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RatSLAM : a hippocampal model for simultaneous localization and mapping

Milford, Michael J., Wyeth, Gordon F., & Prasser, David (2004) RatSLAM : a hippocampal model for simultaneous localization and mapping. In Proceedings of IEEE International Conference on Robotics and Automation, 2004, IEEE, Hilton New Orleans Riverside Hotel, New Orleans, LA.

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Abstract

The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.

Impact and interest:

25 citations in Scopus
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12 citations in Web of Science®

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1,328 since deposited on 29 Sep 2010
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ID Code: 37593
Item Type: Conference Paper
Keywords: SLAM, hippocampus, moblie robot
DOI: 10.1109/ROBOT.2004.1307183
ISBN: 0780382323
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Copyright Owner: Copyright 2004 IEEE
Deposited On: 30 Sep 2010 09:32
Last Modified: 11 Aug 2011 02:55

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