OpenRatSLAM: An open source brain-based SLAM system

Ball, David, Heath, Scott, Wiles, Janet, Wyeth, Gordon, Corke, Peter and Milford, Michael (2013) OpenRatSLAM: An open source brain-based SLAM system. Autonomous Robots, 34 3: 149-176. doi:10.1007/s10514-012-9317-9

Author Ball, David
Heath, Scott
Wiles, Janet
Wyeth, Gordon
Corke, Peter
Milford, Michael
Title OpenRatSLAM: An open source brain-based SLAM system
Journal name Autonomous Robots   Check publisher's open access policy
ISSN 0929-5593
Publication date 2013-01-01
Year available 2013
Sub-type Article (original research)
DOI 10.1007/s10514-012-9317-9
Open Access Status
Volume 34
Issue 3
Start page 149
End page 176
Total pages 28
Place of publication New York, NY United States
Publisher Springer New York LLC
Language eng
Subject 1702 Cognitive Sciences
Abstract RatSLAM is a navigation system based on the neural processes underlying navigation in the rodent brain, capable of operating with low resolution monocular image data. Seminal experiments using RatSLAM include mapping an entire suburb with a web camera and a long term robot delivery trial. This paper describes OpenRatSLAM, an open-source version of RatSLAM with bindings to the Robot Operating System framework to leverage advantages such as robot and sensor abstraction, networking, data playback, and visualization. OpenRatSLAM comprises connected ROS nodes to represent RatSLAM's pose cells, experience map, and local view cells, as well as a fourth node that provides visual odometry estimates. The nodes are described with reference to the RatSLAM model and salient details of the ROS implementation such as topics, messages, parameters, class diagrams, sequence diagrams, and parameter tuning strategies. The performance of the system is demonstrated on three publicly available open-source datasets.
Keyword Appearance based
Brain based
Open source
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 13 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 26 times in Scopus Article | Citations
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Created: Fri, 29 Nov 2013, 01:58:31 EST by System User on behalf of School of Information Technol and Elec Engineering