All-environment visual place recognition with SMART

Pepperell, Edward, Corke, Peter, & Milford, Michael (2014) All-environment visual place recognition with SMART. In Proceedings of the International Conference on Robotics and Automation, IEEE, Hong Kong Convention and Exhibition Center, Hong Kong, pp. 1612-1618.

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Abstract

This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.

Impact and interest:

21 citations in Scopus
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ID Code: 72732
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Robot Vision, Place Recognition, Localisation
DOI: 10.1109/ICRA.2014.6907067
ISBN: 978-1-4799-3685-4
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2014 IEEE
Deposited On: 11 Jun 2014 22:36
Last Modified: 12 Sep 2016 15:34

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