23

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