Effect of representation size and visual ambiguity on RatSLAM system performance
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Description
RatSLAM is a vision-based SLAM system based on extended models of the rodent hippocampus. RatSLAM creates environment representations that can be processed by the experience mapping algorithm to produce maps suitable for goal recall. The experience mapping algorithm also allows RatSLAM to map environments many times larger than could be achieved with a one to one correspondence between the map and environment, by reusing the RatSLAM maps to represent multiple sections of the environment. This paper describes experiments investigating the effects of the environment-representation size ratio and visual ambiguity on mapping and goal navigation performance. The experiments demonstrate that system performance is weakly dependent on either parameter in isolation, but strongly dependent on their joint values.
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ID Code: | 32841 | ||||
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Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||||
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Measurements or Duration: | 8 pages | ||||
ISBN: | 978-0-9587583-8-3 | ||||
Pure ID: | 33825451 | ||||
Divisions: | Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering Past > Schools > School of Engineering Systems |
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Copyright Owner: | Copyright 2006 [please consult the authors] | ||||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
Deposited On: | 23 Jun 2010 04:30 | ||||
Last Modified: | 03 Mar 2024 10:55 |
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