Towards bio-inspired place recognition over multiple spatial scales
Chen, Zetao, Jacobson, Adam, Erdem, Uğur, Hasselmo, Michael E., & Milford, Michael (2013) Towards bio-inspired place recognition over multiple spatial scales. In Katupitiya, Jayantha, Guivant, Jose, & Eaton, Ray (Eds.) Proceedings of the 2013 Australasian Conference on Robotics & Automation, Australian Robotics & Automation Association, University of New South Wales, Sydney, NSW, pp. 1-9.
This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.
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|Item Type:||Conference Paper|
|Keywords:||Robotics, Multi-scale place recognition system, Rodent brain, Multi-scale spatial maps, Support Vector Machines, Place recognition hypotheses, Localization accuracy, Robotic mapping|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2013 [please consult the authors]|
|Deposited On:||28 Jan 2014 02:06|
|Last Modified:||09 Sep 2016 05:20|
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